DRAFT - DO NOT CITE OR QUOTE EPA/63 5/R-09/003
www.epa.gov/iris
vvEPA
Toxicological Review
Of
Trichloroacetic Acid
(CAS No. 76-03-9)
In Support of Summary Information on the
Integrated Risk Information System (IRIS)
May 2009
NOTICE
This document is an Interagency Review draft. This information is distributed solely for the
purpose of pre-dissemination peer review under applicable information quality guidelines. It has
not been formally disseminated by EPA. It does not represent and should not be construed to
represent any Agency determination or policy. It is being circulated for review of its technical
accuracy and science policy implications.
U.S. Environmental Protection Agency
Washington, DC
-------
DISCLAIMER
This document is a preliminary draft for review purposes only. This information is
distributed solely for the purpose of pre-dissemination peer review under applicable information
quality guidelines. It has not been formally disseminated by EPA. It does not represent and
should not be construed to represent any Agency determination or policy. Mention of trade
names or commercial products does not constitute endorsement or recommendation for use.
DRAFT - DO NOT CITE OR QUOTE
-------
CONTENTS —TOXICOLOGICAL REVIEW OF
TRICHLOROACETIC ACID (CAS No. 76-03-9)
LIST OF TABLES vi
LIST OF FIGURES viii
ABBREVIATIONS AND ACRONYMS ix
FOREWORD xii
AUTHORS, CONTRIBUTORS, AND REVIEWERS xiii
1. INTRODUCTION 1
2. CHEMICAL AND PHYSICAL INFORMATION 3
3. TOXICOKINETICS 5
3.1. ABSORPTION 5
3.2. DISTRIBUTION 7
3.3. METABOLISM 11
3.4. EXCRETION 17
3.5. PHYSIOLOGICALLY BASED AND OTHER TOXICOKINETIC MODELS 19
4. HAZARD IDENTIFICATION 20
4.1. STUDIES IN HUMANS 20
4.1.1. ORAL EXPOSURE 20
4.1.2. DERMAL EXPOSURE 20
4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN
ANIMALS—ORAL AND INHALATION 22
4.2.1. SUBCHRONIC STUDIES 22
4.2.1.1. SUBCHRONIC ORAL STUDIES 22
4.2.1.2. SUBCHRONIC INHALATION STUDIES 38
4.2.2. CHRONIC STUDIES AND CANCER AS SAYS 38
4.2.2.1. ORAL STUDIES 38
4.2.2.2. INHALATION STUDIES 55
4.2.2.3. STUDIES USING OTHER ROUTES OF EXPOSURE 55
4.3. REPRODUCTIVE AND DEVELOPMENTAL STUDIES 57
4.3.1. REPRODUCTIVE STUDIES 57
4.3.2. DEVELOPMENTAL STUDIES 57
4.3.2.1. ORAL DEVELOPMENTAL STUDIES 57
4.3.2.2. INHALATION DEVELOPMENTAL STUDIES 66
4.3.2.3. IN VITRO STUDIES 66
4.4. OTHER ENDPOINT-SPECIFIC STUDIES 67
4.4.1. IMMUNOLOGICAL STUDIES 67
4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE OF
ACTION 68
4.5.1. MECHANISTIC STUDIES 68
4.5.1.1. ONCOGENE ACTIVATION 68
4.5.1.2. CELL PROLIFERATION 70
4.5.1.3. DNAHYPOMETHYLATION 72
4.5.1.4. INHIBITION OF INTERCELLULAR COMMUNICATION 77
4.5.1.5. OXIDATIVE STRESS 78
iii DRAFT - DO NOT CITE OR QUOTE
-------
4.5.1.6. HISTOCHEMICAL CHARACTERISTICS OF TCA-INDUCED
TUMORS 79
4.5.2. GENOTOXICITY STUDIES 81
4.5.2.1. IN VITRO STUDIES 81
4.5.2.2. IN VIVO STUDIES 85
4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS 87
4.6.1. ORAL 87
4.6.1.1. METABOLIC ALTERATIONS 87
4.6.1.2. LIVER TOXICITY 88
4.6.1.3. DEVELOPMENTAL TOXICITY 89
4.6.2. INHALATION 90
4.6.3. MODE OF ACTION INFORMATION 90
4.6.3.1. METABOLIC ALTERATIONS 90
4.6.3.2. LIVER TOXICITY 91
4.6.3.3. DEVELOPMENTAL TOXICITY 92
4.7. EVALUATION OF CARCINOGENICITY 92
4.7.1. SUMMARY OF OVERALL WEIGHT OF EVIDENCE 92
4.7.2. SYNTHESIS OF HUMAN, ANIMAL, AND OTHER SUPPORTING
EVIDENCE 92
4.7.3. MODE-OF-ACTION INFORMATION 93
4.7.3.1. HYPOTHESIZED MODE OF ACTION 96
4.7.3.2. CONCLUSIONS ABOUT THE HYPOTHESIZED MODE OF
ACTION 116
4.8. SUSCEPTIBLE POPULATION AND LIFE STAGES 117
4.8.1. POSSIBLE CHILDHOOD SUSCEPTIBILITY 117
4.8.2. POSSIBLE GENDER DIFFERENCES 118
4.8.3. OTHER FACTORS INFLUENCING SUSCEPTIBILITY 118
5. DOSE-RESPONSE ASSESSMENTS 120
5.1. ORAL REFERENCE DOSE (RFD) 120
5.1.1. CHOICE OF PRINCIPAL STUDY AND CRITICAL EFFECT—WITH
RATIONALE AND JUSTIFICATION 120
5.1.2. METHODS OF ANALYSIS 126
5.1.2.1. BENCHMARK DOSE MODELING OF LIVER AND TESTICULAR
EFFECTS FROM DEANGELO ET AL. (2008) 126
5.1.2.2. BENCHMARK DOSE MODELING OF DEVELOPMENTAL
TOXICITY DAT A FROM SMITH ETAL. (1989) 131
5.1.3. RFD DERIVATION—INCLUDING APPLICATION OF UNCERTAINTY
FACTORS (UFS) 137
5.1.4. RFD COMPARISON INFORMATION 139
5.1.5. PREVIOUS RFD ASSESSMENT 140
5.2. INHALATION REFERENCE CONCENTRATION (RFC) 140
5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE 140
5.4. CANCER ASSESSMENT 141
5.4.1. CHOICE OF STUDY/DATA—WITH RATIONALE AND
JUSTIFICATION 143
5.4.2. DOSE-RESPONSE DATA 144
5.4.3. DOSE CONVERSION 145
5.4.4. EXTRAPOLATION METHODS 146
iv DRAFT - DO NOT CITE OR QUOTE
-------
5.4.5. ORAL CANCER SLOPE FACTOR AND INHALATION UNIT RISK 148
5.4.6. COMPARISON OF CENTRAL TENDENCY ESTIMATES OF ORAL SLOPE
FACTORS 149
6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE
RESPONSE 151
6.1. HUMAN HAZARD POTENTIAL 151
6.2. DOSE RESPONSE 154
6.2.1. NONCANCER/ORAL 154
6.2.2. NONCANCER/INHALATION 155
6.2.3. CANCER/ORAL AND INHALATION 155
7. REFERENCES 157
APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC COMMENTS
AND DISPOSITION A-l
APPENDIX B. INPUT AND OUTPUT DATA FOR BENCHMARK DOSE MODELING OF
DEVELOPMENTAL DATA FROM SMITH ETAL. (1989) B-l
APPENDIX C: MODELING OF LIVER TUMOR INCIDENCE DATA FOR MICE EXPOSED
TO TRICHLOROACETIC ACID IN DRINKING WATER C-l
APPENDIX D: BMD MODELING OF THE INCIDENCE OF HEPATOCELLULAR
CYTOPLASMIC ALTERATIONS, HEPATOCELLULAR INFLAMMATION,
HEPATOCELLULAR NECROSIS, AND TESTICULAR TUBULAR DEGENERATION
IN MICE EXPOSED TO TCA IN DRINKING WATER FOR USE IN DERIVATION OF
THE REFERENCE DOSE D-l
v DRAFT - DO NOT CITE OR QUOTE
-------
LIST OF TABLES
Table 3-1. Binding of TCA to plasma proteins from different species 9
Table 4-1. Summary of pre-chronic studies evaluating effects of TCA after oral
administration in rats and mice 24
Table 4-2a. Summary of longer-term (<52 weeks) studies evaluating noncancer
effects of TCA after oral administration in rats and mice 40
Table 4-2b. Summary of cancer bioassays and tumor promotion studies of TCA
in rats and mice 42
Table 4-3. Incidence and severity of nonneoplastic lesions in male B6C3F1 mice
exposed to TCA in drinking water for 60 weeks 47
Table 4-4. Incidence and severity of hepatocellular necrosis at 30-45 weeks in
male B6C3F1 mice exposed to TCA in drinking water 48
Table 4-5. Prevalence and Multiplicity of hepatocellular neoplasia in male B6C3F1 mice
exposed to TCA in drinking water for 60 weeks 48
Table 4-6. Incidence of hepatocellular neoplasia in male B3C6F1 mice exposed
to TCA in drinking water for 60 weeks 48
Table 4-7. Summary of developmental studies evaluating effects of TCA after oral
administration in rats 58
Table 4-8. Selected data for fetal anomalies, showing dose-related trends
following exposure of female Long-Evans rats to TCA on GDs 6-15 62
Table 4-9. Summary of available genotoxicity data on TCA 85
Table 5-1. Candidate studies for derivation oftheRfD for TCA 122
Table 5-2. Benchmark dose modeling results based on incidence of hepatocellular cytoplasmic
alterations in male B6C3F1 mice exposed to TCA in drinking water for 60 weeks
(DeAngelo et al., 2008) 128
Table 5-3. Benchmark dose modeling results based on incidence of hepatocellular inflammatiion
in male B6C3F1 mice exposed to TCA in drinking water for 60 weeks (DeAngelo et
al., 2008) 129
Table 5-4. Benchmark dose modeling results based on incidence of hepatocellular necrosis in
male B6C3F1 mice exposed to TCA in drinking wter for 30 to 45 weeks (DeAngelo
etal.,2008) 130
vi DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-5. Benchmark dose modeling results based on incidence of testicular tubular
degeneration in male B6C3F1 mice exposed to TCA in drinking water for 60 weeks
(DeAngelo et al., 2008) 131
Table 5-6. Dose response data for developmental endpoints in TCA-treated Long-Evans rats 132
Table 5-7. Benchmark dose modeling results for fetal incidence data 135
Table 5-8. Benchmark dose modeling results for litter incidence of levocardia 136
Table 5-9. Incidences of hepatocellular adenomas, carcinomas, or adenomas and carcinomas
combined in male B6C3F1 mice exposed to TCA in drinking water for 52 weeks
(Bull et al., 2002) 144
Table 5-3. Benchmark dose modeling results for fetal incidence data.. l35Table 5-10. Incidences
of hepatocellular adenomas, carcinomas, or adenomas and carcinomas combined in
male B6C3F1 mice exposed to TCA in drinking water for 52 weeks (Bull et al.,
1990) 144
Table 5-4. Benchmark dose modeling results for litter incidence of levocardia l36Table 5-11.
Incidences of hepatocellular adenomas, carcinomas, or adenomas and carcinomas
combined in male B6C3F1 mice exposed to TCA in drinking water for 60 weeks
(DeAngelo et al., 2008) 145
Table 5-12. Incidences of hepatocellular adenomas, carcinomas, or adenomas and carcinomas
combined in female B6C3F1 mice exposed to TCA in drinking water for 82 weeks
(Pereira, 1996) 145
Table 5-13. Incidences of hepatocellular adenomas, carcinomas, or adenomas and carcinomas
combined in male B6C3Flmice exposed to TCA in drinking water for 104 weeks
(DeAngelo et al., 2008) 145
Table 5-14. Predicted human equivalent lifetime doses associated with 10% extra risk (EDios)
for hepatocellular adenomas and carcinomas combined and their corresponding 95%
lower and upper confidence limits (LEDi0s and UEDi0s, respectively) based on the fit
of a one-stage multistage model 147
Table D-l.l. Benchmark dose modeling results based on incidence of hepatocellular
cytoplasmic alterations in male B6C3F1 mice exposed to TCA in drinking water for
60 weeks (DeAngelo et al., 2008) D-l
Table D-l.2. Benchmark dose modeling results based on incidence of hepatocellular
inflammation in male B6C3F1 mice exposed to TCA in drinking water for 60 weeks
(DeAngelo et al., 2008) D-2
Table D-l.3. Benchmark dose modeling results based on incidence of hepatocellular necrosis in
male B6C3F1 mice exposed to TCA in drinking water for 30 to 45 weeks (DeAngelo
etal.,2008) D-15
vii DRAFT - DO NOT CITE OR QUOTE
-------
Table D-1.4. Benchmark dose modeling results based on incidence of testicular tubular
degeneration in male B6C3F1 mice exposed to TCA in drinking water for 60 weeks
(DeAngelo et al., 2008) D-28
LIST OF FIGURES
Figure 2-1. Trichloroacetic acid 3
Figure 3-1. Proposed metabolic scheme for trichloroacetic acid 13
Figure 4-1. Proposed mode of action for PPARa agonism 95
Figure 5-1. Plot of predicted and observed litter incidence of levocardia in offspring of female
Long-Evans rats exposed to TCA on GDs 6-15 137
Figure 5-2. Comparison of RfDs across target organs or endpoints 139
Figure 5-3. A comparison of estimates of central tendencies (along with corresponding 90%
confidence intervals) of the potency of TCA based on the incidece of hepatocellular
adenomas & carcinomas combined across five rodent bioassays 149
Figure C-l. Observed and predicted combined incidences of hepatocellular adenomas and
carcinomas, based on responses in male B6C3F1 mice exposed to TCA in
drinking water for 52 weeks C-3
Figure C-2. Predicted and observed combined incidences of hepatocellular adenomas and
carcinomas, based on responses in male B6C3F1 mice exposed to TCA in
drinking water for 52 weeks C-4
Figure C-3. Predicted and observed combined incidence of hepatocellular adenomas and
carcinomas, based on responses in male B6C3F1 mice exposed to TCA in
drinking water for 60 weeks C-5
Figure C-4. Predicted and observed combined incidence of hepatocellular adenomas and
carcinomas, based on responses in female B6C3F1 mice exposed to TCA in
drinking water for 82 weeks C-6
Figure C-5. Predicted and observed combined incidence of hepatocellular adenomas and
carcinomas, based on responses in male B6C3F1 mice exposed to TCA in drinking
water for 104 weeks C-7
viii DRAFT - DO NOT CITE OR QUOTE
-------
ABBREVIATIONS AND ACRONYMS
ACO acyl-CoA oxidase
ACP acid phosphatase
AHF altered hepatic foci
AIC Akaike information criterion
ALP alkaline phosphatase
ALT alanine aminotransferase
AST aspartate aminotransferase
AUC area under the curve
BMD benchmark dose
BMDL 95% lower confidence limits on the BMD
BMDS benchmark dose software
BMR benchmark response
BrdU bromodeoxyuridine
BSA bovine serum albumin
CACT carnitine acetyl-CoA transferase
CASRN Chemical Abstracts Service registry number
CpG cytosine-guanine dinucleotide
DCA dichloroacetic acid
DEN diethylnitrosamine
DMR-2 differentially methylated region-2
DMSO dimethylsulfoxide
ECso median effective concentration
EDio central estimate of exposure dose at 10% extra risk
ENU ethylnitrosourea
EPA U.S. Environmental Protection Agency
FMU first morning urine
GC/MS gas chromatography/mass spectrometry
GD gestation day
GGT gamma-glutamyl transpeptidase
GSH glutathione
GST glutathione-S-transferase
GTPase guanosine triphosphatase
HA hepatocellular adenoma
HC hepatocellular carcinoma
HPLC high performance liquid chromatography
IX
DRAFT - DO NOT CITE OR QUOTE
-------
HSDB Hazardous Substances Data Bank
IGF-II insulin-like growth factor
IL interleukin
i.p. intraperitoneal(ly)
IPCS International Programme on Chemical Safety
IPRL isolated perfused rat liver
IRIS Integrated Risk Information System
LD50 median lethal dose
LDH lactate dehydrogenase
LECio lower 95% bound on exposure concentration at 10% extra risk
LEDio lower 95% bound on exposure dose at 10% extra risk
LOAEL lowest-observed-adverse-effects level
LOH loss of heterozygosity
MCA monochloroacetic acid
MDA malondialdehyde
5MeC 5-methylcytosine
MiG MDA-derived deoxyguanosine
MNU N-methyl-N-nitrosourea
MOA mode of action
mRNA messenger RNA
MTase methyltransferase
MTD maximum tolerated dose
NIOSH National Institute for Occupational Safety and Health
NLM National Library of Medicine
NOAEL no-observed-adverse-effects level
NRC National Research Council
NTD neural tube development
8-OHdG 8-oxo-2'-deoxyguanosine
PAS periodic acid-Schiffs reagent
PB phenobarbital
PEN phenyl-tertiary-butyl nitroxide
PBPK physiologically based pharmacokinetic
PCNA proliferating cell nuclear antigen
PCO palmitoyl-CoA oxidase
PCR polymerase chain reaction
PFOA perfluorooctanoic acid
PG prostaglandin
x
DRAFT - DO NOT CITE OR QUOTE
-------
PH partial hepatectomy
pKa dissociation constant of an acid
POD point of departure
POR prevalence odds ratio
PP-A peroxisome proliferation-associated
PPAR peroxisome proliferator-activated receptor
PPRE peroxisome proliferator response element
RDS replicative DNA synthesis
RfC reference concentration
RfD reference dose
RT-PCR reverse transcription PCR
SA superoxide anion
SAM S-adenosylmethionine
SOD superoxide dismutase
SSB single-strand break
SSCP single-stranded confirmation polymorphism
SuDH succinate dehydrogenase
TEARS thiobarbituric acid-reactive substances
TCA trichloroacetic acid
TCE trichloroethylene
TGF transforming growth factor
TPA 12-O-tetradecanoylphorbol 13-acetate
UF uncertainty factor
XI
DRAFT - DO NOT CITE OR QUOTE
-------
FOREWORD
The purpose of this Toxicological Review is to provide scientific support and rationale
for the hazard and dose-response assessment in IRIS pertaining to chronic exposure to
trichloroacetic acid (TCA). It is not intended to be a comprehensive treatise on the chemical or
toxicological nature of TCA.
The intent of Section 6, Major Conclusions in the Characterization of Hazard and Dose
Response, is to present the major conclusions reached in the derivation of the reference dose,
reference concentration and cancer assessment, where applicable, and to characterize the overall
confidence in the quantitative and qualitative aspects of hazard and dose response by addressing
the quality of data and related uncertainties. The discussion is intended to convey the limitations
of the assessment and to aid and guide the risk assessor in the ensuing steps of the risk
assessment process.
For other general information about this assessment or other questions relating to IRIS,
the reader is referred to EPA's IRIS Hotline at (202) 566-1676 (phone), (202) 566-1749 (fax), or
hotline.iris@epa.gov (email address).
xii DRAFT - DO NOT CITE OR QUOTE
-------
AUTHORS, CONTRIBUTORS, AND REVIEWERS
CHEMICAL MANAGER
Diana Wong, Ph.D., DABT
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
AUTHORS
Diana Wong, Ph.D., DABT
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Ted Berner
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Lori Moilanen, Ph.D., DABT
Syracuse Research Corporation
Syracuse, NY
Peter McClure, Ph.D., DABT
Syracuse Research Corporation
Syracuse, NY
Brian Anderson, M.E.M.
Syracuse Research Corporation
Syracuse, NY
REVIEWERS
This document has been reviewed by EPA scientists, and interagency reviewers from
other federal agencies.
INTERNAL EPA REVIEWERS
Robert McGaughy, Ph.D.
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Joyce Donohue, Ph.D.
Office of Water
U.S. Environmental Protection Agency
Xlll
DRAFT - DO NOT CITE OR QUOTE
-------
Washington, DC
Susan Rieth
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Weihsueh Chiu
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Jane Caldwell
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Karen Hogan
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
xiv DRAFT - DO NOT CITE OR QUOTE
-------
1. INTRODUCTION
This document presents background information and justification for the Integrated Risk
Information System (IRIS) Summary of the hazard and dose-response assessment of
trichloroacetic acid (TCA). IRIS Summaries may include oral reference dose (RfD) and
inhalation reference concentration (RfC) values for chronic and other exposure durations, and a
carcinogenicity assessment.
The RfD and RfC, if derived, provide quantitative information for use in risk assessments
for health effects known or assumed to be produced through a nonlinear (presumed threshold)
mode of action. The RfD (expressed in units of mg/kg-day) is defined as an estimate (with
uncertainty spanning perhaps an order of magnitude) of a daily exposure to the human
population (including sensitive subgroups) that is likely to be without an appreciable risk of
deleterious effects during a lifetime. The inhalation RfC (expressed in units of mg/m3) is
analogous to the oral RfD, but provides a continuous inhalation exposure estimate. The
inhalation RfC considers toxic effects for both the respiratory system (portal-of-entry) and for
effects peripheral to the respiratory system (extrarespiratory or systemic effects). Reference
values are generally derived for chronic exposures (up to a lifetime), but may also be derived for
acute (<24 hours), short-term (>24 hours up to 30 days), and sub chronic (>30 days up to 10% of
lifetime) exposure durations, all of which are derived based on an assumption of continuous
exposure throughout the duration specified. Unless specified otherwise, the RfD and RfC are
derived for chronic exposure duration.
The carcinogenicity assessment provides information on the carcinogenic hazard
potential of the substance in question and quantitative estimates of risk from oral and inhalation
exposure may be derived. The information includes a weight-of-evidence judgment of the
likelihood that the agent is a human carcinogen and the conditions under which the carcinogenic
effects may be expressed. Quantitative risk estimates may be derived from the application of a
low-dose extrapolation procedure. If derived, the oral slope factor is a plausible upper bound on
the estimate of risk per mg/kg-day of oral exposure. Similarly, an inhalation unit risk is a
plausible upper bound on the estimate of risk per ug/m3 air breathed.
Development of these hazard identification and dose-response assessments for TCA has
followed the general guidelines for risk assessment as set forth by the National Research Council
(1983). EPA guidelines and Risk Assessment Forum Technical Panel Reports that may have
benn used in the development of this assessment include the following: Guidelines for the Health
Risk Assessment of Chemical Mixtures (U.S. EPA, 1986a), Guidelines for Mutagenicity Risk
Assessment (U.S. EPA, 1986b), Recommendations for and Documentation of Biological Values
for Use in Risk Assessment (U.S. EPA, 1988), Guidelines for Developmental Toxicity Risk
Assessment (U.S. EPA, 1991), Interim Policy for Particle Size and Limit Concentration Issues in
1 DRAFT - DO NOT CITE OR QUOTE
-------
Inhalation Toxicity (U.S. EPA, 1994a), Methods for Derivation of Inhalation Reference
Concentrations and Application of Inhalation Dosimetry (U.S. EPA, 1994b), Use of the
Benchmark Dose Approach in Health Risk Assessment (U.S. EPA, 1995), Guidelines for
Reproductive Toxicity Risk Assessment (U.S. EPA, 1996), Guidelines for Neurotoxicity Risk
Assessment (U.S. EPA, 1998), Science Policy Council Handbook: Risk Characterization (U.S.
EPA, 2000a), Benchmark Dose Technical Guidance Document (U.S. EPA, 2000b),
Supplementary Guidance for Conducting Health Risk Assessment of Chemical Mixtures (U.S.
EPA, 2000c), A Review of the Reference Dose and Reference Concentration Processes (U.S.
EPA, 2002), Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), Supplemental
Guidance for Assessing Susceptibility from Early-Life Exposure to Carcinogens (U.S. EPA,
2005b), Science Policy Council Handbook: Peer Review (U.S. EPA, 2006a), and A Framework
for Assessing Health Risks of Environmental Exposures to Children (U.S. EPA, 2006b).
The literature search strategy employed for this compound was based on the Chemical
Abstracts Service Registry Number (CASRN) and at least one common name. Any pertinent
scientific information submitted by the public to the IRIS Submission Desk was also considered
in the development of this document. The relevant literature was reviewed through March,
2009.
DRAFT - DO NOT CITE OR QUOTE
-------
2. CHEMICAL AND PHYSICAL INFORMATION
Trichloroacetic acid (TCA) is a colorless to white crystalline solid with a sharp, pungent
odor (NIOSH, 2003). The dissociation constant (pKa) for TCA at 25°C is 0.51. In aqueous
solutions, TCA occurs almost exclusively in the ionized form as trichloroacetate anion.
Common synonyms for trichloroacetic acid include TCA, trichloroethanoic acid, and trichloro-
methanecarboxylic acid. The structure of TCA is shown in Figure 2-1.
Figure 2-1. Trichloroacetic acid.
Selected physical and chemical properties of TCA (CASRN
: 76-03-9):
Empirical formula
Molecular weight
Density
Melting point
Boiling point
Partition coefficient (log Kow)
Vapor pressure
-log dissociation constant (pKa)
Henry's Law constant
Water solubility
Other solubilities
C2HC13O2 (Budavari, 2001)
163.39 (Budavari, 2001)
1.6126 g/mL at 64°C (Lide, 2000)
57.5°C (Lide, 2000)
196.5°C (Lide, 2000)
1.33(Hanschetal., 1995)
0.16 mmHg at 25°C (Perry and Green, 1984)
0.51 at 25°C (Serjeant and Dempsey, 1979)
1.35 x 10"8 atm-mVmol at 25°C (Bowden et al.,
1998)
1306 g/100 g at 25°C (Morris and Bost, 2002)
At 25°C: methanol, 2143 g/100 g; ethyl ether,
617 g/100 g; acetone, 850 g/100 g; benzene,
201 g/100 g; o-xylene, 110 g/100 g (Morris and
Bost, 2002)
TCA is used as a soil sterilizer and as a laboratory intermediate or reagent in the
synthesis of a variety of medicinal products and organic chemicals (NLM, 2003). Medical
applications of TCA include use as a reagent for the detection of albumin (Lewis, 1997),
application as an antiseptic (Morris and Bost, 2002), and use as a skin peeling agent (Al-Waiz
and Al-Sharqi, 2002; Lee et al., 2002; Coleman, 2001). TCA is also used industrially as an
etching and pickling agent for the surface treatment of metals and (in solution) as a solvent in the
plastics industry (Koenig, 2002).
3 DRAFT - DO NOT CITE OR QUOTE
-------
TCA can be formed as a combustion by-product of organic compounds in the presence of
chlorine (Juuti and Hoekstra, 1998). Stack gases of municipal waste incinerators have been
reported to contain 0.37-3.7 |ig/m3 TCA (Mower and Nordin, 1987). TCA could be a
photooxidation product of tetrachloroethylene and 1,1,1-trichloroethane in the atmosphere (Juuti
and Hoekstra, 1998; Sidebottom and Franklin, 1996; Reimann et al., 1996). Sidebottom and
Franklin (1996) suggested that atmospheric degradation of chlorinated solvents could contribute
only a minor amount of TCA to the atmosphere, based on the mechanistic and kinetic evidence,
as well as the observed global distribution of TCA in precipitation. However, TCA has been
detected in rainwater at concentration range of 0.01-1 |ig/L (Reimann et al., 1996).
TCA is formed from organic material during water chlorination (IPCS, 2000; Coleman et
al., 1980), and has been detected in groundwater and surface water distribution systems and in
swimming pool water. Human exposure to TCA directly occurs through consumption and use of
tap water disinfected with chlorine-releasing disinfectants (U.S. EPA, 2005c). TCA was detected
in vegetables, fruits, and grains (Reimann et al., 1996) and can be taken up into foodstuffs from
the cooking water (U.S. EPA, 2005c). Therefore, human exposure to TCA can also occur via
food consumption.
DRAFT - DO NOT CITE OR QUOTE
-------
3. TOXICOKINETICS
3.1. ABSORPTION
Results from studies with rats and mice indicate that TCA is extensively absorbed by the
gastrointestinal tract. In studies of excreta collected for up to 48 hours from male F344 rats and
B6C3Fi mice given single doses of 14C-labeled TCA ranging from 5 to 100 mg/kg, radioactivity
detected in urine and in CO2 in expired air represented about 57-72% and 4-8% of the
administered dose, respectively (Larson and Bull, 1992). Most of the urinary radioactivity was
unmetabolized TCA, which accounted for 81-90% of the urinary radioactivity and 48-65% of
the administered radioactivity. Urinary radioactivity in metabolites of TCA represented only
minor amounts of the administered radioactivity: 1-3% for dichloroacetic acid (DCA) and 5-
11% for an high performance liquid chromatography (HPLC) fraction coeluting with standards
for glyoxylic acid, oxalic acid, and glycolic acid (which exist as glyoxylate, oxalate, glycolate
anions at physiological pH). Radioactivity detected in feces accounted for only about 2-4% of
the administered radioactivity (Larson and Bull, 1992). In another study in which male B6C3Fi
mice were administered single 100-mg/kg doses of uniformly labeled 14C-TCA by gavage, the
average distribution of radioactivity 24 hours after dose administration was about 55% in urine,
about 5% in CO2, about 5% in feces, with the remainder in the carcasses (Xu et al., 1995).
Radioactivity in urinary metabolites, expressed as percentage of the administered dose, showed
the following distribution: 44.5% as trichloroacetate, 0.2% as dichloroacetate, 0.03% as
monochloroacetate, 0.06% as glyoxylate, 0.11% as glycolate, 1.5 % as oxalate, and 10.2% as
unidentified compounds. Results from both of these studies are consistent with extensive
absorption by the gastrointestinal tract, followed by rapid elimination in the urine, principally as
the nonmetabolized parent compound.
Indicative of rapid absorption, TCA concentrations in the plasma or liver peaked in the
first hour following oral dosing in other short-term studies with mongrel dogs (Hobara et al.,
1988a) and male B6C3Fi mice (Styles et al., 1991). Likewise, peak blood concentrations of
TCA were attained at a mean time of 1.55 hours after oral administration of single doses of
500 |imol/kg (82 mg/kg) TCA to male F344 rats (Schultz et al., 1999). Comparison of the areas
under the curve (AUCs) of plasma concentrations of TCA following oral administration and
intravenous administration of TCA at the same dose level indicated that oral bioavailability of
TCA was approximately equivalent to intravenous bioavailability (Schultz et al., 1999). The
average ratio of oral:intravenous AUCs was 1.16. The 16% higher AUC value for oral exposure
likely reflects measurement or statistical variability and/or differences in clearance rate by the
two routes of administration. The mean absorption time, which was determined as the difference
in the mean residence time in blood following oral and intravenous dosing, was 6 hours for TCA.
The mean absorption time is dependent on clearance from the blood as well as the absorption
5 DRAFT - DO NOT CITE OR QUOTE
-------
rate; therefore, the longer mean absorption time as compared to time-to-peak blood
concentration of 1.55 hours may reflect slower clearance following oral dosing (Schultz et al.,
1999).
Results from studies of urinary excretion of TCA by human subjects following 30-minute
sessions in chlorinated swimming pool water indicate that TCA is rapidly absorbed by the skin
(Kim and Weisel, 1998). TCA concentrations in pool water were measured before and after the
subjects (2 males and 2 females) either walked without submerging their heads (dermal exposure
only) or swam (dermal exposure plus incidental oral exposure) in the pool for 30 minutes. TCA
concentrations in the swimming pool water at various sessions varied from 57 to 871 |ig/L with a
mean of 420 jig/L and a median of 278 |ig/L. Entire urine voids were collected for at least 24
hours before exposure and 20-40 hours following exposure, at approximately 3-hour intervals.
Additional urine samples were collected 5-10 minutes immediately before and after exposures.
During the 24 hours prior to and following exposure, subjects avoided activities such as drinking
chlorinated tap water or visiting the dry cleaner, which might have resulted in urinary TCA
excretion. For each exposure session, the amount of urinary TCA associated with exposure was
calculated for each subject from the amount of TCA excreted within 3 hours after exposure
minus the amount excreted within 3 hours prior to exposure. Pre-exposure amounts of TCA in
urine ranged from 155 ng to 1183 ng, whereas postexposure amounts ranged from 294 ng to
1590 ng. The amount of urinary TCA associated with the 30-minute exposure sessions ranged
from 33 to 824 ng, depending on the subject and exposure session. Urinary excretion rates
(ng/minute), calculated for various intervals before and after exposure, showed peaks at the
postexposure 5-10-minute period that were about threefold higher than pre-exposure period
rates. Excretion rates calculated for the first full 3-hour interval after exposure returned to
values that were not discernable from pre-exposure rates. A scatter plot of the amount of urinary
TCA per exposed body surface area (ng/m2) in subjects under the dermal-exposure-alone
scenario versus TCA exposure expressed as the TCA concentration in water multiplied by the
exposure duration (|ig/L x h), indicated that urinary excretion (and thus, presumably dermal
absorption) was higher with higher exposure. For exposures of about 20 and 420 jig TCA /L x
h, values for urinary TCA per surface area ranged from about 10 to 50 ng/m2 and 60 to 160
ng/m2, respectively. The results from this study indicate that dermal absorption and subsequent
urinary elimination of TCA are rapid, but were inadequate to provide more quantitative measures
of dermal absorption for TCA, such as dermal permeability coefficients.
No studies were identified on the extent or rate of TCA absorption following inhalation
exposure.
DRAFT - DO NOT CITE OR QUOTE
-------
3.2. DISTRIBUTION
The tissue distribution of TCA following absorption has been most completely
characterized in male F344 rats injected intravenously with radiolabeled [1-14C]TCA at doses of
0, 6.1, 61, or 306 jimol/kg (0, 1, 10, or 50 mg/kg) (Yu et al., 2000). TCA equivalent
concentrations in plasma, red blood cells, and eight tissues (based on levels of detected
radioactivity) were determined at various time points for up to 24 hours after injection (1, 3, 6, 9,
and 24 hours). Peak concentrations in plasma and all tissues were observed at the postexposure
first sampling. Levels of radioactivity in urine, feces, and expired air were also measured.
Overall kinetic behavior was similar at all three doses (i.e., TCA equivalent concentrations
declined with time in plasma and tissues, and first-order elimination rate constants were not
consistently changed across tissues with increasing dose level). At early time points, the highest
TCA equivalent concentrations were measured in plasma, followed by kidney, red blood cells,
liver, skin, small intestine, large intestine, muscle, and fat; the relative order of these
concentrations remained unchanged up to 3 hours following dosing. However, at 24 hours
following dosing, the distribution pattern was changed, with the liver showing the highest TCA
equivalent concentration. First-order rate constants for the disappearance of TCA equivalents
from plasma and tissues were calculated and subsequently classified by the study authors into
three groups: (1) fast elimination (rate constants between 0.065 and 0.156) in plasma, red blood
cells, muscle, and fat; (2) moderate elimination (rate constants between 0.064 and 0.077) in
kidney and skin; and (3) slow elimination (rate constants between 0.037 and 0.063) in liver,
small intestine, and large intestine.
To explore a possible explanation for the apparent differences in elimination kinetics of
TCA in the plasma and liver of rats, Yu et al. (2000) compared the time courses of the
distribution of nonextractable TCA equivalents (i.e., radioactivity from TCA metabolically
incorporated into macromolecules) and extractable TCA equivalents in plasma and liver for up
to 24 hours after injection. In both plasma and liver, nonextractable TCA equivalents increased
to plateau levels within 6 to 10 hours after injection. Although the concentrations of
nonextractable TCA equivalents in liver were higher than those in plasma, the total amount of
TCA metabolized in these 24-hour studies (nonextractable TCA equivalents plus radioactivity in
CO2 in expired air) was estimated to be less than 20% of the administered dose. Results from in
vitro binding studies indicated that noncovalent, reversible binding of TCA in rat plasma
(presumably to proteins) was much more extensive than binding in liver homogenates (Yu et al.,
2000). Yu et al. (2000) hypothesized that TCA disappears from the liver more slowly than from
the plasma because of a concentrating transport process in hepatocyte plasma membranes. In
addition, theoretical calculations of cumulative urinary excretion of TCA, assuming glomerular
filtration of free, nonbound plasma TCA (the only operable excretory process), indicated that
actual urinary excretion rates of TCA were slower than the theoretical values (Yu et al., 2000).
7 DRAFT - DO NOT CITE OR QUOTE
-------
It was hypothesized that this difference may be due to the occurrence of reabsorption of TCA
into renal tubules and/or from the bladder. Support for this hypothesis, which provides at least a
partial explanation for the relatively high concentrations of TCA equivalents in the kidney,
includes the observation of reabsorption of TCA into the systemic circulation following injection
into the bladder of dogs (Hobara et al., 1988b, 1987).
Reversible binding of trichloroacetate anion to positively charged proteins in plasma has
been hypothesized to play a role in determining the tissue distribution and elimination of TCA
and has been demonstrated in in vivo and in vitro studies (Lumpkin et al., 2003; Toxopeus and
Frazier, 2002, 1998; Yu et al., 2000; Schultz et al., 1999; Templin et al., 1993).
Unbound TCA accounted for an average 53% (±4%) (SD) of the total TCA plasma
concentration in blood samples collected at 0.25, 1, and 3 hours after intravenous injection of
single doses of 500 |imol TCA/kg (81.7 mg/kg) to male F344 rats (Schultz et al., 1999). In this
in vivo study, gas chromatography and electron capture detection were used to determine TCA
concentrations in plasma samples and ultrafiltrates of plasma samples from which proteins with
molecular weight >10,000-12,000 were removed. The blood/plasma concentration ratio for
TCA was 0.76, indicating some propensity for TCA to partition to the plasma, and was
consistent with the ability of TCA to bind plasma proteins.
Templin et al. (1993) estimated the degree of in vitro TCA binding to plasma proteins by
incubating [14C]TCA (position of radiolabel not specified) at various concentrations with plasma
obtained from nonexposed male B6C3Fi mice. The amounts of unbound and bound
radioactivity were determined in samples removed after various incubation times, using
ultrafiltration to remove proteins from the samples. At TCA concentrations below 306 nmol/mL,
approximately 50-57% of the TCA was bound to plasma constituents, while percentage binding
decreased with increasing TCA concentrations. Approximately 41, 34, and 23% of TCA was
bound to plasma constituents at TCA concentrations of 306, 612, and 1224 nmol/mL,
respectively.
Templin et al. (1995) measured the binding of TCA to plasma proteins in 4 different
species: dog, rat, mouse, and human. Plasma samples were prepared from whole blood and
incubated with 3-1224 nmol/ml [14C]TCA at 37°C for 30 min. Binding of TCA to plasma
constituents was analyzed using a Scatchard plot and summarized in Table 3-1. Binding of TCA
to plasma proteins was higher in humans than in rats and mice.
DRAFT - DO NOT CITE OR QUOTE
-------
Table 3-1. Binding of TCA to plasma proteins from different species
Mouse
Rat
Dog
Human
6 nmol/mL
55%
53.5%
64.8%
84.3%
61 nmol/mL
52%
48.9%
58.5%
83.3%
612 nmol/mL
34%
38.3%
54.2%
74.8%
Note. Values expressed as percent of [14C]-TCA associated with protein fraction, expressed as mean value for two
replications of pooled samples.
Source: Templin et al. (1995)
Toxopeus and Frazier (1998) investigated the kinetics of TCA in isolated perfused rat
liver (IPRL) from male F344 rats. The IPRL system was dosed with either 5 or 50 jimol of
TCA, and TCA concentrations were monitored in perfusion medium supplemented with 4%
bovine serum albumin (BSA) and in bile for 2 hours. Liver viability was assessed by measuring
lactate dehydrogenase (LDH) leakage into perfusion medium and by the rate of bile production.
At the end of the exposure period, the concentration of TCA in liver was measured. In the study
with 50 (imol TCA, the total TCA concentration (free and bound to BSA) in perfusion medium
decreased slightly during the first 30 minutes and then remained constant for the duration of the
exposure period; the total TCA concentration in the perfusion medium was relatively constant in
the study with 5 (imol TCA. At the high concentration, approximately 93% TCA was bound to
BSA, and the free TCA concentration averaged 15.4 jiM at 5 minutes of exposure and 14.9 jiM
at 120 minutes. At the low concentration, 96% of the TCA was bound to protein and the free
TCA concentration was approximately constant at 0.9 to 1 |iM over the study period. The
calculated free-TCA concentration in the liver intracellular space was higher than the free-TCA
concentration in the perfusion medium. Enzyme leakage and bile flow were similar at both TCA
exposure levels to those in the control liver, indicating the absence of hepatotoxicity. The
authors concluded that the binding of TCA to BSA in perfusion medium limits the uptake of
TCA by the liver and that TCA is virtually unmetabolized by the liver. These findings are
consistent with those from in vivo mouse studies (e.g., Templin et al., 1993) demonstrating TCA
binding to plasma proteins and suggest that TCA kinetics may be influenced by plasma-protein
binding. In a similar study conducted in the same laboratory, using concentrations of 50, 250, or
1000 jiM TCA (Toxopeus and Frazier, 2002), more than 90% of the TCA in the perfusion
medium was bound to albumin, confirming the results for extent of binding obtained by
Toxopeus and Frazier (1998).
Lumpkin et al. (2003) measured the in vitro binding of TCA at 13 concentrations ranging
from 0.06 to 6130 jiM (0.01 to 1000 |ig/mL) to plasma proteins in samples of plasma from
humans, rats, and mice. Pooled plasma for each species was obtained from commercial sources.
Neither donor strain (for rodents) nor donor sex were specified. Binding was determined by
9 DRAFT - DO NOT CITE OR QUOTE
-------
using an equilibrium dialysis technique. Plots of bound versus free TCA concentrations were
compared with simulations from three binding models—a single saturable site model, a two
saturable site model, and a saturable plus unsaturable site model—to explore the mechanistic
basis for species differences. Plots of bound versus free TCA concentration indicated that the
proportion of bound TCA is substantially higher for human than for rodent plasmas. Decreases
in the proportion of bound to free TCA at concentrations exceeding 307 jiM were indicative of
saturation of plasma binding. Human plasma showed the most pronounced binding over the
tested range of concentrations, followed by rat, then mouse. Binding to human plasma was
highest (86.8%) at the lowest quantifiable TCA concentration (0.12 jiM). The bound fraction in
human plasma remained relatively constant, with a mean value of 81.6% over a 3.7 order of
magnitude increase in TCA concentration. In comparison, maximum and average quasi-steady
state bound fractions were 66.6% and 38.6% for the rat and 46.6% and 19.1% for the mouse,
respectively.
The study authors noted that the average value of TCA protein binding for the mouse was
considerably lower than the range of 34-57% determined in vitro in male B6C3Fi mice reported
by Templin et al. (1993). The reason for the disparity is unclear, but Lumpkin et al. (2003) noted
that Templin et al. (1993) used Scatchard analysis over a narrower range of TCA concentrations
to estimate binding parameters. The best fits to the observed data were obtained using the single
saturable binding process model, but data limitations (inadequate number of data points at low
TCA concentrations) precluded acceptable fits of the two saturable process model. Use of
albumin rather than total plasma protein concentration also improved model fit. The calculated
binding capacity (Bmax) values for humans, rats, and mice were 709, 283, and 29 jiM of TCA,
respectively. The average number of binding sites per molecule of protein (N) were 2.97, 1.49,
and 0.17, respectively. The low N value observed for mice may indicate other, competing
ligands for TCA in mouse plasma. The dissociation constant values for humans, rats, and mice
were 174.6, 383.6, and 46.1 jiM, respectively. The higher binding capacity of human plasma
was correlated with a higher number of binding sites per molecule of protein and higher reported
plasma concentrations of albumin (239 jiM for humans versus 190-196 jiM for rodents).
A possible toxicological significance of these findings for binding of TCA to plasma
proteins is that the extent of plasma binding may influence the distribution of TCA from blood to
target tissues to a degree that may influence species differences in susceptibility to TCA toxicity.
Based on the results from these in vitro binding studies and published reports of peak plasma
concentrations of total TCA in mice (580 jiM) and rats (300 jiM) following gavage exposure to
1,200 mg/kg TCE, Lumpkin et al. (2003) calculated that plasma levels of free TCA would be
about four- to fivefold higher in mice than in rats at this dose level. Lumpkin et al. (2003)
speculated that this difference was consistent with the apparent relative susceptibility of mice to
TCA-induced liver tumors. The relative susceptibility of rats and mice to TCA-induced liver
10 DRAFT - DO NOT CITE OR QUOTE
-------
tumors awaits confirmation from further research (as discussed in Section 4.7), as does the
hypothesis that toxicokinetics of TCA in humans may be more like TCA toxicokinetics in rats
than in mice.
Abbas and Fisher (1997) determined in vitro tissue:blood partition coefficients for TCA
in B6C3Fi mouse tissues by using a closed vial equilibration method. The tissue to blood
partition coefficients were 1.18 for the liver, 0.88 for the muscle, 0.74 for the kidney, and 0.54
for the lung. Comparable empirical data for TCA tissue:blood partition coefficients in other
species were not located.
No additional studies were identified that might confirm the nature and extent of species
differences in TCA distribution. Indirect evidence, primarily from studies involving exposure to
chlorinated solvents, suggests that TCA is available for systemic distribution in humans, as
determined by appearance of TCA in the blood and urine. TCA is a metabolite of
trichloroethylene (TCE) and has been frequently measured in the urine or blood of humans
exposed to TCE as a result of environmental contamination (Bruning et al., 1998; Skender et al.,
1994; Vartiainen et al., 1993; Ziglio et al., 1983; Ziglio, 1981) and in volunteer studies (Fisher et
al., 1998; Brashear et al., 1997; NIOSH, 1973). TCA is also found in the blood and urine of
humans without known chlorinated-solvent exposures (Hajimiragha et al., 1986) and in
individuals exposed to low concentrations of TCA in swimming pool water (Kim and Weisel,
1998) and drinking water (Calafat et al., 2003; Froese et al., 2002; Kim and Weisel, 1998).
No studies investigating the toxicokinetics or degree of maternal-to-fetus or blood-to-
breast milk transfer of TCA were located, although TCA has been detected in mouse fetuses and
amniotic fluid following 1-hour inhalation exposures of pregnant C57BL mice to high
concentrations of TCE or tetrachloroethylene (presumably 1100-1200 ppm) (Ghantous et al.,
1986). In these studies, peak TCA concentrations in fetuses and amniotic fluid were attained 4
hours after cessation of exposure.
3.3. METABOLISM
As discussed in Sections 3.1 and 3.2, results from studies of rats and mice involving oral
or intravenous administration of radiolabeled TCA indicate that TCA is metabolized to only a
limited extent. Urinary excretion of nonmetabolized TCA accounted for about 48% to 55% of
administered oral doses ranging from 5 to 100 mg/kg in rats and mice (Xu et al., 1995; Larson
and Bull, 1992). Radioactivity in CO2 collected in expired air accounted for 5-8% of
administered doses in these studies, and amounts of radioactivity detected in individual
metabolites in urine, such as DCA, monochloroacetic acid (MCA), glyoxylic acid, glycolic acid,
and oxalic acid, were generally small, each accounting for less than 2 or 3% of administered
doses (Xu et al., 1995; Larson and Bull, 1992). In contrast, orally administered radiolabeled
DCA is much more extensively metabolized in rats and mice than TCA (Larson and Bull, 1992).
11 DRAFT - DO NOT CITE OR QUOTE
-------
Based on measurement of radioactivity in expired CC>2 and in nonextractable radioactivity in
plasma and tissues (i.e., radioactivity from metabolized TCA incorporated into macromolecules),
Yu et al. (2000) estimated that less than 20% of an administered intravenous dose of 50 mg
TCA/kg was metabolized in rats within 24 hours. Within 24 hours after injection of 1 or 50 mg
TCA/kg, urinary excretion accounted for about 48% and 87% \ and total exhaled CC>2 accounted
for about 12% and 8%, of the administered doses, respectively (Yu et al., 2000). These results
are consistent with the idea that, at the higher dose level, metabolism of TCA may have been
saturated, leading to an increased percentage dose excreted as TCA in the urine and a decreased
percentage of dose exhaled as metabolized CC>2. However, the distribution of radioactivity
among TCA and potential metabolites in the urine was not quantified in this study (Yu et al.,
2000), so confirmation of this idea awaits further research.
Figure 3-1 presents a proposed metabolic scheme for TCA, which is based on results
from in vivo and in vitro studies in animals. The first proposed step is the reductive
dehalogenation of TCA by cytochrome P450 enzymes, producing DCA (i.e., dichloroacetate) via
a free radical intermediate, the dichloroacetate radical. Early evidence in support of this step
was restricted to the detection of radioactivity from TCA in urinary DCA (Xu et al., 1995;
Larson and Bull, 1992) and the formation of lipid peroxidation by-products following
incubations of liver microsomes with TCA (Ni et al., 1996; Larson and Bull, 1992).
These values were extracted from Figure 2 of the Yu et al. (2000) report.
12 DRAFT - DO NOT CITE OR QUOTE
-------
Cl O
Cl—C-C TCA
Cl OH
P450
O=C-OH
01 Q. DCA radical
I
Cl
OH O
1 II
P — P
w w ^
H2 OH
Glycolic acid
/
/
/
'
2
ff ff -ci + c, [>
— "" P P < -» r-
ii 9
H OH OH
H! ^ H O
1 1 II
-c. -• — ci— c-c
1 1 1
01 Cl OH
Glyoxylic acid L J .^
/
\
0
OH
0 0 /
H
Cl OH
X'
^
H 0
y H-C-C MCA
OH Cl OH
Oxalic acid
DCA
Figure 3-1. Proposed metabolic scheme for trichloroacetic acid.
Note: Molecules in brackets are intermediate proposed by Xu et al. (1995).
Sources: Adapted from Bull (2000); Lash et al. (2000); Merdink et al. (2000);
Xuetal. (1995).
13
DRAFT - DO NOT CITE OR QUOTE
-------
Some uncertainty about the metabolic formation of DC A from TCA has been expressed,
because DCA has been shown to form as an artifact during sample processing (Ketcha et al.,
1996). Using analytical processes and methods to prevent the artifactual conversion of TCA to
DCA, Merdink et al. (1998) reported that DCA was not detected in blood samples from male
B6C3Fi mice given single intravenous doses of 100 mg/kg TCA. Likewise, Yu et al. (2000)
reported that radiolabeled DCA or other radiolabeled metabolites were not detected in plasma,
urine, or other tissues collected from male F344 rats following intravenous injection of 14C-
labeled TCA, although metabolism of TCA was indicated in this study by the detection of
radioactivity in exhaled CO2 and in nonextractable materials (e.g., incorporated into cellular
macromolecules) in plasma and tissue extracts. However, simulations with a pharmacokinetic
model indicated that the rapid elimination of DCA from blood, relative to its formation, is
consistent with the lack of accumulation of measurable amounts of DCA in the blood following
injection of TCA (Merdink et al., 1998). Studies with a chemical Fenton reaction system and
with suspensions of rat or mouse liver microsomes incubated with TCA, detected the
dichloroacetate radical by gas chromatography (GC)/mass spectrography (MS) analysis
following trapping of an adduct between the dichloroacetate radical and phenyl-tert-butyl
nitroxide (PEN) (Merdink et al., 2000), providing evidence for the occurrence of the metabolic
conversion of TCA to DCA via reductive dehalogenation.
As shown in Figure 3-1, the reductive dechlorination of DCA to MCA has been proposed
to proceed via a proposed monochloroacetate radical, which has also been proposed to be
transformed to glyoxylic acid via oxidative dechlorination (Xu et al., 1995). Also shown in
Figure 3-1 is a proposed oxidative dechlorination pathway that transforms DCA to oxalic acid
via a proposed monochloroaldehyde intermediate (Xu et al., 1995). More direct evidence for
these pathways is not available, and enzymes that may catalyze the reactions are not
characterized. Glyoxylic acid can be metabolically transformed to glycolic acid and oxalic acid,
as well as to CO2; via mainstream carbon metabolic pathways (Figure 3-1).
Although the metabolism of TCA to DCA has been proposed as shown in Figure 3-1, the
mechanisms of dehalogenation of DCA have not been conclusively determined. The metabolism
of both TCA and DCA to similar downstream metabolites, as shown in Figure 3-1, suggests that
they may be sequential metabolites in the same pathway. For this reason, a brief summary of
DCA metabolism is included here. For a more detailed analysis of data on DCA metabolism, the
reader is referred to the IRIS ToxicologicalReview ofDichloroaceticAcid(\J.S. EPA, 2003a).
Dichloroacetic acid undergoes metabolic conversion via dechlorination and oxygenation to yield
glyoxylate, oxalate, carbon dioxide, and several glycine conjugates, including hippuric acid
(James et al., 1998; Lin et al., 1993; Evans and Stacpoole, 1982; Crabb et al., 1981). In vitro
experiments have demonstrated that conjugation with glutathione (GSH) also occurs and that this
is the primary metabolic conversion pathway for DCA in the B6C3Fi mouse, F344 rat, and
14 DRAFT - DO NOT CITE OR QUOTE
-------
human-liver cytosol (James et al., 1997; Lipscomb et al., 1995). The GSH-dependent
oxygenation of DC A to form the initial major metabolite, glyoxylic acid, is catalyzed by
glutathione-S-transferase-zeta (GST-Q (Tong et al., 1998a, b).
Studies on enzyme pathways that might play a role in the metabolism of TCA are limited
to one that evaluated the toxic effects of DC A and TCA on liver slices from male B6C3Fi mice,
as well as the metabolic capacity of the liver for these two compounds (Pravacek et al., 1996).
To evaluate cytotoxicity (as evidenced by potassium content and liver enzyme leakage), the liver
slices were exposed for up to 8 hours at concentrations of TCA ranging from 0 to 86 mM (14
mg/mL) TCA. To determine if TCA treatments can alter phase I or phase II biotransformations,
the liver slices were exposed to a low or high concentration of DCA or TCA, and the conversion
of 7-ethoxycoumarin to 7-hydroxycoumarin (a measure of phase I metabolism) and formation of
sulfate and glucuronide conjugates of hydroxycoumarin (a measure of phase II metabolism) were
assessed. TCA treatment with 1000 |ig/mL increased phase I metabolism but had no effect on
phase II metabolism at either 25 or 1000 jig/mL. Metabolism of TCA was monitored by the rate
of removal of the parent compound. The removal of TCA was not saturable at non-cytotoxic
concentrations over the range of concentrations tested (0 to 5000 |ig/mL); thus, neither the Km
(the concentration at which half-maximal metabolic rate is reached) nor Vmax (maximum
metabolic rate) was estimated. In contrast, DCA metabolism was saturable. Based on this
difference in kinetics, Pravacek et al. (1996) suggested that TCA and DCA might be metabolized
through distinct pathways, a finding consistent with other data demonstrating that the primary
metabolic pathway for DCA is NADPH and GSH-dependent (e.g., Cornett et al., 1999, 1997;
Lipscomb et al., 1995), whereas that of TCA appears to be mediated by cytochrome P450
pathways. However, it was noted that an alternative explanation for these data is that both TCA
and DCA share a metabolic pathway that has a lower capacity for DCA.
TCA may be converted to DCA in situ in the gastrointestinal tract of mice, leading to the
question of whether or not this process may influence levels of DCA in blood following
exposure of mice to TCE (which is metabolically transformed to TCA) or TCA itself
(Moghaddam et al., 1997, 1996). Under in vitro anaerobic conditions, microflora from the
cecum of B6C3Fi mice were clearly shown to convert TCA to DCA (Moghaddam et al., 1996).
In contrast, gavage administration of 1200 mg/kg TCE to control male B6C3Fi mice and to mice
whose gut was depleted of microflora by antibiotic treatment resulted in equivalent
concentrations of DCA and other TCE metabolites (TCA, chloral hydrate, and trichloroethanol)
in blood and liver (Moghaddam et al., 1997). These results suggest that metabolic formation of
DCA by gut microflora does not influence circulating levels of DCA. In this study, antibiotic
treatment resulted in large increases, compared with control values, in the total cecum content of
TCA (4.0- and 9.5-fold at 4 and 8 hours after exposure), trichloroethanol (4.4- and 1.8-fold), and
chloral hydrate (96.0- and 69.0-fold) but no significant change in total cecum content of DCA
15 DRAFT - DO NOT CITE OR QUOTE
-------
(93 and 74% of control values at 4 and 8 hours) (Moghaddam et al., 1997). The lack of a large
effect of antibiotic treatment on DCA cecum content in situ, even when TCA levels were
increased by this treatment, suggests that some other pathway may exist (other than conversion
of TCA to DCA) for the appearance of DCA in the cecum of mice exposed to TCE.
In order to determine if TCA-induced lipid peroxidation is due to the formation of radical
intermediates following dehalogenation of TCA by cytochrome P450 enzymes, Austin et al.
(1995) evaluated the effects of pretreating mice with TCA. Male B6C3Fi mice were pretreated
with 1000 mg/L (estimated to be 228 mg/kg-day by the study authors) TCA in drinking water for
14 days, then administered 300 mg/kg TCA, DCA, or an equivalent volume of distilled water
(control) by gavage as an acute challenge. Animals were sacrificed 9 hours following the acute
challenge, and lipid peroxidation, peroxisome proliferation, and TCA-induced changes in phase I
metabolism were measured. Measures of phase I metabolism included (1) changes in 12-
hydroxylation of lauric acid (an assay specific for CYP4A isoform activity, which is believed to
be associated with induction of peroxisome proliferation in rats and mice (Gibson, 1989); (2)
changes in/7-nitrophenol hydroxylation (an assay specific for CYP2E1 activity); (3) immunoblot
analysis for induction of cytochrome P450 isoforms CYP2E1, CYP4A, CYP1A1/2, CYP2B1/2,
and CYP3A1; and (4) total liver P450. Pretreatment with TCA increased 12-hydroxylation of
lauric acid, demonstrating an increase in CYP4A activity (and apparently reflecting a
peroxisome-proliferation response), whereas/7-nitrophenol hydroxylation was unchanged,
indicating no effect on CYP2E1 activity. Immunoblot analysis, a measure of the amount of a
protein, was consistent with the increase in CYP4A activity. Increased band intensities on the
immunoblot appeared to occur at locations corresponding to those that have been identified as
the CYP4A2 and CYP4A3 isoform bands. Similarly, immunoblot analysis was consistent with
the absence of an effect on CYP2E1 activity and also showed no changes in CYP1A1/2, 2B1/2,
and 3A1 protein levels. TCA pretreatment did not alter the overall amount of total liver
microsomal P450. These data demonstrate that pretreatment of mice with TCA modifies the
lipoperoxidative responses following acute challenge. The study authors suggested that this
results from activities associated with peroxisome proliferation and might be related to a shift in
the expression of P450 isoforms. The increased levels of CYP4A in TCA-pretreated mice are
consistent with results observed in other studies with other peroxisome proliferators (Okita and
Okita, 1992).
Results from another study with B6C3Fi mice indicated that pretreatment with DCA or
TCA in drinking water at concentrations of 2 g/L for 14 days had very little influence on the
metabolism or kinetics of elimination of single 100-mg/kg gavage doses of 14Ci;2-labeled TCA
(Gonzalez-Leon et al., 1999). Pretreated mice and control mice showed similar TCA blood
concentration-time profiles. No significant differences in elimination kinetic parameters, such as
volume of distribution, area-under-the-curve, elimination half time, total body clearance, and
16 DRAFT - DO NOT CITE OR QUOTE
-------
renal clearance, were found between pretreated mice and control mice. The amount of radiolabel
exhaled as CO2, taken as an index of metabolism of TCA, was also not influenced by
pretreatment. These results provide no evidence that pretreatment with TCA may induce levels
of enzymes involved in the metabolism of TCA or inhibit metabolism of TCA or DCA
(Gonzalez-Leon et al., 1999).
In summary, the available data on TCA metabolism in animal studies indicate that (1)
TCA is not as extensively metabolized as other chlorinated acids, such as DCA (Larson and
Bull, 1992); (2) TCA is metabolically converted to DCA, but levels of DCA in blood, liver, and
urine are low or not detectable, presumably due to rapid metabolic transformation of DCA into
other metabolites (Merdink et al., 2000, 1998; Yu et al., 2000; Xu et al., 1995; Larson and Bull,
1992); (3) the metabolic conversion of TCA to DCA via reductive dehalogenation is likely
catalyzed by cytochrome P450 enzymes through the dichloroacetate radical intermediate
(Merdink et al., 2000); (4) enzymes involved in TCA metabolism are poorly characterized; (5)
microbial metabolism of TCA to DCA in the gut does not appear to influence circulating levels
of DCA in the blood (Moghaddam et al., 1997, 1996); and (6) pretreatment of mice with TCA in
drinking water does not markedly influence (e.g., enhance or inhibit) the metabolism or
elimination kinetics of single challenge doses of TCA (Gonzalez-Leon et al., 1999; Austin et al.,
1995).
3.4. EXCRETION
As described previously in Section 3.2, TCA in urine has been used as a biomarker for
exposure to chlorinated solvents, which are metabolized to TCA, or exposure to disinfectant by-
products. This use is consistent with results from studies of rodents clearly showing that,
following oral or parenteral exposure to 14C-labeled TCA, TCA is principally eliminated from
the body as the parent compound in the urine and that elimination of metabolites in the urine,
elimination via the feces, and exhalation of completely metabolized TCA as CO2 represent minor
routes of elimination (Yu et al., 2000; Xu et al., 1995; Larson and Bull, 1992). For example,
during a 48-hour period following administration of single doses of radiolabeled TCA ranging
from 5 to 100 mg/kg to male F344 rats or male B6C3Fi mice, radioactivity in urine, CC>2, and
feces accounted for about 58-72%, 4-8%, and 2-4% of the administered dose, respectively
(Larson and Bull, 1992). Nonmetabolized TCA accounted for 81 to 90% of the radioactivity
detected in the urine (Larson and Bull, 1992). Similarly, within 24 hours of intravenous
injection of single doses of 1, 10, or 50 mg/kg radiolabeled TCA into male F344 rats, urinary
excretion of radioactivity accounted for 48%, 67%, and 84% of the administered doses,
respectively, whereas radioactivity in feces and CO2 in expired air accounted for 4-8% and 8-
12% of the administered doses, respectively (Yu et al., 2000).
17 DRAFT - DO NOT CITE OR QUOTE
-------
Results from studies that monitored TCA concentration in bile from isolated rat livers
perfused with TCA solution (Toxopeus and Frazier, 2002, 1998) or from dogs given intravenous
doses of TCA (Hobara et al., 1986) indicate that rates of biliary excretion of TCA are low. For
example, when isolated rat livers were perfused for 2 hours with medium containing initial TCA
concentrations of 5 or 50 jiM, excretion of TCA in bile was linear over time and cumulative
excretion was 0.1% of the total dose by the end of the experiment (Toxopeus and Frazier, 1998).
These results are consistent with the findings of low amounts of radioactivity in feces in the
studies with radiolabeled TCA (Yu et al., 2000; Xu et al., 1995; Larson and Bull, 1992).
Studies comparing the relative importance of urinary, fecal, and exhalation routes of
elimination in humans are not available.
Although elimination half-lives for TCA in urine were not reported in the available
animal toxicokinetic studies involving direct exposure to TCA (e.g., Yu et al., 2000; Schultz et
al., 1999; Xu et al., 1995; Larson and Bull, 1992), the consistent finding of more than 50% of
administered doses being excreted in the urine within 24-hours of dose administration is
consistent with the hypothesis that significant portions of absorbed TCA can be rapidly
eliminated from the body. However, the demonstrations of significant reversible binding of
TCA to plasma proteins (e.g., Lumpkin et al., 2003; Toxopeus and Frazier, 2002, 1998; Templin
et al., 1993) provide indirect evidence that bound TCA may contribute to TCA eliminated in the
urine over periods of time longer than 24 hours after administration.
Limited support for a relatively slow elimination from the human body of at least some
portion of absorbed TCA comes from a study of urinary TCA excretion in three human subjects
during a 2-week period in which they ingested their normal tap water containing TCA, followed
by a 2-week period in which tap water was replaced with bottled water containing no detectable
TCA (Froese et al., 2002). TCA ingestion from tap water averaged 5.6 ± 3.1, 41 ± 27, and 73 ±
47 |ig/day for the three subjects, reflecting substantial intrasubject and intersubject variability in
daily intakes of TCA from tap water. TCA concentration was measured in first morning urine
(FMU) samples and normalized to creatinine concentration to adjust for differences in FMU
volume. The logarithm of the creatinine-normalized TCA concentration was plotted against time
during the bottled-water period and evaluated for a linear fit. The values for elimination half-life
determined in this way ranged from 2.3 to 3.7 days. A study of urinary excretion of TCA
following inhalation exposure to perchloroethylene (of which TCA is a metabolite) reported
similar urinary elimination half-lives for TCA in humans. Volkel et al. (1998) exposed three
male and three female human subjects and three male and three female Wistar rats to 10, 20, or
40 ppm perchloroethene (tetrachloroethylene) for 6 hours via inhalation and measured
metabolites in the urine. Urine was collected at intervals before exposure, during exposure, and
up to 79 hours after beginning exposure. Urine was analyzed by GC/MS for concentrations of
DC A, TCA, and N-acetyl-S-(trichlorovinyl)-L-cysteine. TCA was the major metabolite
18 DRAFT - DO NOT CITE OR QUOTE
-------
recovered in the urine of both humans and rats. Half-lives of elimination of TCA from urine
(estimated from the time course of TCA concentrations in urine following exposure) were 45.6 ±
2.5 hours in humans and 11.0 ± 1.2 hours in rats. It is uncertain if the apparent difference in
elimination half-lives between humans and rats was due to species differences in rates of
conversion of perchloroethylene to TCA, species differences in other processes more directly
related to the appearance of TCA in the urine, or some other physiological difference between
rats and humans.
In contrast to the relatively slow urinary excretion of TCA after cessation of 2 weeks of
exposure to tap water containing TCA (Froese et al., 2002) or cessation of a 6-hour inhalation
exposure to perchloroethylene (Volkel et al., 1998), rapid urinary elimination kinetics of TCA
were indicated in humans following exposure to TCA in swimming pool water (Kim and Weisel,
1998). In this study, four subjects (two/sex) walked in the pool for one 30-minute period
(dermal exposure only) or swam (dermal exposure and presumed oral exposure from incidental
ingestion of pool water during swimming) during a separate 30-minute period. TCA levels in
the urine void collected 5 to 10 minutes after each 30-minute exposure period were elevated and
generally returned to pre-exposure levels within 3 hours after exposure (i.e., were
indistinguishable from pre-exposure levels). The relatively rapid return to pre-exposure levels
within 3 hours after cessation of exposure is consistent with fast elimination kinetics in this
study. However, as discussed in Section 3.1, there was large variability in the pre-exposure
levels of TCA in urine2, limiting the ability of this study to detect differences in pre- and
postexposure levels of TCA in urine.
In summary, results from studies with animals indicate that urinary excretion of TCA is
the principal route of elimination of TCA from the body (Yu et al., 2000; Xu et al., 1995; Larson
and Bull, 1992). Other minor routes of elimination include urinary elimination of metabolites,
exhalation of completely metabolized TCA as CC>2, and excretion of TCA in the bile or feces
(Toxopeus and Frazier, 2002, 1998; Yu et al., 2000; Xu et al., 1995; Larson and Bull, 1992;
Hobara et al., 1986). Although data on the kinetics of urinary elimination of TCA are limited,
there are estimates that the half-life of TCA in urine from human subjects may be on the order of
2-3 days (Froese et al., 2002; Volkel et al., 1998). These findings are consistent with the idea
that reversible binding of TCA to plasma proteins may influence the delivery of TCA to target
tissues and prevent faster elimination of absorbed TCA in the urine.
3.5. PHYSIOLOGICALLY BASED AND OTHER TOXICOKINETIC MODELS
Physiologically based toxicokinetic models have not been developed for TCA.
2Pre-exposure amounts of TCA in urine ranged from 155 ng to 1183 ng, whereas postexposure amounts
ranged from 294 ng to 15,990 ng (Kim and Weisel, 1998).
19 DRAFT - DO NOT CITE OR QUOTE
-------
4. HAZARD IDENTIFICATION
4.1. STUDIES IN HUMANS
4.1.1. Oral Exposure
No human epidemiology studies that evaluated TCA alone were located. Most of the
human health data for chlorinated acetic acids concern components of complex mixtures of water
disinfectant by-products. These complex mixtures of disinfectant by-products have been
associated with increased potential for bladder, rectal, and colon cancer in humans (reviewed by
Boorman et al., 1999 and Mills et al., 1998) and adverse effects on reproduction (reviewed by
Nieuwenhuijsen et al., 1999 and Mills et al., 1998).
Most of the studies of human health effects following exposure to water disinfectant by-
products have used trihalomethanes and haloacetic acids concentrations as the exposure metric
(King et al., 2005; Hinkley et al., 2005; Porter et al., 2005). For example, a population-based
case-control study conducted by Klotz and Pyrch (1999) examined the relationship among
drinking water exposure to haloacetic acids (and other disinfection by-products, including
trihalomethanes and haloacetonitriles) and neural tube defects. The study included 112 eligible
cases of neural tube defects in 1993 and 1994 that were identified through the New Jersey Birth
Defect and Fetal Death Registries. A total of 248 controls were selected randomly from all New
Jersey births with approximately 10 controls selected for each month over 24 months. A
statistically significant difference between cases and controls was observed when cases were
restricted to subjects with known residency at conception and to those with isolated neural tube
defects (i.e., cases where no other birth defects were present). A prevalence odds ratio (FOR) of
2.1 was reported (95% confidence interval 1.1-4.0) for the highest tertile (third) of
trihalomethane exposure. However, only a slight nonstatistically significant excess risk (FOR
1.2, 95% confidence interval 0.5-2.6) was found for the highest tertile (>35 ppb) of haloacetic
acids (HAAS). The specific haloacetic acids that were measured as part of the total haloacetic
acid exposure estimate were not reported. Based on the results of the study, the authors
concluded that haloacetic acid concentration did not exhibit a clear association with neural tube
defects.
No clinical studies of the effects of oral or inhalation exposure of humans to TCA were
located.
4.1.2. Dermal Exposure
Identified case reports demonstrate the corrosive potential of TCA to human skin.
Depending upon concentration and duration of contact, TCA can denature and precipitate
protein. This characteristic has been used clinically in chemical skin peeling treatments for
many years. TCA at concentrations ranging from 15 to 35% has been used in skin peeling
20 DRAFT - DO NOT CITE OR QUOTE
-------
treatments to treat conditions such as actinic damage, scars, wrinkles, and dyspigmentation
(Cotellessa et al., 2003; Lee et al., 2002; Coleman, 2001; Kang et al., 1998; Chiarello et al.,
1996; Moy et al., 1996; Tse et al., 1996; Witheiler et al., 1996; Rubin, 1995). Concentrations of
45% and higher have an increased risk of scarring. The skin peeling procedure results in a pink
erythema and swelling for the first few days posttreatment and is followed by exfoliation of the
dead skin. Histological studies (Moy et al., 1996; Tse et al., 1996) indicate that the TCA-
induced skin damage is characterized by epidermal loss, early inflammatory response, and
collagen degeneration. Adverse side effects or complications resulting from these treatments are
uncommon (Fung et al., 2002; Coleman, 2001) and are usually mild in severity (Fung et al.,
2002). Reported side effects in patients receiving the skin peel procedure have included
infection (Coleman, 2001), persistent (>1 month) erythema (Al-Waiz and Al-Sharqi, 2002;
Coleman, 2001), transient hyperpigmentation (Fung et al., 2002; Lee et al., 2002; Coleman,
2001), acne or cyst formation (Lee et al., 2002; Coleman, 2001), keratoacanthomas3 (Cox,
2003), and fine crusting (Kim et al., 2002). One case was reported where a 35% TCA solution
inadvertently entered the eye of a patient receiving a dermal peel resulting in marked
conjunctivitis and abrasions that involved 25% of the cornea (Fung et al., 2002). Complete
corneal healing was reported within 72 hours of initiation of supportive care and no lasting
effects were evident, suggesting that the response to TCA was reversible under the reported
exposure conditions.
Nunns and Mandal (1996) reported two cases of inflammation of the vulva caused by the
use of TCA in topical treatments of genital warts. The surface of each wart was coated with
TCA (concentration was not reported). Initially the patients complained of burning, which was
short-lived. After a second TCA treatment a week later, the patients reported continual soreness
or burning. On clinical examination, marked erythema and tenderness in the vulvar and
vestibular areas were noted. The symptoms in these patients lasted for 2 to 15 weeks. Wilson et
al. (2001) did not report any adverse side effects in patients (n = 95) treated for genital warts
using either TCA, cryotherapy, or electrocautery (number of patients treated with TCA was not
reported); however, the study was not specifically designed to identify adverse side effects in
treated patients.
3Keratoacanthomas are round, firm, usually flesh-colored growths that have a central crater that is scaly or
crusted.
21 DRAFT - DO NOT CITE OR QUOTE
-------
4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIOASSAYS IN
ANIMALS—ORAL AND INHALATION
4.2.1. Subchronic Studies
4.2.1.1. Subchronic Oral Studies
4.2.1.1.1. Rats. Prechronic (<90 days) oral exposure studies are summarized in Table 4-1.
Mather et al. (1990) evaluated toxicological effects in male Sprague-Dawley rats (10/dose
group) dosed with neutralized TCA in drinking water at concentrations of 0, 50, 500, or 5000
ppm (approximately 0, 4.1, 36.5, or 355 mg/kg-day) for 90 days. Animals were weighed at the
beginning of the study and at the time of necropsy. Blood was collected at the time of sacrifice
for clinical chemistry analysis (blood urea nitrogen, creatinine, glucose, alanine-amino
transferase, alkaline phosphatase (ALP), cholesterol, total protein, albumin, calcium,
phosphorus, creatinine phosphokinase, and gamma glutamyl transpeptidase). In addition, the
following immune function parameters were evaluated: antibody production, delayed
hypersensitivity, natural killer cell cytotoxicity, and production of prostaglandin (PG) E2 and
interleukin (IL)-2. Hepatic peroxisomal and microsomal enzyme induction was also assessed.
At sacrifice, a complete necropsy was performed, and the liver, kidneys, and spleen were
weighed.
Histopathological examination was conducted on the brain, heart, lungs, kidneys, spleen,
thymus, pancreas, adrenals, testes, lymph nodes, gastrointestinal tract, urinary bladder, muscle,
and skin. TCA administration did not affect body weight at any dose. At 355 mg/kg-day,
relative liver and kidney weights were significantly (p < 0.05) increased (7 % and 11%,
respectively) compared with controls. At the high dose, hepatic peroxisomal enzyme activity
was significantly (15%., p < 0.05) increased (as measured by palmitoyl-CoA oxidase [PCO]
activity). The liver, spleen, and kidney of high-dose animals were enlarged; however, no
microscopic lesions were observed at any dose. No consistent treatment-related effects were
seen on clinical chemistry or immune function parameters. EPA determined the no-observed-
adverse-effects level (NOAEL) for this study was 36.5 mg/kg-day and the lowest-observed-
adverse-effects level (LOAEL) was 355 mg/kg-day, based on increased liver size and weight and
peroxisome proliferation, as well as statistically significantly increased kidney weight and size
and increased spleen size.
In a Subchronic study Bhat et al. (1991) administered 1A of an LD50 dose of TCA, DCA,
or MCA in drinking water to male Sprague-Dawley rats (five/dose) for 90 days. Based on the
reported LD50 of 3300 mg/kg for TCA, 1A of this value would correspond to an administered
daily dose of approximately 825 mg/kg-day. Body weights were monitored throughout the
study. The animals were sacrificed after 90 days of exposure, and the liver, lung, heart, spleen,
thymus, kidney, testes, and pancreas were removed and weighed. These organs and the brain
were microscopically examined. Liver sections were also stained for collagen deposition. No
22 DRAFT - DO NOT CITE OR QUOTE
-------
other toxicity parameters were evaluated. TCA exposure resulted in a significant depression
(17%, p < 0.0001) of body weight gain throughout the exposure period. lexicologically
significant changes in liver weight were not observed. Exposure to TCA induced minimal to
moderate collagen deposition (an indication of liver injury) in portal triads and large central
veins in 4/5 animals (minimal collagen deposition was observed in 1/5 controls). Morphological
changes in the liver included portal vein dilation/extension of minimal to moderate severity in
5/5 TCA-treated animals. Perivascular inflammation of the lungs occurred at unspecified
incidences. EPA determined the only dose tested in this study, 825 mg/kg-day, was high and
may be more likely a frank effect level rather than a LOAEL for significantly reduced body
weight gain.
In a 50-day drinking water study (Celik, 2007), 4 months old female Sprague Dawley rats
were administered 2000 ppm (300 mg/kg-day, assuming a default water intake of 0.15 L/kg-day)
TCA to the treatment group (numbers unknown), while the control group received natural spring
water. At the end of the study, blood samples were collected. Animals were sacrificed, and
brain, liver, kidney samples were obtained. Serum marker enzymes [aspartate aminotransferase
(AST), alanine aminotransferase (ALT), creatine phosphokinase (CPK), acid phosphatase
(ACP), alkaline phosphatase (ALP), and lactate dehydrogenase (LDH)]; erythrocytes and tissue
antioxidant defense systems [GSH, glutathione reductase (GR), superoxide dismutase (SOD),
glutathione-S-transferase (GST) catalase (CAT)] and malondialdehyde (MDA) (product of lipid
peroxidation) were measured.
TCA significantly increased serum AST, ALT, CPK, and ACP activity (p < 0.05) in
treated rats. A slight but insignificant increase in MDA was found in the erythrocytes and liver.
Antioxidant enzymes SOD and CAT were significantly increased in the brain, liver, and kidney.
However, no changes in GSH, GR and GST activities were found in all tissues. Celik (2007)
concluded elevated serum marker enzymes probably resulted from damage to liver cells by TCA
and subsequent leakage of the enzymes into plasma, and that the increases in SOD and CAT
activities in the tissues after TCA treatment were probably due to increased generation of ROS.
23 DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-1. Summary of pre-chronic studies evaluating effects of TCA after oral administration in rats and mice
Reference
Species
Exposure
route
Exposure
duration
Doses
evaluated
Effects3
NOAEL
(mg/kg-day)
LOAEL
(mg/kg-day)
Comments
Rats
Mather et al.
(1990)
Bhat et al.
(1991)
Acharya et
al. (1997,
1995)
Davis (1990)
Sprague-
Dawley
rats
(males,
10/dose)
Sprague-
Dawley
rats
(males,
5/group)
Wistar rats
(males, 5-
6/dose)
Sprague-
Dawley
rats (6/sex
/dose)
Oral,
drinking
water
Oral,
drinking
water
Oral,
drinking
water
(A) Oral,
drinking
water
(B) Oral,
gavage
90 Days
90 Days
10 Weeks
(A) 14 Days
(B) 3 doses
over 24 h
0,4.1, 36.5, or
355 mg/kg-day
0 or 825 mg/kg-
day
0 or 3. 8 mg/kg-
day
(A) 5.2-309
mg/kg-day
(B)0, 0.15, or
0.4 mg/kg
Increased absolute spleen weight;
increased relative liver and kidney
weights; increased liver, kidney
and spleen sizes; peroxisome
proliferation
Decreased body weight gain;
minor changes in liver
morphology; collagen deposition;
perivascular inflammation of the
lungs
Decreased terminal body weight;
liver and kidney histopathological
changes; increased glycogen;
changes in liver lipid and
carbohydrate homeostasis;
decreased kidney GSH
(A) Limited endpoints were
monitored. No effects were
observed on weight gain, urine
volume and osmolality, plasma
glucose and liver lactate levels.
(B) Decreased plasma and liver
lactate levels
36.5
Not
determined
Not
determined
(A) Not
determined
(B) Not
determined
355
825
3.8
(A) Not
determined
(B)0.15
l/4oftheLD50
(3300 mg/kg) was
administered daily.
Doses were estimated
based on default
drinking water intake
values for rats. 3.8
mg/kg-day is judged as
an equivocal LOAEL
because the observed
severity of the observed
liver changes was
considered minimal.
(B) At 0.15 mg/kg,
plasma glucose levels
were also decreased in
females. These results
are consistent with
effects on intermediary
carbohydrate
metabolism. Similar
effects were not
observed in the 14 days
study.
24
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-1. Summary of pre-chronic studies evaluating effects of TCA after oral administration in rats and mice
Reference
DeAngelo et
al. (1989)
Goldsworthy
and Popp
(1987)
Celik (2007)
Species
Sprague-
Dawley,
F344, and
Osborne-
Mendel
rats
(males,
6/group
/strain)
F344 rats
(males,
6/group)
Sprague-
Dawley
rats
(female)
Exposure
route
Oral,
drinking
water
Oral,
gavage
Oral,
drinking
water
Exposure
duration
14 Days
10 Days
50 days
Doses
evaluated
0, 212, 327, or
719 mg/kg-day
0 or 500 mg/kg
in corn oil
0, 300 mg/kg-
day
Effects3
Hepatic peroxisome proliferation
induction (Osborne-Mendel and
F344 rats)
Hepatic and renal peroxisome
proliferation, increased relative
liver weight
Increase in serum AST, ALT,
CPK, and ACP activities; increase
in SOD and CAT activities in
brain, liver, and kidney tissues.
NOAEL
(mg/kg-day)
327
Not
determined
Not
determined
LOAEL
(mg/kg-day)
719
500
300
Comments
Peroxisome
proliferation was
observed only in
Osborne-Mendel and
F344 rats. These results
suggest that Sprague-
Dawley rats were the
least sensitive of the
three strains evaluated
to peroxisome
proliferation.
The cyanide-insensitive
PCOb activity assay was
used to measure the
peroxisome proliferative
response.
Mice
Kato-
Weinstein et
al. (2001)
Parrish et al.
(1996)
B6C3FJ
mice
(males,
5/dose)
B6C3FJ
mice
(males,
6/group)
Oral,
drinking
water
Oral,
drinking
water
(A) 4 or 8
Weeks
(B)12
Weeks
3 or 10
Weeks
(A) 750 mg/kg-
day
(B) 0, 75, 250,
or 750 mg/kg-
day
0, 25, 125, 500
mg/kg-day
Increased absolute and relative
liver weights; decreased liver
glycogen content
Increased absolute and relative
liver weights; peroxisome
proliferation (increased PCOb
activity and increased 12-
hydroxylation of lauric acid)
Not
determined
25
75
125
Doses were estimated
based on default
drinking water intake
values for male B6C3Fi
mice.
Doses were estimated
based on default
drinking water intake
values for male B6C3F!
mice; results were
similar for the 3- and
10-week evaluations;
8-OHdGc levels were
not affected by TCA.
25
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-1. Summary of pre-chronic studies evaluating effects of TCA after oral administration in rats and mice
Reference
Austin et al.
(1995)
DeAngelo et
al. (1989)
Sanchez and
Bull (1990)
Dees and
Travis
(1994)
Goldsworthy
and Popp
(1987)
Species
B6C3FJ
mice
(males,
6/group)
B6C3Fb
C3H,
Swiss-
Webster,
C57BL/6
mice
(n=6)
B6C3FJ
mice
(males,
12/group)
B6C3FJ
mice
(5/sex
/dose)
B6C3FJ
mice
(males,
7-8/group)
Exposure
route
(A) Oral,
drinking
water
(B) Oral,
gavage
Oral,
drinking
water
Oral,
drinking
water
Oral,
gavage
Oral,
gavage
Exposure
duration
(A) 14 Days
(B) Single
dose
14 Days
14 Days
11 Days
10 Days
Doses
evaluated
(A) 0 or
250 mg/kg-day
(B) 0 or
300 mg/kg
0, 261, or
442 mg/kg-day
0, 75, 250, or
500 mg/kg-day
0, 100, 250,
500, or
1000 mg/kg-day
0 or 500 mg/kg
in corn oil
Effects3
(A) Increased relative liver weight
(B) Decreased TBARSd; Increased
PCOb, catalase, and CYP4A
activities
Increased relative liver weight,
peroxisome proliferation (PCOb
activity)
Increased liver weight; hepatocyte
proliferation (DNA labeling)
Increased absolute and relative
liver weight; increased hepatocyte
labeling
Induction of hepatic and renal
peroxisome proliferation;
increased relative liver weight
NOAEL
(mg/kg-day)
Not
determined
Not
determined
75
Not
determined
Not
determined
LOAEL
(mg/kg-day)
250
261
250
100
500
Comments
(A) Doses were
estimated based on
default drinking water
intake values for male
B6C3FJ mice.
(B) Acute
administration occurred
after a 14-day
pretreatment period.
C57BL/6 mice were
more sensitive than the
other strains to
peroxisome
proliferation.
Doses were estimated
based on default
drinking water intake
values for male B6C3Fi
mice.
At 500 mg/kg-day, there
was a slightly increased
hepatocyte diameter
because of increased
glycogen deposition.
The cyanide-insensitive
PCOb activity assay was
used to measure the
proliferative response.
Liverbody weight ratios
were also significantly
increased in both.
26
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-1. Summary of pre-chronic studies evaluating effects of TCA after oral administration in rats and mice
Reference
Austin et al.
(1996)
Laughter et
al. (2004)
Species
B6C3FJ
mice
(males,
6/group)
SV129
wild-type
mice;
PPARea-
null mice
(males,
3-5/group)
Exposure
route
Oral,
gavage
Drinking
water
Exposure
duration
Single dose
7 days
Doses
evaluated
0, 30, 100, or
300 mg/kg
0,57.5, 115,
230, or 460
mg/kg-day
Effects3
Oxidative stress (increased
8-OHdGc levels)
Induction of markers of
peroxisome proliferation in wild-
type but not PPARa-null mice at
2.0 g/L; induction of CYP4A at
1.0 g/L. Wild-type mice receiving
high dose exhibited centrilobular
hepatocyte hypertrophy
NOAEL
(mg/kg-day)
Not reported
115
LOAEL
(mg/kg-day)
Not reported
230
Comments
Doses were estimated
based on default
drinking water intake
values for male B6C3F!
mice; 8-OHdGc levels at
30 or 100 mg/kg were
not reported.
No reported or default
data were available for
estimation of average
daily doses.
aThe effects listed in this table may have occurred either at the LOAEL or at higher doses.
bPalmitoyl-CoA oxidase.
°8-Oxo-2'-deoxyguanosine.
dThiobarbituric acid-reactive substances.
ePeroxisome proliferator activated receptor.
Source: Adapted from U.S. EPA (2005c).
27
DRAFT - DO NOT CITE OR QUOTE
-------
Acharya et al. (1995) evaluated liver and kidney toxicity of TCA as part of a study on the
interactive toxicity of tertiary butyl alcohol and TCA. Young male Wistar rats (50 days old)
(five-six/dose) were exposed to water containing 0 or 25 ppm or approximately 0 or 3.8 mg/kg-
day, assuming a default water intake of 0.15 L/kg-day (U.S. EPA, 1988) TCA for 10 weeks.
Animals were weighed weekly during treatment, and food and water consumption were recorded
daily. Blood was taken from animals after the 10-week exposure, and the following parameters
were evaluated: succinate dehydrogenase (SuDH), ALP, acid phosphatase (ACP), aspartate
aminotransferase (AST), aniline aminotransferase (ALT), and serum triglyceride, cholesterol,
and glucose levels. In addition, glycogen, triglyceride, cholesterol, GSH, lipid peroxidation, and
diene conjugation were determined in liver homogenates. Microscopic examination of tissues
was not performed.
In animals treated only with TCA, terminal body weight was decreased by approximately
17% in the absence of changes in food consumption (data not shown). Little, if any, TCA-
induced liver toxicity was observed. Relative liver weight did not differ significantly in TCA-
treated animals. No significant changes were detected in AST, ALT, ALP, or ACP. In contrast
to the serum markers of liver necrosis, indicators of lipid and carbohydrate homeostasis were
affected by TCA. SuDH activity was increased by roughly 30% compared with controls. Liver
triglyceride and cholesterol levels were significantly decreased, while liver-glycogen levels were
dramatically increased (roughly eightfold). Serum cholesterol levels were also increased
approximately twofold. The study authors suggested that this profile of carbohydrate and lipid
changes was consistent with the onset of hepatomegaly, which would increase the energy
demands of the liver and activate SuDH, leading to increased oxidative phosphorylation and
mobilization of lipids (decreased liver triglyceride and cholesterol). There was little evidence
for induction of oxidative stress in the liver. Kidney, but not liver, GSH levels were decreased to
approximately 66% of control values and no increase in lipid peroxidation was observed in the
liver.
In a follow-up study using the same exposure protocol (Acharya et al., 1997),
histopathological changes in the liver and kidney were evaluated. The study authors noted that
minimal hepatic alterations were observed in the TCA treatment group, indicating that the
3.8 mg/kg dose was marginally toxic. Liver histopathological changes that were noted included
centrilobular necrosis, hepatocyte vacuolation, loss of hepatic architecture, and hypertrophy of
periportal region. Incidence and severity data were not reported for these lesions. Hypertrophy
of the periportal region observed in the latter study may have accounted for the observed
marginal increase in liver weight in the former study. The magnitude of the severity of these
changes was reportedly small (the magnitude of the response could not be accurately quantified
from the reported figures) and is consistent with the absence of effects on serum-liver enzymes
in their earlier study.
28 DRAFT - DO NOT CITE OR QUOTE
-------
Histopathological changes were also noted in the kidneys of TCA-treated animals and
included degeneration of renal tubules with syncytial arrangement of the nucleus in the epithelial
cells, degeneration of the basement membrane of Bowman's capsule, diffused glomeruli,
vacuolation of glomeruli, and renal tubular proliferation in certain areas (incidence and severity
not reported). Based on the liver and kidney histopathological changes at the single dose tested,
the study authors indicated that TCA is a liver and kidney toxicant.
Taken together, the two studies by Acharya et al. (1997, 1995) suggest that the single
dose tested, 3.8 mg/kg-day, is an apparent LOAEL. However, a number of questions regarding
these studies preclude a definitive determination of the LOAEL. First, Acharya et al. (1995)
noted a lack of increase in liver enzyme activity. Although liver histopathological changes were
observed, they were described as "only marginal" by the authors. The authors did not discuss
the severity of the histopathological changes in relation to untreated controls, and no incidence
data were provided. Therefore, it is not clear whether the effects observed at the single TCA-
only dose that was evaluated were adverse. Due to this uncertainty, EPA determined 3.8 mg/kg-
day could be best described as an equivocal LOAEL. It should be noted that Wistar rats were
actually more sensitive than mice to increases in cyanide insensitive acyl-CoA oxidase (AGO)
activity by TCA (Elcombe, 1985).
Davis (1990) investigated the effects of TCA on weight gain, urine volume and
osmolality, and plasma glucose and liver lactate levels in Sprague-Dawley rats in a 14-day study.
Groups of rats (six animals/sex and dose group) received TCA in drinking water at
concentrations of 0, 0.04, 0.16, 0.63, or 2.38 g/L (equivalent to approximate dose levels of 0, 5.2,
20.8, 81.9, or 309 mg/kg-day, based on a water consumption factor of 0.13 L/kg-day for
Sprague-Dawley rats from U.S. EPA, 1988). High-dose rats consumed less food and water and
lost weight during the first few days of exposure. Weight gain was similar to controls at
subsequent time points. Urine volume and osmolality were not affected except for a temporary
lesser increase in osmolality to match decrease in urine volume on day 7 in high-dose females.
No clearly adverse effects or dose-related trends were demonstrated. No effects on plasma
glucose or liver lactate levels occurred after the 14-day exposure period. EPA has not
determined the NOAEL for Davis (1990) since limited endpoints were monitored in this study.
Additional information collected by Davis (1990) suggests that TCA may have transient
effects on plasma glucose and plasma and liver lactate levels in rats. Three gavage doses of
0.92 |imol/kg or 2.45 |imol/kg TCA (approximately 0.15 and 0.40 mg/kg, respectively) were
administered to Sprague-Dawley rats (five/sex/dose) over 24 hours. The rats were killed 3 hours
after the last dose. Significantly reduced plasma (45%) and liver lactate (48%) levels were
observed in females. Plasma lactate level was significantly reduced in males (30%) at the high
dose. Plasma glucose level was significantly reduced (25%) in females given the high dose.
These data suggest that TCA can affect intermediary metabolism, although the absence of effects
29 DRAFT - DO NOT CITE OR QUOTE
-------
on plasma lactate or glucose levels in the 14-day study conducted by Davis (1990) suggests that
the effect may be transient.
The ability of TCA to induce peroxisome proliferation and oxidative stress has been
evaluated in a number of studies. Goldsworthy and Popp (1987) investigated the ability of TCA
to induce hepatic and renal peroxisome proliferation (as assessed by the cyanide-insensitive PCO
activity assay) in adult male F344 rats (five-six/dose) given 500 mg/kg-day TCA in corn oil via
oral gavage for 10 consecutive days. Toxicological parameters other than liver and kidney
weights were not evaluated. Hepatic peroxisomal enzyme activity increased significantly (p <
0.05) in rats receiving TCA, resulting in levels of enzyme activity approximately 2.8-fold greater
than controls. Liver-to-body weight ratios were also significantly (41%, p < 0.05) increased
relative to controls. Body weight gain was not changed. Renal peroxisomal enzyme activity
was significantly (p < 0.05) increased by approximately 1.8-fold over controls in rats. Kidney
weights were not affected by treatment. This study demonstrated that TCA treatment induced
peroxisome proliferation in the livers and kidneys of male F344 rats.
DeAngelo et al. (1989) conducted a series of experiments in three strains of rats and four
strains of mice to determine relative species and strain sensitivities to the induction of hepatic
peroxisome proliferation by chloroacetic acids (results of the mouse studies are described later in
this section). Male Sprague-Dawley, F344, and Osborne-Mendel rats (six/dose/strain) received
drinking water supplemented with 0, 6, 12, or 31 mM (approximately 0, 212, 327, or 719 mg/kg-
day as calculated by the study authors) for 14 days. Hepatic PCO activity was used to assess
peroxisome proliferation in all three strains. Carnitine acetyl-CoA transferase (CACT) activity
(another peroxisomal enzyme marker) was determined only in Sprague-Dawley rats, and
induction of the peroxisome proliferation-associated (PP-A) protein was evaluated in high-dose
Sprague-Dawley rats. Morphometric analysis of peroxisome proliferation was conducted by
electron microscopy on liver sections from two high-dose Sprague-Dawley rats. No other
toxicological parameters were evaluated.
TCA treatment did not significantly affect body weights or liver-to-body weight ratios in
either Osborne-Mendel or F344 rats. The final mean body weight of Sprague-Dawley rats was
significantly reduced at 719 mg/kg-day when compared with controls (16% reduction). No
effects were seen on liver-to-body weight ratios in any of the strains. PCO activity was elevated
in Osborne-Mendel rats by 2.4-fold and in F344 rats by 1.6-fold over control values at the high
dose. In contrast, PCO activity was not affected in treated Sprague-Dawley rats at any dose.
CACT activity, however, was increased by 321% above the controls in Sprague-Dawley rats at
the high dose (significant increases were not observed at lower doses), but the volume fraction of
cytoplasm from hepatic tissue occupied by peroxisomes was decreased to less than half that seen
in controls in this strain. The reason for this paradoxical effect was not addressed. Taken
together, these observations suggest that Sprague-Dawley rats are not sensitive to peroxisome
30 DRAFT - DO NOT CITE OR QUOTE
-------
proliferation in response to TCA exposure under the experimental conditions tested. EPA
determined the NOAEL and LOAEL for peroxisome proliferation were 327 mg/kg-day and 719
mg/kg-day, respectively, in both Osborne-Mendel and F344 rats.
Collectively, the data in rats suggest that short-term exposure to TCA primarily affects
the liver, although effects on the kidneys and lungs have also been observed. Liver effects have
included increased size and weight, collagen deposition, indications of altered lipid and
carbohydrate metabolism, and peroxisome proliferation. Effects were observed at doses as low
as 0.45 mg/kg-day(decreased liver and plasma lactate levels) (Davis, 1990). Strain differences
were also evident. An equivocal LOAEL of 3.8 mg/kg-day (liver and kidney pathology) was
identified in 10-week studies in Wistar rats (Acharya et al., 1997, 1995). In a 90-day study
(Mather et al., 1990), a much higher LOAEL of 355 mg/kg-day (increase in liver and kidney
weight and peroxisome proliferation) was identified in Sprague-Dawley rats.
4.2.1.1.2. Mice. Prechronic studies in mice are summarized in Table 4-1. The available
prechronic studies in mice have primarily been conducted to evaluate TCA-induced effects on
the liver and the mode of action (MOA) underlying hepatic effects. No prechronic toxicity
studies that evaluated a complete suite of toxicological parameters (e.g., body weight, clinical
pathology, gross pathology, and microscopic pathology of a comprehensive set of tissues) in
mice were located.
Goldsworthy and Popp (1987) investigated the ability of TCA to induce hepatic and renal
peroxisome proliferation as assessed by the cyanide-insensitive PCO activity assay in adult male
B6C3Fi (7-8/dose) mice given 0 or 500 mg/kg in corn oil for 10 days via oral gavage. Relative
liver and kidney weight were the only other toxicological parameters evaluated. Hepatic
peroxisomal enzyme activity increased significantly (p < 0.05) in mice receiving TCA, resulting
in levels of enzyme activity that were 280% of the controls. Renal peroxisomal enzyme activity
was significantly (p < 0.05) increased to 305% of control levels in mice. Liver-to-body weight
ratios were also significantly (p < 0.05, 40%) increased relative to controls.
DeAngelo et al. (1989) investigated the effects of TCA exposure on hepatic peroxisome
proliferation using four strains of male mice (B6C3Fi, C3H, Swiss-Webster, and C57BL/6).
Groups of six mice per strain and dose were exposed to TCA in drinking water that contained 0,
12, or 31 mM (approximately 0, 261, or 442 mg/kg-day) TCA for 14 days. No effects were seen
on body weight, but liver-to-body weight ratios were significantly increased at both dosages in
all four strains. The activity of PCO was elevated in all four strains for all TCA dose groups.
PCO levels were 276%, 325%, and 456% above controls at 12 mM and 648%, 644%, and 678%
above controls at 31 mM for Swiss Webster, C3H, and B6C3Fi mice, respectively. PCO activity
in C57BL/6 mice was increased by 2100% and 2500% above control levels at the high and low
doses for TCA, respectively, indicating that this is a particularly sensitive strain of mouse.
31 DRAFT - DO NOT CITE OR QUOTE
-------
In another phase of this study, catalase activity was increased by 461% above controls in
B6C3Fi mice at the high dose, with accompanying increases in the level of PP-A protein and
number and size of peroxisomes in liver cytoplasm. The results indicated that mice, in general,
are more sensitive than rats to the effects of TCA on peroxisome proliferation, as indicated by
PCO activity. As described previously, levels of PCO activity in F344 and Osborne-Mendel rats
were increased only by approximately 63% and 138%, respectively, at an approximate TCA
dosage level of 719 mg/kg-day, and no significant effects on PCO activity occurred at 327
mg/kg-day in any strain. No effects were seen on this parameter in Sprague-Dawley rats at any
dose (DeAngelo et al., 1989).
Miyagawa et al. (1995) conducted acute toxicity testing for dose-range finding as part of
a study on a hepatocyte replicative DNA synthesis test for 41 putative Ames-negative mouse
hepatocarcinogens. Groups of male B6C3Fi mice (four or five/dose) were administered a single
oral-gavage dose of TCA to determine the maximum tolerated dose (MTD), which was set at
about half the LD50. The MTD for TCA was estimated to be 500 mg/kg.
Several studies have evaluated the ability of TCA to induce oxidative stress in the liver of
treated mice. These studies range from single-dose studies to studies of 10 weeks in duration. In
an acute study by Austin et al. (1996), male B6C3Fi mice (six/group) were treated with a single
oral dose of TCA (0, 30, 100, or 300 mg/kg). Mice were deprived of food for 3 hours prior to
dosing. Liver nuclear DNA was extracted to assess increases in 8-oxo-2'-deoxyguanosine
(8-OHdG) adducts, a measure of oxidative damage to DNA resulting from oxidative stress.
TCA has been shown to induce lipid peroxidation in rodents (Larson and Bull, 1992) and
compounds that produce oxidative stress also increase 8-OHdG, which is capable of inducing
DNA base transversions that might be involved in the carcinogenic process (Chang et al., 1992).
A significant increase in 8-OHdG in nuclear DNA in the liver was observed in the 300 mg/kg
group at 8-10 hours post-dosing. The maximum 8-OHdG level was observed at 8 hours and was
an increase of approximately 33% (estimated from Chang et al., 1992, Figure 3) over controls.
The 8-OHdG levels in groups dosed with 30 or 100 mg/kg were not reported.
Austin et al. (1996) contrasted the profile of oxidative DNA damage induced by TCA in
this study with TCA-induced levels of thiobarbituric acid-reactive substances (TEARS, an
indicator of lipid peroxidation) reported in a previous study (Larson and Bull, 1992). In the
earlier study, Larson and Bull (1992) reported a maximum concentration of TEARS at 9 hours
post-dosing in the livers of mice given 2000 mg/kg TCA. The Larson and Bull (1992) study also
reported that a single oral dose of TCA-induced TEARS levels 9 hours after dosing by 1.15-,
1.7-, 2-, and 2.7-fold over controls at doses of 100, 300, 1000, and 2000 mg/kg, respectively.
Austin et al. (1996) suggested that the ability of haloacetates to increase both TEARS and 8-
OHdG levels indicates that oxidative stress may be related to their hepatocarcinogenicity. The
concordance between TEARS and 8-OHdG levels also suggested a common mechanism of
32 DRAFT - DO NOT CITE OR QUOTE
-------
induction of these two markers. Neither a NOAEL nor a LOAEL were identified for Austin et
al. (1996) because no standard measures of liver or systemic toxicity were reported. A limitation
of this study is that a high single dose was used.
Parrish et al. (1996) evaluated the ability of haloacetic acids to induce oxidative DNA
damage in the livers of mice. Male B6C3Fi mice (six/group) were exposed to 0, 100, 500, or
2000 mg/L TCA in drinking water for either 3 or 10 weeks. The study authors did not estimate
the average daily doses resulting from exposure to these concentrations. Based on default water-
intake values of 0.25 L/kg-day for male B6C3Fi mice (U.S. EPA, 1988), the corresponding
doses were approximately 0, 25, 125, and 500 mg/kg-day. Body weight and liver weight were
evaluated. Several indicators for peroxisome proliferation were measured, including cyanide-
insensitive PCO activity and increased 12-hydroxylation of lauric acid, which have been
identified in other studies as "classical" responses resulting from exposure to compounds that are
known peroxisome proliferators (Parrish et al., 1996). The level of 8-OHdG in liver nuclear
DNA was also evaluated as an indicator of oxidative DNA damage. No histopathological
examination or standard clinical chemistry measurements were performed.
No differences in body weight were observed for any of the treatments (Parrish et al.,
1996). The absolute liver weight was increased at the high dose, and relative liver weight was
increased at the mid and high dose (by 13% and 33%, respectively) following exposure for 3
weeks (p < 0.05). After 10 weeks of exposure, the absolute liver weights were significantly
increased at the mid dose and higher, and there were statistically significant increases in relative
liver weight beginning at the mid dose (increases of 12% and 35%, respectively). Significant
dose-related increments in cyanide-insensitive PCO activity were observed in mice treated at all
TCA doses for 3 weeks (indicating peroxisome proliferative changes before liver weight
changes); these increases persisted when treatment was extended to 10 weeks. Significantly
increased 12-hydroxylation of lauric acid was also observed after 3 and 10 weeks of TCA
exposure (the response was statistically significant at the high dose), whereas 8-OHdG levels
were unchanged at both time periods. Thus, oxidative damage to genomic DNA as measured by
8-OHdG adducts did not occur with prolonged TCA treatment, even though peroxisome
proliferation was induced, as indicated by increased PCO activity and 12-hydroxylation of lauric
acid. The authors concluded that the lack of an increase in 8-OHdG indicated that this type of
DNA base damage was not likely to be associated with the initiation of cancer by TCA; either
the formation of these adducts was inhibited or their repair was enhanced with continued TCA
treatment. The increased relative liver weight of approximately 10% at the mid dose (125
mg/kg-day) was accompanied by a significant increase in PCO activity but not 12-hydroxylation
of lauric acid. The magnitude of these changes at the high dose was much greater, with relative
liver weight increasing roughly 35% over controls and significant increases in both indicators of
peroxisome proliferation. Microscopic examination of the liver was not conducted in these
33 DRAFT - DO NOT CITE OR QUOTE
-------
experiments. However, based on significant increases in relative liver weight (p<0.05)
accompanied by markers of peroxisome proliferation, EPA considered the mid dose of 125
mg/kg-day a LOAEL. The low dose of 25 mg/kg-day is considered a NOAEL.
Austin et al. (1995) tested whether TCA pretreatment would alter the lipid-peroxidation
response of a subsequent acute dose of TCA. They also explored the relationship between TCA-
induced lipid peroxidation and the ability of TCA to induce markers of peroxisome proliferation
or cytochrome P450s following short-term treatments. Male B6C3Fi mice (18/group) were
treated with 0 or 1000 mg/L TCA for 14 days, which corresponds to estimated average daily
doses of approximately 0 or 250 mg/kg-day based on the default water intake of 0.25 L/kg-day
for male B6C3Fi mice (U.S. EPA, 1988). For the lipid peroxidation experiments, the water or
TCA pretreated mice were divided into six/group and administered 300 mg/kg of TCA, DC A, or
an equivalent volume of distilled water by gavage (control) as an acute challenge. Animals were
sacrificed 9 hours after the acute challenge. The livers were removed and homogenized, and the
following endpoints were evaluated: (1) lipoperoxidative response, as measured by the
production of TEARS; (2) indicators of peroxisome proliferation, as measured by increased PCO
activity, increased catalase activity, and changes in microsomal 12-hydroxylation of lauric acid
(an indicator for the activity of cytochrome P450 4A (CYP4A); (3) hydroxylation of
/>-nitrophenol (as an index of CYP2E1 activity); and (4) protein levels for a panel of cytochrome
P450s, as described in Section 3.3. In addition to measurements following 14 days of treatment,
TEARS levels were also measured for the acute-challenge experiments.
No changes in water consumption or body weight were observed, although relative liver
weight was increased by 29% after 14 days of TCA treatment. TCA-treated mice had a lower
mean TEARS level as compared with controls, but the difference was not statistically
significant. In the acute challenge experiment, TCA-pretreated mice exhibited a significant
decrement in TEARS in liver homogenates, following acute dosing with either TCA or DCA, as
compared with animals that received the same acute challenge but had not been pretreated. In
contrast to the decrease in TEARS induced by TCA pretreatment, PCO, catalase, and CYP4A
activities were increased by 4.5-fold, 1.7-fold, and 2-fold, respectively, with TCA pretreatment.
The TCA pretreated group showed no increase in CYP2E1 activity and no changes in the overall
amount of total liver microsomal P450. These data demonstrate that treatment of mice with TCA
reduced lipoperoxidative responses but increased other markers that have been associated with
peroxisome proliferation. The study authors suggested that reduction in the TEARS response
observed in TCA-pretreated animals resulted from activities associated with peroxisome
proliferation and might be related to a shift in the expression of P450 isoforms, such as CYP4A.
The increased levels of CYP4A in TCA-pretreated mice are consistent with results observed in
other studies with other peroxisome proliferators (Gibson, 1989). Peroxisomes were not
measured directly. However, based on significant increases in relative liver weight and several
34 DRAFT - DO NOT CITE OR QUOTE
-------
indirect markers of peroxisome proliferation (PCO, catalase, and CYP4A activities), the single
dose tested of 250 mg/kg-day is considered a LOAEL for this study.
In summary, the ability of TCA to induce oxidative-stress responses such as lipid
peroxidation and oxidative DNA damage, and the relationship between these responses and
indicators of peroxisome proliferation or altered cytochrome P450 activities has been tested in a
series of studies following acute or short-term TCA dosing in mice (Austin et al., 1996; Parrish
et al., 1996; Austin et al., 1995; Larson and Bull, 1992). TCA induces both lipid peroxidation
(TEARS) and oxidative DNA damage (8-OHdG) following administration of single oral doses.
However, these increases appear transient, since neither lipid peroxidation (Austin et al., 1995)
nor 8-OHdG formation (Parrish et al., 1996) were increased in multiple-dose studies. In
contrast, responses associated with peroxisome proliferation are induced following TCA dosing
for up to 10 weeks (Parrish et al., 1996; Austin et al., 1995). These results suggest that
peroxisome proliferation is more likely than oxidative stress responses to be associated with liver
toxicity observed in prechronic studies.
Sanchez and Bull (1990) investigated the effects of trichloroacetate on reparative
hyperplasia in the livers of male B6C3Fi mice (12 animals/dose group). TCA was administered
in the drinking water for 14 days at concentrations of 0, 300, 1000, or 2000 mg/L, which
correspond to estimated average daily doses of approximately 0, 75, 250, or 500 mg/kg-day
based on the default water intake of 0.25 L/kg-day for male B6C3Fi mice (U.S. EPA, 1988).
Food and water consumption were recorded during the exposure period. After 14 days of
exposure, animals were sacrificed; their livers and kidneys were removed and weighed,
hepatocyte diameter was determined, and cell proliferation in the liver was assessed using
[3H]thymidine labeling after 2-day (n = 4), 5-day (n = 4), or 14-day (n = 12) treatments. Liver
weight was significantly (p < 0.05) increased compared with controls at 250 (23%) and 500
(38%) mg/kg-day. Hepatocyte diameter was significantly (p < 0.05, 13%) increased at 500
mg/kg-day. Period acid-Schiff s reagent (PAS)-positive material (glycogen) was confined to
periportal areas. Necrosis was evident in 2 of 20 sections examined from high-dose animals, but
it was not possible to determine whether this low frequency was treatment-related. A significant
(p < 0.05) increase in incorporation of [3H]thymidine into hepatic DNA was seen at 5 and 14
days at the highest dose. However, this effect was not correlated with replicative synthesis of
DNA as measured autoradiographically. These data suggest that other processes must account
for the increased incorporation of radiolabel. The study authors suggested increased DNA repair
synthesis or alterations in thymidine pool size as possible explanations for the observed results
but noted that the mechanism for [3H]thymidine could not be determined based on the available
data. EPA determined the LOAEL for this study to be 250 mg/kg-day for increased liver weight,
and the NOAEL to be 75 mg/kg-day.
3 5 DRAFT - DO NOT CITE OR QUOTE
-------
Dees and Travis (1994) evaluated the ability of TCA to induce DNA synthesis in the
livers of male and female B6C3Fi mice. Mice (five/sex/dose) were given 11 daily gavage doses
of 0, 100, 250, 500, or 1000 mg/kg-day TCA in corn oil. Twenty-four hours after the last dose,
[3H]thymidine was administered intraperitoneally (i.p.). Six hours later, the mice were sacrificed
and their livers were removed. Liver samples were subsequently fixed for histopathological
examination and evaluation of DNA synthesis (based on incorporation of the radiolabeled
thymidine). Final mean body weight and liver weight were also determined. There were no
clinical signs of toxicity at the time of sacrifice, and no significant effects on body weight or
body-weight gain. Absolute and relative liver weights were statistically significantly increased
in all male and female treatment groups when compared with controls. In males, the relative
liver weight was increased by 15% (at 500 mg/kg-day) to 28% (at 250 mg/kg-day), and the
increases were not dose related. In contrast, the relative liver weight in females was increased by
9% or less at all doses, indicating males may be more sensitive than females.
Histopathological changes were observed for both males and females at 1000 mg/kg-day.
Histopathological changes included a slight increase in the eosinophilic cytoplasmic staining of
hepatocytes near the central veins (incidence not reported). The increase in eosinophilic staining
was accompanied by a loss of cytoplasmic vacuoles. In the intermediate zone, subtle changes in
cellular architecture were noted, including that the normally parallel pattern of hepatic cords was
in disarray. Dee and Travis (1994) indicated that the appearance resembled areas of nodular
cellular proliferation but did not discuss their criteria for evaluation of this lesion. In TCA-
treated mice, [3H]thymidine incorporation (observed autoradiographically) was mostly localized
in the intermediate zone in cells that resembled mature hepatocytes, while labeling in controls
occurred primarily in the peri-sinusoidal cells. Similar patterns of labeling were observed in
male and female mice. In addition, mitotic figures (indicative of dividing cells) were observed in
the livers of TCA-treated mice but not in controls, and these dividing cells had often
incorporated the radiolabel into the DNA. The observed mitotic figures and active labeling of
dividing cells suggest the labeling of newly replicated DNA rather than labeling of damaged
DNA as proposed by Sanchez and Bull (1990). The number of mature hepatocytes labeled with
[3H]thymidine appeared to increase with increasing TCA dose, reaching a maximum of
approximately 2.5-fold increase at 1000 mg/kg-day (no statistical analysis was reported). In
contrast, the proportions of radiolabel incorporated into other cells (principally small peri-
sinusoidal cells) remained relatively constant at all TCA doses.
Incorporation of [3H]thymidine in extracted liver DNA also increased as TCA dose
increased. In female mice, labeling was 1.1-, 2.0-, 2.9-, and 3.3-fold the control value at 100,
250, 500, and 1000 mg/kg-day, respectively. In male mice, labeling was 1.3-, 1.4-, 1.8-, and
2.0-fold the control value at 100, 250, 500, and 1000 mg/kg-day, respectively. The increase in
DNA synthesis ([3H]thymidine/|ig DNA) became statistically significant at 250 mg/kg-day and
36 DRAFT - DO NOT CITE OR QUOTE
-------
higher for female mice and 100 mg/kg-day and higher for males. No difference in total liver
DNA content (mg DNA/g liver) was observed. Peroxisome proliferation was not quantified.
Dee and Travis (1994) concluded that their results are consistent with an increase in DNA
synthesis and cell division/proliferation in response to TCA treatment. The authors further
suggested that, since only slight histopathological effects were observed at the highest dose, it
was unlikely that the increased DNA synthesis and cell division were secondary to tissue repair.
Based on the increased relative liver weight (16%) at 100 mg/kg-day, accompanied by an
increase in the [3H]thymidine incorporation (1.3-fold) in male mice and supported by the
histopathological evidence of cell proliferation, EPA determined 100 mg/kg-day was the
LOAEL for this study. A NOAEL was not observed.
Kato-Weinstein et al. (2001) evaluated the ability of several haloacetic acids to affect
liver glycogen content, serum insulin levels, and serum glucose levels in mice. Groups of 5 male
B6C3Fi mice were exposed daily to neutralized TCA (>98% pure) in the drinking water at 3 g/L
for 4 or 8 weeks and at 0.3, 1, or 3 g/L for 12 weeks. The concentrations provided correspond to
estimated average daily doses of approximately 0, 75, 250, or 750 mg/kg-day, respectively,
based on a reference water intake value of 0.25 L/kg-day for male B6C3Fi mice (U.S. EPA,
1988). Body and liver weights were recorded and liver glycogen content and serum glucose and
insulin levels were determined after 4, 8, or 12 weeks of exposure. Localization of glycogen in
the liver was evaluated by PAS staining.
TCA treatment did not affect body weight at any tested concentration. Relative liver
weights were significantly (p < 0.05) greater than controls at all exposure groups, and absolute
liver weights were significantly (p < 0.05) greater than controls at all exposure groups except in
mice exposed at 0.3 g/L for 12 weeks. The magnitude of these increases was 20% to 50%
greater than controls. The time course for liver glycogen content was significantly lower (p <
0.05, approximately 25-33% as estimated from Kato-Weinstein et al. (2001, Figure 1A) than
controls after 8 and 12 weeks of treatment at 3 g/L. After 12 weeks of treatment, liver glycogen
concentration was significantly decreased at all tested concentrations. No consistent or dose-
related effects on insulin or glucose levels were observed at any concentration of TCA in this
study. Histopathological examination of livers from control animals revealed that glycogen-rich
(strong PAS staining) and glycogen-poor (low PAS staining) cells were mixed in each hepatic
zone, with slightly higher numbers of glycogen-rich cells in the portal area. In comparison, PAS
staining was confined to the periportal region in animals exposed to 0.3 and 1.0 g/L of TCA.
This observation suggests that glycogen depletion occurred in the central lobular area as a result
of depletion of glycogen from cells that appear to concentrate it in the liver of control mice. This
result can be compared with observations made by Bull et al. (1990) and Sanchez and Bull
(1990), who reported that TCA-treated animals displayed less evidence for glycogen
37 DRAFT - DO NOT CITE OR QUOTE
-------
accumulation and noted that when staining occurred it was more prominent in the periportal than
in centrilobular portions of the liver acinus.
Laughter et al. (2004) exposed wild-type SV129 mice and a mouse strain lacking a
functional form of peroxisome proliferator activated receptor a (PPARa) (PPARa-null mice) to
TCA at 0, 0.25, 0.5, 1, or 2 g/L in the drinking water (neutralized) for 7 days. These
concentrations correspond to estimated daily doses of approximately 0, 57.5, 115, 230, or 460
mg/kg-day, respectively, based on a reference water intake value of 0.23 L/kg-day for male
B6C3Fi mice (U.S. EPA, 1988). WY 14,693 at 50 mg/kg was given as the positive control.
Following exposure, the mice were sacrificed and livers were removed and weighed.
Subsamples of liver were processed for histopathological examination, analysis of CYP4A and
AGO protein expression, and measurement of PCO activity. Exposure to TCA increased liver-
to-body-weight ratios in wild-type mice but the response was not statistically significant.
Exposure to TCA induced markers of peroxisome proliferation in wild-type mice but not
PPARa-null mice. Exposure to 1 or 2 g/L TCA significantly increased the level of CYP4A
protein, and exposure to 2 g/L significantly increased PCO and AGO activity in liver
homogenates from wild-type mice only, indicating that PPARa is necessary for TCA to induce
lipid metabolism enzymes associated with peroxisome proliferation. Centrilobular hepatocyte
hypertrophy was observed in wild-type mice exposed to 2 g/L TCA but not in PPARa-null mice
exposed to the same concentration. The results of this study indicate that TCA induces liver
effects through activation of PPARa.
4.2.1.2. Subchronic Inhalation Studies
No short-term toxicity studies for TCA were identified for exposure by the inhalation
route.
4.2.2. Chronic Studies and Cancer Assays
Long-term oral toxicity studies for TCA are available for rats and mice. The available
data are summarized in Table 4-2a (noncancer data) and Table 4-2b (cancer and tumor
promotion data).
4.2.2.1. Oral Studies
4.2.2.1.1. Rats.
4.2.2.1.1.1. Chronic studies. DeAngelo et al. (1997) evaluated the tumorigenicity of TCA in
male F344 rats exposed for 104 weeks via drinking water. Groups of 50 rats received TCA in
drinking water (adjusted to physiologic pH) at 0, 50, 500, or 5000 mg/L, resulting in time-
weighted mean daily doses of 0, 3.6, 32.5, or 364 mg/kg as calculated by the study authors.
Dosing was initiated at 28-30 days of age. Interim sacrifices (18-21 rats/group) were conducted
3 8 DRAFT - DO NOT CITE OR QUOTE
-------
at 15, 30, 45, and 60 weeks, and gross lesions in the body and internal organs were examined.
The organs examined histologically at the interim and terminal sacrifices were liver, kidney,
spleen, and testes. The survivors were sacrificed at 104 weeks. At study termination, blood
from all treatment groups was analyzed for serum AST and ALT activity and livers were
analyzed for cyanide-insensitive PCO activity and extent of hepatocyte proliferation
([3H]thymidine incorporation). At sacrifice, all animals were subjected to a complete necropsy.
A comprehensive set of tissues including all major organs was examined microscopically in
high-dose rats. The liver, kidney, spleen, and testes were examined in the remaining dose
groups.
Survival in dosed animals was similar to that in controls (79%, 75%, 59%, and 76% in
the control, low-, mid-, and high-dose groups, respectively), and there were no significant
differences in water consumption between exposed and control groups. An MTD was reached,
as indicated by a 10.7% decrease in the final mean body weight of the high-dose animals relative
to controls. Absolute liver weight was decreased by 11% at the high dose. No significant
differences from the control values were observed in the absolute and relative weights of the
kidney, spleen, or testes. AST activity was significantly decreased in the mid-dose group, but
the data did not show a dose-related trend. ALT activity increased in a dose-related manner and
the response was statistically significant at the high dose. Peroxisome proliferation in the livers
of animals exposed to the high dose (364 mg/kg-day) of TCA was significantly increased, based
on a twofold increase in cyanide-insensitive PCO activity throughout the exposure period. There
was no evidence of a dose-related increase in hepatocyte proliferation. Most nonneoplastic
hepatic lesions were spontaneous and age related. A minimal to mild treatment-related increase
in hepatic cytoplasmic vacuolization was evident in the low and mid doses but not at the high
dose (data not shown). A mild increase in the severity of hepatocellular necrosis was observed
in the high-dose animals (data not shown). No treatment-related histopathological changes were
noted for the kidney, spleen, or testes. No dose-related increases in the incidences of neoplasms
or hyperplasia were observed in the liver or other tissues. Animals for interim sacrifices were
from the same exposed groups. The number of animals at final sacrifice ranged from 19-24/dose
group. Hence, the power of detection of this bioassay was limited by the relatively small group
sizes. DeAngelo et al. (1997) determined the study NOAEL/LOAEL to be 32.5 mg/kg-day, and
364 mg/kg-day, respectively, based on decreased body weight, increased serum ALT activity,
mild hepatocellular necrosis, and increased peroxisome proliferation.
39 DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-2a. Summary of longer-term studies evaluating noncancer effects of TCA after oral administration in
rats and mice
Reference"
Species
Exposure
route
Exposure
duration
Doses evaluated
Noncancer effects
evaluated
Effects
NOAEL
(mg/kg-day)
LOAEL
(mg/kg-day)
Comments
Rats
DeAngelo
etal. (1997)
F344 rats
(males,
50/group)
Oral,
drinking
water
104 Weeks
0, 3.6, 32.5, or
364 mg/kg-day
Body weight, ALT
and AST activity,
histopathology
(liver, kidneys,
spleen, testes,
excised lesions at
interim and
terminal sacrifice;
comprehensive
histopath exam in
high-dose group at
terminal sacrifice),
peroxisome
proliferation
Decreased body
weight, increased
serum ALT
activity; mild
hepatocellular
necrosis; increased
peroxisome
proliferation
32.5
364
Time-weighted
average daily
doses were
calculated by
the study
authors; a
comprehensive
set of tissues
was
microscopically
examined.
Mice
DeAngelo
et al. (2008)
B6C3FJ
mice
(males,
Study
l:50/group;
Study 2:
58/group;
Study 3:
72/group;
27-30/dose
at terminal
sacrifice;
5/dose at
interim
sacrifices)
Oral,
drinking
water
Study 1:60
weeks
Studies 2 and
3: 104 weeks
Study 1:0, 8, 68,
or 602 mg/kg-
day; Study 2: 0,
572 mg/kg-day;
Study 3:0, 6, 58
mg/kg-day
Body weight, liver
weight, serum LDH
activity, liver PCO
activity, hepatocyte
proliferation,
histopathologic
examination for
gross lesions, liver,
kidney, spleen and
testis at interim and
terminal necropies;
complete
histopathologic
examination on 5
mice from the high-
dose and control
groups
Decreased body
weight, increased
absolute and
relative liver weight
in the 68 and 602
mg/kg-day groups,
hepatic
inflammation and
necrosis, increased
LDH activity in the
68 and 602 mg/kg-
day groups at 30
weeks, increased
liver PCO activity
in te 68 and 602
mg/kg-day groups,
increased labeling
index for nuclei
outside of hepatic
proliferative
lesions, and
testicular tubular
8
68
Time-weighted
average daily
doses were
calculated by
the study
authors; a
comprehensive
set of tissues
was
microscopically
examined.
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-2a. Summary of longer-term studies evaluating noncancer effects of TCA after oral administration in
rats and mice
Reference"
Pereira
(1996)
Bull et al.
(1990)
Herren-
Freund et
al. (1987)
Species
B6C3FJ
mice
(females,
38-1347
group)
B6C3FJ
mice
(A) (5-35
mice/dose
/time point,
see text)
(B)(H
males/
dose)
B6C3FJ
mice
(males, 22-
33/group)
Exposure
route
Oral,
drinking
water
Oral,
drinking
water
Oral,
drinking
water
Exposure
duration
51 or 82
Weeks
(A) 52
Weeks (w/
interim
sacrifices at
15, 24, and
37 weeks)
(B)37
Weeks + 15-
week
recovery
61 Weeks
Doses evaluated
0, 78, 262, or
784 mg/kg-day
(A) 0, 164, or
329 mg/kg-day
(B) 0, 309
mg/kg-day
0, 500, or
1250 mg/kg-day
Noncancer effects
evaluated
Body and liver
weight
Liver
histopathology
Liver and kidney
weight and
histopathology
Liver weight and
histopathology
Effects
degeneration at 602
mg/kg-day
Increased relative
liver weight
Increased absolute
and relative liver
weight,
cytomegaly, modest
glycogen
accumulation
Increased absolute
and relative liver
weight
NOAEL
(mg/kg-day)
78
Not achieved
Not achieved
LOAEL
(mg/kg-day)
262
164
500
Comments
Increased liver
weight was
observed after
82 weeks at 262
mg/kg-day; 262
mg/kg-day was
judged to be an
equivocal
LOAEL in the
absence of
other measures
of liver toxicity.
Only the liver
and kidneys
were evaluated;
dose was
estimated by
the authors.
Only the liver
was
microscopically
examined.
"Cancer studies that evaluated noncancer endpoints are included in this table; data from Von Tungeln et al. (2002) were not included in this table because
animals were dosed via a non-oral exposure route (i.p. injection).
Source: Adapted from U.S. EPA (2005c).
41
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-2b. Summary of cancer bioassays and tumor promotion studies of TCA in rats and mice
Reference
Species
Study type
Exposure
route
Exposure
duration
Doses evaluated
Results
Comments
Rats
DeAngelo
etal.
(1997)
Parnell et
al. (1988)
F344 rats
(males,
50/group)
Sprague-
Dawley
rats (males,
6-12/dose
and
sampling
time)
Cancer
assay,
multiple
organs
Promotion,
multiple
organs,
partially
hepatec-
tomized rats
Oral, drinking
water
Oral, drinking
water
104 Weeks
Up to 12 months
0,3.6, 32.5, or
364 mg/kg-day
0, 2.9, 29.6, and
277 mg/kg-day at 6
months
Negative
Positive for gamma-
glutamyl
transpeptidase
(GGT)-positive foci
in liver
A comprehensive set of tissues
was microscopically examined;
only about 30 animals/
concentration were exposed for
>60 weeks.
TCA promoted GGT-positive
foci in diethylnitrosamine
(DEN)-initiated rats at all doses
evaluated, but only one rat
showed a liver carcinoma. TCA
showed no evidence as an
initiator.
Mice
DeAngelo
etal.
(2007)
Pereira
(1996)
Bull et al.
(2002)
B6C3FJ
mice
(males, 27-
30/dose at
terminal
sacrifice;
5/dose at
interim
sacrifices
B6C3FJ
mice
(females,
38-1347
group)
B6C3FJ
mice
(males, 20
or 407
group)
Cancer
bioassay
Cancer
bioassay
Cancer
bioassay
Oral, drinking
water
Oral, drinking
water
Oral, drinking
water
Study 1:60
Weeks;
interim sacrifices
at 4, 15, 30, and 45
weeks
Studies 2 and : 104
weeks
5 lor 82 Weeks
52 Weeks
Study 1:0, 8, 68, or
602 mg/kg-day;
Study 2: 0, 572
mg/kg-day;
Study 3:0, 6, 58
mg/kg-day
0, 78, 262, and
784 mg/kg-day
0, 120, or
480 mg/kg-day
Positive for liver
tumors starting at
45 weeks
Positive at 5 1 and
82 weeks
Increased incidence
of liver tumors
Liver, kidneys, spleen, and
testes were evaluated
microscopically for tumors;
complete histopathologic
evaluation was conducted on
other organs for 5 mice from the
control and high dose groups
Only the liver was evaluated for
tumors.
Only the liver was
microscopically examined;
doses were estimated based on a
default water intake of
0.25 L/kg-day.
42
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-2b. Summary of cancer bioassays and tumor promotion studies of TCA in rats and mice
Reference
Bull et al.
(1990)
Von
Tungeln et
al. (2002)
Herren-
Freund et
al. (1987)
Pereira and
Phelps
(1996)
Pereira et
al. (2001)
Pereira et
al. (1997)
Species
B6C3FJ
mice (5-
35/dose)
B6C3FJ
mice (23-
24/sex
/dose,
males and
females)
B6C3FJ
mice
(males, 22-
33/group)
B6C3FJ
mice
(females,
8-40/
group)
B6C3FJ
mice (14-
16/sex)
B6C3FJ
mice
(females,
20-457
dose)
Study type
Chronic
toxicity
study with
microscopic
examination
of the liver
Neonatal
cancer assay
Cancer
assay and
tumor
promotion,
liver
Cancer
assay and
tumor
promotion
Tumor
promotion
Tumor
promotion
Exposure
route
Oral, drinking
water
i.p. injection
Oral, drinking
water
Oral, drinking
water
Oral, drinking
water
Oral, drinking
water
Exposure
duration
(A) 52 Weeks (w/
interim sacrifices
at 15, 24, and 37
weeks)
(B) 37 Weeks +
15 -week recovery
Doses
administered at 8
and 15 days of age;
tumors evaluated
12 or 20 months of
age
61 Weeks
Up to 52 weeks
31 Weeks
44 Weeks
Doses evaluated
(A) 0, 164, or
329 mg/kg-day
(B) 0, 309 mg/kg-
day
2000 or 1000 nmol
(16-32 mg/kg), total
dose over a 2-day
period (at 8 and
15 days of age)
0, 400, or
1000 mg/kg-day
0, 78, 262, or
784 mg/kg-day
0 or 960 mg/kg-day
0, 235, or
980 mg/kg-day
Results
Positive for cancer,
and increased
absolute and relative
liver weight,
cytomegaly, apparent
glycogen
accumulation
Negative for tumor
induction
Positive for tumor
production and for
tumor promotion
Positive with or
without N-methyl-N-
nitrosamine (MNU)
initiation
Positive for liver and
kidney tumor
promotion
Positive, liver tumors
Comments
Hepatoproliferative lesions were
only observed in males, but
noncancer effects were
reportedly similar in incidence
and severity in males and
females; only the liver and
kidneys were evaluated.
TCA induced oxidative stress
but not a significant increase in
tumors in the neonatal mouse.
Only the liver was
microscopically examined; liver
tumors were observed either
with or without ethylnitrosamine
(ENU) pretreatment.
Only the liver was examined for
tumors.
Only the liver and kidneys were
examined for tumors; MNU was
used as an initiator; statistically
significant increases in tumor
yield were only observed in
males.
MNU was used as an initiator;
only the liver was
microscopically examined.
Source: Adapted from U.S. EPA (2005c).
43
DRAFT - DO NOT CITE OR QUOTE
-------
4.2.2.1.1.2. Tumor initiation and promotion studies. Parnell et al. (1988) investigated the
initiating and promoting effects of TCA by using two short-term tests: the rat hepatic enzyme-
altered foci assay and stimulation of peroxisomal-dependent PCO activity in the liver. In the
initiation protocol, male Sprague-Dawley rats (6-12/treatment/time point) underwent a two-
thirds partial hepatectomy (PH) or sham operation as control, followed 24 hours later by a single
oral gavage dose of 10 mg/kg diethylnitrosamine (DEN) (a known initiator) or 1500 mg/kg of
TCA. Additional groups of hepatectomized rats began a regimen of exposure to 5000 mg/L of
TCA in drinking water (about 600 mg/kg-day) for 10, 20, or 30 days to assess the effects of an
extended initiation period. Two weeks following the initiation period, all groups were promoted
for the remainder of the study (up to 12 months after beginning the promotion phase) with 500
mg/L phenobarbital (PB) in the drinking water. Animals were randomly sampled 24 hours after
the end of the initiation period, 24 hours prior to the start of the promotion phase, and 3, 6, and
12 months after beginning promotion. In the initiation study, the positive control is the group
with PH, treated with DEN as the initiator and PB for promotion.
In the promotion protocol, rats (6-12/treatment/time point) underwent the two-thirds
hepatectomy or sham operation followed 24 hours later by administration of a single 10 mg/kg
oral dose of DEN (the initiator) or distilled water (control). Promotion was begun two weeks
later by addition of 500 mg/L PB (the positive control) or 0, 50, 500, or 5000 mg/L TCA
(equivalent to doses of about 0, 6, 60, or 600 mg/kg-day as calculated using the chronic water
intake factor of 0.12 L/kg-day for Sprague-Dawley rats [U.S. EPA, 1988]) to the drinking water.
The test animals were randomly sampled at 2 weeks and 1, 3, 6, and 12 months after beginning
promotion. In the initiation bioassay, only the positive control group showed a statistically
significant induction of gamma-glutamyl transpeptidase (GGT)-positive foci at the 3-, 6-, and
12-month evaluation intervals. None of the groups that received initiation doses of TCA or the
associated controls exhibited significant induction of GGT-positive foci. Thus, TCA does not
appear to be an initiator based on the results of this assay.
In the promotion bioassay, GGT-positive foci were induced in the positive control
(PH/DEN/PB) at all evaluation intervals. Exposure of rats to 50, 500, or 5000 mg/L TCA as a
promoter for 6 or 12 months produced a significant increase in the number and size (mean area)
of GGT-positive foci over the negative control groups (PH alone, PH/DEN, or TCA alone). At 3
months, rats in the 50 and 5000 mg/L TCA promotion groups also had significantly greater
numbers of GGT-positive foci compared with the negative controls (data on size of foci were not
reported for this time point.) The promotion protocol also resulted in a statistically significant,
but weak (10-20% greater than controls), increase in peroxisomal-specific PCO activity at the
5000 mg/L drinking water level. No significant gross or histopathological lesions,
hepatomegaly, or changes in organ-to-body-weight ratios could be attributed to TCA exposure
and only one hepatocellular carcinoma in an animal from the PH/DEN/5000 mg/L TCA group
44 DRAFT - DO NOT CITE OR QUOTE
-------
was found in this study. The study authors concluded that TCA has significant, but relatively
weak, tumor promoting activity in the tested bioassay model. It should be noted that the
observed promotion effect was from both PH and TCA. There was no study group that treated
sham- operated rats with DEN, followed by TCA. Partial hepatectomy can function as a
promoter by itself.
4.2.2.1.2. Mice.
4.2.2.1.2.1. Chronic studies. DeAngelo et al. (2008) evaluated the induction of hepatocellular
neoplasia in male B6C3Fi mice exposed to TCA in drinking water in three studies. Male
B6C3Fi mice (50/dose at study initiation) were exposed to 0.05, 0.5, or 5 g/L TCA in the
drinking water for 60 weeks (Study 1); to 4.5 g/L TCA (58 animals/group) for 104 weeks (Study
2); or to 0.05 and 0.5 g/L TCA (72/group) for 104 weeks (Study 3). The pH of the dosing
solutions were adjusted to 6.0 - 7.1 by the addition of 10 N sodium hydroxide. Mice in the
control group in Study 1 received 2 g/L sodium chloride (NaCl) in the drinking water; while
those in Study 2 received 1.5 g/L neutralized acetic acid to account for any taste aversion of
TCA in dosing solutions. In Study 3, deionized water served as the control. Body weights and
water consumption were measured twice monthly for the first 2 months and then monthly
afterwards. In Study 1, groups of five animals from each dose group were examined at necropsy
at 4, 15, 31, and 45 weeks. In Study 2, serial necropsies were conducted at 15, 30, 45, and 60
weeks. In Study 3, serial necropsies were conducted at 26, 52 and 78 weeks.
At interim necropsies, livers, kidneys, spleens, and testes were examined for gross lesions
and microscopically for proliferative and non-neoplastic lesions. At studies termination, a
complete necropsy was performed, and pathological examination was conducted on gross
lesions, liver, kidney, spleen and testis A complete pathologic examination was performed on 5
mice from the high-dose and control groups. To determine long-term hepatocellular damage
during TCA treatment, arterial blood was collected at 30 and 60 weeks (Study 1) and 4, 30, and
104 weeks (Study 2) and serum lactate dehydrogenase (LDH) activity was measured. Portions
of liver tissue were frozen and analyzed for palmitoyl CoA oxidase (PCO) activity, a marker of
peroxisome proliferation. Five days prior to each scheduled necropsy, osmotic pumps
containing 200 ul [3H]thymidine (62-64 Ci/mmol) or 20 mg/ml BrdU (Study 3) were implanted
subcutaneously. Autoradiography using paraffin-embedded sections of liver was performed to
evaluate hepatocyte proliferation, as measured by the incorporation of 3H-labeled thymidine or
BrdU into nuclear DNA. The labeling Index (LI) was calculated by dividing the number of
labeled hepatocyte nuclei (S-phase) by the total number of hepatocyte nuclei scored.
For Study 1, time-weighted mean daily doses (MDD) of 8, 68, and 602 mg/kg-day were
calculated by the study authors from concentration and consumption data for the low-, mid-, and
high-dose groups. Animals in the mid- and high-dose groups consumed significantly less water
45 DRAFT - DO NOT CITE OR QUOTE
-------
than the controls. No significant differences in animal survival were noted for any treatment
group. A MDD of 572 mg/kg-day was calculated by the study authors for 4.5 g/L TCA (Study
2) and 6 and 58 mg/kg-day for 0.05 and 0.5 mg/kg-day (Study 3). With the exception of liver
neoplasia, all data presented by DeAngelo et al. (2008) were from the 60 week study (Study 1).
No decrease in animal survival was found at any TCA dose in all studies. Exposure to
TCA in the drinking water decreased body weight by 15% in the high-dose group relative to the
control. Significant, dose-related increases in absolute and relative liver weights were observed
in the 0.5 and 5 g/L treatment groups at all scheduled sacrifices, with the exception of the 0.5 g/L
dose group at 30 days. Nonneoplastic alterations in the liver and testes were seen at study
termination at 60 week and appeared to be dose-related (Tables 4-3 and 4-4). The major
nonneoplastic alterations observed in the liver included hepatocellular cytoplasmic alteration,
inflammation and necrosis. Cytoplasmic alterations were observed in all treatment groups.
These lesions were most prominent in the 5 g/L TCA group throughout the study and were most
severe after 60 weeks of treatment. The alterations were characterized by an intense eosinophilic
cytoplasm with deep basophilic granularity and slight cytomegaly. The distribution ranged from
centrilobular to diffuse. Hepatic necrosis was observed in the middle and high-dose group at all
time points and was reported to be most severe at 30-45 weeks; the study report provided only
combined data for the 30- and 45-week interim sacrifices (Table 4-4).
A significant increase in the severity of inflammation was seen in the high-dose group at
60 weeks. A dose-related increase in serum LDH activity was observed at 30 weeks, and
significant increases were measured in the 0.5 and 5.0 g/L dose groups. No change in LDH
activity was found in any treatment groups at 60 weeks. No other hepatic changes showed
statistically significant increases in incidence or severity level. An increased incidence of
testicular tubular degeneration was seen in the 0.5 and 5 g/L treatment groups (Table 4-3). No
treatment-related changes were observed in the spleen or kidney.
Exposure to TCA induced tumors in the liver at 60 week (Table 4-5). There were
significant dose-related trends for increased prevalence and multiplicity of adenomas and
carcinomas. The prevalence and numbers of hepatocellular carcinomas and hepatocellular
adenomas were significantly increased in the high-dose group. The number of animals with
either lesion was significantly increased in the 0.5 g/L treatment group. Neoplasia was first seen
in all dose groups after 45 weeks of treatment. The prevalence and number of tumors in the 5
g/L group were 60% (3/5 animals with a lesion) and 0.80 lesions/animal. One hepatocellular
carcinoma was found in the 0.5g/L group and one hepatocellular adenoma was found in the 0.05
g/L group. No induction of tumors was reported in other organs.
Significant increases above the control values were also observed for the prevalence and
multiplicity of adenomas, carcinomas, and either adenomas or carcinomas for mice exposed to
4.5 g/L TCA for 104 weeks (Study 2) or 0.5 g/L TCA for 104 weeks (Study 3). (Table 4-6).
46 DRAFT - DO NOT CITE OR QUOTE
-------
Neoplastic lesions observed at organ sites other than the liver were considered spontaneous for
the male mice and did not exceed the tumor incidences when compared to a historical control
data base.
Liver PCO activity was significantly increased at the mid and high doses when compared
with control values. The range of PCO activity for mice exposed to 0.5 g/L was 129-260%
above the control value; for 5 g/L it was 326-575% above the control value. Autoradiographs of
the livers from animals exposed to 5 g/L TCA showed significantly increased labeling of
hepatocyte nuclei at 30 (about 3-fold) and 40 weeks (about 2.5- fold). Increased nuclear
labeling was observed in the mid-dose treatment group at 60 weeks (about 3-fold). These data
indicate that TCA induced treatment-related tumors in male mice at doses that also induced
peroxisome proliferation and hepatocyte proliferation. EPA determined the study NOAEL (from
60 week study) for liver effects (increase in liver weight, increase in liver PCO activity, hepatic
necrosis) and increase in testicular tubular degeneration was 8 mg/kg-day, and the LOAEL was
68 mg/kg-day.
Table 4-3. Incidence and severity of nonneoplastic lesions in male B6C3Fi
mice exposed to TCA in drinking water for 60 weeks
Lesion
Hepatocellular
cytoplasmic
alteration
Hepatocellular
inflammation
Testicular
tubular
degeneration
Treatment
Dose3
(mg/kg-day)
Numberb
Incidence0
Severityd
Incidence0
Severityd
Incidence
Severity
Control
0
30
7%
0.10 ±0.40
10%
0.13 ±0.40
7%
0.10 ±0.40
0.05 g/L TCA
8
27
48%e
0.70 ±0.82
0
0
0
0
0.5 g/L TCA
68
29
20.6%e
0.34 ±0.72
7%
0.07 ±0.03
14%e
0.17 ±0.47
5 g/L TCA
602
29
93%e
1.60 ±0.62°
24%e
0.24 ±0.44
21%e
0.21 ±0.41
a Time-weighted mean daily dose
b Number of animals examined.
0 Percentage of animals with alteration.
d Severity: 0 = no lesion, 1 = minimal, 2 = mild, 3 = moderate, 4 = severe (reported severity was the average
severity of all animals in the dose group).
e Statistically significant from the control group, p < 0.05.
Source: DeAngelo et al. (2008).
47
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-4. Incidence and severity of hepatocellular necrosis at 30-45 weeks
in male B6C3Fi mice exposed to TCA in drinking water
Treatment
Dose3 (mg/kg-day)
Number13
Incidence0
Severityd
Control
0
10
0
0
0.05 g/L TCA
8
10
0
0
0.5 g/L TCA
68
10
30.0%
0.50 ±0.97
5 g/L TCA
602
10
50.0%
1.30±1.49e
a Time-weighted mean daily dose
b. Number of animals examined.
0 Percentage of animals with alteration .
d Severity: 0= no lesion, 1 = minimal, 2 = mild, 3 = moderate, 4 = severe (reported severity was the average
severity of all animals in the dose group).
e Statistically significant from the control group, p < 0.05.
Source: DeAngelo et al. (2008)
Table 4-5. Prevalence and multiplicity of hepatocellular neoplasia in male
B3C6Fi mice exposed to TCA in drinking water for 60 weeks
Treatment
HAC
HCC
HAorHCc
Dose3
Numberb
Prevalence"1
Multiplicity6
Prevalence11
Multiplicity6
Prevalence"1
Multiplicity"
Control
0
30 (30)
7%
0.07±0.05e
7%
0.07 ±0.05
14%
0.13 ±0.06
0.05 g/L TCA
8
27 (30)
15%
0.15 ±0.07
4%
0.04 ±0.04
15%
0.19 ±0.09
0.5 g/L TCA
68
29 (30)
22%
0.24 ±0.10
21%
0.28 ±0.22
38%f
0.52±0.14f
5 g/L TCA
602
29 (30)
38%f
0.55 ± 0.15 f
38%f
0.41±0.11f
55.%f
1.00±0.19f
a Time-weighted mean daily dose
b Number of animals examined. () number of animals/group scheduled for terminal necropsy
0 HA = hepatocellular adenoma, HC = hepatocellular carcinoma, HA or HC = either hepatocellular adenoma or
hepatocellular carcinoma.
d Percentage of animals with a lesion as reported in the study report.
e Number of lesions/animal, Mean ± SEM.
f Statistically significant from the control group, p < 0.05.
Source: DeAngelo et al. (2008)
48
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-6. Incidence of hepatocellular neoplasia in male B3C6Fi mice exposed to
TCA in drinking water for 104 weeks
Study
Duration
104
weeks
Study
Duratio
n
104
weeks
Treatment
HAC
HC
HA+HC
Dose3
(mg/kg-day)
Numberb
Prevalence"1
Multiplicity6
Prevalence11
Multiplicity6
Prevalence"1
Multiplicity6
Treatment
HA
HC
HA+HC
Dose3
(mg/kg-day)
Numberb
Prevalence"1
Multiplicity6
Prevalence"1
Multiplicity6
Prevalence"1
Multiplicity6
Control
0
25 (32)
0
0
12
0.20 ±0.12
12
0.20 ±0.12
Control
0
42 (50)
21
0.21±0.06
55
0.74 ±0.12
64
0.93 ±0.12
0.05 g/L TCA
6
35 (50)
23
0.34 ±0.12
40
0.71 ±0.19
57
1.11±0.21
0.5 g/L TCA
58
37 (50)
51f
0.78±0.15f
78f
1.46±0.21f
87f
2.14±0.26f
4.5 g/L TCA
572
36 (43)
59f
0.61±0.16f
78g
1.50±0.22f
89f
2.11±0.25f
3 Time-weighted mean daily dose calculated over 104 weeks
b Animals surviving > 78 weeks, () number of animals/group scheduled for terminal necropsy.
0 HA = adenoma, HC = carcinoma, HA or HC = either adenoma or carcinoma
d Number of animals with a lesion/number of animals examined
6 Mean number of lesions ± SEM
f Statistically significant from the control group, p <0.03
Bull et al. (1990) examined the induction of tumors in the liver of B6C3Fi mice given
TCA in drinking water (neutralized to pH 6.8-7.2). Groups of mice (24 males/2 g/L TCA dose
group, 11 males/1 g/L TCA dose group, 35 males/control group, 10 females/group) were
exposed to neutralized TCA (males: 0, 1, or 2 g/L; females: 0 or 2 g/L) for 52 weeks. Interim
sacrifices were performed at 15, 24, and 37 weeks on separate groups of male mice (five
males/group). An additional group of 11 males received 2 g/L TCA for 37 weeks, followed by a
15-week recovery period. The 0, 1, and 2 g/L concentrations used in this study correspond to
estimated average daily doses of 0, 164, and 329 mg/kg-day as calculated from data for total
dose provided in the study report. The approximate average daily dose for the 37-week exposure
with recovery was 309 mg/kg-day.
49 DRAFT - DO NOT CITE OR QUOTE
-------
No effects of treatment on survival or body weight were observed. Body weight and
food and water consumption data were recorded but not reported. A significant increase in the
relative liver weight was seen in the 1 g/L males (30% increase from control), 2 g/L males (63%
increase), and 2 g/L females (25% increase) at 52 weeks when compared with controls. No
changes in kidney weights were observed. Mild intracellular swelling and some indication of
glycogen accumulation in the periportal region were observed in the livers of treated male and
female mice at 52 weeks. Male mice in the 2 g/L group had dose-related accumulation of
lipofuscin near proliferative lesions (no incidence reported) and hyperplastic liver nodules
(9/24).
The incidences of hepatocellular adenomas in male mice were 0/35 (0%), 2/11 (18%),
and 1/24 (4%), and the incidences of hepatocellular carcinomas were 0/35 (0%), 2/11 (18%), and
4/24 (17%) in the 0, 1, and 2 g/L exposure groups, respectively. Female mice did not develop
any tumors in response to TCA treatment and might be less sensitive to TCA treatment than
males. However, fewer female mice (52 weeks: 2g/L, 10 females) were evaluated in this study
than were male mice (37 weeks: 2g/L, 11 males; 52 weeks: 1 g/L, 11 males; 2 g/L, 24 males),
which may have limited the ability of the study to detect tumors in female mice. Fifteen weeks
after exposure to 2 g/L for 37 weeks, hepatocellular carcinomas developed in 3/11 (30%) male
mice, but hepatic adenomas had not occurred by that date. Since the maximum exposure
duration in this study was only 52 weeks, this study may not have evaluated mice for an
adequate length of time to observe the full carcinogenic potential of TCA. In addition, the
numbers of animals tested were less than adequate. EPA determined the LOAEL for noncancer
effects was 164 mg/kg-day based on increase in liver weight, cytomegaly, and modest glycogen
accumulation.
Pereira (1996) administered 0, 2.0, 6.67, or 20.0 mmol/L TCA (0, 327, 1090, or 3268
mg/L) (neutralized with sodium hydroxide to pH 6.5-7.5) in drinking water to female B6C3Fi
mice from 7-8 weeks of age until sacrifice after 360 days (51 weeks) or 576 days (82 weeks) of
exposure. A control group of 134 mice was administered 20 mmol NaCl. There were 93, 46,
and 38 mice in the low-, mid-, and high-dose groups, respectively. Estimates of daily doses
resulting from exposure to treated drinking water were not reported. Based on the default water
intake for female B6C3Fi mice of 0.24 L/kg-day, calculated from the default body weight in an
allometric equation (U.S. EPA, 1988), the estimated doses are 0, 78, 262, and 784 mg/kg-day.
Drinking water consumption was monitored during the first 4 weeks of exposure. Body weights
were monitored throughout the study. At sacrifice, livers were collected, weighed, and
processed for histopathological examination.
Drinking water consumption was decreased only for the first week for the high-dose
group. Body weight was decreased beginning after 51 weeks of treatment with 20 mmol/L TCA.
Body weights were significantly decreased (p < 0.05) by approximately 10% on sporadic
50 DRAFT - DO NOT CITE OR QUOTE
-------
occasions beginning at week 51 until study termination. Relative liver weight increased with
dose (linear regression coefficient, r = 0.991). The relative liver weights of the high-dose group
increased by roughly 40% over controls at 360 days, and liver weights for the mid- and high-
dose groups increased by roughly 25% and 60% over controls, respectively, after 576 days. EPA
determined the increase in liver weight to be 2.0 mmol/L (78 mg/kg-day) and the LOAEL to be
6.67 mmol/L (262 mg/kg-day). However, this study was not designed to evaluate noncancer
effects of TCA.
The adversity of the liver weight increase at 6.67 mmol/L is supported by short-term
studies in B6C3Fi mice that have reported some evidence for glycogen accumulation (Sanchez
and Bull, 1990), increased hepatocyte labeling (Dees and Travis, 1994), and peroxisome
proliferation (Parrish et al., 1996) at TCA doses that increased liver weights. The incidence of
hepatocellular carcinoma was significantly increased (p < 0.05) at 20 mmol/L (784 mg/kg-day)
after 360 days (control: 0/40, 0%; 2.0 mmol/L [78 mg/kg-day]: 0/40, 0%; 6.67 mmol/L [262
mg/kg-day]: 0/19, 0%; 20.0 mmol/L [784 mg/kg-day]: 5/20, 25%). At 576 days the incidence
of foci of altered hepatocytes was significantly increased at 6.67 and 20.0 mmol/L (10/90,
11.1%; 10/53, 18.9%; 9/27, 33.3%; 11/18, 61.1%). The incidence of hepatocellular adenomas
was significantly increased at 20.0 mmol/L (2/90, 2.2%; 4/53, 7.6%; 3/27, 11.1%; 7/18, 38.9%),
and the incidence of hepatocellular carcinomas was significantly increased at 6.67 and 20.0
mmol TCA (2/90, 2.2%; 0/53, 0%; 5/27, 18.5%; 5/18, 27.8%).
As part of experiments designed to evaluate if TCA alone was responsible for TCE-
induced liver tumors, Bull et al. (2002) exposed 40 male B6C3Fi mice to neutralized TCA in
drinking water at 2 g/L for 52 weeks (Experiment 1) and 20 male mice at 0.5 or 2 g/L for 52
weeks (Experiment 2). Controls (12 in Experiment 1 and 20 in Experiment 2) were given
untreated drinking water. After exposure, animals were sacrificed and livers were removed,
weighed, grossly examined, and processed for histopathological examination. No other tissues
were examined histologically. The estimated doses resulting from exposure to these
concentrations were not reported. However, based on reference water intake of 0.24 L/kg-day
for male B6C3Fi mice (U.S. EPA, 1988), the estimated doses used in this study were 0, 120, and
480 mg/kg-day. Groups of animals were also exposed to TCE, DCA, and various concentrations
of a mixture of DCA and TCA. Those results are not fully discussed in the context of this
toxicological review.
Tumors were stained with anti c-Jun antibody H-ras codon 61 mutation frequency and
spectra were characterized, and these results were compared with those from DCA- and TCE-
induced tumors. Proteins involved in the MAP kinase-signaling cascade (Ras, MeK, active
Erkl/2, and c-Fos) were examined by Western blotting in order to determine if the three
common codon 61 mutations of ras had different effects on downstream effectors. Tumor
incidence and multiplicity were significantly (p < 0.05) greater than controls at all TCA exposure
51 DRAFT - DO NOT CITE OR QUOTE
-------
concentrations. Tumor incidence in animals exposed to TCA at 2 g/L for 52 weeks (Experiment
1) was 33/40 compared with 4/12 in controls; tumor incidences in mice exposed to TCA at 0.5 or
2 g/L for 52 weeks (Experiment 2) were 11/20 and 9/20, respectively, compared with an
incidence of 1/20 in controls. All tumor cells from TCA-treated mice were nonreactive with the
c-Jun antibody (c-Jun"), which is consistent with previous reports (Stauber and Bull, 1997). The
mutation frequency at H-ras codon 61 in TCA-induced tumors (44%) was lower than the
frequency of codon 61 mutations (56%) in spontaneous liver tumors in B6C3Fi mice but higher
than that in TCE-induced tumors (21%). The H-ras mutation spectrum of TCA-induced tumors
did not differ significantly from that of historical controls. TCA had no effect on activation of
the MAP kinase cascade.
4.2.2.1.2.2. Tumor promotion studies. Herren-Freund et al. (1987) investigated the
initiation/promotion potential of TCA in male B6C3Fi mice (22-33/group). At 15 days of age,
mice were pretreated with a single i.p. dose of ethylnitrosourea (ENU) as a tumor initiator at
doses of 0 mg/kg (uninitiated control, treated with 2 uL/g sodium acetate and 5 g/L TCA), 2.5
mg/kg (2 and 5 g/L TCA groups), or 10 mg/kg (5 g/L TCA group only). Following
pretreatment, TCA was administered in the drinking water at concentrations of 2 or 5 g/L (500 or
1250 mg/kg-day) as calculated using a subchronic water intake factor of 0.25 L/kg-day (U.S.
EPA, 1988) from 4 to 65 weeks of age. The negative control groups for tumor promotion (22-23
animals/group) received 2 g/L NaCl in drinking water and 0, 2.5, or 10 mg/kg ENU. The mice
were sacrificed after 61 weeks of exposure. Survival data were not reported.
Significant decreases of 9-12% in final mean body weight were observed in the 5 g/L
TCA groups relative to the corresponding NaCl control. Absolute and relative liver weights
were significantly increased (by 41-73%) in all TCA treatment groups relative to the
corresponding NaCl control group. The incidences of hepatocellular adenomas (8/22, 36%) and
hepatocellular carcinomas (7/22, 32%) were significantly increased in the uninitiated group
receiving 5 g/L TCA when compared with the uninitiated NaCl control group (hepatocellular
adenomas: 2/22, 9%; hepatocellular carcinoma: 0/22,0%). The incidences of hepatocellular
adenomas (NaCl control: 1/22, 5%; TCA 2 g/L: 11/33, 33%; 5 g/L: 6/23, 26%) and
hepatocellular carcinomas (NaCl control: 1/22, 5%; TCA 2 g/L: 16/33, 48%; 5 g/L: 11/23,
48%) were significantly increased in the TCA groups initiated with 2.5 mg/kg ENU. Mice
initiated with 10 mg/kg ENU and then administered 5 g/L TCA also showed increase in the
incidence of hepatocellular carcinomas, although the increase was not statistically significant.
Thus, TCA enhanced the incidence of adenomas and hepatocellular carcinomas above control
levels, with or without prior initiation. The study authors concluded that TCA acted as a
complete carcinogen in B6C3Fi mice.
52 DRAFT - DO NOT CITE OR QUOTE
-------
Pereira and Phelps (1996) assessed liver tumor promotion activity by TCA in female
B6C3Fi mice. Test animals were treated with 25 mg/kg of the tumor initiator, N-methyl-N-
nitrosamine (MNU), at 15 days of age or given 4 mL/kg sterile saline (vehicle control). Starting
at 7 weeks of age, animals were administered neutralized TCA in drinking water at
concentrations of 0, 2.0, 6.67, or 20.0 mmol/L (0, 327, 1090, or 3268 mg/L) for either 31 weeks
(n = 8-15/group) or 52 weeks (n = 39 for MNU controls, 40 for the low-dose TCA-only group,
19 for the mid- and high-dose TCA-only groups, and 6-23 for TCA + MNU groups). Dose
estimates were not reported by the study authors. The drinking water concentrations used
resulted in doses of approximately 0, 78, 262, or 784 mg/kg-day based on the default drinking
water value of 0.24 L/kg-day for female B6C3Fi mice (U.S. EPA, 1988). A recovery group (n =
11) was removed from treatment after 31 weeks and retained for an additional 21 weeks.
At 31 weeks, treated animals exhibited a slight, dose-related linear increase in relative
liver weights. At 31 and 52 weeks, no significant increase in foci of altered hepatocytes,
adenomas, or carcinomas was observed in mice that received MNU only. In mice administered
TCA but not initiated with MNU, the only tumorigenic response was a slight increase in the
yield of hepatocellular carcinomas/animal (0.50 tumors/mouse) in the high-dose group (784
mg/kg-day) after 52 weeks of treatment. Animals initiated with MNU and treated with TCA
exhibited an increase in liver tumors following both 31 and 52 weeks of exposure in the 784
mg/kg-day group and following 52 weeks of exposure in the 262 mg/kg-day group. Both the
numbers of adenomas/mouse and carcinomas/mouse were statistically elevated as compared with
controls, and the tumor yield generally increased with increasing duration of exposure from 31 to
52 weeks. However, there was no significant increase in the yield of altered hepatocyte foci at
either time point in any dose group. The concentration-response relationships for total
lesions/mouse (foci plus tumors) after both 31 and 52 weeks of treatment were best described by
a linear-regression line.
When exposure to 784 mg/kg-day TCA was terminated after 31 weeks and the animals
held for an additional 21 weeks, the yield of tumors/mouse remained stable. However, the yield
of hepatocellular carcinomas increased from 0.20/mouse in mice exposed for 31 weeks to
0.73/mouse in mice held to 52 weeks. When treatment continued between weeks 31 and 52, the
yield of tumors/mouse rose from 1.50 at 31 weeks to 4.21 at study termination. These findings
indicate that, although the occurrence of additional TC A-promoted tumors was dependent on
continuous treatment, the stability and progression to carcinoma appeared to be independent of
further treatment. Histochemical staining indicated that more than 71% of tumors promoted with
either 262 or 784 mg/kg-day TCA were basophilic and did not contain GST-Ti, a phase II
conjugation enzyme highly expressed in some tumor types, except for very small areas
comprising less than 5% of the tumor. The predominantly basophilic nature of the tumors
promoted by TCA is consistent with the character of lesions induced by tumorigenic compounds
53 DRAFT - DO NOT CITE OR QUOTE
-------
that are rodent peroxisomal proliferators, but "spontaneous" liver tumors in mice have also been
reported to be predominantly basophilic and lacking GST-rc (Pereira and Phelps, 1996).
Pereira et al. (2001) administered MNU to B6C3Fi mice (16 males and 14 females) via
i.p. injection at 30 mg/kg, then exposed the MNU-initiated mice to TCA at 4 g/L in the drinking
water for 31 weeks. Based on reference drinking water intake values for B6C3Fi mice (0.25 and
0.24 L/kg-day for males and females, respectively), male and female mice received
approximately 1000 and 960 mg/kg-day, respectively. After the treatment period, the liver and
kidneys were removed, weighed, and microscopically examined. The study was designed to
evaluate the effects of chloroform on TCA-induced tumor promotion, and only the TCA-only
treated groups are discussed in this review. Relative liver weight was significantly (p < 0.001,
75% in males and 35% in females) increased compared with controls. A significant (p < 0.05)
increase in the number of mice with liver tumors (adenomas + adenocarcinomas) was observed
in TCA-treated males initiated with MNU (incidence of 13/16 compared with 2/8 MNU-treated
controls). These tumors were >97% basophilic. Although an increase was also observed in
females (incidence of 6/14 compared with 2/29 controls), the increase was not statistically
significant (p < 0.05). Similarly, an increase in kidney tumors was also observed in male mice
initiated with MNU and promoted by TCA (incidence of 0/8 in MNU-only treated controls
compared with an incidence of 14/16 in MNU + TCA treated mice). Incidences of kidney
tumors in female mice were not significantly increased compared with MNU-treated controls
(incidence not reported). The study authors also investigated hypomethylation of the c-Myc
gene in liver and kidney tumors from TCA-treated mice. These results are discussed in Section
4.5.1.
In a study designed to compare the promotion of liver tumors in TCA and DCA-treated
mice initiated with MNU, Pereira et al. (1997) exposed female B6C3Fi mice (20-45/dose) to
TCA at 6 or 25 mmol/L in drinking water with or without addition of various concentrations of
DCA for 44 weeks. Based on reference water intake for female B6C3Fi mice of 0.24 L/kg-day
(U.S. EPA, 1988), the estimated doses are 0, 235, and 980 mg/kg-day. Body weight was
monitored throughout the study. Livers were removed, weighed, and microscopically examined
for presence of tumors. Liver sections were also stained immunohistochemically for GST-u. A
significant increase in adenomas was observed in TCA-only treated mice at 25 mmol/L (0.52
tumors/mouse compared with 0.07 tumors/control mouse) but not at 6 mmol/L (0.15
tumors/mouse). The tumors from TCA-treated mice were exclusively basophilic and were
generally without GST-u (with the exception of 4 carcinomas at 25 mmol/L TCA), which is
consistent with the results reported by Pereira and Phelps (1996). In contrast, tumors from
DCA-treated mice were primarily eosinophilic and were positive for GST-u. When TCA and
DCA were administered together (25 mmol/L TCA +15.6 mmol/L DCA), the tumor yield
increased synergistically. At the lower concentration, the relationship was at least additive. The
54 DRAFT - DO NOT CITE OR QUOTE
-------
tumors in the livers from mice treated with DCA + TCA were more consistent with the
characteristics of DCA-induced livers (eosinophilic and containing GST-u). These data suggest
that TCA and DCA both promote tumor formation; however, the different tumor characteristics
are consistent with the conclusion that the mechanisms for the tumor-promoting activity of each
compound are different.
Bannasch et al. (2003, 2001) have presented detailed information about phenotype for
foci of altered hepatocytes observed in the rat following treatment with classic peroxisome
proliferators and the changes that occur as foci progress to liver tumors. The phenotype for
altered hepatic foci (AHF) induced by TCA in mice (mixed basophilic and eosinophilic) and
progressed to basophilic in tumors is inconsistent with the peroxisome proliferator phenotype
(amphophilic - basophilic) described for hepatic preneoplastic lesions in rats. The analysis
presented by these authors has potential implications for evaluation of the MO A leading to
tumors in mice treated with TCA and their potential relevance to humans. However, there is, at
present, no pattern of gene expression to serve as a template for agents that are PPARa agonists
that could be used to compare the phenotypes described by Bannasch et al. (2003, 2001) with
those observed for TCA; the existing data for TCA do not include the detailed characterization
of phenotype required to support such a comparison. In addition, the patterns of tumor
phenotype and differences between the primary lineages observed in preneoplastic foci and those
induced by peroxisome proliferators have not been as well studied in the mouse. Consequently,
the implications of the work of Bannasch et al. (2003, 2001) for analysis of foci and lesions
produced by TCA are unclear.
4.2.2.2. Inhalation Studies
No chronic toxicity studies or cancer studies in animals exposed by inhalation to TCA are
available.
4.2.2.3. Studies Using Other Routes of Exposure
Von Tungeln et al. (2002) evaluated the neonatal tumorigenicity of TCA in B6C3Fi mice
(23-24 animals/sex/dose) in two bioassays. For each assay, TCA was dissolved in
dimethylsulfoxide (DMSO) and administered via i.p. injections at 8 and 15 days of age. In
Assay A, neonatal mice were given a total dose of 2000 nmol (approximately 33 mg/kg based on
a reference body weight of 0.01 kg for B6C3Fi mice at weaning) (U.S. EPA, 1988) and were
sacrificed at 12 months of age. In Assay B, neonatal mice were given a total dose of 1000 nmol
(approximately 16 mg/kg) and were sacrificed at 20 months of age. 4-Aminobiphenyl was used
as the concurrent positive control (22-24 mice/sex/dose) and total doses of 1000 and 500 nmol
were given by i.p. injection for Assays A and B, respectively. DMSO solvent control groups
(23-24 mice/sex) were included in each assay. Body weight (at 28-day intervals) and mortality
55 DRAFT - DO NOT CITE OR QUOTE
-------
were evaluated in all treatment groups. At sacrifice, all test animals were necropsied for gross
tumor count, microscopic examination of tissues, and histopathological diagnoses. No
unscheduled deaths occurred in Assay A. In Assay B, one mouse each died in the male and
female solvent control groups and in the female TCA group. A marginal, nonstatistically
significant increase in liver tumors was observed in TCA-treated males in Assay A (4/24) when
compared with the control group (1/24). The incidence of liver tumors in TCA-treated males in
Assay B (5/23) was less than in the control group (7/23). No tumors were observed in DMSO-
treated control females in either assay. The study authors concluded that TCA did not induce
significant tumor incidences when compared with the DMSO controls. In contrast, all male mice
treated with 4-aminobiphenyl (the positive control substance) in Assays A and B developed liver
tumors and 9/22 male mice in Assay B also developed lung tumors. Nine of 23 female mice
treated with 4-aminobiphenyl in Assay B developed liver tumors; no tumors were diagnosed in
female mice dosed with 4-aminobiphenyl in Assay A.
In a related mechanistic study, Von Tungeln et al. (2002) dosed an additional group of
male neonatal B6C3Fi mice with TCA to evaluate TCA-induced formation of malondialdehyde
(MDA)-derived deoxyguanosine (MiG) adducts and 8-OHdG in hepatic DNA in relation to TCA
tumorigenicity. This study was conducted because previous results from the same laboratory
had shown that (1) in vitro metabolism of TCA by hepatic microsomes isolated from adult mice
results in lipid peroxidation, with subsequent production of MDA (Ni et al., 1996) (see Section
3.3 for a summary of this study) and (2) metabolism of TCA in the presence of calf thymus DNA
resulted in the formation of MiG adducts (Ni et al., 1995, as cited in Von Tungeln et al., 2002).
In addition, TCA induces formation of 8-OHdG (see Section 4.2.1.1), and induction of elevated
levels of 8-OHdG may induce tumors (Wagner et al., 1992).
Male neonatal B6C3Fi mice (the number of animals treated was not stated) were given a
total dose of 2000 nmol TCA by i.p. injection as described for the neonatal mice cancer assays
summarized above (Von Tungeln et al., 2002). The test animals were sacrificed 1, 2, or 7 days
after the final TCA treatment at 15 days of age, and liver tissue was collected for extraction of
DNA and determination of levels of MiG and 8-OHdG. TCA induced a significant (p < 0.05)
increase in MiG adduct formation in liver DNA at 24 and 48 hours (but not 7 days) after the
final dose. The increase was approximately 190% of the control value at each time point. TCA
treatment also resulted in a significant (p < 0.05) increase in 8-OHdG formation in liver DNA at
24 and 48 hours and at 7 days after administration of the final dose. The magnitude of the
increase was approximately 2.5-fold greater than the control values. Because TCA was not
carcinogenic in the neonatal cancer bioassays conducted by Van Tungeln et al. (2002), these
results suggest that neonatal B6C3Fi mice are not sensitive to either TCA-induced lipid
peroxidation or oxidative stress as a MOA for tumor induction under the experimental conditions
used in these studies. The study authors speculated that TCA was negative in their neonatal
56 DRAFT - DO NOT CITE OR QUOTE
-------
cancer bioassays because it may act as a cell proliferator. According to this hypothesis, liver
cells were already replicating at a very high rate in the neonatal mice when TCA was
administered; therefore, any additional cell proliferation induced by TCA may have been
negligible in comparison with the existing rate of proliferation.
4.3. REPRODUCTIVE AND DEVELOPMENTAL STUDIES
4.3.1. Reproductive Studies
One in vitro study was identified that suggested that TCA might decrease fertilization.
The effect of TCA on in vitro fertilization was examined in B6D2Fi mouse gametes (Cosby and
Dukelow, 1992). TCA was constituted in a culture medium to yield concentrations of 100, 250,
or 1000 ppm on a v/v basis (approximately 160, 400, or 1600 mg/L) and incubated with mouse
oocytes and sperm for 24 hours. Each culture dish was subsequently scored for percentage
oocytes fertilized. The percent of oocytes fertilized was significantly decreased from 82% for
controls to 53% for oocytes exposed to 1000 mg/L TCA (p < 0.001).
4.3.2. Developmental Studies
4.3.2.1. Oral Developmental Studies
Seven studies have evaluated the potential of TCA to induce developmental toxicity in
rats (Table 4-7). In addition, one study has been conducted to identify embryonic genes, which
undergo changes in expression (up- or down-regulation) in response to maternal TCA exposure.
No studies in other test species (e.g., mice or rabbits) were located.
Smith et al. (1989) dosed pregnant Long-Evans rats (20-21/dose) with 0, 330, 800, 1200,
or 1800 mg/kg-day TCA via oral gavage on gestation days (GDs) 6-15. Clinical signs of
toxicity and body weight gain were monitored throughout the exposure period. The dams were
sacrificed on GD 20. The liver, spleen, and kidneys were removed and weighed. The uterine
horns were examined for the number and location of fetuses or resorption sites. The fetuses were
subsequently removed and weighed, measured, sexed, and evaluated for external malformations.
Two-thirds of each litter was preserved for evaluation of visceral abnormalities. The remaining
one-third of the fetuses was reserved and processed for evaluation of skeletal abnormalities.
57 DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-7. Summary of developmental studies evaluating effects of TCA after oral administration in rats
Reference
Smith et al.
(1989)
Johnson et
al. (1998)
Fisher et al.
(2001)
Species
Long-Evans rats
(20-2 1/ dose)
Sprague-
Dawley rats (55
controls and 1 1
TCA-treated
rats)
Sprague-
Dawley rats
(19/dose)
Exposure
route
Oral,
gavage
Oral,
drinking
water
Oral,
gavage
Exposure
duration
CDs 6-15
CDs 1-22
CDs 6-15
Doses
evaluated
0, 330, 800,
1200, or
1800 mg/kg-day
Oor291mg/kg-
day
0 or 300 mg/kg-
day
Effects
Decreased fetal
weight, decreased
crown-rump length,
increased incidence of
soft-tissue
malformations and
cardiovascular
malformations,
increased maternal
spleen and kidney
weights
Increase in cardiac
malformations, number
of implantation
sites/litter, number of
resorption sites/litter,
and total number of
resorptions among
treated dams
Decreased maternal
weight gain, reduced
fetal body weight
NOAEL
(mg/kg-day)
Maternal:
None
Developmental:
None
Maternal:
None
Developmental:
None
Maternal:
none
LOAEL
(mg/kg-day)
Maternal:
330
Developmental:
330
Maternal:
291
Developmental:
291
Maternal:
300
Comments
Critical Study for
1994 RfD.
Dose estimated by the
authors, based on the
average amount of
water consumed by
the animals on a daily
basis.
The tested
concentration/dose
was also a maternal
LOAEL for decreased
weight gain. Study
was not adequately
designed and/or
reported, and a
complete array of
standard
developmental end
points was not
assessed.
Cardiac defects were
the only visceral
malformation
58
DRAFT - DO NOT CITE OR QUOTE
-------
Reference
Singh
(2005a)
Singh
(2005b)
Singh
(2006)
Species
Inbreded
Charles Foster
rats
(6-12/group)
Inbreded
Charles Foster
rats
Inbred Charles
Foster rats
Exposure
route
Oral
gavage
Oral
gavage
Oral
gavage
Exposure
duration
GD 6-15
GD 6-15
GD 6-15
Doses
evaluated
0, 1000, 1200,
1400, 1600, or
1800 mg/kg-day
0, 1000, 1200,
1400, 1600,
1800 mg/kg-day
0, 1000, 1200,
1400, 1600,
1800 mg/kg-day
Effects
Increase in post-
implantation loss,
decreased fetal testes
weight, reduction in
the diameter of the
seminiferous tubules,
increased apoptosis of
the gonocytes
Decrease in fetal
ovaries weight,
decrease in the number
of oocytes and the size
of the ovaries,
apoptosis of oocytes
Decrease in maternal
weight gains; decrease
in fetal weight and
fetal brain weight;
hydrocephalus,
vacuolation, and
hemorrhages in fetal
brains
NOAEL
(mg/kg-day)
Developmental:
none
Developmental
(increase in
implantation
loss): none
Effect on fetal
testes: 1000
Effect on fetal
ovary: 1200
Maternal: 1000
Effect on fetal
brain: none
LOAEL
(mg/kg-day)
Developmental:
300
Developmental :
1000
Effect on fetal
testes: 1200
Effect on fetal
ovary: 1400
Maternal: 1200
Effect on fetal
brain: 1000
Comments
evaluated; maternal
toxicity indicated by
decreased body
weight gain for GDs
7-15 and 18-21; mean
uterine weight was
also significantly (p <
0.05) less than
controls.
Only evaluated effects
on fetal testes
Only evaluated effects
on fetal ovaries
Focused only on
effects of TCA on
fetal brains
59
DRAFT - DO NOT CITE OR QUOTE
-------
Reference
Warren et
al. (2006)
Species
Sprague-
Dawley
Crl:CDR (SD)
BRrats
Exposure
route
Oral
gavage
Exposure
duration
GD 6-15
Doses
evaluated
0, 300 mg/kg-
day
Effects
Decrease in fetal
weight, no eye
malformation, no
significant reductions
in lens area, globe
area, medial canthus
distance, and
interocular distance.
NOAEL
(mg/kg-day)
Developmental:
none
LOAEL
(mg/kg-day)
Development: 300
Comments
Focused on eye
malformations and
microphthalmia in
fetal rats
60
DRAFT - DO NOT CITE OR QUOTE
-------
Evidence of maternal toxicity was observed in all TCA treatment groups as indicated by
a significant (p < 0.05) increase in spleen (up to 74% increase) and kidney (up to 24% increase)
weights when compared with the control group. Unadjusted mean terminal (GD 20) body
weights were significantly reduced (p < 0.05; 5-12%) at all doses, but no statistically significant
differences were observed in average percent maternal weight gain when adjusted for gravid
uterine weight. Dams exposed to 800, 1200, or 1800 mg/kg-day had significantly (p < 0.05)
decreased body weight gains on GDs 6-9 and GDs 15-20 (up to a 54% decrease). The weight
change for GDs 15-20 may have been influenced by reductions in fetal body weight. The
number of litters totally resorbed was significantly increased (5/21 and 12/20, respectively), and
the number of viable litters (14/21 and 8/20, respectively) was significantly decreased at 1200
and 1800 mg/kg-day. Developmental effects were observed at all doses (Table 4-8) and included
significant (p < 0.05) decreases in mean fetal weight per fetus (up to a 33% decrease in males
and females); significant decreases in fetal crown-rump length (up to a 15% decrease in males
and females); increased percentages of fetuses affected per litter with cardiovascular
malformations, particularly levocardia and interventricular septal defects; and increased
percentages of fetuses affected per litter for total soft-tissue malformations. The maternal and
developmental LOAELs in this study are 330 mg/kg-day. Maternal and developmental NOAEL
values for TCA could not be determined because adverse effects were observed at all tested
doses.
Johnson et al. (1998) evaluated the teratogenicity of TCA by exposing pregnant Sprague-
Dawley rats to 0 (n = 55) or 2730 (n = 11) mg/L TCA in neutralized drinking water on GDs 1-
22. The authors estimated the doses to be 0 or 291 mg/kg-day, based on the average amount of
water consumed by the animals on a daily basis and measured body weights. Maternal toxicity
was evaluated by clinical observation and maternal weight gain. Dams were sacrificed on GD
22, and implantation sites, resorption sites, fetal placements, fetal weights, placental weights,
fetal crown-rump lengths, gross fetal abnormalities, and abnormal fetal abdominal organs were
recorded. In addition, the fetal hearts were removed, dissected, and examined microscopically
for abnormalities using a detailed microdissection cardiac evaluation technique. No signs of
maternal toxicity were reported. Although the authors reported that the weight gain during
pregnancy of treated females was not significantly different from controls, the average maternal
weight gain for TCA-exposed animals was 84.6 g as compared with 122 g for control animals,
representing a 30% decrease in maternal body weight gain. No measure of variation around the
mean (e.g., standard deviation or standard error) was reported, and it is not clear why this
reduction was not reported as statistically significant. Nonetheless, a decrease of this magnitude
in body weight gain during pregnancy is considered to be lexicologically significant. Average
daily drinking water consumption was reported as 38 mL/day in treated rats as compared with 46
61 DRAFT - DO NOT CITE OR QUOTE
-------
mL/day in control rats; this difference was not reported as statistically significant, but it was
unclear from the publication whether a statistical analysis was performed.
Table 4-8. Selected data for fetal anomalies, showing dose-related trends
following exposure of female Long-Evans rats to TCA on GDs 6-15
Type
Dose (mg/kg-day)
0
330
800
1200
1800
Malformations: mean % fetuses affected per litter ± SD (number of litters affected/number examined)3
Total soft tissue (visceral)
Cardiovascular
3.50 ±8.7
(4/26)
0.96 ±4.9
(1/26)
9.06 ± 12.9b
(8/19)
5.44 ± 10.0b
(6/19)
30.37 ±28.1b
(15/17)
23.59±28.0b
(12/17)
55.36 ±36.1b
(12/14)
46.83 ±36.5b
(11/14)
96.88 ± 8.8b
(8/18)
94.79 ± 9.9b
(8/8)
Levocardia: number of fetuses or litters affected/number examined0
Fetal incidence
Litter incidence
0/196
0/26
9/151
6/19
20/111
12/17
24/69
10/14
17/22
7/8
Intraventricular septal defect: number of fetuses or litters affected/number examined0
Fetal incidence
Litter incidence
0/196
0/26
0/151
0/19
6/111
4/17
3/69
3/14
5/22
5/8
Fetal crown-rump length (cm): mean± SDd
Male
Female
3.71 ±0.12
3.64 ±0.15
3.58±0.10b
3.53±0.09b
3.46±0.10b
3.38±0.12b
3.36±0.15b
3.33±0.16b
3.16±0.12b
3.15±0.15b
Mean fetal body weight (g): mean ± SD°
Male
Female
3.70 ±0.24
3.54 ±0.20
3.20±0.26b
3.08±0.27b
2.98±0.17b
2.83±0.18b
2.74±0.30b
2.67 ± 0.29b
2.49±0.16b
2.36±0.15b
"Table 5 of Smith et al. (1989).
bMean is significantly different from control mean (p < 0.05) as reported by Smith et al., 1989.
"Table 6 of Smith et al. (1989).
dTable 4 of Smith et al. (1989).
Statistically significant increases were reported in average number of resorption sites
(2.7 resorptions/litter in treated animals, compared with 0.7 in the controls), total number of
resorptions (30 resorptions reported among 11 treated females as compared with 40 resorptions
among 55 control females), and average number of implantation sites (defined as sites where the
fetus was implanted but did not mature) (1.1 implantation sites/litter, compared with 0.2 in the
controls). In treated groups, the total number of fetuses reported was 115 in 11 rats, resulting in
an average number of fetuses/litter of 10.5. In the control group, the total number of fetuses was
reported as 605 in 55 rats, with an average number of fetuses/litter of 11.3. These differences
were not reported as statistically significant. The number of maternal rats with abnormal fetuses
was 7 out of 11 for TCA-treated animals as compared with 9 out of 55 for controls. No
significant differences were reported in the numbers of live or dead fetuses, fetal weight,
placental weight, fetal crown-rump length, fetal external morphology, or fetal gross external or
noncardiac internal congenital abnormalities; however, data for these endpoints were not
reported in the paper and could not be independently assessed.
62 DRAFT - DO NOT CITE OR QUOTE
-------
Cardiac abnormalities were evident in 10.5% of the fetuses in the TCA group, compared
with 2.15% of the controls. Although these results were not reported in terms of the more
appropriate measure of number of affected litters, the study authors stated that the incidence of
cardiac malformations was significantly greater in treated rats as compared with control rats on
both a per-fetus basis (p = 0.0001) and a per-litter basis (p = 0.0004). Complete fetal
examinations for internal or skeletal abnormalities were not conducted, and the study is limited
by the small size of the exposed group and the use of only one dosed group. Based on the
lexicologically significant decrease in maternal body weight, 291 mg/kg-day is considered to be
a maternal LOAEL. Based on an increase in cardiac malformations occurring at a maternally
toxic dose, the developmental LOAEL is 291 mg/kg-day. A limitation of this study is that
maternal and developmental NOAELs could not be determined because adverse effects were
observed at the only dose tested.
In contrast to the results of Smith et al. (1989) and Johnson et al. (1998), Fisher et al.
(2001) did not observe significant differences in the fetal or litter incidence of heart
malformations following administration of neutralized TCA in distilled water to groups of
pregnant Sprague-Dawley rats (n = 19). Doses of 0 or 300 mg/kg-day were given by oral gavage
on GDs 6-15. Vehicle control animals (n = 19) received distilled water. Positive control
animals (n = 12) received all-trans retinoic acid (15 mg/kg-day) dissolved in soybean oil. On
GD 21, body weight, uterine weight, number and viability of fetuses, and number of
implantation and resorption sites were recorded for each pregnant animal. All treated rats were
then sacrificed, full term fetuses were removed, and the following parameters were recorded:
sex, fetal weight (per fetus and per litter), percent of dams with an early resorption, and number
of fetuses per dam. The heart of each full-term fetus was thoroughly examined in situ and then
removed, sectioned, and microscopically examined for cardiac malformations using a detailed
cardiac microdissection technique that included staining of fetal heart tissue for detection of
malformations.
The single dose evaluated produced maternal toxicity as indicated by decreased body
weight gain from GDs 7-15 and 18-21 (p < 0.05, approximately 17% relative to controls).
Mean uterine weight was significantly less than controls (p < 0.05, 9%). The number of
implantations, percent of dams with an early resorption, and number of fetuses per litter were
similar to control values. Mean fetal body weight (per litter and per fetus) on GD 21 was
significantly less than that of controls (p < 0.05, approximately 8%). The heart malformation
incidence in the TCA-treated group was similar to controls; 3.3% (9/269) of the fetuses and 42%
(8/19) of the litters from TCA-treated animals were affected compared with 2.9% (8/273) of
fetuses and 37% (7/19) of litters from control animals. Maternal exposure to the positive control
(trans retinoic acid) significantly increased the incidence of cardiac defects when analyzed on a
per fetus (32.9%) or per litter basis (92%) when compared with the corresponding soybean oil
63 DRAFT - DO NOT CITE OR QUOTE
-------
vehicle fetal and litter control incidences (6.5% and 52%, respectively). These data identify a
maternal LOAEL of 300 mg/kg-day based on significantly reduced body weight gain and uterine
weight. A developmental LOAEL of 300 mg/kg-day was identified, based on significantly
reduced mean fetal body weight on a per litter and per fetus basis. Maternal and developmental
NOAEL values were not identified in this single dose study because adverse effects were noted
at the only dose tested.
Singh (2005a; 2005b;2006) treated pregnant inbreded Charles Foster rats ( 6-12 rats/dose
group; control group = 25) with 0, 1000, 1200, 1400, 1600, or 1800 mg/kg-day TCA via oral
gavage on gestation days (GD) 6-15 and examined the effect of TCA on the developing testis
(Singh, 2005a), developing ovary (Singh, 2005b), and developing brain (Singh, 2006). TCA was
neutralized by sodium hydroxide to pH 7.0-7.5 before administration to rats. Control animals
received distilled water via oral gavage. The pregnant rats were euthanized on GD 19, and the
fetuses and placenta were collected for examination. The testes of each pup of different dose
groups were dissected out, weighed, and subjected to histological examination (Singh, 2005a).
Percentage of post implantation loss was significantly increased in a dose-related manner (22%
at 1000 mg/kg-day vs 3% for control group). No external abnormalities were observed. The
average weights of the fetal testes were significantly reduced when compared to the control, at
1200 mg/kg-day and higher. Histological examination of fetal rat testes of the 1200 mg/kg-day
dose group revealed a reduction in the diameter of the seminiferous tubules, which only
occupied the peripheral region. This effect was more pronounced in the higher dosed groups.
Examination of the testes at higher magnification revealed increased apoptosis of the gonocytes
as well as the sertoli cells within the seminiferous tubules in comparison to the controls at 1200
mg/kg-day and higher.
The rat fetal ovaries of each pup of different dose groups from the above study was also
dissected out, weighed, and subjected to histological examination (Singh, 2005b). The average
weights of the ovaries were significantly reduced for the dose groups >1400 mg/kg-day.
Histological examination of the fetal ovaries showed small size cells with less prominent nuclei
at the coelomic epithelium with >1400 mg/kg-day TCA. The cortical cords proliferating from
the coelomic epithelium traversing the gonads were either shortened or lacking. Oocytes in the
ovarian stroma showed shrinkage in size with distorted cell membrane and indistinct nucleus,
suggestive of cell apoptosis. The number of oocytes and the size of ovary were reduced. Singh
(2005b) suggested the gonadal changes were due to anoxia and oxidative stress resulted from
TCA exposure.
The rat fetal brains of different dose groups from the above study was evaluated (Singh,
2006). Maternal weight gains were decreased at TCA doses > 1200 mg/kg-day (38% at 1200
mg/kg-day). Mean fetal weight and fetal brain weight decreased significantly at TCA doses
>1000 mg/kg-day; while the length of the fetal brain increased significantly at 1000 and 1200
64 DRAFT - DO NOT CITE OR QUOTE
-------
mg/kg-day (about 10% at 1000 mg/kg-day), but decreased significantly (8-16%) at TCA doses >
1400 mg/kg-day when compared with controls. At doses >1000 mg/kg-day, the fetal brains
showed hydrocephalus with breech of the ependymal lining, altered choroids plexus architecture,
and increased apoptosis. Vacuolation of the neutropil was a prominent feature with TCA
exposure, with an incidence of 26% at 1000 mg/kg-day (0% in controls), and reached 100% in
the 1600 and 1800 mg/kg-day dose groups. The incidence of brain hemorrphages increased to
30% at TCA doses > 1200 mg/kg-day (0% in controls), and reached 100% at 1800 mg/kg-day.
The infarcts were mainly concentrated in the periventricular zone. Singh (2006) concluded the
rat fetal brain was susceptible to the toxic effects of TCA.
In a study that evaluated if trichloroethylene, TCA and DC A affect eye development in
the Sprague-Dawley rat (Warren et al., 2006), pregnant Sprague-Dawley Crl:CDR (SD) BR rats
were administered on GD 6-15 300 mg/kg-day TCA by gavage. M\-tram retinoic acid (RA) (15
mg/kg-day) was used as a positive control. A subset of the fetuses evaluated in the Fisher et al.
(2001) study was selected for ocular examination [1185 fetuses (71%) from 108 dams]. The
number of fetuses undergoing ocular examination was reduced further to approximately 30%
compared to the cardiac study. Heads of GD 21 days fetuses were fixed in Bouin's solution,
examined for gross external malformations, sectioned, and subjected to computerized
morphometry. For detection of subtle eye anomalies, the following measurements on head
sections were determined: interocular distance, total area of the cut surface, areas of left and
right lenses, and areas of left and right globes.
Mean fetal body weight was statistically significantly reduced in the TCA and RA
treatment groups. Mean maternal body weight was also reduced in these treatment groups, but
the reduction was not significant (Warren et al., 2006). Fetuses with exencephaly or micro-
/anophthalmia were found only in the RA treatment group. Mean fetal lens and globe areas were
statistically significantly reduced in the RA treatment group. However, mean lens, globe areas,
mean medial canthus and interocular distances were reduced by only 1-9 %, and the reductions
were not statistically significant. Thus, TCA did not appear to affect eye development in the
Sprague-Dawley rat at 300 mg/kg-day.
Collier et al. (2003) investigated the effects of TCA on gene expression in embryos
collected on GDs 10.5-11 from pregnant Sprague-Dawley rats exposed to 27.3 or 2.75 mg/mL
(100 or 10 mM) TCA in drinking water on GDs 0-11. The objective of the study was to identify
altered expression of genes (using a subtractive hybridization technique) that might be used as
markers of exposure to TCE or its metabolites (i.e., TCA) in the developing rat heart, such that
these genes may be used to explain the gross cardiac effects associated with exposure. Exposure
to TCA down-regulated rat ribosomal protein S10 (a housekeeping gene) and rat chaperonin 10
(a stress response gene) and up-regulated rat Ca2+-ATPase (a calcium-responsive gene) and rat
gClqBP (function not reported). The expression of the up-regulated genes was found to be
65 DRAFT - DO NOT CITE OR QUOTE
-------
strongly cardiac-specific at E10.5-E11. However, no correlation between up-regulation of these
genes and occurrence of TCA-mediated cardiac defects has yet been identified.
4.3.2.2. Inhalation Developmental Studies
No studies on the developmental toxicity of TCA were identified for exposure by the
inhalation route.
4.3.2.3. In Vitro Studies
TCA has also been tested in a number of alternative screening assays for assessment of
developmental toxicity. Hunter et al. (1996) conducted a 24-hour exposure of 3-6 somite staged
CD-I mice embryos to 11 haloacetic acids, including TCA. TCA was tested at concentrations of
0, 0.5, 1, 2, 3, 4, or 5 mM. Effects on neural-tube development (NTD) were observed at
concentrations lower than effects on other morphological processes. Other statistically
significant dysmorphology included eye defects, pharyngeal-arch defects, and heart defects.
TCA produced abnormal embryonic development at concentrations greater than or equal to
2 mM, with a very steep dose-response slope from 2 to 5 mM. No adverse effects were observed
at 1 mM or below, and defects of the eyes, arches, and heart were seen only in embryos that also
had very high rates of NTD abnormalities. The observed effects did not result from low pH in
the culture medium, since they were not seen when HC1 was added to adjust the culture medium
to similar pH values.
The potential developmental toxicity of TCA was studied in vitro using a rat whole-
embryo culture system by Saillenfait et al. (1995). Groups of 10 to 20 explanted embryos from
Sprague-Dawley rats on GD 10 were cultured for 46 hours in 0, 0.5, 1, 2.5, 3.5, 5, or 6 mM
TCA. TCA induced statistically significant, concentration-related decreases in the growth and
development parameters of conceptuses. Yolk sac diameter was significantly decreased,
beginning at a concentration of 1 mM. Other developmental measures, including crown-rump
length, head length, somite (embryonic segment) number, protein content, and DNA content,
were significantly decreased beginning at 2.5 mM and above. The total number of malformed
embryos was increased beginning at 2.5 mM. At 2.5 mM, 55% of the embryos had brain defects,
50% had eye defects, 32% had reduced embryonic axes, 55% had reductions in the first
branchial arch, and 36% had otic (auditory) system defects.
TCA has also been evaluated in developmental toxicity screening assays in
nonmammalian systems. TCA was evaluated using the FETAX assay in a study that assessed
the developmental toxicity of TCE and its metabolites (Fort et al., 1993). Early Xenopus laevis
embryos were exposed to a range of TCA concentrations for 96 hours. The culture stock solution
was buffered to pH 7.0. The median lethal concentration was 4060 mg/L and the median
effective concentration (ECso) for malformations was 1740 mg/L. Malformations were observed
66 DRAFT - DO NOT CITE OR QUOTE
-------
at concentrations greater than 1500 mg/L and included gut miscoiling, craniofacial defects,
microophthalmia, microencephaly, and various types of edema.
Fu et al. (1990) studied the developmental toxicity potential of TCA by using a
regeneration assay from reaggregated Hydra attenuata cells. The hydra system is an in vitro
assay that determines the degree to which a test chemical can perturb embryonic development at
maternally subtoxic doses and thus is considered to be useful as a prescreening assay for
developmental toxicity (Fu et al., 1990). In this study, both intact adult hydra and artificial
"embryos" (pellets of the disassociated and randomly reaggregated, terminally differentiated and
pluripotent stem cells of hydra) were treated with TCA at concentrations ranging from 10"3 to
103 mg/L. The minimal effective toxic concentration for adults (A) and artificial embryos (D)
were determined, and the A/D ratio was evaluated as a developmental-toxicity hazard index.
The TCA treatment resulted in an A/D ratio of 1.0. This result suggested that the developing
hydra are no more sensitive to TCA than adult hydra and indicates that in this test system TCA
does not selectively interfere with embryonic development at adult subtoxic doses. According to
the authors (Fu et al., 1990), the hydra system is designed to overestimate developmental hazard
potential and is considered to be more sensitive to developmental toxicity than most in vitro
mammalian test systems; its primary utility is to identify compounds for in vivo developmental
toxicity testing. Based on these results, TCA would not be considered a high-priority compound
for further testing in vivo.
4.4. OTHER ENDPOINT-SPECIFIC STUDIES
4.4.1. Immunological Studies
The available information on the potential for TCA to affect the immune system is
limited. Mather et al. (1990) (described in Section 4.2) did not observe any effects on several
immunotoxicity parameters, including antibody production, delayed hypersensitivity, natural
killer cell cytotoxicity, and production of PGE2 and IL-2 in male Sprague-Dawley rats (10
males/dose) exposed to TCA in drinking water at up to 355 mg/kg-day for 90 days. However,
Tang et al. (2002) reported that TCA was positive in the guinea pig maximization test. A 58%
sensitization rate (7/12) was observed in animals given an intradermal injection (2% solution)
and topical application (5% solution), then challenged with a topical application of a 2% TCA
solution 21 days after the first intradermal induction. The following scale was used to grade the
reactions: 0 = no reaction, 1 = scattered mild redness, 2 = moderate and diffuse redness, and 3 =
intensive erythema and swelling. The mean score for redness in this study was 1.1, and the mean
score for swelling was 0.0. Histologic examination of the affected skin revealed that TCA
induced allergenic transformation. These limited data suggest that TCA could induce a mild
allergenic response upon exposure to sub-irritating doses.
67 DRAFT - DO NOT CITE OR QUOTE
-------
4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE OF
ACTION
4.5.1. Mechanistic Studies
Several studies have been conducted for the primary purpose of evaluating the potential
mechanisms by which TCA induces tumors in laboratory animals. These studies can be divided
into four types: oncogene activation, cell proliferation, DNA hypomethylation, and inhibition of
intercellular communication. Histochemical properties of TCA-induced tumors have also been
characterized in a number of studies, and these properties have been compared with the same
properties in DCA-induced tumors in order to compare the potential mechanisms of tumor
induction. A number of studies have also been conducted that evaluated the induction of
peroxisome proliferation by TCA; these studies are described in Section 4.2.
4.5.1.1. Oncogene Activation
Ferreira-Gonzalez et al. (1995) studied the K- and H-ras proto-oncogene mutation
patterns in TCA-induced tumors in male B6C3Fi mice. The ras gene encodes a plasma
membrane-bound guanosine triphosphatase (GTPase). This GTPase activates kinase cascades
that regulate cell proliferation. The ras gene was studied because changes in the rate and
spectrum of mutations in the ras proto-oncogene have been linked to the carcinogenic
mechanism of various liver carcinogens.
Mice (number per group not reported) were exposed to 0 or 4500 mg/L (1080 mg/kg-day
based on default water intake values in U.S. EPA, 1988) TCA in drinking water for 104 weeks.
The incidence of liver carcinomas was 19% in the untreated mice and 73.3% in the TCA-
exposed group. DNA samples were extracted from 32 spontaneous liver tumors from the control
group and from 11 liver tumors in mice treated with TCA. DNA samples containing point
mutations in exons 1, 2, and 3 of the K- and H-ras genes were detected by the presence of single-
stranded conformation polymorphisms (SSCPs). The SSCP analysis involved amplification of
DNA from the control or tumor tissue to generate DNA fragments containing normal or mutated
ras gene fragments. Since single-stranded DNA fragments containing base-pair changes have
different mobilities when run in polyacrylamide gels (gel electrophoresis), the pattern of bands
observed following gel electrophoresis served to indicate the presence of a mutated base.
In the spontaneous tumors from control mice, ras mutations were detected only at the H-
61 codon (i.e., the mutation was in the H-ras gene, in the 61st codon, which is in the second
exon); 58% of the spontaneous liver carcinomas showed mutations in H-61, compared with 45%
of the tumors from TCA-treated mice. One TCA-induced tumor showed a mutation in K-61
(i.e., in the K-ras gene, in the second exon). Identification of the specific base-pair change was
done by sequencing of the DNA fragment obtained in the SSCP analysis. Comparative sequence
analysis of exon 2 mutations from spontaneous and TCA-induced tumors revealed that mutations
detected in the TCA tumors matched the mutation spectrum seen in the spontaneous tumors from
68 DRAFT - DO NOT CITE OR QUOTE
-------
control mice. Therefore, TCA changed neither the rate of ras mutations nor the type of
mutations occurring at codon 61.
These results were confirmed in a more recent study. Bull et al. (2002) (described in
Section 4.2) exposed male B6C3Fi mice (20-40/group) at 125-500 mg/kg-day in the drinking
water for 52 weeks. A decrease in the mutation frequency in H-ras codon 61 in TCA-induced
tumors compared with spontaneous tumors from control animals was observed, confirming the
observations of Ferreira-Gonzalez et al. (1995). Also, the type of H-ras codon 61 mutations was
similar to the spectra of mutations observed in spontaneous tumors from control animals.
Based on the absence of an effect on mutation rate, the authors indicated that it was not
clear if TCA was acting through a genotoxic or nongenotoxic mechanism (Ferreira-Gonzalez et
al., 1995). However, the number of tumors with ras mutations was slightly decreased in TCA-
treated animals, consistent with TCA acting through a nongenotoxic mechanism. Because of the
large proportion of tumors carrying a ras mutation, the authors concluded that ras mutations are
important for the development of carcinogen-induced as well as spontaneous tumors. TCA
increased the tumor yield but did not change mutations in ras, leading the study authors to
conclude that TCA might facilitate the growth of preneoplastic lesions that arise from
spontaneously initiated (i.e., ras mutated) hepatocytes.
The authors further suggested that TCA was not enhancing growth of preneoplastic
lesions through increased cell proliferation, since TCA has not been demonstrated to be
mitogenic, a statement the authors based on the results of DeAngelo et al. (1989). More recent
studies seem to confirm this result. Although TCA might induce hepatocyte proliferation
following short-term dosing in mice (Stauber and Bull, 1997; Dees and Travis, 1994), chronic
exposure of mice to TCA decreased normal hepatocyte proliferation and the high proliferation
rate in AHF was not TCA-dependent (Stauber and Bull, 1997).
As an alternative to increased cell-growth signaling to explain enhanced growth of pre-
initiated cells, Ferreira-Gonzalez et al. (1995) suggested that TCA might be blocking pathways
that suppress cell growth, such as intercellular communication (Benane, 1996; Klaunig et al.,
1989). Another possible nongenotoxic mechanism might be mediated by increased peroxisomal
proliferation, which, based on current knowledge of other peroxisomal proliferators, has an
inhibitory effect on apoptosis that might facilitate the growth of initiated cells (Stauber and Bull,
1997).
Tao et al. (1996) investigated whether liver tumors initiated by MNU and promoted by
TCA exhibited loss of heterozygosity (LOH) in four polymorphic loci on chromosome 6.
According to the authors, inactivation of one or more of the polymorphic alleles at these loci
may be related to the inactivation of an, as yet, unidentified tumor-suppressor gene, resulting in
oncogene activation that may be a key event in the pathogenesis of some liver tumors. This
hypothesis is supported by the results of a study by Davis et al. (1994), in which 20% of hepatic
69 DRAFT - DO NOT CITE OR QUOTE
-------
tumors induced by perchloroethene exhibited LOH on chromosome 6, suggesting the presence of
a tumor suppressor gene at this site. In this study, 15-day-old female B6C3Fi mice were
pretreated with 25 mg/kg MNU via i.p. injection and administered TCA in drinking water at a
concentration of 20.0 mmol/L (3268 mg/L) for 52 weeks. The authors did not provide a dose
estimate, but the approximate dose is 784 mg/kg-day, based on the default drinking water-intake
value for female B6C3Fi mice (U.S. EPA, 1988). Thirty-seven liver tumors promoted by TCA
were examined for LOH by using four polymorphic loci on chromosome 6. Ten of 37 tumors
(7/27 carcinomas and 3/10 adenomas) promoted by TCA showed evidence of LOH for at least
two loci on chromosome 6. The C57BL/6J alleles at both the D6mit9 and D6mit323 loci were
lost in all 10 tumors exhibiting LOH, and 2 of these 10 tumors also lost at least one of the
C3H/HeJ alleles. No LOH on chromosome 6 was observed in 24 DCA-promoted liver tumors.
The observed LOH on chromosome 6 in many of the tumors suggests the presence of an
unidentified tumor-suppressor gene on this chromosome. However, as the majority of tumors in
TCA-treated mice did not exhibit LOH on chromosome 6, the authors concluded that other
molecular activity is probably involved in the hepatocarcinogenesis of TCA.
4.5.1.2. Cell Proliferation
Investigations of the effects of TCA on cell growth rates have produced conflicting
results. Miyagawa et al. (1995) examined the effect of TCA (and a battery of putative
nongenotoxic liver carcinogens and noncarcinogens) on replicative DNA synthesis (RDS), to
assess the utility of measurement of cell proliferation as a screening assay for detecting
nongenotoxic carcinogens. Groups of male B6C3Fi mice (four or five per dose) were
administered a single oral gavage dose of TCA in an acute toxicity test to determine the MTD.
The MTD for TCA was reported to be approximately one-half of the LDso. Groups of four or
five animals were administered a single oral gavage dose of one-half of the MTD (250 mg/kg, as
estimated from data provided by the authors) or the MTD (500 mg/kg, as estimated from data
provided by the authors) and incorporation of [3H]thymidine in harvested hepatocytes was
measured 24, 39, or 48 hours after dosing. For TCA, positive responses were observed at
250 mg/kg at 24 and 39 hours (6.5- and 4.9-fold above controls) and at 500 mg/kg (9.8-fold
above controls). Although the mean increase in RDS met the criteria for a positive response, the
increases did not appear to be statistically significant, based on the standard deviations supplied
in the summary table.
In contrast to the increased cell proliferation observed by Miyagawa et al. (1995),
Channel and Hancock (1993) found that TCA can decrease the rate of progression through S-
phase of the cell cycle. WB344 cells, a non-tumorigenic epithelial rat hepatocyte cell line, were
exposed to TCA-free medium or medium containing 100 |ig/mL TCA. Cell growth rates were
assessed by cell counting, and transition through the cell cycle was monitored by labeling
nascent DNA with bromodeoxyuridine (BrdU). The resulting labeling data were used to identify
70 DRAFT - DO NOT CITE OR QUOTE
-------
fractions of cells in various stages of the cell cycle and to model transit times through each
phase. The transit time through S-phase was estimated to be 5.20 hours for treated and 5.02
hours for control cells, respectively (p < 0.05). As further support for this effect, cells in S-phase
were elevated by approximately 5-20% for the first 6 hours after release from TCA-treatment
but returned to control values after this initial period. In contrast to these results indicating
slowing of S-phase transit, relative movement plots (also related to S-phase transit time) did not
differ from controls. The authors suggested, however, that this might reflect the insensitivity of
relative movement plots for detection of small treatment-related changes, such as those observed
for TCA. The authors suggested that the observed pattern of cell cycle perturbation (i.e., a
slightly extended period of S-phase), would be consistent with a sublethal effect of cytotoxicity
and would be less serious than a decrease in transit time through G2M phase (which could
potentially increase chromosomal mismatches and rearrangements, due to an insufficient time
spent in mitosis). The toxicological significance of these results by Miyagawa et al. (1995) and
Channel and Hancock (1993) are difficult to interpret, since they might not reflect the cell
growth conditions of normal hepatocytes in vivo. For this reason, these studies are of limited use
in evaluating the effects of TCA on cell growth in vivo but are summarized here for
completeness.
Pereira (1996) evaluated cell proliferation in the liver of female B6C3Fi mice (10/group)
treated with 0, 2, 6.67, or 20 mmol/L TCA for 5, 12, or 33 days by estimating hepatocyte BrDU-
labeling index. TCA increased the BrDU-labeling index after 5 days of exposure for all three
concentrations, but not for exposure of 12 days or 33 days. Thus, cell proliferation was
enhanced by 5 days exposure to TCA but not for longer exposure of 12 or more days.
In a cell proliferation study reported by Stauber and Bull (1997), male B6C3Fi mice were
pretreated with 2000 mg/L of TCA (480 mg/kg-day based on default water-intake values in U.S.
EPA, 1988) in drinking water for 50 weeks. The mice were then given drinking water
containing 0, 20, 100, 500, 1000, or 2000 mg/L TCA (estimated doses of 0, 5, 23, 115, 230, and
460 mg/kg-day, based on default water intake values in U.S. EPA., 1988) for two additional
weeks to assess whether cell proliferation induced by TCA in either normal liver cells or tumors
was dependent on continued treatment. All dose groups contained 12 animals, except for the
2000 mg/L group, which consisted of 22 mice. Five days prior to sacrifice, DNA in replicating
hepatocytes was labeled in vivo using BrdU administered via subcutaneously implanted pumps.
Liver tissue was stained, and dividing nuclei were counted. Cell division rates were evaluated
separately in normal hepatocytes, in tumors, and in AHF.
A transient but significant elevation in normal hepatocyte division rates was evident in
mice consuming 2000 mg/L TCA for 14 or 28 days (apparently as part of the pretreatment
phase), but continued treatment for 52 weeks resulted in a significant decrease in hepatocyte
division rate. In the mice treated for 50 weeks with 2000 mg/L and then shifted to the lower
71 DRAFT - DO NOT CITE OR QUOTE
-------
concentrations for 2 weeks, the cell division rate in normal liver cells was elevated (but not
statistically significantly so) at 100 and 500 mg/L, but in mice exposed to 1000 or 2000 mg/L for
2 weeks, there was a significant decrease in cell division. Cell division rates in TCA-induced
AHF and tumors were high at all doses. Rates of cell division in AHF and tumors remained high
in mice whose exposure was terminated during the last 2 weeks of the study, indicating that
these rates were independent of continued TC A treatment.
TCA-induced lesions were histochemically stained with anti-c-JIM and anti-c-FOS
antibodies, component proteins of the AP-1 transcription factor that up-regulates expression of
genes required for DNA synthesis. No differences were observed in the levels of proteins
reacting with c-JUN and c-FOS antibodies in either liver AHF or tumors, relative to normal
hepatocytes, indicating that TCA produces little, if any, direct stimulation of the replication of
initiated cells through this pathway. However, three tumors induced by TCA each contained a
nodule that stained heavily for c-FOS, and cell-division rates within these nodules were very
high, suggesting a transition to an aggressive tumor. The low frequency of this marker (3/52
tumors) suggested that its presence in these nodules was not due to a direct effect of TCA.
Based on these results, the study authors proposed a mechanism for TCA-induced
hepatocarcinogenesis. They proposed that the initial growth stimulation induced by TCA causes
normal cells to compensate by increasing signals that inhibit cell proliferation, which ultimately
results in the TCA-induced growth inhibition observed with chronic treatment. Pre-initiated
cells refractory to this growth inhibition would then have a selective growth advantage. The
authors noted that the lack of effect on c-JUN by TCA is consistent with tumor characteristics of
other peroxisome proliferators in rats (Rao et al., 1986). Because cell replication in AHF was
independent of TCA (i.e., discontinued TCA treatment did not alter AHF or tumor-cell labeling),
the authors proposed that TCA might enhance growth of initiated cells by suppressing apoptosis
in such cells, as has been demonstrated for other peroxisome proliferators and is consistent with
agonism of PPARa receptor playing an important role in TCA-induced carcinogenesis. Cell
proliferation has also been observed in several short-term studies (Dees and Travis, 1994;
Sanchez and Bull, 1990) that are described in Section 4.2. The results of these studies were
consistent with the results described by Stauber and Bull (1997).
4.5.1.3. DNA Hypomethylation
The hypomethylation of DNA in response to TCA exposure was investigated by Tao et
al. (1998) as a potential nongenotoxic mechanism involved in TCA-induced tumor promotion
and carcinogenesis. Mammalian DNA naturally contains the methylated base 5-methylcytosine
(5MeC), which plays a role in regulation of gene expression and DNA imprinting (Razin and
Kafri, 1994). An overall decrease in the content of 5MeC in DNA is often found in tumors and
has been considered to represent an important event in the clonal expansion of premalignant cells
during neoplastic progression (Counts and Goodman, 1995, 1994).
72 DRAFT - DO NOT CITE OR QUOTE
-------
In this study, female B6C3Fi mice were injected intraperitoneally with 25 mg/kg of
MNU at 15 days of age. When the mice were 6 weeks of age, TCA, neutralized to a
concentration of 25 mmol/L (4085 mg/L), was administered in drinking water for 44 weeks.
This concentration corresponds to approximately 980 mg/kg-day, based on a default water factor
of 0.24 L/kg-day for female B6C3Fi mice for chronic exposure (U.S. EPA, 1988). Control mice
received only MNU.
To test the effects of short-term treatment with TCA on DNA methylation, mice not
administered MNU were given 0 or 25 mmol/L TCA in drinking water for 11 days,
corresponding to approximately 1062 mg/kg-day, based on the strain-specific water factor for a
short-term study (U.S. EPA, 1988). DNA extracted from liver tissue and tumors were
hydrolyzed, and 5MeC and the four DNA bases were separated and quantified by HPLC.
After 11 days of exposure to TCA (without pretreatment with MNU), the level of 5MeC
in total-liver DNA was decreased (about 60%) relative to untreated controls. After 44 weeks of
TCA treatment, 5MeC levels were not different from controls that had received only MNU. No
difference in DNA methylation was observed between the control groups in the short-term
(drinking water control) and long-term (MNU only control) experiments. These results indicate
that TCA caused only a transient decrease in DNA methylation in the liver.
In TCA-promoted hepatocellular adenomas and carcinomas, the level of 5MeC in DNA
was decreased when compared with either noninvolved tissue from the same animal (40% and
51%, respectively) or liver tissue from control animals given only MNU. Termination of TCA
treatment 1 week prior to sacrifice did not change the levels of 5MeC in either adenomas or
carcinomas; however, they remained lower than in noninvolved tissue. 5MeC levels in DNA
from carcinomas were lower than in DNA from adenomas, suggesting that DNA methylation is
further decreased with tumor progression. DNA hypomethylation tends to favor gene
expression, which may drive cell-proliferation responses. Therefore, based on the change
observed in the adenomas and carcinoma tissue compared with the uninvolved tissue, the study
authors suggested that hypomethylation of DNA, as indicated by decreased 5MeC in tumor
DNA, is involved in the carcinogenic and tumor-promoting activity of TCA.
The marked increase in hypomethylated DNA in mouse liver tumors observed by Tao et
al. (1998) indicates that the methylation of numerous genes is decreased. Tao et al. (2004,
2000a, b) investigated the methylation status and expression of specific genes in mouse liver
tumors and uninvolved liver tissue, as well as in livers of mice initiated with MNU but not
exposed to TCA, in a series of studies described below.
Tao et al. (2000a) evaluated the methylation and expression ofc-jun and c-myc
protooncogenes in mouse liver after short-term exposure to TCA. Female B6C3Fi mice (four
per group) were dosed by gavage for 5 days with 500 mg/kg TCA in water neutralized with
sodium hydroxide to pH 6.5 to 7.5. This dose was selected because it was reported to increase
73 DRAFT - DO NOT CITE OR QUOTE
-------
liver growth, cell proliferation and lipid peroxidation in mice (Dees and Travis, 1994; Larson
and Bull, 1992). Vehicle-control mice received the same volume of water or corn oil. At 30
minutes after each dose of TCA or vehicle, the mice received 0, 30, 100, 300 or 450 mg/kg
methionine by i.p. injection. The mice were sacrificed 100 minutes after the last dose and the
livers excised. Methylation status in the promoter region for c-jun and c-myc protooncogenes
was evaluated using methylation-sensitive restriction endonuclease Hpall digestion, followed by
Southern blot analysis of DNA. Hpall does not cut CCGG sites when the internal cytosine is
methylated, and Southern blots probed for the promoter region of these 2 genes would only
contain extra bands in Hpall digested hypomethylated DNA. Expression of mRNA for c-jun and
c-myc protooncogenes and c-jun and c-myc proteins were also analyzed.
Decreased methylation in the promoter regions of the c-jun and c-myc genes and
increased levels of their mRNA and proteins were found in the livers of TC A-treated mice.
Methionine prevented the decreased methylation of the two genes in a dose-dependent manner,
with the effective dose >100 mg/kg. Methionine also prevented the increased levels of the
mRNA and proteins from the two genes at 450 mg/kg. Tao et al. (2000a) concluded that the
prevention of TCA-induced DNA hypomethylation by methionine suggested that the decrease in
the formation of 5-MeC in DNA is due to decrease in the concentration of S-adenosylmethionine
(SAM) as substrate, and the dose of TCA must be sufficient to decrease the level of SAM in
order for it to be active as a carcinogen.
In another study, Tao et al. (2000b) examined the methylation of c-jun and c-myc genes,
expression of both genes, and activity of DNA methyltransferase (DNA MTase) in mouse liver
tumors initiated by MNU and promoted by TCA in female B6C3Fi mice. The tumors were
obtained from test animals used in the promotion study described by Pereira and Phelps (1996)
(see section 4.2.2.1). Briefly, the test animals were given either 25 mg/kg MNU or the saline
vehicle control at 15 days of age. Starting at 6 weeks of age, animals were given neutralized
TCA in drinking water at 20.0 mmol/L (3268 mg/L) continuously until 52 weeks of age. Dose
estimates were not reported by the study authors, but the concentration provided in drinking
water would result in a dose of approximately 784 mg/kg-day based on the default drinking
water value of 0.24 L/kg-day for female B6C3Fi mice (U.S. EPA, 1988). TCA-promoted liver
tumors and noninvolved liver tissue, as well as liver tissue from MNU-initiated mice not
exposed to TCA, were collected when the animals were euthanized at 52 weeks of age.
Methylation status in the promoter regions of the c-jun and c-myc genes was determined
by Southern blot analysis of DNA extracted from the three types of harvested tissues and
digested with the methylation-sensitive restriction endonuclease Hpall. Expression of the c-jun
and c-myc genes was determined by Northern blot analysis of messenger RNA (mRNA) levels
and Western blot analysis of protein levels. DNA MTase activity was determined in nuclear
extracts prepared from the harvested liver tumors or the other two types of liver tissues described
74 DRAFT - DO NOT CITE OR QUOTE
-------
previously. The study authors concluded that the promoter regions ofc-jun and c-myc in tumors
were hypomethylated relative to the promoter regions in noninvolved liver tissue from TCA-
promoted animals. The expression of the mRNA and protein for each of these genes was also
increased in TCA-promoted tumors relative to noninvolved liver tissue. DNA MTase activity
was significantly increased in liver tumors from TCA-promoted mice when compared with
noninvolved liver from the same mice. Collectively, these results suggest that TCA-promoted
carcinogenesis involves decreased methylation and increased expression of the c-jun and c-myc
protooncogenes in the presence of increased DNA MTase activity.
In a related study, Tao et al. (2004) investigated DNA hypomethylation and the
methylation status and expression of the insulin-like growth factor (IGF-II) gene4 in TCA-
promoted mouse liver tumors and noninvolved liver tissue, as well as in liver tissue samples
from MNU-initiated mice that were not exposed to TCA. Expression of IFG-II gene was
investigated because increased hepatic cell proliferation is associated with increased expression
of growth-related genes, such as IGF-II (Furstenberger and Senn, 2002; Werner and Le Roith,
2000). Loss of imprinting4 and increased expression of IGF-II have been observed in liver
tumors. (Scharf et al. 2001; Khandwala et al., 2000).
In this study, mouse liver tumors and tissues were obtained from female B6C3Fi mice as
described above (Tao et al., 2000). At necropsy, no liver tumors were found in mice that were
treated with MNU alone or TCA alone. The levels of 5-MeC in DNA extracted from tumors and
liver tissues were quantified by a dot blot analysis procedure that used a mouse monoclonal
primary antibody specific for 5-MeC. Methylation status of 28 CpG sites5 in the differentially
methylated region-2 (DMR-2) of the mouse IGF-II gene was determined by a bisulfite-modified
DNA sequencing procedure. In this procedure, DNA extracted from tumors and liver tissues
was incubated with sodium metabisulfite to convert unmethylated (but not methylated) cytosine
to uracil to enable detection of unmethylated sites in the sequencing analysis. Bisulfite-modified
DNA was recovered and the DMR-2 region of the IGF-II gene was amplified by polymerase
chain reaction (PCR) for sequencing. Expression of IGF-II mRNA was determined by reverse
transcription PCR (RT-PCR). The level of 5-MeC in DNA from noninvolved liver tissue in
mice treated with TCA was decreased relative to that in DNA from mice initiated with MNU but
4IGF-II is involved in cell division, differentiation and apoptosis. According to information presented in
Tao et al. (2004), the IGF-II gene is imprinted with the paternal allele being expressed and the maternal allele is
methylated and silent in normal adult tissue, including the mouse liver, while in tumors the imprinting is lost. Loss
of imprinting is accompanied by increased expression of its mRNA in tumors.
5CpG sites are regions in DNA where a cytosine nucleotide (C) is situated next to a guanine nucleotide
(G). The "p" denotes the phosphodiester bond that links the nucleotides. CpG sites are relatively rare in eukaryotic
genomes except in regions near the promoter regions of genes. Methylation of the cytosine nucleotide at CpG sites
to form 5MeC is believed to play a critical role in regulation of gene expression. Decreased or hypomethylation is
associated with gene expression, while increased methylation has an inhibitory effect on gene expression. Aberrant
promoter methylation has been proposed as a possible mechanism for increased protooncogene expression in
cancer.
75 DRAFT - DO NOT CITE OR QUOTE
-------
not exposed to TCA. The level of 5-MeC in TCA-promoted tumors was further decreased
relative to the noninvolved liver tissue, indicating hypomethylation. These observations confirm
the previous results of Tao et al. (1998) for DNA hypomethylation obtained using HPLC
analysis.
Sequencing of the DMR-2 region of the IGF-II gene promoter revealed that 21 to 24 CpG
sites were methylated in initiated liver, compared with 15 to 17 sites in noninvolved liver tissue
from TCA-promoted mice. Thus, exposure to TCA reduced the percentage of CpG sites that
were methylated from approximately 79% to 58%. The number of methylated CpG sites was
further reduced to 0 to 7 (approximately 11%) in liver tumors promoted by TCA. mRNA
expression was significantly increased (5.1-fold) in liver tumors relative to noninvolved liver
tissue from mice treated with TCA. mRNA expression was not increased in noninvolved liver
tissue from TCA-promoted animals when compared to level of expression in the MNU-initiated
control. These results demonstrated that TCA treatment caused hypomethylation of DNA and of
the IGF-II gene in the noninvolved mouse liver tissue and TCA-promoted liver tumors. Thus,
the hypothesis that DNA hypomethylation is involved in the mechanism for tumorigenicity of
TCA is supported.
The temporal association of DNA methylation and cell proliferation in mice treated with
TCA has been investigated by Ge et al. (2001). Female B6C3Fi mice were given daily gavage
doses of 500 mg/kg TCA and sacrificed at 24, 36, 48, 72, and 96 hours after the first dose. (TCA
was neutralized to pH 6-7 with NaOH.) The liver, kidney, and urinary bladder were removed
and weighed, and subsamples were processed for extraction of DNA and determination of
methylation status in the promoter region of the c-myc protooncogene. Methylation status was
determined by southern blot analysis following digestion of the isolated and purified DNA with a
methyl-sensitive restriction enzyme. Liver and kidney tissue were collected for measurement of
cell proliferation by determination of proliferating cell nuclear antigen (PCNA)-labeling and
mitotic indices.
Relative liver weights were significantly increased at the 36-, 72-, and 96-hour time
points; there was no effect of TCA on relative kidney weights. The PCNA labeling index was
significantly increased in liver cells at 72 and 96 hours relative to controls. The mitotic index
was significantly elevated in liver cells at 96 hours after the first dose. Southern blot analysis
indicated that the tumor promoter region of the c-myc protooncogene in the liver was
hypomethylated at the 72 and 96 hour time points. These data indicate that TCA caused
simultaneous enhancement of cell proliferation and decreased methylation in liver cells starting
at 72 hours after exposure. TCA also decreased methylation in the promoter region of the c-myc
gene in the kidney and urinary bladder after 72 and 96 hours of treatment, but the response was
less pronounced than in liver. Cell proliferation data for the kidney were not reported. The
76 DRAFT - DO NOT CITE OR QUOTE
-------
study authors proposed that TCA induces hypomethylation by inducing DNA replication and
preventing the methylation of the newly synthesized strands of DNA.
Pereira et al. (2001) examined the effect of chloroform (a disinfection by-product present
as a co-contaminant with TCA in drinking water) on TCA-induced hypomethylation and
expression of the c-myc protooncogene in female B6C3Fi mice. Chloroform has been reported
to cause hypomethylation of DNA and of the c-myc gene by preventing the methylation of
hemimethylated DNA formed when DNA is replicated (Coffin et al., 2000). Six mice per
treatment group were exposed to 0, 400, 800, or 1600 mg/L chloroform in the drinking water for
17 days. A TCA dose of 500 mg/kg was administered daily by oral gavage on the last five days
of the exposure period. At sacrifice, livers were removed and processed for extraction of DNA.
Methylation of the promoter region was evaluated using Hpall restriction enzyme digestion
followed by Southern blot analysis. Expression of c-myc mRNA was evaluated using RT-PCR
followed by Northern blot analysis. TCA decreased methylation in the promoter region of the c-
myc gene and increased expression of c-myc mRNA. Coadministration of chloroform did not
affect the extent of TCA-induced hypomethylation or mRNA expression or the incidence or
multiplicity of liver tumors promoted by TCA. The ability of chloroform and TCA to
hypomethylate c-myc and increase c-myc mRNA expression in the liver was correlated with their
effect on liver tumor promotion.
4.5.1.4. Inhibition of Intercellular Communication
Benane et al. (1996) assessed the effects of TCA on gap junction intercellular
communication in Clone 9 (ATCC CRL 1439), a normal liver epithelial cell line from a 4-week-
old Sprague-Dawley male rat. The cells were grown in a nutrient mixture, plated, and exposed
to TCA at a range of concentrations for varying time periods. Lucifer yellow scrape-load dye
transfer was used as a measure of gap junction intercellular communication. Following an initial
screen to identify the lowest concentration at which TCA affected dye transfer, the main study
was conducted at concentrations of 0, 0.5, 1.0, 2.5, and 5 mM. Cells were treated for 1, 4, 6, 24,
48, or 168 hours. At a concentration of 0.5 mM, there were no statistically significant
differences in dye transfer among control and treated cells at any of the time points. At a
concentration of 1.0 mM, statistically significant differences were found for all time periods
except 4 and 168 hours. At concentrations of 2.5 and 5 mM, the level of dye transfer was
statistically decreased as compared with controls for all time points. The lowest concentration
and shortest time to reduce dye transfer was 1 mM over a 1-hour period. The reduction in dye
transfer increased with higher concentrations and longer treatment time. 12-O-
tetradecanoylphorbol 13-acetate (TPA), a tumor promoter and a known disrupter of intercellular
communication, used as positive control, caused a rapid reduction in dye transfer.
Klaunig et al. (1989) performed a series of experiments to determine the effects of TCA
on gap junction intracellular communication in primary cultured B6C3Fi mouse and F344 rat
77 DRAFT - DO NOT CITE OR QUOTE
-------
hepatocytes. Mouse and rat hepatocytes were isolated from 6- to 8-week-old male mice and rats
by two-stage collagenase perfusion and plated in glass petri dishes or flasks. Following
preliminary experiments to identify cytotoxic concentrations, 24-hour-old hepatocytes were
treated with 0, 0.1, 0.5, or 1 mM TCA dissolved in DMSO for up to 24 hours. The controls
included "no treatment" and solvent controls in sealed and unsealed culture vessels.
Phenobarbital was used as the positive control. Effects on gap junction intercellular
communication were evaluated by the ionophoretic microinjection of flourescent Lucifer Yellow
CH dye into one hepatocyte and observation of the dye spread to adjacent hepatocytes. Adjacent
cells that fluoresced were designated as dye-coupled (i.e., communicating through gap
junctions). The experimental results were expressed as the number of coupled/noncoupled
recipient cells and a percentage of coupled cells. TCA inhibited dye transfer in both 24-hour-old
and freshly plated mouse hepatocytes. The inhibitory effect in 24-hour-old cultures was
transient; dye-coupling was significantly reduced at all tested concentrations after 4 hours of
treatment but not after 8 or 24 hours. PB, the positive control, significantly reduced dye transfer
in cells treated with 1 or 2 mM after 4 or 8 hours of treatment but not after 8 hours. In an
experiment to compare the response of freshly plated and 24-hour-old mouse hepatocytes, all
tested concentrations of TCA significantly inhibited dye transfer in both types of culture after 3
and 6 hours of treatment. The inhibitory effect on dye transfer in mouse cells was unaffected by
treatment with SKF-525A, a cytochrome P450 inhibitor.
Dye transfer in 24-hour-old primary rat hepatocytes was unaffected by treatment with
TCA at concentrations up to ImM for as long as 24 hours. Dye transfer in freshly plated rat
primary rat hepatocytes was unaffected by treatment with concentrations up to ImM TCA for as
long as 6 hours. PB, the positive control, significantly reduced the percentage of coupled cells in
cultures treated with 1 or 2 mM after 4 or 8 hours of treatment but not after 8 hours. The results
obtained for primary F344 rat hepatocytes by Klaunig et al. (1989) differ from those reported in
rat cell cultures by Benane et al. (1996), who observed inhibition of dye transfer in cells from a
Sprague-Dawley rat epithelial cell line treated with 1 mM for durations of 1 to 168 hours. The
reason for the differential response in rat liver cells is unknown but may be related to differences
in the originating strain or in the type of cultured cell tested (primary cultured hepatocytes vs.
established cell line).
4.5.1.5. Oxidative Stress
The ability of TCA to induce oxidative-stress responses, such as lipid peroxidation and
oxidative DNA damage, and the relationship between these responses and indicators of
peroxisome proliferation or altered cytochrome P450 activities have been tested in a series of
studies following acute or short-term TCA dosing in mice (Austin et al., 1996, 1995; Parrish et
al., 1996; Larson and Bull, 1992). TCA induces both lipid peroxidation (TEARS) and oxidative
78 DRAFT - DO NOT CITE OR QUOTE
-------
DNA damage (8-OHdG) following administration of single oral doses. These studies are
described in Section 4.2.
A potential mechanism of TCA-induced oxidative stress was investigated by Hassoun
and Ray (2003). Studies are available that reported macrophages could be activated and become
a source of reactive oxygen species that may produce damage to surrounding tissues (Karnovsky
et al., 1988; Briggs et al., 1986). In this study, the ability of TCA to activate cultured
macrophages (J744A.1 cell line) in vitro to become a source of reactive oxygen species was
evaluated. Oxidative stress was evaluated by time- and concentration-dependent production of
superoxide anion (SA) in response to TCA; resulting cytotoxicity, as indicated by effects on
superoxide dismutase (SOD) activity and cell viability; and release of LDH by the cells into
cultured media. Cells were exposed to TCA at 8-32 mM for 24-60 hours (pH of TCA solution
was adjusted to pH 7.0 by NaOH).
Incubation with TCA caused a significant decrease in cell viability as assessed by trypan
blue staining at all concentrations tested, although at 8 mM cell viability was only significantly
reduced compared with controls at the 60-hour incubation. Reduced cell viability results
correlated well with increased LDH activity in media. Twenty-four hour incubation with TCA
did not cause increases in SA levels; however, incubations of 36 and 60 hours caused significant
increases in SA levels at 16, 24, and 32 mM (p < 0.05). SOD activity was also affected by TCA
treatment. Significant increases in SOD activity occurred at lower TCA concentrations (8-24
mM) compared with controls, but SOD activity at the highest concentration (32 mM) for 24-36
hour was similar to controls. Incubation of cells with 32 mM TCA for 60 hours resulted in 100%
cell death. These results indicate that incubation with TCA at 8-32 mM for 24-60 hours induces
macrophage activation, which resulted in cytotoxicity due to oxidative stress. The study authors
noted that, although TCA exposure concentrations were high, they were comparable to those
used in animal studies (Austin et al., 1996; Larson and Bull, 1992; Bull et al., 1990; Sanchez and
Bull, 1990).
4.5.1.6. Histochemical Characteristics of TCA-induced Tumors
Biomarkers of cell growth, differentiation, and metabolism in proliferative hepatocellular
lesions promoted by TCA were investigated by Latendresse and Pereira (1997) to further
determine differences in DCA and TCA carcinogenesis. Female B6C3Fi mice were initiated
with an i.p. injection of MNU at 15 days of age and treated with TCA in drinking water at a
concentration of 20 mmol/L from age 49 days to age 413 days. The authors did not provide a
dose estimate, but the approximate dose is 784 mg/kg-day, based on the default drinking water
intake value for female B6C3Fi mice (U.S. EPA, 1988). At 413 days of age, the mice were
sacrificed and liver tissues were examined histologically. A panel of histochemical markers was
evaluated, including TGF-a (a transforming growth factor that stimulates cell proliferation and is
expressed in tumor cells), TGF-P (a transforming growth factor that is inhibitory to hepatocyte
79 DRAFT - DO NOT CITE OR QUOTE
-------
proliferation), c-JUN and c-FOS (component proteins of the AP-1 transcription factor that
regulates expression of genes involved in DNA synthesis), c-MYC (a regulator of gene
transcription induced during cell proliferation), the cytochrome P450s CYP2E1 (potentially
involved in TCA metabolism) and CYP4A1 (induced by peroxisome proliferation signaling),
and GST-Ti (a marker for certain tumor types).
TCA-induced foci of altered hepatocytes and tumors tended to be predominantly
basophilic and stained variably for the histochemical markers examined. In TCA-treated mice,
none of the markers stained positive in more than 50% of the cells/tumor, except c-JUN, which
was observed in greater than 50% of cells from 9 of the 13 tumors evaluated. This profile of
marker expression contrasts with the tumors from DCA-treated mice for which more than half of
the examined tumors expressed TGF-a, c-MYC, CYP2E1, CYP4A1, and GST-7i in greater than
50% of the cells. The contrasting histochemical-marker profiles, induced by DCA and TCA,
provide evidence for a different MOA for these two haloacetic acids. In a recent study, Bull et
al. (2002) (described in Section 4.2) observed that TCA-induced tumors were uniformly lacking
c-Jun expression, but DCA-induced tumors often expressed c-Jun, providing further evidence of
a different MOA for TCA and DCA induction of liver tumors.
In the case of the TCA-promoted tumors, the minimal immunostaining for most markers
(with the exception of c-JUN) suggested that these proteins are not particularly important in
TCA-induced tumor promotion. On the other hand, Latendresse and Pereira (1997) pointed out
that the regional staining variability within the lesions for c-JUN and c-MYC proteins is
consistent with localized clonal expansion and/or tumor progression. Non-tumor hepatocytes in
TCA-treated animals were generally negative for TGF-P and GST-u staining and positive for
CYP2E1 (centrilobular region) and CYP4A1 (panlobular region). CYP4A1 is an enzymatic
marker for peroxisome proliferation, since its expression precedes peroximal response, and is
coordinated with the transcription of the peroxisomal p-oxidation enzymes. The expression of
CYP4A1 in normal hepatocytes in TCA-treated animals is consistent with TCA-induced
peroxisome proliferation. However, CYP4A1 was not highly expressed in the tumor cells. This
result suggests that, if PPARa agonism is involved in TCA-induced cancer, it is likely that the
effect occurs earlier in the tumorigenic process than was evaluated in this study.
Pereira (1996) studied the characteristics of the lesions in female B6C3Fi mice to
evaluate differences in MOA of DCA and TCA. AHF and tumors induced by DCA were
reported as being predominantly eosinophilic. AHF induced by TCA were equally distributed
between basophilic and eosinophilic; whereas hepatic tumors induced by TCA were
predominantly basophilic, including all observed hepatocellular carcinomas (n=l 1), and lacked
GST-71 expression. These characteristics for TCA-induced tumors were also reported by Pereira
et al. (1997) (described in Section 4.2). Tumors in control mice were also mostly basophilic or
mixed basophilic and eosinophilic. Since comparable numbers of the foci of TCA-treated
80 DRAFT - DO NOT CITE OR QUOTE
-------
animals were basophilic and eosinophilic, the author suggested that the basophilic foci induced
by TCA treatment may be more likely to progress to tumors.
The author also evaluated cell proliferation following 5, 12, or 33 days of treatment with
TCA. TCA increased the BrdU-labeling index after 5 days of exposure but not after the longer
exposure durations; the degree of increase was similar for all three of the doses tested. The
authors found that the tumorigenic activity of TCA was linearly related to the concentration in
drinking water. Bull et al. (1990) (described in Section 4.2) also observed this linear
relationship. Based on differences in the shape of the tumor dose-response curve and staining
characteristics of tumors, the author concluded that DC A and TCA act through different
mechanisms. The characteristics of the foci and tumors induced by TCA were described as
being consistent with the predominant basophilic staining observed in tumors induced by
peroxisome proliferators, suggesting that this pathway might be involved in the observed
hepatocarcinogenicity of TCA.
Similarly, Bull et al. (1990) (described in Section 4.2) also presented evidence that the
mechanisms of TCA and DCA carcinogenesis are different. In this study, DCA-treated mice
showed marked cytomegaly, substantial glycogen accumulation, and necrosis of the liver. The
dose-response relationship between proliferative liver lesions and DCA treatment followed a
"hockey stick" pattern. In contrast, these effects were either minimal or absent in TCA-treated
mice and accumulation of lipofuscin (an indication of lipid peroxidation) was observed only in
TCA-treated mice. In contrast to the dose-response curve for DCA, the dose-response curve for
TCA and proliferative lesions was linear. Based on these data, the authors suggested that DCA
may induce tumors by stimulating cell division through cytotoxicity, while TCA may induce
tumors via lipid peroxidation.
4.5.2. Genotoxicity Studies
4.5.2.1. In Vitro Studies
TCA has been evaluated in a number of in vitro test systems (Table 4-9). The
mutagenicity of TCA has been assessed in several variations of the Ames test. Among the
strains that have been evaluated (i.e., TA98, TA100, TA104, TA1535, and RSJ100), the
available studies have produced mixed results. Rapson et al. (1980) reported negative results for
TCA in strain TA100 in the absence of metabolic activation (S9). Similarly, Nelson et al. (2001)
reported negative results in strain TA104 with or without addition of S9 or rat cecal homogenate.
In an assay designed to investigate the genotoxicity of the volatile organic solvent
tetrachloroethylene and its metabolites, TCA was also negative in Salmonella typhimurium
TA100 at up to cytotoxic concentrations (600 ppm without S9, and -80 ppm with S9). The
assay utilized the vaporization technique, which permits the evaluation of volatile agents as
vapors within a closed system (DeMarini et al., 1994). In this system, agar cultures on petri
81 DRAFT - DO NOT CITE OR QUOTE
-------
dishes were inserted into a sealed Tedlar bag, and various amounts of the test compound were
injected through a septum on the bag into the inverted top of the petri dish. In a more recent
study by Kargalioglu et al. (2002), TCA (0.1-100 mM) was not mutagenic when tested in TA98,
TA100, and RSJ100 with or without S9.
In contrast, Giller et al. (1997) reported that TCA demonstrated mutagenic activity in an
Ames fluctuation test in S. typhimurium TA100 in the absence of S9 at noncytotoxic
concentrations ranging from 1750 to 2250 |ig/mL. The addition of S9 decreased the mutagenic
response, and genotoxic effects were observed at 3000-7500 |ig/mL. Cytotoxic concentrations
in the Ames fluctuation assay were 2500 and 10,000 |ig/mL without and with microsomal
activation, respectively. Similarly, TCA induced a weak increase in "SOS DNA repair" (an
inducible error-prone repair system) in S. typhimurium strain TA1535 in the presence of S9 (Ono
etal., 1991).
In other bacterial test systems, TCA was negative in the SOS chromotest (which
measures DNA damage and induction of the SOS repair system) mEscherichia coli PQ37, +/-
S9 (Giller et al., 1997). The test evaluated concentrations of TCA ranging from 10 to 10,000
|ig/mL. Similarly, TCA was not genotoxic in the Microscreen prophage-induction assay in E.
coli with TCA concentrations ranging from 0 to 10,000 |ig/mL, with and without S9 activation
(DeMarini etal., 1994).
Table 4-9. Summary of available genotoxicity data on TCA
Endpoint
Test system
Metabolic
activation
Concentration/Dose
Results
Reference
In vitro studies
Reverse
mutations
S. typhimurium (TA98)
S. typhimurium
(TA100)
S. typhimurium
(TA100)
S. typhimurium
(TA104)
S. typhimurium TA100
(TCA vapors were
tested in a closed
system)
S. typhimurium TA100
(fluctuation assay)
+/-
+/-
-
+/-
+/-
+/-
10-80 mM
5-100/0.5-80 mM
0.1-1000 jig/plate
1 mg/mL
0-600 mg/L
+ S9: 3000-7500
ug/mL; -S9: 1750-
2250 ug/mL
Negative
Negative
Negative
Negative
Negative
Positive,
addition of S9
decreased
mutagenicity
Toxic
concentration:
10,000 ug/mL
with S9; 2500
Ug/mL
without S9
Kargalioglu
et al., 2002
Kargalioglu
et al., 2002
Rapson et
al., 1980
Nelson et
al., 2001
DeMarini et
al., 1994
Giller et al.,
1997
82
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-9. Summary of available genotoxicity data on TCA
Endpoint
Test system
Metabolic
activation
Concentration/Dose
Results
Reference
In vitro studies
Prophage
induction
SOS repair
induction
SOS
chromotest
Forward
mutations
Chromosomal
aberrations
Chromosomal
damage
DNA strand
breaks
S. typhimurium
RSJ100
E. coli Microscreen
assay
S. typhimurium
(TA1535)
E. coli (PQ37)
Cultured mammalian
cells (L5178Y/TK+/-
mouse lymphoma cells)
Mouse lymphoma cells
Cultured human
peripheral lymphocytes
CHO AS52 cells
+/-
+/-
+
+/-
+/-
+/-
+/-
0.1-100/5-80
0-10 mg/mL
58.5 ug/mL
10-10,000 ug/mL
+S9: 0-3400 ug/mL;
-S9: 0-2150 ug/mL
0-2500 ug/mL
2000 and 5000
Ug/mL
1-25 mM
Negative
Negative
Positive
Negative
+ S9: weakly
positive
-S9:
Equivocal
Weakly
positive
TCA as Free
Acid: Positive;
Neutralized
TCA:
Negative
Negative
Kargalioglu
et al., 2002
DeMarini et
al., 1994
Ono etal.,
1991
Ciller et al.,
1997
Harrington-
Brock etal.,
1998
Harrington-
Brock etal.,
1998
Mackay et
al., 1995
Plewa et al.,
2002
In vivo studies
Chromosome
aberration
Micronucleus
induction
Sperm-Head
Abnormalities
Micronucleus
induction
Micronucleus
induction
Swiss mice, bone
marrow
Swiss mice, bone
marrow
Swiss mice
C57BL mice, bone
marrow evaluated
Newt larvae
(Pleurodeles waltl),
erythrocytes
NA
NA
NA
NA
NA
0, 125, 250 or 500
mg/kg i.p.; 500
m/kg p.o.
(TCA not
neutralized before
administration)
0, 125, 250 or 500
mg/kg i.p. (2 daily
doses)
(TCA not
neutralized before
administration)
0, 125, 250, 500
mg/kg i.p. divided
into 5 daily doses
(TCA not
neutralized before
administration)
337 -1300 mg/kg
i.p. (25% MLD -
80%MLD)
(Neutralized TCA
was administered)
40, 80, 160 ug/mL
(TCA not
neutralized before
treatment)
Positive
Positive
Positive
Negative
Weakly
positive at 80
ug/mL
Bhunya and
Behera,
1987
Bhunya and
Behera,
1987
Bhunya and
Behera,
1987
Mackay et
al., 1995
Ciller et al.,
1997
83
DRAFT - DO NOT CITE OR QUOTE
-------
Table 4-9. Summary of available genotoxicity data on TCA
Endpoint
Test system
Metabolic
activation
Concentration/Dose
Results
Reference
In vitro studies
DNA strand
breaks
(alkaline
unwinding
assay)
Oxidative
DNA damage
(8-OHdG
adducts)
B6C3F! mice and
Sprague-Dawley rats
B6C3FJ mice
B6C3FJ mice and F344
rats
B6C3FJ mice
B6C3FJ mice
NA
NA
NA
NA
NA
0.6 mmol/kg oral
(TCA not
neutralized)
500 mg/kg p.o. in
1,2, or 3 daily doses
(TCA neutralized)
Mice: 10 mmol/kg,
oral
Rats: 5 mmol/kg
(TCA neutralized)
300 mg/kg, single
dose (TCA
neutralized)
0-3 g/L TCA oral,
for 21 days or 71
days
Positive
Negative
Negative
Positive
Negative
Nelson and
Bull, 1988
Stylesetal.,
1991
Chang et al.,
1992
Austin et
al., 1996
Parrish et
al., 1996
NA = Not applicable
+/- = with or without S9
MLD = median lethal dose
TCA mutagenicity has also been tested in cultured mammalian cells. The potential of
TCA to induce mutations in L5178Y/TK+" -3.7.2C mouse lymphoma cells was examined by
Harrington-Brock et al. (1998). The mouse lymphoma cells were incubated in culture medium
treated with TCA concentrations up to 2150 |ig/mL without S9 metabolic activation and up to
3400 |ig/mL with S9. TCA was in free acid form when evaluated without S9. When it was
evaluated with S9, the sodium salt form was used to maintain neutral pH. In the absence of S9,
TCA increased the mutant frequency by twofold or greater only at concentrations resulting in
<11% survival (2000 |ig/mL or higher), leading the study authors to characterize the
mutagenicity of TCA as equivocal. In the presence of S9, a doubling of mutant frequency was
seen at concentrations of 2250 |ig/mL and higher, including several concentrations with survival
>10%. No statistical evaluation of these data was conducted. Due to the weak mutagenic
response, cytogenetic analysis was not conducted with TCA-treated cells. However, the study
authors noted that the mutants included both large-colony and small-colony mutants. The small-
colony mutants are indicative of chromosomal damage, which cannot be attributed to low pH,
since the authors stated that no pH change was observed in the presence of S9. Harrington-
Brock et al. (1998) noted that TCA (with S9 activation) was one of the least potent mutagens
evaluated in this in vitro system and that the weight of evidence suggested that TCA was
unlikely to be mutagenic. Other mutagenicity/genotoxicity studies support this conclusion.
Plewa et al. (2002) evaluated the induction of DNA strand breaks by TCA (1-25 mM) in
CHO cells. TCA was found to be not genotoxic in this assay. Mackay et al. (1995) investigated
84 DRAFT - DO NOT CITE OR QUOTE
-------
the ability of TCA to induce chromosomal DNA damage in an in vitro assay using cultured
human lymphocytes. Treatment with TCA as free acid, with and without metabolic activation,
induced chromosome damage in cultured human peripheral lymphocytes only at concentrations
(2000 and 3500 jig/mL) that significantly reduced the pH of the medium. Neutralized TCA had
no effect in this assay even at a cytotoxic concentration of 5000 jig/mL, suggesting that reduced
pH was responsible for the TCA-induced clastogenicity in this study. To further evaluate the
role of pH changes in the induction of chromosome damage, isolated liver-cell nuclei from
B6C3Fi mice were suspended in a buffer at various pH levels and were stained with chromatin-
reactive (fluorescein isothiocyanate) and DNA-reactive (propidium iodide) fluorescent dyes.
Chromatin staining intensity decreased with decreasing pH, suggesting that pH changes alone
can alter chromatin conformation. Thus, Mackay et al. (1995) concluded that TCA-induced pH
changes were likely to be responsible for the chromosome damage induced by un-neutralized
TCA.
4.5.2.2. In Vivo Studies
TCA has been tested for genotoxicity in several in vivo test systems (Table 4-9). Bhunya
and Behera (1987) treated Swiss mice with 125, 250, or 500 mg/kg unneutralized TCA i.p. (the
highest dose, 500 mg/kg, was also administered orally for the chromosome aberration assay).
Three different cytogenetic assays: bone marrow chromosomal aberrations, micronucleus and
sperm-head abnormalities were carried out. TCA induced chromosomal aberrations and
micronuclei in bone-marrow, and altered sperm morphology of treated mice. In a later study,
Mackay et al. (1995) utilized the study design of Bhunya and Behera (1987) including an extra
sampling time at 24 h to investigate the ability of TCA to induce chromosomal DNA damage in
the in vivo bone-marrow micronucleus assay in mice. C57BL mice were given neutralized TCA
intraperitoneally at doses of 0, 337, 675, or 1080 mg/kg-day for males and 0, 405, 810, or 1300
mg/kg-day for females for two consecutive days, and bone-marrow samples were collected 6 and
24 hours after the last dose. The administered doses represented 25, 50, and 80% of the median
lethal dose, respectively. No significant treatment-related increase in micronucleated
polychromatic erythrocytes was observed. Mackay et al. (1995) concluded the positive results
previously observed by Bhunya and Behera (1987) may have been due to a non-genotoxic
mechanism, possibly caused by physico-chemically induced stress resulting from intraperitoneal
pH changes. In another study, unneutralized TCA induced a small increase in the frequency of
micronucleated erythrocytes at 80 |ig/mL in a newt (Pleurodeles waltl larvae) micronucleus test
(Giller et al., 1997).
Studies on the ability of TCA to induce single-strand breaks (SSBs) have produced
mixed results (Chang et al., 1992; Styles et al., 1991; Nelson and Bull, 1988). Nelson and Bull
(1988) evaluated the ability of TCA to induce single-strand DNA breaks in vivo in Sprague-
85 DRAFT - DO NOT CITE OR QUOTE
-------
Dawley rats and B6C3Fi mice. Single oral doses of unneutralized TCA in 1% Tween were
administered to three groups of three animals, with an additional group as a vehicle control.
Animals were sacrificed after 4 hours, and 10% liver suspensions were analyzed for single-
strand DNA breaks by the alkaline unwinding assay. Dose-dependent increases in single-strand
DNA breaks were induced in both rats and mice, with mice being more susceptible than rats.
The lowest dose of TCA that produced significant SSBs was 0.6 mmol/kg (98 mg/kg) in rats but
0.006 mmol/kg (0.98 mg/kg) in mice.
Styles et al. (1991) tested TCA for its ability to induce strand breaks in male B6C3Fi
mice in the presence and absence of liver growth induction. The test animals were given 1, 2, or
3 daily doses of neutralized TCA (500 mg/kg) by gavage and killed one hour after the final dose.
Additional mice were given a single 500 mg/kg gavage dose and sacrificed 24 hours after
treatment. Liver nuclei DNA were isolated, and the induction of single strand breaks was
evaluated using the alkaline unwinding assay. Exposure to TCA did not induce strand breaks
under the conditions tested in this assay. In a study by Chang et al. (1992), administration of
single oral doses of neutralized TCA (1 to 10 mmol/kg) to B6C3Fi mice did not induce DNA
strand breaks in a dose-related manner as determined by the alkaline unwinding assay. No DNA
damage (as strand breakage) was detected in F344 rats administered by gavage up to 5 mmol/kg
(817 mg/kg) neutralized TCA. In evaluating these studies, the reason for the inconsistent results
among studies may be related to whether TCA was administered as sodium salt (neutralized) or
as free acid (not neutralized). The different results did not appear to be related to the method
chosen to measure strand breakage. Although Chang et al. (1992) used a different unwinding
assay, Nelson and Bull (1988) and Styles et al. (1991) employed the same unwinding assay and
obtained contrasting results.
Two related studies were conducted to evaluate the relationship between TCA-induced
lipid peroxidation and oxidative DNA damage (Austin et al., 1996; Parrish et al., 1996)
(described in detail in Section 4.2.1.1). In the acute study by Austin et al. (1996), male B6C3Fi
mice (six/group) were treated with a single oral dose of TCA (0, 30, 100, or 300 mg/kg), and 8-
OHdG adducts were measured in liver DNA. A significant increase of about one-third in 8-
OHdG levels was observed in the 300 mg/kg group at 8-10 hours post-dosing. Parrish et al.
(1996) expanded on this study by evaluating TCA-induced oxidative DNA damage following
repeated dosing. Male B6C3Fi mice (6/group) were exposed to 0, 100, 500, or 2000 mg/L TCA
in drinking water for either 3 or 10 weeks (approximate doses of 0, 25, 125, or 500 mg/kg-day).
The levels of 8-OHdG levels were unchanged at both time periods. Thus, oxidative damage to
genomic DNA as measured by 8-OHdG adducts did not occur with prolonged TCA treatment.
In summary, these data collectively provide limited evidence regarding the genotoxicity
of TCA. No mutagenicity was reported in S. typhimurium strain TA100 in the absence of
metabolic activation (Rapson et al., 1980) or in an alternative protocol using a closed system
86 DRAFT - DO NOT CITE OR QUOTE
-------
(DeMarini et al., 1994), but a mutagenic response was induced in this same strain in the Ames
fluctuation test reported by Giller et al. (1997). On the other hand, mutagenicity in mouse
lymphoma cells was only induced at cytotoxic concentrations (Harrington-Brock et al., 1998).
Measures of DNA-repair responses in bacterial systems have been similarly inconclusive, with
induction of DNA repair reported in S. typhimurium by Ono et al. (1991) but not by Giller et al.
(1997) in E. coli. Although positive results were reported for unneutralized TCA in three in vivo
cytogenetic assays by Bhunya and Behera (1987), later in vitro studies by Mackay et al. (1995)
using neutralized TCA reported negative results, suggesting TCA-induced clastogenicity may
occur secondary to pH changes (Mackay et al., 1995). TCA-induced hepatic DNA strand breaks
and chromosome damage have been observed in several studies (Giller et al., 1997; Nelson and
Bull, 1988) and were suggested by the results of Harrington-Brock et al. (1998), However, these
effects have not been uniformly reported (Chang et al., 1992; Styles et al., 1991), and may be
related to low pH when TCA was not neutralized. TCA induced oxidative DNA damage in the
livers of mice following a single dose (Austin et al., 1996) but not following repeated dosing
over 3 or 10 weeks (Parrish et al., 1996).
4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS
No epidemiological data that evaluate TCA alone for noncancer effects in humans are
available. The experimental database for animals includes prechronic and chronic studies
conducted in rats and mice. A major limitation of the experimental database is that few studies
have examined toxic effects in organs other than the liver. Based on the currently available data,
oral exposure of rats and mice to TCA induces systemic, noncancer effects in animals that can be
grouped into three general categories: metabolic alterations, liver toxicity, and developmental
toxicity. These effects are described below.
4.6.1. Oral
4.6.1.1. Metabolic Alterations
Chronic exposure to TCA results in accumulation of lipofuscin in areas surrounding
hepatoproliferative lesions in the liver of mice (Bull et al., 1990). Lipofuscin is a complex of
lipid-protein substances derived from lipid peroxidation of membranes and hence provides
evidence of lipid peroxidation initiated by a free radical species generated from its metabolism.
Alternatively, Bull et al. (1990) suggested that accumulation of lipofuscin could be related to the
ability of TCA to induce peroxisomal oxidative enzymes. TCA also demonstrated its ability to
induce lipid peroxidation by the formation of TEARS in the liver of rats and mice when
administered acutely (Austin et al. 1996; Larson and Bull, 1992). This lipid peroxidative
response was reduced with pretreatment of TCA for 14 days (Austin et al., 1995). Decreased
87 DRAFT - DO NOT CITE OR QUOTE
-------
liver triglyceride and cholesterol levels were observed in Wistar rats treated with 25 ppm TCA in
drinking water for 10 weeks, while serum triglyceride level increased (Acharya et al., 1995).
Exposure to TCA has been reported to alter liver glycogen content in rats. TCA
significantly increased glycogen content in the livers of rats exposed to 25 mg/L in the drinking
water (neutralization not reported) for 10 weeks, as assessed by analysis of liver homogenates
(Acharya et al., 1995). Bull et al. (1990) reported that "TCA-treated animals displayed less
evidence of glycogen accumulation [than DCA-treated animals] and it was more prominent in
periportal than centrilobular portions of the liver acinus" as assessed by periodic acid/Schiff s
reagent staining in a 52-week study of mice exposed to 1 or 2 g/L in drinking water. In a study
where mice were exposed to 0.3, 1.0, or 2.0 g/L TCA in neutralized drinking water for 14 days,
Sanchez and Bull (1990) reported that glycogen as detected by PAS-staining in hepatic sections
from animals receiving the highest concentrations of TCA "displayed a much less intense
staining [than DCA-treated mice] that was confined to periportal areas." In contrast, Kato-
Weinstein et al. (2001) reported significantly decreased glycogen content, especially in the
central lobular region in mice treated with 3.0 g/L in neutralized drinking water for 4 or 8 weeks
and in mice treated with 0.3, 1.0, or 3.0 g/L for 12 weeks, as measured chemically in liver
preparations and verified histologically by PAS staining. The reason for the discrepancy is
unknown but does not appear to be related to differences in study duration or administered dose.
4.6.1.2. Liver Toxicity
The liver has consistently been identified as a target organ for TCA toxicity in short-term
(Sanchez and Bull, 1990; DeAngelo et al., 1989; Goldsworthy and Popp, 1987) and longer-term
(Bhat et al., 1991; Bull et al., 1990; Mather et al., 1990) studies. Collective analysis of the
available studies reveals a common spectrum of liver effects that includes changes in lipid and
carbohydrate homeostasis, increased liver weight, increased hepatic DNA labeling, and
hepatocyte necrosis. Peroxisome proliferation has been a primary endpoint evaluated (DeAngelo
et al., 1997; Parrish et al., 1996), with mice reported to be more sensitive to this effect than rats.
TCA induced peroxisome proliferation (in the absence of effects on liver weight) in
B6C3Fi mice exposed for 3 or 10 weeks to drinking water concentrations as low as 0.5 g/L
(approximately 125 mg/kg-day) (Parrish et al., 1996). The NOAEL in this study was 25 mg/kg-
day. In rats exposed to TCA for up to 104 weeks (DeAngelo et al., 1997), peroxisome
proliferation was observed at 364 mg/kg-day but not at 32.5 mg/kg-day. Peroxisome
proliferation has also been demonstrated in a number of other short-term and long-term exposure
studies in both rats and mice (Austin et al., 1995; Mather et al., 1990; DeAngelo et al., 1989;
Parnell et al., 1988; Goldsworthy and Popp, 1987). Increased liver weight and significant
increases in hepatocyte proliferation have been observed in short-term studies in mice at doses as
low as 100 mg/kg-day (Dees and Travis, 1994), but no increase in hepatocyte proliferation was
88 DRAFT - DO NOT CITE OR QUOTE
-------
noted in rats given TCA at up to 364 mg/kg-day (DeAngelo et al., 1997). More clearly adverse
liver-toxicity endpoints, including increased serum levels of liver enzymes (indicating leakage
from cells) or histopathological evidence of necrosis, have been reported in rats but generally
only at high doses. For example, increased hepatocyte necrosis was observed at a dose of 364
mg/kg-day in a rat chronic drinking water study (DeAngelo et al., 1997).
One commonly observed histopathological change associated with alteration of lipid and
carbohydrate homeostasis is glycogen accumulation in the liver (Acharya et al., 1995; Bull et al.,
1990; Sanchez and Bull, 1990). Acharya et al. (1995) reported decreased levels of liver
triglyceride and liver cholesterol and increased liver glycogen in rats given TCA for 10 weeks.
Serum triglyceride levels, glucose levels, and SuDH levels were increased.
Rats are less sensitive than mice to the peroxisome-proliferating effects of TCA. For
example, PCO activity was measured by DeAngelo et al. (1989) (described in Section 4.2) in
four strains of male mice and three strains of male rats exposed to TCA in drinking water for 14
days. PCO activity was increased by 648-2500% over controls in the mouse strains compared
with increases of up to 138% over controls in rats at the same drinking water concentrations (31
mM), clearly demonstrating the greater response in exposed mice.
The relevance of TCA effects associated with peroxisome proliferation to human health
is presently uncertain. Further information on this issue is presented in Section 4.7.3.1.1.4.
4.6.1.3. Developmental Toxicity
Six published studies have addressed the developmental toxicity of TCA in rats exposed
via the oral route. The available data indicate that TCA is a developmental toxicant. TCA
significantly increased resorptions, decreased implantations, and increased cardiovascular
malformations at 291 mg/kg-day in Sprague-Dawley rats (Johnson et al., 1998) and decreased
fetal weight and length, and increased cardiovascular malformations at 330 mg/kg-day in Long-
Evans rats (Smith et al., 1989). In a study focused on cardiac teratogenicity, Fisher et al. (2001)
observed significantly reduced fetal body weights on GD21 following treatment of Sprague-
Dawley rats with 300 mg/kg-day of TCA. In contrast to the previous studies, Fisher et al. (2001)
did not observe treatment-related effects on the incidence of cardiac malformations. The reason
for this discrepancy is unknown but might be related to purity of the test material, differences in
test strains among laboratories, differences in experimental design, methods used to detect
cardiac abnormalities, and/or route of administration (gavage versus drinking water). The
available data do not permit identification of NOAEL values for the developmental or maternal
toxicity of TCA, since in each study adverse effects were observed at the lowest or only dose
tested.
TCA was also demonstrated to cause toxicity in the developing testis (Singh, 2005a),
developing ovary (Singh, 2005b), and developing brain (Singh, 2006) when pregnant inbreded
89 DRAFT - DO NOT CITE OR QUOTE
-------
Charles Foster rats were treated with 1000 - 1800 mg/kg-day TCA on GD 6-15. However, these
studies were limited by the administration of a higher dose range of TCA to rats than the
previous studies by Smith et al. (1989) and Johnson et al. (1998).
Although in vitro test systems are limited in their utility to predict adverse developmental
effects and associated toxic potencies in intact organisms, they are useful in generating
mechanistic hypotheses. Mouse and rat whole embryo cultures have been used to assess the
potential for developmental toxicity of TCA (Hunter et al., 1996; Saillenfait et al., 1995). TCA
induces a variety of morphological changes in mouse and rat whole embryo cultures, supporting
the appearance of soft-tissue malformations observed in vivo at maternally toxic doses. The
xenopus assay system (frog embryo teratogenesis assay) (Fort et al., 1993) provided positive
results for developmental toxicity of TCA. In contrast, testing using hydra (freshwater
invertebrate hydrozoa) as a model has given negative results (Fu et al., 1990).
4.6.2. Inhalation
No inhalation studies are available.
4.6.3. Mode of Action Information
Target organs for the toxicity of TCA in humans have not been specifically identified.
The experimental database for MOA in animals is limited to studies in rats and mice, and few
studies have evaluated events in organs other than the liver. Based on currently available data,
systemic, noncancer effects induced in animals can be grouped into three general categories:
metabolic alterations, liver toxicity, and developmental toxicity.
4.6.3.1. Metabolic Alterations
Exposure to TCA causes disturbances in lipid homeostasis. TCA is a PPARa agonist. An
associated event with the activation of PPARa receptor by TCA is proliferation of peroxisomes
(reviewed in Bull, 2000; Austin et al., 1996; Parrish et al., 1996; Austin et al., 1995).
Peroxisomes contain hydrogen peroxide and fatty acid oxidation systems important in lipid
metabolism. Activation of the peroxisome proliferation pathway induces the transcription of
genes that encode enzymes responsible for fatty acid metabolism (Lapinskas and Gorton, 1999),
suggesting that lipid homeostasis might be affected through this mechanism. Alternatively,
metabolism of TCA might generate free radical species that initiate lipid peroxidation (Bull et al.
1990). The appearance of DCA in the urine of TCA-exposed animals provided evidence for a
free radical-generating, reductive dechlorination metabolic pathway (Larson and Bull, 1992).
TCA has been reported to induce glycogen accumulation in rats (Acharya et al., 1995)
and possibly in mice (Bull et al., 1990; Sanchez and Bull, 1990). The data are not fully
consistent, however, as Kato-Weinstein et al. (2001) observed decreased glycogen content in
90 DRAFT - DO NOT CITE OR QUOTE
-------
mice treated with TCA. Although TCA-induced changes in glycogen storage have not been well
studied, examination of DC A effects on the same endpoint can be informative. DCA-induced
glycogen accumulation is potentially pathological, because chronic treatment might result in
glycogen stores, becoming difficult to mobilize (Kato-Weinstein et al., 1998). The mechanism
for glycogen accumulation is not known, but it may be associated with inhibition of
glycogenolysis, since the observed effects resemble those observed in glycogen storage disease,
an inherited deficiency or alteration in any one of the enzymes involved in glycogen metabolism.
In this regard, the enzymatic basis for increased hepatic glycogen accumulation was studied by
Kato-Weinstein et al. (1998). TCA was not evaluated as part of this study. However, TCA
might act similarly to DCA, since both compounds induce glycogen accumulation (Acharya et
al., 1995), although the degree of accumulation is less with TCA. Therefore, the study has
implications for the mechanism of TCA-induced glycogen accumulation. Kato-Weinstein et al.
(1998) reported that DCA concentrations that induced glycogen accumulation did not alter
glycogen synthase activity and had no effect on glycogen phosphorylase (which degrades
glycogen) or the activity of glucose-6-phosphatase (which converts glucose-6-phosphate to
glucose) from liver homogenates. In an in vitro study using purified enzyme, DCA did not alter
the activity of glycogen synthase kinase-3p (which down-regulates glycogen synthase activity
and up-regulates glycogen phosphorylase activity). Based on the absence of an effect on
enzymes that regulate glycogen synthesis rates and decreased glycogen degradation observed in
fasted mice, the authors concluded that glycogen accumulation was related to a decrease in
degradation rate. There are currently no data on TCA to show that it acts via a similar MOA.
4.6.3.2. Liver Toxicity
Increased liver weight is typically observed concurrently with or at lower doses than
other endpoints following oral dosing with TCA. Changes in liver weight can reflect increases
in cell size, cell number, or both. TCA appears to induce both hepatocellular enlargement
(Acharya et al., 1997; Mather et al., 1990) and cell proliferation as assessed by differences in
hepatocyte DNA labeling (Dees and Travis et al., 1994; Sanchez and Bull, 1990). Increased cell
proliferation in normal cells may, however, be transient, with no change or even decreased
growth observed after chronic exposure (DeAngelo et al., 1997; Pereira, 1996). Both
cytomegaly and increased cell proliferation might be explained by TCA-induced peroxisome
proliferation (Lapinskas and Gorton, 1999). There is little evidence that increased cell
proliferation is secondary to hepatocyte cytotoxicity, as previously discussed in Section 4.4.1.1.,
although TCA can induce hepatic necrosis at high doses (DeAngelo et al., 1997).
Oxidative stress may also contribute to the toxicity of TCA in the liver. Several studies
have shown that TCA induces oxidative-stress responses (e.g., lipid peroxidation and oxidative
DNA damage) in the liver in single dose or short-term studies (Austin et al., 1996, 1995; Parrish
et al., 1996; Larson and Bull, 1992). Oxidative stress may contribute to the short-term toxicity
91 DRAFT - DO NOT CITE OR QUOTE
-------
of TCA; however, the contribution of oxidative stress to the chronic toxicity of TCA is uncertain
because the response is transient and is not observed in longer-term studies (Parrish et al., 1996).
4.6.3.3. Developmental Toxicity
The mechanism(s) for developmental toxicity are unknown. However, TCA was found
to accumulate in amniotic fluid when pregnant rodents were exposed to trichloroethylene or
tetrachloroethylene (Ghantous et al., 1986). Thus, TCA may also be accumulated in amniotic
fluid when pregnant rodents were exposed to this chemical, as most of the parent compound
remain unmetabolized. Accumulated TCA in the amniotic fluid may be transported through fetal
skin and swallowing and excreted by the fetus. Singh (2006) suggested TCA in the aminiotic
fluid may be circulated for several times and contributes to the long term retention in the fetus.
Since TCA is a strong acid with high protein binding, and was reported to cause placental lesion
(Ghantous et al., 1986), developmental toxicities may be related to anoxia resulting from toxic
effect on the placenta, and apoptosis resulted from oxidative stress, as observed in studies by
Singh (2005a, 2005b, 2006). On the other hand, Selmin et al. (2008) reported that TCA
disrupted the expression of genes involved in processes important during embryonic
development. A microarray study conducted on P19 mouse embryonal carcinoma cells treated
with TCA provided evidence that TCA altered the expressions of several genes implicated in
calcium regulation and heart development (Selmin et al., 2008). Real-time PCR analysis
confirmed the effect of TCA on genes involved in calcium regulation (CamK and RyR),
glucose/insulin signaling (Dok3), and ubiquitin-mediated cell proliferation (Ubec2).
4.7. EVALUATION OF CARCINOGENICITY
4.7.1. Summary of Overall Weight of Evidence
Based on the observations summarized in Section 4.2.2 and criteria outlined in the
Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), as well as mode of action
considerations, TCA is described as "likely to be carcinogenic to humans." The selection of this
descriptor for TCA is based on positive results for liver carcinogenicity in male and female mice
in multiple studies, development of liver tumors in mice with less than life-time exposure, no
positive evidence of carcinogenicity in rats, and no data on carcinogenicity in humans
4.7.2. Synthesis of Human, Animal, and Other Supporting Evidence
There are no epidemiological studies of TCA carcinogenicity in humans. The
experimental database for carcinogenicity of TCA consists of studies in rats and mice. The
results of the mice studies indicate that, in mice, TCA is a complete carcinogen that significantly
increased the incidence of liver tumors in male and female B6C3Fi mice exposed via drinking
water for 52 to 82 weeks (Bull et al., 2004, 2002; Pereira, 1996; Pereira and Phelps, 1996; Bull
92 DRAFT - DO NOT CITE OR QUOTE
-------
et al., 1990; DeAngelo et al., 2008; Herren-Freund et al., 1987). Incidence of tumors increased
with increasing TCA concentrations (Bull et al., 2002, 1990; Pereira, 1996; DeAngelo et al.,
2008). These results were obtained under conditions where the background incidence of tumors
in control animals was generally low. The development of tumors in animals exposed to TCA
progressed rapidly, as evident from the observation of significant numbers of tumors in less-
than-lifetime studies of 82 weeks or less. Positive evidence for tumor promotion by TCA
(following exposure to known tumor initiators) has been reported for liver tumors in B6C3Fi
mice (Pereira et al., 2001, 1997) and for GGT-positive foci in livers of partially hepatectomized
Sprague-Dawley rats (Parnell et al., 1988).
In contrast to the results observed for mice, treatment related tumors were not observed
in a study of male F344/N rats exposed to TCA via drinking water for 104 weeks (DeAngelo et
al., 1997). The carcinogenicity of TCA has not been evaluated in female rats or in other species
of experimental animals. However, treatment of primary cultures of male Long Evans rat
hepatocytes with 0.01 - 1.0 mM TCA for 10-40 h did not induce proliferation of the cultured
hepatocytes (Walgren et al., 2005)..
A significant limitation of the experimental database for carcinogenicity is the limited
number of studies that included microscopic examination of a comprehensive set of organs in
addition to the liver. The most complete evaluations were conducted by DeAngelo et al. (2008),
who examined a comprehensive set of organs in B6C3Fi mice from the high dose and control
groups. The kidney, liver, spleen, and testes were examined in all dose groups. DeAngelo et al.
(1997) also examined a comprehensive set of organs in F344 rats receiving the highest dose of
TCA and selected tissues (kidney, liver, spleen, testes) in the remainder of the treatment groups.
The MOA for TCA-induced liver carcinogenesis has not been established. The available
data collectively provide limited evidence regarding the genotoxicity of TCA. Tumor induction
appears to include perturbation of cell growth, both through growth inhibition of normal cells
and proliferation of selected cell populations. Specific mechanisms of altered growth control
that have been investigated for TCA include activation of the PPARa pathway, global DNA
methylation, and/or reduced intracellular communication. Of these, PPARa agonism has been
advanced as the most likely MOA contributing to the development of liver tumors. However,
significant gaps in knowledge exist in the hypothesized PPARa MOA, and .
4.7.3. Mode-of-Action Information
Exposure to TCA in drinking water has induced increased incidence of liver tumors in
B6C3Fi mice exposed for 52-82 weeks (Peirera et al., 2001, 1996; Bull et al., 2000, 1990;
Herren-Freund et al., 1987), but did not increase incidence of tumors in male F344 rats exposed
to TCA up to 102 weeks (DeAngelo et al., 1997). At the present time, the events leading to
development of liver cancer in mice exposed to TCA have not been fully characterized, although
93 DRAFT - DO NOT CITE OR QUOTE
-------
several modes of action have been postulated. As discussed below, many of the experimental
data for TCA are consistent with a PPARa-mediated MOA for development of liver tumors in
mice. However, because it is possible that more than one MOA is operative in the development
of mouse liver tumors, it is important to consider whether other MO As could contribute to the
observed pattern of response following TCA exposure. Events that may be related to
hepatocarcinogenesis are illustrated in Figure 4-1.
94 DRAFT - DO NOT CITE OR QUOTE
-------
TCA
Activation of PPARa
Activation
of
non-parenchymal
cells
Inhibition of
Intercellular comm
Cell cycle growth
and apoptosis gene
expression
Peroxisome gene
expression
Peroxisome proliferation
Oxidative stress
DNA damage
Growth inhibition of normal cells;
proliferation of selected cells
I
Preneoplastic foci
Figure 4-1. Possible Key Events in the MOA(s) for TCA
carcinogenesis
95
DRAFT - DO NOT CITE OR QUOTE
-------
4.7.3.1. Hypothesized Mode of Action
Tumor induction for TCA appears to include events such as perturbation of cell growth
and/or reduced intercellular communication. There is support for the involvement of PPARa
agonism; however, whether there is a single mode of action capable of producing TCA induced
tumors or if this requires multiple mode of action is unknown.
4.7.3.1.1. PPARa agonism.
Peroxisome proliferation has been proposed as a possible MOA for development of
tumors in mice exposed to TCA (e.g., Bull, 2000). Peroxisome proliferation refers to an increase
in the number and volume fraction of peroxisomes (subcellular organelles) in the cytoplasm of
mammalian and other eukaryotic cells. Peroxisomes are known to proliferate under a variety of
altered physiological and metabolic states and in response to exposure to a wide array of
xenobiotic compounds generally referred to as peroxisome proliferators (Klaunig et al., 2003).
Peroxisome proliferators are a structurally diverse group of non- or weakly mutagenic chemicals
that induce a predictable suite of pleiotropic (multiple) responses, including the induction of
tumors in rats and mice (Klaunig et al., 2003). At one time, peroxisome proliferation was
proposed as a causative factor in the development of liver tumors. However, increased
knowledge of the molecular events leading to peroxisome proliferation suggests that it is an
associative rather than a causal event in development of liver tumors (Klaunig et al., 2003).
Current understanding of the events leading to peroxisome proliferation indicates that
peroxisome proliferating chemicals initiate the pleiotropic response by interacting with PPARs.
PPARs are ligand-activated transcription factors that belong to the nuclear receptor
"superfamily." When activated^ by peroxisome-proliferators (agonists), PPARs bind to
response elements in the promoter regions of genes and elicit changes in gene expression. Three
PPAR isoforms have been identified to date and are designated PPARa, PPARp/5, and PPARy.
Gene disruption experiments in mice indicate that PPARa is required for the pleiotropic
response (including development of liver tumors) observed following exposure to peroxisome
proliferators, as demonstrated using the prototypical PPARa agonist WY 14,643 (Klaunig et al.,
2003). However, peroxisome-proliferation-like events have been observed in PPARa-null mice
treated with extremely high doses of ligands specific for other PPAR family members (Klaunig
et al., 2003), suggesting possible cross talk between PPAR isoforms.
PPARa is highly expressed in cells that have active fatty acid oxidation capacity,
including hepatocytes, cardiomyocytes, enterocytes, and the proximal tubule cells of the kidney,
6The term "activation" refers to an alteration of the three-dimensional structure of the receptor protein or
receptor complex resulting in altered response element binding potential. The alterations initiated by ligand binding
96 DRAFT - DO NOT CITE OR QUOTE
-------
and it is well accepted that PPARa plays a central role in lipid metabolism (Klaunig et al.,
2003). Ligand or pharmaceutical activation of PPARa facilitates increased mobilization,
transport, and oxidation of fatty acids, which serve as energy substrates during periods of
starvation or activation, by hypolipidemic drugs such as clofibrate (Klaunig et al., 2003).
PPARa is known to interact with other transcription factors (e.g., the retinoic acid receptor and
thyroid hormone receptor), co-activators, and corepressors to regulate gene expression.
4.7.3.1.1.1. Identification of key events. Klaunig et al. (2003) have proposed a MOA
hypothesis for induction of liver tumors by PPARa agonists that incorporates the following key
events. PPARa ligands activate PPARa, which subsequently alters the transcription of genes
involved in peroxisome proliferation, cell cycling/apoptosis, and lipid metabolism. The changes
in gene expression lead to perturbations in cell proliferation and apoptosis and to peroxisome
proliferation. Suppression of apoptosis coupled with increased cell proliferation allows DNA-
damaged cells to persist and proliferate, resulting in preneoplastic hepatic foci and ultimately in
tumors via selective clonal expansion. Peroxisome proliferation may lead to oxidative stress,
which potentially contributes to the proposed MOA by causing indirect DNA damage and/or by
contributing to the stimulation of cell proliferation. PPARa agonists also inhibit gap junction
intracellular communication and stimulate Kupffer cells, the resident macrophages of the liver.
Kupffer cells were identified as playing a role in peroxisome proliferator-induced effects,
independently of PPARa. Specifically, Kupffer cells were reported to mediate acute effects of
peroxisome proliferators on cell proliferation and production of oxidants in liver (Hasmall et al.,
2000; Parzefall et al., 2001; Rusyn et al., 2000; Rusyn et al., 2001), though, as discussed below,
the contribution of Kupffer and other non-parenchymal cells (NPCs) to the chronic effects of
PPARa agonists, including hepatocarcinogenesis, is not well known.
In describing this progression of events, Klaunig et al. (2003) distinguish between what
they consider to be causal (i.e., required for this MOA) and associative (i.e., markers of PPARa
agonism but not shown to be directly involved with formation of liver tumors) events. Among
the key events postulated for PPARa-induced hepatocarcinogenesis, activation of PPARa is
highly specific for this MOA. While alterations in cell proliferation and apoptosis and clonal
expansion are common to other modes of action, recent findings by Shah et al. (2007) indicate
that regulation of cell proliferation by peroxisome proliferators may also be PPARa specific.
Oxidative stress occurring in conjunction with peroxisomal proliferation is regarded as a general
phenomenon and is not considered to be a highly specific marker of PPARa-induced liver
carcinogenesis. Moreover, while it is known that activation of PPARa leads to increase in cell
may include events such as loss of heat shock and chaperone proteins, nuclear translocation, and protein turnover
(Klaunig et al., 2003).
97 DRAFT - DO NOT CITE OR QUOTE
-------
proliferation and inhibition of apoptosis, it is uncertain whether this is due to a direct interaction
with an unidentified target gene or occurs through secondary or tertiary events..
Our understanding of the PPARa agonism mode of action has been expanded with recent
findings. First, it has been demonstrated in a transgenic mouse model that activation of PPARa
alone in hepatocytes was not sufficient to induce hepatocellular tumors (Yang et al., 2007). In
this mouse model, the potent viral transcriptional activator VP16 was fused to the mouse PPARa
cDNA to create a transcription factor that constitutively activates PPARa -responsive genes in
the absence of ligands. The transgenic mice demonstrated responses that mimic wild-type mice
when treated with peroxisome proliferator Wy-14643, including significantly decreased serum
fatty acids and marked induction of PPARa target genes encoding fatty acid oxidation enzymes,
suggesting the transgene functions in the same manner as peroxisome proliferators to regulate
fatty acid metabolism. In addition, while these transgenic mice demonstrated increased
hepatocellular proliferation (Yang et al., 2007), no liver tumors were observed. Therefore, it
appeared that many of the hepatocellular responses commonly associated with PPARa agonism
-fatty acid oxidation, peroxisome proliferation, hepatocellular proliferation, and cell-cycle
control genes expression - were not sufficient to induce liver tumors. However, it should be
noted that while most PPARa target genes were activated in the LAP-VP16 PPARa mice,
several genes e.g. c-myc, were not activated without ligand treatment.
Second, progress has been made as to the involvement of NPCs, which include Kupffer
cells, hepatic stellate cells, and sinusoid endothelial cells, in peroxisome-proliferator-induced
liver tumors, though many questions remain. Yang et al. (2007) suggest that activation of NPCs,
plays an important role in peroxisome proliferator-induced hepatocarcinogenesis. Specifically,
induction of proliferation of NPCs was only observed in wild-type mice upon Wy-14643
treatment, but not in the transgenic mice. Yang et al. (2007) suggested that lack of tumor
induction in transgenic mice as compared to Wy-14643-treated wild-type mice may be
associated with the differences of NPC activation. (However, Shah et al. (2007) (see below)
suggested another possibility may be PPARa agonists such as Wy-14643 regulate genes in
addition to that for the VP16 PPARa fusion protein. These possibilities are being investigated
by these researchers.) To examine the role of Kupffer cell-derived oxidants in the mode of action
for liver carcinogenesis, Woods et al. (2007) treated NADPH-oxidase deficient mice (their
Kupffer cells cannot produce oxidants), along with wild-type and PPARa knockout mice, with
Wy-14643 for 1 week, 5 weeks, or 5 months. Wy-14643 treatment induced similar levels of
hepatocyte proliferation and DNA damage in NADPH-oxidase deficient mice and wild-type
mice, while both were abolished in PPARa knockout mice. Woods et al. (2007) concluded that
Kupffer cell-derived oxidants may play a limited, if any, role in long-term effects of peroxisome
proliferators such as hepatocarcinogenesis.
98 DRAFT - DO NOT CITE OR QUOTE
-------
Third, a novel mechanism by which PPARa regulates gene expression, hepatocellular
proliferation and tumorigenesis was uncovered by Shah et al. (2007). Activated PPARa was
demonstrated to be a major regulator of hepatic microRNA (miRNA)7 expression, especially let-
7C, an miRNA found to be potential tumor suppressor (Lee and Dutta, 2006; Zhang et al., 2007)
and inhibit the expression of the ras oncogene (Johnson et al., 2005). Let-7C was found to be
inhibited following treatment with 0.1% Wy-14643, a potent PPARa agonist, in wild-type mice
for 4-h, 2-week or 11-month. No decrease in Let-7 miRNA was observed in the PPARa-null
mice that underwent the same treatment. In addition, expression of the longer primary let-7C
transcript (pri-let-7C) was also decreased following 4-h and 2-week Wy-14643 treatments.
Moreover, pri-let-7C, AK033222, and pri-mir-99a were regulated in a PPARa-dependent
manner, as Wy-14643 had no effect on pri-let-7C, AK033222, or pri-mir-99a in PPARa-null
mice treated for 4-h or 2-week. [The chromosomal positional relationship of let-7C was found to
be downstream of mir-99a and EMBL transcript AK033222 (Shah et al., 2007)].
Shah et al. (2007) observed that Let -7C regulated c-myc gene expression via direct
interaction with the 3' untranslated region of c-myc mRNA, causing mRNA degradation.
Increasing let-7C expression in the mouse hepatoma cell line Hepa-1 decreased c-myc expression
in a dose-dependent manner. PPARa-mediated induction of c-myc via let-7 C subsequently
increased expression of the oncogenic mir-17-92 polycistronic cluster, which has been
implicated in enhanced cell cycle progression, blockade of tumor cell apoptosis, and increased
neovascularization. These events did not occur in PPARa-null mice (Shah et al., 2007). When
Hepa-1 cells were transfected with 5-25 nM let-7C, at 72 h posttransfection, cell growth was
inhibited in a dose-dependent manner. Let-7C decreased BrdU incorporation in a dose-
dependent manner, but had no effect on cell apoptosis. In addition, cotransfection of let-7C and
c-myc increased cell proliferation in Hepa-1 cells compared to cells transfected with let-7 C
alone, suggesting that c-myc is a critical downstream effector of let-7C.
No difference in basal let-7C expression was observed between wild-type mice and the
LAP-VP16 PPARa transgenic mice mentioned previously, even though PPARa was activated in
the hepatocytes of transgenic mice. However, Shah et al. (2007) reported that Wy-14643
treatment decreased let-7C expression in these transgenic mice (which still possessed native
PPARa), suggesting either that ligand treatment is needed for inhibition of let-7C, indicating that
PPARa agonists may regulate genes in addition to that for the VP16 PPARa fusion proteins, or
activation of NPCs is critical for tumorigenesis and let-7c expression. Moreover, let-7C was not
7 MicroRNAs (miRNAs) are noncoding RNAs that are transcribed in the nucleus as single primary transcripts (pri-
miRNAs) or large polycistronic transcripts encoding several miRNAs. Mature miRNA molecules are partially
complementary to one or more messenger RNA (mRNA) molecules, and they function to downregulate gene
expression.
99 DRAFT - DO NOT CITE OR QUOTE
-------
suppressed in humanized PPARa mice which were resistant to Wy-14643 induced
hepatocellular proliferation and liver tumor formation (Shah et al., 2007). Wy-14643 treatment
of humanized PPARa mice also did not induce c-myc and mir-17 expression. These findings
suggested the let-7C signaling cascade may be critical for PPARa agonist-induced liver
proliferation and tumorigenesis.
Fourth, another mechanism, hypomethylation of DNA, has been proposed by Pogribny et
al. (2007) as an important link between hepatocellular proliferation and hepatocarcinogenesis in
the mode of action of peroxisome proliferators. Hypomethylation of DNA is an early event to
most cancers, including liver (Yamada et al., 2005; Baylin et al., 1998; Counts and Goodman,
1995; Gama-Sosa et al., 1983) and has been postulated to be a secondary mechanism involved in
carcinogenesis (Good and Watson, 2002). DNA hypomethylation is associated with opening of
the chromatin configuration and transcriptional activation, leading to chromosomal instability
and aberrant gene expression (Baylin et al., 1998; 2001; Dunn, 2003; Jones and Gonzalgo,
1997).
When male SV129 mice were fed a control or Wy-14643-containing (1000 ppm) diet for
1 week, 5 weeks or 5 months, treatment with Wy-14643 led to progressive global
hypomethylation of liver DNA as determined by Hpall-cytosine extension assay, reaching the
maximum effect of >200% at 5 months. Trimethylation of histone H4 lysine 20 and H3 lysine 9
was significantly decreased at all time points. Since the majority of cytosine methylation in
mammals resides in repetitive DNA sequences, Pogribny et al. (2007) measured the effect of
Wy-14643 on the methylation status of major and minor satellites, as well as in the intracisternal
A particle (IAP) of long terminal repeats (LTR) retrotransposone, and long interspersed
nucleotide elements 1 and 2 (LINE1 and LINE2, representing the non-LTR retrotransposons) in
liver DNA and found exposure to Wy-14643 resulted in a gradual loss of cytosine methylation in
major and minor satellites, IAP, LINE1 and LINE2 elements. Previously, oral gavage of female
B6C3F1 mice with 50 mg/kg Wy-14643 for up to 4 days resulted in hypomethylation of the c-
myc gene in the liver, and temporally correlated with an earlier burst of cell proliferation (Ge et
al, 2001). No effect on c-myc promoter methylation was observed with long term treatment
(Pogribny et al., 2007). Pogribny et al.( 2007) concluded alterations in the genome methylation
patterns with long term exposure to Wy-14643 may not be confined to specific cell proliferation-
related genes. It has been demonstrated that genome-wide hypomethylation in cancer, including
liver cancer, largely involves repetitive DNA elements (Chalitchagorn et al., 2004; Schultz et al.,
2006).
Pogribny et al. (2007) also found Wy-14643 had no effect on DNA and histone
methylation status in PPARa-null mice at any of the evaluated time points. Previously,
treatment of PPARa-null mice with Wy-14643 for 11 months produced no liver tumors, whereas
treatment of wild-type mice with 1000 ppm Wy-14643 resulted in 100% incidence of
100 DRAFT - DO NOT CITE OR QUOTE
-------
hepatocellular adenomas and carcinomas (Peters et al., 1997). In addition, Wy-14643 had no
effect on liver cell proliferation in PPARa-null mice (Woods et al., 2007; Peters et al., 1997).
Therefore, these epigenetic alterations were PPARa-dependent and may play a key role in
hepatotumorigenesis of peroxisome proliferators. It was suggested that peroxisome proliferator-
induced increases in hepatocellular proliferation prevented the methylation of newly synthesized
strands of DNA (Ge et al., 2001), since a temporal relationship between increased cell
proliferation and DNA hypomethylation of the c-myc gene was observed after a single dose of
Wy-14643 to mice. Long-term treatment of wild-type mice with Wy-14643 in Pogribny et al.
(2007) demonstrated gradual worsening dysregulation of normal methylation patterns in
genomic DNA.
4.7.3.1.1.2. Biological plausibility, consistency, specificity of association
TCA is classifiable as a peroxisome proliferator based on morphological and biochemical
evidence from multiple studies. With respect to peroxisome proliferation, microscopic
examination or responses consistent with peroxisome proliferation (e.g., enzyme induction,
increased liver weight), has been observed in male F344 rats exposed to TCA by oral gavage for
14 days (Goldsworthy and Popp, 1987), in male F344 rats exposed to TCA in drinking water for
14 days (DeAngelo et al., 1989) or 104 weeks (DeAngelo et al., 1997), in male Osborne-Mendel
rats exposed to TCA in drinking water for 14 days (DeAngelo et al., 1989), and in male Sprague-
Dawley rats treated with TCA in the drinking water for 90 days (Mather et al., 1990). In mice,
peroxisome proliferation or changes consistent with peroxisome proliferation have been reported
in male B6C3Fi mice exposed to TCA in drinking water for 2-10 weeks (Parrish et al., 1996;
Austin et al., 1995; Sanchez and Bull, 1990; DeAngelo et al., 1989), in male B6C3Fi mice
exposed by oral gavage for 10 days (Goldsworthy and Popp, 1987), and in male C57B1/6 and
Swiss-Webster mice exposed to TCA in the drinking water for 14 days (DeAngelo et al., 1989).
Furthermore, PPARa-null mice exposed to 2 g/L TCA in drinking water for 7 days do not show
the characteristic responses of AGO, PCO, and CYP4A induction associated with PPARa
activation and peroxisome proliferation in wild-type mice (Laughter et al., 2004). In addition,
the livers from wild-type but not PPAR-null mice exposed to TCA developed centrilobular
hepatocyte hypertrophy, although no significant increase in relative liver weight was observed.
In addition, PPARa agonism in response to treatment with TCA has been demonstrated
in vitro in COS-1 cells transfected with human and mouse PPARa expression plasmids together
with a peroxisome proliferator response element (PPRE)-luciferase reporter (Maloney and
Waxman, 1999). Cells were treated for 24 hours with 0.1 to 5 mM TCA. TCA activated human
and mouse PPARa with no difference between species in receptor sensitivity or maximal
responsiveness.
101 DRAFT - DO NOT CITE OR QUOTE
-------
Third, TCA has been shown to increase hepatocyte proliferation in DNA-labeling
experiments in mice (Dees and Travis, 1994). Relatively small (two- to threefold), but
statistically significant increases in [3H]thymidine incorporation in hepatic DNA were observed
in mice exposed to 100-1000 mg/kg TCA for 11 days at doses that increased relative liver
weight. Dees and Travis (1994) observed increased hepatic DNA labeling at doses lower than
those associated with evidence of necrosis, suggesting that TCA-induced cell proliferation is not
due to regenerative hyperplasia. The study authors reached this conclusion based on (1) the
pattern of observed histopathological changes, which indicated nodular areas of cellular
proliferation, and (2) the results of liver DNA labeling experiments, which showed incorporation
of [3H]thymidine in extracted liver DNA but no difference in total liver DNA content (mg
DNA/g liver). Dees and Travis (1994) concluded that their results were consistent with an
increase in DNA synthesis and cell division in response to TCA treatment. The authors further
suggested that the absence of histopathological effects makes it unlikely that the increased
radiolabel was secondary to tissue repair.
Hepatocyte proliferation in response to treatment with TCA has also been demonstrated
in studies by Stauber and Bull (1997), Pereira (1996), and Sanchez and Bull (1990). Details of
these studies were provided in Section 4.5.1.2 and 4.2.1.1. Dose-related increase in
incorporation of [3 HJthymidine into hepatic DNA was observed in B6C3F1 mice treated with
0.3 - 2 g/L TCA for 5 or 14 days (Sanchez and Bull, 1990). This increase was significant at 2
g/L TCA. No increases in labeled hepatocytes as seen by autoradiography were apparent at 2 or
5 days. Thus, increase in incorporation of [3 H] thymidine did not correlate with replicative
synthesis of DNA measured autoradiographically up to 5 days of treatment. Pereira (1996)
reported TCA increased the BrDU-labeling index (calculated as the percentage of hepatocytes
with labeled nuclei) in mice exposed to 0.33 to 3.3 g/L TCA for 5 days, but not after 12 or 33
days. Stauber and Bull (1997) reported a statistically significant 2- to 3- fold elevation in
division rate in normal hepatocytes after male B6C3F1 mice were treated for 14 or 28 days with
2 g/L TCA. However, continued treatment for 52 weeks resulted in a decrease in division rate in
normal hepatocytes. Cell division rates in TCA-induced AHF and tumors were high at all TCA
doses administered in the last 2 weeks of the study.
DeAngelo et al. (2008) reported hepatocyte proliferation in B6C3Flmice exposed to 5
g/L TCA at 30 and 40 weeks; with mice exposed to 0.5 g/L TCA demonstrated hepatocyte
proliferation at 60 weeks. Therefore, DeAngelo et al. (2008) observed hepatocyte proliferation
in mice after long term TCA treatment, in contrast to Stauber and Bull (1997), who observed it
as a transient event. This result was in agreement with the observation by Woods et al. (2007)
that the robust proliferative effect of Wy-14643 in rodent livers extended beyond the short time
frame that was traditionally considered. Hepatocyte proliferation has been demonstrated in
chronic studies with other peroxisome proliferators (Woods et al., 2007; Ward et al., 1988;
102 DRAFT - DO NOT CITE OR QUOTE
-------
Yeldandi et al., 1989). It should also be noted that TCA did not induce hepatocyte proliferation
or tumors in F344 rats after 104 weeks exposure (DeAngelo et al., 1997), consistent with the
hypothesis that cell proliferation is a causal event in tumorigenesis under the PPARa MOA.
Moreover, as presented previously, whereas PPARa-null mice treated with 2 g/L TCA in
drinking water for 7 days did not develop centrilobular hepatocyte hypertrophy, treated wild-
type mice did (Laughter et al., 2004). Thus, TCA-induced hepatocyte hypertrophy is PPARa-
dependent.
A recent report by the National Research Council (NRC) of the National Academy of
Science Assessing the Human Health Risks ofTrichloroethylene: Key Scientific Issues (NRC,
2006) stated that "[tjhere is sufficient weight of evidence to conclude that the mode of action of
trichloroacetic acid as a rodent liver carcinogen is principally as a liver peroxisome proliferator
in a specific strain of mouse, B6C3F1."
However, Ito et al. (2007) recently reported that the peroxisome proliferator di(2-
ethylhexyl)phthalate (DEHP) induces hepatic tumorigenesis through a PPARa-independent
pathway. Specifically, they administered relatively low doses of DEHP (0, 0.01%, and 0.05% in
diet) to wild-type and PPARa knockout mice for 22 months, and found a higher incidence of
liver tumors in treated PPARa knockout than in treated wild-type mice at the higher dose. (This
was the first published study using PPARa knockout mice that were treated for over 1 year,
allowing for the full expression of tumor development.) DEHP treatment also increased dose-
dependently 8-OHdG levels in mice of both genotypes, although the degree of increase was
higher in PPARa knockout mice. Ito et al. (2007) suggested that increases in oxidative stress
induced by DEHP exposure may lead to induction of inflammation, resulting in higher incidence
of liver tumors in PPARa knockout mice, and a potential PPARa-independent pathway for
DEHP-induced liver tumors. It should be noted that DEHP induced liver tumors in rats and
mice, TCA induced liver tumors only in mice. Therefore, the MOA for hepatocarcinogenesis
for DEHP and TCA may not be comparable. However, this finding for DEHP does show that
demonstration of many of the key events proposed for a PPARa MOA is insufficient to preclude
existence a PPARa-independent pathway for tumorigenesis. Previously, Melnick et al. (2001)
have suggested PPARa-independent pathways for tumorigenesis by DEHP.
Researchers have explored other possible key events for a PPARa agonism MOA,
including the possible roles of let-7C micro-RNA and hypomethylation of DNA on
hepatocarcinogenesis of PPARa agonists in mice. These are discussed with respect to available
data on TCA below.
First, the expression of c-myc mRNA was increased in TCA-treated female B6C3F1 mice
(Pereira et al., 2001). c-myc has been demonstrated to be a critical downstream effector of let-
7C (Shah et al., 2007). Thus, increased expression of c-myc mRNA in TCA-treated mice is
consistent with the proposed let-7C micro-RNA mediated signaling cascade in alteration of gene
103 DRAFT - DO NOT CITE OR QUOTE
-------
expression, hepatocellular proliferation and tumorigenesis in TCA- treated mice. However, it
has not been shown that TCA-induced increases in c-myc expression are PPARa-dependent, as
increased expression of c-myc is common to both carcinogens and non-carcinogenic mitogens
(Hasmall et al. 1997).
Second, experimental evidence supports the hypothesis that hypomethylation of DNA
may be related to the carcinogenicity of TCA in mice. In female B6C3Fi mice initiated by an
i.p. injection of MNU and then administered TCA in drinking water at 25 mmol/L (4085 mg/L)
for 44 weeks, the level of 5MeC in DNA of hepatocellular adenomas and carcinomas was
decreased 40% and 51%, respectively, as compared with noninvolved tissue from the same
animal and control animals given only MNU; termination of TCA treatment 1 week prior to
sacrifice did not change the levels of 5MeC in either adenomas or carcinomas (Tao et al., 1998).
In another experiment, female B6C3Fi mice that were treated with 25 mmol/L (1062 mg/kg-day)
of TCA for 11 days in their drinking water also showed a 60% decrease in the level of 5MeC in
total liver DNA (Tao et al., 1998).
The substantial decrease in the level of 5MeC in these studies indicated that many genes
may be involved. Increased mRNA and proteins ofc-jun and c-myc protooncogenes have been
reported in TCA-induced foci of altered hepatocytes and liver tumors in studies by Latendresse
and Pereira (1997) and Nelson et al. (1990). Accordingly, Tao et al. (2000a, b) investigated the
methylation of DNA in the promoter regions ofc-jun and c-myc protooncogenes.
Using methylation-sensitive restriction enzymes followed by Southern blot analysis, Tao
et al. (2000a) reported that the promoter regions of the c-jun and c-myc genes were
hypomethylated in mice exposed to 500 mg/Kg TCA for 5 days. Expression of the mRNA and
proteins of these two protooncogenes were increased. In another study (Tao et al., 2000b), the
expression of the mRNA and proteins of the two protooncogenes were found to be increased in
MNU-initiated and TCA-promoted mouse liver tumors. DNA MTase activity was increased in
tumors while decreased in noninvolved liver.
Increased expression of c-jun and c-myc has been associated with increased cell
proliferation (Fausto and Webber, 1993; Saeter and Seglen, 1990). Therefore, increased
expression and decreased methylation of the c-jun and c-myc genes could be involved in the
carcinogenic activity of TCA by facilitating cell proliferation.
TCA-induced hypomethylation is supported by a study using a bisulfite-modified DNA
sequencing procedure (Tao et al., 2004) that demonstrated that the DMR-2 region of the IGF-II
gene was hypomethylated in liver and tumors from mice initiated with MNU and treated with
TCA. The percentage of CpG sites that were methylated was reduced from 79.3% to 58% in
liver and further reduced to 10.7% in tumors promoted by TCA.
An association between hypomethylation and cell proliferation in liver of TCA-treated
mice was demonstrated by Ge et al. (2001). Increase in DNA replication (evidenced by
104 DRAFT - DO NOT CITE OR QUOTE
-------
increased PCNA-labeling index and mitotic-labeling index) was observed 72 hours and 96 hours
after the first gavage daily dose of 500 mg/kg TCA. Hypomethylation of the internal cytosine of
CCGG sites in the promoter region of the c-myc gene began between 48 and 72 hours from the
initiation of treatment with TCA and continued to 96 hours.
Based on the above experimental results, TCA induced global and locus-specific DNA
hypomethylation in mouse liver. Given the recent finding, discussed above, that the DNA
hypomethylation by the potent PPARa agonist Wy-14643 was PPARa-dependent (Pogribny et
al. 2007), the data on TCA is consistent with a PPARa MOA. However, because
hypomethylation is a relatively ubiquitous phenomenon in carcinogenesis, and it has not been
demonstrated that TCA-induced hypomethylation is PPARa-dependent, alternative mechanisms
cannot be discounted.
There are a number of inconsistencies and data gaps that reduce the confidence in the
conclusion that TCA induced hepatocarcinogenesis through a PPARa MOA. First, while TCA
induces peroxisome proliferation (a marker for PPARa agonism) in both rats and mice, to date,
it has only been shown to be tumorigenic in B6C3F1 mice but not F344 rats (DeAngelo et al.,
1997) (the only strains tested for carcinogenicity). No complete explanation for this species
difference has been developed, although the NRC (2006) suggested that at the same doses, rats
and mice have different responsiveness to peroxisome proliferation. For instance, Bull (2000)
noted that, under similar dosing regimens, a 2- to 3-fold increase in peroxisome proliferation was
observed in F344 rats compared with a 10-fold increase over controls in mice (strains not
specified). However, this relationship may not hold for all mouse and rat species and strains and
may be chemical specific. For example, Elcombe (1985) reported that Wistar rats displayed a
higher induction of peroxisome proliferation than mice in response to TCA, as measured by
increases in cyanide insensitive palmitoyl CoA oxidation in both species. Moreover, evidence
from other peroxisome proliferators suggests that the degree of peroxisome proliferation and
hepatocarcinogenic potency are not well correlated (Marsman et al. 1988). Another finding that
may explain liver tumors only occurring in mice but not in rats is that hepatocyte proliferation
only occurred in TCA-treated mice (DeAngelo et al., 2007), but not in treated rats (DeAngelo et
al., 1997). Since cell proliferation is a critical event in tumorigenesis under the PPARa agonism
MOA, this may be the main reason that tumors were not found in exposed rats.
Another possible explanation for the lack of TCA-induced tumors in rats is that the
binding of TCA to total plasma protein may be higher in rats than in mice, reducing its
bioavailability in the liver. However, the extent of these differences in binding is not clear. For
instance, at around 600 uM, Lumpkin et al. (2003) report the plasma-bound fraction of TCA in
rats to be about a 4- to 5-fold more than that in mice, while Templin et al. (1993, 1995) report
this difference to be only about 1.1-fold.
105 DRAFT - DO NOT CITE OR QUOTE
-------
TCA has also been associated with a PPARa-mediated MOA based on evidence that the
phenotypic characteristics of TCA-induced tumors appear similar to those of tumors induced by
other peroxisome proliferators (NRC, 2006). However, upon closer examination, certain
characteristics of TCA-induced foci and tumors, including mutation frequencies and spectra,
phenotypic characteristics, and immunostaining characteristics, are different from those induced
by other peroxisome proliferators, and those characteristics that are similar may be relatively
non-specific to peroxisome proliferators.. This suggests that PPARa agonism may not be the sole
MOA for TCA-induced tumors in mice.
Specifically, with respect to mutations in TCA-induced foci and tumors, both Ferreira-
Gonzalez et al. (1995) and Bull et al. (2002) observed that the H-ras codon 61 mutation
frequency and spectrum of TCA-induced tumors were similar to historical controls, while
peroxisome proliferators ciprofibrate (CPF) [Hegi et al., 1993] and methylclofenapate (MCP)
[Stanley et al., 1994] have lower H-ras codon 61 mutation frequency than spontaneous tumors in
B6C3F1 mice (11/46 vs 85/130 for MCP; and 8/39 vs 32/50 for CPF) and their mutation
spectrums differed from that of spontaneous tumors. The lower frequency and distinct pattern of
H-ras mutation observed in MCP and CPF would suggest the activation of H-ras protooncogene
in spontaneous liver lesions not involved in hepatocarcinogenesis by these two peroxisome
proliferators. Since the H-ras codon 61 mutation frequency and spectrum of TCA-induced
tumors were similar to historical controls, a similar conclusion as to the role of H-ras activation
cannot be drawn for TCA-induced tumors. On the other hand, Ferreira-Gonzalez et al. (1995)
reported K-ras codon 61 mutations in one out of 11 TCA-induced liver tumors, and none in 32
spontaneous tumors from control animals. Both Hegi et al. (1993) and Stanley et al. (1994)
found such rare mutation in one out of 31 CPF- induced and one MCP-induced hepatocarcinoma,
suggesting that such rare mutation may be caused by indirect DNA damage induced by treatment
(Hegi et al., 1993). Reynolds et al. (1987) reported K-ras mutations from both peroxisome
proliferators furfural and furan-induced mouse liver tumors, but not at codon 61. However, it
should be noted that in all cases, the overall rates of K-ras mutations are low (less than 10% of
tumors), so their reliability as indicators of MOA is likely to be low.
With respect to tumor phenotype, although Stauber and Bull (1997) reported TCA-
induced foci and tumors to be predominantly basophilic, Pereira et al. (1996) reported the foci of
altered hepatocytes in mice treated with TCA were half basophilic and half eosinophilic, with
liver tumors predominantly basophilic. By contrast, it has been suggested that peroxisome
proliferators selectively promote basophilic foci generally (Cattley et al. 1994). Furthermore,
Weber et al. (1988) and Bannasch et al. (2001) reported that foci of altered hepatocytes in rats
treated with peroxisome proliferators are amphophilic-basophilic [amphophilic: increased
granular acidophilia, and randomly scattered cytoplasmic basophilia], suggesting a phenotype
that also has increased mitochondrial proliferation and and peroxisome proliferation. Thus, the
106 DRAFT - DO NOT CITE OR QUOTE
-------
phenotype of TCA hepatic preneoplastic lesions may be different than that induced by
peroxisome proliferators.
According to the extensive published literature (Bannasch et al., 2001; Bannasch, 1996;
Weber et al., 1988), altered hepatic foci in hepatocarcinogenesis generally fall into three types:
1) glycogenotic-basophilic lineage: glycogenotic clear and acidophilic (smooth endoplasmic
reticulum-rich) hepatocytes which progress to glycogen-poor, homogeneously basophilic
(ribosome rich) phenotype in undifferentiated hepatocellular carcinomas; 2) tigroid-basophilic
lineage: tigroid foci, a variant of glycogenotic foci (probably occurring at low dose), contain
large basophilic bodies on a clear or eosinophilic cytoplasmic background. 3) amphophilc -
basophilic cell lineage: ampholilic cells consist of glycogen-poor cytoplasm containing both
abundant granular-acidophilic (mitochondria and peroxisomes) and basophilic (ribosomes)
component. Amphophilic cells occur when rats are treated with nongenotoxic peroxisome
proliferators. All three types of foci can progress to a basophilic phenotype as tumors progress.
Experimental support for these three altered hepatocyte lineages is available. Kraupp-
Grasl et al. (1990, 1991) noted a difference in the ability of a peroxisome proliferator to promote
tigroid foci and weakly basophilic foci, which are characterized by weak diffuse basophilia and
some eosinphilia (equivalent to amphophilic foci described earlier). In their experiments, using
phenobarbital (PB) or the peroxisome proliferator nafenopin (NAF) as promoters, only NAF and
not PB promoted the weakly basophilic foci. In addition, a substantial number of spontaneous
foci (the number of which were actually decreased by NAF) were tigroid. Both tigroid and
weakly basophilic foci may appear to be basophilic at the light microscopic level; thus, it is not
clear from Stauber and Bull (1997) and Pereira et al. (1996) whether the reported "basophilic"
foci from TCA treatment are actually "tigroid" or "weakly basophilic." Moreover, because of
the natural progression of several lineages of preneoplastic lesions, including those not induced
by peroxisome proliferators, to basophilic neoplasms (Bannasch et al. 1996), basophilic tumors
themselves are non-specific to peroxisome proliferators.
With respect to immunostaining characteristics, the foci and tumors induced by
peroxisome proliferators have been noted to not express GGT and GSTpi (Rao et al. 1986). It
has been shown by Parnell et al. (1988) that TCA promotes GGT-positive foci, in partial
hepatectomized rats initiated with DEN, which is the opposite of that expected for peroxisome
proliferators. (However, it is not known if TCA promotes GGT-positive foci in rats that were
not partially hepatectomized.) With respect to GSTpi, Pereira and Phelps (1996), Pereira et al.
(1997), and Latendresse and Pereira (1997) found most tumors in their initiation-promotion
studies of MNU+TCA to be lacking in GSTpi, consistent with that expected from peroxisome
proliferators. However, basophilic foci that are both GGT negative and GSTpi negative are not
specific to peroxisome proliferators. For instance, Kraupp-Grasl et al. (1990) and Grasl-Kraupp
et al. (1993) reported that tigroid foci, which display basophilia, were predominantly GGT
107 DRAFT - DO NOT CITE OR QUOTE
-------
negative regardless of whether they were found in control rats or rats given AfBl only, AfBl
plus the peroxisome proliferator NAF, or AfBl plus the non-peroxisome proliferator PB. Ittrich
et al. (2003) stated that GSTpi is negative in preneoplastic and neoplastic cell populations with
increased basophilic components.
With respect to immunostaining characteristic for c-Jun, Stauber and Bull (1997)
suggested that their observation that all TCA induced tumors were c-Jun negative, a
characteristic also found by Bull et al. (2002), was consistent with peroxisome proliferators.
However, tumors promoted by TCA in the experiments of Lantendresse and Pereira (1997)
variably stained for c-Jun. Furthermore, although spontaneous and some chemically-induced
foci and tumors have been reported to express or stain for c-Jun (Sakai et al., 1995; Suzuki et al.
1990; Nakano et al., 1994), both induction (Tharappel et al., 2003) and suppression (Yokoyama
et al., 1993) of c-Jun by short-term exposure to peroxisome proliferators has been reported in the
liver or in vitro, with no studies located that report c-Jun immunostaining of peroxisome
proliferator-induced foci or tumors. Therefore, it is questionable to use immunostaining
characteristic for c-Jun as an indicator for the PPARa mode of action.
In summary, proposed key events in the hypothesized PPARa agonism MOA have been
shown to occur with TCA treatment, including PPARa activation and hepatocellular
proliferation. However, the available data are insufficient to discern whether the PPARa MOA
is a sole causative factor for TCA hepatocarcinogenesis. Studies on PPARa published since
NRC (2006) indicate that the TCA mechanism of action is more complex than that presented in
NRC (2006), and much remains unclear. Specifically, a study by Yang et al. (2007) showed that
ligand-independent PPARa activation in hepatocytes evokes the MOA but not
hepatocarinogenesis in a transgenic mouse model. In addition, while other data associated
PPARa agonism with DEHP hepatocarcinogenesis, a second recent study found that DEHP
induces liver tumors in PPARa- null mice (Ito et al., 2007). Together, these studies demonstrate
that PPARa activation is neither sufficient for carcinogenesis, nor necessary for DEHP-induced
liver tumors. While prior reviews (e.g. Klaunig et al., 2003) have proposed that PPARa agonism
and its sequelae constitute a MOA for hepatocarcinogenesis as a sole causative factor, these
newer data have raised considerable doubt about the validity of this hypothesis for DEHP 8. In
addition, effects of TCA including increased c-myc expression and hypomethylation of DNA are
not specific to the PPAR-a activation MOA and other data also contribute uncertainty as to
whether PPARa-independent MOA may be involved in TCA-induced tumors in mice.
8 The NRC report entitled Phthalates and Cumulative Risk Assessment: The Task Ahead states
the Ito et al. (2007) results "suggest that DEHP might cause hepatic cancer in rodents through a
mechanism that is independent of PPARa, as has been suggested by others (see, for example,
Takashima et al. 2008)." A separate NRC report entitled Science and Decisions: Advancing Risk
Assessment states that the Ito et al. (2007) study "calls into question" the conclusion regarding
DEHP carcinogenicity that is based on the PPAR-a activation MOA.
108 DRAFT - DO NOT CITE OR QUOTE
-------
4.7.3.1.1.3. Dose-response Concordance.
_Clear dose response concordance between proposed key events and tumor response is
lacking.
The doses that induce peroxisome proliferation in mice are similar to tumorigenic doses
of TCA (Bull, 2000). B6C3Fi and other strains of mice treated with 1-5 g/L TCA in drinking
water for 14 days showed dose dependent increases in hepatic peroxisomal enzyme CACT
activity and cyanide- insensitive PCO activity (DeAngelo et al., 1989). Dose-dependent
increases in relative liver weights were also observed. Similarly, dose-related increases in
hepatic cyanide-insensitive AGO activity and 12-hydroxylation of lauric acid were observed in
male B6C3Fi mice treated with 0.1 to 2 g/L TCA in drinking water for 3 or 10 weeks.
Peroxisome proliferation was evaluated in only one chronic bioassay in mice (DeAngelo
et al., 2007). PCO activity was increased in mice treated with 0.5 g/L (68 mg/kg-day) or 5 g/L
(602 mg/kg-day) of TCA, the dose levels that were carcinogenic, providing support that PPARa
agonism is related to tumor formation. However, as stated above, peroxisome proliferation is an
associative event and marker of PPARa agonism and not correlated with carcinogenic potency of
PPARa agonists.
The doses that induce hepatocellular proliferation in mice corresponded to tumorigenic
doses of TCA in DeAngelo et al. (2008). Increase in incidence of hepatocellular adenomas and
carcinomas was observed in male B6C3Fi mice exposed to 0.5 g/L or 5 g/L TCA for 30 to 60
weeks, but not at 0.05g/L TCA. Significant increase in hepatocellular proliferation was found in
mice exposed to 5 g/L TCA at 30 and 45 week, and in 0.5 g/L TCA group at 60 week. A small
increase in hepatocyte proliferation was found in the 0.05 g/L TCA group at 78 week. Doses of
0.3 - 3.3 g/L TCA that caused hepatocellular proliferation in short-term studies (Sanchez and
Bull, 1990; Pereira, 1996) were similar to the tumorigenic doses.
4.7.3.1.1.4. Human relevance. In its framework for making conclusions about human
relevance, the U.S. EPA Cancer Guidelines (U.S. EPA 2005) outlines the following elements to
evaluate: (1) identifying critical similarities and differences between test animals and humans
regarding the sequence of key precursor events; (2) flagging quantitative differences for
consideration in dose-response assessment, such as the potential for different internal doses of
the active agent or differential occurrence of a key precursor event; (3) considering all
populations and life stages, including special attention to whether tumors can arise from
childhood exposure.
With respect to the first element, there is no evidence for qualitative differences between
rodents and humans in the key events described above for the proposed PPARa MOA. Humans
possess PPARa at sufficient levels to mediate the human hypolipidemic response to peroxisome-
109 DRAFT - DO NOT CITE OR QUOTE
-------
proliferating fibrate drugs (Klaunig et al., 2003). Klaunig et al. (2003) reached a conclusion
[reiterated by NRC (2006)] that the key events are plausible in humans in the sense that "a point
in the rat/mouse key events cascade where the pathways is biologically precluded in humans
cannot be identified, in principle." The human and mouse forms of PPARa are comparable in
their affinity for TCA, as shown in vitro by Maloney and Waxman (1999). Therefore, the
PPARa MOA described above should be relevant to humans.
With respect to the second question, the limited available data suggest there are
quantitative differences between rodents and humans in the occurrence of events following
PPARa activation. However, these data do not appear sufficient for use in dose-response.
Walgreen et al. (2000) found TCA did not increase palmitoyl CoA oxidation and caused a
decrease in DNA synthesis in primary and long term human hepatocytes cultures (in contrast to
rodents). Palmer et al. (1998) and Tugwood et al. (1999) reported about ten-fold less PPARa
mRNA in human liver as compared to rat or mouse, but mRNA levels are not necessarily
indicative of protein levels. Walgren et al. (2000) found on average lower levels of PPARa
protein in human livers as compared to rodents, but expression levels were highly variable
among individuals, and at least in one case was comparable to rodents. Moreover, expression
levels may not be related to potency, as the hypolipidaemic response to PPARa agonists is
similar in humans and rodents. On the other hand, humans and non-human primates appear less
sensitive than rodents to the PPARa-mediated peroxisome proliferation response and its
associated changes in regulation of peroxisomal genes and proteins. However, none of these
effects are thought to be causally related to hepatocarcinogenesis (Klaunig et al. 2003), and it
appears that carcinogenic potency and degree of peroxisomal response are not well correlated
(Marsman et al. 1988).
Lack of induction of cell proliferation or increased apoptosis have been observed in vitro
with human hepatocytes, but no method for quantitative extrapolation in vitro-to-in vivo of
results from these systems is available. Moreover, these assay systems remove the NPCs (e.g.,
Kupffer cells) during preparation, which has been shown to prevent the proliferative response to
PPARa agonists (Hasmall et al. 2000; Parzefall et al. 2001). In vivo, no increase in cell
proliferation was observed in non-human primates treated with PPARa agonists (Doull et al.
1999), but no human data is available. Hoivik et al (2004) noted that fenofibrate and ciprofibrate
induced treatment related increases in liver weight, hypertrophy, numbers of peroxisomes,
numbers of mitochondria and smooth endoplasmic reticulum in cynomologous monkeys at 15
days of exposure. However, no cell proliferation was found.
While the observed species differences in the occurrence of key events may be explained
partially by differences in expression levels of PPARa in liver, recent studies (Cheung et al.,
2004; Morimura et al.,2006; Shah et al. 2007) using PPARa-humanized mice fed Wy-14643
suggested that structural differences in human and mouse PPARa receptors may be more critical.
110 DRAFT - DO NOT CITE OR QUOTE
-------
A PPARa-humanized mouse line in which the human PPARa was expressed in liver under
control of the tetracycline responsive regulatory system was used in these studies. The PPARa-
humanized mice were fed the prototype peroxisome proliferator Wy-14643 or lipid-lowering
drug fenofibrate. Decreased serum triglycerides was observed in both the wild-type and PPARa-
humanized (hPPARa) mice, with no difference in basal serum triglyceride levels between the
two types of mice. In addition, a robust induction of the expression of genes encoding enzymes
involved in peroxisomal, mitochondrial, and microsomal fatty acid catabolism, and those
involved in fatty acid synthesis and transport was found in hPPARa mice after 2 weeks of Wy-
14643 or fenofibrate feeding. Hepatomegaly and increases in hepatocyte size were observed in
mice fed Wy-14643 for 2 weeks. However, the extent of cell size and hepatomegaly was
markedly less in hPPARa mice when compared with wild-type mice, especially after 8 weeks of
Wy-14643 feeding.
Cheung et al. (2004) also evaluated peroxisome proliferator-induced replicative DNA
synthesis by measuring BrdUrd incorporation into hepatocytes nuclei in hPPARa mice and wild-
type mice after 8 weeks feeding with Wy-14643. In wild-type mouse livers, Wy-14643
treatment resulted in a BrdUrd labeling index of 57.9% compared with 1.6% in untreated
controls. However, in hPPARa mice, Wy-14643 treatment did not increase the incorporation of
BrdUrd with average labeling indices of 2.8% and 1.6% in Wy-14643 - and control-treated
mice, respectively. In addition, Wy-14643 treatment resulted in a marked induction in the
expression of various genes involved in cell cycle control (PCNA, c-myc, CDK1, CDK4, and
cyclins A2, Dl, and E) in the livers of wild-type mice. However, the expression of these genes
was unchanged with Wy-14643 treatment in hPPARa mice. On the other hand, genes encoding
peroxisomal, mitochondrial, and microsomal fatty acid oxidation enzymes were still markedly
induced in hPPARa mice following 8 weeks of Wy-14643 feeding. Therefore, whereas human
PPARa in mice regulates induction of fatty acid catabolism and lipid lowering, it does not
stimulate the adverse cell proliferative response that is thought to contribute to liver
carcinogenesis. In addition, as discussed above, Shah et al. (2007) reported that microRNA let-
7C was not suppressed in Wy-14643-treated hPPARa mice. Wy-14643 treatment of hPPARa
mice also did not induce c-myc and mir-17 expression.
Decreased susceptibility of hPPARa mice to Wy-14643-induced liver tumorigenesis was
shown by Morimura et al. (2006). When the feeding study of 0.1% Wy-14643 was extended to
44 weeks for hPPARa mice, and 38 weeks for wild-type mice, the incidence of liver tumors,
including hepatocellular carcinoma, was 71% in wild-type mice (5 adenomas and 2 carcinomas
out of 7 mice; 3 out of 10 treated mice died of toxicity). However, only 5% of Wy-14643-
treated hPPARa mice developed liver tumors (1 adenoma out of 20 mice, the adenoma
resembled spontaneous tumor). In addition, upregulation of cell cycle regulated genes such as
cyclin Dl (cdl) and cyclin-dependent kinases (Cdks) 1 and 4 were observed in non-tumorous
111 DRAFT - DO NOT CITE OR QUOTE
-------
liver tissues of Wy-14643-treated wild-type mice. The cMyc mRNA was also significantly
overexpressed in the Wy-14643-treated wild-type mice. On the other hand, expression of the
tumor suppressor gene, p53, was increased only in the livers of Wy-14643-treated hPPARa
mice. Morimura et al. (2006) concluded that structural differences between human and mouse
PPARa were responsible for the differential susceptibility to the peroxisome proliferator-induced
hepatocarcinogenesis.
These data in hPPARa mice are consistent with toxicodynamic differences between
humans and mice are due to structural differences between human and mouse PPARa.
However, it should be noted that only Wy-14643 has been tested in hPPARa mice for
carcinogen!city so far, and the duration of treatment was less than 1 year, so more studies need to
be conducted, especially with TCA, before definitive conclusions can be made regarding human
relevance using hPPARa mice.
As discussed previously, toxicokinetic differences also exist between human and mouse.
Binding of TCA to plasma proteins was found to be higher in humans than in mice in two in
vitro studies (Templin et al., 1995; Lumpkin et al., 2003). Thus, plasma levels of free TCA
would be expected to be lower in humans than in mice administered the same dose of TCA,
consistent with less susceptibility of humans than mice to TCA-induced liver tumors.
With respect to the final question, little data on population variability and life-stages,
particularly with respect to childhood exposures and susceptability, are available either for TCA
or PPARa agonists in general.
A number of other reports have also made conclusions as to the human relevance of the
PPARa-agonist induced hepatocarcinogenesis, both in general and with respect to specific
chemicals. The recent NRC (2006) report reiterated the position of Klaunig et al. (2003) that
"[w]hereas the mode of action is plausible in humans, the weight of evidence suggests that this
mode of action is not likely to occur in humans based on differences in several key steps when
taking into consideration kinetic and dynamic factors." In the framework for MOA used here
(U.S. EPA 2005a), human relevance is considered in the context of hazard characterization. As
discussed above, both humans and rodents share the ability for PPARa receptor activation but
with similarities and differences in a number of responses. In addition, in this analysis (U.S.
EPA 2005a), quantitative differences due to "kinetic and dynamic factors" are flagged for
consideration in dose-response assessment. Toxicokinetics of TCA are discussed earlier in this
document. With respect to toxicodynamics, as discussed above, data suitable for use in dose-
response analysis of TCA hepatocarcinogenic risk are lacking.
Another recent report is the SAB review of EPA's draft risk assessment of potential
human health effects associated with perfluorooctanoic acid (PFOA) and its salts (SAB, 2006).
The SAB concluded that PFOA-induced liver tumors in rats were considered relevant to humans
based on the following considerations : 1) "uncertainties still exist as to whether PPARa
112 DRAFT - DO NOT CITE OR QUOTE
-------
agonism constitute the sole mode of action for PFOA effects on liver"; 2) "Uncertainties exist
with respect to the relevance to exposed fetuses, infants and children of the PPARa agonism
mode of action for induction of liver tumors in adults"; 3) "the interplay between PPARa
agonism and Kupffer cells (resident macrophages in the liver) has not been characterized...
Kupffer cells do not express PPARa, but are activated by peroxisome proliferators. Prevention
of Kupffer cell activation by glycine inhibited, although not completely, the development of liver
tumors by the potent peroxisome proliferator, WY-14643. There are no data available on the
effects of peroxisome proliferators on human Kupffer cells". These conclusions are similar to
those above for TCA.
4.7.3.1.1.5. Summary. In summary, the data for TCA, while supportive of the involvement of
PPARa in hepatocarcinogenesis, are not sufficient to conclude that it is the sole MOA.
Moreover, there is a substantial uncertainty and inconsistency with this proposed MOA. Thus,
the current data do not rule out the possibility that TCA could induce cancer in humans by a
MOA not associated with PPARa agonism. To the extent that PPARa is involved, the key
events in the proposed MOA by Klaunig et al (2003) to be causally related to carcinogenesis are
biologically plausible in humans, so this MOA would be considered relevant to humans. On the
other hand, toxicokinetic and toxicodynamic differences between species exist in the responses
to PPARa agonists and specifically to TCA, although the available data on such differences are
not suitable for use in dose-response analysis of TCA hepatocarcinogenic risk. While
tremendous progress has been made on our knowledge of the PPARa MOA, further studies with
various types of PPARa agonists need to be conducted before definitive conclusions can be
drawn regarding the relative human sensitivity to the hepatocarcinogenic effects of PPARa
agonists.
4.7.3.1.2. Decreased intercellular communication.
Inhibition of intercellular communication has been attributed to tumor induction by some
peroxisome proliferators (Klaunig et al., 2003, 1988). However, similar inhibition has been
reported with nongenotoxic liver carcinogens that are not peroxisome proliferators. Thus, this
proposed MOA is not specific to peroxisome proliferators and PPARa agonism. This MOA is
not well characterized.
From a physiological perspective, the formation of gap junctions with short half-lives in
cell membranes can be considered a regulatory control factor for tumor formation (Benane et al.,
1996). Transfer of molecules from neighboring normal cells to transformed cells via
intercellular communication allows growth suppression of transformed cells. Blocking
intercellular communication on a repetitive basis releases the "initiated" cells from the growth
control constraint exerted by neighboring cells and facilitates tumor formation. Studies by
113 DRAFT - DO NOT CITE OR QUOTE
-------
Benane et al. (1996) and Klaunig et al. (1989) (see Section 4.5.1) suggest that TCA-induced
inhibition of gap junction intercellular communication could potentially play a role in regulation
of cell differentiation, growth and homeostasis, and tumor promotion.
4.7.3.1.3. Altered cell proliferation.
TCA-induced changes in cell growth regulation have also been suggested as a
mechanism for the formation of liver tumors. As discussed previously, TCA-induced cell
proliferation may be PPARa-dependent, as centrilobular hepatocyte hypertrophy (cell
proliferation itself was not measured) was observed only in the livers of wild-type mice treated
with up to 2.0 g/L TCA in drinking water for 7 days, but not in PPARa-null mice treated with
the same dose of TCA (Laughter et al., 2004). The discussion here evaluates other possible
pathways.
There is little evidence that hepatocyte cytotoxicity followed by regenerative hyperplasia
is associated with TCA exposure. As described above for noncarcinogenic liver effects of TCA,
increased liver weight has been consistently reported as a low-dose effect in numerous studies,
but liver necrosis is generally either not reported or occurs only at much higher doses (Parrish et
al., 1996; Pereira; 1996; Acharya et al., 1995; Dees and Travis, 1994).
In vitro studies also support the conclusion that TCA does not induce tumors through cell
growth secondary to necrosis, because TCA does not appear to be highly toxic to hepatocytes.
Pravacek et al. (1996) evaluated the hepatotoxicity of DC A and TCA in liver slices from male
B6C3F1 mice and the metabolic capacity of the liver for these two compounds. In the
cytotoxicity studies, the liver slices were exposed for up to 8 hours at concentrations of TCA
ranging from 0 to 86 mM. Cytotoxicity was dependent on the duration of exposure, with a
greater effect observed at 8 hours than at 3 or 6 hours. Estimated EC50 concentrations were
reported for each of four measures of cytotoxicity, including potassium leakage, LDH, AST, and
ALT activities in the medium. Estimated EC50 values ranged from 64 to 72 mM for potassium
leakage, LDH activity, and AST activity, while no dose response was observed for ALT activity.
In another in vitro study using hepatocyte suspensions from male B6C3F1 mice and Sprague-
Dawley rats, the possible role of cytotoxic effects in contributing to TCA-induced
hepatocarcinogenicity was evaluated (Bruschi and Bull, 1993). Cytotoxicity was measured by
the release of LDH and by tryphan blue exclusion in the exposed cells, as well as by depletion of
intracellular reduced GSH. No effects were seen in TCA-treated cells at concentrations up to 5.0
mM and exposure times up to 240 minutes, suggesting that little cytotoxicity occurs from
exposure to TCA as measured by the biomarkers employed. Thus, the in vitro results suggest
that TCA is not highly cytotoxic to hepatocytes.
Rather than regenerative hyperplasia, differential effects on growth of normal and
initiated cells have been suggested as an alternative MOA of TCA, although the underlying
114 DRAFT - DO NOT CITE OR QUOTE
-------
mechanism is unclear, and may involve PPARa. Bull (2000) suggested that TCA acts by
increasing the clonal expansion of initiated cells while decreasing growth of normal cells. Data
from Stauber and Bull (1997) were cited as evidence for this MOA. In this experiment, mice
were exposed to a high concentration of TCA for 50 weeks and then removed from treatment or
continued at the same exposure for an additional 2 weeks. Evaluation of cell proliferation found
that the growth of TCA-initiated tumor cells was high and similar levels were seen in mice taken
off TCA treatment and in animals maintained on TCA for the entire experiment. By contrast,
replication was inhibited in normal hepatocytes. Thus, initiated cells would have a growth
advantage over growth-inhibited normal cells following continuous treatment.
Bull (2000) argued that TCA might not only inhibit growth of normal cells but may also
enhance growth of initiated cells with certain phenotypes, based on the results of Stauber et al.
(1998). Stauber et al. (1998) demonstrated that TCA increases cell proliferation of c-JUN
negative hepatocytes in vitro. These investigators treated isolated hepatocytes from naive 5- to
8-week-old mice with TCA at concentrations ranging from 0 to 2.0 mM and plated the cells to
allow them to form colonies. Exposure of the cells to 0.5 mM TCA and above significantly
increased colony formation in the absence of cytotoxicity as compared with controls.
Anchorage-independent colonies were induced by TCA in a dose-dependent manner and were c-
JUN negative, which is the same phenotype observed in TCA-induced liver tumors in mice
exposed in vivo to TCA. The expression of c-JUN was not induced when isolated hepatocytes
were cultured as monolayers in the presence of 2.0 mM TCA, indicating that TCA selectively
affects subpopulations of anchorage-independent hepatocytes. The authors concluded that the
results of this study demonstrated that TCA promotes the survival and growth of different
populations of initiated hepatocytes. The ability of TCA to act as a tumor promoter (Parnell et
al., 1988; Latendresse and Pereira, 1997; Pereira and Phelps, 1996) supports the selective growth
MOA described in Bull (2000).
4.7.3.1.4. Genotoxicity.
TCA has been tested for genotoxicity in a variety of in vitro and in vivo assays as
described in Section 4.4.2. Most but not all studies report negative (Kargalioglu et al., 2002;
Nelson et al., 2001; DeMarini et al., 1994; Rapson et al., 1980) results for mutagenicity in S.
typhimurium in the absence of cytotoxicity. Mutagenicity in mouse lymphoma cells was only
induced at cytotoxic concentrations (Harrington-Brock et al., 1998). Both positive and negative
responses have been observed in vivo. TCA-induced DNA strand breaks and chromosome
damage were observed in the liver in several studies (Giller et al., 1997; Nelson and Bull, 1988;
Bhunya and Behera, 1987) and were suggested by the results of Harrington-Brock et al. (1998),
although these effects have not been uniformly reported (Chang et al., 1992; Styles et al., 1991).
However, some evidence indicates that TCA-induced chromosome damage assayed in vitro and
115 DRAFT - DO NOT CITE OR QUOTE
-------
in vivo can be secondary to pH changes rather than a direct effect of TCA (Mackay et al., 1995),
underscoring the need to carefully evaluate assay conditions.
In other studies of potential genotoxicity, DNA-repair responses to TCA in bacterial
systems have been inconsistent, with induction of DNA repair reported in S. typhimurium (Ono
et al., 1991) but not in E. coli (Giller et al., 1997). Oxidative DNA damage, as measured by be
genotoxicity. TCA induced oxidative DNA damage in the livers of mice following a single dose
(Austin et al., 1996) but not following repeated dosing over 3 or 10 weeks (Parrish et al., 1996),
possibly suggesting either effective DNA repair and/or adaptation to repeated TCA exposures.
Ferreira-Gonzalez et al. (1995) found that the mutation frequency and mutation spectrum in the
H-ras gene were similar in tumors from control and TCA-treated mice, suggesting that TCA was
not inducing tumors through direct DNA damage at this locus. The pattern of TCA-induced
tumors in mice does not support a mutagenic mode of action. Tumors were observed only in
livers of TCA-exposed mice. No tumors were found in TCA treated rats.
In summary, there is some evidence that TCA is weakly mutagenic; however, the overall
evidence for the mode of action(s) for carcinogenicity is inconclusive.
4.7.3.2. Conclusions About the Hypothesized Mode of Action
In summary, TCA is clearly carcinogenic in mice (Bull et al., 2002, 1990, 2000, 2004;
Pereira, 1996). Numerous recent studies have investigated the mechanism by which TCA
induces liver tumors. The data do not support a genotoxic mechanism (Bull, 2000; Moore and
Harrington-Brock, 2000). Rather, tumor induction appears to involve perturbation of cell growth
and/or reduced intercellular communication (Benane et al., 1996). There is support for the
involvement of PPARa; however, uncertainties remain if PPARa agonism is the sole
carcinogenic MO A of TCA in mice.
116 DRAFT - DO NOT CITE OR QUOTE
-------
4.8. SUSCEPTIBLE POPULATION AND LIFE STAGES
4.8.1. Possible Childhood Susceptibility
Age-dependent differences in susceptibility to TCA have not been investigated in
systemic toxicity studies. The dose spacing in the available developmental toxicity studies
(Table 4-7) is inadequate to determine the relative fetal and maternal toxicity of TCA. The
LOAELs for developmental toxicity range from 291 mg/kg-day (Johnson et al., 1998) to 1000
mg/kg-day (Singh, 2005a). Most developmental LOAELs occurred at maternally toxic doses.
Therefore, these developmental toxicity data are too limited to draw any conclusions on whether
developing organisms might be a sensitive subpopulation. In subchronic toxicity studies, a
LOAEL and NOAEL of 355 and 36.5 mg/kg-day, respectively, were observed in male rats
exposed to TCA in drinking water for 90 days (Mather et al., 1990). In the Parrish et al. (1996)
10-week drinking water study with male mice, the LOAEL and NOAEL were 125 and 50 mg/kg-
day, respectively. The LOAELs observed in the subchronic toxicity studies suggest that systemic
effects are observed at doses similar to, or less than, those at which developmental toxicity has
been observed; however, no developmental NOAELs are available for comparison with the
subchronic systemic NOAELs. Given the lack of a developmental NOAEL, it is uncertain what
dose would be protective for developmental toxicity.
The data are also insufficient to determine whether there are age-dependent differences in
the toxicokinetics (e.g., plasma binding and metabolism) of TCA that might lead to differences
in health risk. There are no published comparative data for plasma binding of TCA in young and
old animals. The enzymes responsible for the metabolism of TCA have not been conclusively
identified. Even in the cases where relevant metabolizing enzymes have been identified, no
information on age-dependent changes in the expression or activity of these enzymes has been
identified. The health implications of any differences between children and adults in metabolic
capacity are also difficult to determine for the haloacetic acids, since the toxic form of each
compound has not been identified. The mechanisms involved in haloacetic acid toxicity are not
sufficiently understood to make this determination. The preliminary results of Hunter and
Rogers (1999) in whole embryo culture suggest that, at least for the developmental effects, the
parent compound may be involved in the toxicity of MCA, while for TCA a metabolite may be
involved. However, in vitro studies such as whole embryo culture have limited utility for
predicting the developmental toxicity of chemical agents in intact organisms and are considered
to be useful only for hypothesis generation not for hypothesis testing. Further in vivo studies are
needed to determine whether there are age-related differences in susceptibility to toxic effects of
TCA.
The cancer potency of TCA in very young animals has been investigated in a mouse
neonatal cancer assay (Von Tungeln et al., 2002). In this study, neonatal male and female
B6C3Fi mice were given i.p. injections of TCA in DMSO at 1000 or 2000 nmol (total dose,
117 DRAFT - DO NOT CITE OR QUOTE
-------
which corresponds to approximately 16 or 32 mg/kg) in split doses delivered at 8 and 15 days of
age. The test animals were sacrificed and evaluated for liver tumors at 12 (high dose) or 20 (low
dose) months of age. The incidence of hepatic tumors in TCA-treated animals did not differ
significantly from tumor incidences observed in the solvent controls.
4.8.2. Possible Gender Differences
No data directly relevant to the evaluation of the effects of gender on TCA toxicity in
humans were located. The available animal data, although limited, suggest that males may be
more sensitive to the carcinogenicity of TCA than females. Only one cancer bioassay was
located that concurrently exposed both male and female mice to TCA (Bull et al., 1990)
(described in Section 4.2). In this study, male and female B6C3Fi mice were exposed to TCA in
the drinking water at concentrations that resulted in doses of up to approximately 329 mg/kg-day
for 52 weeks. A clear dose-related increase in animals with proliferative lesions (hyperplastic
nodules, adenomas, or carcinomas) was observed in males (incidence of up to 19/24, which
occurred at 329 mg/kg-day). In contrast, the incidence of proliferative lesions in females was
not increased (data not reported). Although no other studies were available that evaluated the
carcinogenicity of TCA in males and females concurrently, the available single-sex cancer
bioassays conducted in separate laboratories also suggest that males may be more sensitive than
females to TCA carcinogenicity. For example, Pereira et al. (2001) (described in Section 4.2)
observed a tumor incidence of 25% in female B6C3Fi mice exposed to TCA in the drinking
water at a dose of 784 mg/kg-day for 51 weeks. In contrast, tumor incidences ranging from 55%
to 83% have been reported in males exposed to lower TCA doses (309 to 480 mg/kg-day) in the
drinking water for a comparable duration (Bull et al., 2000, 1990). These data indicate that TCA
is a more potent carcinogen in male than in female mice.
Although males appear to be more sensitive than females to carcinogenicity of TCA, the
available data suggest that males and females are about equally sensitive to noncancer effects
induced by TCA. For example, Bull et al. (1990) observed that the type and magnitude of the
noncancer liver effects induced by TCA were similar in male and female B6C3Fi mice exposed
to TCA in the drinking water at comparable doses for 52 weeks. Davis (1990) did not observe
marked differences in the susceptibility of males and females to TCA-induced noncancer effects
in a short-term toxicity study. Although both of these studies were limited by the scope of
toxicological parameters evaluated, they suggest that male and female animals are similar in
their sensitivity to TCA-induced noncancer effects.
4.8.3. Other Factors Influencing Susceptibility
Limited information was identified regarding other factors (e.g., genetic polymorphisms,
enzyme deficiencies, or altered health states) that might influence susceptibility to TCA. Some
118 DRAFT - DO NOT CITE OR QUOTE
-------
data are available for DCA and may be relevant to TCA. Several genetic polymorphisms have
been identified in GST-(^, a key enzyme involved in DCA metabolism. As noted previously, it is
unclear whether TCA is metabolized to DCA (Bull, 2000; Lash et al., 2000); these
polymorphisms would be relevant to TCA susceptibility only if DCA is a metabolite of TCA.
As noted previously, TCA induces glycogen accumulation. Kato-Weinstein et al.
(1998) suggested that prolonged glycogen accumulation can become irreversible. These data
suggest that individuals with glycogen storage disease (an inherited deficiency or alteration in
any one of the enzymes involved in glycogen metabolism) constitute another group that may be
more susceptible to TCA toxicity.
No quantitative evaluation has been conducted on the health impact of environmental
exposures for individuals harboring polymorphisms in genes related to glycogen storage or
antioxidant response. In each of these cases, a significant background load of the stressor may
be present; thus, the excess risk associated with low doses of TCA is not clear.
119 DRAFT - DO NOT CITE OR QUOTE
-------
5. DOSE-RESPONSE ASSESSMENTS
5.1. ORAL REFERENCE DOSE (RfD)
The RfD9 for TCA was derived through a three-step process of: 1) evaluating all toxicity
studies, and selecting the critical effects from these studies that occur at the lowest dose; 2)
selecting the dose or point of departure10 (POD) at which the critical effect either is not observed
or would be predicted to occur at a relatively low incidence (e.g., 10%), and 3) dividing this
POD by uncertainty factors (UFs) to reflect uncertainties in extrapolating from study conditions
to conditions of human environmental exposure.
5.1.1. Choice of Principal Study and Critical Effect—with Rationale and Justification
Chronic, subchronic, and developmental animal toxicity studies considered for derivation
of the oral RfD are summarized in Table 5-1. Two of the available chronic oral drinking water
studies (DeAngelo et al., 1997; DeAngelo et al., 2008) were identified as potential candidates
from which to derive the RfD. The study in rats by DeAngelo et al. (1997) identified a NOAEL
of 32.5 mg/kg-day and a LOAEL of 364 mg/kg-day based on significantly decreased body
weight, a statistically significant and dose-related increase in serum ALT activity, and
histopathological changes in the liver. The study in mice by DeAngelo et al. (2008) identified a
NOAEL of 8 mg/kg-day and a LOAEL of 68 mg/kg-day for hepatocellular cytoplasmic
alterations, increase in liver weight, increase in liver peroxisome proliferation, hepatic necrosis,
and testicular tubular degeneration. Histopathological examinations were conducted on organs
other than the liver in both DeAngelo et al. (1997) and DeAngelo et al. (2008), other chronic
mice studies have only evaluated the liver. In a cancer study in mice by Pereira (1996), only a
limited number of end points were evaluated, but a higher NOAEL for liver effects of 78 mg/kg-
day was identified. Two other chronic-duration drinking water studies (Bull et al., 1990; Herren-
Freund et al., 1987) were not further considered for derivation of the RfD because they examined
only a limited number of endpoints in the liver and used higher administered doses than those
employed by DeAngelo et al. (1997) and DeAngelo et al. (2008).
Subchronic toxicity data were available from studies conducted in rats by Mather et al.
(1990) and Bhat et al. (1991). The 90-day drinking water study by Mather et al. (1990)
established NOAEL and LOAEL values of 36.5 and 355 mg/kg-day for effects on relative liver
9The RfD is an estimate (with uncertainty spanning perhaps an order of magnitude) of a daily exposure to
the human population (including sensitive subgroups) that is likely to be without appreciable risk of deleterious
effects during a lifetime. It can be derived from a NOAEL, LOAEL, or benchmark dose, with uncertainty factors
generally applied to reflect limitations of the data used. The RfD is expressed in terms of mg/kg-day of exposure to
an agent.
10The POD denotes a dose at the lower end of the observed dose-response curve where extrapolation to
lower doses begins. For effects other than cancer, the POD is either a NOAEL, a LOAEL if no NOAEL can be
identified, or a modeled point (for example, an LECio or LED10) if the data are suitable for dose-response modeling.
120 DRAFT - DO NOT CITE OR QUOTE
-------
and kidney weights and peroxisome proliferation. These values are similar to and support the
NOAEL and LOAEL values obtained for hepatic effects in the chronic study of DeAngelo et al.
(1997) in rats. Bhat et al. (1991) observed decreased body weight gain, minor changes in liver
morphology, and inflammation of the lungs in rats administered a dose equivalent to one-fourth
of the LDso of 3300 mg/kg (or approximately 825 mg/kg-day).
121 DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-1. Candidate studies for derivation of the RfD for TCA
Reference
Species
Exposure
route
Exposure
duration
Doses evaluated
(mg/kg-day)
Observed effects
NOAEL
(mg/kg-day)
LOAEL
(mg/kg-day)
Comments
Chronic studies
DeAngelo
etal.
(1997)
DeAngelo
etal.
(2008)
Pereira
(1996)
Bull et al.
(1990)
Herren-
Freund et
al. (1987)
F344 rats
(males,
50/group)
B6C3FJ mice
(males,
50/group)
B6C3FJ mice
(females,
38-1347
group)
B6C3FJ mice
(11-24/sex
and dose)
B6C3FJ mice
(males, 22-
337 group)
Oral,
drinking
water
Oral,
drinking
water
Oral,
drinking
water
Oral,
drinking
water
Oral,
drinking
water
104 Weeks
60 weeks
51 or 82
Weeks
(A) 52
Weeks
(B)37
Weeks +
15 -week
recovery
61 Weeks
0, 3.6, 32.5, or
364
0, 8, 68 or 602
mg/kg-day
0, 78, 262, or 784
(A) 0, 164, or
329
(B) 0 or 309
0, 500, or 1250
Decreased body weight,
increased serum ALT
activity; increased
peroxisome proliferation
Hepatocellular cytoplasmic
alteration, increase in liver
weight, increase in liver
peroxisome proliferation,
hepatic necrosis, testicular
tubular degeneration.
Increased relative liver weight
Increased absolute and
relative liver weight,
cytomegaly, glycogen
accumulation
Increased absolute and
relative liver weight
32.5
8
78
None
None
364
68
262
164
500
Time-weighted average
daily doses were calculated
by the authors; a
comprehensive set of
tissues was microscopically
examined.
Time-weighted average
daily doses were calculated
by the authors; a
comprehensive set of
tissues was microscopically
examined for the control
and high dose groups.
Increased liver weight was
observed after 82 weeks at
262 mg/kg-day; 262
mg/kg-day was judged to
be an equivocal LOAEL in
the absence of other
measures of liver toxicity.
Only the liver and kidneys
were evaluated; dose was
estimated by the authors.
Only the liver was
microscopically examined.
QUOTE
122
DRAFT - DO NOT CITE OR
-------
Table 5-1. Candidate studies for derivation of the RfD for TCA
Reference
Species
Exposure
route
Exposure
duration
Doses evaluated
(mg/kg-day)
Observed effects
NOAEL
(mg/kg-day)
LOAEL
(mg/kg-day)
Comments
Subchronic studies
Mather et
al. (1990)
Bhat et al.
(1991)
Sprague-
Dawley rats
(males,
10/dose)
Sprague-
Dawley rats
(males,
5/group)
Oral,
drinking
water
Oral,
drinking
water
90 Days
90 Days
0,4.1, 36.5, or
355
0 or 825
Decreased absolute spleen
weight; increased relative
liver and kidney weights;
peroxisome proliferation
Decreased body weight gain;
minor changes in liver
morphology; collagen
deposition; perivascular
inflammation of the lungs
36.5
None
355
825
1/4 of the LD50 (3,300
mg/kg) was administered
daily.
Developmental studies
Smith et
al. (1989)
Johnson et
al. (1998)
Long-Evans
rats (20-
2 I/dose)
Sprague-
Dawley rats
(55 controls
andllTCA-
treated rats)
Oral,
gavage
Oral,
drinking
water
CDs 6-15
CDs 1-22
0, 330, 800,
1200, or 1800
0 or 291
Maternal: Decreased body
weight; increased spleen and
kidney weights
Developmental:
Decreased fetal weight,
decreased crown-rump
length, increased incidence of
soft-tissue and cardiovascular
malformations; increased
maternal spleen and kidney
weights
Maternal: Toxicologically
significant decrease in
maternal body weight
Developmental:
Increase in cardiac
malformations; increase in
number of implantation
sites/litter, number of
Maternal:
None
Develop-
mental:
None
Maternal:
None
Develop-
mental:
None
Maternal:
330
Develop-
mental:
330
Maternal:
291
Develop-
mental:
291
Critical study for 1994
RfD.
The developmental LOAEL
was also a maternal
LOAEL.
LED10 values of 28 and 3 1
mg/kg-day were obtained
for reduced fetal body
weight and litter incidence
of levocardia, respectively,
by benchmark dose
modeling. (See Tables 5-3
and 5-4).
Dose estimated by the
authors, based on the
average amount of water
consumed by the animals
on a daily basis.
Study was not adequately
designed and/or reported,
and a complete array of
123
DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-1. Candidate studies for derivation of the RfD for TCA
Reference
Fisher et
al. (2001)
Species
Sprague-
Dawley rats
(19/dose)
Exposure
route
Oral,
gavage
Exposure
duration
CDs 6-15
Doses evaluated
(mg/kg-day)
0 or 300
Observed effects
resorption sites/litter, and
total resorptions
Maternal: Decreased body
weight gain on GDs 7-15 and
18-21; decreased uterine
weight
Developmental: Decreased
fetal body weight (per litter
and per fetus)
NOAEL
(mg/kg-day)
Maternal:
None
Develop-
mental:
None
LOAEL
(mg/kg-day)
Maternal:
300
Develop-
mental: 300
Comments
standard developmental end
points was not assessed.
A limited number of fetal
endpoints were evaluated,
including sex, fetal weight,
and incidence of heart
malformations.
Source: Adapted in part from U.S. EPA (2003b). Additional details on these studies are provided in Section 4 of this document.
124
DRAFT - DO NOT CITE OR QUOTE
-------
Three developmental toxicity studies (Fisher et al., 2001; Johnson et al., 1998; Smith et
al., 1989) were also evaluated as potential candidates for use in the derivation of the RfD. Smith
et al. (1989) identified a developmental LOAEL of 330 mg/kg-day (the lowest dose tested) for
increased incidence of fetal cardiac malformations and significantly reduced fetal body weight
and crown-rump length in Long-Evans rats dosed by gavage on GDs 6-15. Johnson et al. (1998)
identified a developmental LOAEL of 291 mg/kg-day for fetal cardiac malformations in a single-
dose study where Sprague-Dawley rats were dosed via drinking water on GDs 1-22. Fisher et
al. (2001) observed decreased fetal body weight, but saw no evidence of cardiac malformations
in a single-dose study where Sprague-Dawley rats were dosed with 300 mg/kg-day by gavage on
GDs 6-15. These studies were considered for use in the derivation of an oral RfD. Although
both Smith et al. (1989) and Johnson et al. (1998) observed increased incidences of cardiac
defects following treatment of pregnant rats with TCA, Fisher et al. (2001) observed no
significant increase in cardiac anomalies despite using a sensitive staining technique for analysis
of fetal cardiac tissues.
The chronic drinking water study in mice by DeAngelo et al. (2008) was considered the
most appropriate choice among the available studies for derivation of the RfD. In this study, the
route of exposure was oral, both a LOAEL and NOAEL were identified for liver effects which
were both lower than the corresponding values identified in the chronic drinking water study in
rats (DeAngelo et al., 1997), and the data in this chronic mouse study were consistent with the
findings in both chronic drinking water studies in rats (Mather et al., 1990; DeAngelo et al.,
1997). In addition, complete histopathological examinations were conducted for all organs for
the control and high dose groups, whereas other studies in mice only evaluated the liver.
Moreover, the incidence data in DeAngelo et al. (2008) were amenable to BMD modeling.
Selected data from the developmental toxicity study conducted by Smith et al. (1989)
were analyzed by benchmark dose (BMD) modeling for comparison with the POD for liver
effects (DeAngelo et al., 2008) selected for derivation of the RfD. The developmental data
analyzed were: 1) incidence data for fetuses with visceral malformations (of which levocardia
was the principal lesion), 2) data on fetal body weight and fetal crown-rump length, and 3) litter
incidence data for levocardia. The methods used and results obtained from this BMD modeling
are described in detail in Sections 5.1.2.2 and 5.1.2.3. The most sensitive modeled responses
were fetal body weight and litter incidence of levocardia. The 95% lower confidence limits
(BMDLos) on the BMD values obtained for these endpoints were 28 mg/kg-day (average from
three models) and 31.3 mg/kg-day, respectively, at a benchmark response (BMR) of 5% extra
risk.
125 DRAFT - DO NOT CITE OR QUOTE
-------
5.1.2. Methods of Analysis
5.1.2.1. Benchmark Dose Modeling of Liver and Testicular Effects from DeAngelo et al.
(2008)
BMD modeling was used to analyze liver and testicular effects in male mice exposed to
TCA in drinking water (DeAngelo et al., 2008). Incidence data for hepatocellular cytoplasmic
alterations, hepatocellular inflammation, hepatocellular necrosis, and testicular tubular
degeneration are summarized in Tables 4-3 and 4-4. All of the available dichotomous models in
U.S. EPA's BMDS (version 1.4.1) were fit to these incidence data. Doses (i.e., BMDio and
BMDLio) associated with a benchmark response (BMR) of 10% extra risk were calculated and
are presented in Tables 5-2 through 5-5. A BMR of 10% is generally used in the absence of
information regarding what level of change is considered biologically significant, and also to
facilitate a consistent basis of comparison across assessments.
Details of the BMD modeling conducted for each endpoint presented in Tables 5-2
through 5-5 are provided in Appendix B. In general, model fit was assessed by a chi-square
goodness-of-fit test (i.e., models with p < 0.1 failed to meet goodness-of-fit criterion) and visual
inspection of the respective plots of observed versus predicted values from the fitted models. If
BMDLio estimates from these models were within a factor of two of each other, no appreciable
model dependence was suggested. Of the fitted models exhibiting adequate fit (i.e., p > 0.1), the
model yielding the lowest AIC value was selected as the best fitting model. If more than one
model shared the lowest AIC, BMDLio values from these models were averaged to obtain a
POD.
As Table 5-2 shows for hepatocellular cytoplasmic alterations, all of the dichotomous
models fitted to these data exhibited statistically significant lack of fit, indicating lack of dose-
response relationship for hepatocellular cytoplasmic alterations. Therefore, this endpoint was
not selected as a candidate for RfD development using BMD methods. For hepatocellular
inflammation, Table 5-3 shows that the logistic, one-stage multistage, probit, and log-probit
models all exhibited adequate fit. Because the logisitic and log-probit models shared the lowest
AIC value (i.e., 74.19), the BMDLi0s from these two models were averaged to yield a potential
POD of 260.5 mg/kg-day. In Table 5-4, four of the seven models fitted to the incidence of
hepatocellular necrosis did not exhibit statistically significant lack of fit. These four models
were the gamma, log-logistic, one-stage multistage, and Weibull. Of these four models, the log-
logisitic yielded the lowest AIC value (i.e., 30.42), and thus the BMDLio of 18 mg/kg-day
estimated by this model was selected as a potential POD. Finally, as shown in Table 5-5, all of
the models fitted to the incidence of testicular tubular degeneration exhibited adequate fit, but
the log-logisitic model yielded the lowest AIC (i.e., 76.08). Therefore, the BMDLio estimate of
127.4 mg/kg-day from the log-logistic model was selected as another potential POD. Clearly,
the endpoint of hepatocellular necrosis was the most sensitive of the three endpoints, as it
126 DRAFT - DO NOT CITE OR QUOTE
-------
resulted in the lowest POD estimate of 18 mg/kg-day. Hepatocellular necrosis also had the
highest severity score. Therefore, the POD of 18 mg/kg-day was selected as a potential
candidate for use in derivation of the RfD.
127 DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-2. Benchmark dose modeling results based on incidence of
hepatocellular cytoplasmic alterations in male B6C3Fi mice exposed to
TCA in drinking water for 60 weeks (DeAngelo et al., 2008)
Fitted
Dichotomous
Model3
Gamma
Logistic
Log-Logistic
Multistage (2°)
Probit
Log-Probit
Weibull
Chi-Square
Goodness-of-Fit
Test/>-Valueb
0.0002
0.0005
0.0002
0.0009
0.0005
0.0002
0.0002
AICC
116.16
115.06
116.16
114.5
115.03
116.16
116.16
BMD10d
(mg/kg-day)
286.4
65.9
350.8
126.9
66.1
249.6
398.2
BMDL10e
(mg/kg-day)
34.9
47.2
49.7
28.0
50.3
53.4
33.0
Footnotes:
a All dichotomous dose-response models were fit using BMDS, Version 1.4.1. Note that all
models fitted exhibited a statistically significant (p < 0.1) lack of fit.
b />-Value from the chi-square goodness-of-fit test for the selected model. Values < 0.1 suggest
that the model exhibits a significant lack of fit, and a different model should be chosen.
0 AIC = Akaike's Information Criterion, a value useful for evaluating model fit. For those
models exhibiting adequate fit, lower values of the AIC suggest better model fit.
d BMD10 = Benchmark dose at 10% extra risk.
e BMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
128
DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-3. Benchmark dose modeling results based on incidence of
hepatocellular inflammation in male B6C3Fi mice exposed to TCA in
drinking water for 60 weeks (DeAngelo et al., 2008)
Fitted
Dichotomous
Model3
Gamma
Logistic
Log-Logistic
Multistage (1°)
Probit
Log-Probit
Weibull
Chi-Square
Goodness-of-Fit
Test/>-Valueb
0.096
0.24
0.096
0.22
0.24
0.26
0.096
AICC
76.15
74.19
76.16
74.29
74.20
74.19
76.16
BMD10d
(mg/kg-day)
354.2
391.9
351.0
292.0
376.1
394.1
361.9
BMDL10e
(mg/kg-day)
151.6
276.6
132.1
149.4
257.1
244.4
151.6
Footnotes:
a All dichotomous dose-response models were fit using BMDS, Version 1.4.1. The "best-fit"
models are indicated in boldface type.
b />-Value from the chi-square goodness-of-fit test for the selected model. Values < 0.1 suggest
that the model exhibits a significant lack of fit, and a different model should be chosen.
0 AIC = Akaike's Information Criterion, a value useful for evaluating model fit. For those
models exhibiting adequate fit, lower values of the AIC suggest better model fit.
d BMD10 = Benchmark dose at 10% extra risk.
e BMDL10 = 95% lower confidence limit on the benchmark dose at 10% extra risk.
129
DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-4. Benchmark dose modeling results based on incidence of
hepatocellular necrosis in male B6C3Fi mice exposed to TCA in drinking
water for 30 to 45 weeks (DeAngelo et al., 2008)
Fitted
Dichotomous
Model3
Gamma
Logistic
Log-Logistic
Multistage (1°)
Probit
Log-Probit
Weibull
Chi-Square
Goodness-of-Fit
Test/>-Valueb
0.18
0.058
0.49
0.18
0.060
0.036
0.18
AICC
31.85
36.39
30.42
31.85
36.26
36.84
31.85
BMD10d
(mg/kg-day)
64.9
205.1
40.7
64.9
188.0
158.7
64.9
BMDL10e
(mg/kg-day)
37.6
128.4
17.9
37.6
120.0
54.3
37.6
Footnotes:
a All dichotomous dose-response models were fit using BMDS, Version 1.4.1. The "best-fit"
model is indicated in boldface type.
b />-Value from the chi-square goodness-of-fit test for the selected model. Values < 0.1 suggest
that the model exhibits a significant lack of fit, and a different model should be chosen.
0 AIC = Akaike's Information Criterion, a value useful for evaluating model fit. For those
models exhibiting adequate fit, lower values of the AIC suggest better model fit.
d BMD10 = Benchmark dose at 10% extra risk.
e BMDL10 = 95% lower confidence limit on the benchmark dose at 10% extra risk.
130
DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-5. Benchmark dose modeling results based on incidence of
testicular tubular degeneration in male B6C3Fi mice exposed to TCA in
drinking water for 60 weeks (DeAngelo et al., 2008)
Fitted
Dichotomous
Model3
Gamma
Logistic
Log-Logistic
Multistage (1°)
Probit
Log-Probit
Weibull
Chi-Square
Goodness-of-Fit
Test/>-Valueb
0.19
0.16
0.19
0.19
0.17
0.13
0.19
AICC
76.16
76.59
76.08
76.16
76.54
77.06
76.16
BMD10d
(mg/kg-day)
321.9
439.7
298.2
321.9
425.3
471.6
321.9
BMDL10e
(mg/kg-day)
153.3
290.3
127.4
153.3
271.2
276.8
153.3
Footnotes:
a All dichotomous dose-response models were fit using BMDS, Version 1.4.1. The "best-fit"
model is indicated in boldface type.
b />-Value from the chi-square goodness-of-fit test for the selected model. Values < 0.1 suggest
that the model exhibits a significant lack of fit, and a different model should be chosen.
0 AIC = Akaike's Information Criterion, a value useful for evaluating model fit. For those
models exhibiting adequate fit, lower values of the AIC suggest better model fit.
d BMD10 = Benchmark dose at 10% extra risk.
e BMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
5.1.2.2. Benchmark Dose Modeling of Developmental Toxicity Data from Smith et al (1989)
Selected data from the developmental toxicity study conducted by Smith et al. (1989)
(Table 5-6) were analyzed by BMD modeling for comparison with the POD derived from
DeAngelo et al. (2008). Nested developmental toxicity models were employed in order to
account for inter-individual correlation of toxicity endpoints within litters. Supporting
information for the BMD analyses is provided in Appendix C. The fetal data analyzed were as
follows: 1) quantal incidence data for fetuses with visceral malformations (of which levocardia
was the principal lesion), and 2) continuous data for fetal body weight and fetal crown-rump
length. These endpoints were selected based on the availability of individual animal data, which
is required for the nested analysis used to account for inter-individual correlation within litters.
To facilitate comparison of BMDs across endpoints, individual data for fetal body weight and
crown-rump length were converted into quantal form, as discussed in the next paragraph.
The continuous data were converted into quantal form (i.e., incidence of the number of
responders per number of members in a group) for analysis. Conversion involved: 1) an
131 DRAFT - DO NOT CITE OR QUOTE
-------
assumption that the data (either body weight or crown-rump length) were normally distributed,
and 2) the use of the estimated distribution of the controls to define a response. Responders were
defined as displaying a measured value < a critical value = the overall control mean -za * SD,
where za = the percentage point of the standard normal distribution at a probability level of a
(conversions were calculated with a = 0.05; for large numbers of samples, za is approximately
equal to 1.645), and SD = standard deviation of the mean of the control group.
Table 5-6. Dose response data for developmental endpoints in TCA-treated
Long-Evans rats
Endpoint
Dose (mg/kg-day)
0
330
800
1200
1800
Quantal data
Fetuses with visceral malformations
Fetal incidence3'13
Litter incidence13'0
Mean % fetuses affected per
litter"
6/176
4/26
3. 50 ±8.7
14/140
8/19
9.06±12.9d
27/111
15/17
30.4 ±28.1
29/65
11/14
55.4±36.1d
19/20
8/8
96.98 ±8.8d
Fetuses with cardiovascular malformations
Fetal incidence
Litter incidence
Mean % fetuses affected per
litte/
NRe
NR
0.96 ±4.9
NR
NR
5.44±10.0d
NR
NR
23.6±28.0d
NR
NR
46.8±36.5d
NR
NR
94.8±9.9d
Fetuses with levocardia
Fetal incidencef
Litter incidencef
Mean % fetuses affected per
litter
0/196
0/26
NR
9/151
6/19
NR
20/111
12/17
NR
24/69
10/14
NR
17/22
7/8
NR
Continuous data
Mean fetal crown-rump length in cmg
Male
Female
3.71 ±0.12
3.64 ±0.15
3.58±0.10d
3.53±0.09d
3.46±0.10d
3.38±0.12d
3.36±0.15d
3.33±0.16d
3.16±0.12d
3.15±0.15d
Mean fetal body weight in gg
Male
Female
3.70 ±0.24
3.54 ±0.20
3.20±0.26d
3.08±0.27d
2.98±0.17d
2.83±0.18d
2.74±0.30d
2.67±0.29d
2.49±0.16d
2.36±0.15d
Tetal incidence = number of fetuses affected/number of fetuses examined.
bUnpublished data provided to Dr. R. Kavlock, EPA, by Dr. K. Smith.
°Litter incidence = number of litters with < 1 affected fetus/number of litters examined.
dMean is significantly different from control mean (p < 0.05) as reported by Smith et al., 1989.
eNR = not reported or able to be calculated from available sources.
fFrom Tables 5 or 6, Smith et al. (1989).
gFrom Table 4, Smith et al. (1989).
Source: Smith etal. (1989).
This conversion method assumes that the control group has a 5% background response
rate (i.e., 5% of individuals in the control population have body weight or crown-rump length
132 DRAFT - DO NOT CITE OR QUOTE
-------
below the critical value). Standard deviations used in this method were derived from all fetal
body weights or crown-rump lengths in the control group without regard to litter. These
estimates, therefore, contain both between-litter and within-litter variations. The control group
mean body weight was 3.64 g (SD = 0.287; n = 284); the calculated critical value for a = 0.05
was 3.16 g. The control group mean crown-rump length was 3.7 cm (SD = 0.163; n = 282); the
calculated critical value for a = 0.05 was 3.4 cm. Thus, for the two continuous variable
endpoints, the quantilization process classified each fetus in each litter as either a responder
(e.g., body weight <_3.16 g or crown-rump length ^3.4 cm) or a nonresponder (body weight
value > 3.16 g or crown-rump length > 3.4 cm).
Three nested models, each of which included dose and litter size as explanatory variables
and accounted for intralitter correlation by assuming a B-binomial distribution for individual fetal
responses (see eq. 5-1), were used to model each data set. The models were as follows: 1) a log-
logistic model as described by Kupper et al. (1986); 2) the model described by Rai and van
Ryzin (1985); and 3) the modified model described by Kodell et al. (1991). Computer programs
developed by Richard Howe based on the three papers cited above (TERALOG, TERAVAN,
and TERAMOD, respectively, from ICF Kaiser International, 1208 Gaines Street, Ruston, LA,
71270)11 were used to fit these models by maximum likelihood methods to the Smith et al.
(1989) data sets. The following equations represent the models (d = dose; s = litter size; do =
threshold dose, set to zero for these data sets; a = background response parameter; p = dose rate
parameter; 0i, 02 = litter size parameters):
TERALOG: P(d,s) = a + 0ixs+{l-a-0ixs}/{!+ exp[p + 02 x s - y log (d-d0)]},
where 0
-------
responses for body weight decrease are estimated to occur at lower doses than those producing
equivalent responses for increased visceral malformations or crown-rump length decrease. For
example, using the 0,0.05 critical values of 3.16 g and 3.4 cm to define response of body weight
and crown-rump length, the BMD05 values for increased incidence of fetuses with decreased
body weight were 72, 25, and 23 mg/kg-day for the three models, respectively, compared with
BMDos values of 399, 369, and 320 mg/kg-day for increased visceral malformations, and 391,
375, and 345 mg/kg-day for increased incidence of fetuses with decreased crown-rump length
(Table 5-7). Corresponding BMDL05 values were 41,21, and 21 mg/kg-day for decreased body
weight compared with 220, 218, and 212 mg/kg-day for visceral malformations, and 278, 272,
and 241 mg/kg-day for crown-rump length <3.4 cm. The average BMDos and BMDLos
(calculated from the values obtained using each of the three models) for fetal body weight were
40 and 28 mg/kg-day, respectively. It should be noted that these values are well below the
lowest tested dose of 330 mg/kg-day. The use of the BMDLos for decreased fetal body weight as
a potential POD for theRfD is discussed in Section 5.1.3.
134 DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-7. Benchmark dose modeling results for fetal incidence data
Model
BMD05a
(mg/kg-day)
BMDL05b
(mg/kg-day)
BMD10a
(mg/kg-day)
BMDL10b
(mg/kg/day)
Fetal body weight
TERALOG
TERAMOD
TERAVAN
72
25
23
41
21
21
107
50
48
67
42
43
Fetal crown-rump length
TERALOG
TERAMOD
TERAVAN
391
375
345
278
272
241
530
525
510
417
420
439
Fetal visceral malformations
TERALOG
TERAMOD
TERAVAN
399
369
320
220
218
212
537
518
485
352
358
397
Note: Continuous data (body weight and crown-rump length) were converted to quantal data before modeling, as
discussed in text.
aBMD05, BMD10 = maximum likelihood estimates of dose associated with 5% or 10% extra risk of fetuses with
decreased body weight, decreased crown-rump length, or visceral malformations.
bBMDL05, BMDL10 = 95% lower confidence limits for the respective BMD05 or BMD10 values.
Source: Smith etal. (1989).
Litter incidence data (number of affected litters/number of litters examined) for
levocardia (Table 5-8) were modeled using the Benchmark Dose Software (BMDS) program
(Version 1.3.1) developed by the U. S. EPA National Center for Environmental Assessment (U. S.
EPA, 2000b) in accordance with U.S. EPA (2000d) recommendations. The data were analyzed
using dichotomous models (gamma, logistic and log-logistic, probit and log-probit, multistage,
and Weibull) in the BMDS program. Use of nested models was not required because the data
analyzed were reported on a per litter basis, and thus no adjustment was required for intralitter
correlation. Note, however, that the extent of levocardia within each litter is not captured in this
incidence measure. The BMD and BMDL values were calculated based on BMRs of 5% and
10% extra risk that a litter would have at least one fetus affected with levocardia. Confidence
bounds calculated by the BMDS software used a maximum likelihood profile method. Output
from the BMDS program was evaluated by using the criteria described in U.S. EPA (2000d).
The best fits to the data were obtained with the multistage and gamma models (Table 5-
8), as judged by Akaike's information criterion (AIC). The results from these models were
identical (as were the forms of the models based on the data input). Figure 5-1 plots predicted
(from the fitted gamma model) and observed incidence of levocardia as a function of
administered dose, as well as the BMD0s and the lower 95 % limit on the BMD0s (the BMDLos).
The BMDos and BMDLos values estimated for the litter incidence of levocardia by these models
were 42 mg/kg-day and 31 mg/kg-day (rounded values), respectively. It should be noted that
135 DRAFT - DO NOT CITE OR QUOTE
-------
these values are well below the lowest tested dose. The use of the BMDLos for increased
incidence of litters with levocardia as a potential POD for the RfD is discussed in Section 5.1.3.
Table 5-8. Benchmark dose modeling results for litter incidence of levocardia
Model
Multistage
Gamma
Log-logistic
Log-probit
Weibull
Logistic
Probit
Goodness-of-fit
p-value
0.9430
0.9430
0.9106
0.9069
0.8648
0.0520C
0.0449C
AICa
69.8459
69.8459
71.6069
71.6259
71.8203
80.642
80.6568
BMD05
42
42
74
87
36
144
136
BMDLos
31b
31b
17
9
1
101
99
BMD10
86
86
122
130
76
253
244
BMDL10
64b
64b
36
20
5
187
185
aAIC = Akaike Information Criterion.
Preferred model(s) based on criteria described in U.S. EPA (2000d).
'Because goodness-of-fit ^-values were below the recommended minimum value of 0.1, the results of these models
were not further considered for estimation of the BMD.
Source: Smith etal. (1989).
136
DRAFT - DO NOT CITE OR QUOTE
-------
Gamma Multi-Hit Model with 0.95 Confidence Level
1
£0.6
<
.1 0.4
"o
2 nn
u. 0.2
0
Gamma Multi-Hit
BMDLBMD
0
500
14:31 08/102004
1000
dose
1500
Figure 5-1. Plot of predicted and observed litter incidence of levocardia in
offspring of female Long-Evans rats exposed to TCA on GDs 6-15.
Note: The BMD and BMDL are the predicted dose and lower 95% confidence
limit associated with a 5% extra risk for litters with at least one fetus with
levocardia.
5.1.3. RfD Derivation—Including Application of Uncertainty Factors (UFs)
The chronic mouse drinking water study by DeAngelo et al. (2008) was selected as the
principal study for derivation of the oral RfD as discussed in Section 5.1.1. The RfD for TCA is
calculated using the POD based on the incidence of hepatocellular necrosis identified in the
principal study (eq. 5-2).
RfD = POD -H UF
= 18 mg/kg-day- 1000
= 0.018 mg/kg-day, rounded to 0.02 mg/kg-day
(5-2)
where 18 mg/kg-day = POD for the incidence of hepatocellular necrosis in mice exposed to TCA
via drinking water for 30 to 45 weeks (DeAngelo et al., 2008) and 1000 = composite UF chosen
to account for extrapolation from animals to humans, interindividual variability in humans, and
insufficiencies in the database (see below).
137
DRAFT - DO NOT CITE OR QUOTE
-------
For developmental endpoints, BMDLos values were used as the POD. Reproductive and
developmental studies having nested study designs often have greater sensitivity, and a BMR of
5% has typically been used for such studies (U.S. EPA, 2000b). Use of the BMDL05 value for
either reduced fetal body weight (28 mg/kg-day) or litter incidence of levocardia (31 mg/kg-day)
(Smith et al., 1989) as an alternative POD and the composite UF of 1000 would result in an RfD
of 0.03 mg/kg-day (i.e., a value 50 percent higher than the one obtained using the POD based on
hepatocellular necrosis). Because these alternate derivations are based on results extrapolated
about an order of magnitude below the observed data, however, they are relatively uncertain
compared with the POD derived from the principal study. Thus, the RfD for TCA was derived
from the POD for hepatocellular necrosis observed by DeAngelo et al. (2008).
The following UFs were applied in the calculation of the RfD to address extrapolation
from animal study conditions to conditions of human environmental exposure: 10 for
consideration of intraspecies (human) variability, 10 for extrapolation from an animal study to
humans (animal-to-human), and a factor of 10 to account for deficiencies in the TCA database.
The total UF = 10 x 10 x 10 = 1000.
The UFs used in calculation of the RfD were selected for the following reasons:
• Human variation. A default UF value of 10 is used to account for human variability and
protection of potentially sensitive subpopulations. This value was selected because there
are no data on human variability in the toxicokinetics or toxicodynamics of TCA and
because information on differences in human susceptibility to TCA as a consequence of
age, sex, health, or genetic factors is lacking.
• Animal-to-human extrapolation. A default UF of 10 is used to account for extrapolation
from an animal study to humans. No suitable data on the toxicity of TCA to humans
exposed by the oral route were identified. Insufficient information is currently available
to assess rat-to-human differences in TCA toxicokinetics or toxicodynamics.
• Database insufficiencies. An UF of 10 is used to account for database insufficiencies.
There are no TCA-specific systemic toxicity data in humans. Although subchronic and
chronic animal studies of TCA have been conducted in rats and mice, most studies have
focused primarily or exclusively on liver lesions and have not examined other organs for
microscopic lesions. Other data gaps include lack of a multigeneration reproductive
toxicity study and lack of a developmental toxicity study in a second species.
138 DRAFT - DO NOT CITE OR QUOTE
-------
• Subchronic-to-chronic extrapolation. An UF for study duration was not required in this
assessment because the principal study was of chronic duration.
• LOAEL-to-NOAEL extrapolation. An UF for LOAEL-to-NOAEL adjustment was not
required in this assessment because the current approach is to address this extrapolation
as one of the considerations in selecting a BMR for BMD modeling. In this case, a BMR
corresponding to a 10% increase in the incidence of hepatocellular necrosis was selected
under the assumption that it represents a minimally biologically significant change.
5.1.4. RfD Comparison Information
The RfD derived from DeAngelo et al. (2008) mouse study was compared with potential
RfDs derived from DeAngelo et al. (2007) rat study and Smith et al. (1980) rat study. RfD
derived from these studies are similar.
Figure 5-1. Comparison of RfDs Across Target Organs or Endpoints
IUU -
10 -
">;
ro
8£ i
I
0 01 -
./v
66i
-------
5.1.5. Previous RfD Assessment
The previous IRIS assessment for TCA does not have an RfD. .
5.2. INHALATION REFERENCE CONCENTRATION (RfC)
No inhalation studies adequate for the derivation of an RfC12 were located. The available
information was inadequate for a route-to-route extrapolation from the oral pathway to the
inhalation pathway. Physiologically-based toxicokinetic models, which might be useful for
route-to-route extrapolation, have not been developed for TCA.
5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE
The following discussion identifies uncertainties associated with the RfD for TCA. As
presented earlier in this chapter (Sections 5.1.3 ), the UF approach, following EPA methodology
for RfD development (U.S. EPA, 2002), was applied to a POD. For the RfD, the POD was
determined as BMDLio for hepatocellular necrosis in treated mice. Factors accounting for
uncertainties associated with a number of steps in the analyses were adopted to account for
extrapolating the POD, the starting point in the analysis, to a diverse population of varying
susceptibilities. These extrapolations are carried out with default approaches instead of from
data on TCA, given the paucity of experimental TCA data to inform individual steps.
Selection of principal study and critical effect for reference value determination
The selected principal study was the most complete study in mice, with well defined
NOAEL/LOAEL, and data was amenable to dose-response modeling. Complete
histopathological examination was conducted for the high dose and control groups. Liver
toxicity, specifically hepatocellular necrosis, was selected as the critical effect for RfD. Liver
toxicity was the most consistent, and sensitive effect in rats and mice. Thus, there is little
uncertainty that this effect is relevant to humans.
Animal to human extrapolation
No human exposure studies are available for derivation of the RfD. For derivation of the
RfD, extrapolating dose-response data from animals to humans is a source of uncertainty.
Uncertainties pertaining to unknown interspecies differences in toxicokinetics and
toxicodynamics were addressed by application of a UF of 10.
Dose-response modeling
12The RfC is an estimate (with uncertainty spanning perhaps an order of magnitude) of a daily exposure to the
human population (including sensitive subgroups) that is likely to be without appreciable risk of deleterious effects
during a lifetime. It can be derived from a NOAEL, LOAEL, or benchmark concentration, with UFs generally
applied to reflect limitations of the data used.
140 DRAFT - DO NOT CITE OR QUOTE
-------
BMD modeling was used to estimate the POD for the RfD. While models with better
biological support may exist, the selected models provided adequate mathematical fits to the
experimental data sets. BMD modeling has advantages over a POD based on a NOAEL or
LOAEL because they are a reflection of the particular exposure concentration or dose at which a
study was conducted, they lack characterization of the dose-response curve, and they do not
address the variability of the study population. NOAELs and LOAELs also are less amenable to
quantitative uncertainty analysis.
Intrahuman variability
Heterogeneity among humans is another source of uncertainty. Uncertainty related to
human variation needs consideration, also, in extrapolation from a small subset of presumably
healthy humans to a larger, more diverse population. Although male mice appear to be more
sensitive than female mice to carcinogenicity of TCA, available data suggest that males and
females are about equally sensitive to noncancer effects induced by TCA. Limited information
was identified regarding other factors (e.g., genetic polymorphism) that might influence
susceptibility to TCA (see Section 4.8.3). A UF of 10 was used to account for intrahuman
variability. A factor of 10 was found to be generally sufficient to account for human variability
(Renwick and Lazarus, 1998).
5.4. CANCER ASSESSMENT
As discussed in Section 4.1.1, no epidemiologic studies currently exist that have
investigated the carcinogenicity of TCA in humans. The carcinogenicity of TCA has been
evaluated, however, in studies of both rats and mice. In mice, the results of these studies provide
evidence that TCA is a complete carcinogen, as exposure to TCA in drinking water for periods
of from 52 to 104 weeks significantly increased the incidence of liver tumors in male and female
B6C3Fi mice (Bull et al., 2004, 2000, 1990; Pereira, 1996; Pereira and Phelps, 1996; DeAngelo
et al., 2008; Herren-Freund et al., 1987). In several of these studies, a clear monotonic dose-
response relationship was evident, and the background incidence of tumors in control animals
was generally low (Pereira, 1996; Bull et al., 1990; DeAngelo et al., 2008). Moreover, the
development of tumors in animals exposed to TCA progressed rapidly, as evident from the
observation of significant numbers of tumors in less-than-lifetime studies of 82 weeks or less.
Positive evidence for tumor promotion by TCA (following exposure to known tumor initiators)
has been reported for liver tumors in B6C3Fi mice (Pereira et al., 2001, 1997) and for GGT-
positive foci in livers of partially hepatectomized Sprague-Dawley rats (Parnell et al., 1988). In
contrast to the results observed for mice, TCA was not carcinogenic in a study of male F344/N
rats exposed via drinking water for 104 weeks (DeAngelo et al., 1997). The carcinogenicity of
TCA has not been evaluated in female rats or in other species of experimental animals.
141 DRAFT - DO NOT CITE OR QUOTE
-------
As discussed in Section 4.7.3, data from recent TCA studies that have investigated the
MOA for hepatocarcinogenesis do not support a direct genotoxic mechanism. Instead, tumor
induction appears to result from perturbation of cell growth and/or reduced intracellular
communication, possibly through a PPARa MOA. There is considerable debate about the
mechanism by which peroxisome proliferators cause liver tumors in rodent models and whether
these chemicals represent a human cancer risk (NRC, 2006). Much experimental data for TCA
are consistent with a PPARa-mediated MOA (NRC, 2006). Two different interpretations of
available data were considered here in order to evaluate current scientific uncertainties relative to
dose-response assessment and peroxisome proliferator liver tumor induction.
The first possible interpretation is that the MOA or MO As for TCA-induced liver tumors
are unknown. Data suggests a number of potentially interrelated MOAs.While PPARa-mediated
effects appearto play a role in the induction of some rodent liver tumors, certain data
inconsistencies are troubling. Unresolved issues for PPARa as a MOAinclude: inconsistencies in
experimental results among species, sexes and PPARa agonists; some proposed key events are
not PPARa-specific; clear dose concordance between proposed key events and tumor response is
lacking, PPARa activation by itself was insufficient to induce liver tumors (Yang et al., 2007),
and PPARa activation was not necessary for tumor induction by DEHP (Ito et al, 2007). While
much progress has been made recently in filling gaps in our understanding of MO As further
studies, especially with TCA, are needed. Based on these concerns it seemed premature to
conclude that PPARa is the sole operative MOA for TCA induced liver tumors. This
interpretation would imply a weight of evidence conclusion that TCA is Likely to be
Carcinogenic to Humans, with use of the default linearly extrapolated dose-response analysis.
The second possible interpretation proposes that PPARa is the significant MOA in mouse liver
tumor induction by TCA, and the determination of human relevance is likely to depend on
comparison of cross-species dose-response relationships. Under this interpretation, weight of
evidencecould be either likely or unlikely to be carcinogenic depending on the relative cross-
species (mouse to human) differences in toxicokinetic or toxicodynamic sensitivity. Humans do
have functional PPARa receptors as evidence by PPARa-mediated responses to the therapeutic
fibrates drugs. Data from chemicals other than TCA suggest that humans are refractory to some,
but not all, PPARa activation effects. Careful consideration should be given to how kinetic and
dynamic factors control human vs. animal response. While this assessment has evaluated some
possible kinetic and dynamic factors, the effort is by no means comprehensive. Further effort are
outside the scope of the TCA document.
As new data become available, our interpretation may change. For instance, if key events
were identified that support nonlinear dose-response relationships below those leading to
observed effects, then nonlinear extrapolation could be utilized in the dose-response assessment.
If key causal events were identified that were both well correlated with cancer potency and for
142 DRAFT - DO NOT CITE OR QUOTE
-------
which cross-species sensitivity were known quantitatively, then the dose-response assessment
could account for the relative sensitivity between humans and mice to TC A-induced tumors. If it
were shown that one or more key events in TCA-induced tumorigenesis were completely
precluded in humans, then the weight-of evidence could be changed to "not likely to be
carcinogenic in humans.'"
In conclusion, TCA is determined to "Likely to be Carcinogenic to Humans" under
EPA's Guidelines for Carcinogen Assessment (USEPA, 2005a). Three lines of evidence
support this classification: 1) TCA is carcinogenic in the liver in multiple studies conducted in
B6C3F1 mice of both sexes; 2) tumor response was robust, occurring at substantially less-than-
lifetime exposures at which tumor rates in control animals was relatively low; and 3) the
available data for TCA do not suggest that the MOA for hepatocarcinogenesis in mice is not
relevant to humans. Finally, two significant limitations of the database for TCA carcinogenicity
are: 1) limited number of mouse studies that included microscopic evaluation of a
comprehensive set of organs in addition to the liver; and 2) the absence of epidemiologic studies
of TCA carcinogenicity in humans.
In the absence of a well-characterized MOA that could explain dose-response
relationships at doses lower than those leading to observed effects, the cancer dose-response
modeling is carried out using linear extrapolation (U.S. EPA, 2005a). Nonlinear extrapolation is
not considered an option, given the absence of data to extend the dose-response curves below the
bioassay doses. In addition, no data were found that were suitable for accounting for inter-
species differences in toxicokinetics or toxicodynamics in dose-response modeling.
In the previous assessment of TCA conducted by IRIS, TCA was classified as a "C," or
"possible human carcinogen." The previous IRIS assessment did not provide quantitative
estimates of carcinogenic risk from oral or inhalation exposure to TCA.
5.4.1. Choice of Study/Data—with Rationale and Justification
Using the U.S. EPA Benchmark Dose Software (BMDS, version 1.4.1), the multistage
model was fit to liver tumor incidence data (i.e., adenomas and carcinomas combined) from
bioassay s in B6C3Fi mice exposed to TCA in drinking water for 52 weeks (two studies in male
mice: Bull et al., 2002, 1990), 60 weeks (one study in male mice: DeAngelo et al., 2008), 82
weeks (one study in female mice: Pereira, 1996), and 104 weeks (one study in male mice:
DeAngelo et al., 2008). The tumor incidence data for adenomas, carcinomas, and adenomas and
carcinomas combined are presented in Seection5.32.
These studies in mice were selected for analysis and derivation of an oral slope factor for
TCA, because they: 1) included adequate numbers of animals for statistical analyses; 2) showed
statistically significant increased incidences of liver tumors (i.e., combined incidences of
adenomas and carcinomas), compared with control values; and 3) included multiple TCA
143 DRAFT - DO NOT CITE OR QUOTE
-------
exposure levels, thus allowing for a better characterization of the dose-response relationship,
especially at low dose.
5.4.2. Dose-Response Data
The dose-response data (i.e., incidence of hepatocellular adenomas and carcinomas
combined and human equivalent lifetime dose) from the five bioassays referenced above are
shown in Tables 5-9 through 5-13 and were fit using the multistage model in BMDS (version
1.4.1).
Table 5-9. Incidences of hepatocellular adenomas, carcinomas, or adenomas
and carcinomas combined in male B6C3Fi mice exposed to TCA in drinking
water for 52 weeks (Bull et al., 2002)
TCA concentration
(g/L)
0
0.5
2
Estimated
daily intake"
(mg/kg-day)
0
120
480
Human lifetime
equivalent doseb
(mg/kg-day)
0
2.38
9.5
Incidence of
adenomas
0/20
5/20
6/20
Incidence of
carcinomas
0/20
3/20
3/20
Incidence of
adenomas or
carcinomas0
0/20
6/20
8/20
a Doses were calculated using reference water intakes of 0.24 L/kg-day for male B6C3FJ mice (U.S. EPA, 1988).
b See text for conversion of mouse daily intakes to human equivalent lifetime doses.
0 Bull et al. (2002) reported combined incidences of adenomas or carcinomas for each dose group.
Table 5-10. Incidences of hepatocellular adenomas, carcinomas, or
adenomas and carcinomas combined in male B6C3Fi mice exposed to TCA in
drinking water for 52 weeks (Bull et al., 1990)
TCA concentration3
(g/L)
0
1
2
Estimated
daily intake1"
(mg/kg-day)
0
164
329
Human lifetime
equivalent dosec
(mg/kg-day)
0
3.25
6.51
Incidence of
adenomas
0/35
2/11
1/24
Incidence of
carcinomas
0/35
2/11
4/24
Incidence of
adenomas or
carcinomas'1
0/35
4/11
5/24
a An experimental design that included a control group and one dose group (2 g/L) using female mice was also part
of this study, but the data were deemed inadequate for modeling because a response at a single dose was considered
insufficient for properly characterizing a dose-response relationship.
b Calculated using total doses (g/kg) reported by Bull et al. (1990).
0 See text for conversion of mouse daily intakes to human equivalent lifetime doses.
dBull et al. (1990) did not report combined incidences for adenomas and carcinomas, so this total assumes that each
animal had either adenomas or carcinomas, but not both.
Table 5-11. Incidences of hepatocellular adenomas, carcinomas, or
adenomas and carcinomas combined in male B6C3Fi mice exposed to TCA in
drinking water for 60 weeks (DeAngelo et al., 2008)
|| TCA concentration | Estimated | Human lifetime | Incidence of | Incidence of | Incidence of ||
144 DRAFT - DO NOT CITE OR QUOTE
-------
(g/L)
0
0.05
0.5
5
daily intake"
(mg/kg-day)
0
8
68
602
equivalent doseb
(mg/kg-day)
0
0.24
2.07
18.3
adenomas0
2/30
4/27
6/29
11/29
carcinomas0
2/30
1/27
6/29
11/29
adenomas or
carcinomas'1
4/30
4/27
11/29
16/29
a Intakes were reported by DeAngelo et al. (2008).
b See text for conversion of mouse daily intakes to human equivalent lifetime doses.
0 Calculated from reported percentages of mice with adenomas or carcinomas.
d DeAngelo et al. (2008) reported combined incidences of adenomas or carcinomas for each dose group.
Table 5-12. Incidences of hepatocellular adenomas, carcinomas, or
adenomas and carcinomas combined in female B6C3Fi mice exposed to TCA
in drinking water for 82 weeks (Pereira, 1996)
TCA concentration
(mmol/L)
0
2
6.67
20
Estimated
daily intake"
(mg/kg-day)
0
78
262
784
Human life-time
equivalent doseb
(mg/kg-day)
0
6.1
20.4
61.1
Incidence of
adenomas
2/90
4/53
3/27
7/18
Incidence of
carcinomas
2/90
0/53
5/27
5/18
Incidence of
adenomas or
carcinomas0
4/90
4/53
8/27
12/18
a Intakes were calculated using reference water intake of 0.24 L/kg-day for female B6C3F! mice (U.S. EPA, 1988).
b See text for conversion of mouse daily intakes to human equivalent lifetime doses.
0 Pereira (1996) did not report combined incidences for adenomas and carcinomas, so this total assumes that each
animal had either adenomas or carcinomas, but not both.
Table 5-13. Incidences of hepatocellular adenomas, carcinomas, or
adenomas and carcinomas combined in male B6C3Fi mice exposed to TCA in
drinking water for 104 weeks (DeAngelo et al., 2008)
TCA concentration
(g/L)
0
0.05
0.5
Estimated
daily intake"
(mg/kg-day)
0
5.6
58
Human lifetime
equivalent doseb
(mg/kg-day)
0
0.84
8.7
Incidence of
adenomas0
9/42
8/35
19/37
Incidence of
carcinomas0
23/42
14/35
29/37
Incidence of
adenomas or
carcinomas'1
27/42
20/35
32/37
a Intakes were reported by DeAngelo et al. (2008).
b See text for conversion of mouse daily intakes to human equivalent lifetime doses.
0 Calculated from reported percentages of mice with adenomas or carcinomas.
d DeAngelo et al. (2008) reported combined incidences of adenomas or carcinomas for each dose group.
5.4.3. Dose Conversion
Before fitting the multistage model to the incidence data for adenomas and carcinomas
combined in Tables 5-9 through 5-13, estimated daily intakes of TCA from the mouse studies
were converted to human equivalent doses for continuous lifetime exposure using an interspecies
scaling factor of 0.15 (i.e., [male B6C3Fi mouse reference body weight/human reference body
145
DRAFT - DO NOT CITE OR QUOTE
-------
weight]0'25 = [0.0373/70]0'25 = 0.15) (U.S. EPA, 1992, 1988) and exposure duration scaling
factors of 0.132, 0.203, or 0.520 to adjust the 52-, 60-, or 82-week exposure durations,
respectively, to equivalent lifetime exposure durations (i.e., [duration of experiment/duration of
lifetime]3 = [52/102]3 = 0.132, or = [60/102]3= 0.203, or [82/102]3=0.520). These factors for
adjusting to lifetime equivalent durations are based on the assumption that the age-specific rate
for cancer in humans will increase by at least the third power of age (U.S. EPA, 1980). An
exposure duration scaling factor was not used in converting animal doses to human equivalents
in the 104-week study of DeAngelo et al. (2008) (Table 5-13) because 104 weeks represents a
lifetime exposure in mice. The human equivalent lifetime doses used in the dose-response
modeling are shown in the third column of Tables 5-9 through 5-13.
Individual animal data (specifying when tumors were detected in each animal with a liver
tumor) from the five bioassays were not available, precluding application of more sophisticated
dose-response modeling approaches to estimating lifetime cancer risks (e.g., by fitting models
that predict tumor incidence as a function of two explanatory variables, dose and time, and using
these models to predict tumor incidences for lifetime exposure). The multistage model was
restricted to two stages or less for the 52-week Bull et al. (2002, 1990) and the 104-week
DeAngelo et al. (2008) data sets employing three dose groups (including controls) and to three
stages or less for the 82-week Pereira (1996) and the 60-week DeAngelo et al. (2008) data sets
employing four dose groups (including controls). For each of the five data sets, a one-stage
multistage model provided the best fit to the data as determined by the chi-square goodness-of-fit
statistic and Akaike's information criterion (AIC). Model predictions compared with observed
incidences are shown in Figures D-l, D-2, D-3, D-4, and D-5 in Appendix D.
5.4.4. Extrapolation Methods
Adequacy of fit of the multistage model to each of the data sets was evaluated through
use of the chi-square goodness-of-fit statistic (see Table 5-14 and computer outputs in Appendix
D). For those models that did not exhibit significant lack of fit, the fitted model was used to
estimate the human equivalent lifetime dose associated with 10% extra risk (EDi0), and its
corresponding 95% lower and upper confidence limits (LEDio and UEDio, respectively) (Table
5-14). Candidate oral cancer slope factors were derived by linear extrapolation from the LEDio,
i.e., 0.1/LEDio, while a lower bound on these slope factors were derived by linear extrapolation
from the UEDio, i.e., 0.1/UEDio (Table 5-14). Slopes from the linear extrapolation from the
were also calculated, i.e., 0.1/EDi0 (Table 5-14).
146 DRAFT - DO NOT CITE OR QUOTE
-------
Table 5-14. Predicted human equivalent lifetime doses associated with 10% extra risk
(EDins) for hepatocellular adenomas and carcinomas combined and their corresponding
95% lower and upper confidence limits (LEDi0s and UEDi0s, respectively) based on the fit
of a one-stage multistage model. Oral cancer slope factors and their estimated 95% lower
bounds are also presented.
Study Reference
(study duration)
ED10
(mg/kg-
day)
LED10
(mg/kg-
day)
UED10
(mg/kg-
day)
x2
goodness
-of-fit
^j-value
Slope of linear
extrapolation
from ED10a
(mg/kg-day)1
Oral cancer
slope factor1"
(mg/kg-day) *
Oral cancer
slope factor:
Lower bound0
(mg/kg-day)1
Male Mice
Bull et al., 2002 (52 weeks)
Bull et al., 1990 (52 weeks)
DeAngeloetal.,2008
(60 weeks)
DeAngeloetal.,2008
(104 weeks)
1.41
1.97
2.83
0.89
0.93
1.19
1.71
0.50
2.79
3.61
5.86
2.37
0.16
0.12
0.15
0.32
7.1 x 10"2
5.1 x 10'2
3.5 x 10"2
1.1 x 10'1
1.1 x 10"1
8.4 x 10'2
5.8 x 1Q-2
2.0 x 10'1
3.6 x 10"2
2.8 x 10'2
1.7 x 1Q-2
4.2 x 10'2
Female Mice
Pereira, 1996 (82 weeks)
7.14
4.96
11.00
0.5
1.4 x 10'2
2.0 x 10'2
9.1 x 10'3
a The slope of a linear extrapolation from the ED10 is calculated as follows: 0.1/ED10.
b The oral cancer slope factor is derived by linearly extrapolating from the LED10 (i.e., 0.1/LED10).
0 The 95% lower bound on the oral cancer slope factor is derived by linearly extrapolating from the
0.1/UED10).
(i.e.,
As discussed in Section 4.7.3, studies investigating mode of action for TCA-induced liver
tumors do not provide strong evidence for genotoxicity (Bull, 2000; Moore and Harrington-
Brock, 2000). Rather, tumor induction appears to involve perturbation of cell growth, through
activation of the PPARa pathway (Bull, 2000; Austin et al., 1996; Parrish et al., 1996), and
reduced intracellular communication (Benane et al., 1996). However, the existing evidence is
not sufficient to determine which, if any, of these mechanisms are causally related to the
observed tumor responses. In addition, data are not available to identify dose-response
relationships for possible precursor events for TCA-induced liver tumors. Therefore, data from
these mouse studies are too limited for the application of biologically-based dose-response
models, or other more sophisticated methods of analysis. Moreover, based on dose-response
modeling, both Pereira (1996) and Bull et al. (1990) concluded that the tumorigenic response of
TCA exhibited a linear relationship with increasing dose. Therefore, linear extrapolation from
the LEDio for liver tumors was used for deriving an oral slope factor for TCA.
147
DRAFT - DO NOT CITE OR QUOTE
-------
5.4.5. Oral Cancer Slope Factor and Inhalation Unit Risk
The oral cancer slope factor is an upper-bound estimate of risk per increment of dose that
can be used to estimate lifetime cancer risk from different TCA exposure levels. The slope
factor is ,equal to 0. l/LEDi0 if the LEDio is used as the POD (U.S. EPA, 2005a). The slope
factors based on the tumor responses in male mice in the Bull et al. (2002, 1990) and DeAngelo
et al. (2008) studies, and the tumor responses in female mice in the Pereira (1996) study, ranged
from 2 x 10"2 to 2 x 10"1 per mg/kg-day (Table 5-14).
To reflect the variability or uncertainty associated with these estimated slope factors, the
lower bound risk per unit concentration was derived by linearly extrapolating from the UEDio
(i.e., 0.1/UEDio). These lower bounds are shown in the last column of Table 5-14 and ranged
from 9.1 x 10"3 to 4.2 x 10"2 per mg/kg-day. In comparing the oral cancer slope factors and their
lower bounds, differences ranged from a low of two-fold based on Pereira (1996) to a high of
almost five-fold based on the 104-week data from DeAngelo et al. (2008), with the differences in
the other three studies falling in the three-fold range
Oral cancer slope factors were derived from male mice studies with durations of from 52
to 104 weeks. During conversion of animal doses to human equivalent doses for continuous
lifetime exposure, cross-time scaling factors of [duration of experiment/ duration of animal life]3
were used for all studies except the 104-week study of DeAngelo et al. (2008). Due to the
uncertainty inherent in applying this scaling factor, the slope factor derived from the study of
longest duration may be preferred. Moreover, TCA may be a more potent carcinogen in male
than in female mice, as discussed previously in Section 4.8.2. Also, the four slope factors
derived from the incidence data in male mice varied by about three-fold. Based on these
considerations, the slope factor derived from the study of longest duration (i.e., the 104-week
data from DeAngelo et al., 2008) is recommended, i.e., 2 x 10"1 (mg/kg-day)"1. This slope factor
seems to possess the greatest statistical variability (i.e., the difference between this cancer slope
factor and its estimated lower bound is almost five-fold); however, the confidence intervals
among the estimates all overlap.
Assuming an adult human weighs 70 kg and ingests 2 L of water per day, the 95% upper
confidence limit on the oral cancer unit risk for TCA in drinking water is 6 x 10"3 (mg/L)"1.
Conversely, the 95% lower bound risk per unit concentration for TCA in drinking water is 1.2 x
10"3 (mg/L)"1. Drinking water concentrations associated with upper-bound increased lifetime
cancer risks of 10"4, 10"5, and 10"6 are estimated to be 0.02, 0.002, and 0.0002 mg/L TCA,
respectively, while drinking water concentrations associated with lower-bound increased lifetime
cancer risks of 10"4, 10"5, and 10"6 are estimated to be 0.08, 0.008, and 0.0008 mg/L TCA,
respectively, a four-fold difference.
The slopes of the linear extrapolation from the EDi0, the central estimate of exposure
associated with 10% extra cancer risk, were also derived. Five such slopes (7.1 x 10"2, 5.1 x 10"2,
148 DRAFT - DO NOT CITE OR QUOTE
-------
3.5 x 10"2, 1.1 x 10"1, and 1.4 x 10"2) were derived from the same studies used to derive the oral
cancer slope factors (Bull et al. 2002, 1990; DeAngelo et al., 2008; Pereira, 1996). Again,
selecting the study of longest duration (the 104-week data from DeAngelo et al., 2008), the slope
of the linear extrapolation from the EDi0 is 1 x 10"1 (mg/kg-day)"1.
No inhalation unit risk for TCA was derived. Cancer bioassays involving inhalation
exposure to TCA are not currently available, and a route-to-route extrapolation (from oral to
inhalation) is not recommended at this time because the currently available physiologically-
based toxicokinetic models, which might be useful for route-to-route extrapolation, do not
include an inhalation pathway.
5.4.6. Comparison of Central Tendency Estimates of Oral Slope Factors
Estimates of central tendencies and 90% confidence intervals for the potency of TCA
across 5 mouse studies were compared in Figure 5-2. Central tendency estimates from 5 studies
fall within a tight range - less than an order of magnitude between the highest and lowest values.
149 DRAFT - DO NOT CITE OR QUOTE
-------
Figure 5-3. A comparison of estimates of central tendency (along with
corresponding 90% confidence intervals) of the potency of TCA based on the
incidence of hepatocellular adenomas and carcinomas combined across five rodent
bioassays.
03
in
in
03
o
bo
15
h
i B-
-B— i
i i
1 1
1 1
1 1
JMale mice - 52 vj/ks
i i(Bull et al., 2002)
j' '_ £
{Male mice - 52 vj/ks
|(Bulletal., 1990J)
i Male mice -60 wks
](DeAngelo et al.], 1997)
[Female mice - 8{2 wks
i(Pereira, 1996) i
i i
i(DeAngelo et al.i, 2008)
0.001 0.01 0.1 1 10
Human equivalent TCA potency estimates (per mg/kg-day)
100
150
DRAFT - DO NOT CITE OR QUOTE
-------
6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION
OF HAZARD AND DOSE RESPONSE
6.1. HUMAN HAZARD POTENTIAL
Trichloroacetic acid (TCA, CASRN 76-03-9) has the chemical formula C2HC13O2 and a
molecular weight of 163.39 g/mol. At room temperature, TCA is a colorless to white crystalline
solid with a sharp, pungent odor. It is used as a soil sterilant and as a laboratory reagent in the
synthesis of medicinal products and organic chemicals. TCA is used in industry as an etching
and pickling agent. Medical applications of TCA include use as an antiseptic, as a reagent for
detection of albumin, and as a skin peeling agent. TCA is formed as a combustion by-product of
organic compounds in the presence of chlorine. TCA is also formed by the interaction of organic
material with chlorine during drinking water disinfection. TCA has been detected in water
distribution systems, tap water used for drinking and household activities, and swimming pools.
Direct human exposure to TCA occurs via ingestion of disinfected tap water, inhalation,
and dermal contact. TCA is also formed as a metabolite in the human body after exposure to the
environmental contaminants TCE, tetrachloroethylene, and chloral hydrate. This document does
not attempt to characterize the risk from any particular exposure scenario; instead it focuses on
characterizing the human hazards and dose-response relationships for health effects of TCA.
TCA is readily absorbed by the oral route in rats and by the dermal and oral routes in
humans. Once absorbed, TCA is available for systemic distribution, based on the appearance of
TCA in blood after oral exposure in rodents. Tissue distribution of TCA appears to be
dependent on the time of measurement following dosing. TCA binds to plasma proteins, which
is an important determinant of the extent to which TCA partitions from plasma into target
tissues. No studies were identified that investigated the tissue distribution of TCA in humans,
but the appearance of TCA in the blood and urine of humans exposed to chlorinated solvents or
orally administered chloral hydrate indicates that it is present in the systemic circulation as a
downstream metabolite. No studies investigating the kinetics or degree of maternal-to-fetus or
blood-to-breast-milk transfer of TCA were located.
TCA is not readily metabolized, as indicated by minimal first-pass metabolism in the
liver following oral dosing with TCA and by limited amounts of radioactivity excreted in
exhaled air or present as non-extractable radioactivity in plasma and liver following i.v.
administration of [1-14C]TCA. Results from animal studies indicate that TCA is not as
extensively metabolized as other chlorinated acids, such as DCA, and that TCA is metabolically
converted to DCA. However, with exposure to TCA, levels of DCA in blood, liver, and urine
are low or not detectable, presumably due to rapid metabolic transformation of DCA into other
metabolites. The metabolic conversion of TCA to DCA via reductive dehalogenation is likely
catalyzed by cytochrome P450 enzymes through the dichloroacetate radical intermediate, but, in
151 DRAFT - DO NOT CITE OR QUOTE
-------
general, enzymes involved in TCA metabolism are poorly characterized. The primary route of
excretion of TCA is in the urine, with exhalation of CC>2 and fecal excretion contributing to a
much lesser extent.
The available human data do not provide a definitive picture of the possible noncancer
adverse effects of long-term human exposure to TCA. No human epidemiology or occupational
studies of TCA were located. Case reports and accounts of the medical use of TCA for skin
treatments demonstrate its potential for skin corrosion and eye irritation. However, no
information on systemic toxicity following dermal exposure of humans to TCA was identified.
In animals, TCA induces systemic, noncancer effects that can be grouped into three
general categories: liver toxicity, metabolic alterations, and developmental toxicity. Studies in
rats and mice indicate that TCA primarily affects the liver, although effects on the lungs and
kidneys have also been noted in rats. Observed hepatic effects in rodents include increased size
and weight, collagen deposition, indications of altered lipid and carbohydrate metabolism,
histopathological changes, peroxisome proliferation, evidence of lipid peroxidation, and
oxidative damage to hepatic DNA. TCA may influence intermediary carbohydrate metabolism,
as shown by altered glycogen content in the livers of mice treated with TCA. Administration of
TCA to female rats during pregnancy induced developmental effects in six studies at doses that
also resulted in maternal toxicity. Two of these studies are single dose studies. The observed
effects include fetal cardiac malformations, decreased crown-rump length, reduced fetal body
weight, decreased fetal testes weight, decreased fetal ovary weight, increased apoptosis of
gonocytes, and decreased fetal brain weight. The pattern of observed fetal cardiac malformation
effects has not been completely consistent across the available studies. The reason for this
inconsistency is unknown but may be related to factors such as the dosing method, differences in
the strain or source of the test animals, and/or the method used for evaluation of cardiac
malformations.
There appear to be different modes of action for the liver toxicity, metabolic alterations,
and developmental effects induced by TCA. For liver effects, some changes such as cytomegaly
and cell proliferation may be explained by TCA-induced peroxisome proliferation. Oxidative
stress responses such as lipid peroxidation and/or oxidative DNA damage may also contribute to
the hepatotoxicity of TCA. The cellular mechanisms underlying changes in lipid and
carbohydrate homeostasis have not been conclusively identified. It has been proposed that TCA
may alter carbohydrate and lipid homeostasis by activation or inhibition of key liver enzymes; by
activation of the peroxisome proliferation pathway, which in turn induces transcription of genes
that encode enzymes responsible for fatty acid metabolism; and/or by suppression of one or more
steps of the glycogen degradation process. The MOA for developmental toxicity is unknown. It
has been suggested that TCA, as a strong acid, might induce developmental toxicity by causing
152 DRAFT - DO NOT CITE OR QUOTE
-------
lesion in the placenta, resulting in anoxia, oxidative stress and apoptosis in the developing fetus
or embryo.
The genotoxicity of TCA has been evaluated in assays of mutagenicity, DNA repair,
clastogenicity, micronucleus induction, and DNA strand breaks. The weight of evidence from
these studies suggests that TCA is at most weakly genotoxic.
No human oral or inhalation cancer data are available specifically for TCA. In animals,
the carcinogenic potential of TCA has been evaluated in oral bioassays conducted in mice and
rats. TCA has induced tumors in the livers of male and female mice in multiple bioassays, but
treatment-related tumors of the liver or other organs were not observed in a chronic drinking
water bioassay of rats.
Using the Guidelines for Carcinogen Risk Assessment (U.S. EPA 2005a), TCA is
determined to be "Likely to be Carcinogenic to Humans " by all routes of exposure. In the
previous assessment of TCA conducted by IRIS, TCA was classified as a "C," or "possible
human carcinogen."
Three lines of evidence support the weight of evidence descriptor of Likely to be
Carcinogenic to Humans: 1) TCA is carcinogenic in the liver in multiple studies conducted in
B6C3F1 mice of both sexes; 2) tumor response was robust, occurring at substantially less-than-
lifetime exposures at which tumor rates in control animals was relatively low; and 3) the
available data for TCA do not suggest that the MOA for hepatocarcinogenesis in mice is not
relevant to humans. Finally, two significant limitations of the database for TCA carcinogenicity
are: 1) limited number of mouse studies that included microscopic evaluation of a
comprehensive set of organs in addition to the liver; and 2) the absence of epidemiologic studies
of TCA carcinogenicity in humans.
In the absence of a well-characterized MOA that could explain dose-response
relationships at doses lower than those leading to observed effects, the cancer dose-response
modeling is carried out using default linear extrapolation (U.S. EPA, 2005a). Nonlinear
extrapolation is not considered an option, given the absence of data to extend the dose-response
curves below the bioassay doses. In addition, no data were found that were suitable for
accounting for inter-species differences in toxicokinetics or toxicodynamics in dose-response
modeling.
It is possible that there are segments of the human population that are especially
susceptible to the toxic effects of TCA as a result of age, gender, health status, or genetic factors,
but there are no studies specifically on TCA to fully evaluate this possibility. Age-dependent
differences in susceptibility to noncancer effects of TCA have not been investigated in systemic
toxicity studies. The developmental toxicity data on TCA are too limited to draw any
conclusions on whether developing organisms might be a sensitive subpopulation. The LOAELs
observed in the subchronic toxicity studies suggest that systemic effects are observed at doses
153 DRAFT - DO NOT CITE OR QUOTE
-------
similar to or less than those at which developmental toxicity has been observed; however, no
developmental NOAELs are available for comparison with the subchronic systemic NOAELs.
Given the lack of a developmental NOAEL, it is uncertain what dose would be protective for
developmental toxicity. The existing data on TCA are also insufficient to determine whether
there are age-dependent differences (e.g., plasma binding and metabolism) in the toxicokinetics
of TCA that might lead to differences in health risk. There are no published comparative data
for plasma binding of TCA in young and old animals. In the only study to evaluate the cancer
potency of TCA in young animals, the incidence of liver tumors in mice injected with TCA as
neonates did not differ significantly from solvent controls when evaluated at 15 or 20 months of
age.
No data for gender effects on TCA toxicity in humans were located. Studies in mice and
rats where males and females were tested concurrently suggest that both sexes are about equally
susceptible to the noncancer effects of TCA. In contrast, male mice appear to be more
susceptible to the carcinogenic effects of TCA, based on the observation of a dose-related
increase in proliferative lesions in males but not females when both sexes were tested
concurrently. Other factors that might confer greater susceptibility to the toxic effects of TCA
include a medical history of glycogen storage disease or genetic deficiencies in
glyoxalate-metabolizing enzymes or antioxidant response.
6.2. DOSE RESPONSE
6.2.1. Noncancer/Oral
No human data were available for oral dose-response analysis; therefore, the oral RfD is
based on data from laboratory animals. An estimated BMDLio of 18 mg/kg-day derived using
BMD modeling based on the increased incidence of hepatocellular necrosis in male B6C3F1
mice exposed to TCA via drinking water for 30 to 45 weeks (DeAngelo et al., 2008) was
selected as the POD for calculation of the RfD. This value was divided by a composite UF of
1,000 that includes individual factors of 10 each to account for variability among humans,
extrapolation from laboratory animal data to humans, and database limitations. The oral RfD is
therefore 18 mg/kg-day/1,000 = 0.02 mg/kg-day. Alternative RfDs derived from the BMDL05
for developmental effects in rats (Smith et al., 1989) and from the NOAEL for liver effects in
rats (DeAngelo et al., 1997) support this RfD derived for liver effects in mice. The graph in
Figure 5-1 shows a comparison of these three RfDs, and how they were derived from their
respective PODs that illustrate the similarity between these toxicity values.
Confidence in the principal study chosen for the RfD is medium. The study appears to
have been well designed and well conducted; quantitative data for the incidence and severity of
the various endpoints were included in the published paper. Study duration was up to 104
weeks. The observed hepatocellular neoplasia correlated well with peroxisome proliferation, and
154 DRAFT - DO NOT CITE OR QUOTE
-------
complete histopatholgical examination was conducted for control and high-dose groups.
Confidence in the database is medium. Human data are limited primarily to case reports of skin
or eye effects associated with medical treatments and information on systemic toxicity is lacking.
Significant gaps in the animal database include absence of a multigeneration reproductive
toxicity study, and lack of a developmental toxicity study in a second species. Overall
confidence in the RfD is medium, reflecting these considerations.
The existing IRIS assessment for TCA does not have an RfD. An RfD for TCA of 0.03
mg/kg-day was derived in EPA's proposed Stage 2 Disinfectants and Disinfection Byproducts
Rule (U.S. EPA, 2006), based on the NOAEL of 32.5 mg/kg-day for liver histopathological
changes identified by DeAngelo et al. (1997). The RfD included a composite UF of 1,000.
6.2.2. Noncancer/Inhalation
An inhalation RfC has not been calculated for TCA. No inhalation studies in humans or
animals that were adequate for the derivation of RfC were located. Route-to-route extrapolation
and use of PBPK modeling techniques were considered as alternative approaches for derivation
of the RfC. However, the existing information on the toxicokinetics of TCA was inadequate for
a route-to-route extrapolation from the oral pathway to the inhalation pathway and validated
PBPK models are not currently available for TCA.
6.2.3. Cancer/Oral and Inhalation
Under the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), TCA is
determined to be "Likely to be Carcinogenic to Humans" for all routes of exposure,. Five
candidate oral cancer slope factors (1.1 x 10'1, 8.4 x 10'2, 5.8 x 10'2, 2.0 x 10'1, and 2.0 x 10'2
per mg/kg-day) were derived from liver tumor incidence data from male B6C3Fi mice exposed
to TCA in drinking water for 52 weeks (Bull et al., 2002, 1990), 60 weeks (DeAngelo et al.,
2008), or 104 weeks (DeAngelo et al., 2008), or from female B6C3Fi mice exposed to TCA in
drinking water for 82 weeks (Pereira, 1996), respectively. A graph comparing these five
candidate oral slope factors, along with their corresponding estimates of central tendency and
95% lower bounds are shown in Figure 6-2. This graph shows that the candidate oral slope
factors vary over about an order of magnitude with the 104-week tumor incidence data from
DeAngelo et al. (1997) yielding the highest potency.
Previously, in Chapter 5, the oral cancer slope factor of 2 x 10"1 per mg/kg-day derived
from the study of longest duration (104 weeks) was recommended as the oral cancer slope factor
for TCA. This slope factor also possesses the greatest statistical variability (i.e., the difference
between this cancer slope factor and its estimated lower bound is almost five-fold); however, the
confidence intervals among the estimates based on male mice all overlap.
To derive these oral cancer slope factors, the average daily intakes of TCA from the
mouse studies were converted to human equivalent lifetime doses using an interspecies scaling
155 DRAFT - DO NOT CITE OR QUOTE
-------
factor based on equivalence of (mg/kg)3/4 per day (U.S. EPA, 1992), and a cross-time scaling
factor based on the assumption that the age-specific rate for cancer increases by at least the third
power of age (U.S. EPA, 1980). A cross-time scaling factor was not used for the 104-week
mouse study (DeAngelo et al., 2008) because exposure duration was for a full lifetime. Using
the EPA Benchmark Dose Software (BMDS, version 1.4.1), the multistage model was fit to
mouse liver tumor incidence data (i.e., combined adenomas and carcinomas) and associated
human equivalent lifetime TCA doses. Oral cancer slope factors were calculated by linear
extrapolation from the lower 95% confidence limit on model-predicted human equivalent
lifetime doses associated with 10% extra risk for liver tumors (LEDi0s). In addition, to reflect
the variability or uncertainty associated with these estimated slope factors, the lower bound risk
per unit concentration was derived by linearly extrapolating from the UEDio (i.e., 0.1/UEDio).
The default linear low-dose extrapolation method was selected because the shape of
cancer dose-response curves is linear, and current understanding of the MOA whereby TCA
induces liver tumors is not sufficient to rule out the possibility of a linear slope at low doses. In
addition, data from mouse studies are too limited for other more sophisticated methods of
analysis (i.e., biologically-based dose-response modeling). Moreover, available data do not
provide strong evidence for a direct genotoxic mode of action and suggest that tumor induction
may involve perturbation of cell growth through PPARa agonism, and reduced intercellular
communication. However, current understanding is insufficient to determine which, if any, of
these modes of action may be causally related to the observed tumor responses, and data are not
available to characterize dose-response relationships for as yet unidentified precursor events for
TCA-induced liver tumors.
No inhalation unit risk for TCA was derived. Cancer bioassays involving inhalation
exposure to TCA are not currently available, and a route-to-route extrapolation (from oral to
inhalation) is not recommended at this time because the currently available physiologically-
based toxicokinetic models, which might be useful for route-to-route extrapolation, do not
include an inhalation pathway.
156 DRAFT - DO NOT CITE OR QUOTE
-------
7. REFERENCES
Abbas, R; Fisher, JW. (1997) A physiologically based pharmacokinetic model for trichloroethylene and its
metabolites, chloral hydrate, trichloroacetate, dichloroacetate, trichloroethanol, and trichloroethanol glucuronide in
B6C3FJ mice. Toxicol Appl Pharmacol 147:15-30.
Acharya, S; Mehta, K; Rodrigues, S; et al. (1995) Administration of subtoxic doses of t-butyl alcohol and
trichloroacetic acid to male Wistar rats to study the interactive toxicity. Toxicol Lett 80:97-104.
Acharya, S; Mehta, K; Rodrigues, S; et al. (1997) A histopathological study of liver and kidney in male Wistar rats
treated with subtoxic doses of t-butyl alcohol and trichloroacetic acid. Exp Toxic Pathol 49:369-373.
Allen, BC; Kavlock, RJ; Kimmel, CA; et al. (1994) Dose-response assessment for developmental toxicity. Ill
Statistical models. Fundam Appl Toxicol 23:496-509.
Al-Waiz, MM; Al-Sharqi, AL (2002) Medium-depth chemical peels in the treatment of acne scars in dark-skinned
individuals. Dermatol Surg 28(5):383-387.
Austin, EW; Okita, JR; Okita, RT; et al. (1995) Modification of lipoperoxidative effects of dichloroacetate and
trichloroacetate is associated with peroxisome proliferation. Toxicology 97:59-69.
Austin, EW; Parrish, JM; Kinder, DH; et al. (1996) Lipid peroxidation and formation of 8-hydroxydeoxyguanosine
from acute doses of halogenated acetic acids. Fundam Appl Toxicol 31:77-82.
Bannasch, P. (1996) Pathogenesis of hepatocellular carcinoma: sequential cellular, molecular, and metabolic
changes. Prog Liver Dis 14:161-97.
Bannasch, P; Kopp-Schneider, A; Nehrbass, D. (2001) Significance of hepatic preneoplasia for cancer
chemoprevention. IARC SciPubl 154:223-240.
Bannasch, P; Haertel, T; Su, Qin; et al. (2003) Significance of hepatic preneoplasia in risk identification and early
detection of neoplasia. Toxicol Pathol 31(1):134-139.
Baylin, SB; Herman, JG; Graff, JR et al. (1998) Alterations in DNA methylation: a fundamental aspect of neoplasia.
Adv. Cancer Res 72: 141-196.
Baylin, SB; Esteller, M; Rountree, MR; et al. (2001) Aberrant patterns of DNA methylation, chromatin formation
and gene expression in cancer. Hum Mol Genet 10(7):687-692.
Benane, SG; Blackman, CF; House, DE. (1996) Effect of perchloroethylene and its metabolites on intercellular
communication in clone 9 rat liver cells. J Toxicol Environ Health 48:327-437.
Bhat, HK; Ahmed, AE; Ansari, GAS. (1991) Toxicokinetics of monochloracetic acid: a whole-body
autoradiography study. Toxicology 63:35-43.
Bhunya, SP; Behera, BC. (1987) Relative genotoxicity of trichloroacetic acid (TCA) as revealed by different
cytogenetic assays: bone marrow chromosome aberration, micronucleus and sperm-head abnormality in the mouse.
MutatRes 188:215-221.
Boorman, GA; Dellarco, V; Dunnick, JK; et al. (1999) Drinking water disinfection byproducts: review and
approach to toxicity evaluation. Environ Health Perspect 107(Suppl 1):207-217.
Bowden, DJ; Clegg, SL; Brimblecombe, P. (1998) The Henry's Law constants of the haloacetic acids. J Atmos
Chem 29:85-107.
Boyes, J; Bird, A. (1991) DNA methylation inhibits transcription indirectly via a methyl-CpG binding protein. Cell
64:1123-1134.
157 DRAFT - DO NOT CITE OR QUOTE
-------
Brashear, WT; Bishop, CT; Abbas, R. (1997) Electrospray analysis of biological samples for trace amounts of
trichloroacetic acid, dichloroacetic acid, and monochloroacetic acid. J Anal Toxicol 21:330-334.
Briggs, RT; Robinson, JM; Karnovsky, ML; et al. (1986) Superoxide production by polymorphonuclear leukocytes.
A cytochemical approach. Histochemistry 84:371-378.
Bruning, T; Vamvakas, S; Makropoulos, V; et al. (1998) Acute intoxication with trichloroethene: clinical
symptoms, toxicokinetics, metabolism, and development of biochemical parameters for renal damage. Toxicol Sci
41:157-165.
Bruschi, SA; Bull, RJ. (1993) In vitro cytoxicity of mono-, di-, and trichloroacetate and its modulation by hepatic
peroxisome proliferation. Fundam Appl Toxicol 21:366-375.
Budavari, S.; ed. (2001) The Merck index: an encyclopedia of chemicals, drugs, and biologicals. 13th edition.
Whitehouse Station, NJ: Merck and Co., Inc.; p. 1716.
Bull, RJ. (2000) Mode of action of liver introduction by trichloroethylene and its metabolites, trichloroacetate and
dichloroacetate. Environ Health Perspect 108(Suppl2):241-259.
Bull, RJ; Sanchez, IM; Nelson, MA; et al. (1990) Liver tumor induction in B6C3F! mice by dichloroacetate and
trichloroacetate. Toxicology 63:341-359.
Bull, RJ; Orner, GA; Cheng, RS; et al. (2002) Contribution of dichloroacetate and trichloroacetate to liver tumor
induction in mice by trichloroethylene. Toxicol Appl Pharm 182:55-65.
Bull, RJ; Sasser, LB; Lei, XC. (2004) Interactions in the tumor-promoting activity of carbon tetrachloride,
trichloroacetate, and dichloroacetate in the liver of male B6C3F! mice. Toxicology 199:169-183.
Calafat, AM; Kuklenyik, Z; Caudill, SP; et al. (2003) Urinary levels of trichloroacetic acid, a disinfection by-
product in chlorinated drinking water, in a human reference population. Environ Health Perspect 111(2): 151-154.
Cattley, RC; Miller, RT; Gorton, JC. (1995) Peroxisome proliferates: potential role of altered hepatocyte growth
and differentiation in tumor development. Prog ClinBiolRes 391:295-303.
Celik, I (2007) Determination of toxicity of trichloroacetic acid in rats: 50 days drinking water study. Pesticide
Biochemistry and Physiology 89: 39-45.
Chang, LW; Daniel, FB; DeAngelo, AB. (1992) Analysis of DNA strand breaks induced in rodent liver in vivo,
hepatocytes in primary culture, and a human cell line by chloroacetic acids and chloroacetaldehydes. Environ Mol
Mutagen 20:277-288.
Channel, SR; Hancock, BL. (1993) Application of kinetic models to estimate transit time through cell cycle
compartments. Toxicol Lett 68( 1-2) :213-221.
Chalitchagorn, K; Shuangshoti, S; Hourpai, N et al. (2004) Distinctive pattern of LINE-1 methylation level in
normal tissues and the association with carcinogenesis. Oncogene 23: 8841-8846.
Cheung, C; Aklyama, TE; Ward, JM; et al. (2004) Diminished hepatocellular proliferation in mice humanized for
the nuclear receptor peroxisome proliferator-activated receptor a. Cancer Research 64: 3849-3854.
Chiarello, SE; Resnik, BI; Resnik, SS. (1996) The TCA Masque. A new cream formulation used alone and in
combination with Jessner's solution. Dermatol Surg 22(8):687-690.
Coffin, JC; Ge, R; Yang, S; et al. (2000) Effect of trihalomethanes on cell proliferation and DNA methylation in
female B6C3F1 mouse liver. Toxicol Sci 58:243-252.
Coleman, WP. (2001) Dermal peels. Dermatol Clin 19(3):405-411.
158 DRAFT - DO NOT CITE OR QUOTE
-------
Coleman, WE; Melton, RG; Kopfler, FC; et al. (1980) Identification of organic compounds in a mutagenic extract
of a surface drinking water by a computerized gas chromatography/mass spectrometry system (GS/MS/COM).
Environ Sci Technol 14(5):576-588.
Collier, JM; Selmin, O; Johnson, PD; et al. (2003) Trichloroethylene effects on gene expression during cardiac
development. Clin Mol Teratol 67(7):488-495.
Cornett, R; Yan, Z; Henderson, G; et al. (1997) Cytosolic biotransformation of dichloroacetic acid (DCA) in the
Sprague-Dawley rat. Fundam Appl Toxicol 36(Suppl):318.
Cornett, R; James, MO; Henderson, GN; et al. (1999) Inhibition of gluathione S-transferase zeta and tyrosine
metabolism by dichloroacetate: a potential unifying mechanism for its altered biotransformation and toxicity.
Biochem Biophys Res Commun 262:752-756.
Cosby, NC; Dukelow, WR. (1992) Toxicology of maternally ingested trichloroethylene (TCE) on embryonal and
fetal development in mice and of TCE metabolites on in vitro fertilization. Fundam Appl Toxicol 19(2):268-274.
Cotellessa, C; Peris, K; Fargnoli, MC; et al. (2003) Microabrasion versus microabrasion followed by 15%
trichloroacetic acid for treatment of cutaneous hyperpigmentations in adult females. Dermatol Surg 29(4):352-356.
Counts, JL; Goodman, JI. (1994) Hypomethylation of DNA: an epigenetic mechanism involved in tumor promotion.
Mol Carcinog 11:185-188.
Counts, JL; Goodman, JI. (1995) Hypomethylation of DNA: a nongenotoxic mechanism involved in tumor
promotion. Toxicol Lett 82/83:663-672.
Cox, S. (2003) Rapid development of keratoacanthomas after a body peel. Dermatol Surg 29(2):201-203.
Crabb, DW; Yount, EA; Harris, RA. (1981) The metabolic effects of dichloroacetate. Metabolism 30:1024-1039.
Davis, ME. (1986) Effect of chloroacetic acids on the kidneys. Environ Health Perspect 69:209-214.
Davis, ME. (1990) Subacute toxicity of trichloroacetic acid in male and female rats. Toxicology 63(l):63-72.
Davis, LM; Caspary, WJ; Shakallah, SA; et al. (1994) Loss of heterozygosity in spontaneous and chemically
induced tumors of B6C3F! mice. Carcinogenesis 15:1637-1645.
DeAngelo, AB; Daniel, FB; McMillan, L; et al. (1989) Species and strain sensitivity to the induction of peroxisome
proliferation by chloroacetic acids. Toxicol Appl Pharmacol 101:285-289.
DeAngelo, AB; Daniel, FB; Most, BM; et al. (1997) Failure of monochloroacetic acid and trichloroacetic acid
administered in the drinking water to produce liver cancer in male F344/N rats. J Toxicol Environ Health 52:425-
445.
DeAngelo, AB; Daniel, FB; Wong, D; et al. (2008) The induction of hepatocellular neoplasia by trichloroacetic acid
administered in the drinking water of the male B6C3F1 mouse . JToxicology Environ Health, Part A 71: 1056-
1068. .
Dees, C; Travis, C. (1994) Trichloroacetate stimulation of liver DNA synthesis in male and female mice. Toxicol
Lett 70:343-355.
DeMarini, DM; Perry, E; Sheldon, ML. (1994) Dichloroacetic acid and related compounds: induction of prophage
in E. coli and mutagenicity and mutation spectra in Salmonella TA 100. Mutagenesis 9:429-437.
Dunn, BK (2003) Hypomethylation: one side of a larger picture. AnnN. Y. Acad Sci 983: 28-42.
159 DRAFT - DO NOT CITE OR QUOTE
-------
Elcombe, CR. (1985) Species differences in carcinogenicity and peroxisome proliferation due to trichloroethylene: a
biochemical human hazard assessment. Arch Toxicol Suppl 8:6-17.
Evans, OB; Stacpoole, PW. (1982) Prolonged hypolactatemia and increased total pyruvate dehydrogenase activity
by dicloroacetate. Biochem Pharmacol 31:1295-1300.
Fausto, N; Webber, EM. (1993) Control of liver growth. Crit Rev Eukaryotic Gene Expr 3:117-135.
Ferreira-Gonzalez, A; DeAngelo, AB; Nasim, S; et al. (1995) Ras oncogene activation during hepatocarcinogenesis
in B6C3F! male mice by dichloroacetic and trichloroacetic acids. Carcinogenesis 16(3):495-500.
Fisher, JW; Mahle, D; Abbas, R. (1998) A human physiologically based pharmacokinetic model for
trichloroethylene and its metabolites, trichloroacetic acid and free trichloroethanol. Toxicol Appl Pharmacol
152(2):339-359.
Fisher, JW; Channel, SR; Eggers, JS; et al. (2001) Trichloroethylene, trichloroacetic acid, and dichloroacetic acid:
do they affect fetal rat heart development? Int J Toxicol 20(5):257-267.
Fort, D; Stover, E; Rayburn, J; et al. (1993) Evaluation of the developmental toxicity of trichloroethylene and
detoxification metabolites using xenopus. Teratog Carcinog Mutagen 13:35-45.
Froese, KL; Sinclair, MI; Hrudey, SE. (2002) Trichloroacetic acid as a biomarker of exposure to disinfection by-
products in drinking water: a human exposure trial in Adelaide, Australia. Environ Health Perspect 110(7):679-
687.
Fu, L; Johnson, EM; Newman, LM. (1990) Prediction of the developmental toxicity hazard potential of halogenated
drinking water disinfection by-products tested by the in vitro hydra assay. Reg Toxicol Pharmacol 11:213-219.
Fung, JF; Sengelmann, RD; Kenneally, CZ. (2002) Chemical injury to the eye from trichloroacetic acid. Dermatol
Surg28(7):609-610.
Furstenberger, G; Senn, HJ. (2002) Insulin-like growth factors and cancer. Lancet Oncol 3:298-302.
Gama-Sosa, MA; Slagel, VA; Trewyn, RW; et al. (1983) The 5-methylcytosine content of DNA from human
tumors. Nucleic Acids Res 11:6883-6894.
Ge, R; Yang, S; Kramer, PM; et al. (200 la) The effect of dichloroacetic acid and trichloroacetic acid on DNA
methylation and cell proliferation in B6C3F! mice. J Biochem Mol Toxicol 15(2): 100-106.
Ge, R; Wang, W; Kramer, PM; et al. (200 Ib) Wy-14643-induced hypomethylation of the c-myc gene in mouse
liver. Toxicol. Sci 62: 28-35.
Ghantous, H; Danielsson, RG; Dencker, L; et al. (1986) Trichloroacetic acid accumulates in murine amniotic fluid
after tri- and tetrachloroethylene inhalation. Acta Pharmacol Toxicol 58:105-114.
Gibson, GG. (1989) Comparative aspects of the mammalian cytochrome P450 IV gene family. Xenobiotica
19(10):1123-1148.
Giller, S; Le Curieux, F; Erb, F; et al. (1997) Comparative genotoxicity of halogenated acetic acids found in
drinking water. Mutagenesis 12(5):321-328.
Goldsworthy, TL; Popp, JA. (1987) Chlorinated hydrocarbon-induced peroxisomal enzyme activity in relation to
species and organ carcinogenicity. Toxicol Appl Pharmacol 88:225-233.
Gonzalez-Leon, A; Merdink, JL; Bull, PJ; et al. (1999) Effect of pre-treatment with dichloroacetic or
trichloroacetic acid in drinking water on the pharmacokinetics of a subsequent challenge dose in B6C3F! mice.
Chemic-Biol Inter 123:239-253.
160 DRAFT - DO NOT CITE OR QUOTE
-------
Grasl-Kraupp, B; Waldhor, T; Huber, W; et al. (1993) Glutathione S-transferase isoenzyme patterns in different
subtypes of enzyme-altered rat liver foci treated with the peroxisome proliferator nafenopin or with phenobarbital.
Carcinogenesis 14(11):2407-12.
Hajimiragha, H; Ewers, U; Jansen-Rosseck, R; et al. (1986) Human exposure to volatile halogenated hydrocarbons
from the general environment. Int Arch Occup Environ Health 58:141-150.
Hansch, C; Leo, A; Hoekman, D. (1995) Exploring QSAR. In: Heller, Stephen R; ed. Hydrophobic, electronic, and
steric constants. ACS professional reference book. Washington, DC: American Chemical Society; p. 4.
Harrington-Brock, K; Doerr, CL; Moore, MM. (1998) Mutagenicity of three disinfection by-products; di- and
trichloroacetic acid and chloral hydrate inL5178Y/TK+" - 3.7.2C mouse lymphoma cells. MutatRes 413:265-276.
Hassoun, EA; Ray, S. (2003) The induction of oxidative stress and cellular death by the drinking water disinfection
by-products, dichloroacetate and trichloroacetate in J774.A1 cells. Comp Biochem Physiol C Pharmacol Toxicol
Endocrinol 135:119-128.
Hegi, ME; Fox, RR; Belinsky, SA; et al. (1993) Analysis of activated protooncogenes in B6C3F! mouse liver
tumours induced by ciprofibrate, a potent peroxisome proliferator. Carcinogenesis 14:145-149.
Herren-Freund, SL; Pereira, MA; Khoury, MD; et al. (1987) The carcinogenicity of trichloroethylene and its
metabolites, trichloroacetic acid and dichloroacetic acid, in mouse liver. Toxicol Appl Pharmacol 90:183-189.
Hinckley, F; Bachand, AM; Reiff, JS (2005) Late pregnancy exposures to disinfection by-products and growth-
related birth outcomes. Environmental Health Persceptives 113: 1808-1813.
Hobara, T; Kobayashi, J; Kawamoto, T; et al. (1986) Biliary excretion of trichloroethylene and its metabolites in
dogs. Toxicol Lett 32:119-122.
Hobara, T; Kobayashi, J; Kawamoto, T; et al. (1987) The cholecystohepatic circulation of trichloroethylene and its
metabolites in dogs. Toxicol Lett 44:283-295.
Hobara, T; Kobayashi, J; Kawamoto, T; et al. (1988a) Intestinal absorption of chloral hydrate, free trichloroethanol
and trichloroacetic acid in dogs. Pharmacol Toxicol 62:250-258.
Hobara, T; Kobayashi, J; Kawamoto, T; et al. (1988b) The absorption of trichloroethylene and its metabolites from
the urinary bladder of anesthetized dogs. Toxicology 48(2):141-153.
Hunter, ES; Rogers, EH. (1999) Dysmorphogenic effects of three metabolites of haloacetic acids in mouse embryo
culture. Teratology 59(6):402.
Hunter, ES, III; Rogers, EH; Schmid, JE; et al. (1996) Comparative effects of haloacetic acids in whole embryo
culture. Teratology 54:57-64.
IPCS (International Programme on Chemical Safety). (2000) Disinfectants and disinfectant by-products.
Environmental health criteria. Vol. 216. World Health Organization, Geneva, Switzerland. Available online at
http ://www. inchem. org/documents/ehc/ehc/ehc216 .htm.
Ito, Y; Yamenoshita, O; Asaeda, N; et al. (2007) Di(2-ethylhexyl)phthalate induces hepatic tumorigenesis through a
peroxisome proliferator-activated receptor a-independent pathway. J. Occup Health 49: 172-182.
James, MO; Cornett, R; Yan, Z; et al. (1997) Glutathione-dependent conversion to glyoxylate, a major pathway of
DCA biotransformation in hepatic cytosol from humans and rats, is reduced in DCA-treated rats. Drug Metab Disp
25(11): 1223-1227.
161 DRAFT - DO NOT CITE OR QUOTE
-------
James, MO; Yan, Z; Cornell, R; el al. (1998) Pharmacokinelics and melabolism of [14C]dichloroacelale in male
Sprague-Dawley rals. Identification of glycine conjugates, including hippurale, as urinary melaboliles of
dichloroacelale. Drug Melab Dispos 26(1 1): 1 134-1 143.
Johnson, PD; Dawson, BV; Goldberg, SJ. (1998) Cardiac leralogenicily of Irichloroelhylene melaboliles. J Am
Coll Cardiol 32(2):540-545.
Jones, PA; Buckley, JD. (1990) The role of DNA melhylalion in cancer. Adv Cancer Res 54:1-23.
Jones, PA and Gonzalgo, ML (1997) Altered DNA melhylalion and genome instability: A new palhway lo cancer?
Proc Nail. Acad Sci 94: 2103-2105.
Juuli, S; Hoekslra, E. (1998) New directions: Ihe origins and occurrence of Irichloroacelic acid. Almos Environ
32(17):3059-3060.
Kang, WH; Kim, NS; Kim, YB; el al. (1998) A new Irealmenl for syringoma. Combination of carbon dioxide laser
and Irichloroacelic acid. Dermalol Surg 24(12): 1370-1374.
Kargalioglu, Y; McMillan, BJ; Minear, RA el al. (2002) Analysis of Ihe cyloloxicity and mulagenicily of drinking
water disinfection by-producls in Salmonella typhimurium. Teralog Carcinog Mulagen 22: 1 13-128.
Karnovsky, M; Badwey, J; Lochner, J; el al. (1988) Trigger phnomena for the release of oxygen radicals by
phagocytic leukocytes. In: Cerulie, P; Fridovich, I; McCord, J., eds. Oxy. -radicals in molecular biology and
palhology. New series. Vol. 82. New York: AlanR. Liss; pp. 61-81.
Kalo-Weinslein, J; Lingohr, MK; Orner, GA; el al. (1998) Effecls of dichloroacetele on glycogen metabolism in
e. Toxicology 130:141-154.
Kalo-Weinslein, J; Slauber, AJ; Orner, GA; el al. (2001) Differential effecls of dihalogenaled and Irihalogenaled
acetates in the liver of B6C3FJ mice. J Appl Toxicol 21:81-89.
Keshel, I; Lieman-Hurwilz, J; Cedar, H. (1986) DNA melhylalion affecls Ihe formation of active chromatin. Cell
44:535-543.
Kelcha, MM; Stevens, DK; Warren, DA; el al. (1996) Conversion of Irichloroacelic acid lo dichloroacelic acid in
biological samples. J Anal Toxicol 20(4):236-241.
Khandwala, HM; McCulcheon, IE; Flyvbjerg, A el al. (2000) The effecls of insulin-like growlh factors on
lumorigenesis and neoplastic growlh. EndocrinRev 21:215-244.
Kim, H; Weisel, CP. (1998) Dermal absorption of dichloro- and Irichloroacelic acids from chlorinated water. J
Expo Anal Environ Epid 8(4):555-575.
Kim, YJ; Shin, BS; Chung, BS; el al. (2002) A simple technique for Irealmenl of nasal telangieclasia using
Irichloroacetic acid and CO2 laser. Dermalol Surg 28(8):729-73 1.
King, WD; Dodds, L; Allen, AC el al. (2005) Haloacetic acids in drinking water and risk for stillbirth. Occup.
Environ Med 62: 124-127.
Klaunig, J; Ruch, R; DeAngelo, A; el al. (1988) Inhibition of mouse hepalocyle intercellular communication by
phthalale esters. Cancer Lett 43 :65-7 1 .
Klaunig, J; Ruch, RJ; Lin ELC. (1989) Effecls of Irichloroelhylene and ils metabolites on rodenl hepalocyle
intercellular communication. Toxicol Appl Pharmacol 99:454-465.
Klaunig, J; Babich, MA; Baelcke, KP; el al. (2003). PPARa agonisl-induced rodenl lumors: modes of action and
human relevance. Cril Rev Toxicol 33(6):655-780.
162 DRAFT - DO NOT CITE OR QUOTE
-------
Klotz, JB; Pyrch, LA. (1999) Neural tube defects and drinking water disinfection by-products. Epidemiology
10:383-390.
Kodell, R; Howe, R; Chen, J; et al. (1991) Mathematical modelling of reproductive and developmental toxic effects
for quantitative risk assessment. Risk Anal 8:15-21.
Koenig, G. (2002) Ullmann's encyclopedia of industrial chemistry. Electronic version available through
subscription to Wiley Interscience, http://www3.interscience.wiley.com/cgi-bin/home. Article online posting date:
June 15, 2000. Accessed December 4, 2003. Weinheim, Germany: John Wiley & Sons.
Kraupp-Grasl, B; Huber W; Putz B; et al. (1990) Tumor promotion by the peroxisome proliferator nafenopin
involving a specific subtype of altered foci in rat liver. Cancer Res 50(12):3701-8.
Kraupp-Grasl, B; Huber, W; Taper, H; et al. (1991) Increased susceptibility of aged rats to hepatocarcinogenesis by
the peroxisome proliferator nafenopin and the possible involvement of altered liver foci occurring spontaneously.
CancerRes51(2):666-71.
Kupper, LL; Portier, C; Hogan, MD; et al. (1986) The impact of litter effects on dose-response modelling in
teratology. Biometrics 42:85-98.
Lapinskas, PJ; Gorton, JC. (1999) Molecular mechanisms of hepatocarcinogenic peroxisome proliferates. In: Puga,
A; Wallace, KB; eds. Molecular biology of the toxic response. Philadelphia, PA: Taylor and Francis; pp. 219-253.
Larson, JL; Bull, RJ. (1992) Metabolism and lipoperoxidative activity of trichloroacetate and dichloroacetate in rats
and mice. Toxicol Appl Pharmacol 115:268-277.
Lash, LH; Fisher, JW; Lipscomb, JC; et al. (2000) Metabolism of trichlorethylene. Environ Health Perspect
108(Suppl 2): 177-200.
Latendresse, JR; Pereira, MA. (1997) Dissimilar characteristics of N-methyl-N-nitrosourea-initiated foci and tumors
promoted by dichloroacetic acid or trichloroacetic acid in the liver of female B6C3F! mice. Toxicol Pathol
25(5):433^40.
Laughter, AR; Dunn, CS; Swanson, CL; et al. (2004) Role of the peroxisome proliferator-activated receptor alpha
(PPARalpha) in responses to trichloroethylene and metabolites, trichloroacetate and dichloroacetate in mouse liver.
Toxicology 203:83-98.
Lee, JB; Chung, WG; Kwahck, H; et al. (2002) Focal treatment of acne scars with trichloroacetic acid: chemical
reconstruction of skin scars method. Dermatol Surg 28(11): 1017-1021.
Lewis, RJ, Sr; ed. (1997) Hawley's condensed chemical dictionary. 13th edition. New York: John Wiley & Sons,
Inc.; p. 1124.
Lide, DR; ed. (2000) CRC handbook of chemistry and physics. 81st edition. Boca Raton, FL: CRC Press LLC; pp.
3-9.
Lin, EL; Mattox, JK; Daniel, FB. (1993) Tissue distribution, excretion, and urinary metabolites of dichloroacetic
acid in the male Fischer 344 rat. J Toxicol Environ Health 38(1): 19-32.
Lipscomb, JC; Mahle, DA; Brashear, WT; et al. (1995) Dichloroacetic acid: metabolism in cytosol. Drug Metab
Dispos 23(11): 1202.
Lumpkin, MH; Bruckner, JV; Campbell, JL; et al. (2003) Plasma binding of trichloroacetic acid in mice, rats, and
humans under cancer bioassay and environmental exposure conditions. Drug Metab Dispos 31(10): 1203-1207.
163 DRAFT - DO NOT CITE OR QUOTE
-------
Mackay, JM; Fox, V; Griffiths, K; et al. (1995) Trichloroacetic acid: investigation into the mechanism of
chromosomal damage in the in vitro human lymphocyte cytogenetic assay and the mouse bone marrow
micronucleus test. Carcinogenesis 16(5): 1127-1133.
Maloney, EK; Waxman, DJ. (1999) Trans-activation of PPAR-alpha and PPAR-gamma by structurally diverse
environmental chemicals. Toxicol Appl Pharmacol 161:209-218.
Marsman, DS; Cattley, RC; Conway, JG; et al. (1988) Relationship of hepatic peroxisome proliferation and
replicative DNA synthesis to the hepatocarcinogenicity of the peroxisome proliferators di(2-ethylhexyl)phthalate
and [4-chloro-6-(2,3-xylidino)-2-pyrimidinylthio]acetic acid (Wy-14,643) in rats. Cancer Res 48(23):6739-6744.
Mather, GG; Exon, JH; Koller, LD. (1990) Subchronic 90-day toxicity of dichloroacetic and trichloroacetic acid in
rats. Toxicology 64:71-80.
Merdink, JL; Gonzalez-Leon, A; Bull, RJ; et al. (1998) The extent of dichloroacetate formation from
trichloroethylene, chloral hydrate, trichloroacetate, and trichloroethanol inB6C3P! mice. Toxicol Sci 45:33-41.
Merdink, JL; Bull, RJ; Schultz, RJ. (2000) Trapping and identification of the dichloroacetate radical from the
reductive dehalogenation of trichloroacetate by mouse and rat liver microsomes. Free Rad Biol Med 29:125-130.
Mills, CJ; Bull, RJ; Cantor, KP; et al. (1998) Health risks of drinking water chlorination by-products: report of an
expert working group. Chronic Dis Can 19(3):91-101.
Miyagawa, M; Takasawa, H; Sugiyama, A; et al. (1995) The in vivo-in vitro replicative DNA synthesis (RDS) test
with hepatocytes prepared from male B6C3F! mice as an early prediction assay for putative nongenotoxic (Ames-
negative) mouse hepatocarcinogens. MutatRes 343:157-183.
Moghaddam, AP; Abbas, R; Fisher, JW; et al. (1996) Metabolism of trichloroacetic acid to dichloroacetic acid by
rat and mouse gut microflora, and in vitro study. Biochem Biophys Res Commun 228:639-645.
Moghaddam, AP; Abbas, R; Fisher, JW; et al. (1997) Role of mouse intestinal microflora in dichloroacetic acid
formation, an in vivo study. Human Exp Toxicol 16:629-635.
Moore, MM; Harrington-Brock, K. (2000) Mutagenicity of trichloroethylene and its metabolites: implications for
the risk assessment of trichloroethylene. Environ Health Perspect 108(Suppl 2):215-23.
Morimura, K; Cheung, C; Ward, J; et al. (2006) Differential susceptibility of mice humanized for peroxisome
proliferator-activated receptor a to Wy-14643-induced liver tumorigenesis. Carcinogenesis 27: 1074-1080.
Morris, ED; Bost, JC. (2002) Acetic acid, halogenated derivatives. In: Kirk-Othmer encyclopedia of chemical
technology. Electronic version available through subscription to Wiley Interscience
http://www3.interscience.wiley.com/cgi-bin/home. Article online posting date July 19, 2002. Accessed Dec. 4,
2003. New York: John Wiley & Sons.
Mower, J; Nordin, J. (1987) Characterization of halogenated organic acids in five gases from municipal waste
incinerators. Chemosphere 16(6):1181-1192.
Moy, LS; Peace, S; Moy, RL. (1996) Comparison of the effect of various chemical peeling agents in a mini-pig
model. DermatolSurg22(5):429-432.
Nakano, H; Hatayama, I; Satoh, K; et al. c-Jun expression in single cells and preneoplastic foci induced by
diethylnitrosamine in B6C3F1 mice: comparison with the expression of pi-class glutathione S-transferase.
Carcinogenesis 15(9): 1853-7.
Nelson, MA; Bull, RJ. (1988) Induction of strand breaks in DNA by trichloroethylene and metabolites in rat and
mouse liver in vivo. Toxicol Appl Pharmacol 94:45-54.
164 DRAFT - DO NOT CITE OR QUOTE
-------
Nelson, MA; Sanchez, IM; Bull, RJ; and Sylvester, SR. (1990) Increased expression of c-myc and c-Ha-ras in
dichloroacetate and trichloroacetate-induced liver tumors in B6C3F1 mice. Toxicology 64:47-57.
Nelson, GM; Swank, AE; Brooks, LR; et al. (2001) Metabolism, microflora effects, and genotoxicity in haloacetic
acid-treated cultures of rat cecal microbiota. Toxicol Sci 60(2):232-241.
Ni, YC; Kadlubar, FF; Fu, PP. (1995) Formation of a malondialdehyde-modified 2"-deoxyguanosinyl adduct from
metabolism of chloral hydrate by mouse liver microsomes. BiochemRes Commun216:1110-1117. (cited in Von
Tungeln et al., 2002)
Ni, YC; Wong, TT; Lloyd, RV; et al. (1996) Mouse liver microsomal metabolism of chloral hydrate, trichloracetic
acid, and trichloroethanol leading to induction of lipid peroxidation via a free radical mechanism. Drug Metab
Dispos 24:81-90.
Nieuwenhuijsen, MJ; Toledano, MB; Eaton, NE; et al. (1999) Chlorination disinfection byproducts in water and
their association with adverse reproductive outcomes: a review. Occup Environ Med 57:73-85.
NIOSH (National Institute for Occupational Safety and Health). (1973) Urinary metabolites from controlled
exposures of humans to trichloroethylene. Centers for Disease Control and Prevention, Public Health Service, U.S.
Department of Health and Human Services, Cincinnati, OH. Available from the National Technical Information
Service, Springfield, VA, PB82-151713.
NIOSH. (2003) NIOSH pocket guide to chemical hazards. Centers for Disease Control and Prevention, Public
Health Service, U.S. Department of Health and Human Services, Cincinnati, OH. Available online at
http://www.cdc.gov/niosh/npg/npg.html. Accessed December 29, 2003.
NLM (National Library of Medicine). (2003) Trichloroacetic acid. HSDB (Hazardous Substances Data Bank).
National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD. Available online at
http://toxnet.nlm.nih.gov. Accessed December, 2003.
NRC (National Research Council). (1983) Risk assessment in the federal government: managing the process.
Washington, DC: National Academy Press.
NRC. (2006) Assessing the Human Health Risks of Trichloroethylene: Key Scientific Issues. Board on
Environmental Studies and Toxicology. Washington, DC: National Academies Press.
NRC. (2008) Phthalates and cumulative risk assessment: the tasks ahead. National Research Council of the National
Academies, Washington, DC.
NAS. (2008) Science and Decisions: Advancing Risk Assessment. The National Academies, Washington, DC.
Nunns, D; Mandal, D. (1996) Trichloroacetic acid: a cause of vulvar vestibulitis. Acta Derm Venereol Suppl
(Stockh) 76:334.
O'Flaherty, EJ; Scott, W; Schreiner, C; et al. (1992) A physiologically based kinetic model of rat and mouse
gestation: disposition of a weak acid. Toxicol Appl Pharmacol 112(2):245-256.
Okita, RT; Okita, R. (1992) Effects of diethyl phthalate and other plasticizers on laurate hydroxylation in rat liver
microsomes. PharmRes 9:1648-1653.
Ono, Y; Somiya, I; Kawamura, M. (1991) The evaluation of genotoxicity using DNA repairing test for chemicals
produced in chlorination and ozonation processes. Water Sci Technol 23(l-3):329-338.
Parnell, MJ; Exon, JH; Koller, LD. (1988) Assessment of hepatic initiation-promotion properties of trichloroacetic
acid. Arch Environ Contam Toxicol 17(4):429-436.
165 DRAFT - DO NOT CITE OR QUOTE
-------
Parrish, JM; Austin, EW; Stevens, DK; et al. (1996) Haloacetate-induced oxidative damage to DNA in the liver of
maleBeCSFj mice. Toxicology 110:103-111.
Pereira, MA. (1996) Carcinogenic activity of dichloroacetic acid and trichloroacetic acid in the liver of female
B6C3FJ mice. Fundam Appl Toxicol 31:192-199.
Pereira, MA; Phelps, JB. (1996) Promotion by dichloroacetic acid and trichloroacetic acid of N-methyl-N-
nitrosourea-initiated cancer in the liver of female B6C3Fi mice. Cancer Lett 102:133-141.
Pereira, MA; Li, K; Kramer, PM. (1997) Promotion by mixtures of dichloroacetic acid and trichloroacetic acid of
N-methyl-N-nitrosourea-initiated cancer in the liver of female B6C3FJ mice. Cancer Lett 115:15-23.
Pereira MA; Kramer, MP; Conran, PB; et al. (2001) Effect of chloroform on dichloroacetic acid and trichloroacetic
acid-induced hypomethylation and expression of the c-myc gene and on their promotion of liver and kidney tumors
in mice. Carcinogenesis 22(9):1511-1519.
Perry, RH; Green, D. (1984) Perry's chemical handbook. Physical and chemical data. 6th edition. New York:
McGraw Hill.
Peters, JM; Cattley, RC; Gonzalez, FJ. (1997) Role of PPAR alpha in the mechanism of action of the nongenotoxic
carcinogen and peroxisome proliferator Wy-14,643. Carcinogenesis 18(11):2029-2033.
Plewa, MJ; Kargalioglu, Y; Vankerk, D; et al. (2002) Mammalian cell cytotoxicity and genotoxicity analysis of
drinking water disinfection by-products. Environ Mol Mutagen 40:134-142.
Pogribny, IP ; Tryndyak, VP ; Woods, CG ; et al. (2007) Epigenetic effects of the continuous exposure to
peroxisome proliferator WY-14643 in mouse liver are dependent upon peroxisome proliferator activated receptor a
Mutation Research 625: 62-71.
Porter, CK; Putnam, SD; Hunting, KL et al. (2005) The effect of trihalomethane and haloacetic acid exposure on
fetal growth in a Maryland County. Am J. Epidemiol 162: 334-344.
Pravacek, TL; Channel, SR; Schmidt, WJ; etal. (1996) Cytotoxicity and metabolism of dichloroacetic and
trichloroacetic acid in B6C3F! mouse liver tissue. In Vitro Toxicol 9(3):261-269.
Rai, K; van Ryzin J. (1985) A dose-response model for teratological experiments involving quanta! response.
Biometrics 41:1-9.
Rao, MS; Tatematsu, M; Subbarao, V; et al. (1986) Analysis of peroxisome proliferator-induced preneoplastic and
neoplastic lesions of rat liver for placenta! form of glutathione S-transferase and gamma-glutamyltranspeptidase.
Cancer Res 46:5287-5290.
Rapson, WH; Nazar, MA; Butsky, W. (1980) Mutagenicity produced by aqueous chlorination of organic
compounds. Bull Environ Contam Toxicol 24:590-596.
Razin, A; Kafri, T. (1994) DNA methylation from embryo to adult. Prog Nucleic Acid Res Mol Biol 48:53-81.
Reimann, S; Grob, K; Frank, H. (1996) Environmental chloroacetic acids in foods analyzed by GC-ECD. Mitteil
Aus Dem Geb der Lebensmittel und Hygiene 87(2):212-222.
Renwick, AG ; Lazarus, NR. (1998) Human variability and noncancer risk assessment~an analysis of the default
uncertainty factor. Regul Toxicol Pharmacol 27( 1, Pt. 1):3-20.
Reynolds, SH; Stowers, SJ; Patterson, RM; et al. (1987) Activated oncogenes in B6C3F1 mouse liver tumors:
implications for risk assessment. Science 237(4820): 1309-16.
166 DRAFT - DO NOT CITE OR QUOTE
-------
Rubin, MG. (1995) The efficacy of a topical lidocaine/prilocaine anesthetic gel in 35% trichloroacetic acid peels.
Dermatol Surg 21(3):223-225.
Saeter, G; Seglen, PO. (1990) Cell biology of hepatocarcinogenesis. CritRev Oncogen 1:437-466.
SAB (Science Advisory Board). (2006) SAB review of EPA's draft risk assessment of potential human health
effects associated with PFOA and its salts. Available online from:
http://www.epa.gov/sab/pdf/2006_0120_final_draft_pfoa_report.pdf.
Saillenfait, AM; Langonne, I; Sabate, JP. (1995) Developmental toxicity of trichloroethylene, tetrachloroethylene
and four of their metabolites in rat whole embryo culture. Arch Toxicol 70:71-82.
Sakai, M; Matsushima-Hibiya, Y; Nishizawa, M; et al. Suppression of rat glutathione transferase P expression by
peroxisome proliferators: interaction between Jun and peroxisome proliferator-activated receptor alpha. Cancer Res
55(22):5370-6.
Sanchez, IM; Bull, RJ. (1990) Early induction of reparative hyperplasia in B6C3F! mice treated with
dichloroacetate and trichloroacetate. Toxicology 64:33-46.
Scharf, JG; Dombrowski, F; Ramadori, G. (2001) The IGF axis and hepatocarcinogenesis. Mol Pathol 54:138-144.
Schmutte, C; Jones, P. (1998) Involvement of DNA methylation in human carcinogenesis. Biol. Chem 379:377-
388.
Schultz, IR; Merdink, JL; Gonzalez-Leon, A; et al. (1999) Comparative toxicokinetics of chlorinated and
brominated haloacetates in F344 rats. Toxicol Appl Pharmacol 158(2): 103-114.
Schulz, WA; Steinhoff, C; Flori, AR. (2006) Methylation of endogenous human retroelements in health and disease.
Curr Top Microbiol. Immunol. 310: 211-250.
Selmin, OI; Thorne, PA; Caldwell, PT et al. (2008) Trichloroethylene and trichloroacetic acid regulate calcium
signaling pathways in murine embryonal carcinoma cells P19. Cardiovasc Toxicol 8: 47-56.
Serjeant, EP; Dempsey, B. (1979) lonisation constants of organic acids in aqueous solution. IUPAC chemical data
series no. 23. New York: Pergamon Press; p. 989.
Shah, YZM; Morimura, K; Yang, Q; et al. (2007) Peroxisome proliferation-activated receptor a regulates a micro-
RNA-mediated signaling cascade responsible for hepatocellular proliferation. Molecular and Cellular Biology 27:
4238-4247.
Sidebottom, H; Franklin, J. (1996) The atmospheric fate and impact of hydrochlorofluorocarbons and chlorinated
solvents. Pure Appl Chem 68(9): 1757-1769.
Singh, R (2005a) Testicular changes in rat exposed to trichloroacetic acid (TCA) during organogenesis. Biomedical
Research 16: 45-52.
Singh, R (2005b) Effect of maternal administration of trichloroacetic acid (TCA) on fetal ovary rats. Biomedical
Research 16: 195-200.
Singh, R (2006) Neuroembryopathic effect of trichloroacetic acid in rats exposed during organogenesis. Birth
Defects Research (Part B) 77: 47-52.
Skender, L; Karacic, V; Bosner, B; et al. (1994) Assessment of urban population exposure to trichloroethylene and
tetrachloroethylene by means of biological monitoring. Arch Environ Health 49(6) :445-451.
Smith, MK; Randall, JL; Read, EJ; et al. (1989) Teratogenic activity of trichloroacetic acid in the rat. Teratology
40:445-451.
167 DRAFT - DO NOT CITE OR QUOTE
-------
Stanley, LA; Blackburn, DR; Devereaux, S; et al. (1994) Ras mutations in methylclofenapate-induced B6C3F1 and
C57BL/10J mouse liver tumours. Carcinogenesis 15:1125-1131.
Stauber, AJ; Bull, RJ. (1997) Differences in phenotype and cell replicative behavior of hepatic tumors induced by
dichloroacetate (DCA) and trichloroacetate (TCA). Toxicol Appl Pharmacol 144(2):235-246.
Stauber, AJ; Bull, RJ; Thrall, BD. (1998) Dichloroacetate and trichloroacetate promote clonal expansion of
anchorage-independent hepatocytes in vivo and in vitro. Toxicol Appl Pharmacol 150:287-294.
Styles, JA; Wyatt, I; Coutts, C. (1991) Trichloroacetic acid: studies on uptake and effects on hepatic DNA and liver
growth in mouse. Carcinogenesis 12(9):1715-1719.
Su, Q; Bannasch, P. (2003) Relevance of hepatic preneoplasia for human hepatocarcinogenesis. Toxicol Pathol
31(1):126-133.
Suzuki, H; Fujita, H; Mullauer, L; et al. (1990) Increased expression of c-jun gene during spontaneous
hepatocarcinogenesis in LEG rats. Cancer Lett 53(2-3):205-12.
Takashima, K; Ito, Y; Gonzalez, FJ; et al (2008) Different mechanisms of DEHP-induced hepatocellular adenoma
tumorigenesis in wild-type and Ppar-alpha-null mice. J. Occup. Health 50: 169-180.
Tang, XJ; Li, LY; Huang, JX; et al. (2002) Guinea pig maximization test for trichloroethylene and its metabolites.
Biomed Environ Sci 15(2): 113-118.
Tao, L; Li, K; Kramer, PM; et al. (1996) Loss of heterozygosity on chromosome 6 in dichloroacetic acid and
trichloroacetic acid-induced liver tumors in female B6C3Fi mice. Cancer Lett 108:257-261.
Tao, L; Kramer, PM; Ge, R; et al. (1998) Effect of dichloroacetic acid and trichloroacetic acid on DNA methylation
in liver and tumors of female B6C3F! mice. Toxicol Sci 43:139-144.
Tao, L; Yang, S; Xie, M; et al. (2000a) Effect of trichloroethylene and its metabolites, dichloroacetic acid and
trichloroacetic acid, on the methylation and expression of c-jun and c-myc protooncogenes in mouse liver:
prevention by methionine. Toxicol Sci 54:399- 407.
Tao, L; Yang, S; Xie, M; et al. (2000b) Hypomethylation and overexpression of c-jun and c-myc protooncogenes
and increased DNA methyltransferase activity in dichloroacetic and trichloroacetic acid-promoted mouse liver
tumors. Cancer Lett 158:185-193.
Tao, L; Li, K; Kramer, PM; et al. (2004) Hypomethylation of DNA and the insulin-like growth factor-II gene in
dichloroacetic acid and trichloroacetic acid-promoted mouse liver tumors. Toxicology 196:127-136.
Templin, MV; Parker, JC; Bull, RJ. (1993) Relative formation of dichloroacetate and trichloroacetate from
trichloroethylene in male B6C3F! mice. Toxicol Appl Pharmacol 123:1-8.
Templin, MV; Stevens, DK; Stenner, RD; et al. (1995) Factors affecting species differences in the kinetics of
metabolites of trichloroethylene. J Toxicol Environ Health 44:435-447.
Tharappel, JC; Nalca, A; Owens, AB; et al. (2003) Cell proliferation and apoptosis are altered in mice deficient in
the NF-kappaB p50 subunit after treatment with the peroxisome proliferator ciprofibrate. Toxicol Sci 75(2):300-8.
Tong, Z; Board, PG; Anders, MW. (1998a) Glutathione transferase zeta catalyzes the oxygenation of the carcinogen
DCA to glyoxylic acid. Biochem J 331(2):371-374.
Tong, Z; Board, PG; Anders, MW. (1998b) Glutathione transferase zeta-catalyzed biotransformation of
dichloroacetic acid and other alpha-haloacids. Chem Res Toxicol 11:1332-1338.
168 DRAFT - DO NOT CITE OR QUOTE
-------
Toxopeus, C; Frazier, JM. (1998) Kinetics of trichloracetic acid and dichloroacetic acid in the isolated perfused rat
liver. Toxicol Appl Pharmacol 152:90-98.
Toxopeus, C; Frazier, JM. (2002) Simulation of trichloroacetic acid kinetics in the isolated perfused rat liver using a
biologically based kinetic model. Toxicol Sci 70(l):27-39.
Tse, Y; Ostad, A; Lee, H; et al. (1996) A clinical and histologic evaluation of two medium-depth peels: glycolic
acid versus Jessner's trichloroacetic acid. Dermatol Surg 22:781-786.
U.S. EPA (Environmental Protection Agency). (1980) Guidelines and methodology used in the preparation of
health effect assessment chapters of the consent decree water criteria documents. Federal Register 45(231):79347-
79357.
U.S. EPA. (1986a) Guidelines forthe health risk assessment of chemical mixtures. Federal Register
51(185):34014-34025. Available from: .
U.S. EPA. (1986b) Guidelines for mutagenicity risk assessment. Federal Register 51(185):34006-34012. Available
from: .
U.S. EPA. (1988) Recommendations for and documentation of biological values for use in risk assessment.
Prepared by the Environmental Criteria and Assessment Office, Office of Health and Environmental Assessment,
Cincinnati, OH for the Office of Solid Waste and Emergency Response, Washington, DC; EPA/600/6-87/008.
Available from from: .
U.S. EPA. (1991) Guidelines for developmental toxicity risk assessment. Federal Register 56(234):63798-63826.
Available from: .
U.S. EPA. (1992) Draft report: a cross-species scaling factor for carcinogen risk assessment based on equivalence
of mg/kg3/4/day. Federal Register 57(109):24152-24173.
U.S. EPA. (1994a) Interim policy for particle size and limit concentration issues in inhalation toxicity studies.
Federal Register 59(206):53799. Available from: .
U.S. EPA. (1994b) Methods for derivation of inhalation reference concentrations and application of inhalation
dosimetry. Office of Research and Development, Washington, DC; EPA/600/8-90/066F. Available from:
.
U.S. EPA. (1995) Use of the benchmark dose approach in health risk assessment. Risk Assessment Forum,
Washington, DC; EPA/630/R-94/007. Available from:
.
U.S. EPA. (1996) Guidelines for reproductive toxicity risk assessment. Federal Register 61(212):56274-56322.
Available from: .
U.S. EPA. (1998) Guidelines for neurotoxicity risk assessment. Federal Register 63(93):26926-26954. Available
from: .
U.S. EPA. (2000a) Science policy council handbook: risk characterization. Office of Science Policy, Office of
Research and Development, Washington, DC; EPA 100-B-00-002. Available from:
.
U.S. EPA. (2000b) Benchmark dose technical guidance document [external review draft]. Risk Assessment Forum,
Washington, DC; EPA/630/R-00/001. Available from: .
U.S. EPA. (2000c) Supplementary guidance for conducting health risk assessment of chemical mixtures. Risk
Assessment Forum, Washington, DC; EPA/630/R-00/002. Available from:
.
169 DRAFT - DO NOT CITE OR QUOTE
-------
U.S. EPA. (2000d) Help manual for benchmark dose software version 1.20. Office of Research and Development,
Washington, DC; EPA600/R-00/014F.
U.S. EPA. (2002) A review of the reference dose and reference concentration processes. Risk Assessment Forum,
Washington, DC; EPA/630/P-02/002F. Available from: .
U.S. EPA. (2003a) Toxicological review of dichloroacetic acid. Integrated Risk Information System (IRIS).
National Center for Environmental Assessment, Washington, DC. Available online at
http://www.epa.gov/iris/toxreviews/0654-tr.pdf.
U.S. EPA. (2005a) Guidelines for carcinogen risk assessment. Risk Assessment Forum, Washington, DC;
EPA/630/P-03/001B. Available from: .
U.S. EPA. (2005b) Supplemental guidance for assessing susceptibility from early-life exposure to carcinogens. Risk
Assessment Forum, Washington, DC; EPA/630/R-03/003F. Available from: .
U.S. EPA. (2005c) Drinking water addendum to the criteria document for trichloroacetic acid. Prepared for Health
and Ecological Criteria Division, Office of Science and Technology, Office of Water, Washington, DC.
U.S. EPA. (2006a) Science policy council handbook: peer review. Third edition. Office of Science Policy, Office of
Research and Development, Washington, DC; EPA/ 100/B-06/002. Available from:
.
U.S. EPA. (2006b) A Framework for Assessing Health Risk of Environmental Exposures to Children. National
Center for Environmental Assessment, Washington, DC, EPA/600/R-05/093F. Available from:
.
U.S. EPA. (2006c) National primary drinking water regulations: stage 2 disinfectants and disinfection byproducts
rule. Federal Register 71(2):387-493.
Vartiainen, TE; Pukkala, T; Rienoja, T; et al. (1993) Population exposure to tri- and tetrachloroethene and cancer
risk: two cases of drinking water pollution. Chemosphere 27(7):1171-1181.
Vogelstein, B; Fearon, ER; Hamilton, SR; et al. (1988) Genetic alterations during colorectal-tumor development. N
EnglJMed 319:525-532.
Volkel, W; Friedwald, M; Lederer, E; et al. (1998) Biotransformation of perchloroethene: dose-dependent excretion
of trichloroacetic acid, dichloroacetic acid, and N-acetyl-s-(trichlorovinyl)-l-cysteine in rats and humans after
inhalation. Toxicol Appl Pharmacol 153:20-27.
Von Tungeln, LS; Yi, P; Bucci, TJ; et al. (2002) Tumorigenicity of chloral hydrate, trichloroacetic acid,
trichloroethanol, malondialdehyde, 4-hydroxy-2-nonenal, crotonaldehyde, andacroleinintheB6C3F(l) neonatal
mouse. Cancer Lett 185(1): 13-19.
Wagner, JR; Hu, CC; Ames, BN. (1992) Endogenous oxidative damage of deoxycytidine inDNA. Proc Natl Acad
Sci 89:3380-3384.
Walgren, JL; Kurtz, DT; and McKillan, JM (2005) Lack of direct mitogenic activity of dichloroacetate and
trichloroacetate in cultured rat hepatocytes. Toxicology 211: 220-230.
Ward, JM; Hagiwara, A; Anderson, LM et al. (1988) The chronic hepatic or renal toxicity of di(2-
ethylhexyl)phthalate, acetaminophen, sodiumbarbital, and Phenobarbital in male B6C3F1 mice: autoradiographic,
immunohistochemical, and biochemical evidence for levels of DNA synthesis not associated with carcinogenesis or
tumor promotion. Toxicology and Applied Pharmacology 96: 494-506.
170 DRAFT - DO NOT CITE OR QUOTE
-------
Warren, DA; Gracter, LJ; Channel, SR; et al. (2006) Trichloroethylene, trichloroacetic acid, and dichloroacetic acid:
do they affect eye development in the Sprague-Dawley rat? Int J of Toxicology 25: 279-284.
Weber, E; Moore, MA; Bannasch, P. (1988) Enzyme histochemical and morphological phenotype of amphophilic
foci and amphophilic/tigroid cell adenomas in rat liver after combined treatment with dehydroepiandrosterone and
N-nitrosomorpholine. Carcinogenesis 9(6): 1049-1054.
Webster, KE; Ferree, PM; Holmes, RP; et al. (2000) Identification of missense, nonsense, and deletion mutations in
the GRHPR gene in patients with primary hyperoxaluria type II (PH2). Hum Genet 107:176-185.
Werner, H; Le, RD. (2000) New concepts in regulation and function of the insulin-like growth factors: implications
for understanding normal growth and neoplasia. Cell Mol Life Sci 57:932-942.
Wilson, JD; Brown, CB; Walker, PP. (2001) Factors involved in clearance of genital warts. Int J STD AIDS
12:789-792.
Witheiler, D; Lawrence, N; Cox, SL; et al. (1996) Facial actinic keratoses (AK) treated with Jessner's solution (JD)
and 35% trichloroacetic widespread acid (TCA) peel vs 5% fluorouracil (5-FU) cream: long-term. Dermatol Surg
22:807-815.
Woods, CG; Burns, AM; Bradford, BU; et al. (2007) Wy-14643-induced cell proliferation and oxidative stress in
mouse liver are independent of NADPH oxidase. Toxicol. Science 98(2): 366-374. .
Xu, G; Stevens, DK; Bull, RJ. (1995) Metabolism of bromodichloroacetate in B6C3F: mice. Drug Metab Disp
23(12):1412-1416.
Yokoyama, Y; Tsuchida, S; Hatayama, I; et al. (1993) Lack of peroxisomal enzyme inducibility in rat hepatic
preneoplastic lesions induced by mutagenic carcinogens: contrasted expression of glutathione S-transferase P form
and enoyl CoA hydratase. Carcinogenesis 14(3):393-398.
Yang, Q; Ito, S; Gonzalez, FJ (2007) Hepatocyte-restricted constitutive activation of PPARa induces
hepatoproliferationbutnothepatocarcinogenesis. Carcinogenesis 28: 1171-1177.
Yeldandi, AV; Milano, M; Subbarao, V et al. (1989) Evaluation of liver cell proliferation during ciprofibrate-
induced hepatocarcinogenesis. Cancer Letters 47: 21-27.
Yu, KO; Barton, HA; Mahle, DA; et al. (2000) In vivo kinetics of trichloroacetate in male Fisher 344 rats. Toxicol
Sci 54:302-311.
Ziglio, GG. (1981) Human exposure to environmental trichloroethylene and tetrachloroethylene: preliminary data
on population groups of Milan, Italy. Bull Environ Contam Toxicol 26:131-136.
Ziglio, GG; Fara, GM; Beltramelli, G; et al. (1983) Human environmental exposure to trichloro- and
tetrachloroethylene from water and air in Milan, Italy. Arch Environ Contam Toxicol 12:57-64.
171 DRAFT - DO NOT CITE OR QUOTE
-------
APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC
COMMENTS AND DISPOSITION
[to be added]
A-1 DRAFT - DO NOT CITE OR QUOTE
-------
APPENDIX B. INPUT AND OUTPUT DATA FOR BENCHMARK DOSE MODELING
OF DEVELOPMENTAL DATA FROM SMITH ET AL. (1989)
A. Data sets for modeling rat fetal response to exposure to trichloroacetic acid in drinking
water during CDs 6-15 (Smith et al., 1989).
A.I. Data for fetal body weights <3.16 g (a = 0.05)
As summarized from the individual animal data sheets (see Section B). Each triplet of numbers
represents a distinct set of litters within a dose group; in order, the numbers in each triplet
represent number of fetuses with body weight <3.16 g, number of fetuses in the litter, number of
litters.
Dose = 0
0 6 1,1 6 1,1 7 1,1 8 1,0 9 2,2 10 1, 3 10 1,0 11 4, 2 11 1,0 12 7,1 12 1, 2 12 1,0 13 1, 0 14 2,3 15 1
Dose = 330 mg/kg-day
0 1 1,5 6 1,0 9 1,1 10 1,8 10 1,6 11 1, 8 11 1,0 12 1, 5 12 1, 11 12 1,7 13 1, 8 13 1, 11 13 1, 13 13 1,
1 14 1, 1214 1,015 1, 1215 1, 1616 1
Dose = 800 mg/kg-day
1 2 1,2 3 1,4 4 1,6 7 1, 7 7 1,5 8 1,9 9 1,8 10 1,4 11 1,8 11 1,11 11 3,12 12 1,12 13 1,13 13 1, 8 14 1
Dose = 1200 mg/kg-day
1 1 2,4 4 1,4 6 1,6 6 1,2 7 1,6 7 2,7 7 1,9 9 1,10 11 1,11 11 1,13 13 1
Dose = 1800 mg/kg-day
1 1 2,2 2 2,3 3 1,6 6 2,8 8 1
A.2. Data for fetal visceral malformations
As summarized from the individual pathology reports by R. Kavlock.
Each triplet of numbers represents a distinct set of litters within a dose group; in order, the
numbers in each triplet represent number of malformed fetuses, number of fetuses in the litter,
number of litters.
Dose = 0
0 4 1,1 4 1,0 5 1,0 6 3,0 7 1,2 7 1,0 8 12,1 8 1,2 8 1,0 9 1,0 10 3,
Dose = 330 mg/kg-day
0 1 1,0 4 1,1 6 1,0 7 2,0 8 3,1 8 1,2 8 1,0 9 3,2 9 1,3 9 1,0 10 1,1 10 2,3 10 1
Dose = 800 mg/kg-day
1 1 1,0 2 1,0 3 1,1 5 1,2 5 1,1 6 1,2 6 1,1 7 1,1 8 3,3 8 1,4 8 1,5 8 1,1 9 1,3 9 1,2 10 1
Dose = 1200 mg/kg-day
1 1 2,1 4 1, 2 4 1, 3 4 1,0 5 2, 2 5 1, 4 5 1, 5 5 1,4 6 1,3 8 2,3 9 1
Dose = 1800 mg/kg-day
1 14,22 1,341,441,66 1
B-l DRAFT - DO NOT CITE OR QUOTE
-------
A.3. Data for fetal crown-rump length <3.4 cm g (a = 0.05)
As summarized from the individual animal data sheets (see Section B). Each triplet of numbers
represents a distinct set of litters within a dose group; in order, the numbers in each triplet
represent number of fetuses with crown-rump length <3.4 cm, number of fetuses in the litter,
number of litters.
Dose = 0
061161171081
092010 12 101
0 114 1 11 1
0 129013 1
0 142 1 15 1
Dose = 330 mg/kg-day
011161
0 9 1 0 10 1 2 10 1
0 11 1 111 1
0 12301321 132
0 14 1 1 14 1
0 15 1 1 15 17 161
Dose = 800 mg/kg-day
121031041
071171
581591
2 101
0 112 1 11 14 11 1611 1
11 121
0 13 1 5 13 1 1 14 1
Dose = 1200 mg/kg-day
1 1244 1
061661
171273571
291011 1 10 11 1
3 13 1
Dose = 1800 mg/kg-day
011111
121221
33 1
66288 1
B-2 DRAFT - DO NOT CITE OR QUOTE
-------
B. Individual fetal body weight and crown-rump length data from the Smith et al. (1989)
rat developmental study.
KEY:
Column 1 Dam ID
Column 2 Pup ID
Column 3 Dose (mg/kg)
Column 4 Litter Size
Column 5 Sex
Column 6 Weight (g)
Column 7 Crown-Rump Length (cm)
532
532
532
532
532
532
535
535
535
535
535
535
536
536
536
536
536
536
536
536
536
536
536
4
5
8
10
11
13
2
3
5
11
12
16
1
3
4
5
6
7
10
11
13
14
15
1200
1200
1200
1200
1200
1200
1800
1800
1800
1800
1800
1800
800
800
800
800
800
800
800
800
800
800
800
6
6
6
6
6
6
6
6
6
6
6
6
11
11
11
11
11
11
11
11
11
11
11
M
F
F
M
M
M
F
F
M
F
M
F
F
M
M
F
M
M
F
F
F
M
F
3.
2.
2.
2.
3.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
.32
.93
.94
.71
.21
.00
.14
.24
.17
.29
.54
.46
.47
.79
.62
.59
.94
.76
.68
.59
.91
.95
.97
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.5
.5
.4
.4
.5
.5
.1
.0
.0
.2
.1
.2
.2
.5
.2
.2
.5
.5
.4
.1
.2
.4
.2
537 7 1800 1 M 2.79 3.4
538
538
538
538
538
538
539
539
539
539
539
539
4
6
9
10
16
17
1
2
3
4
6
9
1800
1800
1800
1800
1800
1800
1200
1200
1200
1200
1200
1200
6
6
6
6
6
6
7
7
7
7
7
7
M
M
F
M
F
M
F
M
F
M
F
M
2.
2.
2.
2.
2.
2.
2.
3.
2.
2.
2.
2.
.51
.19
.40
.38
.21
.41
.86
.31
.86
.70
.82
.86
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.3
.2
.2
.1
.1
.2
.3
.5
.3
.3
.4
.3
B-3 DRAFT - DO NOT CITE OR QUOTE
-------
539 10 1200 7 M 2.76 3.3
540
540
540
540
540
540
540
540
540
541
541
541
541
541
541
541
541
541
541
541
542
542
542
542
542
542
543
543
543
543
543
543
543
543
543
543
543
544
544
544
544
544
544
544
545
545
545
545
545
545
1
2
3
4
7
8
11
12
13
2
3
4
6
7
10
12
13
14
15
16
3
4
6
9
10
11
1
2
3
5
6
7
8
9
10
11
12
2
3
5
6
8
9
10
1
2
3
5
6
7
800
800
800
800
800
800
800
800
800
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
0
0
0
0
0
0
800
800
800
800
800
800
800
800
800
800
800
0
0
0
0
0
0
0
800
800
800
800
800
800
9
9
9
9
9
9
9
9
9
11
11
11
11
11
11
11
11
11
11
11
6
6
6
6
6
6
11
11
11
11
11
11
11
11
11
11
11
7
7
7
7
7
7
7
13
13
13
13
13
13
M
F
M
M
M
M
F
F
M
M
F
M
M
M
M
F
M
F
M
M
F
M
M
M
M
M
M
M
M
M
F
F
F
M
F
M
M
F
F
F
M
M
F
M
M
F
M
F
M
M
2.
2.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
3.
3.
4.
3.
3.
3.
2.
2.
2.
2.
2.
2.
3.
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
3.
2.
2.
2.
.77
.79
.01
.94
.93
.82
.43
.58
.86
.37
.56
.58
.64
.47
.84
.30
.73
.54
.45
.51
.42
.67
.06
.71
.07
.68
.88
.94
.85
.86
.62
.97
.10
.09
.14
.92
.00
.46
.55
.48
.76
.57
.04
.61
.91
.43
.09
.70
.97
.68
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.3
.3
.4
.5
.4
.4
.1
.1
.3
.0
.1
.4
.2
.1
.3
.1
.3
.2
.2
.3
.4
.5
.8
.6
.0
.7
.5
.3
.4
.5
.2
.4
.3
.3
.4
.4
.5
.4
.5
.5
.7
.5
.2
.6
.4
.3
.3
.3
.4
.4
B-4 DRAFT - DO NOT CITE OR QUOTE
-------
545
545
545
545
545
545
545
546
546
546
546
546
546
546
546
546
546
546
547
547
548
548
548
548
548
548
548
548
548
548
548
548
549
549
549
549
549
549
550
550
550
550
550
550
550
550
550
550
550
550
551
551
8
9
10
11
12
13
14
1
2
3
4
5
6
7
8
9
10
11
1
3
1
2
3
4
5
7
8
9
10
11
12
13
4
6
7
8
9
12
1
2
3
5
6
7
8
9
11
12
13
14
1
3
800
800
800
800
800
800
800
0
0
0
0
0
0
0
0
0
0
0
1800
1800
0
0
0
0
0
0
0
0
0
0
0
0
1200
1200
1200
1200
1200
1200
0
0
0
0
0
0
0
0
0
0
0
0
800
800
13
13
13
13
13
13
13
11
11
11
11
11
11
11
11
11
11
11
2
2
12
12
12
12
12
12
12
12
12
12
12
12
6
6
6
6
6
6
12
12
12
12
12
12
12
12
12
12
12
12
8
8
M
F
M
F
M
F
M
F
F
M
F
M
M
M
M
M
F
F
F
M
F
M
M
F
F
F
F
M
F
F
F
M
F
M
M
M
M
M
M
M
F
F
F
M
M
M
F
M
M
F
F
M
2.
2.
2.
2.
2.
2.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
2.
2.
2.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
.72
.39
.74
.76
.99
.97
.85
.11
.07
.47
.19
.29
.68
.42
.19
.36
.22
.47
.30
.41
.75
.51
.35
.46
.90
.73
.83
.76
.58
.63
.37
.53
.23
.66
.08
.35
.49
.25
.47
.85
.58
.71
.52
.52
.31
.38
.55
.33
.56
.39
.75
.35
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.2
.1
.4
.4
.5
.4
.4
.5
.3
.6
.4
.4
.7
.4
.5
.6
.5
.5
.0
.1
.8
.9
.7
.7
.7
.5
.7
.6
.7
.5
.7
.8
.0
.3
.9
.1
.2
.0
.7
.7
.6
.5
.5
.6
.6
.5
.5
.6
.7
.5
.3
.5
B-5 DRAFT - DO NOT CITE OR QUOTE
-------
551
551
551
551
551
551
552
552
552
552
552
552
552
552
552
552
552
552
553
553
553
553
553
553
553
553
553
553
553
553
553
553
554
554
554
554
554
554
554
554
4
6
7
9
10
11
1
2
3
4
6
7
8
9
10
12
13
14
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1
3
6
7
8
10
11
12
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1800
1800
1800
1800
1800
1800
1800
1800
8
8
8
8
8
8
12
12
12
12
12
12
12
12
12
12
12
12
14
14
14
14
14
14
14
14
14
14
14
14
14
14
8
8
8
8
8
8
8
8
M
F
F
M
M
F
F
F
M
M
M
F
F
M
M
M
M
M
F
F
M
F
M
F
M
M
M
F
F
M
M
M
M
M
M
M
M
M
M
M
3.
2.
2.
3.
3.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
2.
2.
2.
2.
2.
2.
.07
.96
.99
.20
.26
.12
.63
.68
.69
.71
.49
.78
.38
.49
.40
.82
.87
.59
.46
.77
.97
.76
.58
.73
.91
.86
.58
.73
.65
.71
.84
.66
.70
.14
.34
.33
.48
.82
.50
.42
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.3
.3
.2
.5
.4
.3
.1
.3
.1
.2
.2
.3
.2
.1
.0
.4
.3
.2
.6
.4
.6
.6
.4
.5
.6
.7
.6
.5
.5
.8
.5
.7
.3
.0
.1
.1
.0
.2
.1
.2
555 13 1800 1 F 2.36 3.0
560
560
560
560
560
560
560
560
560
560
1
2
3
4
5
6
7
8
9
10
0
0
0
0
0
0
0
0
0
0
10
10
10
10
10
10
10
10
10
10
M
F
M
F
M
M
F
F
M
F
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
.35
.43
.94
.33
.21
.30
.25
. 14
.38
.42
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.5
.5
.3
.4
.5
.6
.4
.3
.5
.5
B-6 DRAFT - DO NOT CITE OR QUOTE
-------
561
561
561
561
562
562
562
562
1
2
5
7
7
8
11
13
800
800
800
800
1200
1200
1200
1200
4
4
4
4
4
4
4
4
M
M
M
F
F
M
F
M
2.
3.
2.
2.
2.
2.
2.
2.
.95
.12
.99
.95
.49
.76
.68
.50
3.
3.
3.
3.
3.
3.
3.
3.
.5
.5
.6
.4
.1
.2
.2
.2
564 13 1200 1 M 2.54 3.3
567
567
567
568
568
568
568
568
568
568
568
568
568
568
569
569
569
569
569
569
569
569
569
569
572
572
572
572
572
572
572
573
573
573
573
573
573
573
573
573
573
7
8
11
3
4
5
6
7
8
9
10
11
12
13
1
2
4
5
6
7
8
9
10
12
1
2
6
7
8
11
12
1
2
3
4
5
6
7
8
9
11
800
800
800
800
800
800
800
800
800
800
800
800
800
800
0
0
0
0
0
0
0
0
0
0
800
800
800
800
800
800
800
0
0
0
0
0
0
0
0
0
0
3
3
3
11
11
11
11
11
11
11
11
11
11
11
10
10
10
10
10
10
10
10
10
10
7
7
7
7
7
7
7
12
12
12
12
12
12
12
12
12
12
M
M
M
M
F
M
F
M
F
M
F
F
F
M
M
F
F
F
F
M
M
M
F
F
M
M
F
F
M
F
M
F
M
F
M
F
M
M
F
M
F
3.
2.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
3.
3.
3.
2.
2.
3.
3.
3.
4 .
3.
4 .
4 .
3.
4 .
4 .
3.
3.
3.
.04
.64
.18
.59
.82
.93
.73
.83
.72
.86
.79
.94
.90
.02
.55
.35
.40
.16
.70
.76
.67
.88
.30
.06
.25
.07
.50
.89
.12
.05
.15
.16
.90
.05
.09
.92
.39
.37
.95
.85
.84
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
4 .
4 .
3.
4 .
3.
3.
.6
.4
.6
.3
.4
.5
.4
.4
.4
.4
.4
.4
.4
.5
.7
.6
.6
.7
.6
.6
.5
.5
.6
.5
.7
.5
.4
.5
.5
.5
.6
.9
.8
.9
.8
.0
.0
.9
.0
.8
.9
B-7 DRAFT - DO NOT CITE OR QUOTE
-------
573
573
574
574
574
574
574
574
574
574
574
576
576
576
576
576
576
576
576
576
576
576
576
577
577
577
578
578
578
578
578
578
578
580
580
580
580
580
580
580
580
580
580
580
580
581
581
582
582
582
12
13
1
2
3
4
5
7
8
9
10
1
2
3
4
5
6
7
10
11
12
13
14
3
5
14
4
6
9
11
13
14
15
1
2
3
4
5
6
7
8
9
10
11
12
10
12
2
4
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1800
1800
1800
1200
1200
1200
1200
1200
1200
1200
0
0
0
0
0
0
0
0
0
0
0
0
1800
1800
1200
1200
1200
12
12
9
9
9
9
9
9
9
9
9
12
12
12
12
12
12
12
12
12
12
12
12
3
3
3
7
7
7
7
7
7
7
12
12
12
12
12
12
12
12
12
12
12
12
2
2
11
11
11
M
F
M
F
F
F
F
M
M
M
M
M
F
F
M
M
M
F
M
M
M
M
M
M
F
M
M
M
F
M
M
M
F
M
F
F
M
F
F
F
F
M
F
F
M
M
F
M
F
M
3.
3.
3.
3.
3.
3.
3.
3.
4.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
2.
3.
3.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
3.
3.
3.
4.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
2.
2.
3.
.73
.51
.78
.71
.89
.71
.66
.93
.21
.85
.74
.52
.38
.40
.86
.51
.69
.72
.75
.67
.90
.51
.67
.37
.28
.37
.68
.58
.29
.78
.42
.74
.52
.90
.56
.70
.10
.68
.91
.90
.65
.75
.66
.77
.68
.57
.66
.92
.91
.12
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
4.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
4.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.8
.9
.9
.8
.9
.9
.7
.9
.8
.8
.6
.6
.6
.7
.7
.8
.4
.8
.5
.0
.7
.7
.2
.2
.1
.8
.7
.5
.5
.3
.5
.3
.0
.7
.6
.8
.8
.8
.8
.7
.6
.8
.8
.7
. 1
.4
.6
.5
.5
B-8 DRAFT - DO NOT CITE OR QUOTE
-------
582
582
582
582
582
582
582
582
583
583
583
583
583
583
583
583
583
583
583
583
585
585
585
585
585
585
585
585
585
585
585
585
585
587
587
587
587
587
587
587
587
587
587
587
587
587
588
588
588
588
588
588
588
6
7
8
9
10
11
13
14
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
13
1
2
3
5
6
7
8
9
10
11
12
13
14
1
2
3
5
6
7
9
1200
1200
1200
1200
1200
1200
1200
1200
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
11
11
11
11
11
11
11
11
12
12
12
12
12
12
12
12
12
12
12
12
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
11
11
11
11
11
11
11
M
M
F
M
M
M
M
M
F
M
M
M
F
M
F
F
M
M
F
F
M
M
F
M
M
F
M
M
M
M
F
F
M
M
F
F
F
F
M
F
F
M
F
M
M
F
M
M
M
M
M
F
F
2.
3.
2.
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
2.
2.
3.
2.
2.
3.
2.
3.
2.
2.
3.
2.
3.
3.
3.
2.
2.
.81
.10
.97
.08
.00
.82
.13
.22
.65
.83
.71
.85
.63
.80
.50
.52
.87
.80
.66
.79
.55
.44
.46
.79
.52
.56
.86
.86
.77
.60
.53
.49
.34
.09
.91
.05
.99
.75
.12
.67
.73
.18
.51
.05
.81
.66
.06
.88
.21
.29
.19
.96
.97
B-9
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.4
.5
.6
.4
.7
.4
.6
.6
.8
.8
.8
.8
.8
.8
.7
.7
.8
.8
.8
.8
.8
.9
.8
.9
.7
.8
.9
.9
.9
.8
.7
.7
.7
.7
.5
.6
.5
.5
.6
.5
.5
.5
.4
.5
.5
.4
.5
.4
.5
.6
.6
.5
.4
DRAFT - DO NOT CITE OR QUOTE
-------
588
588
588
588
589
589
589
589
589
589
589
589
589
589
589
591
591
591
591
591
591
591
591
591
591
591
591
591
594
594
594
594
594
594
594
595
595
595
595
595
595
595
596
596
596
596
596
596
596
596
596
596
10
11
12
13
1
2
3
4
5
6
7
8
9
10
11
1
2
3
4
5
8
9
10
11
12
13
14
15
1
3
4
5
6
7
10
1
3
4
7
8
11
12
1
2
3
4
5
6
7
8
9
10
800
800
800
800
0
0
0
0
0
0
0
0
0
0
0
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
1200
0
0
0
0
0
0
0
0
0
0
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
13
13
13
13
13
13
13
13
13
13
13
13
13
7
7
7
7
7
7
7
7
7
7
7
7
7
7
15
15
15
15
15
15
15
15
15
15
F
F
M
F
F
M
F
F
F
M
F
M
F
F
M
M
F
M
M
F
M
M
F
F
M
F
F
M
F
M
F
F
M
M
M
F
F
M
F
M
F
M
F
M
F
F
M
F
M
M
F
F
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
2.
2.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
2.
3.
2.
2.
2.
2.
2.
3.
2.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.94
.03
.16
.16
.34
.72
.52
.41
.51
.72
.62
.73
.44
.46
.68
.07
.66
.91
.83
.69
.12
.92
.98
.91
.78
.60
.79
.77
.67
.91
.58
.82
.64
.24
.90
.73
.64
.76
.39
.07
.42
.76
.02
.39
.07
.39
.38
.22
.22
.15
.30
.45
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.4
.4
.5
.7
.7
.8
.8
.8
.7
.7
.8
.7
.7
.8
.8
.4
.3
.3
.4
.5
.4
.4
.5
.6
.4
.3
.4
.5
.5
.4
.3
.4
.3
.5
.4
.5
.4
.5
.1
.4
.0
.4
.3
.9
.5
.7
.7
.5
.5
.7
.7
.7
B-10 DRAFT - DO NOT CITE OR QUOTE
-------
596
596
596
596
596
597
597
597
597
597
597
597
599
599
599
599
599
599
599
600
600
600
600
600
600
600
600
600
600
601
601
601
601
601
601
601
601
602
602
602
602
602
602
602
602
602
603
603
603
603
603
11
12
13
14
15
7
8
11
12
13
14
15
2
3
4
5
10
11
12
1
3
5
6
7
9
10
11
12
13
1
2
4
5
6
9
10
11
2
4
5
9
10
11
12
13
14
3
4
5
6
7
0
0
0
0
0
1200
1200
1200
1200
1200
1200
1200
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
800
0
0
0
0
0
0
0
0
1200
1200
1200
1200
1200
1200
1200
1200
1200
800
800
800
800
800
15
15
15
15
15
7
7
7
7
7
7
7
7
7
7
7
7
7
7
10
10
10
10
10
10
10
10
10
10
8
8
8
8
8
8
8
8
9
9
9
9
9
9
9
9
9
11
11
11
11
11
F
M
M
F
M
M
M
F
F
M
F
M
M
M
F
M
M
F
M
F
F
M
M
F
M
M
F
F
M
F
F
M
M
M
F
F
M
F
F
M
M
F
M
M
F
M
F
M
F
M
M
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
2.
2.
2.
2.
2.
2.
3.
3.
2.
2.
3.
2.
2.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
2.
2.
2.
2.
2.
2.
2.
3.
3.
3.
3.
3.
.28
.36
.48
.19
.58
.31
.20
.33
.28
.38
.12
.16
.73
.94
.44
.68
.65
.64
.68
.41
.01
.19
.78
.70
.42
.98
.85
.67
.06
.34
.60
.47
.57
.46
.15
.57
.20
.50
.66
.44
.63
.21
.56
.62
.36
.46
.16
.20
.15
.19
.07
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.6
.8
.8
.9
.4
.4
.6
.5
.6
.3
.4
.3
.6
.4
.5
.5
.5
.7
.3
.6
.5
.2
.4
.7
.7
.6
.5
.6
.8
.9
.7
.8
.6
.5
.7
.8
.5
.4
.3
.5
.2
.5
.6
.4
.5
.6
.6
.4
.5
.5
B-11 DRAFT - DO NOT CITE OR QUOTE
-------
603
603
603
603
603
603
604
604
604
604
604
604
604
604
604
605
605
605
605
605
605
605
605
605
605
605
605
606
606
606
606
606
606
606
606
606
606
606
608
611
611
612
612
612
612
612
612
612
612
612
612
612
9
11
12
13
14
15
1
2
4
6
7
8
9
10
11
2
3
4
5
6
7
8
9
10
11
12
13
1
2
3
4
5
6
7
8
9
11
12
11
6
8
1
2
3
4
5
6
7
8
9
10
11
800
800
800
800
800
800
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1200
800
800
800
800
800
800
800
800
800
800
800
800
800
11
11
11
11
11
11
9
9
9
9
9
9
9
9
9
12
12
12
12
12
12
12
12
12
12
12
12
11
11
11
11
11
11
11
11
11
11
11
1
2
2
14
14
14
14
14
14
14
14
14
14
14
M
M
F
M
M
F
M
F
F
M
M
F
F
M
M
F
M
F
M
M
M
F
M
M
F
M
M
M
F
M
F
F
M
M
F
M
M
F
M
F
F
M
M
F
F
M
M
F
M
M
M
F
3.
3.
3.
3.
3.
3.
4.
3.
3.
4.
4.
3.
3.
3.
3.
3.
4.
3.
4.
4.
4.
3.
4.
3.
3.
4.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
3.
3.
2.
2.
3.
3.
3.
2.
3.
3.
3.
2.
.28
.20
.28
.24
.22
.03
.03
.89
.94
.39
.12
.72
.81
.98
.98
.86
.50
.93
.27
.39
.01
.64
.12
.98
.57
.36
.98
.59
.39
.60
.33
.29
.94
.90
.52
.78
.67
.49
.16
.96
.17
.26
.93
.95
.22
.18
.03
.63
.07
.28
.39
.95
3.
3.
3.
3.
3.
3.
3.
3.
3.
4.
3.
3.
3.
4.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.7
.6
.4
.5
.6
.4
.9
.8
.9
.0
.9
.6
.7
.0
.9
.7
.9
.8
.8
.8
.9
.9
.9
.8
.5
.8
.8
.7
.5
.6
.5
.4
.7
.6
.7
.8
.9
.7
.1
.3
.7
.6
.4
.6
.7
.5
.5
.2
.4
.6
.5
.5
B-12 DRAFT - DO NOT CITE OR QUOTE
-------
612
612
612
613
613
613
613
613
613
613
613
613
613
613
613
613
12
13
14
1
2
4
5
6
7
8
9
10
11
12
13
14
800
800
800
330
330
330
330
330
330
330
330
330
330
330
330
330
14
14
14
13
13
13
13
13
13
13
13
13
13
13
13
13
F
M
M
F
M
F
F
M
F
F
M
M
F
M
F
F
3.
2.
3.
2.
3.
2.
2.
2.
2.
3.
3.
2.
3.
3.
3.
2.
.18
.99
.10
.63
.29
.84
.92
.87
.89
.08
.36
.76
.04
.07
.01
.84
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.5
.5
.5
.4
.6
.4
.5
.6
.5
.6
.8
.4
.6
.7
.4
.4
614 1 330 1 M 3.34 3.:
615
615
615
615
615
615
615
615
615
615
615
615
615
615
616
616
616
616
616
616
616
616
616
616
616
616
617
617
617
617
617
617
617
617
617
1
2
3
4
5
6
7
8
9
11
12
13
14
15
1
2
3
4
5
7
8
9
10
11
12
14
1
2
3
4
6
7
8
9
10
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
14
14
14
14
14
14
14
14
14
14
14
14
14
14
12
12
12
12
12
12
12
12
12
12
12
12
11
11
11
11
11
11
11
11
11
M
F
M
F
M
M
M
F
F
F
M
F
M
M
M
M
M
F
F
F
F
M
F
F
M
F
F
M
F
F
F
F
F
F
M
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
3.
3.
2.
3.
2.
3.
3.
3.
3.
2.
3.
3.
2.
3.
2.
3.
3.
2.
2.
2.
3.
.23
.01
.01
.15
.12
.44
.08
.02
.13
.02
.02
.15
.97
.95
.04
.08
.87
.17
.99
.39
.24
.20
.50
.95
.40
.36
.92
.22
.87
.24
.23
.89
.65
.85
.15
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.8
.5
.8
.7
.5
.7
.6
.6
.7
.7
.5
.6
.6
.6
.5
.5
.5
.5
.4
.6
.6
.6
.7
.6
.7
.6
.4
.5
.5
.6
.6
.5
.4
.5
.6
B-13 DRAFT - DO NOT CITE OR QUOTE
-------
617
617
618
618
618
618
618
618
619
619
619
619
619
619
619
619
619
619
619
619
619
620
620
620
620
620
620
620
620
620
620
620
620
620
621
621
621
621
621
621
621
621
621
621
621
621
622
622
622
622
622
622
11
12
2
3
4
6
8
9
1
3
4
5
6
7
8
9
10
11
12
13
14
1
2
3
5
6
7
8
9
10
11
12
13
15
1
2
3
4
5
6
7
8
9
10
11
12
1
3
4
5
6
7
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
11
11
6
6
6
6
6
6
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
13
12
12
12
12
12
12
12
12
12
12
12
12
13
13
13
13
13
13
M
M
M
F
F
F
F
M
M
F
F
M
M
M
F
F
M
M
M
M
F
M
F
M
M
F
F
F
M
F
F
F
F
M
F
M
M
F
M
M
M
M
F
F
M
F
F
F
M
M
F
M
3.
3.
3.
2.
3.
3.
3.
3.
3.
3.
2.
2.
2.
1.
3.
2.
2.
2.
3.
2.
2.
3.
3.
3.
3.
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
3.
3.
3.
2.
.20
.60
.28
.88
.08
.00
.00
.00
.00
.04
.70
.81
.90
.88
.01
.65
.56
.86
.13
.80
.68
.11
.05
.14
.33
.31
.17
.79
.39
.06
.22
.05
.23
.15
.27
.55
.57
.37
.45
.49
.62
.76
.77
.61
.61
.60
.98
.21
.44
.13
.01
.86
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.6
.7
.6
.8
.6
.5
.5
.3
.5
.5
.5
.5
.5
.5
.8
.5
.4
.5
.7
.5
.3
.8
.8
.7
.6
.6
.6
.4
.8
.8
.5
.5
.6
.6
.5
.4
.6
.6
.6
.6
.8
.7
.8
.8
.7
.7
.3
.5
.7
.7
.5
.4
B-14 DRAFT - DO NOT CITE OR QUOTE
-------
622
622
622
622
622
622
622
623
623
623
623
623
623
623
623
623
623
623
623
624
624
624
624
624
624
624
624
624
624
624
624
8
9
10
11
12
13
14
1
2
3
4
5
6
7
8
9
10
11
13
1
2
3
4
5
6
7
8
9
10
11
12
330
330
330
330
330
330
330
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
13
13
13
13
13
13
13
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
12
F
M
F
M
F
M
M
M
M
M
F
M
F
F
M
F
M
F
M
M
F
M
M
M
F
F
F
M
M
F
M
2.
3.
2.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
4.
4.
3.
3.
.99
.50
.83
.40
.95
.56
.16
.58
.77
.69
.75
.82
.63
.66
.28
.94
.58
.66
.64
.93
.84
.98
.92
.82
.64
.74
.62
.05
.10
.70
.80
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.4
.6
.4
.6
.4
.6
.6
.5
.8
.6
.8
.7
.5
.6
.5
.4
.6
.7
.6
.9
.9
.9
.8
.8
.8
.7
.7
.8
.9
.8
.9
625 1 330 15 M 3.46 3.7
625
625
625
625
625
625
625
625
625
625
625
625
625
625
626
626
626
626
626
626
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1
2
3
4
5
6
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
15
15
15
15
15
15
15
15
15
15
15
15
15
15
10
10
10
10
10
10
F
F
F
M
F
M
F
M
M
F
M
M
F
F
F
F
M
M
M
M
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
3.
2.
2.
.38
.46
.40
.66
.58
.68
.54
.64
.59
.57
.94
.63
.28
.69
.09
.63
.98
.30
.86
.61
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.5
.5
.5
.6
.6
.8
.6
.5
.6
.5
.7
.6
.5
.6
.5
.5
.2
.5
.4
.3
B-15 DRAFT - DO NOT CITE OR QUOTE
-------
626
626
626
626
627
627
627
627
627
627
627
627
627
627
627
627
627
627
627
627
629
629
629
629
629
629
629
629
629
629
629
629
629
629
629
630
630
630
630
630
630
630
630
630
630
631
631
631
631
631
631
631
631
7
8
9
10
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
1
2
3
4
5
6
8
9
10
11
12
13
14
15
16
2
3
4
5
6
7
8
9
10
11
1
3
4
5
7
8
9
10
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
10
10
10
10
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
16
15
15
15
15
15
15
15
15
15
15
15
15
15
15
15
10
10
10
10
10
10
10
10
10
10
9
9
9
9
9
9
9
9
F
M
M
M
F
M
M
M
M
M
M
F
F
F
M
F
F
M
M
M
F
F
M
F
F
M
F
F
F
F
M
M
F
M
M
F
F
M
F
F
M
F
F
F
F
M
M
M
M
F
F
M
F
2
3
3
3
2
3
2
2
3
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
3
2
2
3
3
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
.86
.14
.18
.12
.51
.02
.81
.75
.07
.69
.76
.44
.62
.85
.65
.65
.58
.84
.79
.42
.88
.94
.05
.58
.71
.91
.70
.18
.76
.75
.09
.23
.81
.95
.32
.22
.57
.21
.28
.40
.28
.40
.05
.38
.39
.53
.68
.80
.26
.61
.35
.57
.64
B-16
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.4
.5
.6
.5
.1
.5
.4
.4
.5
.3
.3
.4
.4
.3
.4
.3
.3
.5
.4
.3
.5
.4
.0
.4
.5
.6
.5
.5
.6
.5
.6
.7
.5
.4
.6
.6
.8
.5
.6
.6
.6
.5
.5
.6
.5
.6
.8
.7
.5
.6
.5
.6
.7
DRAFT - DO NOT CITE OR QUOTE
-------
631 11 330 9 M 3.58 3.7
632
632
632
632
632
632
632
632
632
632
632
633
633
633
633
633
633
633
633
633
633
633
633
634
634
634
634
634
634
634
634
634
634
634
635
635
635
635
635
635
636
636
636
636
636
636
636
636
636
636
636
1
2
3
4
5
6
7
8
9
10
12
1
2
3
4
5
6
7
8
9
10
11
12
1
2
4
5
6
7
8
9
10
11
12
2
3
4
6
7
8
1
2
4
5
6
7
8
9
10
11
12
0
0
0
0
0
0
0
0
0
0
0
330
330
330
330
330
330
330
330
330
330
330
330
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
11
11
11
11
11
11
11
11
11
11
11
12
12
12
12
12
12
12
12
12
12
12
12
11
11
11
11
11
11
11
11
11
11
11
6
6
6
6
6
6
14
14
14
14
14
14
14
14
14
14
14
M
F
M
M
M
F
M
F
M
M
F
F
F
F
F
M
M
F
F
M
F
M
M
M
F
F
F
F
M
F
M
F
M
M
M
F
M
M
F
M
M
M
M
F
M
M
M
F
M
M
F
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
2.
3.
2.
3.
3.
2.
3.
3.
2.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
4 .
3.
3.
3.
3.
3.
.77
.81
.99
.98
.91
.72
.87
.89
.85
.82
.66
.61
.02
.97
.12
.94
.15
.17
.81
.14
.05
.98
.66
.66
.68
.69
.48
.55
.81
.61
.90
.73
.71
.52
.54
.43
.67
.41
.55
.63
.60
.99
.75
.46
.90
.24
.92
.66
.97
.99
.61
3.
3.
3.
4.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
4 .
3.
3.
3.
3.
3.
.8
.7
.8
.0
.6
.7
.9
.8
.7
.7
.6
.8
.6
.4
.5
.4
.5
.6
.4
.5
.5
.6
.4
.7
.6
.7
.7
.6
.6
.7
.8
.6
.7
.5
.5
.4
.6
.4
.6
.5
.6
.8
.7
.8
.8
.0
.8
.7
.8
.8
.6
B-17 DRAFT - DO NOT CITE OR QUOTE
-------
636
636
636
637
637
637
637
637
637
637
637
637
637
637
637
637
637
638
638
638
638
638
638
638
638
638
638
638
13
15
16
1
2
3
4
5
6
7
8
9
10
11
12
13
14
1
3
4
5
6
7
9
10
11
12
13
0
0
0
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
14
14
14
14
14
14
14
14
14
14
14
14
14
14
14
14
14
11
11
11
11
11
11
11
11
11
11
11
M
F
F
F
F
F
M
F
F
F
M
M
M
M
F
M
M
M
M
M
F
M
F
M
M
M
F
F
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
3.
2.
3.
3.
2.
2.
.71
.54
.54
.47
.37
.63
.59
.41
.32
.56
.36
.42
.66
.49
.52
.72
.76
.08
.32
.14
.94
.08
.24
.97
.39
.12
.45
.95
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.7
.6
.6
.6
.5
.5
.7
.6
.6
.3
.5
.7
.7
.8
.8
.7
.9
.6
.7
.5
.5
.4
.6
.4
.7
.6
.3
.5
B-18
DRAFT - DO NOT CITE OR QUOTE
-------
C. Input Data and Results for BMDS Modeling of Litter Incidence Data for Levocardia
(Smith et al., 1989)
C. 1 BMR = 10% extra risk
$Revision: 2.2 $ $Date: 2001/03/14 01:17:00 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:12:21 2004
BMDS MODEL RUN: GAMMA
The form of the probability function is:
P[response]= background+(1-background)*CumGamma[slope*dose,power],
where CumGamma(.) is the cummulative Gamma distribution function
Dependent variable = COLUMNS
Independent variable = COLUMN1
Power parameter is restricted as power >=1
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0185185
Slope = 0.00171859
Power = 1.3
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background -Power
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Slope
Slope 1
Parameter Estimates
Variable Estimate Std. Err.
Background 0 NA
Slope 0.00122482 0.000223166
Power 1 NA
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-19 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood) Deviance Test DF
-33.5379
-33.9229 0.770003 4
-57.0522 47.0286 4
69.8459
P-value
0.9424
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est .
0.
0.
0.
0.
0.
. Prob.
.0000
.3325
.6246
.7700
.8897
Expect
0.
6.
10.
10.
7.
;ed 01
.000
.317
.619
.780
.118
^served i
0
6
12
10
7
Size
26
19
17
14
8
Scalec
Residi
-0
0
-0
-0
1
lal
0
.1545
.6918
.4956
.1329
Chi-square =
0.77
DF = 4
P-value = 0.9430
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 86.0214
BMDL = 64.4009
Gamma Multi-Hit Model with 0.95 Confidence Level
cimma Multi-Hit
10-8
10.6
<
.20.4
"o
S*
u-0.2
0
BMDL
BMD
0 500
14:1204/192004
1000
dose
1500
B-20
DRAFT - DO NOT CITE OR QUOTE
-------
Logistic Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:20 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:21:37 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Slope parameter is restricted as slope >= 1
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
User has chosen the log transformed model
Default Initial Parameter Values
background = 0
intercept = -9.49904
slope = 1.51318
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
intercept slope
intercept 1 -1
slope -1 1
Parameter Estimates
Variable Estimate Std. Err.
background 0 NA
intercept -9.37008 3.27162
slope 1.49364 0.500096
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-21 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model Log(likelihood) Deviance Test DF
Full model -33.5379
P-value
Fitted
Reduced
Dose
0.0000
330.0000
800.0000
1200.0000
1800.0000
model
model
AIC:
Est
0
0
0
0
0
-33.
-57.
71.
Goodne
. Prob.
.0000
.3300
.6489
.7721
.8612
.8035
.0522
.6069
3SS
Exp
of
ect
0
6
11
10
6
0
Fit
;ed
.000
.269
.032
.809
.890
.531045
47.0286
Observed
0
6
12
10
7
3 0.912
4 <.0001
Scaled
Size Residual
26 0
19 -0.1315
17 0.492
14 -0.5153
8 0.1126
Chi-square =
0.54
DF = 3
P-value = 0.9106
Benchmark Dose Computation
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
0.1
Extra risk
0.95
121.785
36.0084
Log-Logistic Model with 0.95 Confidence Level
1
Log-Logistic
0.6
00.4
T3
CO
uIO.2
0
BMDL BMD
0 500
14:21 04/192004
1000
dose
1500
B-22
DRAFT - DO NOT CITE OR QUOTE
-------
Logistic Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:20 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:27:15 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = I/[1+EXP(-intercept-slope*dose)]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Slope parameter is not restricted
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
background = 0 Specified
intercept = -2.53856
slope = 0.00272866
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
intercept slope
intercept 1 -0.81
slope -0.81 1
Parameter Estimates
Variable Estimate Std. Err.
intercept -2.23996 0.490016
slope 0.00303543 0.00064016
B-23 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.5379
-38.321
-57.0522
80.642
Deviance Test DF
9.56618
47.0286
P-value
0.02264
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est
0
0
0
0
0
. Prob.
.0962
.2247
.5470
.8026
.9617
Expect
2
4
9
11
7
;ed 01
.502
.270
.298
.236
.694
^served i
0
6
12
10
7
Size
26
19
17
14
8
Scaled
Residu
-1
0.
1
-0.
-1
al
.664
9508
.316
8301
.278
Chi-square =
7.73
DF = 3
P-value = 0.0520
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 252.908
BMDL = 187.109
Logistic Model with 0.95 Confidence Level
1
^°-8
T3
£0.6
<
c
°04
'•c
(0
LLO 2
U— W . ^
0
^___^—
0 X^l ^
I ,/ j
/\ l "
^/ _|_ -L :
l ,/ ^
-------
Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:30:14 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*dose^l) ]
The parameter betas are restricted to be positive
Dependent variable = COLUMNS
Independent variable = COLUMN1
Total number of observations = 5
Total number of records with missing values = 0
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.0545961
Beta(l) = 0.00112706
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Beta(l)
Beta(l) 1
Parameter Estimates
Variable Estimate Std. Err.
Background 0 NA
Beta(l) 0.00122482 0.000276934
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-25 DRAFT - DO NOT CITE OR QUOTE
-------
Model
Full model
Analysis of Deviance Table
Log (likelihood) Deviance Test DF
-33.5379
P-value
Fitted
Reduced
Dose
i: 1
0.0000
i: 2
330.0000
i: 3
800.0000
i: 4
1200.0000
i: 5
1800.0000
Chi-squar
model -33.9229 0
model -57.0522
AIC: 69.8459
Goodness of Fit
Est . Prob . Expected
0.0000 0.000
0.3325 6.317
0.6246 10.619
0.7700 10.780
0.8897 7.118
e = 0.77 DF = 4
.770003 4
47.0286 4
Observed Size
0 26
6 19
12 17
10 14
7 8
P-value = 0.9430
0.9424
<.0001
Chi^2 Res.
0.000
-0.075
0.347
-0.315
-0.150
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 86.0214
BMDL = 64.4009
Multistage Model with 0.95 Confidence Level
-------
Probit Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:53 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:34:52 2004
BMDS MODEL RUN Log Probit
The form of the probability function is:
P[response] = Background
+ (1-Background) * CumNorm(Intercept+Slope*Log(Dose)),
where CumNorm(.) is the cumulative normal distribution function
Dependent variable = COLUMNS
Independent variable = COLUMN1
Slope parameter is not restricted
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
User has chosen the log transformed model
Default Initial (and Specified) Parameter Values
background = 0
intercept = -5.72134
slope = 0.911264
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
intercept slope
intercept 1 -1
slope -1 1
Parameter Estimates
Variable Estimate Std. Err.
background 0 NA
intercept -5.71203 1.93477
slope 0.909892 0.294137
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-27 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model Log(likelihood) Deviance Test DF
Full model -33.5379
P-value
Fitted
Reduced
Dose
0.0000
330.0000
800.0000
1200.0000
1800.0000
model
model
AIC:
Est
0
0
0
0
0
-
Goo
. Prob.
.0000
.3316
.6444
.7701
.8661
-33.813
57.0522
71.6259
dness of
Expect
0.
6.
10.
10.
6.
0
Fit
;ed
.000
.301
.955
.781
.929
.550064
47.0286
Observed
0
6
12
10
7
3 0.9078
4 <.0001
Scaled
Size Residual
26 0
19 -0.1464
17 0.5296
14 -0.4963
8 0.07399
Chi-square =
0.55
DF = 3
P-value = 0.9069
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 130.221
BMDL = 19.6033
Probit Model with 0.95 Confidence Level
^0.8
t5
| 0.6
00.4
t5
£0.2
0
Probit
T
0
500
14:3404/192004
1000
dose
1500
B-28
DRAFT - DO NOT CITE OR QUOTE
-------
Probit Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:53 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:40:51 2004
BMDS MODEL RUN Probit
The form of the probability function is:
P[response] = CumNorm(Intercept+Slope*Dose),
where CumNorm(.) is the cumulative normal distribution function
Dependent variable = COLUMNS
Independent variable = COLUMN1
Slope parameter is not restricted
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
background = 0 Specified
intercept = -1.84332
Slope = 0.00207787
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
intercept
intercept 1
slope -0.8
slope
-0.8
1
Parameter Estimates
Variable Estimate Std. Err.
intercept -1.34013 0.270743
slope 0.00175814 0.000331975
Analysis of Deviance Table
Model Log(likelihood) Deviance Test DF P-value
B-29 DRAFT - DO NOT CITE OR QUOTE
-------
Full model
Fitted model
Reduced model
AIC:
-33.5379
-38.3284
-57.0522
80.6568
9.58089
47.0286
0.02249
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est
0
0
0
0
0
. Prob.
.0901
.2236
.5265
.7792
.9660
Expect
2
4
8
10
7
;ed 01
.343
.249
.950
.909
.728
^served i
0
6
12
10
7
£
Size I
26
19
17
14
8
Jcaled
Residual
-1.605
0.9639
1.482
-0.586
-1.419
Chi-square =
DF = 3
P-value = 0.0449
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 243.96
BMDL = 185.061
Probit Model with 0.95 Confidence Level
1 0.6
o
CD
•50.4
0.2
0
Probit
BMDL
BMP
0 500
14:4004/192004
1000
dose
1500
B-30 DRAFT - DO NOT CITE OR QUOTE
-------
Quantal Linear Model $Revision: 2.2 $ $Date: 2000/03/17 22:27:16 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:42:25 2004
BMDS MODEL RUN Probit
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*dose)]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0185185
Slope = 0.000985037
Power = 1 Specified
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background -Power
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Slope
Slope 1
Parameter Estimates
Variable Estimate Std. Err.
Background 0 NA
Slope 0.00122482 0.000223165
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-31 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood) Deviance Test DF
-33.5379
-33.9229 0.770003 4
-57.0522 47.0286 4
69.8459
P-value
0.9424
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est .
0.
0.
0.
0.
0.
. Prob.
.0000
.3325
.6246
.7700
.8897
Expect
0.
6.
10.
10.
7.
;ed 01
.000
.317
.619
.780
.118
^served i
0
6
12
10
7
Size
26
19
17
14
8
Scalec
Residi
-0
0
-0
-0
1
lal
0
.1545
.6918
.4956
.1329
Chi-square =
0.77
DF = 4
P-value = 0.9430
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 86.0214
BMDL = 64.4009
Quantal Linear Model with 0.95 Confidence Level
1 0-8
1 0.6
<
OQ.4
CO
0.2
0
uantal Linear
BMDL
BMD
0 500
14:4204/192004
1000
dose
B-32
1500
DRAFT - DO NOT CITE OR QUOTE
-------
Quantal Quadratic Model $Revision: 2.2 $ $Date: 2000/03/17 22:27:16 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:48:26 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*dose^2)]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0185185
Slope = 5.472436-007
Power = 2 Specified
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Power
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Background
Background 1
Slope -0.64
Slope
-0.64
1
Variable
Background
Slope
Parameter Estimates
Estimate
0.016097
1.227746-006
Std. Err.
0.0753872
3.1613e-007
B-33
DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Dose Est
0.0000 0
330.0000 0
800.0000 0
1200.0000 0
1800.0000 0
Log (likelihood) Deviance Test
-33.5379
-38.4501
-57.0522
80.9002
Goodness of Fit
. Prob . Expected
.0161 0.419
.1392 2.645
.5516 9.377
.8321 11.649
.9816 7.853
9.82436
47.0286
Observed
0
6
12
10
7
DF P-value
3 0.02012
4 <.0001
Scaled
Size Residual
26 -0.6522
19 2.223
17 1.279
14 -1.179
8 -2.242
Chi-square =
13.42
DF = 3
P-value = 0.0038
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 292.945
BMDL = 247.169
Quantal Quadratic Model with 0.95 Confidence Level
Quanta! Quadratic
£0.6
-------
Weibull Model $Revision: 2.2 $ $Date: 2000/03/17 22:27:16 $
Input Data File: C:\BMDS\UNSAVED1.(d)
Gnuplot Plotting File: C:\BMDS\UNSAVEDl.plt
Mon Apr 19 14:50:47 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*dose^power)]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Power parameter is not restricted
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0185185
Slope = 0.0025741
Power = 0.871847
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Slope Power
Slope 1 -1
Power -1 1
Parameter Estimates
Variable Estimate Std. Err.
Background 0 NA
Slope 0.00172885 0.00372313
Power 0.949024 0.317666
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-3 5 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Log(likelihood)
-33.5379
Deviance Test DF
P-value
Fitted
Reduced
model
model
AIC:
-33.
-57.
71.
.9102
.0522
.8203
Goodness of
Dose
0.0000
330.0000
800.0000
1200.0000
1800.0000
Est
0
0
0
0
0
. Prob.
.0000
.3459
.6261
.7643
.8804
Fit
Expected
0.
6.
10.
10.
7.
.000
.572
.643
.701
.043
0.74446
47.0286
Observed
0
6
12
10
7
3 0.8627
4 <.0001
Scaled
Size Residual
26 0
19 -0.276
17 0.6801
14 -0.4413
8 -0.04715
Chi-square =
0.74
DF = 3
P-value = 0.8648
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 75.9968
BMDL = 5.08236
Weibull Model with 0.95 Confidence Level
Weibull
I0'8
1 0.6
<
.20.4
CD
0.2
0
BMDL
BMP
0 500
14:5004/192004
1000
dose
1500
B-36
DRAFT - DO NOT CITE OR QUOTE
-------
C.2 BMR = 5% extra risk
Gamma $Revision: 2.2 $ $Date: 2001/03/14 01:17:00 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:38:24 2004
BMDS MODEL RUN
The form of the probability function is:
P[response]= backgrounds- (1-background)*CumGamma[slope*dose,power]
where CumGamma(.) is the cummulative Gamma distribution function
Dependent variable = COLUMNS
Independent variable = COLUMN1
Power parameter is restricted as power >=1
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0185185
Slope = 0.00171859
Power = 1.3
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background -Power
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Slope
Slope 1
Parameter Estimates
Variable Estimate Std. Err.
Background 0 NA
Slope 0.00122482 0.000223166
Power 1 NA
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-37 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood) Deviance Test DF
-33.5379
-33.9229 0.770003 4
-57.0522 47.0286 4
69.8459
P-value
0.9424
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est .
0.
0.
0.
0.
0.
. Prob.
.0000
.3325
.6246
.7700
.8897
Expect
0.
6.
10.
10.
7.
;ed 01
.000
.317
.619
.780
.118
^served i
0
6
12
10
7
Size
26
19
17
14
8
Scalec
Residi
-0
0
-0
-0
1
lal
0
.1545
.6918
.4956
.1329
Chi-square =
0.77
DF = 4
P-value = 0.9430
Benchmark Dose Computation
Specified effect = 0.05
Risk Type = Extra risk
Confidence level = 0.95
BMD = 41.8783
BMDL = 31.3527
Gamma Multi-Hit Model with 0.95 Confidence Level
amma Multi-Hit
I 0.6
"o
00.4
0.2
0
BMDL
0
500
14:31 08/102004
1000
dose
1500
B-38
DRAFT - DO NOT CITE OR QUOTE
-------
Logistic Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:20 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:27:27 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Slope parameter is restricted as slope >= 1
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
User has chosen the log transformed model
Default Initial Parameter Values
background = 0
intercept = -9.49904
slope = 1.51318
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) - back ground - have been estimated at
a boundary point, or have been specified by the user, and do not appear in the
correlation matrix )
intercept slope
intercept 1 -1
slope -1 1
Parameter Estimates
Variable Estimate Std. Err.
background 0 NA
intercept -9.37008 3.27162
slope 1.49364 0.500096
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-39 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood) Deviance Test DF
-33.5379
-33.8035 0.531045 3
-57.0522 47.0286 4
71.6069
P-value
0.912
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est .
0.
0.
0.
0.
0.
. Prob.
.0000
.3300
.6489
.7721
.8612
Expect
0
6
11
10
6
;ed 01
.000
.269
.032
.809
.890
^served i
0
6
12
10
7
Size
26
19
17
14
8
Scale<
Resid
-0
-0
0
d
ual
0
.1315
0.492
.5153
.1126
Chi-square =
0.54
DF = 3
P-value = 0.9106
Benchmark Dose Computation
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
0.05
Extra risk
0.95
73.8468
17.0566
Log-Logistic Model with 0.95 Confidence Level
1
£0.6
.20.4
t5
co
uIO.2
Log-Logistic
0
BMDL
BMP
0 500
14:4408/102004
1000
dose
B-40
1500
DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:47:29 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*dose^l) ]
The parameter betas are restricted to be positive
Dependent variable = COLUMNS
Independent variable = COLUMN1
Total number of observations = 5
Total number of records with missing values = 0
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.0545961
Beta(l) = 0.00112706
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Beta(l)
Beta(l) 1
Parameter Estimates
Variable Estimate Std. Err.
Background 0 NA
Beta(l) 0.00122482 0.000276934
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-41 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model Log(likelihood) Deviance Test DF
Full model -33.5379
P-value
Fitted model -33.9229 0.770003 4 0.
9424
Reduced model -57.0522 47.0286 4 <.0001
AIC: 69.8459
Dose
i: 1
0.0000
i: 2
330.0000
i: 3
800.0000
i: 4
1200.0000
i: 5
1800.0000
Chi -square =
Goodness of Fit
Est . Prob . Expected Observed Size Chi^2 Res.
0.0000 0.000 0 26
0.3325 6.317 6 19 -
0.6246 10.619 12 17
0.7700 10.780 10 14
0.8897 7.118 7 8 -
0.77 DF = 4 P-value = 0.9430
0.000
0.075
0.347
0.315
0.150
Benchmark Dose Computation
Specified effect = 0.05
Risk Type
Extra risk
Confidence level = 0.95
BMD = 41.8783
BMDL = 31.3527
1 Multisl
|0.6
§0.4
"-i— »
o
E
£0.2
: T
°EWIDL
0
Multistage Model with 0.95 Confidence Level
'^ ^i ^\
cage
A
. i
r
BMD
500 1000 1500
dose
14:4708/102004
B-42
DRAFT - DO NOT CITE OR QUOTE
-------
Logistic Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:20 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:43:19 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = I/[1+EXP(-intercept-slope*dose)]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Slope parameter is not restricted
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
background = 0 Specified
intercept = -2.53856
slope = 0.00272866
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
intercept slope
intercept 1 -0.81
slope -0.81 1
Parameter Estimates
Variable Estimate Std. Err.
intercept -2.23996 0.490016
slope 0.00303543 0.00064016
B-43 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.5379
-38.321
-57.0522
80.642
Deviance Test DF
9.56618
47.0286
P-value
0.02264
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est
0
0
0
0
0
. Prob.
.0962
.2247
.5470
.8026
.9617
Expect
2
4
9
11
7
;ed 01
.502
.270
.298
.236
.694
^served i
0
6
12
10
7
Size
26
19
17
14
8
Scaled
Residu
-1
0.
1
-0.
-1
al
.664
9508
.316
8301
.278
Chi-square =
7.73
DF = 3
P-value = 0.0520
Benchmark Dose Computation
Specified effect = 0.05
Risk Type = Extra risk
Confidence level = 0.95
BMD = 143.741
BMDL = 101.162
Logistic Model with 0.95 Confidence Level
.20.4
.
it 0.2
0
Logistic
BMDL
BMP
0 500
14:4308/102004
1000
dose
1500
B-44
DRAFT - DO NOT CITE OR QUOTE
-------
log Probit Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:53 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:50:58 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = Background
+ (1-Background) * CumNorm(Intercept+Slope*Log(Dose)
where CumNorm(.) is the cumulative normal distribution function
Dependent variable = COLUMNS
Independent variable = COLUMN1
Slope parameter is not restricted
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
User has chosen the log transformed model
Default Initial (and Specified) Parameter Values
background = 0
intercept = -5.72134
slope = 0.911264
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
intercept slope
intercept 1 -1
slope -1 1
Parameter Estimates
Variable Estimate Std. Err.
background 0 NA
intercept -5.71203 1.93477
slope 0.909892 0.294137
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-45 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model Log(likelihood) Deviance Test DF
Full model -33.5379
P-value
Fitted
Reduced
Dose
0.0000
330.0000
800.0000
1200.0000
1800.0000
model
model
AIC:
Est
0
0
0
0
0
-
Goo
. Prob.
.0000
.3316
.6444
.7701
.8661
-33.813
57.0522
71.6259
dness of
Expect
0.
6.
10.
10.
6.
0
Fit
;ed
.000
.301
.955
.781
.929
.550064
47.0286
Observed
0
6
12
10
7
3 0.9078
4 <.0001
Scaled
Size Residual
26 0
19 -0.1464
17 0.5296
14 -0.4963
8 0.07399
Chi-square =
0.55
DF = 3
P-value = 0.9069
Benchmark Dose Computation
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
0.05
Extra risk
0.95
87.3528
8.59815
Probit Model with 0.95 Confidence Level
£0.6
<
00.4
CO
0.2
0
Probit
BMDL BMP
0 500
14:5008/102004
1000
dose
1500
B-46
DRAFT - DO NOT CITE OR QUOTE
-------
Probit Model $Revision: 2.1 $ $Date: 2000/02/26 03:38:53 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:52:38 2004
BMDS MODEL RUN
The form of the probability function is:
P [response] = CumNorm(Intercept+Slope*Dose) ,
where CumNorm(.) is the cumulative normal distribution function
Dependent variable = COLUMNS
Independent variable = COLUMN1
Slope parameter is not restricted
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
background = 0 Specified
intercept = -1.84332
Slope = 0.00207787
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
intercept slope
intercept 1 -0.8
slope -0.8 1
Parameter Estimates
Variable Estimate Std. Err.
intercept -1.34013 0.270743
slope 0.00175814 0.000331975
B-47 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.5379
-38.3284
-57.0522
80.6568
Deviance Test DF
9.58089
47.0286
P-value
0.02249
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est
0
0
0
0
0
. Prob.
.0901
.2236
.5265
.7792
.9660
Expect
2
4
8
10
7
;ed 01
.343
.249
.950
.909
.728
^served i
0
6
12
10
7
£
Size I
26
19
17
14
8
Jcaled
Residual
-1.605
0.9639
1.482
-0.586
-1.419
Chi-square =
DF = 3
P-value = 0.0449
Benchmark Dose Computation
Specified effect = 0.05
Risk Type = Extra risk
Confidence level = 0.95
BMD = 136.4
BMDL = 98.798
Probit Model with 0.95 Confidence Level
•
£0.6
•20.4
ca
LH0.2
0
Probit
BMDL BMD
0 500
14:5208/102004
1000
dose
1500
B-48
DRAFT - DO NOT CITE OR QUOTE
-------
Quantal Linear Model $Revision: 2.2 $ $Date: 2000/03/17 22:27:16 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:54:57 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*dose)]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0185185
Slope = 0.000985037
Power = 1 Specified
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background -Power
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Slope
Slope 1
Parameter Estimates
Variable Estimate Std. Err.
Background 0 NA
Slope 0.00122482 0.000223165
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-49 DRAFT - DO NOT CITE OR QUOTE
-------
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood) Deviance Test DF
-33.5379
-33.9229 0.770003 4
-57.0522 47.0286 4
69.8459
P-value
0.9424
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est .
0.
0.
0.
0.
0.
. Prob.
.0000
.3325
.6246
.7700
.8897
Expect
0.
6.
10.
10.
7.
;ed 01
.000
.317
.619
.780
.118
^served i
0
6
12
10
7
Size
26
19
17
14
8
Scalec
Residi
-0
0
-0
-0
1
lal
0
.1545
.6918
.4956
.1329
Chi-square =
0.77
DF = 4
P-value = 0.9430
Benchmark Dose Computation
Specified effect = 0.05
Risk Type = Extra risk
Confidence level = 0.95
BMD = 41.8783
BMDL = 31.3527
Quantal Linear Model with 0.95 Confidence Level
Quantal Linear
£0.6
<
00.4
t>
CO
it 0.2
0
BMDLBMP
0 500
14:5408/102004
1000
dose
1500
B-50
DRAFT - DO NOT CITE OR QUOTE
-------
Quantal Quadratic Model $Revision: 2.2 $ $Date: 2000/03/17 22:27:16 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:55:51 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*dose^2)]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0185185
Slope = 5.472436-007
Power = 2 Specified
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Power
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Background
Background 1
Slope -0.64
Slope
-0.64
1
Variable
Background
Slope
Parameter Estimates
Estimate
0.016097
1.227746-006
Std. Err.
0.0753872
3.1613e-007
B-51
DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.5379
-38.4501
-57.0522
80.9002
Deviance Test DF
9.82436
47.0286
P-value
0.02012
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
)ose
.0000
.0000
.0000
.0000
.0000
Est .
0.
0.
0.
0.
0.
. Prob.
.0161
.1392
.5516
.8321
.9816
Expect
0
2
9
11
7
;ed 01
.419
.645
.377
.649
.853
^served i
0
6
12
10
7
Size
26
19
17
14
8
Scaled
Residual
-0.6522
2.223
1.279
-1.179
-2.242
Chi-square =
13.42
DF = 3
P-value = 0.0038
Benchmark Dose Computation
Specified effect = 0.05
Risk Type = Extra risk
Confidence level = 0.95
BMD = 204.398
BMDL = 172.459
Quantal Quadratic Model with 0.95 Confidence Level
Quanta! Quadratic
2 0-8
10.6
.20.4
rt0
0.2
0
BMDL BMP
0 500
14:5508/102004
1000
dose
1500
B-52
DRAFT - DO NOT CITE OR QUOTE
-------
Weibull Model $Revision: 2.2 $ $Date: 2000/03/17 22:27:16 $
Input Data File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.(d)
Gnuplot Plotting File: C:\BMDS\DINP\TCAA_SMITH_LEVOCARDIA.plt
Tue Aug 10 14:57:55 2004
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*dose^power)]
Dependent variable = COLUMNS
Independent variable = COLUMN1
Power parameter is not restricted
Total number of observations = 5
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0185185
Slope = 0.0025741
Power = 0.871847
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Slope Power
Slope 1 -1
Power -1 1
Parameter Estimates
Variable Estimate Std. Err.
Background 0 NA
Slope 0.00172885 0.00372313
Power 0.949024 0.317666
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
B-53 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model Log(likelihood) Deviance Test DF
Full model -33.5379
P-value
Fitted
Reduced
Dose
0.0000
330.0000
800.0000
1200.0000
1800.0000
model
model
AIC:
Est
0
0
0
0
0
-33.
-57.
71.
Goodne
. Prob.
.0000
.3459
.6261
.7643
.8804
.9102
.0522
.8203
3SS Of
Expect
0.
6.
10.
10.
7.
Fit
;ed
.000
.572
.643
.701
.043
0.74446
47.0286
Observed
0
6
12
10
7
3 0.8627
4 <.0001
Scaled
Size Residual
26 0
19 -0.276
17 0.6801
14 -0.4413
8 -0.04715
Chi-square =
0.74
DF = 3
P-value = 0.8648
Benchmark Dose Computation
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
0.05
Extra risk
0.95
35.5948
1.01863
Weibull Model with 0.95 Confidence Level
Weibull
0.6
<
.§0.4
CO
0.2
0
BMDL
BMP
0 500
14:5708/102004
1000
dose
1500
B-54
DRAFT - DO NOT CITE OR QUOTE
-------
APPENDIX C
MODELING OF LIVER TUMOR INCIDENCE DATA FOR MICE EXPOSED TO
TRICHLOROACETIC ACID IN DRINKING WATER
Using the U.S. EPA Benchmark Dose Software (BMDS, version 1.4.1), the multistage
model was fit to liver tumor incidence data (i.e., adenomas and carcinomas combined) from
bioassays in B6C3Fi mice exposed to TCA in drinking water for 52 weeks (two studies in male
mice: Bull et al., 2002, 1990), 60 weeks (one study in male mice: DeAngelo et al., 2007), 82
weeks (one study in female mice: Pereira, 1996), and 104 weeks (one study in male mice:
DeAngelo et al., 2007). The tumor incidence data for adenomas, carcinomas, and adenomas and
carcinomas combined are shown in Tables 5-5, 5-6, 5-7, 5-8, and 5-9 in Section 5.3.2.
Average daily intakes from these mouse studies were converted to human equivalent
doses for continuous lifetime exposure using an interspecies scaling factor of 0.15 ([male
B6C3Fi mouse reference body weight/human reference body weight]0'25 = [0.0373/70]0'25 = 0.15)
(U.S. EPA, 1992, 1988) and exposure duration scaling factors of 0.132, 0.203, or 0.520 to adjust
the 52-, 60-, or 82-week doses, respectively, to equivalent lifetime exposures ([duration of
experiment/duration of life]3 = [52/102]3 = 0.132 or = [60/102]3= 0.203 or [82/102]3= 0.520).
These factors for adjusting to lifetime equivalent doses are based on the assumption that the age-
specific rate for cancer in humans will increase by at least the third power of age (U.S. EPA,
1980). An exposure duration scaling factor was not used in converting animal doses to human
equivalents in the 104-week study of DeAngelo et al. (2007) because 104 weeks represents a
lifetime exposure in mice.
Individual animal data (specifying when tumors were detected in each animal with a liver
tumor) from the five bioassays were not available, precluding application of more sophisticated
approaches to estimating lifetime cancer risks (e.g., by fitting models that predict tumor
incidence as a function of two explanatory variables, dose and time). The multistage model was
restricted to two stages or less for the 52-week Bull et al. (2002, 1990) and the 104-week
DeAngelo et al. (2007) data sets employing three dose groups (including controls) and to three
stages or less for the 82-week Pereira (1996) and the 60-week DeAngelo et al. (2007) data sets
employing four dose groups (including controls). For each of the five data sets, the one-stage
multistage model provided the best fit to the data as determined by the chi-square goodness-of-fit
statistic and Akaike's Information Criterion (AIC). Model predictions compared with observed
incidences are shown in Figures C-l, C-2, C-3, C-4, and C-5 of this appendix.
C-l DRAFT - DO NOT CITE OR QUOTE
-------
Adequacy of model fit was evaluated for each of the data sets through use of the chi-
square goodness-of-fit statistic. The fitted model was used to estimate the human equivalent
lifetime dose associated with 10% extra risk (EDW\ and its corresponding 95% lower and upper
confidence limits (LEDio and UEDio, respectively). Candidate oral cancer slope factors were
derived by linear extrapolation from the LEDio, i.e., 0.1/LEDio, and their lower bounds were
derived by linear extrapolation from the UEDio, i.e., 0.1/UEDio.
The slope factors based on the tumor responses in male mice in the Bull et al. (2002,
1990) and DeAngelo et al. (2007) studies, and the tumor responses in female mice in the Pereira
(1996) study, ranged from 2 x 10"2 to 2 x 10"1 per mg/kg-day (Table 5-10). The four slope
factors derived from male mice varied by less than four-fold.
The standard output from BMDS (version 1.4.1) is reproduced below for each of the five
datasets that were modeled.
C-2 DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
0.7
0.6
0.5
T3
CD
°'4
§ °-3
ta
CD
£ 0.2
0.1
Multistage
BMDU BMD
dose
08:56 06/27 2007
Figure C-l. Observed and predicted combined incidences of hepatocellular
adenomas and carcinomas, based on responses in male B6C3Fi mice exposed
to TCA in drinking water for 52 weeks.
Note: Doses on x-axis are human equivalent doses for lifetime exposure in units of mg/kg-day.
BMD and BMDL refer to ED10 and LED10, respectively.
Source: Bull et al. (2002).
C-3
DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
-------
0.8
0.7
0.6
!J=
< 0.4
g
"G n ^
ro u-°
0.2
0.1
0
Multistage Model with 0.95 Confidence Level
Multistage
BMDL
BMD
10
15
dose
09:08 06/27 2007
Figure C-3. Predicted and observed combined incidence of hepatocellular
adenomas and carcinomas, based on responses in male B6C3Fi mice exposed
to TCA in drinking water for 60 weeks.
Note: Doses on x-axis are human equivalent doses for lifetime exposure in units of mg/kg-day.
BMD and BMDL refer to ED10 and LED10, respectively.
Source: DeAngelo et al. (2007).
C-5
DRAFT - DO NOT CITE OR QUOTE
-------
a
ro
0.8
0.6
0.4
0.2
Multistage Model with 0.95 Confidence Level
Multistage
BMDL
BMP
10
20
30
dose
40
50
60
09:1406/272007
Figure C-4. Predicted and observed combined incidence of hepatocellular
adenomas and carcinomas, based on responses in female B6C3Fi mice
exposed to TCA in drinking water for 82 weeks.
Note: Doses on x-axis are human equivalent doses for lifetime exposure in units of mg/kg-day.
BMD and BMDL refer to ED10 and LED10, respectively.
Source: Pereira(1996).
C-6
DRAFT - DO NOT CITE OR QUOTE
-------
0.9
0
ta
0
g
0.7
0.6
0.5
0.4
Multistage
BMP
0 1
09:37 06/27 2007
Multistage Model with 0.95 Confidence Level
4 5
dose
8
Figure C-5. Predicted and observed combined incidence of hepatocellular adenomas and
carcinomas, based on responses in male B6C3Fi mice exposed to TCA in drinking water
for 104 weeks.
Note: Doses on x-axis are human equivalent doses for lifetime exposure in units of mg/kg-day. BMD and BMDL
refer to ED10 and LED10, respectively.
Source: DeAngelo et al. (2007).
C-7
DRAFT - DO NOT CITE OR QUOTE
-------
BMDS Outputs
Bull et al. (2002)
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*doseAl)]
The parameter betas are restricted to be positive
Dependent variable = Response
Independent variable = Dose
Total number of observations = 3
Total number of records with missing values = 0
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.100138
Beta(l) = 0.046377
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Beta(l)
Beta(l) 1
Parameter Estimates
95.0% Wald Confidence
Interval
Variable Estimate Std. Err. Lower Conf. Limit
Upper Conf. Limit
Background 0 * *
*
Beta(l) 0.0745471 * *
*
* - Indicates that this value is not calculated.
C-8 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-25.6775
-27.3086
-32.5964
56.6172
# Param's
3
1
1
Deviance Test d.f.
3.26212
13.8377
P-value
0.1957
0.000989
Dose
Est. Prob.
Goodness of Fit
Expected Observed Size
Scaled
Residual
0.0000
2.3800
9.5000
ChiA2 = 3.70
0.0000
0.1626
5075
0
0.000
3.251
10.149
d.f. = 2
P-value = 0.1573
20
20
20
0.000
1.666
-0.961
Benchmark Dose Computation
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
BMDU =
0.1
Extra risk
0.95
1.41334
0.932428
2.78979
Taken together, (0.932428, 2.78979) is a 90
interval for the BMD
% two-sided confidence
Bull et al. (1990)
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*doseAl)]
The parameter betas are restricted to be positive
Dependent variable = Response
Independent variable = Dose
Total number of observations = 3
C-9
DRAFT - DO NOT CITE OR QUOTE
-------
Total number of records with missing values
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
= 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.105918
Beta(l) = 0.0358328
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background
have been estimated at a boundary point, or have been
specified by the user,
and do not appear in the correlation matrix )
Beta(l)
Beta(l)
Parameter Estimates
Interval
Variable
Upper Conf. Limit
Background
*
Beta(1)
Estimate
0
0.053545
Std. Err.
95.0% Wald Confidence
Lower Conf. Limit
* - Indicates that this value is not calculated.
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-19.4921
-21.2941
-26.8563
44.5881
# Param's
3
1
1
Deviance
3.604
14.7286
Test d.f.
2
2
P-value
0.165
0.0006335
C-10
DRAFT - DO NOT CITE OR QUOTE
-------
Goodness of Fit
Scaled
Dose Est. Prob. Expected Observed Size Residual
0.0000 0.0000 0.000 0 35 0.000
3.2500 0.1597 1.757 4 11 1.846
6.5100 0.2943 7.063 5 24 -0.924
ChiA2 = 4.26 d.f. = 2 P-value = 0.1187
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 1.9677
BMDL = 1.18795
BMDU = 3.61033
Taken together, (1.18795, 3.61033) is a 90 % two-sided confidence
interval for the BMD
DeAngelo et al (2008) (60 weeks)
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*doseAl)]
The parameter betas are restricted to be positive
Dependent variable = Response
Independent variable = Dose
Total number of observations = 4
Total number of records with missing values = 0
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
C-11 DRAFT - DO NOT CITE OR QUOTE
-------
Default Initial Parameter Values
Background = 0.204406
Beta(l) = 0.0324139
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background 1 -0.5
Beta(l) -0.5 1
Interval
Variable
Upper Conf. Limit
Background
*
Beta(l)
Parameter Estimates
Estimate
0.183783
0.0372004
Std. Err.
95.0% Wald Confidence
Lower Conf. Limit
* - Indicates that this value is not calculated.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-62.3001
-64.1175
-70.6679
# Param's
4
2
1
Deviance Test d.f.
3.63465
16.7355
P-value
0.1625
0.000801
Goodness of Fit
Dose
0.0000
0.2400
2.0700
18.3000
Est. Prob.
0.1838
0.1910
0.2443
0.5868
Expected
5.514
5.158
7.084
17.017
Observed
4
4
11
16
Size
30
27
29
29
Scaled
Residual
-0.713
-0.567
1.692
-0.384
ChiA2 = 3.84
d.f. =2
P-value = 0.1465
C-12
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 2.83224
BMDL = 1.70985
BMDU = 5.86213
Taken together, (1.70985, 5.86213) is a 90 % two-sided confidence
interval for the BMD
Pereira (1996)
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*doseAl)]
The parameter betas are restricted to be positive
Dependent variable = Response
Independent variable = Dose
Total number of observations = 4
Total number of records with missing values = 0
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.00433121
Beta(l) = 0.0177692
C-13 DRAFT - DO NOT CITE OR QUOTE
-------
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background 1 -0.43
Beta(l) -0.43 1
Parameter Estimates
Interval
Variable
Upper Conf. Limit
Background
*
Beta(l)
Estimate
0.0373114
0.0147581
Std. Err.
95.0% Wald Confidence
Lower Conf. Limit
- Indicates that this value is not calculated.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-58.4099
-59.1702
-79.1216
122.34
# Param's
4
2
1
Deviance Test d.f.
1.52058
41.4233
P-value
0.4675
<.0001
Goodness of Fit
Dose
0.0000
6.1000
20.4000
61.1000
Est. Prob.
0.0373
0.1202
0.2876
0.6093
Expected
3.358
6.370
7.765
10.967
Observed
4
4
8
12
Size
90
53
27
18
Scaled
Residual
0.357
-1.001
0.100
0.499
ChiA2 = 1.39
d.f. =2
P-value = 0.4994
C-14
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 7 . 13914
BMDL = 4.96187
BMDU = 11.0023
Taken together, (4.96187, 11.0023) is a 90 % two-sided confidence
interval for the BMD
DeAngelo et al (2008) (104 weeks)
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*doseAl)]
The parameter betas are restricted to be positive
Dependent variable = Response
Independent variable = Dose
Total number of observations = 3
Total number of records with missing values = 0
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.590554
Beta(l) = 0.125738
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background 1 -0.47
Beta(l) -0.47 1
C-15 DRAFT - DO NOT CITE OR QUOTE
-------
Parameter Estimates
Interval
Variable
Upper Conf. Limit
Background
*
Beta (1)
Estimate
0.597398
0.118941
Std. Err.
95.0% Wald Confidence
Lower Conf. Limit
* - Indicates that this value is not calculated.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-65.9288
-66.4266
-70.3031
136.853
# Param's
3
2
1
Deviance Test d.f.
0.995585
8.74855
P-value
0.3184
0.0126
Dose
Est. Prob.
Goodness of Fit
Expected Observed Size
Scaled
Residual
0.0000
0.8400
8.7000
ChiA2 = 1.00
0.5974
0.6357
0.8570
d.f. =1
25.091 27 42
22.249 20 35
31.707 32 37
P-value = 0.3164
0.601
-0.790
0.137
Benchmark Dose Computation
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
BMDU =
0.1
Extra risk
0.95
0.885825
0.496499
2.36969
Taken together, (0.496499, 2.36969) is a 90
interval for the BMD
% two-sided confidence
C-16
DRAFT - DO NOT CITE OR QUOTE
-------
APPENDIX D
BMD modeling of the incidence of hepatocellular cytoplasmic alterations, hepatocellular
inflammation, hepatocellular necrosis, and testicular tubular degeneration in mice exposed
to TCA in drinking water for use in derivation of the reference dose
Table D-l.l. Benchmark dose modeling results based on incidence of
hepatocellular cytoplasmic alterations in male B6C3Fi mice exposed to
TCA in drinking water for 60 weeks (DeAngelo et al., 2008)
Fitted
Dichotomous
Model3
Gamma
Logistic
Log-Logistic
Multistage (2°)
Probit
Log-Probit
Weibull
Chi-Square
Goodness-of-Fit
Test/>-Valueb
0.0002
0.0005
0.0002
0.0009
0.0005
0.0002
0.0002
AICC
116.16
115.06
116.16
114.5
115.03
116.16
116.16
BMD10d
(mg/kg-day)
286.4
65.9
350.8
126.9
66.1
249.6
398.2
BMDL10e
(mg/kg-day)
34.9
47.2
49.7
28.0
50.3
53.4
33.0
Footnotes:
a All dichotomous dose-response models were fit using BMDS, Version 1.4.1. Note that all
models fitted exhibited a statistically significant (p < 0.1) lack of fit.
b />-Value from the chi-square goodness-of-fit test for the selected model. Values < 0.1 suggest
that the model exhibits a significant lack of fit, and a different model should be chosen.
0 AIC = Akaike's Information Criterion, a value useful for evaluating model fit. For those
models exhibiting adequate fit, lower values of the AIC suggest better model fit.
d BMD10 = Benchmark dose at 10% extra risk.
e BMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
All of the fitted models exhibited statistically significant lack of fit and thus were unsuitable for
use in indentifying a POD.
D-l
DRAFT - DO NOT CITE OR QUOTE
-------
Table D-1.2. Benchmark dose modeling results based on incidence of
hepatocellular inflammation in male B6C3Fi mice exposed to TCA in
drinking water for 60 weeks (DeAngelo et al., 2008)
Fitted
Dichotomous
Model3
Gamma
Logistic
Log-Logistic
Multistage (1°)
Probit
Log-Probit
Weibull
Chi-Square
Goodness-of-Fit
Test/>-Valueb
0.096
0.24
0.096
0.22
0.24
0.26
0.096
AICC
76.15
74.19
76.16
74.29
74.20
74.19
76.16
BMD10d
(mg/kg-day)
354.2
391.9
351.0
292.0
376.1
394.1
361.9
BMDL10e
(mg/kg-day)
151.6
276.6
132.1
149.4
257.1
244.4
151.6
Footnotes:
a All dichotomous dose-response models were fit using BMDS, Version 1.4.1. The "best-fit"
models are indicated in boldface type.
b />-Value from the chi-square goodness-of-fit test for the selected model. Values < 0.1 suggest
that the model exhibits a significant lack of fit, and a different model should be chosen.
0 AIC = Akaike's Information Criterion, a value useful for evaluating model fit. For those
models exhibiting adequate fit, lower values of the AIC suggest better model fit.
d BMD10 = Benchmark dose at 10% extra risk.
e BMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
Of the seven models fitted, four (i.e., logistic, one-stage multistage, probit, and log-probit)
showed adequate fit, and thus the BMDS outputs from these four models are provided below.
D-2
DRAFT - DO NOT CITE OR QUOTE
-------
Logistic Model with 0.95 Confidence Level
ta
ro
0.4
0.3
0.2
0.1
Logistic
BMD
tL
100
200
300
dose
400
500
600
12:0709/052008
Logistic Model. (Version: 2.10; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 12:07:17 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = I/[1+EXP(-intercept-slope*dose)]
Dependent variable = Response
Independent variable = Dose
Slope parameter is not restricted
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
background = 0 Specified
intercept = -2.90541
slope = 0.00303299
D-3
DRAFT - DO NOT CITE OR QUOTE
-------
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been specified by the user,
and do not appear in the correlation matrix )
intercept
intercept 1
slope -0.76
slope
-0.76
1
Variable
intercept
slope
Parameter Estimates
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.0575
-35.0966
-38.4712
74.1932
# Param' s
4
2
1
Deviance
4.07833
10.8276
Test d.f.
2
3
P-value
0.1301
0.0127
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0542
0.0554
0.0650
0.2411
Expected
1.626
1.495
1.886
6.993
Observed
3
0
2
7
Size
30
27
29
29
Scaled
Residual
1.108
-1.258
0.086
0.003
ChiA2 =2.82
d.f. =2
P-value = 0.2444
D-4
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 391.918
BMDL = 276.646
D-5 DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
ta
£
§
ta
ro
0.4
0.3
0.2
0.1
Multistage
BMD
piyip
100
200
300
dose
400
500
600
12:11 09/052008
Multistage Model. (Version: 2.8; Date: 02/20/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALEjyiOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 12:11:21 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*doseAl)]
The parameter betas are restricted to be positive
Dependent variable = Response
Independent variable = Dose
Total number of observations = 4
Total number of records with missing values
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
= 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
D-6
DRAFT - DO NOT CITE OR QUOTE
-------
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.0486161
Beta(l) = 0.000374222
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background 1 -0.52
Beta(l) -0.52 1
Parameter Estimates
Std. Err.
Indicates that this value is not calculated.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-33.0575
-35.1449
-38.4712
74.2898
# Param's
4
2
1
Deviance
4.17486
10.8276
Test d.f.
2
3
P-value
0.124
0.0127
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0513
0.0540
0.0743
0.2365
Expected
1.539
1.459
2.154
6.860
Observed
3
0
2
7
Size
30
27
29
29
Scaled
Residual
1.209
-1.242
-0.109
0.061
ChiA2 =3.02
d.f. =2
P-value = 0.2209
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 291.976
BMDL = 149.431
D-7
DRAFT - DO NOT CITE OR QUOTE
-------
BMDU = 928.712
Taken together, (149.431, 928.712) is a 90 % two-sided confidence
interval for the BMD
D-8 DRAFT - DO NOT CITE OR QUOTE
-------
Probit Model with 0.95 Confidence Level
0.4
H °-3
1
§ 0.2
ta
ro
0.1
Probit
BMD
100
200
300
dose
400
500
600
12:1309/052008
Probit Model. (Version: 2.9; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALEjyiOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 12:13:23 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = CumNorm(Intercept+Slope*Dose) ,
where CumNorm(.) is the cumulative normal distribution function
Dependent variable = Response
Independent variable = Dose
Slope parameter is not restricted
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
D-9 DRAFT - DO NOT CITE OR QUOTE
-------
background =
intercept =
slope =
0 Specified
-1.7688
0.0018081
Asymptotic Correlation Matrix of Parameter Estimates
intercept
slope
intercept
1
-0.69
slope
-0.69
1
Model
Full model
Fitted model
Reduced model
Analysis of Deviance Table
Log(likelihood)
-33.0575
-35.0988
-38.4712
# Param' s
4
2
1
Deviance
4.08263
10.8276
Test d.f.
2
3
P-value
0.1299
0.0127
AIC:
74.1975
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0538
0.0551
0.0659
0.2409
Expected
1.613
1.488
1.912
6.987
Observed
3
0
2
7
Size
30
27
29
29
Scaled
Residual
1.122
-1.255
0.066
0.005
ChiA2 =2.84
d.f. = 2
P-value = 0.2419
D-10
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 376.053
BMDL = 257.089
D-l 1 DRAFT - DO NOT CITE OR QUOTE
-------
Probit Model with 0.95 Confidence Level
0.4
"8 0.3
1
§ 0.2
t3
CO
LL
0.1
0
12:14(
rTODIt
i _
\ T - -4
^^-—
: F "t :---T x ;
; ^L 1 ;
0 100 200 300 400 500 600
dose
D9/05 2008
Probit Model. (Version: 2.9; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALEjyiOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 12:14:41 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = Background
+ (1-Background) * CumNorm(Intercept+Slope*Log(Dose) ) ,
where CumNorm(.) is the cumulative normal distribution function
Dependent variable = Response
Independent variable = Dose
Slope parameter is restricted as slope >= 1
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
User has chosen the log transformed model
D-12 DRAFT - DO NOT CITE OR QUOTE
-------
Default Initial (and Specified) Parameter Values
background = 0.1
intercept = -7.0776
slope = 1
Asymptotic Correlation Matrix of Parameter Estimates
background intercept
background 1 -0.26
intercept -0.26 1
Parameter Estimates
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.0575
-35.0974
-38.4712
74.1948
# Param's
4
2
1
Deviance Test d.f.
P-value
4.07991
10.8276
0.13
0.0127
D-13
DRAFT - DO NOT CITE OR QUOTE
-------
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0577
0.0577
0.0588
0.2419
Expected
1.730
1.557
1.705
7.014
Observed
3
0
2
7
Size
30
27
29
29
Scaled
Residual
0.995
-1.285
0.233
-0.006
ChiA2 = 2.70 d.f. = 2 P-value = 0.2597
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 394.098
BMDL = 244.412
D-14 DRAFT - DO NOT CITE OR QUOTE
-------
Table D-1.3. Benchmark dose modeling results based on incidence of
hepatocellular necrosis in male B6C3Fi mice exposed to TCA in drinking
water for 30 to 45 weeks (DeAngelo et al., 2008)
Fitted
Dichotomous
Model3
Gamma
Logistic
Log-Logistic
Multistage (1°)
Probit
Log-Probit
Weibull
Chi-Square
Goodness-of-Fit
Test/>-Valueb
0.18
0.058
0.49
0.18
0.060
0.036
0.18
AICC
31.85
36.39
30.42
31.85
36.26
36.84
31.85
BMD10d
(mg/kg-day)
64.9
205.1
40.7
64.9
188.0
158.7
64.9
BMDL10e
(mg/kg-day)
37.6
128.4
17.9
37.6
120.0
54.3
37.6
Footnotes:
a All dichotomous dose-response models were fit using BMDS, Version 1.4.1. The "best-fit"
model is indicated in boldface type.
b />-Value from the chi-square goodness-of-fit test for the selected model. Values < 0.1 suggest
that the model exhibits a significant lack of fit, and a different model should be chosen.
0 AIC = Akaike's Information Criterion, a value useful for evaluating model fit. For those
models exhibiting adequate fit, lower values of the AIC suggest better model fit.
d BMD10 = Benchmark dose at 10% extra risk.
e BMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
Of the seven models fitted, four (i.e., gamma, log-logistic, one-stage multistage, and Weibull)
showed adequate fit, and thus the BMDS outputs from these four models are provided below.
D-15
DRAFT - DO NOT CITE OR QUOTE
-------
Gamma Multi-Hit Model with 0.95 Confidence Level
T3
•Q
0
it
C
O
ta
LL
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
\ Gamrric
i Multi-Hit
r -•- ~.
~- I ;
I T „_ — ;
L
^
^^^^^ o ~~-
^^-~~~^~^ ;
^^^^
: ^^ I ^^~~ :
f =1
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0454545
Slope = 0.00722137
D-16
DRAFT - DO NOT CITE OR QUOTE
-------
Power =
1.3
Asymptotic Correlation Matrix of Parameter Estimates
Slope
Slope
1
Variable
Background
Slope
Power
95.0% Wald Confidence Interval
Lower Conf. Limit Upper Conf. Limit
Model
Full model
Fitted model
Reduced model
Analysis of Deviance Table
Log(likelihood)
-13.0401
-14.925
-20.0161
# Param's
4
1
1
Deviance Test d.f.
3.76969
13.952
P-value
0.2874
0.002971
AIC:
31.8499
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0000
0.0129
0.1045
0.6235
Expected
0.000
0.129
1.045
6.235
Observed
0
0
3
5
Size
10
10
10
10
Scaled
Residual
0.000
-0.361
2.021
-0.806
ChiA2 =4.87
d.f. =3
P-value = 0.1818
D-17
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 64.9271
BMDL = 37.5509
D-18 DRAFT - DO NOT CITE OR QUOTE
-------
Log-Logistic Model with 0.95 Confidence Level
T3
0
ro
0.8
0.7 :
0.6 \
0.4
0.3
0.2 ':
0.1
0
Log-Logisti
BMD,
100
200
300
dose
400
500
600
14:21 09/052008
Logistic Model. (Version: 2.10; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_HEPATOCELLULAR_NECROSIS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_HEPATOCELLULAR_NECROSIS_DEANGELO_2008.pit
Fri Sep 05 14:21:36 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = background+(1-background)/[1+EXP(-intercept-siope*Log(dose) ) ]
Dependent variable = Response
Independent variable = Dose
Slope parameter is restricted as slope >= 1
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
User has chosen the log transformed model
Default Initial Parameter Values
D-19 DRAFT - DO NOT CITE OR QUOTE
-------
background =
intercept =
slope =
-5.96722
1
Asymptotic Correlation Matrix of Parameter Estimates
intercept
intercept
1
Variable
background
intercept
slope
Estimate
0
-5.90256
1
Parameter Estimates
Std. Err.
95.0% Wald Confidence Interval
Lower Conf. Limit Upper Conf. Limit
Indicates that this value is not calculated.
Model
Full model
Fitted model
Reduced model
Analysis of Deviance Table
Log(likelihood)
-13.0401
-14.2076
-20.0161
# Param' s
4
1
1
Deviance
2.33493
13.952
Test d.f.
3
3
P-value
0.5059
0.002971
AIC:
30.4152
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0000
0.0214
0.1567
0.6219
Expected
0.000
0.214
1.567
6.219
Observed
0
0
3
5
Size
10
10
10
10
Scaled
Residual
0.000
-0.468
1.247
-0.795
ChiA2 =2.40
d.f. =3
P-value = 0.4927
D-20
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 40.6639
BMDL = 17.8767
D-21 DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
T3
•Q
0
it
C
O
ta
LL
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
o
\ Multista
fiQ
9e ;
~- i ;
I T „_ — ;
L
^
^^^^^ o ^
^^-~~~^~^ ;
^^^^
: ^^ I ^^~~ :
f
-------
Default Initial Parameter Values
Background = 0.0817489
Beta(l) = 0.00104526
Asymptotic Correlation Matrix of Parameter Estimates
Beta(l)
Beta (1)
Variable
Background
Beta(1)
Std. Err.
95.0% Wald Confidence Interval
Lower Conf. Limit Upper Conf. Limit
Model
Full model
Fitted model
Reduced model
Analysis of Deviance Table
Log(likelihood)
-13.0401
-14.925
-20.0161
# Param' s
4
1
1
Deviance
3.76969
13.952
Test d.f.
3
3
P-value
0.2874
0.002971
AIC:
31.8499
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0000
0.0129
0.1045
0.6235
Expected
0.000
0.129
1.045
6.235
Observed
0
0
3
5
Size
10
10
10
10
Scaled
Residual
0.000
-0.361
2.021
-0.806
ChiA2 =4.87
d.f. = 3
P-value = 0.1818
D-23
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 64.9271
BMDL = 37.5509
BMDU = 167.542
Taken together, (37.5509, 167.542) is a 90 % two-sided confidence
interval for the BMD
D-24 DRAFT - DO NOT CITE OR QUOTE
-------
Weibull Model with 0.95 Confidence Level
T3
•Q
0
it
<£
C
O
ta
LL
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
! Weibull
r -T- ~.
~- I ;
I T „_ — ;
L
~~
^^^^^ o ^
^^-~~~^~^ ;
^^^^^ j
: ^^ I ,-^ :
f =1
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0454545
Slope = 0.00107413
Power = 1
D-25
DRAFT - DO NOT CITE OR QUOTE
-------
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background -Power
have been estimated at a boundary point, or have been specified by the user,
and do not appear in the correlation matrix )
Slope
Slope 1
95.0% Wald Confidence Interval
Lower Conf. Limit Upper Conf. Limit
Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
Model
Full model
Fitted model
Reduced model
Analysis of Deviance Table
Log(likelihood)
-13.0401
-14.925
-20.0161
# Param's
4
1
1
Deviance
3.76969
13.952
Test d.f.
3
3
P-value
0.2874
0.002971
AIC:
31.8499
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0000
0.0129
0.1045
0.6235
Expected
0.000
0.129
1.045
6.235
Observed
0
0
3
5
Size
10
10
10
10
Scaled
Residual
0.000
-0.361
2.021
-0.806
ChiA2 =4.87
d.f. =3
P-value = 0.1818
D-26
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 64.9271
BMDL = 37.5509
D-27 DRAFT - DO NOT CITE OR QUOTE
-------
Table D-1.4. Benchmark dose modeling results based on incidence of
testicular tubular degeneration in male B6C3Fi mice exposed to TCA in
drinking water for 60 weeks (DeAngelo et al., 2008)
Fitted
Dichotomous
Model3
Gamma
Logistic
Log-Logistic
Multistage (1°)
Probit
Log-Probit
Weibull
Chi-Square
Goodness-of-Fit
Test/>-Valueb
0.19
0.16
0.19
0.19
0.17
0.13
0.19
AICC
76.16
76.59
76.08
76.16
76.54
77.06
76.16
BMD10d
(mg/kg-day)
321.9
439.7
298.2
321.9
425.3
471.6
321.9
BMDL10e
(mg/kg-day)
153.3
290.3
127.4
153.3
271.2
276.8
153.3
Footnotes:
a All dichotomous dose-response models were fit using BMDS, Version 1.4.1. The "best-fit"
model is indicated in boldface type.
b />-Value from the chi-square goodness-of-fit test for the selected model. Values < 0.1 suggest
that the model exhibits a significant lack of fit, and a different model should be chosen.
0 AIC = Akaike's Information Criterion, a value useful for evaluating model fit. For those
models exhibiting adequate fit, lower values of the AIC suggest better model fit.
d BMD10 = Benchmark dose at 10% extra risk.
e BMDL10 = 95% lower confidence limit on the benchmark dose at 10% extra risk.
All seven models fitted showed adequate fit, and thus the BMDS outputs from these seven
models are provided below.
D-28
DRAFT - DO NOT CITE OR QUOTE
-------
Gamma Multi-Hit Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
| 0.2
g
| 0.15
LL
0.1
0.05
0
: oarnrna iviuiii-nii
r T 1
1 T ;
;T _^— ^^
L \^-^^^ 1 J
i j^^l ;
! BMDlJ BMD ;
0 100 200 300 400 500 600
dose
13:4709/052008
Gamma Model. (Version: 2.11; Date: 10/31/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 13:47:08 2008
HMDS MODEL RUN
The form of the probability function is:
P[response]= background+(1-background)*CumGamma[slope*dose,power],
where CumGamma(.) is the cummulative Gamma distribution function
Dependent variable = Response
Independent variable = Dose
Power parameter is restricted as power >=1
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0806452
Slope = 0.00135334
D-29
DRAFT - DO NOT CITE OR QUOTE
-------
Power =
1.3
Asymptotic Correlation Matrix of Parameter Estimates
Background
Slope
Background
1
-0.45
Slope
-0.45
1
Parameter Estimates
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.7671
-36.0814
-38.4712
76.1628
# Param's
4
2
1
Deviance
4.62871
9.40833
Test d.f.
2
3
P-value
0.09883
0.02433
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0556
0.0581
0.0764
0.2245
Expected
1.669
1.569
2.216
6.511
Observed
2
0
4
6
Size
30
27
29
29
Scaled
Residual
0.263
-1.291
1.247
-0.228
ChiA2 = 3.34
d.f. =2
P-value = 0.1882
D-30
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 321.919
BMDL = 153.274
D-31 DRAFT - DO NOT CITE OR QUOTE
-------
Logistic Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
| 0.2
g
| 0.15
LL
0.1
0.05
0
: ' . . . ' ' ' ' :
r T 1
I T ;
; T ^H> ;
r ll— -t^ — " — ^
! BMDLJ BMD ;
0 100 200 300 400 500 600
dose
13:4809/052008
Logistic Model. (Version: 2.10; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 13:48:30 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = I/[1+EXP(-intercept-slope*dose)]
Dependent variable = Response
Independent variable = Dose
Slope parameter is not restricted
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
background = 0 Specified
intercept = -2.82219
slope = 0.00269617
D-32
DRAFT - DO NOT CITE OR QUOTE
-------
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been specified by the user,
and do not appear in the correlation matrix )
intercept
intercept 1
slope -0.72
slope
-0.72
1
Variable
intercept
slope
Parameter Estimates
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.7671
-36.2929
-38.4712
76.5859
# Param' s
4
2
1
Deviance
5.05173
9.40833
Test d.f.
2
3
P-value
0.07999
0.02433
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0639
0.0650
0.0739
0.2133
Expected
1.917
1.755
2.142
6.187
Observed
2
0
4
6
Size
30
27
29
29
Scaled
Residual
0.062
-1.370
1.319
-0.085
ChiA2 =3.63
d.f. =2
P-value = 0.1630
D-33
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 439.685
BMDL = 290.255
D-34 DRAFT - DO NOT CITE OR QUOTE
-------
Log-Logistic Model with 0.95 Confidence Level
o
0.4
0.35
0.3
0.2
0.15
0.1
0.05
0
Log-Logistic
BlvD
P.MD
0
100
200
300
dose
400
500
600
13:5009/052008
Logistic Model. (Version: 2.10; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 13:50:29 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = background+(1-background)/[1+EXP(-intercept-siope*Log(dose) ) ]
Dependent variable = Response
Independent variable = Dose
Slope parameter is restricted as slope >= 1
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
User has chosen the log transformed model
Default Initial Parameter Values
D-3 5 DRAFT - DO NOT CITE OR QUOTE
-------
background =
intercept =
slope =
0.0666667
-7.67626
1
Asymptotic Correlation Matrix of Parameter Estimates
background intercept
background 1 -0.47
intercept -0.47 1
Indicates that this value is not calculated.
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.7671
-36.0406
-38.4712
76.0812
# Param's
4
2
1
Deviance
4.54705
9.40833
Test d.f.
2
3
P-value
0.1029
0.02433
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0541
0.0569
0.0775
0.2274
Expected
1.623
1.536
2.246
6.595
Observed
2
0
4
6
Size
30
27
29
29
Scaled
Residual
0.305
-1.276
1.218
-0.263
ChiA2 = 3.27
d.f. =2
P-value = 0.1945
D-36
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 298.169
BMDL = 127.35
D-37 DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
| 0.2
g
| 0.15
LL
0.1
0.05
0
: IvIUIlloldyt;
r T 1
~r ^
1 T ;
r ^^-^^
L ^l^--^^ 1 I
i j^^l ;
! BMDlJ BMD ;
0 100 200 300 400 500 600
dose
13:51 09/052008
Multistage Model. (Version: 2.8; Date: 02/20/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 13:51:55 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*doseAl)]
The parameter betas are restricted to be positive
Dependent variable = Response
Independent variable = Dose
Total number of observations = 4
Total number of records with missing values
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
= 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
D-38
DRAFT - DO NOT CITE OR QUOTE
-------
Default Initial Parameter Values
Background = 0.0609653
Beta(l) = 0.00029145
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background 1 -0.56
Beta(l) -0.56 1
Variable
Background
Beta(l)
Std. Err.
95.0% Wald Confidence Interval
Lower Conf. Limit Upper Conf. Limit
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.7671
-36.0814
-38.4712
76.1628
# Param's
4
2
1
Deviance
4.62871
9.40833
Test d.f.
2
3
P-value
0.09883
0.02433
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0556
0.0581
0.0764
0.2245
Expected
1.669
1.569
2.216
6.511
Observed
2
0
4
6
Size
30
27
29
29
Scaled
Residual
0.263
-1.291
1.247
-0.228
ChiA2 = 3.34
d.f. = 2
P-value = 0.1882
D-39
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 321.92
BMDL = 153.274
BMDU = 1517.45
Taken together, (153.274, 1517.45) is a 90 % two-sided confidence
interval for the BMD
D-40 DRAFT - DO NOT CITE OR QUOTE
-------
Probit Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
"G 0.25
< 0.2
g
§ 0.15
LL
0.1
0.05
0
E Drohiit :
r lODIl
r T 1
~r ^
1 T ;
: ' T -1- i :
; J>] — — " ^ ;
Mi ]
; M ;
! BMDlJ BMD ;
0 100 200 300 400 500 600
dose
13:5309/052008
Probit Model. (Version: 2.9; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 13:53:07 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = CumNorm(Intercept+Slope*Dose) ,
where CumNorm(.) is the cumulative normal distribution function
Dependent variable = Response
Independent variable = Dose
Slope parameter is not restricted
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
background = 0 Specified
D-41
DRAFT - DO NOT CITE OR QUOTE
-------
intercept = -1.72179
slope = 0.00160607
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
have been estimated at a boundary point, or have been specified by the user,
and do not appear in the correlation matrix )
intercept slope
intercept 1 -0.67
slope -0.67 1
Variable
intercept
slope
Analysis of Deviance Table
Model Log(likelihood) # Param's Deviance Test d.f. P-value
Full model -33.7671 4
Fitted model -36.2697 2 5.00537 2 0.08186
Reduced model -38.4712 1 9.40833 3 0.02433
AIC: 76.5395
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0631
0.0643
0.0741
0.2144
Expected
1.893
1.737
2.149
6.219
Observed
2
0
4
6
Size
30
27
29
29
Scaled
Residual
0.080
-1.362
1.312
-0.099
ChiA2 = 3.59 d.f. = 2 P-value = 0.1658
D-42 DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 425.313
BMDL = 271.161
D-43 DRAFT - DO NOT CITE OR QUOTE
-------
Probit Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
< 0.2
.0
1 0.15
s_
u_
0.1
0.05
0
: rTODIt :
f T 1
r \
L T ;
I T 4 \
r ^ J> ^^^-~^\ ;
; , ^^____^^--^^ 1 ;
: :
; BMDiJ BMP ;
0 100 200 300 400 500 600
dose
13:5409/052008
Probit Model. (Version: 2.9; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 13:54:25 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = Background
+ (1-Background) * CumNorm(Intercept+Slope*Log(Dose) ) ,
where CumNorm(.) is the cumulative normal distribution function
Dependent variable = Response
Independent variable = Dose
Slope parameter is restricted as slope >= 1
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
D-44
DRAFT - DO NOT CITE OR QUOTE
-------
User has chosen the log transformed model
Default Initial (and Specified) Parameter Values
background = 0.0666667
intercept = -6.86605
slope = 1
Asymptotic Correlation Matrix of Parameter Estimates
background
background
intercept
1
-0.31
intercept
-0.31
1
Variable
background
intercept
slope
95.0% Wald Confidence Interval
Lower Conf. Limit Upper Conf. Limit
0.0151099 0.12325
-8.16415 -6.71138
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.7671
-36.5279
-38.4712
77.0558
# Param' s
4
2
1
Deviance
5.52164
9.40833
Test d.f.
2
3
P-value
0.06324
0.02433
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0692
0.0692
0.0698
0.2086
Expected
2.075
1.868
2.024
6.049
Observed
2
0
4
6
Size
30
27
29
29
Scaled
Residual
-0.054
-1.417
1.440
-0.022
ChiA2 =4.09
d.f. =2
P-value = 0.1297
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
D-45
DRAFT - DO NOT CITE OR QUOTE
-------
BMD = 471.64
BMDL = 276.75
D-46 DRAFT - DO NOT CITE OR QUOTE
-------
Weibull Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
| 0.2
g
| 0.15
LL
0.1
0.05
0
E \A/nihi ill :
VVclUUM
r T 1
1 T ;
r _^— ^^
L \^-^^^ 1 J
i j^^l ;
! BMDlJ BMD ;
0 100 200 300 400 500 600
dose
13:5609/052008
Weibull Model using Weibull Model (Version: 2.10; Date: 10/31/2007;
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.pit
Fri Sep 05 13:56:04 2008
HMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*doseApower)]
Dependent variable = Response
Independent variable = Dose
Power parameter is restricted as power >=1
Total number of observations = 4
Total number of records with missing values = 0
Maximum number of iterations = 250
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial (and Specified) Parameter Values
Background = 0.0806452
Slope = 0.00026597
Power = 1
D-47
DRAFT - DO NOT CITE OR QUOTE
-------
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Power
have been estimated at a boundary point, or have been specified by the user,
and do not appear in the correlation matrix )
Background
Background 1
Slope -0.45
Slope
-0.45
1
Parameter Estimates
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-33.7671
-36.0814
-38.4712
76.1628
# Param's
4
2
1
Deviance Test d.f.
P-value
4.62871
9.40833
0.09883
0.02433
Goodness of Fit
Dose
0.0000
8.0000
68.0000
602.0000
Est. Prob.
0.0556
0.0581
0.0764
0.2245
Expected
1.669
1.569
2.216
6.511
Observed
2
0
4
6
Size
30
27
29
29
Scaled
Residual
0.263
-1.291
1.247
-0.228
ChiA2 = 3.34
d.f. = 2
P-value = 0.1882
D-48
DRAFT - DO NOT CITE OR QUOTE
-------
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 321.919
BMDL = 153.274
D-49 DRAFT - DO NOT CITE OR QUOTE
------- |