DRAFT - DO NOT CITE OR QUOTE EPA/635/R-09/003A
www.epa.gov/iris
&EPA
TOXICOLOGICAL REVIEW
OF
TRICHLOROACETIC ACID
(CAS No. 76-03-9)
In Support of Summary Information on the
Integrated Risk Information System (IRIS)
September 2009
NOTICE
This document is an External 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
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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.
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CONTENTS—TOXICOLOGICAL REVIEW OF
TRICHLOROACETIC ACID (CAS No. 76-03-9)
LIST OF TABLES v
LIST OF FIGURES vi
LIST OF ABBREVIATIONS AND ACRONYMS viii
FOREWORD xi
AUTHORS, CONTRIBUTORS, AND REVIEWERS xii
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 BIO ASSAYS IN
ANIMALS—ORAL AND INHALATION 22
4.2.1. Subchronic Studies 22
4.2.2. Chronic Studies and Cancer Assays 38
4.3. REPRODUCTIVE AND DEVELOPMENTAL STUDIES 57
4.3.1. Reproductive Studies 57
4.3.2. Developmental Studies 57
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 67
4.5.1. Mechanistic Studies 67
4.5.2. Genotoxicity Studies 81
4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS 87
4.6.1. Oral 87
4.6.2. Inhalation 89
4.6.3. Mode-of-Action Information 90
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
4.8. SUSCEPTIBLE POPULATION AND LIFE STAGES 115
4.8.1. Possible Childhood Susceptibility 115
4.8.2. Possible Gender Differences 116
4.8.3. Other Factors Influencing Susceptibility 117
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5. DOSE-RESPONSE ASSESSMENTS 118
5.1. ORAL REFERENCE DOSE (RfD) 118
5.1.1. Choice of Principal Study and Critical Effect—with Rationale and
Justification 118
5.1.2. Methods of Analysis 123
5.1.3. RfD Derivation—Including Application of Uncertainty Factors (UFs) 131
5.1.4. RfD Comparison Information 133
5.1.5. Previous RfD Assessment 133
5.2. INHALATION REFERENCE CONCENTRATION (RfC) 133
5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE 134
5.4. CANCER ASSESSMENT 135
5.4.1. Choice of Study/Data—with Rationale and Justification 137
5.4.2. Dose-Response Data 137
5.4.3. Dose Conversion 139
5.4.4. Extrapolation Methods 140
5.4.5. Oral Cancer Slope Factor and Inhalation Unit Risk 142
5.4.6. Previous Cancer Assessment 142
6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE
RESPONSE 143
6.1. HUMAN HAZARD POTENTIAL 143
6.2. DOSE RESPONSE 146
6.2.1. Noncancer/Oral 146
6.2.2. Noncancer/Inhalation 147
6.2.3. Cancer/Oral and Inhalation 147
7. REFERENCES 149
APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC COMMENTS
AND DISPOSITION A-l
APPENDIX B. BENCHMARK DOSE MODELING RESULTS FOR THE INCIDENCE OF
HEPATOCELLULAR INFLAMMATION, HEPATOCELLULAR NECROSIS, AND
TESTICULAR TUBULAR DEGENERATION IN MICE EXPOSED TO TCA IN
DRINKING WATER FOR USE IN DERIVATION OF THE REFERENCE DOSE B-1
APPENDIX C. INPUT AND OUTPUT DATA FOR BENCHMARK DOSE MODELING OF
DEVELOPMENTAL DATA FROM SMITH ETAL. (1989) C-l
APPENDIX D. MODELING OF LIVER TUMOR INCIDENCE DATA FOR MICE EXPOSED
TO TRICHLOROACETIC ACID IN DRINKING WATER D-l
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LIST OF TABLES
Table 3-1. Binding of TCA to plasma proteins from different species 9
Table 4-1. Summary of acute, short-term and subchronic studies evaluating effects of
TCA after oral administration in rats and mice 24
Table 4-2a. Summary of longer-term 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 47
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 B6C3F1 mice exposed to TCA
in drinking water for 104 weeks 49
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 61
Table 4-9. Summary of available genotoxicity data on TCA 82
Table 5-1. Candidate studies for derivation of the RfD for TCA 119
Table 5-2. BMD 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) 124
Table 5-3. BMD modeling results based on incidence of hepatocellular necrosis in male
B6C3F1 mice exposed to TCA in drinking water for 30 to 45 weeks
(DeAngelo et al., 2008) 125
Table 5-4. BMD 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) 125
Table 5-5. Dose response data for developmental endpoints in TCA-treated
Long-Evans rats (Smith et al., 1989) 127
Table 5-6. BMD modeling results for fetal incidence data (Smith et al., 1989) 129
Table 5-7. BMD modeling results for litter incidence of levocardia (Smith et al., 1989) 130
Table 5-8. Incidences of hepatocellular adenomas, carcinomas, or adenomas and
carcinomas combined in male B6C3F1 mice exposed to TCA in drinking
water for 52 weeks (Bull etal., 2002) 138
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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 etal., 2002) 138
Table 5-10. 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) 138
Table 5-11. 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) 139
Table 5-12. Incidences of hepatocellular adenomas, carcinomas, or adenomas and
carcinomas combined in male B6C3F1 mice exposed to TCA in drinking
water for 104 weeks (DeAngelo et al., 2008) 139
Table 5-13. Candidate oral cancer slope factors derived from bioassays in B6C3F1 mice 141
Table B-l.l. 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) B-l
Table B-l.2. 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 et al., 2008) B-10
Table B-l.3. 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) B-19
Table C-l. BMD modeling results for litter incidence of levocardia (Smith et al., 1989).... C-19
LIST OF FIGURES
Figure 2-1. Trichloroacetic acid 3
Figure 3-1. Proposed metabolic scheme for TCA 13
Figure 4-1. Possible key events in theMOA(s) for TCA carcinogenesis 94
Figure 5-1. Plot of predicted and observed litter incidence of levocardiain offspring of
female Long-Evans rats exposed to TCA on GDs 6-15 131
Figure 5-2. Comparison of RfDs across target organs or endpoints 133
Figure D-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 D-2
Figure D-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 D-3
Figure D-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 D-4
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Figure D-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 D-5
Figure D-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 D-6
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LIST OF 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 limit on the BMD
BMDS benchmark dose software
BMR benchmark response
BrdU bromodeoxyuridine
BSA bovine serum albumin
CACT carnitine acetyl-CoA transferase
CAT catalase
CASRN Chemical Abstracts Service Registry Number
CPF ciprofibrate
CpG cytosine-guanine dinucleotide
CPK creatine phosphokinase
CYP450 cytochrome P450
DCA dichloroacetic acid
DEHP di(2-ethylhexyl)phthalate
DEN diethylnitrosamine
DMR-2 differentially methylated region-2
DMSO dimethyl sulfoxide
ECso median effective concentration
EDio 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
GR glutathione reductase
GSH glutathione
GST glutathione S-transferase
GTPase guanosine triphosphatase
HPLC high performance liquid chromatography
IAP intracisternal A particle
IGF insulin-like growth factor
IL interleukin
i.p. intraperitoneal(ly)
IPCS International Programme on Chemical Safety
Vlll
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IPRL
IRIS
LDH
LEDio
LINE
LOAEL
LOH
LTR
MCA
MCP
MDA
MDD
5MeC
MNU
MOA
MTase
MTD
NAF
NIOSH
NLM
NOAEL
NPC
NRC
NTD
8-OHdG
PAS
PB
PBPK
PCNA
PCO
PCR
PFOA
PG
PH
POD
POR
PP-A
PPAR
PPRE
RA
RDS
RfC
RfD
RT-PCR
SA
SAM
isolated perfused rat liver
Integrated Risk Information System
median lethal dose
lactate dehydrogenase
lower 95% bound on exposure dose at 10% extra risk
long interspersed nucleotide element
lowest-observed-adverse-effect level
loss of heterozygosity
long terminal repeat
monochloroacetic acid
methylclofenapate
malondialdehyde
mean daily dose
5-methylcytosine
MDA-derived deoxyguanosine
N-methyl-N-nitrosourea
mode of action
methyltransferase
maximum tolerated dose
nafenopin
National Institute for Occupational Safety and Health
National Library of Medicine
no-observed-adverse-effect level
non-parenchymal cell
National Research Council
neural tube development
8-hydroxy-2'-deoxyguanosine
periodic acid-Schiffs reagent
phenobarbital
physiologically based pharmacokinetic
proliferating cell nuclear antigen
palmitoyl-CoA oxidase
polymerase chain reaction
perfluorooctanoic acid
prostaglandin
partial hepatectomy
point of departure
prevalence odds ratio
peroxisome proliferation-associated
peroxisome proliferator-activated receptor
peroxisome proliferator response element
retinoic acid
replicative DNA synthesis
reference concentration
reference dose
reverse transcription PCR
superoxide anion
S-adenosylmethionine
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SD standard deviation
SOD superoxide dismutase
SSB single-strand break
SSCP single-stranded conformation polymorphism
SuDH succinate dehydrogenase
TEARS thiobarbituric acid-reactive substances
TCA trichloroacetic acid
TCE trichloroethylene
TGF transforming growth factor
UF uncertainty factor
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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).
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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
TedBerner, M.S.
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
CONTRACTOR SUPPORT
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
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Joyce Donohue, Ph.D.
Office of Water
U.S. Environmental Protection Agency
Washington, DC
Susan Rieth, MPH
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Weihsueh Chiu, Ph.D.
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Jane Caldwell, Ph.D.
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
Karen Hogan, M.S.
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
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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 subchronic (>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
been 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
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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.
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2. CHEMICAL AND PHYSICAL INFORMATION
Trichloroacetic acid (TCA) is a colorless to white crystalline solid with a sharp, pungent
odor (National Institute for Occupational Safety and Health [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.
Cl
Cl
o
Cl
OH
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 (O'Neil, 2001)
163.39 (O'Neil, 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 (Liley et al., 1984)
0.51 at 25°C (Serjeant and Dempsey, 1979)
1.35 x 10~8 atm-m3/mol at 25°C (Bowden et al.,
1998)
1,306 g/100 g at 25°C (Morris and Bost, 2002)
At 25°C, methanol, 2,143 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 laboratory intermediate or reagent in the synthesis of
a variety of medicinal products and organic chemicals (National Library of Medicine [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
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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).
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; Reimann et al., 1996; Sidebottom and Franklin, 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 a concentration range of 0.01-1 |ig/L (Reimann et al., 1996).
TCA is formed from organic material during water chlorination (International
Programme on Chemical Safety [IPCS], 2000; Coleman et al., 1980) and has been detected in
groundwater, surface water distribution systems, and 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.
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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 CC>2 in expired air represented about 57-72% and 4-8%, respectively, of
the administered dose (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 a 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 CC>2, and 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
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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 (two males and two females) either walked in the pool 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 |ig/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 1,183 ng, whereas
postexposure amounts ranged from 294 ng to 1,590 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- to 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 hour) indicated that urinary
excretion (and, thus, presumably, dermal absorption) was higher with higher exposure. For
exposures of about 20 and 420 |ig/L x hour TCA, 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.
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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 0.081 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 6-10 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 more extensive than binding in liver homogenates. 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, unbound 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). It was
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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 of 53 ± 4% (mean ± standard deviation [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/kg (81.7 mg/kg) TCA 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 unexposed 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 1,224 nmol/mL,
respectively.
Templin et al. (1995) measured the binding of TCA to plasma proteins in four different
species: dog, rat, mouse, and human. Plasma samples were prepared from whole blood and
incubated with 3-1,224 nmol/mL [14C]-TCA at 37°C for 30 minutes. Binding of TCA to plasma
constituents was analyzed by using a Scatchard plot and is summarized in Table 3-1. Binding of
TCA to plasma proteins was higher in humans than in rats and mice.
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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 are 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 jimol 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 1,000 |iM 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 6,130 jiM (0.01-1,000 |ig/mL) to plasma proteins in samples of plasma from
humans, rats, and mice. Pooled plasma for each species was obtained from commercial sources.
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Neither donor strain (for rodents) nor donor sex were specified. Binding was determined by
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.
Lumpkin et al. (2003) 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
by 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 were
2.97, 1.49, and 0.17, respectively. The low number of binding sites observed for mice may
indicate existence of other ligands competing for TCA binding sites 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)
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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
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: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 1,100-1,200 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 48-55% 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 CC>2 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
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doses (Xu et al., 1995; Larson and Bull, 1992). In contrast, orally administered radiolabeled
DC A is more extensively metabolized in rats and mice than is TCA (Larson and Bull, 1992).
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/kg
TCA was metabolized in rats within 24 hours. Within 24 hours after injection of 1 or 50 mg/kg
TCA, urinary excretion accounted for about 48 and 87%l and total exhaled CO2 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 of 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 (CYP450) 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).
1 These values were extracted from Figure 2 of the Yu et al. (2000) report.
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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, fo
— — P P < ^ r-
II
-------
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 CC>2 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/mass spectrometry (GC/MS) analysis following
trapping of an adduct between the dichloroacetate radical and phenyl-tertiary-butyl nitroxide
(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 monochloroacetaldehyde 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 in this review. For a more detailed analysis of data on DCA
metabolism, the reader is referred to the IRIS Toxicological Review ofDichloroaceticAcid(\J.S.
EPA, 2003). DCA 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
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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
(0-14 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 1,000 |ig/mL increased
phase I metabolism but had no effect on phase II metabolism at either 25 or 1,000 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
(0-5,000 |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 the primary metabolic
pathway for TCA appears to be mediated by CYP450 pathways. However, an alternative
explanation for these data was noted, namely, 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 1,200 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
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(4- and 9.5-fold at 4 and 8 hours after exposure), trichloroethanol (4.4- and 1.8-fold), and chloral
hydrate (96- and 69-fold) but no significant change in total cecum content of DC A (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 CYP450 enzymes, Austin et al. (1995)
evaluated the effects of pretreating mice with TCA. Male B6C3Fi mice were pretreated with
1,000 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 CYP450 isoforms CYP2E1, CYP4A, CYP1A1/2, CYP2B1/2, and
CYP3A1; and (4) total liver CYP450. Pretreatment with TCA increased 12-hydroxylation of
lauric acid, demonstrating an increase in CYP4A activity (and apparently reflecting a
peroxisome proliferation response), whereas p-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
lipid peroxidation responses following acute challenge. The study authors suggested that this
modification resulted 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 [l,2-14C]-labeled
TCA (Gonzalez-Leon et al., 1999). Pretreated mice and control mice showed similar TCA blood
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concentration-time profiles. No significant differences in elimination kinetic parameters, such as
volume of distribution, AUC, elimination half time, total body clearance, and renal clearance,
were found between pretreated mice and control mice. The amount of radiolabel exhaled as
CC>2, 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 CYP450 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). Non-metabolized TCA accounted for 81-90% 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).
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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 DCA, TCA, and N-acetyl-S-(trichlorovinyl)-L-cysteine. TCA was the major
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metabolite 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 5-10 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 to 1,183 ng, whereas postexposure amounts
ranged from 294 to 15,990 ng (Kim and Weisel, 1998).
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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]; Mills et al. [1998]) and adverse effects on reproduction (reviewed by
Nieuwenhuijsen et al. [1999]; Mills et al. [1998]).
Most of the studies of human health effects following exposure to water disinfectant
by-products have used trihalomethanes and haloacetic acid concentrations as the exposure metric
(Hinckley et al., 2005; King et al., 2005; Porter et al., 2005). For example, a population-based
case-control study conducted by Klotz and Pyrch (1999) examined the relationship between
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 (not statistically significant) excess risk (FOR
1.2, 95% confidence interval 0.5-2.6) was found for the highest tertile (>35 ppb) of the 5
regulated 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 on 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 treatments to treat
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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 causing 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.
Histologic 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 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 with 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 with a central crater that is scaly or
crusted.
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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. Subchronic (<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 5,000
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 aminotransferase
[ALT], alkaline phosphatase [ALP], cholesterol, total protein, albumin, calcium, phosphorus,
creatinine phosphokinase, and gamma-glutamyl transpeptidase [GGT]). 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.
Histopathologic 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 that the no-
observed-adverse-effect level (NOAEL) for this study was 36.5 mg/kg-day and the lowest-
observed-adverse-effect 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 a median lethal dose (LD50) of
TCA, DC A, or MCA in drinking water to male Sprague-Dawley rats (five/dose) for 90 days.
Based on the reported LD50 of 3,300 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
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deposition. No 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). Morphologic 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 that the only dose tested in this study, 825 mg/kg-
day, 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-month-old female Sprague-Dawley rats
were administered 2,000 ppm (300 mg/kg-day, assuming a default water intake of 0.15 L/kg-
day) TCA (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, and
kidney samples were obtained. Serum marker enzymes (aspartate aminotransferase [AST], ALT,
creatine phosphokinase [CPK], acid phosphatase [ACP], ALP, and LDH), erythrocytes and
tissue antioxidant defense systems (GSH, glutathione reductase [GR], superoxide dismutase
[SOD], 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.
The 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
reactive oxygen species.
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Table 4-1. Summary of acute, short-term and subchronic 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,
five/group
Wistar rats
(males,
five to
six/dose)
Sprague-
Dawley
rats
(six/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 histopathologic
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 osmolarity, 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
(3,300 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-day
study (A).
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Table 4-1. Summary of acute, short-term and subchronic 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,
six/group
/strain)
F344 rats
(males,
six/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 or 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
PCO activity assay was
used to measure the
peroxisome proliferative
response.
Mice
Kato-
Weinstein et
al. (2001)
B6C3FJ
mice
(males,
five/dose)
Oral,
drinking
water
(A) 4 or 8
weeks
(B)12
weeks
(A) 750 mg/kg-
day
(B) 0, 75, 250,
or 750 mg/kg-
day
Increased absolute and relative
liver weights; decreased liver
glycogen content
Not
determined
75
Doses were estimated
based on default
drinking water intake
values for male B6C3Fi
mice.
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Table 4-1. Summary of acute, short-term and subchronic studies evaluating effects of TCA after oral
administration in rats and mice
Reference
Parrish et al.
(1996)
Austin et al.
(1995)
DeAngelo et
al. (1989)
Sanchez and
Bull (1990)
Species
B6C3FJ
mice
(males,
six/group)
B6C3FJ
mice
(males,
six/group)
B6C3Fb
C3H,
Swiss-
Webster,
C57BL/6
mice
(n=6)
B6C3FJ
mice
(males,
12/group)
Exposure
route
Oral,
drinking
water
(A) Oral,
drinking
water
(B) Oral,
gavage
Oral,
drinking
water
Oral,
drinking
water
Exposure
duration
3 or 10
weeks
(A) 14 days
(B) Single
dose
14 days
14 days
Doses
evaluated
0, 25, 125,
500 mg/kg-day
(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
Effects3
Increased absolute and relative
liver weights; peroxisome
proliferation (increased PCO
activity and increased 12-
hydroxylation of lauric acid)
(A) Increased relative liver weight
(B) Decreased TBARSC; increased
PCO, CAT, and CYP4A activities
Increased relative liver weight,
peroxisome proliferation (PCO
activity)
Increased liver weight; hepatocyte
proliferation (DNA labeling)
NOAEL
(mg/kg-day)
25
Not
determined
Not
determined
75
LOAEL
(mg/kg-day)
125
250
261
250
Comments
Doses were estimated
based on default
drinking water intake
values for male B6C3Fi
mice; results were
similar for the 3- and
10-week evaluations;
8-OHdGb levels were
not affected by TCA.
(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.
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Table 4-1. Summary of acute, short-term and subchronic studies evaluating effects of TCA after oral
administration in rats and mice
Reference
Dees and
Travis
(1994)
Goldsworthy
and Popp
(1987)
Austin et al.
(1996)
Laughter et
al. (2004)
Species
B6C3FJ
mice
(five/sex
/dose)
B6C3FJ
mice
(males,
seven to
eight
/group)
B6C3FJ
mice
(males,
six/group)
SV129
wild-type
mice;
PPARda-
null mice
(males,
three to
five/group
Exposure
route
Oral,
gavage
Oral,
gavage
Oral,
gavage
Oral,
drinking
water
Exposure
duration
1 1 days
10 days
Single dose
7 days
Doses
evaluated
0, 100, 250,
500, or
1,000 mg/kg-
day
0 or 500 mg/kg
in corn oil
0, 30, 100, or
300 mg/kg
0,57.5, 115,
230, or
460 mg/kg-day
Effects3
Increased absolute and relative
liver weight; increased hepatocyte
labeling
Induction of hepatic and renal
peroxisome proliferation;
increased relative liver weight
Oxidative stress (increased
8-OHdGb levels)
Induction of markers of
peroxisome proliferation in wild-
type but not PPARda-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
determined
Not
determined
Not reported
115
LOAEL
(mg/kg-day)
100
500
Not reported
230
Comments
The cyanide-insensitive
PCO activity assay was
used to measure the
proliferative response.
Liverbody weight ratios
were also significantly
increased in both.
Doses were estimated
based on default
drinking water intake
values for male B6C3F!
mice; 8-OHdGb 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.
b8-hydroxy-2'-deoxyguanosine.
cThiobarbituric acid-reactive substances.
dPeroxisome proliferator-activated receptor.
Source: Adapted from U.S. EPA (2005c).
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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 to 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 TCA (U.S. EPA, 1988) 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, ACP, AST, 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),
histopathologic 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 histopathologic changes that were noted included
centrilobular necrosis, hepatocyte vacuolation, loss of hepatic architecture, and hypertrophy of
the 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 the earlier study (Acharya et al., 1995).
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Histopathologic 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 histopathologic changes at the single dose tested,
the study authors (Acharya et al., 1997) indicated that TCA is a liver and kidney toxicant.
Taken together, the two studies (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 histopathologic changes were observed,
they were described as "only marginal" by the authors. The authors did not discuss the severity
of the histopathologic 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 that in 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
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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 to six/dose) given 500 mg/kg-day TCA in corn oil
via 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 in controls. Liver-to-body-weight ratios were also significantly (41%, p< 0.05)
increased relative to those in controls. Body weight gain was not changed. Renal peroxisomal
enzyme activity was significantly (p < 0.05) increased by approximately 1.8-fold over that in
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
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proliferation in response to TCA exposure under the experimental conditions tested. EPA
determined that the NOAEL and LOAEL for peroxisome proliferation were 327 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 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. Studies in mice are summarized in Table 4-1. The available 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 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 mice (seven to eight/dose) given 0 or 500 mg/kg in corn oil for 10 days via 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% those 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 increased (40%; p < 0.05) relative to controls.
DeAngelo et al. (1989) investigated the effects of TCA exposure on hepatic peroxisome
proliferation by 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 2,100 and 2,500% above control levels at the high and low
doses for TCA, respectively, indicating that this is a particularly sensitive strain of mouse.
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In another phase of this study, CAT 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 dose
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) tested for acute toxicity as part of a dose-range finding study on
hepatocyte replicative DNA synthesis (RDS) for 41 putative Ames-negative mouse
hepatocarcinogens. Groups of male B6C3Fi mice (four or five/dose) were administered a single
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 10-week studies. 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-hydroxy-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 2,000 mg/kg TCA. The Larson and Bull (1992) study
also reported that a single oral dose of TCA 9 hours after dosing induced TEARS levels 1.15-,
1.7-, 2-, and 2.7-fold over controls at 100, 300, 1,000, and 2,000 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 induction of these
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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
2,000 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, or 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 histopathologic
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 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
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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 CYP450s following short-term treatments. Male B6C3Fi mice (18/group) were treated with
0 or 1,000 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) lipid peroxidation response, as measured by the
production of TEARS; (2) indicators of peroxisome proliferation, as measured by increased PCO
activity, increased CA activity, and changes in microsomal 12-hydroxylation of lauric acid (an
indicator for the activity of CYP4A; (3) hydroxylation of p-nitrophenol (as an index of CYP2E1
activity); and (4) protein levels for a panel of CYP450s, 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, CAT, 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 lipid peroxidation 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
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indirect markers of peroxisome proliferation (PCO, CAT, 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 CYP450 activities has 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
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
subchronic 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, 1,000, or 2,000 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 mg/kg-day (38%). Hepatocyte diameter was significantly increased (13%; p < 0.05) at
500 mg/kg-day. Periodic 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 by autoradiography. 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.
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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 1,000 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 histopathologic
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.
Histopathologic changes were observed for both males and females at 1,000 mg/kg-day.
Histopathologic 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 in autoradiographs) 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 1,000 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 1,000 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 1,000 mg/kg-day, respectively. The increase in
DNA synthesis ([3H]thymidine/|ig DNA) became statistically significant at 250 mg/kg-day and
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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 histopathologic 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
histopathologic 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 five
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 (approximately
25-33% as estimated from Figure 1A in Kato-Weinstein et al. [2001]; p < 0.05) than in 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. Histopathologic 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
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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 (PPAR)a (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 histopathologic 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 physiological pH) at 0, 50, 500, or 5,000 mg/L, resulting in time-
weighted mean daily doses (MDDs) 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
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conducted 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 at 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 histopathologic 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 and LOAEL to be 32.5 and
364 mg/kg-day, respectively, based on decreased body weight, increased serum ALT activity,
mild hepatocellular necrosis, and increased peroxisome proliferation.
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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
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
histopathologic 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 examined
microscopically.
Mice
DeAngelo
et al. (2008)
B6C3FJ mice
(males,
Study 1:
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 or
572 mg/kg-day;
Study 3:0, 6, or
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 the 68
and 602 mg/kg-day
groups, increased labeling
index for nuclei outside
of hepatic proliferative
lesions, and testicular
tubular degeneration at
602 mg/kg-day
8
68
Time-weighted
average daily
doses were
calculated by
the study
authors; a
comprehensive
set of tissues
was examined
microscopically.
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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)
(11 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 or 309
mg/kg-day
0, 500, or
1,250 mg/kg-day
Noncancer effects
evaluated
Body and liver weight,
liver histopathology
Liver and kidney weight
and histopathology
Liver weight and
histopathology
Effects
Increased relative liver
weight
Increased absolute and
relative liver weight,
cytomegaly, modest
glycogen accumulation
Increased absolute and
relative liver weight
NOAEL
(mg/kg
78
Not
achieved
Not
achieved
LOAEL
-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 examined
microscopically.
"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 not dosed by the oral route (i.p. injection).
Source: Adapted from U.S. EPA (2005c).
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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
hepat-
ectomized
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
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-
initiated rats at all doses
evaluated, but only one rat
showed a liver carcinoma. TCA
showed no evidence as an
initiator.
Mice
DeAngelo
etal.
(2008)
Pereira
(1996)
Bull et al.
(2002)
B6C3FJ
mice
(males, 27-
30/dose at
terminal
sacrifice;
five/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 3 :
104 weeks
5 lor 82 weeks
52 weeks
Study 1:0, 8, 68, or
602 mg/kg-day;
Study 2: 0 or
572 mg/kg-day;
Study 3:0, 6, or
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.
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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
(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
3 1 weeks
44 weeks
Doses evaluated
(A) 0, 164, or
329 mg/kg-day
(B) 0 or 309 mg/kg-
day
1,000 or 2,000 nmol
(16 or 32 mg/kg)
total dose over a
2-day period (at 8
and 15 days of age)
0, 400, or
1,000 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 MNUa
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 ethylnitrosourea
pretreatment.
Only the liver was examined for
tumors.
Only the liver and kidneys were
examined for tumors; MNUa
was used as an initiator;
statistically significant increases
in tumor yield were only
observed in males.
MNUa was used as an initiator;
only the liver was
microscopically examined.
aMNU = N-methyl-N-nitrosourea.
Source: Adapted from U.S. EPA (2005c).
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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
gavage dose of 10 mg/kg diethylnitrosamine (DEN) (a known initiator) or 1,500 mg/kg of TCA.
Additional groups of hepatectomized rats began a regimen of exposure to 5,000 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 2 weeks later
by addition of 500 mg/L PB (the positive control) or 0, 50, 500, or 5,000 mg/L TCA (equivalent
to doses of about 0, 6, 60, or 600 mg/kg-day as calculated by 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 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 5,000 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 5,000 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
5,000 mg/L drinking water level. No significant gross or histopathologic 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/5,000 mg/L TCA group was found in
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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. PH 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 was 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 nonneoplastic lesions. At the termination of the
studies, a complete necropsy was performed, and pathological examination was conducted on
gross lesions, liver, kidney, spleen, and testis. A complete pathological examination was
performed on five 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 LDH activity was measured. Portions
of liver tissue were frozen and analyzed for 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 bromodeoxyuridine (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 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 MDDs 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 than the
controls. No significant differences in animal survival were noted for any treatment group. An
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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
weeks and appeared to be dose related (Tables 4-3 and 4-4). The nonneoplastic alterations
observed in the liver included hepatocellular cytoplasmic alteration, necrosis, and inflammation.
Cytoplasmic alterations were observed in all treatment groups; however, the incidence did not
increase monotonically with dose. 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 (a measure of
liver damage) 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.
Areas of inflammation (at high dose only) and necrosis (at mid- and high-dose) were
present during the early course of TCA administration but abated after week 60 in all studies.
Similarly, LDH activity was elevated in the mid- and high-dose groups at week 30 but not at
week 60. Cytoplasmic alterations occurred as early as week 4 and persisted throughout the three
studies at all doses; indicating that this effect did not correlate with other nonneoplastic changes
in the liver. For the 60-week study, EPA determined the LOAEL for effects on the liver
(increased liver weight and hepatic necrosis) and testes (testicular tubular degeneration) to be
0.5 g/L (68 mg/kg-day) and the NOAEL to be 0.05 g/L (8 mg/kg-day).
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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
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±0.62e
24%e
0.24 ±0.44
21%e
0.21 ±0.41
Time-weighted MDD (mg/kg-day).
bNumber of animals examined.
Percentage of animals with alteration.
dSeverity: 0 = no lesion, 1 = minimal, 2 = mild, 3 = moderate, 4 = severe (reported as the average severity of all
animals in the dose group).
Statistically significant from the control group, p < 0.05.
Source: DeAngelo et al. (2008).
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)
Numberb
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
"Time-weighted MDD.
bNumber of animals examined.
Percentage of animals with alteration.
dSeverity: 0 = no lesion, 1 = minimal, 2 = mild, 3 = moderate, 4 = severe (reported as the average severity of all
animals in the dose group).
Statistically significant from the control group, p < 0.05.
Source: DeAngelo et al. (2008).
Exposure to TCA induced tumors in the liver at 60 weeks (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
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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).
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
database.
Table 4-5. Prevalence and multiplicity of hepatocellular neoplasia in male
B6C3Fi mice exposed to TCA in drinking water for 60 weeks
Neoplasia type
HAC
HCC
HAorHCc
Treatment
Dose3
Numberb
Prevalence"1
Multiplicity6
Prevalence"1
Multiplicity6
Prevalence"1
Multiplicity6
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
""Time-weighted MDD (mg/kg-day).
bNumber of animals examined. Parentheses = number of animals/group scheduled for terminal necropsy.
°HA = hepatocellular adenoma, HC = hepatocellular carcinoma, HA or HC = either hepatocellular adenoma or
hepatocellular carcinoma.
Percentage of animals with a lesion as reported in the study report.
eNumber of lesions/animal, mean ± standard error of the mean.
Statistically significant from the control group, p < 0.05.
Source: DeAngelo et al. (2008).
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Table 4-6. Incidence of hepatocellular neoplasia in male B6C3Fi mice
exposed to TCA in drinking water for 104 weeks
Neoplasia type
HAC
HC
HA+HC
HA
HC
HA+HC
Treatment
Dose3
Numberb
Prevalence"1
Multiplicity6
Prevalence"1
Multiplicity"
Prevalence"1
Multiplicity6
Treatment
Dose3
Numberb
Prevalence"1
Multiplicity6
Prevalence"1
Multiplicity"
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
78s
1.50±0.22f
89f
2.11±0.25f
Time-weighted MDD calculated over 104 weeks (mg/kg-day).
bAnimals surviving >78 weeks, parentheses = number of animals/group scheduled for terminal necropsy.
°HA = adenoma, HC = carcinoma, HA or HC = either adenoma or carcinoma.
dNumber of animals with a lesion/number of animals examined.
eMean number of lesions ± standard error of the mean.
Statistically significant from the control group, p < 0.03.
Source: DeAngelo et al. (2008).
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 and 5g/L was 129-
260% and 326-575%, respectively, 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 weeks (about threefold) and 40 weeks (about 2.5-fold). Increased nuclear labeling was
observed in the mid-dose treatment group at 60 weeks (about threefold). These data indicate that
TCA induced treatment-related tumors in male mice at doses that also induced peroxisome
proliferation and hepatocyte proliferation. 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 (males: 24/high dose, 1 I/low dose, 35 controls; females: 10/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/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 corresponded to estimated average
daily doses of 0, 164, and 329 mg/kg-day as calculated from data for total dose provided in the
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study report. The approximate average daily dose for the 37-week exposure with recovery was
309 mg/kg-day.
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: 2 g/L, 10 females) were evaluated in this study
than were male mice (37 weeks: 2 g/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 that 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, 1,090, or
3,268 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 were 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 histopathologic examination.
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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
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 histopathologic 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.
Random tumor samples were stained with an anti c-Jun antibody; all tumors were
analyzed for mutation frequency and spectra of the H-ras codon 61; and these results were
compared with those from DCA- and TCE-induced tumors. Proteins involved in the mitogen-
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activated protein 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 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 mitogen-activated protein
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
1,250 mg/kg-day) as calculated by 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
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enhanced the incidence of hepatocellular adenomas and carcinomas above control levels, with or
without prior initiation. The study authors concluded that TCA acted as a complete carcinogen
inB6C3Fi mice.
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-
nitrosourea (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, 1,090, or 3,268 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 exposure duration increasing 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
were 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-u, a phase II
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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
that are rodent peroxisomal proliferators, but "spontaneous" liver tumors in mice have also been
reported to be predominantly basophilic and lacking GST-u (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 1,000 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 were 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 four carcinomas at 25 mmol/L TCA), which is
consistent with the results reported by Pereira and Phelps (1996). In contrast, tumors from
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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
tumors in the livers from mice treated with DCA + TCA were more consistent with the
characteristics of DCA-induced livers (eosinophilic and containing GST-7i). 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 (AHFs) 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 dimethyl
sulfoxide (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 2,000 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 1,000 nmol
(approximately 16 mg/kg) and were sacrificed at 20 months of age. 4-Aminobiphenyl was used
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as the concurrent positive control (22-24 mice/sex/dose) and total doses of 1,000 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
were evaluated in all treatment groups. At sacrifice, all test animals were necropsied for gross
tumor count, microscopic examination of tissues, and histopathologic 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 increase (not
statistically significant) 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 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
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 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 (number of animals treated not stated) were given a total
dose of 2,000 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 at 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 von Tungeln et al. (2002), these
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results suggest that neonatal B6C3Fi mice are not sensitive to either TCA-induced lipid
peroxidation or oxidative stress as an MOA for tumor induction under the experimental
conditions used in these studies. The study authors speculated that TCA was negative in their
neonatal 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 1,000 ppm on a volume/volume basis (approximately 160, 400, or 1,600 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 1,000 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.
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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 I/dose)
Sprague-
Dawley rats
(55 controls and
11 TCA treated)
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,
1,200, or
1,800 mg/kg-
day
0 or 291 mg/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
Developmental:
none
LOAEL
(mg/kg-day)
Maternal:
330
Developmental:
330
Maternal:
291
Developmental:
291
Maternal:
300
Developmental:
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
evaluated; maternal toxicity
indicated by decreased
body weight gain for GDs
7-15 and 18-21; mean
uterine weight was also
significantly less (p < 0.05)
than in controls.
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Table 4-7. Summary of developmental studies evaluating effects of TCA after oral administration in rats
Reference
Singh
(2005a)
Singh
(2005b)
Singh
(2006)
Warren et
al. (2006)
Species
Inbred Charles
Foster rats
(6-12/group)
Inbred Charles
Foster rats
(6-12/group)
Inbred Charles
Foster rats
(6-12/group)
Sprague-Dawley
Crl:CDR (SD)
BR rats
Exposure
route
Oral,
gavage
Oral,
gavage
Oral,
gavage
Oral,
gavage
Exposure
duration
CDs 6-15
CDs 6-15
CDs 6-15
CDs 6-15
Doses
evaluated
0, 1,000, 1,200,
1,400, 1,600, or
1,800 mg/kg-
day
0, 1,000, 1,200,
1,400, 1,600, or
1,800 mg/kg-
day
0, 1,000, 1,200,
1,400, 1,600, or
1,800 mg/kg-
day
0 or 300 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
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
(increase in
implantation
loss): none
Effect on fetal
testes: 1,000
Effect on fetal
ovary: 1,200
Maternal:
1,000
Effect on fetal
brain: none
Developmental:
none
LOAEL
(mg/kg-day)
Developmental:
1,000
Effect on fetal
testes: 1,200
Effect on fetal
ovary: 1,400
Maternal:
1,200
Effect on fetal
brain: 1,000
Development:
300
Comments
Only evaluated effects on
fetal testes
Only evaluated effects on
fetal ovaries
Focused only on effects of
TCA on fetal brains
Focused on eye
malformations and
microphthalmia in fetal rats
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Smith et al. (1989) dosed pregnant Long-Evans rats (20-21/dose) with 0, 330, 800, 1,200,
or 1,800 mg/kg-day TCA by 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.
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 (5-12%; p < 0.05) 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, 1,200, or 1,800 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 1,200
and 1,800 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.
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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
1,200
1,800
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).
Source: Smith etal. (1989).
Johnson et al. (1998) evaluated the teratogenicity of TCA by exposing pregnant Sprague-
Dawley rats to 0 (n = 55) or 2,730 (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 by 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., SD or standard error) was reported, and it is not clear why this reduction was not
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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 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.
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.
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, Johnson et al. (1998) 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 gavage on
GDs 6-15. Vehicle control animals (n = 19) received distilled water. Positive control animals
(n = 12) received all-trans retinoic acid (RA) (15 mg/kg-day) dissolved in soybean oil. On
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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 by 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 that of 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 (all-trans RA) 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 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 (2006, 2005a, b) treated pregnant inbred Charles Foster rats (6-12 rats/dose group;
control group = 25) with 0, 1,000, 1,200, 1,400, 1,600, or 1,800 mg/kg-day TCA by gavage on
GDs 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
by 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 histologic examination (Singh, 2005a). Percentage of
postimplantation loss was significantly increased in a dose-related manner (22% at 1,000 mg/kg-
day versus 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
1,200 mg/kg-day and higher. Histologic examination of fetal rat testes of the 1,200 mg/kg-day
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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
1,200 mg/kg-day and higher.
The rat fetal ovaries of each pup of different dose groups from the above study were also
dissected out, weighed, and subjected to histologic examination (Singh, 2005b). The average
weights of the ovaries were significantly reduced for the dose groups >1,400 mg/kg-day.
Histologic examination of the fetal ovaries showed small size cells with less prominent nuclei at
the coelomic epithelium with > 1,400 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 resulting from
TCA exposure.
The rat fetal brains of different dose groups from the above study were evaluated (Singh,
2006). Maternal weight gains were decreased at TCA doses > 1,200 mg/kg-day (38% at
1,200 mg/kg-day). Mean fetal weight and fetal brain weight decreased significantly at TCA
doses >1,000 mg/kg-day; while the length of the fetal brain increased significantly at 1,000 and
1,200 mg/kg-day (about 10% at 1,000 mg/kg-day) but decreased significantly (8-16%) at TCA
doses >1,400 mg/kg-day when compared with controls. At doses >1,000 mg/kg-day, the fetal
brains showed hydrocephalus with breech of the ependymal lining, altered choroids plexus
architecture, and increased apoptosis. Vacuolation of the neutrophil was a prominent feature
with TCA exposure, with an incidence of 26% at 1,000 mg/kg-day (0% in controls) and reached
100% in the 1,600 and 1,800 mg/kg-day dose groups. The incidence of brain hemorrhages
increased to 30% at TCA doses > 1,200 mg/kg-day (0% in controls) and reached 100% at
1,800 mg/kg-day. The infarcts were mainly concentrated in the periventricular zone. Singh
(2006) concluded that the rat fetal brain was susceptible to the toxic effects of TCA.
In a study that evaluated if TCE, TCA, and DCA affect eye development in the Sprague-
Dawley rat (Warren et al., 2006), pregnant Sprague-Dawley Crl:CDR (SD) BR rats were
administered 0 or 300 mg/kg-day TCA by gavage on GDs 6-15. 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 (1,185 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 day 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:
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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, anophthalmia,
or microphthalmia 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 and
globe areas and 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 0, 1.63, or
16.3 mg/mL (0, 10, or 100 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 strongly heart specific on embryonic days 10.5-11.
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 stage
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
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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 TC A was studied in vitro by 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 4,060 mg/L and the
median effective concentration (ECso) for malformations was 1,740 mg/L. Malformations were
observed at concentrations greater than 1,500 mg/L and included gut miscoiling, craniofacial
defects, microphthalmia, microcephaly, 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 concentrations 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
hydras are no more sensitive to TCA than adult hydras 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
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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 on exposure to sub-irritating doses.
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 evaluate 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
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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 4,500 mg/L (1,080 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
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
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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 AHFs 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 et al., 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
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 (3,268 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.
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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 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 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 LD50. Groups of four or five animals were administered a single
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 SDs 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 BrdU. The resulting labeling data were used to identify 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
(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.
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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 exposures of 12 or 33 days. Thus, cell proliferation was enhanced by
5 days exposure to TCA but not for longer exposures of 12 or more days.
In a cell proliferation study reported by Stauber and Bull (1997), male B6C3Fi mice were
pretreated with 2,000 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, 1,000, or 2,000 mg/L TCA (estimated doses of 0, 5, 23, 115, 230, or
460 mg/kg-day, based on default water intake values in U.S. EPA [1988]) for 2 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
2,000 mg/L group, which consisted of 22 mice. Five days prior to sacrifice, DNA in replicating
hepatocytes was labeled in vivo by administering BrdU 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 AHFs.
A transient but significant elevation in normal hepatocyte division rates was evident in
mice consuming 2,000 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 2,000 mg/L and then shifted to the lower
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 1,000 or 2,000 mg/L
for 2 weeks, there was a significant decrease in cell division. Cell division rates in TCA-induced
AHFs and tumors were high at all doses. Rates of cell division in AHFs 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 TCA treatment.
TCA-induced lesions were histochemically stained with anti-c-jun 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 AHFs 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, Stauber and Bull (1997) proposed a mechanism for TCA-induced
hepatocarcinogenesis. They proposed that the initial growth stimulation induced by TCA causes
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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 was consistent with tumor characteristics
of other peroxisome proliferators in rats, as demonstrated by Rao et al. (1986). Because cell
replication in AHFs was independent of TCA (i.e., discontinued TCA treatment did not alter
AHFs or tumor-cell labeling), Stauber and Bull (1997) 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 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).
In the Tao et al. (1998) study, female B6C3Fi mice were injected i.p. 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 (4,085 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 1,062 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
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(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 40 and 51% when compared with either noninvolved tissue from the same animal
and liver tissue from control animals given only MNU, respectively. 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, Tao et al.
(1998) 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) indicated that the methylation of numerous genes was 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 of c-jun and c-myc
protooncogenes in mouse liver after short-term exposure to TCA. Female B6C3Fi mice
(four/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
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 by 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 two 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
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prevention of TCA-induced DNA hypomethylation by methionine suggested that the decrease in
the formation of 5-MeC in DNA is due to a 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 oi c-jun and c-myc genes,
expression of both genes, and activity of DNA methyltransferase (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 (3,268 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 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 previously. Tao
et al. (2000b) concluded that the promoter regions of c-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
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.
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from MNU-initiated mice that were not exposed to TCA. Expression of the IGF-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 the study by Tao et al. (2000), mouse liver tumors and tissues were obtained from
female B6C3Fi mice as described above. 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 cytosine-guanine
dinucleotide (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 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 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 by using HPLC analysis.
Sequencing of the DMR-2 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
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 methylation 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.
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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. (2001a). 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
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 1,600 mg/L chloroform in the drinking water for
17 days. A TCA dose of 500 mg/kg was administered daily by gavage on the last 5 days of the
exposure period. At sacrifice, livers were removed and processed for extraction of DNA.
Methylation of the promoter region was evaluated by 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
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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, 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
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. PB was
used as the positive control. Effects on gap junction intercellular communication were evaluated
by the iontophoretic microinjection of fluorescent 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
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positive control, significantly reduced dye transfer in cells treated with 1 or 2 mM after 4 or 8
hours of treatment but not after 24 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 CYP450
inhibitor.
Dye transfer in 24-hour-old primary rat hepatocytes was unaffected by treatment with
TCA at concentrations up to 1 mM for as long as 24 hours. Dye transfer in freshly plated rat
primary rat hepatocytes was unaffected by treatment with concentrations up to 1 mM 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 24 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 1-168 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 versus
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 CYP450 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 induced both lipid peroxidation (TEARS) and oxidative 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 report that 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
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).
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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 hours was similar to that of 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. Hassoun and Ray (2003) 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 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 transforming growth factor (TGF)-a (a growth factor that stimulates cell proliferation
and is expressed in tumor cells), TGF-P (a growth factor that is inhibitory to hepatocyte
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), CYP2E1 (potentially involved in TCA metabolism) and
CYP4A1 (induced by peroxisome proliferation signaling), and GST-u (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-u in greater than
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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
in 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 peroxisomal 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. AHFs and tumors induced by DCA were
reported as being predominantly eosinophilic. AHFs 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 = 11) and lacked
GST-u 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
animals were basophilic and eosinophilic, the author suggested that the basophilic foci induced
by TCA treatment may be more likely to progress to tumors.
Pereira (1996) 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 author 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, Pereira (1996) concluded that DCA 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
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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
Salmonella typhimurium 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 S. 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 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.
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Table 4-9. Summary of available genotoxicity data on TCA
Endpoint
Test system
Metabolic
activation"
Concentration/dose
Results
Reference
In vitro studies
Reverse
mutations
Prophage
induction
SOS repair
induction
SOS chromotest
Forward
mutations
Chromosomal
aberrations
Chromosomal
damage
DNA strand
breaks
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)
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
Chinese hamster ovary
AS52 cells
+/-
+/-
—
+/-
+/-
+/-
+/-
+/-
+
+/-
+/-
+/-
+/-
—
10-80 mM
5-100/0.5-80 mM
0. 1-1,000 ug/plate
1 mg/mL
0-600 mg/L
+ S9: 3,000-
7,500 ug/mL;
-S9: 1,750-
2,250 ug/mL
0. 1-100/5-80 mM
0-10 mg/mL
58.5 ug/mL
10-10,000 ug/mL
+S9: 0-3,400 ug/mL;
-89:0-2,150 ug/mL
0-2,500 ug/mL
2,000 and
5,000 ug/mL
0.1-3mM
Negative
Negative
Negative
Negative
Negative
Positive,
addition of S9
decreased
mutagenicity.
Toxic
concentration:
10,000 ug/mL
with S9;
2,500 ug/mL
without S9
Negative
Negative
Positive
Negative
+ S9: weakly
positive
-S9: equivocal
Weakly positive
TCA as free
acid: positive;
neutralized
TCA: negative
Negative
Kargalioglu
et al. (2002)
Kargalioglu
et al. (2002)
Rapson et al.
(1980)
Nelson et al.
(2001)
DeMarini et
al. (1994)
Ciller et al.
(1997)
Kargalioglu
et al. (2002)
DeMarini et
al. (1994)
Ono et al.
(1991)
Ciller et al.
(1997)
Harrington-
Brock et al.
(1998)
Harrington-
Brock et al.
(1998)
Mackay et al.
(1995)
Plewa et al.
(2002)
In vivo studies
Chromosomal
aberration
Swiss mice, bone
marrow
NA
0, 125, 250, or
500 mg/kg i.p.;
500 mg/kg orally
(TCA not neutralized
before administration)
Positive
Bhunya and
Behera
(1987)
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Table 4-9. Summary of available genotoxicity data on TCA
Endpoint
Sperm-head
abnormalities
Micronucleus
induction
DNA strand
breaks (alkaline
unwinding
assay)
Oxidative DNA
damage
(8-OHdG
adducts)
Test system
Swiss mice
Swiss mice, bone
marrow
C57BL mice, bone
marrow evaluated
Newt larvae
(Pleurodeles waltl),
erythrocytes
B6C3F! mice and
Sprague-Dawley rats
B6C3FJ mice
B6C3FJ mice and F344
rats
B6C3FJ mice
B6C3FJ mice
Metabolic
activation"
NA
NA
NA
NA
NA
NA
NA
NA
NA
Concentration/dose
0, 125, 250,
500 mg/kg i.p. divided
into 5 daily doses
(TCA not neutralized
before administration)
0, 125, 250, or
500 mg/kg i.p. (2 daily
doses)
(TCA not neutralized
before administration)
337-1,300 mg/kg i.p.
(25-80% of LD50)
(neutralized TCA was
administered)
40, 80, 160 ug/mL
(TCA not neutralized
before treatment)
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
Results
Positive
Positive
Negative
Weakly positive
at 80 ug/mL
Positive
Negative
Negative
Positive
Negative
Reference
Bhunya and
Behera
(1987)
Bhunya and
Behera
(1987)
Mackay et al.
(1995)
Ciller et al.
(1997)
Nelson and
Bull (1988)
Styles et al.
(1991)
Chang et al.
(1992)
Austin et al.
(1996)
Parrish et al.
(1996)
aNA = not applicable; +/- = with and 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 1,750 to 2,250 jig/mL. The addition of S9 decreased the mutagenic
response, and genotoxic effects were observed at 3,000-7,500 |ig/mL. Cytotoxic concentrations
in the Ames fluctuation assay were 2,500 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
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|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 jig/mL, with and without S9 activation
(DeMarini et al., 1994).
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 2,150 |ig/mL without S9 metabolic activation and up to
3,400 |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 (2,000 |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 2,250 |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 (0.1-3 mM) in
Chinese hamster ovary cells. TCA was found to be not genotoxic in this assay. Mackay et al.
(1995) investigated the ability of TCA to induce chromosomal DNA damage in an in vitro assay
by 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 (2,000 and 3,500 |ig/mL) that significantly reduced the pH of the medium.
Neutralized TCA had no effect in this assay even at a cytotoxic concentration of 5,000 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.
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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 0, 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 and
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 hours 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 at i.p. doses of 0, 337, 675, or 1,080 mg/kg-day for males and
0, 405, 810, or 1,300 mg/kg-day for females for 2 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 LDso. No significant treatment-related increase in micronucleated polychromatic
erythrocytes was observed. Mackay et al. (1995) concluded that the positive results previously
observed by Bhunya and Behera (1987) may have been due to a non-genotoxic mechanism,
possibly caused by physicochemically induced stress resulting from i.p. 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 SSBs in vivo in Sprague-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 SSBs by the alkaline unwinding assay.
Dose-dependent increases in SSBs 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 1 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 SSBs was evaluated by 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
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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 (six/group) were exposed to 0, 100, 500, or 2,000 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 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
(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. TCA-induced hepatic DNA strand breaks and chromosome
damage have been observed in two 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
etal., 1996).
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4.6. SYNTHESIS OF MAJOR NONCANCER EFFECTS
No epidemiologic data that evaluate TCA alone for noncancer effects in humans are
available. The experimental database for animals includes acute, short-term, subchronic, 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 peroxidation
response was reduced with pretreatment of TCA for 14 days (Austin et al., 1995). Decreased
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 PAS 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
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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
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 histopathologic 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 histopathologic 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 648-2,500% 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.
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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, increased cardiovascular
malformations at 291 mg/kg-day in Sprague-Dawley rats (Johnson et al., 1998), 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 GD 21 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 inbred
Charles Foster rats were treated with 1,000-1,800 mg/kg-day TCA on GDs 6-15. However,
these studies were limited by the administration of a higher dose range of TCA to rats than in 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 morphologic 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.
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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, 1995]; Parrish et al. [1996]).
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, since Kato-Weinstein et al. (2001) observed decreased glycogen content in
mice treated with TCA. Although TCA-induced changes in glycogen storage have not been well
studied, examination of DCA 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
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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 4.5.1.2,
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
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 mechanisms for developmental toxicity are unknown. However, TCA was found to
accumulate in amniotic fluid when pregnant rodents were exposed to TCE or tetrachloroethylene
(Ghantous et al., 1986). Thus, TCA may also have accumulated in amniotic fluid when pregnant
rodents were exposed to this chemical, because most of the parent compound remains
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 amniotic 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
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Singh (2006, 2005a, b). 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 embryonic 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 MOA 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.
U.S. EPA's Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a) indicate that
for tumors occurring at a site other than the initial point of contact, the weight of evidence for
carcinogenic potential may apply to all routes of exposure that have not been adequately tested at
sufficient doses. An exception occurs when there is convincing toxicokinetic data that
absorption does not occur by other routes. For TCA, systemic tumors were observed in mice
following oral exposure. Information on carcinogenic effects via the inhalation or dermal routes
in humans or animals is absent. Data evaluating absorption by the inhalation route are
unavailable and limited data are reported for dermal absorption (Kim and Weisel, 1998).
However, based on the observance of systemic tumors following oral exposure, and in the
absence of information to indicate otherwise, it is assumed that an internal dose will be achieved
regardless of the route of exposure. Therefore, TCA is "likely to be carcinogenic to humans" by
all routes of exposure.
4.7.2. Synthesis of Human, Animal, and Other Supporting Evidence
There are no epidemiologic 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
52-82 weeks (DeAngelo et al., 2008; Bull et al., 2004, 2002, 1990; Pereira, 1996; Pereira and
Phelps, 1996; Herren-Freund et al., 1987). Incidence of tumors increased with increasing TCA
concentrations (DeAngelo et al., 2008; Bull et al., 2002, 1990; Pereira, 1996). These results
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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 hours 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 (Yang et al., 2007; Ito et
al., 2007), such that the formation of liver tumors cannot be sufficiently accounted for by this
proposed MOA and the existence of other contributing MOA(s) is assumed.
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 (Pereira et al., 2001, 1996; Bull, 2000; Bull et al., 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
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several MO As 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.
TCA
Activation of
non-parenchymal
cells v
?\
Cell cycle growth
and apoptosis gene
expression
Inhibition of Activation of PPARa
intercellular if
communication
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.
4.7.3.1. Hypothesized Modes 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 or multiple MOA(s) capable of producing TCA
induced tumors is unknown.
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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 nonmutagenic 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 activated6 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 by using the prototypical PPARa agonist Wy-14643 (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,
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 RA receptor and thyroid
hormone receptor), co-activators, and co-repressors to regulate gene expression.
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 may include events such as loss of heat shock and chaperone proteins, nuclear translocation, and protein
turnover (Klaunig et al., 2003).
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4.7.3.1.1.1. Identification of key events. Klaunig et al. (2003) have proposed an 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 (Parzefall et al.,
2001; Rusyn et al., 2001, 2000; Hasmall et al., 2000), 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 events (i.e., required for this MOA) and associative events (i.e.,
markers of PPARa agonism but not shown to be directly involved with formation of liver
tumors). 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 MO As, 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
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.
The understanding of the PPARa agonism MOA 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 proliferatorWy-14643, including significantly decreased serum fatty acids and
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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 next
paragraph) suggested that PPARa agonists, such as Wy-14643, may regulate other genes in
addition to the gene for the VP16 PPARa fusion protein. These possibilities are being
investigated by researchers. To examine the role of Kupffer-cell-derived oxidants in the MO A
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.
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 a potential tumor suppressor (Zhang et al., 2007; Lee and Dutta,
2006) and to inhibit the expression of the ras oncogene (Johnson et al., 2005). Let-7C was
inhibited following treatment with 0.1% Wy-14643, a potent PPARa agonist, in wild-type mice
for 4 hours, 2 weeks, or 11 months. No decrease in let-7C miRNA was observed in the PPARa-
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 mRNA molecules, and they function to down-regulate gene expression.
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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-hour and 2-week Wy-14643
treatments. Moreover, pri-let-7C, AK033222, and pri-mir-99a were regulated in a PPARa-
dependent manner, since Wy-14643 had no effect on pri-let-7C, AK033222, or pri-mir-99a in
PPARa-null mice treated for 4 hours or 2 weeks. 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-7C 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 hours post-transfection, 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, co-transfection of let-7C and
c-myc increased cell proliferation in Hepa-1 cells compared with cells transfected with let-7C
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 other genes in addition to the gene for the VP16 PPARa fusion
proteins, or that activation of NPCs is critical for tumorigenesis and let-7C expression.
Moreover, let-7C was not 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 MOA 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;
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Gama-Sosa et al., 1983) and has been postulated to be a secondary mechanism involved in
carcinogenesis (Watson and Goodman, 2002). DNA hypomethylation is associated with opening
of the chromatin configuration and transcriptional activation, leading to chromosomal instability
and aberrant gene expression (Dunn, 2003; Baylin et al., 2001, 1998; Jones and Gonzalgo,
1997).
When male SV129 mice were fed a control diet or Wy-14643-containing diet
(1,000 ppm) 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 repeat (LTR) retrotransposone, and long
interspersed nucleotide elements (LINE) 1 and 2 (representing the non-LTR retrotransposons) in
liver DNA and found that exposure to Wy-14643 resulted in a gradual loss of cytosine
methylation in major and minor satellites, IAP, LINE1, and LINE2 elements. Previously,
gavage of female B6C3Fi 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., 2001b). No effect on c-myc promoter methylation was observed
with long-term treatment (Pogribny et al., 2007). Pogribny et al. (2007) concluded that
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
(Schulz et al., 2006; Chalitchagorn et al., 2004).
Pogribny et al. (2007) also found that 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 had produced no liver tumors,
whereas treatment of wild-type mice with 1,000 ppm Wy-14643 had resulted in 100% incidence
of hepatocellular adenomas and carcinomas (Peters et al., 1997). In addition, Wy-14643 had 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
hepatocarcinogenesis 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., 2001b), 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.
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(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 morphologic and biochemical evidence from multiple
studies. With respect to peroxisome proliferation, microscopic examination of responses
consistent with peroxisome proliferation (e.g., enzyme induction, increased liver weight) has
been observed in male F344 rats exposed to TCA by 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 gavage for
10 days (Goldsworthy and Popp, 1987), and in male C57BL/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 PPARa-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.
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 100-1,000 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 the pattern
of observed histopathologic changes, which indicated nodular areas of cellular proliferation, and
the results of liver DNA labeling experiments, which showed incorporation of [3H]thymidine in
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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
histopathologic 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 Sections 4.5.1.2 and 4.2.1.1. Dose-related increase in
incorporation of [3H]thymidine into hepatic DNA was observed in B6C3Fi 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 [3H]thymidine did not correlate with replicative
synthesis of DNA measured by autoradiography up to 5 days of treatment. Pereira (1996)
reported that TCA increased the BrdU-labeling index (calculated as the percentage of
hepatocytes with labeled nuclei) in mice exposed to 0.33-3.3 g/L TCA for 5 days but not after
12 or 33 days. Stauber and Bull (1997) reported a statistically significant two- to threefold
elevation in division rate in normal hepatocytes after male B6C3Fi 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 AHFs 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 B6C3Fi mice exposed to
5 g/L TCA at 30 and 40 weeks, with mice exposed to 0.5 g/L TCA demonstrating 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;
Yeldandi et al., 1989). It should also be noted that TCA did not induce hepatocyte proliferation
or tumors in F344 rats after 104 weeks of 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,
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2006), stated that "[t]here 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, B6C3Fi."
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, the authors 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 dose-
dependently increased 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, but 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 of a PPARa-independent pathway for tumorigenesis. Previously, Melnick (2001) has
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 B6C3Fi 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
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,
since increased expression of c-myc is common to both carcinogens and noncarcinogenic
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 (4,085 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
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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 (1,062 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 TC A-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 and 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. (2001b). Increase in DNA replication (evidenced by
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 MO A. However, because
hypomethylation is a relatively ubiquitous phenomenon in carcinogenesis and it has not been
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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 B6C3Fi 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 two- to threefold 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., 2008) 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 jiM, Lumpkin et al. (2003) report the plasma-bound fraction of TCA in
rats to be about four- to fivefold higher than in mice, while Templin et al. (1995, 1993) reported
this difference to be only about 1.1-fold.
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, on 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
nonspecific to peroxisome proliferators.. This suggests that PPARa agonism may not be the sole
MOA for TCA-induced tumors in mice.
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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 do spontaneous
tumors in B6C3Fi mice (11/46 versus 85/130 for MCP; 8/39 versus 32/50 for CPF) and their
mutation spectrums differed from those 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 is 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 1/11 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 1/23 CPF- induced and one MCP-induced hepatocarcinoma (the
number of samples examined was not provided), 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 in mouse liver tumors induced by the peroxisome proliferators furfural
and furan but the mutations were 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 MO A 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 (1996) reported that 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., 1995). 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 peroxisome proliferation. Thus, the
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 that progress to glycogen-poor, homogenously basophilic (ribosome
rich) phenotype in undifferentiated hepatocellular carcinomas; (2) tigroid-basophilic lineage:
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tigroid foci, a variant of glycogenotic foci (probably occurring at low dose), contain large
basophilic bodies on a clear or eosinophilic cytoplasmic background; (3) amphophilic-basophilic
cell lineage: amphophilic cells consist of glycogen-poor cytoplasm containing both abundant
granular-acidophilic (mitochondria and peroxisomes) and basophilic (ribosomes) components.
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. (1991, 1990) 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 eosinophilia (equivalent to amphophilic foci described earlier). In their experiments, using
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 (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, 1996), basophilic tumors
themselves are nonspecific to peroxisome proliferators.
With respect to immunostaining characteristics, the foci and tumors induced by
peroxisome proliferators have been noted to not express GGT and GST-u (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 GST-7i, 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 GST-u, consistent with that expected from peroxisome
proliferators. However, basophilic foci that are both GGT negative and GST-u 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
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 GST-u 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.
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However, tumors promoted by TCA in the experiments of Latendresse 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; Nakano et
al., 1994; Suzuki et al., 1990), both induction (Tharappel et al., 2003) and suppression
(Yokoyama et al., 1993) of c-Jun by short-term exposure to peroxisome proliferators have 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 MOA.
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). Specifically, a study by Yang et al. (2007) showed that ligand-independent
PPARa activation in hepatocytes evokes the MOA but not hepatocarcinogenesis 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 an
MOA for hepatocarcinogenesis as a sole causative factor, these newer data have raised
considerable doubt about the validity of this hypothesis for DEHP8. In addition, effects of TCA,
including increased c-myc expression and hypomethylation of DNA, are not specific to the
PPARa activation MOA, and other data also contribute uncertainty as to whether a PPARa-
independent MOA may be involved in TCA-induced tumors in mice.
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
8 The NRC (2008) report entitled Phthalates and Cumulative Risk Assessment: The Tasks Ahead states that
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 (2009) 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 PPARa activation MOA.
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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., 2008). 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 agoni sts.
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 or 5 g/L TCA for 30-60 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 weeks and in 0.5 g/L TCA group at 60 weeks. A small
increase in hepatocyte proliferation was found in the 0.05 g/L TCA group at 78 weeks. Doses of
0.3-3.3 g/L TCA that caused hepatocellular proliferation in short-term studies (Pereira, 1996;
Sanchez and Bull, 1990) were similar to the tumorigenic doses.
4.7.3.1.1.4. Human relevance. In its framework for making conclusions about human
relevance, the EPA cancer guidelines (U.S. EPA, 2005a) outline 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-
proliferating fibrate drugs (Klaunig et al., 2003). Klaunig et al. (2003) reached a conclusion
(reiterated in 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 pathway 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.
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Walgren et al. (2000) found that 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 Holden and Tugwood (1999) reported about 10-fold less
PPARa mRNA in human liver as compared with 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 compared with rodents, but expression levels were highly
variable among individuals and at least in one case were comparable to rodents' levels.
Moreover, expression levels may not be related to potency, since the hypolipidemic response to
PPARa agonists is similar in humans and rodents. On the other hand, humans and nonhuman
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 (Parzefall et al., 2001; Hasmall et al., 2000). In vivo, no increase in cell
proliferation was observed in nonhuman primates treated with PPARa agonists (Doull et al.,
1999), but no human data are available. Hoivik et al. (2004) noted that fenofibrate and CPF
induced treatment-related increases in liver weight, hypertrophy, numbers of peroxisomes, and
numbers of mitochondria and smooth endoplasmic reticulum in cynomolgus 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 (Shah et al., 2007;
Morimura et al., 2006; Cheung et al., 2004) using PPARa-humanized mice fed Wy-14643
suggested that structural differences in human and mouse PPARa receptors may be more
critical. 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 were 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
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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 RDS by measuring
BrdU incorporation into hepatocyte nuclei in hPPARa mice and wild-type mice after 8 weeks of
feeding with Wy-14643. In wild-type mouse livers, Wy-14643 treatment resulted in a BrdU
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 BrdU with average labeling indices of
2.8 and 1.6% in Wy-14643-treated and control 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, and 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 (five adenomas and two
carcinomas out of 7 mice; 3/10 treated mice died of toxicity). However, only 5% of Wy-14643-
treated hPPARa mice developed liver tumors (one adenoma out of 20 mice; the adenoma
resembled spontaneous tumor). In addition, up-regulation of cell cycle regulated genes, such as
cyclin Dl (cdl) and cyclin-dependent kinases (Cdks) 1 and 4, were observed in non-tumorous
liver tissues of Wy-14643-treated wild-type mice. The c-myc 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 and 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
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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 (Lumpkin et al., 2003; Templin et al., 1995). 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 susceptibility, 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." NRC (2006) also stated "Induction of
peroxisome proliferation in human liver is not a prominent feature; therefore, this key event
related to trichloroacetic acid liver carcinogenesis is not likely to occur in humans." 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 Science Advisory Board's review of EPA's draft risk
assessment of potential human health effects associated with perfluorooctanoic acid (PFOA) and
its salts (U.S. EPA, 2006c). The Science Advisory Board 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 agonism constitutes 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"; and (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
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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. 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
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 an 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 the 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
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, since 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
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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 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
B6C3Fi 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 ECso values were reported for
each of four measures of cytotoxicity, including potassium leakage, LDH, AST, and ALT
activities in the medium. Estimated ECso 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 B6C3Fi 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 trypan 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
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.
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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 (Latendresse
and Pereira, 1997; Pereira and Phelps, 1996; Parnell et al., 1988) 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 4.5.2. Most but not all studies (Kargalioglu et al., 2002; Nelson et
al., 2001; DeMarini et al., 1994; Rapson et al., 1980) report negative 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
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). 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
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this locus. The pattern of TCA-induced tumors in mice does not support a mutagenic MO A.
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 MO As 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., 2004, 2002, 1990; Bull,
2000; Pereira, 1996). Numerous recent studies have investigated the mechanism by which TCA
induces liver tumors. The data do not support a mutagenic 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.
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
1,000 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
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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 1,000 or 2,000 nmol (total dose,
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
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drinking water for a comparable duration (Bull, 2000; Bull et al., 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
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.
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5. DOSE-RESPONSE ASSESSMENTS
5.1. ORAL REFERENCE DOSE (RfD)
The RfD9 for TCA was derived through a three-step process: (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., 2008, 1997) 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 histopathologic 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 increased liver weight, liver peroxisome proliferation, hepatic
necrosis, and testicular tubular degeneration. Histopathologic 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 endpoints were evaluated, but a higher NOAEL of 78 mg/kg-day for
liver effects 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. (2008, 1997).
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 UFs 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, a 95% lower bound on exposure dose or concentration at 10% extra
risk) if the data are suitable for dose-response modeling.
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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-
134/group)
B6C3FJ mice
(11-24/sex
and dose)
B6C3FJ mice
(males, 22-
33/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
0, 78, 262, or
784
(A) 0, 164, or
329
(B) 0 or 309
0, 500, or 1,250
Decreased body weight,
increased serum ALT
activity; increased
peroxisome proliferation
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.
Subchronic studies
Mather et
al. (1990)
Sprague-
Dawley rats
(males,
10/dose)
Oral,
drinking
water
90 days
0,4.1, 36.5, or
355
Decreased absolute spleen
weight; increased relative
liver and kidney weights;
peroxisome proliferation
36.5
355
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Table 5-1. Candidate studies for derivation of the RfD for TCA
Reference
Bhat et al.
(1991)
Species
Sprague-
Dawley rats
(males,
5/group)
Exposure
route
Oral,
drinking
water
Exposure
duration
90 days
Doses evaluated
(mg/kg-day)
0 or 825
Observed effects
Decreased body weight gain;
minor changes in liver
morphology; collagen
deposition; perivascular
inflammation of the lungs
NOAEL
(mg/kg-day)
None
LOAEL
(mg/kg-day)
825
Comments
l/4oftheLD50
(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,
1,200, or 1,800
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
resorption sites/litter, and
total resorptions
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.
Values of 28 and 3 1 mg/kg-
day for the 95% lower
bound of the effective dose
at 10% extra risk (LED10)
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
standard developmental end
points was not assessed.
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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
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
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 (2003). Additional details on these studies are provided in Section 4 of this document.
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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
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 LD50 of 3,300 mg/kg (or approximately 825 mg/kg-day).
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 that
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 (DeAngelo et al., 1997; Mather et al.,
1990). In addition, complete histopathologic 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 benchmark dose (BMD)
modeling.
Selected data from the developmental toxicity study conducted by Smith et al. (1989)
were analyzed by 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 incidence
data for fetuses with visceral malformations (of which levocardia was the principal lesion), data
on fetal body weight and fetal crown-rump length, and litter incidence data for levocardia.
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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 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., benchmark dose [BMDio] and 95% lower confidence limit on
the benchmark dose [BMDLio]) associated with a benchmark response (BMR) of 10% extra risk
were calculated and are presented in Tables 5-2 through 5-4. 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 5-4 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 the goodness-of-fit criterion) and the
Akaike's Information Criterion (AIC) value (i.e., a measure of the deviance of the model fit that
allows for comparison across models for a particular endpoint). Of the models exhibiting
adequate fit, the model yielding the lowest AIC value was selected as the best-fit model. If more
than one model shared the lowest AIC, BMDLio values from these models were averaged to
obtain a POD (U.S. EPA, 2000b).
For hepatocellular inflammation, Table 5-2 shows that the logistic, one-stage multistage,
probit, and log-probit models all exhibited adequate fit. Because the logistic and log-probit
models shared the lowest AIC value (i.e., 74.19), the BMDLios from these two models were
averaged to yield a candidate POD of 260.5 mg/kg-day. As shown in Table 5-3, four of the
seven dichotomous models in BMDS fit to the incidence of hepatocellular necrosis in male mice
exhibited adequate fit. These four models were the gamma, log-logistic, one-stage multistage,
and Weibull models. Among these four models, the gamma, one-stage multistage, and Weibull
models yielded identical fits, essentially reducing the number of adequately fitting models to
two. The log-logistic model yielded the lowest AIC value (i.e., 30.42) of the two adequate fit
models. Thus, the BMDLio of 18 mg/kg-day estimated by the log-logistic model was selected as
a candidate POD. Finally, as shown in Table 5-4, all of the models fit to the incidence of
testicular tubular degeneration exhibited adequate fit. Of these seven models, the gamma, one-
stage multistage, and Weibull models yielded identical fits, essentially reducing the number of
adequately fitting models to five. The log-logistic 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
a candidate POD. Of the three endpoints under consideration, hepatocellular necrosis was the
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most sensitive, as it yielded the lowest POD of 18 mg/kg-day. Therefore, 18 mg/kg-day was
selected as the POD for use in derivation of the RfD.
Table 5-2. BMD 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/7-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
aAll dichotomous dose-response models were fit using BMDS, version 1.4.1. The best-fit models are
indicated in boldface type.
kp-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.
°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.
dBMD10 = Benchmark dose at 10% extra risk.
eBMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
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Table 5-3. BMD 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, Multistage
(1°), and Weibull
Logistic
Log-Logistic
Probit
Log-Probit
Chi-Square Goodness-
of-Fit Test/>-Valueb
0.18
0.058
0.49
0.060
0.036
AICC
31.85
36.39
30.42
36.26
36.84
BMD10d
(mg/kg-day)
64.9
205.1
40.7
188.0
158.7
BMDL10e
(mg/kg-day)
37.6
128.4
17.9
120.0
54.3
aAll dichotomous dose-response models were fit using BMDS, version 1.4.1. The best-fit model is indicated
in boldface type.
bp-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.
°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.
dBMD10 = Benchmark dose at 10% extra risk.
eBMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
Table 5-4. BMD 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, Multistage
(1°), and Weibull
Logistic
Log-Logistic
Probit
Log-Probit
Chi-Square Goodness-
of-Fit Test/7-Valueb
0.19
0.16
0.19
0.17
0.13
AICC
76.16
76.59
76.08
76.54
77.06
BMD10d
(mg/kg-day)
321.9
439.7
298.2
425.3
471.6
BMDL10e
(mg/kg-day)
153.3
290.3
127.4
271.2
276.8
aAll dichotomous dose-response models were fit using BMDS, version 1.4.1. The best-fit model is indicated
in boldface type.
bp-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.
°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.
dBMD10 = Benchmark dose at 10% extra risk.
eBMDL10 = 95% lower confidence limit on the benchmark dose at 10% extra risk.
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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 5-5) 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 interindividual correlation of toxicity endpoints within litters. Supporting
information for the BMD analyses is provided in Appendix C. The fetal data analyzed were
quantal incidence data for fetuses with visceral malformations (of which levocardia was the
principal lesion) and 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 interindividual 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 an assumption
that the data (either body weight or crown-rump length) were normally distributed and 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 x SD, where za is
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 is the standard deviation of the mean of the control group.
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Table 5-5. Dose response data for developmental endpoints in TCA-treated
Long-Evans rats (Smith et al., 1989)
Endpoint
Dose (mg/kg-day)
0
330
800
1,200
1,800
Quantal data
Fetuses with visceral malformations
Fetal incidence3'13
Litter incidence13'0
Mean % fetuses affected per litter0
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
aFetal incidence = number of fetuses affected/number of fetuses examined.
Unpublished 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).
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
below the critical value). SDs 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-Utter 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).
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Three nested models, each of which included dose and litter size as explanatory variables
and accounted for intralitter correlation by assuming a p-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 (TERALOG, TERAVAN, and TERAMOD) (developed based on the three papers
cited above by Richard Howe 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
-------
and 241 mg/kg-day for crown-rump length <3.4 cm. The average BMDos and BMDLos
(calculated from the values obtained by 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.
Table 5-6. BMD modeling results for fetal incidence data (Smith et al., 1989)
Model
BMD05a
(mg/kg-day)
BMDLosb
(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-ramp length) were converted to quanta! 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-ramp length, or visceral malformations.
bBMDL05, BMDL10 = 95% lower confidence limits for the respective BMD05 or BMD10 values.
Litter incidence data (number of affected litters/number of litters examined) for
levocardia (Table 5-7) were modeled using U.S. EPA's BMDS (version 1.3.1) 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 BMDS
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 5-7), as judged by 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
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model) and observed incidence of levocardia as a function of administered dose, as well as the
BMDos and the BMDLos. The BMDos and BMDLos values estimated for the litter incidence of
levocardia by these models were 42 and 31 mg/kg-day (rounded values), respectively. It should
be noted that 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 5-7. BMD modeling results for litter incidence of levocardia (Smith et
al., 1989)
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
0.0520b
0.0449b
AIC
69.8459
69.8459
71.6069
71.6259
71.8203
80.642
80.6568
BMDos
42
42
74
87
36
144
136
BMDLos
31a
31a
17
9
1
101
99
BMD10
86
86
122
130
76
253
244
BMDL10
64a
64a
36
20
5
187
185
""Preferred model(s) based on criteria described in U.S. EPA (2000d).
bBecause 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.
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Gamma Multi-Hit Model with 0.95 Confidence Level
1
I 0.6
<
.1 0.4
ro
it 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 levocardiain
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 by 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- 1,000
= 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 1,000 = composite UF chosen
to account for extrapolation from animals to humans, interindividual variability in humans, and
insufficiencies in the database (see below).
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 BMDLos value for
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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 1,000 would result in an RfD
of 0.03 mg/kg-day (i.e., a value 50% higher than the one obtained by using the POD based on
hepatocellular necrosis). Because these alternative 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 10 to account for deficiencies in the TCA database. The total
UF= 10 x 10 x 10 = 1,000.
The UFs used in the 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.
• 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.
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5.1.4. RfD Comparison Information
The RfD derived from the DeAngelo et al. (2008) mouse study was compared with
potential RfDs derived from the DeAngelo et al. (1997) rat study and the Smith et al. (1989) rat
study. The RfDs derived from these studies are similar (Figure 5-2).
Rat Liver
(DeAngelo etal., 1997)
Mouse Liver
(DeAngelo et al., 2008)
Target Organ or Endpoint
Rat Developmental
(Smith etal., 1989)
Figure 5-2. Comparison of RfDs across target organs or endpoints.
5.1.5. Previous RfD Assessment
The previous IRIS assessment for TCA did not provide 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.
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.
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5.3. UNCERTAINTIES IN THE ORAL REFERENCE DOSE
The following discussion identifies uncertainties associated with the RfD for TCA. As
presented in Section 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 the 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 (DeAngelo et al., 2008) was the most complete study in
mice, with well-defined NOAEL/LOAEL and data that were amenable to dose-response
modeling. Complete histopathologic examination was conducted for the high-dose and control
groups. Liver toxicity, specifically hepatocellular necrosis, was selected as the critical effect for
the 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
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 the latter 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.
Interhuman 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
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sensitive than female mice to the 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 interhuman
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
evaluated the carcinogenicity of TCA in humans. The carcinogenicity of TCA has been
evaluated, however, in several 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., 2002, 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 (Pereira, 1996; Bull et al., 2002, 1990; DeAngelo et al., 2008).
Moreover, the development of tumors in animals exposed to TCA progressed rapidly, as evident
from the appearance of significant numbers of tumors in several of the less-than-lifetime studies
(i.e., 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 in 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.
As discussed in Section 4.7.3, data from recent TCA studies that have investigated the
MOA for hepatocarcinogenesis do not support a direct mutagenic mechanism. Instead, tumor
induction appears to result from perturbation of cell growth and/or reduced intracellular
communication, possibly through a PPARa MOA. Considerable debate currently exists about
the mechanism by which peroxisome proliferators cause liver tumors in rodents, and whether
these chemicals represent a human cancer risk (NRC, 2006). Much of the experimental data on
TCA is consistent with a PPARa-mediated MOA (NRC, 2006). In this document, two
alternative interpretations of available data were considered in order to evaluate current scientific
uncertainties with respect 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 suggest a number of potentially interrelated MO As. While PPARa-mediated
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effects appear to play a role in the induction of some rodent liver tumors, certain inconsistencies
in the data exist. Unresolved issues for PPARa as a MO A for TCA-induced liver tumors
include: inconsistencies in experimental results across species, sex, and PPARa agonists; some
proposed key events are not specific to PPARa; the lack of clear dose concordance between
proposed key events and tumor response; 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 progress has been made recently in filling gaps in the
understanding of this potential MO A, 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 determination
that TCA is "likely to be carcinogenic to humans," with subsequent use of the default linearly
extrapolated dose-response analysis.
An alternative 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, a weight of
evidence determination could be either "likely or unlikely to be carcinogenic to humans"
depending on the relative cross-species (mouse to human) differences in toxicokinetic or
toxicodynamic sensitivity. Humans have functional PPARa receptors as evidenced by PPARa-
mediated responses to the therapeutic fibrate class of 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 of these possible kinetic and dynamic
factors, this effort is by no means comprehensive. Further efforts in this regard are outside the
scope of this TCA Toxicological Review.
As new data become available, conclusions regarding the MOA for TCA-induced liver
tumors may change. For instance, if key events are identified that support a nonlinear dose-
response relationships below those doses 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 which cross-species
sensitivity were known quantitatively, then the dose-response assessment could be conducted to
account for the relative sensitivity between humans and mice to TCA-induced tumors. Finally, if
it were shown that one or more key events in TCA-induced tumorigenesis were precluded in
humans, then the weight-of-evidence determination would be changed to "not likely to be
carcinogenic in humans."
In conclusion, TCA has been determined to be "likely to be carcinogenic to humans"
under EPA's Guidelines for Carcinogen Assessment (U. S. EPA, 2005a). Three lines of evidence
support this determination: 1) TCA is carcinogenic in the liver in multiple studies conducted in
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B6C3Fi mice of both sexes; 2) the tumor response was robust, occurring at substantially less-
than-lifetime exposures at which tumor rates in control animals were relatively low; and 3) there
are data gaps that preclude a decision 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 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). In addition, no data were found that were suitable for
accounting for inter-species differences in toxicokinetics or toxicodynamics in dose-response
modeling.
5.4.1. Choice of Study/Data—with Rationale and Justification
Using 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., 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 from these studies for adenomas, carcinomas, and adenomas
and carcinomas combined are presented in the next section.
These studies in mice cited above 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 exposure levels 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 5-8 through 5-12, and were fit using the multistage model in BMDS (version
1.4.1).
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Table 5-8. 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 B6C3F! 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 5-9. 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., 1990)
TCA concentration"
(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 5-10. 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
(g/L)
0
0.05
0.5
5
Estimated
daily intake"
(mg/kg-day)
0
8
68
602
Human lifetime
equivalent doseb
(mg/kg-day)
0
0.24
2.07
18.3
Incidence of
adenomas0
2/30
4/27
6/29
11/29
Incidence of
carcinomas0
2/30
1/27
6/29
11/29
Incidence of
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.
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Table 5-11. 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 B6C3FJ 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 5-12. 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 5-8 through 5-12, 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
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
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in the 104-week study of DeAngelo et al. (2008) (Table 5-12) 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 5-8 through 5-12.
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), as well as by examining the visual fit of the
model to the data. Plots of 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 5-13 for a summary and the BMDS
computer outputs in Appendix D for further details). For those models that did not exhibit
significant lack of fit (chi-square/*-value > 0.1), the fitted model was used to estimate the human
equivalent lifetime dose associated with 10% extra risk (EDio), and its corresponding 95% lower
bound (LEDio) (Table 5-13). Candidate oral cancer slope factors were derived by linear
extrapolation from the LEDio, i.e., 0.1/LEDi0. Slopes from the linear extrapolation from the
were also calculated, i.e., 0.1/EDi0 (Table 5-13).
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Table 5-13. Candidate oral cancer slope factors derived from cancer bioassays in
B6C3Fi mice
Study Reference
(study duration)
ED10
(mg/kg-day)a
LED10
(mg/kg-day)a
/2 goodness-
of-fit
/7-value
Slope of linear
extrapolation
from ED10b
(mg/kg-day) *
Oral cancer
slope factor0
(mg/kg-day)1
Male Mice
Bull et al., 2002 (52 weeks)
Bulletal., 1990 (52 weeks)
DeAngelo et al., 2008
(60 weeks)
DeAngelo et al., 2008
(104 weeks)
1.41
1.97
2.83
0.89
0.93
1.19
1.71
0.50
0.16
0.12
0.15
0.32
7.1x 1Q-2
5.1 x 10"2
3.5 x 10'2
l.lx 10'1
1.1 x 1Q-1
8.4 x 10"2
5.8 x 10'2
2.0 x 10'1
Female Mice
Pereira, 1996 (82 weeks)
7.14
4.96
0.5
1.4 x 10"2
2.0 x 10"2
aED10 and LED10 were derived from the one-stage multistage model.
bThe slope of a linear extrapolation from the ED10 is calculated as follows: 0.1/ED10.
°The oral cancer slope factor is derived by linearly extrapolating from the LED10 (i.e., 0.1/LED10).
As discussed in Section 4.7.3, studies investigating the 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.
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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 typically derived by linear extrapolation from the LEDio (i.e., 0.1/LEDi0) (U.S. EPA,
2005a). The estimated oral cancer 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
5-13).
Candidate oral cancer slope factors were derived from male mice studies with durations
ranging 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 is generally 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.
The slopes of the linear extrapolation from the EDio, 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,
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). Based on the
study of longest duration (the 104-week data from DeAngelo et al., 2008), the slope of the linear
extrapolation from the EDio 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. Previous Cancer Assessment
In the previous cancer assessment of TCA posted to the IRIS database in 1996, TCA was
classified as a "C," or "possible human carcinogen." This classification was based on a lack of
human data, limited evidence of an increased incidence of liver neoplasms in both sexes of one
strain of mice, and no evidence of carcinogenicity in rats. The previous IRIS assessment did not
provide quantitative estimates of carcinogenic risk from oral or inhalation exposure to TCA.
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6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HAZARD AND DOSE
RESPONSE
6.1. HUMAN HAZARD POTENTIAL
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.
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 intravenous
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 CYP450 enzymes through the dichloroacetate radical intermediate, but, in general,
enzymes involved in TCA metabolism are poorly characterized. The primary route of excretion
of TCA is in the urine, with exhalation of CO2 and fecal excretion contributing to a lesser extent.
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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,
histopathologic 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 MO As 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
lesions 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.
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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 IRIS assessment of TCA, TCA was classified as a "C," or a "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
B6C3Fi mice of both sexes; (2) tumor response was robust, occurring at substantially less-than-
lifetime exposures at which tumor rates in control animals were relatively low; and (3) there are
data gaps that preclude a determination that the MOA for hepatocarcinogenesis in mice is not
relevant to humans. Finally, two significant limitations of the database for TCA carcinogenicity
are the limited number of mouse studies that included microscopic evaluation of a
comprehensive set of organs in addition to the liver and 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). In addition, no
data were found that were suitable for accounting for interspecies 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 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 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
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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
glyoxylate-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 B6C3Fi
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. Figure 5-2 shows
a comparison of these three candidate 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 complete histopathologic 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. Overall confidence in the RfD is medium, reflecting these
considerations.
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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 physiologically based pharmacokinetic (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 KT1, 8.4 x l(T2, 5.8 x l(T2, 2.0 x KT1, 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). These candidate oral slope factors vary over one
order of magnitude, with the 104-week tumor incidence data from DeAngelo et al. (2008)
yielding the highest potency. The oral cancer slope factor of 2 x 10"1 per mg/kg-day derived
from the 104-week bioassay in male B6C3Fi mice (DeAngelo et al., 2008) is recommended as
the oral cancer slope factor for TCA.
To derive these oral cancer slope factors, the average daily intakes of TCA from the
mouse studies were converted to human equivalent lifetime doses by using an interspecies
scaling 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 increased 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 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 (LEDios).
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 mutagenic MOA and suggest that tumor induction may
involve perturbation of cell growth through PPARa agonism and reduced intercellular
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communication. However, current understanding is insufficient to determine which, if any, of
these MO As 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.
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APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC
COMMENTS AND DISPOSITION
[to be added]
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APPENDIX B. BENCHMARK DOSE MODELING RESULTS FOR THE INCIDENCE
OF 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 B-l.l. 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
aAll dichotomous dose-response models were fit using BMDS, version 1.4.1. The best-fit models are
indicated in boldface type.
kp-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.
°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.
dBMD10 = Benchmark dose at 10% extra risk.
eBMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
Of the seven models fit, 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.
B-l
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Logistic Model with 0.95 Confidence Level
T3
-------
the user,
intercept
slope
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
intercept slope
1 -0.76
-0.76 1
Variable
Limit
intercept
1.91338
slope
0.00499983
Parameter Estimates
95.0% Wald Confidence Interval
Estimate
-2.85931
0.00284529
Std. Err.
0.482625
0.00109927
Lower Conf. Lim
-3.80523
0.000690752
Upper Conf.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
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
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 391.918
BMDL = 276.646
B-3
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Multistage Model with 0.95 Confidence Level
ts
£
<
o
ts
CD
0.4
0.3
0.2
0.1
Multistage
BMD
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\MALE_MOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEAMGELO_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
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 = 0.0486161
Beta(l) = 0.000374222
B-4
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Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background 1 -0.52
Beta(l) -0.52 1
Limit
Variable
Background
Beta (1)
Parameter Estimates
Estimate
0.051295
0.000360853
95.0% Wald Confidence Interval
Std. Err. Lower Conf. Limit Upper Conf.
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 Test d.f.
4.17486
10.8276
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 =
Risk Type
Confidence level =
BMD =
BMDL =
BMDU =
0.1
Extra risk
0.95
291.976
149.431
928.712
Taken together, (149.431, 928.712) is a 90
interval for the BMD
two-sided confidence
B-5
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Probit Model with 0.95 Confidence Level
T3
0
ts
£
<
o
ts
CD
0.4
0.3
0.2
0.1
Probit
BMDL
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\MALE_MOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEAMGELO_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
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 = 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
intercept = -1.7688
slope = 0.0018081
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
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-------
the user,
intercept
slope
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
intercept slope
1 -0.69
-0.69 1
Variable
Limit
1.1638
intercept
0.00264235
slope
Parameter Estimates
95.0% Wald Confidence Interval
Estimate
-1.60927
0.00150498
Std. Err.
0.227286
0.000580302
Lower Conf. Lim
-2.05474
0.000367607
Upper Conf.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-33.0575
-35.0988
-38.4712
74.1975
# Param' s
4
2
1
Deviance
4.08263
10.8276
Test d.f.
2
3
P-value
0.1299
0.0127
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
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 376.053
BMDL = 257.089
B-7
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Probit Model with 0.95 Confidence Level
T3
0
ts
£
<
o
ts
CD
0.4
0.3
0.2
0.1
Probit
PMDL
100
200
300
dose
400
500
600
12:1409/052008
Probit Model. (Version: 2.9; Date: 09/23/2007)
Input Data File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_HEPATOCELLULAR_INFLAMMATION_60_WKS_DEAMGELO_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
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 = 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 (and Specified) Parameter Values
background = 0.1
intercept = -7.0776
slope = 1
B-S
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Asymptotic Correlation Matrix of Parameter Estimates
the user,
background
intercept
*** The model parameter(s) -slope
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
background intercept
1 -0.26
-0.26 1
Variable
Limit
background
0.107338
intercept
6.63563
slope
NA - Indicates that this parameter has hit a bound
implied by some ineguality constraint and thus
has no standard error.
Parameter Estimates
95.0% Wald Confidence Interval
Upper Conf.
Estimate
0.0576569
-7.25815
1
Std. Err.
0.0253479
0.31762
NA
Lower Conf. Lim
0.00797583
-7.88067
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-33.0575
-35.0974
-38.4712
74.1948
# Param's
4
2
1
Deviance Test d.f.
4.07991
10.8276
P-value
0.13
0.0127
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 =
Risk Type
Confidence level =
BMD =
BMDL =
0.1
Extra risk
0.95
394.098
244.412
B-9
DRAFT - DO NOT CITE OR QUOTE
-------
Table B-1.2. 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, Multistage (1°),
and Weibull
Logistic
Log-Logistic
Probit
Log-Probit
Chi-Square Goodness-
of-Fit Test^-Valueb
0.18
0.058
0.49
0.060
0.036
AICC
31.85
36.39
30.42
36.26
36.84
BMD10d
(mg/kg-day)
64.9
205.1
40.7
188.0
158.7
BMDL10e
(mg/kg-day)
37.6
128.4
17.9
120.0
54.3
aAll dichotomous dose-response models were fit using BMDS, version 1.4.1. The best-fit models are
indicated in boldface type.
kp-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.
°AIC = Akaike's Information Criteria, a value useful for evaluating model fit. For those models exhibiting
adequate fit, lower values of the AIC suggest better model fit.
dBMD10 = Benchmark dose at 10% extra risk.
eBMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
Of the seven models fit, 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.
B-10
DRAFT - DO NOT CITE OR QUOTE
-------
Gamma Multi-Hit Model with 0.95 Confidence Level
T3
0
t>
it
^
0
TO
it
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
\ Gamrric
i Multi-Hit
~- -•- --
? ^
L J ^^^A \
: ^^-~-~~~^ :
r
^
^_^_---^^^ :
^^~~^~^ H
^^^^^ \
,~^~^^ '-_
: ^^ | ,^ :
E- ,~^~^^ :-
\ ^^ I :
:
: | | l^
^ BMDlJ
^ 1 j
/^ '-
K
BMQ , , , , ;
0 100 200 300 400 500 600
dose
14:1809/052008
Gamma Model. (Version: 2.11; Date: 10/31/2007)
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.plt
Fri Sep 05 14:18:47 2008
BMDS MODEL RUN
The form of the probability function is:
P[response]= background+(1-background)*CumGamma[slope*dose,power],
where CumGamma(.) is the cumulative 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 = 0.0454545
Slope = 0.00722137
Power = 1.3
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background -Power
B-11 DRAFT - DO NOT CITE OR QUOTE
-------
the user,
Slope
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
Slope
1
Parameter Estimates
Interval
Variable
Limit
Background
Slope
0.00277512
Power
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
Estimate
0
0.00162275
1
Std. Err.
NA
0.000587954
NA
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
0.000470383
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-13.0401
-14.925
-20.0161
31.8499
# Param's
4
1
1
Deviance Test d.f.
3.76969
13.952
P-value
0.2874
0.002971
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
=4.87
d.f. = 3
P-value = 0.1818
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 64.9271
BMDL = 37.5509
B-12
DRAFT - DO NOT CITE OR QUOTE
-------
Log-Logistic Model with 0.95 Confidence Level
0.8
0.7
0.6
T3
0
I °'5
< 0.4
g
jo °-3
LJ_
0.2
0.1
0
Log-Lot
\
r
I
r
^
BMPLI
"
"v
^istic ;
^
^-^ \
> // \
// I :
/ 1 j
L J
BMD, , , , , , , ;
0
100 200 300 400 500 600
dose
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.plt
Fri Sep 05 14:21:36 2008
BMDS MODEL RUN
The form of the probability function is:
P[response] = background+(1-background)/[1+EXP(-intercept-slope*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
background = 0
intercept = -5.96722
slope = 1
Asymptotic Correlation Matrix of Parameter Estimates
*** The model parameter(s) -background
-slope
B-13
DRAFT - DO NOT CITE OR QUOTE
-------
the user,
intercept
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
intercept
1
Parameter Estimates
Interval
Variable
Limit
background
intercept
slope
Estimate
-5.90256
1
Std. Err.
* - Indicates that this value is not calculated.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-13.0401
-14.2076
-20.0161
30.4152
# Param's
4
1
1
Deviance Test d.f.
2.33493
13.952
P-value
0.5059
0.002971
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.
P-value = 0.4927
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 40.6639
BMDL = 17.8767
B-14
DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
T3
0
t>
it
^
0
TO
it
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
o
w
\ Multista
9e ;
~ -^— -
E- -E
i y ^^^A \
: ^^-~-~~~^ :
r
^
^^^^^ :
^^~~^~^ \
^^^^^ \
,~^~^^ '-_
: ^^ | ,^ :
E- ,~^~^^ :-
\ ^^ I :
:
: | | l^
E JJ/^1
^ BMDlJ
^ 1 j
/^ '-
K
BMQ , , , , ;
0 100 200 300 400 500 600
dose
14:2309/052008
Multistage Model. (Version: 2.8; Date: 02/20/2007)
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.plt
Fri Sep 05 14:23:03 2008
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*dose/xl) ]
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 = 0.0817489
Beta(l) = 0.00104526
B-15
DRAFT - DO NOT CITE OR QUOTE
-------
Asymptotic Correlation Matrix of Parameter Estimates
the user,
Beta(l)
*** The model parameter(s) -Background
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
Beta(l)
1
Parameter Estimates
Interval
Variable
Limit
Background
Beta (1)
Estimate
0
Std. Err.
0.00162275 *
* - Indicates that this value is not calculated.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-13.0401
-14.925
-20.0161
31.8499
# Param's
4
1
1
Deviance Test d.f.
3.76969
13.952
P-value
0.2874
0.002971
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
Benchmark Dose Computation
P-value = 0.1818
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
BMDU =
0.1
Extra risk
0.95
64.9271
37.5509
167.542
Taken together, (37.5509, 167.542) is a 90
interval for the BMD
% two-sided confidence
B-16
DRAFT - DO NOT CITE OR QUOTE
-------
Weibull Model with 0.95 Confidence Level
T3
0
t>
it
^
0
TO
it
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
! Weibull
~- -•- --
? ^
i y ^^^A \
: ^^-~-~~~^ :
r
^
^_^_---^^^ :
^^~~^~^ H
^^^^^ \
,~^~^^ '-_
: ^^ | ,^ :
E- ,~^~^^ :-
\ ^^ I :
:
: | | l^
^ BMDlJ
^ 1 j
-^^^^ :
K
BMQ , , , , ;
0 100 200 300 400 500 600
dose
14:2809/052008
Weibull Model using Weibull Model (Version: 2.10; Date: 10/31/2007)
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.plt
Fri Sep 05 14:28:13 2008
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*dose/xpower)]
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 = 0.0454545
Slope = 0.00107413
Power = 1
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background -Power
B-17
DRAFT - DO NOT CITE OR QUOTE
-------
the user,
Slope
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
Slope
1
Parameter Estimates
Interval
Variable
Limit
Background
Slope
0.00277512
Power
NA - Indicates that this parameter has hit a bound
implied by some inequality constraint and thus
has no standard error.
Estimate
0
0.00162275
1
Std. Err.
NA
0.000587954
NA
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
0.000470384
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-13.0401
-14.925
-20.0161
31.8499
# Param's
4
1
1
Deviance Test d.f.
3.76969
13.952
P-value
0.2874
0.002971
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
=4.87
d.f. = 3
P-value = 0.1818
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 64.9271
BMDL = 37.5509
B-18
DRAFT - DO NOT CITE OR QUOTE
-------
Table B-1.3. 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, Multistage (1°),
and Weibull
Logistic
Log-Logistic
Probit
Log-Probit
Chi-Square Goodness-
of-Fit Test^-Valueb
0.19
0.16
0.19
0.17
0.13
AICC
76.16
76.59
76.08
76.54
77.06
BMD10d
(mg/kg-day)
321.9
439.7
298.2
425.3
471.6
BMDL10e
(mg/kg-day)
153.3
290.3
127.4
271.2
276.8
aAll dichotomous dose-response models were fit using BMDS, version 1.4.1. The best-fit models are
indicated in boldface type.
kp-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.
°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.
dBMD10 = Benchmark dose at 10% extra risk.
eBMDLio = 95% lower confidence limit on the benchmark dose at 10% extra risk.
All seven models showed adequate fit. The BMDS outputs from these seven models are
provided below.
B-19
DRAFT - DO NOT CITE OR QUOTE
-------
Gamma Multi-Hit Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
0
I °'25
< 0.2
g
| 0.15
ul
0.1
0.05
0
: r* R/I if Lj-t ' ' ' ' :
- oamma Multi-nit :
r T 1
^ ^
i T ;
; ~$ ^^^-^T^^^ ]
r i ^^^-~~^^^ 1 ;
1 |U-^1 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_DEAMGELO_2008.(d)
Gnuplot Plotting File: M:\TCA DOSE-RESPONSE
MODELING\MALE_MOUSE_TESTICULAR_DEGENERATION_60_WKS_DEANGELO_2008.plt
Fri Sep 05 13:47:08 2008
BMDS MODEL RUN
The form of the probability function is:
P[response]= background+(1-background)*CumGamma[slope*dose,power],
where CumGamma(.) is the cumulative 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
Power = 1.3
Asymptotic Correlation Matrix of Parameter Estimates
*** The model parameter(s) -Power
B-20
DRAFT - DO NOT CITE OR QUOTE
-------
the user,
Background
Slope
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
Background Slope
1 -0.45
-0.45 1
Variable
Limit
Background
0.112294
Slope
0.000690665
Power
NA - Indicates that this parameter has hit a bound
implied by some ineguality constraint and thus
has no standard error.
Parameter Estimates
95.0% Wald Confidence Interval
Upper Conf.
Estimate
0.0556454
0.000327288
1
Std. Err.
0.028903
0.000185399
NA
Lower Conf. Lim
-0.0010035
-3.60877e-005
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.
4.62871
9.40833
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
= 3.34
d.f. = 2
P-value = 0.1882
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 321.919
BMDL = 153.274
B-21
DRAFT - DO NOT CITE OR QUOTE
-------
Logistic Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
0
I °'25
c 0.2
g
ro 0.15
ul
0.1
0.05
0
:'....' ' ' ' ' :
I LOQIStIC :
r T 1
^ ^
f T j
I T ^^t ^
\ ^X— -^^^^ L
f ii ^ ^
! 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_DEAMGELO_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
BMDS 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
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
B-22
DRAFT - DO NOT CITE OR QUOTE
-------
the user,
intercept
slope
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
intercept slope
1 -0.72
-0.72 1
Interval
Variable
Limit
intercept
1.80303
slope
0.00441519
Estimate
-2.68463
0.00229179
Parameter Estimates
Std. Err.
0.449806
0.00108339
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
-3.56623
0.000168388
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.7671
-36.2929
-38.4712
76.5859
# Param's Deviance Test d.f. P-value
4
2 5.05173 2 0.07999
1 9.40833 3 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
=3.63
d.f. = 2
P-value = 0.1630
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 439.685
BMDL = 290.255
B-23
DRAFT - DO NOT CITE OR QUOTE
-------
Log-Logistic Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
0
I °'25
c 0.2
g
ro 0.15
ul
0.1
0.05
0
:'.....' ' ' ' ' :
i Log- Logistic :
r T 1
^ ^
f T j
; J-^^^ x ;
1 |U-^1 j
1
! B^DlJ , PMD , , ;
0 100 200 300 400 500 600
dose
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_DEAMGELO_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
BMDS MODEL RUN
The form of the probability function is:
P[response] = background+(1-background)/[1+EXP(-intercept-slope*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
background = 0.0666667
intercept = -7.67626
slope = 1
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -slope
B-24
DRAFT - DO NOT CITE OR QUOTE
-------
the user,
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
background intercept
background 1 -0.47
intercept -0.47 1
Parameter Estimates
Interval
Variable
Limit
background
intercept
slope
Estimate
0.0540864
-7.89489
1
Std. Err.
* - Indicates that this value is not calculated.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.7671
-36.0406
-38.4712
76.0812
# Param's Deviance Test d.f. P-value
4
2 4.54705 2 0.1029
1 9.40833 3 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
= 3.27
d.f. = 2
P-value = 0.1945
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 298.169
BMDL = 127.35
B-25
DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
0
I °'25
c 0.2
g
ro 0.15
ul
0.1
0.05
0
:' ......' ' ' ' ' :
i Multistage :
r T 1
^ ^
f T j
; ^ M ^^^-^T^^^ ]
| jp^l j
i 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_DEAMGELO_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
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*dose/xl) ]
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 = 0.0609653
Beta(l) = 0.00029145
B-26
DRAFT - DO NOT CITE OR QUOTE
-------
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background 1 -0.56
Beta(l) -0.56 1
Interval
Variable
Limit
Background
Beta (1)
Parameter Estimates
Estimate
0.0556454
0.000327288
Std. Err.
Indicates that this value is not calculated.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
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.
4.62871
9.40833
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
Benchmark Dose Computation
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
BMDU =
0.1
Extra risk
0.95
321.92
153.274
1517.45
Taken together, (153.274, 1517.45) is a 90
interval for the BMD
% two-sided confidence
B-27
DRAFT - DO NOT CITE OR QUOTE
-------
Probit Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
0
t> 0.25
st
< no
c 0.2
0
Vi
£ 0.15
i_
LJ_
0.1
0.05
0
: n h't ' ' ' ' ' :
r T 1
^ ^
i T ;
§- H
: ^^ :
: _^— -^t> ^
r ^^-~^~^^ \ ~
\ ^^—~~^^ :
- "^~ 1 i ^ ^ -
E ^__l__ — — " ;
r i ^^^^——^^^ 1 1
r h i
! 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_DEAMGELO_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
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 = 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
intercept = -1.72179
slope = 0.00160607
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -background
B-28
DRAFT - DO NOT CITE OR QUOTE
-------
the user,
intercept
slope
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
intercept slope
1 -0.67
-0.67 1
Interval
Variable
Limit
intercept
1.10211
slope
0.00236517
Estimate
-1.52928
0.00122623
Parameter Estimates
Std. Err.
0.217945
0.000581105
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
-1.95644
8.72829e-005
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.7671
-36.2697
-38.4712
76.5395
# Param's Deviance Test d.f. P-value
4
2 5.00537 2 0.08186
1 9.40833 3 0.02433
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
= 3.59
d.f. = 2
P-value = 0.1658
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 425.313
BMDL = 271.161
B-29
DRAFT - DO NOT CITE OR QUOTE
-------
Probit Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
0
t> 0.25
st
c 0.2
g
CD °-15
LJ_
0.1
0.05
0
: n h't ' ' ' ' ' :
r T 1
^ -E
i T ;
§- -i
: ~T :
L ^^-^T ^
! ^^~~^^^ \
f ^ J> ^^^^\ ;
f 1 ^^_^--^^^ 1 ;
f ix JL ^
i BMDlJ 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_DEAMGELO_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
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 = 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 (and Specified) Parameter Values
background = 0.0666667
intercept = -6.86605
slope = 1
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -slope
B-30
DRAFT - DO NOT CITE OR QUOTE
-------
the user,
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
background intercept
background 1 -0.31
intercept -0.31 1
Interval
Variable
Limit
background
0.12325
intercept
6.71138
slope
Estimate
0.0691801
-7.43777
1
Parameter Estimates
Std. Err.
0.0275874
0.370612
NA
NA - Indicates that this parameter has hit a bound
implied by some ineguality constraint and thus
has no standard error.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
0.0151099
-8.16415
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-33.7671
-36.5279
-38.4712
77.0558
# Param's
4
2
1
Deviance Test d.f.
5.52164
9.40833
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
=4.09
d.f. = 2
P-value = 0.1297
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 471.64
BMDL = 276.75
B-31
DRAFT - DO NOT CITE OR QUOTE
-------
Weibull Model with 0.95 Confidence Level
0.4
0.35
0.3
T3
0
I °'25
< 0.2
g
| 0.15
ul
0.1
0.05
0
: XA/Qihii ill :
- vveiDun :
r T 1
^ ^
i T ;
; ~$ ^^^-^T^^^ ]
r i ^^^-~~^^^ 1 ;
1 |U-^1 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_DEAMGELO_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
BMDS MODEL RUN
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(-slope*dose/xpower)]
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
the user,
Default Initial (and Specified) Parameter Values
Background = 0.0806452
Slope = 0.00026597
Power = 1
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Power
have been estimated at a boundary point, or have been specified by
B-32
DRAFT - DO NOT CITE OR QUOTE
-------
and do not appear in the correlation matrix
Background Slope
Background 1 -0.45
Slope -0.45 1
Parameter Estimates
Interval
Variable
Limit
Background
0.112293
Slope
0.000690658
Power
Estimate
0.0556454
0.000327288
1
Std. Err.
0.0289026
0.000185396
NA
NA - Indicates that this parameter has hit a bound
implied by some ineguality constraint and thus
has no standard error.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
-0.00100271
-3.60816e-005
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.
4.62871
9.40833
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
= 3.34
d.f. = 2
P-value = 0.1882
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 321.919
BMDL = 153.274
B-33
DRAFT - DO NOT CITE OR QUOTE
-------
APPENDIX C. 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 1,56 1,09 1,1 10 1,
1 14 1, 12 14 1,0 15 1, 12 15 1, 16 16 1
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,
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 = 1,200 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 = 1,800 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 = 1,200 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 = 1,800 mg/kg-day
C-l DRAFT - DO NOT CITE OR QUOTE
-------
1 14,22 1,341,441,66 1
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
0920 10 12 10 1
0 114 1 11 1
0 1290 13 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 1230 132 1 132
0 14 1 1 14 1
0 15 1 1 15 17 16 1
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 = 1,200 mg/kg-day
1 1244 1
061661
171273571
291011 1 10 11 1
3 13 1
Dose = 1,800 mg/kg-day
011111
121221
33 1
66288 1
C-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
4
6
9
10
16
17
1
2
3
4
6
1800
1800
1800
1800
1800
1800
1200
1200
1200
1200
1200
6
6
6
6
6
6
7
7
7
7
7
M
M
F
M
F
M
F
M
F
M
F
2.
2.
2.
2.
2.
2.
2.
3.
2.
2.
2.
.51
.19
.40
.38
.21
.41
.86
.31
.86
.70
.82
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
.3
.2
.2
. 1
. 1
.2
.3
.5
.3
.3
.4
C-3 DRAFT - DO NOT CITE OR QUOTE
-------
539
539
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
9
10
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
1200
1200
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
7
7
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
M
M
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
2.
2.
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.
.86
.76
.77
.79
.01
.94
.93
.82
.43
.58
.86
.37
.56
.58
.64
.47
.84
.30
.73
.54
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C-4 DRAFT - DO NOT CITE OR QUOTE
-------
545
545
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545
545
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545
546
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DRAFT - DO NOT CITE OR QUOTE
-------
551
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555 13 1800 1 F 2.36 3.0
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C-6 DRAFT - DO NOT CITE OR QUOTE
-------
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DRAFT - DO NOT CITE OR QUOTE
-------
573
573
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574
574
574
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C-8 DRAFT - DO NOT CITE OR QUOTE
-------
582
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C-9 DRAFT - DO NOT CITE OR QUOTE
-------
588
588
588
588
588
589
589
589
589
589
589
589
589
589
589
589
591
591
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9
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4
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3
4
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13
7
7
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7
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15
15
15
15
15
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15
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.7
C-10 DRAFT - DO NOT CITE OR QUOTE
-------
596
596
596
596
596
596
597
597
597
597
597
597
597
599
599
599
599
599
599
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10
11
12
13
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7
8
11
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3
4
5
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3
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2
4
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8
8
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C-11 DRAFT - DO NOT CITE OR QUOTE
-------
603
603
603
603
603
603
603
604
604
604
604
604
604
604
604
604
605
605
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7
9
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12
13
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1
2
4
6
7
8
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2
3
4
5
6
7
8
9
10
11
12
13
1
2
3
4
5
6
7
8
9
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6
8
1
2
3
4
5
6
7
8
9
10
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.5
C-12 DRAFT - DO NOT CITE OR QUOTE
-------
612
612
612
612
613
613
613
613
613
613
613
613
613
613
613
613
613
11
12
13
14
1
2
4
5
6
7
8
9
10
11
12
13
14
800
800
800
800
330
330
330
330
330
330
330
330
330
330
330
330
330
14
14
14
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13
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13
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2.
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614 1 330 1 M 3.34 3.:
615
615
615
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616
616
616
616
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1
2
3
4
5
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7
8
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12
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1
2
3
4
5
7
8
9
10
11
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1
2
3
4
6
7
8
9
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14
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.6
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.5
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.6
.5
.4
.5
C-13 DRAFT - DO NOT CITE OR QUOTE
-------
617
617
617
618
618
618
618
618
618
619
619
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622
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10
11
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2
3
4
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3
4
5
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7
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9
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1
2
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6
7
8
9
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11
12
13
15
1
2
3
4
5
6
7
8
9
10
11
12
1
3
4
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6
330
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2.
3.
3.
3.
3.
.15
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.44
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3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
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3.
3.
3.
3.
3.
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3.
3.
3.
3.
3.
3.
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
.6
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.6
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.5
.5
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.5
.5
.5
.5
.5
.5
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.5
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.7
.5
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.8
.8
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.6
.6
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.6
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.5
.4
.6
.6
.6
.6
.8
.7
.8
.8
.7
.7
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.5
.7
.7
.5
C-14 DRAFT - DO NOT CITE OR QUOTE
-------
622
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
7
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
330
0
0
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13
13
13
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13
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12
12
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12
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12
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12
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12
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2.
3.
2.
3.
2.
3.
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3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
4.
4.
3.
3.
.86
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.94
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.80
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
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3.
3.
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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
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1
2
3
4
5
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
330
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15
15
15
15
15
15
15
15
15
15
15
15
15
15
10
10
10
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3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
2.
3.
2.
.38
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3.
3.
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3.
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3.
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3.
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.5
.5
.2
.5
.4
C-15 DRAFT - DO NOT CITE OR QUOTE
-------
626
626
626
626
626
627
627
627
627
627
627
627
627
627
627
627
627
627
627
627
627
629
629
629
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629
629
629
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630
630
630
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631
631
631
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631
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6
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
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3
4
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330
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10
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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
M
F
M
M
M
F
M
M
M
M
M
M
F
F
F
M
F
F
M
M
M
F
F
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M
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M
M
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M
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M
F
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M
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M
M
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F
M
2
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
.61
.86
.14
.18
.12
.51
.02
.81
.75
.07
.69
.76
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.62
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.65
.65
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.40
.28
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.39
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.61
.35
.57
C-16
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
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3.
3.
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3.
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3.
3.
3.
3.
.3
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.5
.4
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.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
DRAFT - DO NOT CITE OR QUOTE
-------
631
631
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
10
11
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
330
330
0
0
0
0
0
0
0
0
0
0
0
330
330
330
330
330
330
330
330
330
330
330
330
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9
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6
6
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14
14
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14
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14
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14
F
M
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3.
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2.
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2.
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3.
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3.
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4.
3.
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4 .
3.
3.
3.
3.
.7
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.4
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.4
.5
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.6
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.6
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.4
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.6
.8
.7
.8
.8
.0
.8
.7
.8
.8
C-17 DRAFT - DO NOT CITE OR QUOTE
-------
636
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
12
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
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
14
11
11
11
11
11
11
11
11
11
11
11
F
M
F
F
F
F
F
M
F
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3.
3.
3.
3.
2.
3.
3.
3.
3.
3.
3.
3.
3.
3.
3.
2.
3.
3.
2.
3.
3.
2.
2.
.61
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3.
3.
3.
3.
3.
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
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.6
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.8
.8
.7
.9
.6
.7
.5
.5
.4
.6
.4
.7
.6
.3
.5
C-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)
Table C-l. BMD modeling results for litter incidence of levocardia (Smith et
al., 1989)
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
0.0520b
0.0449b
AIC
69.8459
69.8459
71.6069
71.6259
71.8203
80.642
80.6568
BMD05
42
42
74
87
36
144
136
BMDLos
31a
31a
17
9
1
101
99
BMD10
86
86
122
130
76
253
244
BMDL10
64a
64a
36
20
5
187
185
""Preferred model(s) based on criteria described in U.S. EPA (2000d).
bBecause 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.
Of the seven models fitted, five (i.e., multistage, gamma, log-logistic, log-probit, and
Weibull) showed adequate fit, and thus the BMDS outputs from these five models are provided
below. BMD and BMDL values associated with a BMR of both 5 and 10% are shown.
$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[siope*dose,power]
where CumGamma(.) is the cumulative 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
C-19 DRAFT - DO NOT CITE OR QUOTE
-------
Background =
Slope =
Power =
0.0185185
0 .00171859
1.3
Asymptotic Correlation Matrix of Parameter Estimates
( *** xhe 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.
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood)
-33.5379
-33.9229
-57.0522
69.8459
Deviance Test DF
P-value
0.770003
47.0286
0.9424
<.0001
Goodness of Fit
I
0.
330.
800.
1200.
1800.
3ose
.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 £
0
6
12
10
7
3ize
26
19
17
14
8
Scalec
Residi
-0.
0.
-0.
-0.
I
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 =
BMDL =
41.8783
31.3527
0.1
86.0214
64.4009
C-20 DRAFT - DO NOT CITE OR QUOTE
-------
Gamma Multi-Hit Model with 0.95 Confidence Level
amma Multi-Hit
o
£0.6
"o
03
.9,0.4
I
'.0.2
0
T
BMD
BMD
0 500
14:1204/192004
1000
dose
1500
Graph shows the BMD and BMDL associated with a BMR = 0.1.
C-21
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
HMDS MODEL RUN
The form of the probability function is:
P [response] = background+(1-background)/[1+EXP(-intercept-siope*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
( *** xhe 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.
Analysis of Deviance Table
C-22 DRAFT - DO NOT CITE OR QUOTE
-------
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
-33.8035 0
-57. 0522
71. 6069
Goodness of Fit
. Prob . Expected
.0000 0.000
.3300 6.269
.6489 11.032
.7721 10.809
.8612 6.890
. 531045
47. 0286
Observed
0
6
12
10
7
DF P-value
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
Benchmark Dose Computation
Specified effect = 0.05
Risk Type = Extra risk
Confidence level = 0.95
P-value = 0.9106
0.1
BMD =
BMDL =
73.8468
17.0566
121.785
36.0084
Log-Logistic Model with 0.95 Confidence Level
1
Log-Logistic
o
cc
°0.4
i
:o.2
o
BMDL BMP
0 500
14:21 04/192004
1000
dose
1500
Graph shows the BMD and BMDL associated with a BMR = 0.1.
C-23
DRAFT - DO NOT CITE OR QUOTE
-------
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
HMDS 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
( *** xhe 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.
Analysis of Deviance Table
Model Log(likelihood) Deviance Test DF P-value
Full model -33.5379
Fitted model -33.9229 0.770003 4 0.9424
Reduced model -57.0522 47.0286 4 <.0001
C-24 DRAFT - DO NOT CITE OR QUOTE
-------
AIC:
69.8459
Goodness of Fit
Dose
Est. Prob.
Expected Observed
Size
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
0.1
BMD =
BMDL =
41.8783
31.3527
86.0214
64.4009
Multistage Model with 0.95 Confidence Level
1 Multistage
o>
t5
£0-6
gO.4
t5
CD
it 0.2
BMDL BMD
Chi*2 Res.
i
i
i
i
i
: 1
0 .
: 2
330 .
: 3
800 .
: 4
1200 .
: 5
1800 .
.0000
.0000
.0000
.0000
.0000
0.
0.
0.
0.
0.
. 0000
.3325
. 6246
. 7700
. 8897
0
6
10
10
7
.000
.317
.619
.780
.118
0
6
12
10
7
26
19
17
14
8
0 .
-0 .
0 .
-0 .
-0 .
.000
.075
.347
.315
.150
0 500 1000 1500
dose
14:3004/192004
Graph shows the BMD and BMDL associated with a BMR = 0.1.
C-25
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 14:34:52 2004
HMDS 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
( *** xhe 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.
C-26 DRAFT - DO NOT CITE OR QUOTE
-------
Analysis of Deviance Table
Model Log(likelihood) Deviance Test DF
Full model -33.5379
P-value
Fitted model
Reduced model
AIC:
Dose Est
0.0000 0
330.0000 0
800.0000 0
1200.0000 0
1800.0000 0
-
Goo
. Prob .
.0000
.3316
.6444
.7701
.8661
-33.813 0.550064
57.0522 47.0286
71. 6259
dness of Fit
Expected Observed
0.000 0
6.301 6
10.955 12
10.781 10
6.929 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 = 0.05
Risk Type = Extra risk
Confidence level = 0.95
BMD =
BMDL =
87.3528
8.59815
0.1
130.221
19.6033
Probit Model with 0.95 Confidence Level
r\ r-
0.6
.90.4
"o
03
tO.2
0
Probit
BMDL BMD
1000
dose
1500
0 500
14:3404/192004
Graph shows the BMD and BMDL associated with a BMR = 0.1.
C-27
DRAFT - DO NOT CITE OR QUOTE
-------
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
HMDS 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
( *** xhe 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.
C-28 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
-33 . 9102
-57. 0522
71. 8203
Goodness of Fit
. Prob . Expected
.0000 0.000
.3459 6.572
.6261 10.643
.7643 10.701
.8804 7.043
0 .74446
47. 0286
Observed
0
6
12
10
7
DF P-value
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 = 0.05
Risk Type = Extra risk
Confidence level = 0.95
0.1
BMD =
BMDL =
35.5948
1.01863
75.9968
5.08236
Weibull Model with 0.95 Confidence Level
Wei bul I
-—
1 0.6
0.4
o
03
LH0.2
0
HMDL
BMD
0
14:5004/192004
500
1000
dose
1500
Graph shows the BMD and BMDL associated with a BMR = 0.1.
C-29
DRAFT - DO NOT CITE OR QUOTE
-------
APPENDIX D. MODELING OF LIVER TUMOR INCIDENCE DATA FOR MICE
EXPOSED TO TRICHLOROACETIC ACID IN DRINKING WATER
Using the EPA 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. [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 shown in Tables 5-8 through 5-12 in Section 5.4.2.
Average daily intakes from these mouse studies were converted to human equivalent
doses for continuous lifetime exposure by 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. (2008) 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. (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, the one-stage
multistage model provided the best fit to the data as determined by the chi-square goodness-of-fit
statistic and AIC. Model predictions compared with observed incidences are shown in
Figures D-l, D-2, D-3, D-4, and D-5 of this appendix.
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 EDio, and its
corresponding LEDio. Candidate oral cancer slope factors were derived by linear extrapolation
from the LEDio (i.e., 0.1/LEDi0).
D-1 DRAFT - DO NOT CITE OR QUOTE
-------
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 5-13). The four slope factors
derived from male mice varied by less than fourfold.
The standard output from BMDS (version 1.4.1) is reproduced below for each of the five
data sets that were modeled.
T3
0
03
0.7
0.6
0.5
0.2
0.1
Multistage Model with 0.95 Confidence Level
Multistage
BMDL
BMP
dose
08:56 06/27 2007
Figure D-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).
D-2
DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
T3
0
0.7
0.6
0.5
0.4
.1 0.3
•6
2
u- 0.2
0.1
Multistage
P.MD.
dose
09:03 06/27 2007
Figure D-2. Predicted and observed 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: Bulletal. (1990).
D-3
DRAFT - DO NOT CITE OR QUOTE
-------
0.8
0.7
0.6
T3
«J 0.5
I
< 0.4
g
co
0.2
0.1
0
Multistage Model with 0.95 Confidence Level
Multistage
BMDL
BMD
10
15
dose
09:08 06/27 2007
Figure D-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. (2008).
D-4
DRAFT - DO NOT CITE OR QUOTE
-------
0.8
Tg 0-6
I
0.4
ta
CD
0.2
Multistage Model with 0.95 Confidence Level
Multistage
BMD
BMP
10
09:1406/272007
20
30
dose
40
50
60
Figure D-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).
D-5
DRAFT - DO NOT CITE OR QUOTE
-------
Multistage Model with 0.95 Confidence Level
0
0
0.9
0.7
0.6
0.5
0.4
r
I C.
\
\ J
IVIUIUaiayC
T ;
^^^
\ BMDL
•j
J
^- — x I
-_
BMP , , , , , , , , ;
0123456789
dose
09:37 06/27 2007
Figure D-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. (2008).
D-6
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
the user,
Beta(l)
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Background
have been estimated at a boundary point, or have been specified by
and do not appear in the correlation matrix )
Beta(l)
1
Parameter Estimates
95.0% Wald Confidence
Interval
Variable
Limit
Background
Beta(l)
Estimate
0
Std. Err.
Lower Conf. Limit Upper Conf.
0.0745471 *
* - Indicates that this value is not calculated.
Analysis of Deviance Table
Model
Full model
Fitted model
Reduced model
AIC:
Log(likelihood) # Param's Deviance Test d.f.
-25.6775 3
-27.3086 1 3.26212 2
-32.5964 1 13.8377 2
56.6172
P-value
0.1957
0.000989
Goodness of Fit
D-7
Scaled
DRAFT - DO NOT CITE OR QUOTE
-------
Dose Est._Prob. Expected Observed Size Residual
0.0000 0.0000 0.000 0 20 0.000
2.3800 0.1626 3.251 6 20 1.666
9.5000 0.5075 10.149 8 20 -0.961
= 3.70 d.f. = 2 P-value = 0.1573
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 1.41334
BMDL = 0.932428
BMDU = 2.78979
Taken together, (0.932428, 2.78979) is a 90 % two-sided confidence
interval for the BMD
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
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 = 0.105918
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) 1
D-8 DRAFT - DO NOT CITE OR QUOTE
-------
Parameter Estimates
Interval
Variable
Limit
Background
Beta (1)
Estimate
0
Std. Err.
0.053545 *
* - Indicates that this value is not calculated.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
Model
Full model
Fitted model
Reduced model
AIC:
Analysis of Deviance Table
Log(likelihood)
-19.4921
-21.2941
-26.8563
44.5881
# Param's
3
1
1
Deviance Test d.f.
3. 604
14.7286
P-value
0.165
0.0006335
Dose
Est. Prob.
Goodness of Fit
Expected Observed Size
Scaled
Residual
0.0000
3.2500
6.5100
ChiA2 = 4.26
0.0000
0.1597
0.2943
d.f. = 2
0.000 0 35 0.000
1.757 4 11 1.846
7.063 5 24 -0.924
P-value = 0.1187
Benchmark Dose Computation
Specified effect =
Risk Type
Confidence level =
BMD =
BMDL =
BMDU =
0.1
Extra risk
0.95
1.9677
1.18795
3.61033
Taken together, (1.18795, 3.61033) is a 90
interval for the BMD
% two-sided confidence
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
D-9
DRAFT - DO NOT CITE OR QUOTE
-------
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 = 0.204406
Beta(l) = 0.0324139
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background
Beta(l)
Interval
Variable
Limit
Background
Beta (1)
-0.5
1
Parameter Estimates
Estimate
0.183783
0.0372004
Std. Err.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
* - 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
132.235
# 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
=3.84
d.f. = 2
P-value = 0.1465
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
D-10
DRAFT - DO NOT CITE OR QUOTE
-------
BMD =
BMDL =
BMDU =
2.83224
1.70985
5.86213
Taken together, (1.70985, 5.86213) is a 90
interval for the BMD
two-sided confidence
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
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(l)
Background 1 -0.43
Beta(l) -0.43 1
Interval
Variable
Limit
Background
Beta (1)
Parameter Estimates
Estimate
0.0373114
0.0147581
Std. Err.
Indicates that this value is not calculated.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
Model
Full model
Fitted model
Reduced model
Analysis of Deviance Table
Log(likelihood)
-58.4099
-59.1702
-79.1216
# Param's
4
2
1
Deviance Test d.f.
1.52058
41.4233
P-value
0.4675
<.0001
D-ll
DRAFT - DO NOT CITE OR QUOTE
-------
AIC: 122.34
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
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
D-12 DRAFT - DO NOT CITE OR QUOTE
-------
Beta(l)
-0.47
Interval
Variable
Limit
Background
Beta (1)
Parameter Estimates
Estimate
0.597398
0.118941
Std. Err.
* - Indicates that this value is not calculated.
95.0% Wald Confidence
Lower Conf. Limit Upper Conf.
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
Goodness of Fit
Dose
0.0000
0.8400
8.7000
Est. Prob.
0.5974
0.6357
0.8570
Expected
25.091
22.249
31.707
Observed
27
20
32
Size
42
35
37
Scaled
Residual
0.601
-0.790
0.137
ChiA2 =1.00
d.f. = 1
P-value = 0.3164
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
D-13
DRAFT - DO NOT CITE OR QUOTE
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