r UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
1 WASHINGTON, D.C. 20460
OFFICE OF THE ADMINISTRATOR
SCIENCE ADVISORY BOARD
June 28, 2007
EPA-SAB-07-008
Honorable Stephen L. Johnson
Administrator
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, N.W.
Washington, D.C. 20460
Subject: Advisory on EPA's Assessments of Carcinogenic Effects of Organic
and Inorganic Arsenic: A Report of the US EPA Science Advisory Board
Dear Administrator Johnson:
The U. S. Environmental Protection Agency's (EPA) Office of Pesticide
Programs (OPP), Office of Water (OW), and Office of Research and Development
(ORD) coordinated the development of two scientific documents that address the
carcinogenicity of Dimethylarsinic Acid (DMAV) and inorganic arsenic (iAs). In
response to an Agency request, the Science Advisory Board (SAB) convened an expert
panel to review and comment on key scientific issues presented in these two documents,
including: (a) the metabolism and toxic responses of arsenic species; (b) mode(s) of
carcinogenic action; (c) data selection for dose-response assessment; and (d) approaches
and methods for low-dose extrapolation for DMAV and iAs.
The SAB Panel supported the Agency's conclusion that on the basis of available
data, human exposure to DMAV appears to result in a narrower spectrum of active
metabolites than those expected in the metabolic profile associated with exposure to iAs.
Therefore, the Panel agreed with EPA that, in the absence of human data on DMAV, the
bladder tumor data from DMAV rat bioassays is better suited for DMAV cancer risk
assessment than is epidemiology data from iAs exposure. The Panel, however, noted that
there remain significant uncertainties associated with the use of animal data for DMAV
cancer risk assessment due to the observed metabolic differences between rats and
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humans. The Panel agreed with the Agency's conclusion that DMAv-induced bladder
cancer in rats, at high dose, is mediated by a cytotoxic mode of action, and that this MOA
should be considered relevant to humans. However, the Panel concluded there are not
sufficient data to support a reactive oxygenated species-mediated mode of direct genetic
action for DMAV. The Panel supported the nonlinear approach for low dose
extrapolation of DMAV and the use of uncertainty factors to account for interspecies
differences and human variability for sensitive human populations, and concluded that
presently there is no arsenic-specific information that can inform the choice of specific
values. This means that, at least for now, such choices must be based on more general
considerations, including EPA's science policy judgment of the degree of precaution that
it deems appropriate.
EPA concluded that the mechanisms by which inorganic arsenic induces bladder
cancer in humans are not yet known, but they are likely to be mediated by multiple
modes of action. The Agency used a linear default approach for low dose extrapolation
because it lacked a full understanding of the iAs modes of carcinogenic action. The
Panel agreed that available human and animal data do not fully describe the shape of the
iAs carcinogenic dose-response curve at low doses. Given the considerable uncertainties
regarding low dose extrapolation, the Panel supported the use of a linear cancer risk
model for iAs as recommended by the National Research Council in its 2001 report. The
Panel also supported the use of the epidemiologic data on the Taiwanese population for
estimating human cancer risk for iAs especially to identify the potential range of
responses of human populations. However, the Panel recognized limitations to these
data, and that there is some evidence on iAs from animal toxicology, pharmacokinetics,
and pharmacodynamics research, that suggests other than a linear bladder cancer dose-
response. The Panel urged the Agency to consider other epidemiologic studies from the
U.S. and other countries, utilizing a uniform set of evaluative criteria. The Panel also
recommended sensitivity analyses be conducted to account for human variability in
drinking water consumption rates, dietary intake of iAs from food, and certain other
assumptions currently used in EPA's assessment. The Panel made several suggestions
for improvements in the currently applied risk model's programming and documentation
conventions.
Finally, the Panel believes there is a critical need for a continued research effort to
strengthen EPA's cancer risk assessment for DMAV and iAs. The scientific bases for the
Panel's conclusions and research recommendations are detailed throughout this report.
We look forward to receiving your response to this review and we appreciate the
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opportunity to provide EPA with advice on this important subject and stand ready to
assist the Agency in any future efforts in updating the assessment.
Sincerely,
/Signed/ /Signed/
Dr. M. Granger Morgan, Chair Dr. Genevieve Matanoski, Chair
EPA Science Advisory Board EPA Science Advisory Board
Arsenic Review Panel
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NOTICE
This report has been written as part of the activities of the EPA Science Advisory Board, a public
advisory committee providing extramural scientific information and advice to the Administrator
and other officials of the Environmental Protection Agency. The Board is structured to provide
balanced, expert assessment of scientific matters related to problems facing the Agency. This
report has not been reviewed for approval by the Agency and, hence, the contents of this report
do not necessarily represent the views and policies of the Environmental Protection Agency, nor
of other agencies in the Executive Branch of the Federal government, nor does mention of trade
names or commercial products constitute a recommendation for use. Reports of the EPA
Science Advisory Board are posted on the EPA Web site at: http://www.epa.gov/sab.
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U.S. Environmental Protection Agency
Science Advisory Board
Arsenic Review Panel
CHAIR
Dr. Genevieve Matanoski, Professor, Department of Epidemiology, Johns Hopkins University,
Baltimore, MD
MEMBERS
Dr. H. Vasken Aposhian, Professor, Department of Molecular and Cell Biology, The University
of Arizona, Tucson, AZ
Dr. Aaron Barchowsky, Associate Professor, Department of Environmental and Occupational
Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
Dr. David Brusick, Retired, Convance Labs, Vienna, VA
Dr. Kenneth P. Cantor, Senior Investigator, Occupational and Environmental Epidemiology
Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda,
MD
Dr. John (Jack) Colford, Associate Professor, Division of Public Health, Biology &
Epidemiology, School of Public Health, University of California, Berkeley, CA
Dr. Yvonne P. Dragan, Director of the Division of Systems Toxicology (DST) and Chief of the
Center for Hepatotoxicology, National Center for Toxicological Research (NCTR), Food and
Drug Administration's (FDA), Jefferson, AR
Dr. Sidney Green, Associate Professor, Department of Pharmacology, College of Medicine,
Howard University, Washington, DC
Dr. Sioban Harlow, Professor, Department of Epidemiology, School of Public Health,
University of Michigan, Ann Arbor, MI
Dr. Steven Heeringa, Research Scientist and Director, Statistical Design Group, Institute for
Social Research (ISR), University of Michigan, Ann Arbor, MI
Dr. Claudia Maria Hopenhayn, Associate Professor, Department of Epidemiology,
Markey Cancer Control Program, College of Public Health, University of Kentucky, Lexington,
KY
Dr. James E. Klaunig, Professor and Director, Department of Pharmacology and Toxicology,
School of Medicine, Indiana University, Indianapolis, IN
11
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Dr. X. Chris Le, Professor, Department of Public Health Sciences, Department of Chemistry &
Department of Laboratory Medicine & Pathology, University of Alberta, Edmonton, Alberta,
Canada
Dr. Michele Medinsky, Toxicology Consultant, Toxcon, Durham, NC
Dr. Kenneth Portier, Program Director, Department of Statistics and Evaluation, American
Cancer Society, Atlanta, GA
Dr. Barry Rosen, Professor and Chairman, Department of Biochemistry and Molecular Biology,
School of Medicine, Wayne State University, Detroit, MI
Dr. Toby Rossman, Professor, Environmental Medicine, School of Medicine, New York
University, Tuxedo, NY
Dr. Miroslav Styblo, Research Associate Professor, Department of Nutrition and the Center for
Environmental Medicine, Asthma, and Lung Biology, University of North Carolina, Chapel Hill,
NC
Dr. Justin Teeguarden, Senior Scientist, Pacific Northwest National Laboratory, Richland, WA
Dr. Michael Waalkes, Chief, Inorganic Carcinogenesis Section, Laboratory of Comparative
Carcinogenesis, National Cancer Institute, National Institute of Environmental Health Science,
Research Triangle Park, NC
Dr. Janice Yager, Research Program Manager, Environment Department, Electric Power
Research Institute, Palo Alto, CA
SCIENCE ADVISORY BOARD STAFF
Mr. Thomas Miller, Designated Federal Officer, EPA Science Advisory Board Staff Office
in
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U.S. Environmental Protection Agency
Science Advisory Board
CHAIR
Dr. M. Granger Morgan, Professor and Head, Department of Engineering and Public Policy,
Carnegie Mellon University, Pittsburgh, PA
SAB MEMBERS
Dr. Gregory Biddinger, Environmental Programs Coordinator, ExxonMobil Biomedical
Sciences, Inc, Houston, TX
Dr. James Bus, Director of External Technology, Toxicology and Environmental Research and
Consulting, The Dow Chemical Company, Midland, MI
Dr. Deborah Cory-Slechta, Director, Environmental and Occupational Health Sciences
Institute, Robert Wood Johnson Medical School, University of Medicine and Dentistry of New
Jersey and Rutgers State University, Piscataway, NJ
Dr. Maureen L. Cropper, Professor, Department of Economics, University of Maryland,
College Park, MD
Dr. Virginia Dale, Corporate Fellow, Environmental Sciences Division, Oak Ridge National
Laboratory, Oak Ridge, TN
Dr. Kenneth Dickson, Professor, Institute of Applied Sciences, University of North Texas,
Denton, TX
Dr. Baruch Fischhoff, Howard Heinz University Professor, Department of Social and Decision
Sciences, Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh,
PA
Dr. James Galloway, Professor of Environmental Sciences, Environmental Sciences
Department, University of Virginia, Charlottesville, VA
Dr. Lawrence Goulder, Shuzo Nishihara Professor of Environmental and Resource Economics,
Department of Economics, Stanford University, Stanford, CA
Dr. James K. Hammitt, Harvard Center for Risk Analysis, Harvard University, Boston, MA
Dr. Rogene Henderson, Scientist Emeritus, Lovelace Respiratory Research Institute,
Albuquerque, NM
Dr. James H. Johnson, Dean, College of Engineering, Architecture & Computer Sciences,
Howard University, Washington, DC
IV
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Dr. Agnes Kane, Dept. of Pathology and Laboratory Medicine, Brown University, Providence,
RI.
Dr. Meryl Karol, Associate Dean for Academic Affairs, Graduate School of Public Health,
University of Pittsburgh, Pittsburgh, PA
Dr. Catherine Kling, Professor, Department of Economics, Iowa State University, Ames, IA
Dr. George Lambert, Associate Professor and Director, Center for Child and Reproductive
Environmental Health & Pediatric Clinical Research Center, Department of Pediatrics, UMDNJ-
Robert Wood Johnson Medical School/University of Medicine and Dentistry of New Jersey,
New Brunswick, NJ
Dr. Jill Lipoti, Director, Division of Environmental Safety and Health, New Jersey Department
of Environmental Protection, Trenton, NJ
Dr. Genevieve Matanoski, Professor, Department of Epidemiology, Johns Hopkins University,
Baltimore, MD
Dr. Michael McFarland, Associate Professor, Department of Civil and Environmental
Engineering, Utah State University, Logan, UT
Dr. Judith Meyer, Institute of Ecology, University of Georgia, Athens, GA.
Dr. Jana Milford, Associate Professor, Department of Mechanical Engineering, University of
Colorado, Boulder, CO
Dr. Rebecca Parkin, Professor and Associate Dean, Environmental and Occupational Health,
School of Public Health and Health Services, The George Washington University, Washington,
DC
Mr. David Rejeski, Foresight and Governance Project Director, Woodrow Wilson International
Center for Scholars, Washington, DC
Dr. Stephen Roberts, Department of Physiological Sciences, University of Florida, Gainesville,
FL.
Dr. Joan B. Rose, Professor and Homer Nowlin Chair for Water Research, Department of
Fisheries and Wildlife, Michigan State University, E. Lansing, MI
Dr. Jerald Schnoor, Department of Civil and Environmental Engineering, University of Iowa,
Iowa City, IA.
Dr. Kathleen Segerson, Professor, Department of Economics, University of Connecticut, Storrs,
CT
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Dr. Kristin Shrader-Frechette, O'Neil Professor of Philosophy- Concurrent Professor of
Biological Sciences-and Director of the Center for Environmental Justice and Children's Health,
Department of Biological Sciences and Philosophy Department, University of Notre Dame,
Notre Dame, IN
Dr. Philip Singer, Department of Environmental Sciences and Engineering, University of North
Carolina, Chapel Hill, NC.
Dr. Robert Stavins, Albert Pratt Professor of Business and Government, Environment and
Natural Resources Program, John F. Kennedy School of Government, Harvard University,
Cambridge, MA
Dr. Deborah Swackhamer, Professor, Division of Environmental Health Sciences, School of
Public Health, University of Minnesota, Minneapolis, MN
Dr. Thomas L. Theis, Professor and Director, Institute for Environmental Science and Policy,
University of Illinois at Chicago, Chicago, IL
Dr. Valerie Thomas, Anderson Interface Associate Professor of Natural Systems, School of
Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA
Dr. Barton H. (Buzz) Thompson, Jr., Robert E. Paradise Professor of Natural Resources Law,
Stanford Law School, and Director, Woods Institute for the Environment, Stanford University,
Stanford, CA
Dr. Robert Twiss, Professor, University of California-Berkeley, Ross, CA
Dr. Terry F. Young, Consultant, Environmental Defense, Oakland, CA
Dr. Lauren Zeise, Chief, Reproductive and Cancer Hazard Assessment Section, California
Environmental Protection Agency, Oakland, CA
VI
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TABLE OF CONTENTS
1. EXECUTIVE SUMMARY 1
2. INTRODUCTION 12
2.1 Process for Developing this Report and Structure of the Report 12
2.2 Background 13
3. RESPONSE TO THE CHARGE 17
3.1 Overview 17
3.2 Metabolism and Toxic Responses of Arsenic Species 17
3.2.1 Metabolism and pharmacokinetics 17
3.2.2 Response to mixtures of metabolites 20
3.3 Modes of Carcinogenic Action for DMAV and Inorganic Arsenic 22
3.3.1. Mode of Action of DM Av 22
3.3.2 Human relevance of animal DMAV MO A 26
3.3.3 Modes of carcinogenic action from exposures to Inorganic Arsenic 27
3.4 Selection of Data for Dose-Response Assessment 34
3.4.1 Use of animal data for DMAV 34
3.4.2. Use of human epidemiological data from direct inorganic arsenic exposure 36
3.5 Approaches to Low-Dose Extrapolation for Inorganic Arsenic and DMAV 40
3.5.1 Mode of carcinogenic action understanding for DMAv/in 40
3.5.2 Implementation of the recommendations of theNRC 43
3.5.3 EPAModel Re-Implementation 45
3.5.4 Available literature describing drinking water consumption rates 49
3.5.5 Selection of an estimate of dietary intake of arsenic from food 51
REFERENCES R-l
APPENDIX A Charge to the EPA Science Advisory Board A-l
APPENDIX B Assignments to Charge-Specific Groups B-l
APPENDIX C Abbreviations C-l
vn
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1. EXECUTIVE SUMMARY
New information has been developed on the metabolism, pharmacokinetics (PK)
and mode of carcinogenic action of arsenic and its methylated species and new
epidemiology studies have been conducted on inorganic arsenic since the publication of
reviews by the National Research Council (NRC, 1999, 2001). EPA considered this new
science in the development of the Office of Pesticide Programs' (OPP) Draft Science
Issue Paper: Mode of Action for Cacodylic Acid (Dimethylarsinic Acid) and
Recommendations for Dose Response Extrapolation (USEPA OPP, 2005) and the Office
of Water's (OW) Draft Toxicologic Review of Inorganic Arsenic (USEPA OW, 2005).
EPA's Office of Research and Development (ORD) further captured key scientific issues
to be considered in its Issue Paper Cancer Risk Assessment for Organic Arsenical
Herbicides: Comments on Mode of Action, Human Relevance and Implications for
Quantitative Dose-Response Assessment (Appendix E of USEPA OPP, 2005, USEPA
ORD, 2005). The Science Advisory Board (SAB) was asked to review these documents
and offer advice on the metabolism, mode of action, dose-response, and approaches to
low-dose extrapolation of cancer risk for Dimethylarsinic Acid (DMAV) and inorganic
arsenic (iAs). The full charge to the SAB is in Appendix A to this document.
In response to the Agency's request, the SAB convened an expert Panel to
provide advice to the Agency on these scientific issues. In responding to the EPA
Charge, the Panel reviewed the EPA assessments mentioned above, and considered
comments and information that members of the interested public provided during each of
the Panel's advisory meetings (during 2005 and 2006), and additional studies that are
identified in the reference section of this report. The Panel considered expanding the
Charge to include other health endpoints associated with arsenic and arsenic containing
compounds. However, the Panel decided not to expand its activities beyond the EPA
Charge that largely focused on bladder cancer and to some degree on lung cancer dose-
response issues. It is important to recognize that the Panel did not conduct its own
arsenic risk assessment. To do so would have required an updated literature search and
exploration and resolution of many issues that are discussed throughout this report. The
Panel leaves the larger activity of completing a full risk assessment of all relevant health
endpoints associated with arsenic, and arsenic containing compounds, to the Agency
itself when it conducts its final arsenic assessments.
The Panel was organized into small groups of three to seven members to evaluate
and respond to each specific charge question (see Appendix B to this report for a list of
those members assigned to each charge question). The Panel's response to each question
reflects consensus, though not necessarily unanimous agreement, among Panel Members
that addressed each specific charge question. In addition, all Panel Members had the
opportunity to participate in meeting discussions of each charge question and each was
able to provide written comments on all questions during report drafting. Many Members
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participated in this way and each response reflects adjustments that were considered to be
appropriate by the specific charge group that led the Panel's efforts for each question. In
that manner, this advisory report provides the Panel's judgments on each specific issue.
This advice is intended to assist the Agency's continued efforts to complete its
assessments on various arsenicals. There are many specific conclusions and
recommendations on specific issues associated with each charge question, as well as
recommendations for sensitivity analyses and additional research to answer many of the
remaining questions on arsenic risk. The Panel's advice on each charge question is
discussed in the remainder of this Executive Summary and discussed in detail in Section
3 of this report.
1.1 Metabolism and Toxic Responses of Arsenic Species
Charge Question Al
EPA concluded that available in vivo and in vitro metabolism and pharmaco-
kinetic studies in humans and laboratory animals suggest that the efficiency of
methylation reactions and cellular uptake varies with the arsenic compound administered
exogenously. Most studies suggest a predominantly one-way process in mammals and
that after DMAV exposure, significant amounts of iAs111, iAsv, methylarsonous acid
(MMA111), or methylarsinic acid (MMAV) are not expected at target tissues. EPA asked
the SAB to comment on how best to consider the PK processes in cancer risk assessment
based on data derived from direct dimethylarsinic acid (DMAV) exposure versus direct
inorganic arsenic (iAs) exposure.
Summary Response
The Panel agreed that:
i) Metabolism of iAs appears to be a one-way process in which iAs is
converted to monomethylarsenic (MMA), dimethylarsenic (DMA), and in
some species to trimethylarsenic (TMA) metabolites with arsenic in +3 or
+5 oxidation states. Thus, significant amounts of MMA or iAs are not
expected to be found in tissues or urine of rats or humans as a result of
exposure to DMAV, although iAs may be present in human tissues or urine
from other sources.
ii) In contrast, exposure to iAs may result in production, tissue retention, and
urinary excretion of a variety of tri- and pentavalent iAs and methylated
arsenic species.
iii) The uptake and reduction of DMAV to dimethylarsinous acid (DMA111) are
apparently critical steps in activation of DMAV - though it is not clear if,
where and to what extent these processes occur in humans exposed to
DMAV.
iv) The capacity to reduce DMAV to DMA111 seems to exist in human tissues
and the conversion of even a small amount of exogenous DMAV to
DMA111 is of toxicological concern.
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v) Given the differences in the metabolic pattern for iAs and DMAV, the
Panel believes data derived from DMAV exposure, not from iAs exposure,
is better suited for cancer risk assessment of DMAV.
vi) Significant uncertainties are associated with this approach. The
toxicologic data on DMAV are mainly from rat studies, and considering
several key differences between rats and humans in the metabolism of
arsenic, these uncertainties should be considered in the assessment of
DMAV cancer risk. Additional uncertainties include methylation and
demethylation of arsenic compounds in humans by intestinal bacteria, co-
exposures to other environmental contaminants, deficiencies in nutrients,
and malnutrition.
vii) The physiologically based pharmacokinetic (PBPK) model under
development by EPA may be a useful approach but it is not yet
sufficiently robust to conduct interspecies extrapolations.
viii) EPA should continue developing the arsenic PBPK model and conducting
research to obtain kinetic constants needed to describe rates of uptake,
efflux, metabolism, and elimination of DMAV in rats and humans.
ix) There is a need to validate such models for predicting tissue
concentrations of active species regardless of the source of arsenic
exposure.
Charge Question A2
EPA concluded that direct exposure to iAs111 or iAsvis expected to result in a
more complex mixture of toxic metabolites than with DMAV exposure given that
mixtures of metabolites vary based on which chemical is administered exogenously.
EPA expects a less complex mixture of metabolites following DMAV exposure than
following iAs exposure. EPA further expects that the tumorigenic profiles vary with the
arsenical compound administered. For its DMAV assessment, EPA asked the SAB to
comment on the use of data derived from rodent exposures to organic arsenicals versus
data derived from direct human exposure to iAs.
Summary Response
The Panel agreed that:
i) Neither rodent laboratory data on organic arsenicals nor data from studies
of human exposure to inorganic arsenic provide an optimal basis for the
assessment of DMAV exposure in humans because of differences between
the metabolic profiles for inorganic arsenic and DMA and because of
interspecies differences in their metabolism. Despite these uncertainties,
for now, the data from rodent exposures to DMA appear to be the most
reasonable approach for the DMAV assessment, though this approach has
a significant degree of uncertainty (see charge question Al).
ii) The metabolism of iAs yields a wide spectrum of metabolites which are
apparently not produced during the metabolism of DMAV.
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iii) Production of iAs and MMA metabolites may be associated with specific
toxic or cancer endpoints that are absent in DMAV exposure to rats or
humans.
iv) All published data on toxicological responses to DMAV are from studies
in rodents, mainly rats; no human data are available. As noted in the
response to Al above, these differences raise concerns for risk
assessments based on these data.
1.2. Modes of Carcinogenic Action for DMAV and Inorganic Arsenic
Charge question El
EPA's approach to cancer risk assessment incorporates two key science policy
assumptions when there are inadequate human data and it needs to rely on laboratory
animal data: (a) animal tumor data are predictive of human cancer and (b) effects found
at high experimental doses in animals predict human risk at lower exposure levels.
Understanding a mode of action (MOA) for a chemical can help to inform the agency
about these assumptions and the most appropriate approach to follow in low dose
extrapolation. EPA asked the SAB to comment on the scientific soundness of the
postulated MOA for DMAv-induced bladder carcinogenesis in the rat.
Summary Response
The Panel concluded that:
i) There are adequate data to support an MOA for bladder carcinogenesis
induced by high doses of DMAV in the rat and that MOA involves
cytotoxicity to the bladder epithelium and increased, sustained
regenerative proliferation as key events.
ii) The rat metabolizes a significant fraction of exogenous DMAV to
trimethylarsine oxide (TMAVO) and possibly trimethylarsine (TMA111) and
that these compounds cannot be excluded as additional mediators of the
necrotic cytotoxicity in the bladder of exposed rats.
iii) There are not sufficient data to invoke reactive oxygen species (ROS)-
induced DNA damage as a key event in the carcinogenic process
associated with exposures to DMAV and DMA111.
iv) The Panel's postulated MOA for DMAV is:
a) Reductive metabolism of DMAV to DMA111,
b) High concentrations of DMA111 (and possibly DMAV) in urine cause
urothelial cytotoxicity, and
c) Continuous exposure and persistent stress-associated regenerative cell
proliferation leads to genomic instability, acquisition of genetic
alterations, clonal expansion of altered cells and eventually tumors.
v) The Panel suggested several high priority research needs for this issue.
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Charge question B2
EPA concluded that their postulated MOA for DMAV induced bladder
carcinogenesis in the rat would be relevant to humans as there are little or no data to
suggest that key precursor events and ultimately tumor formation would not occur in
exposed humans if sufficient DMA111 were present. EPA asked the SAB to comment on
the relevance of the postulated key events to tumors in humans and how differences in
humans and experimental animals should be accounted for in DMAvrisk assessments.
Summary Response
The Panel concluded that:
i) If high enough concentrations of DMAV or DMA111 were present in human
urine or the bladder after exposure to DMAvit is plausible that a similar
response would take place; however, no data are available to support or
reject this assumption.
ii) The suggested greater conversion of DMAvto TMAVO or possibly TMA111
in rats vs. in humans, may contribute to induction of bladder cancer in rats,
however, the extent of the contribution is unknown.
iii) No studies have been conducted to determine whether the DMAV
carcinogenic risk differs by life stage, e.g., among the young, or elderly.
Charge Question B3
EPA concluded that iAs causes human cancer most likely by many different
modes of action. This is based on the observed findings that iAs undergoes successive
methylation steps in humans and results in the production of a number of intermediate
metabolic products and that each has its own toxicity. EPA asked the SAB to comment
on the soundness of its conclusion.
Summary Response
The Panel concluded that:
i) Multiple modes of action may operate in carcinogenesis induced by iAs
because there is simultaneous exposure to multiple metabolic products as
well as multiple target organs and the composition of metabolites can
differ in different organs.
ii) Each arsenic metabolite has its own cytotoxic and genotoxic capability.
iii) Inorganic arsenic (iAs111) and its metabolites are not direct genotoxicants
because these compounds do not directly react with DNA. However,
iAS111 and some of its metabolites can exhibit indirect genotoxicity, induce
aneuploidy, cause changes in DNA methylation, and alter signaling and
hormone action. In addition, iAs can act as a transplacental carcinogen
and a cocarcinogen.
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iv) Studies of indirect genotoxicity strongly suggest the possibility of a
threshold for arsenic carcinogenicity. However, the studies discussed
herein do not show where such a threshold might be, nor do they show the
shape of the dose-response curve at these low levels. In addition, a
threshold has not been confirmed by epidemiological studies. This issue is
an extremely important area for research attention, and it is an issue that
should be evaluated in EPA's continuing risk assessment for iAs.
v) Arsenic essentiality and the possibility of hermetic effects are in need of
additional research to determine how they would influence the
determination of a threshold for specific arsenic-associated health
endpoints.
1.3. Selection of Data for Dose-Response Assessment
Charge Question Cl
In the absence of human data, EPA proposed to use the bladder tumor data from
the DMAV rat bioassay for quantifying potential human cancer risk to DMAV. EPA
asked the SAB to comment on the appropriateness of this approach. The SAB was also
asked to comment on whether the iAs epidemiology data can be used to inform the
DMAV dose-response assessment which is now based on data derived from studies in rats
dosed with DMAV.
Summary Response
The Panel agreed that:
i) Given the lack of human data, the bladder tumor data from DMAV rat
bioassays, are the most suitable data set for quantifying potential human
cancer risk from DMAV. The Panel stated that the available data suggest
that the uncertainty associated with extrapolation across forms of arsenic
in the DMAV risk assessment would be greater than interspecies
extrapolation.
ii) The Panel strongly suggested that EPA's DMAV assessment discuss the
key uncertainties in using data from studies in rats to conduct human
health risk assessments. Panel responses to charge questions Al and Cl
discuss issues that members considered important to discuss in EPA's
Science Issue Paper. These issues relate to the pharmacokinetic and
pharmacodynamic similarities and differences between rats and humans in
response to arsenic exposure, the use of rodent bladder tumor models in
general, and issues in the use of rodent data for human risk assessment.
iii) The Panel considers research on these issues to be a high priority.
iv) The Panel concluded that without more detailed information on target
tissue dosimetry for arsenic species, the iAs epidemiology data would be
of limited use to inform the DMAV dose-response assessment derived
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from rat data with DMAV. Additional details are contained in the Panel's
response to charge question Cl.
Charge Question C2
EPA reviewed the available epidemiologic studies including those published since
the NRC 2001 review for U.S. populations exposed to inorganic arsenic via drinking
water. EPA concluded that the Taiwanese dataset remains the most appropriate choice
for estimating cancer risk in humans. The SAB was asked to comment on the soundness
of this conclusion and also on whether these data provide adequate characterization of the
impact of childhood exposure to i As.
Summary Response
The Panel concluded that:
i) Because of various factors (e.g., size and statistical stability of the
Taiwanese database relative to other studies, the reliability of the
population and mortality counts, the stability of residential patterns, and
the inclusion of long-term exposures), this database remains, at this time,
the most appropriate choice for estimating bladder cancer risk among
humans, though the data have considerable limitations that should be
described qualitatively or quantitatively to help inform risk managers
about the strength of the conclusions.
ii) There are other epidemiologic databases from studies of populations also
exposed at high levels of arsenic, and the Panel recommends that these be
used to compare the unit risks at the higher exposure levels that have
emerged from the Taiwan data.
iii) The Panel also suggests that published epidemiology studies of US and
other populations chronically exposed from 0.5 to 160 |ig/L inorganic
arsenic in drinking water be critically evaluated, using a uniform set of
criteria and that the results from these evaluations be transparently
documented in EPA's assessment documents. If, after this evaluation, one
or more of these studies are shown to be of potential utility, the low-level
studies and Taiwan data may be compared for concordance. Comparative
analyses could lead to further insights into the possible influence of these
differences on population responses to arsenic in drinking water.
iv) Regarding childhood exposure to iAs, it was the Panel's view that, based
on available data, it is not clear whether children differ from adults with
regard to their sensitivity to the carcinogenic effects of arsenic in drinking
water. However, the possibility of a different response in degree or kind
should not be ignored and needs to be investigated.
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1.4 Approaches to Low-Dose Extrapolation for iAs and DMAV
Charge Question Dl
EPA's Guidelines for Carcinogen Risk Assessment underscore the importance of
understanding the MOA as the basis for making judgments on how to best extrapolate
cancer risk at lower exposures. EPA concluded that available data on DMAV are not
sufficient to support development of biologically-based models and therefore opted to use
a default nonlinear low-dose extrapolation method. The SAB was asked to comment on
the Agency's scientific rationale in support of this approach and how uncertainty should
be incorporated into low-dose extrapolation.
Summary Response
The Panel concluded that:
i) Though there are adequate data to support the proposed EPA MOA,
neither the MOA postulated by the Panel, nor those postulated by EPA's
ORD or OPP contain key events expected to be a linear function of dose
ofDMAv.
ii) Several processes important to some postulated key events would have
non-linear components or are non-linear (e.g., saturable metabolic
processes, cytotoxicity, formation of heritable alterations in DNA by ROS,
cell proliferation, repair of ROS-induced DNA damage).
iii) The linear approach would be consistent with evidence for direct
genotoxicity of DMAIII/V; however, it is generally accepted that DMAvis
not directly genotoxic and neither DMA111 nor DMAV react directly with
DNA.
iv) There are insufficient data to invoke ROS-induced DNA damage as a key
event in the carcinogenic process associated with exposures to DMAV or
DMA111.
v) The nonlinear approach is more consistent with available DMAV data and
current concepts of chemical carcinogenesis.
vi) Uncertainty is best incorporated through the use of uncertainty factors that
capture pharmacokinetic and pharmacodynamic differences across species
and differences associated with sensitive populations.
vii) There are not sufficient data on comparative dosimetry in rats and humans
to make any conclusive statements about species differences in
pharmacokinetics, though available data on uroepithelial cell cytotoxicity
might allow EPA to assemble a case for pharmacodynamic equivalency.
There is presently no arsenic-specific information that can inform the
choice of uncertainty factors for sensitive human populations. Thus, at
least for now, such choices must be based on more general considerations
including EPA's science policy judgment of the degree of precaution that
it deems appropriate.
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Charge Question D2
EPA determined that the most prudent approach for modeling cancer risk from
iAs is to use a linear model because of the remaining uncertainties regarding the ultimate
carcinogenic metabolites and whether mixtures of toxic metabolites interact at the site(s)
of action. EPA asked the SAB if it concurred with the selection of a linear model
following the recommendations of the NRC (2001) to estimate cancer risk in light of the
multiple modes of carcinogenic action for iAs.
Summary Response
The Panel concluded that:
i) Inorganic arsenic has the potential for a highly complex mode of action.
ii) Until more is learned about the complex PK and PD properties of iAs and
its metabolites there is not sufficient justification for the choice of a
specific nonlinear form of the dose-response relationship.
iii) The NRC (2001) recommendation to base risk assessments on a linear
dose response model that includes the Southwestern Taiwan population as
a comparison group seems the most appropriate approach.
iv) The Panel also recommends that EPA perform a sensitivity analysis of the
Taiwanese data with different exposure metrics, with the subgroup of
villages with more than one well measurement, and using a multiplicative
model that includes a quadratic term for dose.
Charge Question D3
EPA employed the Microsoft Excel software that was previously used by the
NRC (2001) to project estimated cancer risks from iAs exposure. The SAB was asked to
comment on the precision and accuracy of this program.
Summary Response:
The Panel concluded:
i) That the EPA program conformed to the NRC (2001) recommendation for
modeling cancer hazard as a function of age and the average daily dose of
exposure to arsenic through drinking water sources.
ii) The panel did, however, identify and report to the EPA on two potential
discrepancies in the data inputs and one computational error in the portion
of the program that employs the BEIR-IV formula to evaluate excess
lifetime cancer risk from arsenic exposure.
iii) The panel made several suggestions for improvements in the model's
programming and documentation conventions as well as recommendations
for specific sensitivity analyses designed to test the robustness of the
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model to alternative formulations of the hazard function and aggregate
population data inputs.
Charge Question D4
In calculating estimated cancer risk to the US general population from drinking
water exposure to iAs, the EPA utilized epidemiologic data from Taiwan. EPA followed
the NRC (2001) recommendations to account for the differences in the drinking water
consumption rates for the Taiwanese population and U.S. populations. On the basis of
more recent data (noted in USEPA, 2005b), EPA utilized water intake adjustments for 2
to 3.5 liters/day. EPA asked the SAB to recommend a drinking water value.
Summary Response
The Panel agreed that water consumption (via drinking as water, in beverages, or
in cooking water) assumptions have a substantial impact on the assessment of arsenic's
risk. However, the Panel did not recommend specific values for EPA to use in evaluating
dose-response in the Taiwanese study nor for levels of exposure in the U.S. population
risk estimates. It did recommend that uncertainty in this parameter be evaluated for both
the Taiwanese study population and the U.S. populations at risk. The Panel
recommended that EPA should:
i) Evaluate the impact of drinking water consumption rates associated with
more highly exposed population groups with differing exposures and
susceptibilities (e.g., children, pregnant women).
ii) Incorporate variability parameters for individual water consumption into
their analysis for dose-response in the Taiwanese population as they have
done for the U.S. population.
iii) Conduct sensitivity analyses of the impact of using a range of
consumption values for the Taiwanese population.
iv) Provide a better justification for assuming different consumption levels by
gender or in the absence of such a justification, conduct additional
sensitivity analyses to examine the impact of equalizing the gender-
specific consumption level.
v) More fully articulate and document how different sources of water intake,
as well as variability, are incorporated into the risk model (e.g. data for
intake from beverages and cooking water).
Charge Question D5
As recommended by the NRC (2001) EPA considered the background dietary
intake of iAs and incorporated adjustment values of 0, 10, 30, and 50 jig per day into the
cancer modeling based on available new data. The SAB was asked to recommend a
value for the background dietary intake of iAs for both the control population and study
population of Southwestern Taiwan.
10
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Summary Response
The Panel agreed that arsenic levels in food are important considerations for
EPA's assessment of lung and bladder cancer risk associated with exposures to arsenic in
drinking water. However, the Panel did not recommend a specific value for EPA to use
in its base risk assessment. It did recommend a range of values for consideration by EPA
in its sensitivity analysis and the Panel offered suggestions to EPA for additional
analytical steps to clarify the impact of food levels of arsenic on dose-response and
exposure as it revises its risk estimates. These Panel recommendations include that EPA
should:
i) Conduct sensitivity analyses using a range of total arsenic food intake
values from at least 50 to 100 jig per day to perhaps as high as 200 jig per
day to assess the impact of this range of dietary intakes on risk of lung and
bladder cancer from exposure via drinking water in the Taiwan cohort.
ii) Not assume that the control population has an intake value of zero arsenic
from food.
iii) Apply greater rigor in their discussions of data used in these assessments
(e.g., sources, methodological and analytical issues, bioavailability).
iv) Give immediate research attention to the issue of arsenic bioavailability.
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2. INTRODUCTION
2.1. Process for Developing this Report and Structure of the Report
In response to the Agency's request (USEPA, 2005a), the SAB convened an
expert Panel to review the Agency's hazard and dose-response assessments for
dimethylarsinic acid (DMAV) and inorganic arsenic (iAs). The full EPA charge to the
SAB is in Appendix A to this advisory report. The Panel was established in accordance
with the SAB Panel Formation Process: Immediate Steps to Improve Policies and
Procedures (EPA-SAB-EC-COM-02-003). The Panel held public telephone conference
meetings and a face-to-face meeting to plan for and conduct its advisory activities. The
Panel met on September 12-13, 2005 to discuss the issues and deliberate on its response
to the charge questions. The Panel held three subsequent public telephone conference
meetings on January 24, 2006, February 23, 2006 and February 28, 2006 (see GPO,
2005a; 2005b; 2005c; 2005d; 2005e; and 2005f). The Panel considered written comments
and oral statements from the public during each of these advisory meetings. This was
also the case for the chartered SAB's public telephone conference meeting held on
November 27, 2006 to conduct a review of the draft Panel report (see GPO 2006).
Written public comments submitted for consideration at these meetings are available on
the SAB web page.
Several individuals from the public requested that the Panel consider broadening
its charge to include other human health endpoints associated with exposure to arsenic
and to undertake a quantitative dose-response assessment for arsenic induced bladder
cancer. While the Panel recognized that there is a need for the Agency to conduct a
complete and thorough review of all health effects endpoints associated with arsenic
exposure, the Panel limited its advisory to issues relevant to carcinogenicity of various
arsenicals as requested by EPA. The Panel did not conduct a full risk assessment of the
arsenicals of interest itself, because this was beyond the scope of the project and the
resources available to the SAB to conduct such an analysis.
Throughout the Panel's report writing and editing process, and during the
Chartered SAB's quality review, some Panel Members, and some of the interested public,
suggested that additions to literature subsequent to the Panel's deliberations be evaluated
and referenced in the panel's report. The Panel did not add such studies to its discussions
because its active deliberations were complete. The Panel's advice to EPA considers the
review of other relevant studies to be within its suggestion to EPA to evaluate other
endpoints, and other studies, as the Agency completes its arsenic assessments.
This advisory report is structured according to the charge questions submitted by
EPA. Subgroups of Panel members were assigned to focus on specific charge questions
(see Appendix B), and each such group was responsible for leading the discussions for
specific charge questions during the public meetings and for drafting the written
responses to the charge questions based upon the Panel's discussions and deliberations at
the meetings. All Panel members were encouraged to participate in all discussions as
well as to provide comments on the draft responses for each question during the entire
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advisory process. The Panel's draft report (dated September 15, 2006) was reviewed by
the chartered SAB and approved conditional to the Panel Chair making the series of
clarifying editorial revisions; that are now reflected in this final report which has been
approved by the Panel Chair and the SAB Chair.
2.2 Background
EPA's Office of Research and Development (ORD), the Office of Water (OW)
and the EPA Office of Pesticide Programs (OPP), requested that the EPA SAB evaluate
certain components of the EPA draft assessment of potential human carcinogenicity
associated with arsenic, and arsenic containing compounds. Information from the EPA
request is summarized in the remainder of this section of the Panel's report.
Inorganic arsenic (iAs) is found naturally in the environment and it is typically
present in soil and water at some determinate level. Human exposure to inorganic arsenic
can come from drinking water, food, air and anthropogenic sources such as wood
preservatives, industrial wastes, and certain pesticides containing organic arsenic.
Specific statutory mandates require that EPA consider human health risks
associated with arsenic and arsenic containing compounds. The Safe Drinking Water Act
(SDWA) directs EPA to establish national standards for arsenic containing compounds,
among other contaminants, in public drinking water supplies. EPA's Superfund and
Resource Conservation and Recovery Act (RCRA) programs require the evaluation of
exposure to arsenic containing compounds at locations undergoing clean up or
remediation, and the Clean Air Act, requires EPA to set air emissions standards for
certain sources of arsenic. EPA's OPP evaluates the exposure and health risks associated
with arsenicals used as pesticides in the U.S. and under the mandate of the Food Quality
Protection Agency (FQPA) is reevaluating tolerances for arsenicals, and other pesticides.
Tolerances are legal limits of pesticides on or in food or animal feed. Several organic
arsenic containing herbicides are undergoing reregi strati on and/or tolerance reassessment
(e.g., cacodylic acid which is often referred to as dimethylarsinic acid or DMAV, and the
monosodium, disodium, and calcium salts of methanearsonate acid --MSMA, DSMA,
and CAMA, collectively as referred as MMAV).
Arsenic, and arsenic containing compounds, have been the focus of many EPA
assessments as the above statutory authorities suggest. In addition, the National Research
Council (NRC) of the National Academy of Sciences (NAS) has conducted
comprehensive health sciences reviews of arsenic on at least two occasions (NRC, 1999;
NRC, 2001). EPA SAB Panels have also considered inorganic arsenic issues (US EPA
SAB, 2000; USEPA SAB, 2001).
Since the 2001 NAS review, new information has been developed on the mode of
carcinogenic action, metabolism and pharmacokinetics (PK) of arsenic and its methylated
species, and new epidemiology studies have been conducted on inorganic arsenic. EPA
considered this new information in its hazard characterization for tolerance assessment of
dimethylarsinic acid (DMAV) and methylarsonic acid (MMAV)(USEPA OPP, 2005 and
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USEPA ORD, 2005). EPA also developed a revised hazard and dose response
assessment for inorganic Arsenic (USEPA OW, 2005) which relies on the two NRC
reviews and provides an updated human health effects and dose-response assessment for
inorganic arsenic. In its charge to the SAB, EPA asked for advice on the soundness of
the major science conclusions in these two documents. These documents focus on the
assessment of DMAV and inorganic arsenic carcinogenicity (more specifically,
metabolism, mode of action, dose-response, and approaches to low-dose extrapolation of
cancer risk (see the specific Charge questions in subsections 2.2.1 through 2.2.4 and in
Appendix A to the report).
2.2.1 Metabolism and Toxic Responses of Arsenic Species
Charge Question Al. Metabolism and pharmacokinetics: Please comment on
how pharmacokinetic processes are best considered regarding the use of data derived
from direct DMAV exposure versus direct iAs exposure for cancer risk assessment.
Charge Question A2. Response to mixtures of metabolites: Given the
toxicological response profiles observed following direct exposures to iAs versus
and DMAV, and the differences in human and rodent toxicologic responses to ars
please comment on the use of data derived from rodent exposures to the organic
arsenicals versus use of data derived from direct iAs human exposure, in the DMAV
assessment.
2.2.2 Modes of Carcinogenic Action for DMAV and Inorganic Arsenic
v
Charge Question Bl. Mode of action of DMAV: Please comment on the
v
sufficiency of evidence to establish the animal mode of carcinogenic action for DMA .
Are the scientific conclusions sound and consistent with the available evidence on DMAV
and the current state of knowledge for chemical carcinogenesis. Please comment on
whether the key events in DMA's mode of action are supported by the available data.
Specifically comment on the role of: a) reactive oxygen species in producing
chromosomal damage and the strength of the evidence supporting oxidative damage as a
causal key event in DMAv/DMAin s mode of carcinogenic action versus an associative
event or a secondary consequence of cytotoxicity; b) cell proliferation and cytotoxicity
and the strength of the evidence as causal key events in DMAv/DMAin s mode of
carcinogenic action versus associative or secondary events, and c) other potential modes
of action that have substantial scientific support that may be contributing to the
carcinogenicity of DMA.
Charge Question B2. Human relevance of animal DMAV MOA: Please
comment on the relevance of the postulated key events (see Bl) to tumors in humans.
Please comment on how, if at all, differences in the human population vs. experimental
animals should be accounted for in the risk assessment for DMAV. Please comment on
the Agency's conclusion that the young are likely to respond like the adult to the
formation of bladder tumors following exposure to DMA.
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Charge Question B3. Modes of carcinogenic action from exposure to inorganic
arsenic: Please comment on the conclusion that the available data support the hypothesis
that multiple modes of action may be operational following exposure to inorganic
arsenic.
2.2.3 Selection of Data for Dose-Response Assessment
Charge Question C1. Use of animal data for DMAV: Please comment on the use
of the bladder tumor data from the DMAV rat bioassay as the most suitable dataset for
quantifying potential human cancer risk to DMAV, including the weight of evidence to
support this conclusion. Please comment on whether the iAs epidemiology data can be
used to inform the DMAV dose-response assessment derived from rat data with DMAV.
If so, please discuss how such information might be used.
Charge Question C2. Use of human epidemiological data from direct iAs
exposure: Does the SAB agree that the Taiwanese dataset remains the most appropriate
choice for estimating cancer risk in humans? Please discuss the rationale for your
response. Do these data provide adequate characterization of the impact of childhood
exposure to iAs? Please discuss the rationale for your response.
2.2.4 Approaches to Low-Dose Extrapolation for Inorganic Arsenic
and DMAV
Charge Question Dl. Mode of carcinogenic action understanding for DMAv/m
and implications for dose response extrapolation to estimate human cancer risk: Please
comment on the scientific evidence and biological rationale in support of nonlinear
versus linear low dose extrapolation approaches, which approach is more consistent with
the available data on DMAV and current concepts of chemical carcinogenesis, and how
scientific uncertainty should most appropriately be incorporated into low-dose
extrapolation.
Charge Question D2. Implementation of the recommendations of the NRC
(2001): Does the panel concur with the selection of a linear model following the
recommendations of the NRC (2001) to estimate cancer risk at this time? Please discuss
your response in light of the highly complex mode of action for iAs with its metabolites.
Charge Question D3. EPA re-implemented the model presented in the NRC
(2001) in the language R as well as in an Excel spreadsheet format. In addition,
extensive testing of the resulting code was conducted: Please comment upon precision
and accuracy of the re-implementation of the model.
Charge Question D4. Evaluation of Available literature describing drinking water
consumption rates for the southwestern Taiwanese study population: What drinking water
value does the panel recommend for use in deriving the cancer slope factor for inorganic
arsenic?
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Charge Question D5. Selection of an estimate of dietary intake of arsenic from
food: What background dietary intake (of arsenic) value does the panel recommend for
both the control population and study population of Southwestern Taiwan used in
deriving the cancer slope factor for inorganic arsenic?
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3. RESPONSE TO THE CHARGE
3.1 Overview
The SAB Arsenic Review Panel was asked to comment on the i) toxicity/
metabolic profile/bioavailability for different arsenic species, ii) the Agency's
understanding of the mode of action of arsenic carcinogenesis and implications of that on
dose response extrapolation for DMAV and inorganic arsenic, and iii) the implications of
newer epidemiology studies as well as the 2001 National Research Council
recommendations on modeling of the human cancer slope factor for inorganic arsenic.
The SAB Panel's advice is contained in sections 3.2 through 3.5 that follow.
3.2. Metabolism and Toxic Responses of Arsenic Species
3.2.1 Metabolism and pharmacokinetics (Charge Question Al)
EPA's charge states that, "Evidence from in vivo and in vitro metabolism and
pharmacokinetic studies with humans and laboratory animals suggests that the efficiency
of the methylation reaction(s) and cellular uptake varies based on which arsenical
compound is administered exogenously. Most available studies suggest that the
metabolic process in most mammals is primarily a one-way process and that following
direct exposure to DMAV significant amounts of [arsenite] (iAs In), [arsenate] (iAsv),
[methylarsonous acid] (MMA111), or [methylarsonic acid] (MMAV) at the target tissue are
not expected" (USEPA, 2005a). Charge Question A1 asks the SAB to "...comment on
how pharmacokinetic processes are best considered regarding the use of data derived
from direct DMAV exposure versus direct iAs exposure for cancer risk assessment. "
Charge questions Al and A2 address exposure to and the metabolic fate of DMAV
associated organoarsenic-containing herbicides. DMAV from these herbicides can be
degraded by microorganisms, both in the environment and in the intestinal tract, to yield
a variety of methylated and inorganic arsenic species, which have specific metabolic fates
and toxicities. The Panel's responses to questions Al and A2 do not take into
consideration potential byproducts of the microbial degradation of DMAV in the
environment. This is because EPA representatives stated during the September, 2005
Arsenic Review Panel meeting that the environmental conversion of DMAV from
organoarsenic pesticides, and the risk associated with exposures to these conversion
products, will be addressed later by EPA in a separate document.
The panel agrees with the Agency's reasoning behind this question which is
summarized at the beginning of this subsection (3.2.1). In mammalian tissues/cells
(including human), the metabolism of inorganic arsenic (iAs) appears to be a one-way
process in which iAs is converted to MMA, DMA and in some species to TMA
metabolites containing arsenic in +3 or +5 oxidation states (Vahter, 1999; Thomas, et al.,
2001). There is no evidence for demethylation of methylated arsenic species in either
animal or human tissues, though as noted in the preceding paragraph and in subparagraph
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"d" below microbial transformation is possible in the intestine. However, this issue
needs further investigation. While the step-wise addition of methyl groups is likely a
one-way process, a cycling between +3 and +5 arsenic species may occur at each of the
methylation steps due to a spontaneous oxidation of+3 species (Gong, et al., 2001;
Aposhian, et al., 2003) and non-enzymatic (Delnomdedieu, et al., 1994; Scott et al.,
1993) or enzymatic (Zakharayn and Aposhian, 1999; Radabaugh and Aposhian, 2000;
Waters et al., 2004) reduction of+5 species. Given the likely one-way character of
arsenic methylation, significant amounts of MMA or iAs are not anticipated as products
of DMAV metabolism in either rat or human tissues or urine on the basis of available
data.
In contrast, exposure to iAs may result in the production, tissue retention, and
urinary excretion of all the above iAs and methylated arsenic species. Based on data
from rodent studies, both the uptake and reduction of DMAV to DMA111 are apparently
critical steps in the activation of exogenous DMAV. It is not clear, where and to what
extent (if at all) these processes occur in humans exposed to DMAV, although it appears
that uptake may be rate limiting for further metabolism of DMAV. DMA111 is a urinary
metabolite in individuals chronically exposed to iAs (Le et al., 2000; Aposhian, et al.,
2000; Mandal, Ogra and Suzuki, 2001; Del Razo et al., 2001; Valenzuela, etal, 2005),
indicating that the capacity to reduce DMAV to DMA111 exists in human tissues. The
Panel pointed out that even the conversion of a small amount/fraction of exogenous
DMAV to DMA111 is of toxicological significance due to the significant toxicity of
DMA111. Thus, strictly from the point of view of the metabolic pattern, data derived from
DMAV exposure (in the rat), not from iAs exposure in humans, is better suited for cancer
risk assessment of DMAV. However, this approach is uncertain because of specific
metabolic differences between rats and humans, and other factors, including:
a) The uptake pathway or pathways for DMAV in humans is/are
unidentified. The expression or properties of DMAV transporters may
differ in rats and humans, leading to differences in uptake of DMAV in
tissues and organs.
b) Results of laboratory and epidemiological studies suggest that the
pattern for DMAV metabolism in rats is different from that in humans
(Figure 1). Rats metabolize DMAV to DMA111, trimethylarsine oxide
(TMAVO) (Yoshida et al., 1997; Yoshida et al., 1998; Cohen et al.,
2002), and possibly, trimethylarsine (TMA111) (Waters et al., 2004).
DMAV, DMA111, and TMAVO are urinary metabolites of DMAV in the
rat. In addition, TMAVO was also detected in urine of rats chronically
exposed to iAs (Yoshida et al., 1998). In contrast, little or no TMAVO
was found in human urine after a single dose of DMAV (Marafante et
al, 1987; Buchet et al., 1981) or after acute (Mahieu, et al., 1981;
Apostoli et al., 1997; Benramdane et al., 1999) or chronic exposures to
iAs (Vahter, 1999; Thomas et al., 2001). These data suggest that the
capacity to produce TMAVO from iAs or DMAV or to excrete TMAVO
in urine is lower in humans compared to rats. Thus, while it is
possible that the urinary TMAv/in metabolites significantly affect the
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overall toxic or cancerous outcomes in the bladder of rats exposed to
DMAV, the relative lack of these metabolites in human urine suggests
that the outcome in humans would not be as severe as in rats.
However, because the suggested toxicity differences above reflect a
very limited human data set, more research is needed to characterize
the role of TMAv/in metabolites in bladder carcinogenesis induced in
rats by chronic exposures to DMAV. Research is also needed to
determine whether the apparent absence of these metabolites in
humans is associated with a decreased susceptibility to the
carcinogenic effects of DMAV.
c) Accumulation of DMA111 in rat erythrocytes, due to a high-affinity for
binding to hemoglobin (Lu et al., 2004) contributes to a specific
kinetic pattern for DMAV in rats. It is not clear how and to what
extent this factor affects the yield and concentration of the active
arsenic species (e.g., DMA111, TMAVO, or TMAs111) in urine or in
target tissues of rats and how lower accumulation in human
erythrocytes would alter the kinetic pattern for DMAV and
toxic/cancerous outcomes of DMAV exposure in humans.
d) Microorganisms, including intestinal bacteria, have a capacity to either
methylate or demethylate arsenicals (Hall et al., 1997; Cullen et al.,
1984; Cullen et al, 1989; Lehr et al., 2003; Bently and Chasten, 2002;
Tamaki and Frankenberger, 1992; Mukhopadhyay et al, 2002; Ridley
et al., 1977; Qin, et al., 2006). Although the patterns and extent of
DMAV metabolism by human intestinal microflora are not known, it is
possible that oral exposure to DMAV results in the absorption of a
wide spectrum of arsenic metabolites produced by bacteria in the
gastrointestinal tract of exposed individuals. In contrast, bacterial
metabolism would not affect the absorption of DMAV after inhalation
or dermal exposures. Thus, arsenic species found in tissues may differ
with different routes of exposure. Interspecies differences in
endogenous intestinal bacteria may further complicate extrapolation
from rats to humans.
e) Additional factors may affect the metabolic profiles for DMAV in
humans, including co-exposures to other environmental contaminants,
deficiencies of specific nutrients (e.g., selenium) or malnutrition. For
example, poor nutrition has been shown to induce expression of
aquaglyceroporin-9 (AQP9), an iAsm/MMAm transporter (Liu et al.,
2002; Liu et al., 2004; Liu et al., 2006), 20-fold (Carbrey et al., 2003).
All the above concerns should be considered in the risk assessment of DMAV
exposure.
EPA's briefing documents presented information on a physiologically based
pharmacokinetic (PBPK) model for arsenic disposition and metabolism that is under
development. PBPK modeling might be a useful approach for integrating tissue and
excreta concentrations of arsenic metabolites resulting from exposure to the various
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forms of arsenic, including DMAV, in laboratory animals and humans. For now, the
modeling work described by EPA is in the developmental stage and is not considered
sufficiently robust to conduct interspecies extrapolations. However, the Panel strongly
encourages the Agency to proceed with PBPK model development, including laboratory
studies to obtain the kinetic constants needed to describe rates of uptake, efflux,
metabolism, and elimination of DMAV in both rats and humans. When sufficiently
validated, this model could simulate concentrations of active (toxic or carcinogenic)
metabolites in urine and bladder tissue following exposure to DMAV. This approach
could be used for dose response analysis in cancer risk assessment. Such models must be
validated for predicting tissue concentrations of active species regardless of the source of
arsenic exposure.
3.2.2 Response to mixtures of metabolites (Charge Question A2)
EPA's Charge stated that, "Tumorigenic profiles vary based on which arsenical
compound is administered exogenously. In vivo and in vitro studies indicate that each of
the arsenical compounds exhibit similarities and differences in their profiles of biological
activities. Direct exposure to iAs111 or iAs v is expected to result in more of a mixture of
toxic metabolites than for direct exposure to DMAV; the mixture of metabolites is
expected to vary based on which chemical is administered exogenously. The potential
mixture of metabolites following direct exposure to DMAV appears less complex as
compared to iAs" (USEPA, 2005a). Charge Question A2 asks, "Given the toxicological
response profiles observed following direct exposures to iAs versus MMAV andDMAv,
and the differences in human and rodent toxicologic responses to arsenicals, please
comment on the use of data derived from rodent exposures to the organic arsenicals
versus use of data derived from direct iAs human exposure, in the DMAV assessment. "
The Panel believes that neither rodent laboratory data on organic arsenicals nor
data from studies of the results of human exposures to inorganic arsenic provide an
optimal basis for the assessment of DMAV exposures in humans. This is because of the
differences between the metabolic profiles for inorganic arsenic and DMA, and because
of interspecies differences in the metabolism of both arsenicals. The panel agrees that
using the data from rodent exposures to DMAV may, at this time, be the most reasonable
approach for the DMAV assessment.
The reasoning behind this response is linked to the answer to charge question Al
above (see section 3.2.1). The metabolism of iAs yields a wide spectrum of metabolites
(Figure 1) some of which (iAsin/v, MMAIII/V) are apparently not produced during the
metabolism of exogenous DMAV. The production of iAs and MMA metabolites may be
associated with specific toxic or cancerous endpoints that are absent in DMAV exposure
in rats or humans except when there is a significant co-exposure to iAs as is often found
in U.S. drinking water supplies, or in food or the environment. The Panel notes that there
are no published data on toxicological responses to DMAV in humans. The toxic and
carcinogenic effects of DMAV have been examined only in rodents, mainly in rats.
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Rat
r
AsvO43-+2e--
(iAsv)
arsenate
X
V
Human
-> AsIHO33- + CH3+ -> CH3 AsvO32- + 2e -> CH3 AsmO22- + CH3+ -
(iAs111) (MMAV)
arsenite methylarsonic
acid
(MMA111)
methylarsonous
acid
-I- *~V*V
-*(CH3)2AsvO2-+2e-
(DMAV)
dimethylarsinic
acid
^
-> (CH3)2AsHIO-
(DMAm)
dimethylarsinous
acid
J
+ CH/ -* (CH3)3AsvO + 2e
(TMAVO)
trimethylarsine
oxide
-> (CH3)3Asra
(TMAm)
trimethylarsine
^s
Figure 1. Schema of Inorganic Arsenic Metabolism in the Rat and Human: The metabolic pathway for inorganic arsenic in
the rat and human involves a stepwise addition of methyl groups to yield methylarsenic (MMA), dimethylarsenic (DMA), and
trimethylarsenic (TMA) metabolites that contain trivalent arsenic (As111) or pentavalent arsenic (Asv). Results of epidemiological and
laboratory studies suggest that while MMA and DMA are products of this metabolic pathway in both rats and humans, only rats
excrete significant amounts of TMAVO in urine when exposed to inorganic arsenic, MMA or DMA. In addition, in vitro methylation
of inorganic arsenic by recombinant rat, but not human arsenic (+3 oxidation state) methyltransferase produces TMA111. Although
alternative pathways have been suggested for inorganic arsenic metabolism and additional methylated metabolites were found in the
urine of rats and humans exposed to arsenicals, more research is needed to determine the significance of these pathways or metabolites
for inorganic arsenic or DMA metabolism in both species.
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However, a significant degree of uncertainty is associated with this approach due
to the metabolic differences between rats and humans and due to other factors, including
those listed in the response to charge question Al above. The differences in the
production and urinary excretion of TMAIII/V species that could affect the toxic and
cancer outcomes of DMAV exposure are of a particular concern to this panel. TMAVO is
a hepatocarcinogen in rats (Shen et al., 2003). TMAm is apparently more potent than
DMA111 in damaging purified DNA in in vitro systems (Andrews, et al., 2003). On the
other hand, both TMAVO and TMA111 are less acutely toxic or cytotoxic than DMA111
(Yamauchi et al., 1990; Cullen, 2005; Sakurai et al., 1998; Ochi et al., 1994). The
contribution of these two metabolites to cytotoxicity and carcinogenesis in the urinary
bladder of rats exposed to DMAV remains unclear. This uncertainty should be properly
addressed in the risk assessment for DMAV exposure in humans.
3.3 Modes of Carcinogenic Action for DMAV and Inorganic Arsenic
3.3.1. Mode of Action of DMAV (Charge Question Bl)
EPA's Charge stated that, "When relying on laboratory animal data, two critical
assumptions are made: (i) data on animal tumors are predictive of human cancer, and (ii)
animal tumor effects found at high experimental doses predict human risk at lower
exposures. An understanding of a chemical mode of carcinogenic action can help inform
the above assumptions. In the case of DMAV, mode of action (MOA) data are available
and were evaluated using the framework described in EPA's cancer guidelines" (USEPA,
2005a). Charge Question Bl asks the SAB to "... comment on the sufficiency of evidence
to establish the animal mode of carcinogenic action for DMAV. Are the scientific
conclusions sound and consistent with the available evidence onDMAv andthe current
state of knowledge for chemical carcinogenesis? " In addition, the Charge asks the SAB
to " ...comment on whether the key events in DMA 's mode of action are supported by the
available data. Specifically comment on the role of: a) reactive oxygen species in
producing chromosomal damage and the strength of the evidence supporting oxidative
damage as a causal key event in DMAV/DMAIU s mode of carcinogenic action versus an
associative event or a secondary consequence of cytotoxicity; b) cell proliferation and
cytotoxicity and the strength of the evidence as causal key events in DMAv/DMAm s mode
of carcinogenic action versus associative or secondary events, and c) other potential
modes of action that have substantial scientific support that may be contributing to the
carcinogenicity of DMA.
The Panel concluded that there are adequate data to support a MOA for bladder
carcinogenesis induced by high doses of DMAV in the rat that involves cytotoxicity to the
bladder epithelium and increased, sustained regenerative proliferation as key events. The
urine of DMAv-treated rats contains DMA111 at levels that cause necrotic cytotoxicity in
vitro, so it is reasonable to postulate that DMA111 might mediate the necrotic cytotoxicity
in the rat bladder. However, the rat (unlike the human) metabolizes a significant fraction
of exogenous DMAV to TMAVO (Cohen et al., 2002; Yoshida et al., 1997, 1998) and
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possibly to TMA111 (Waters et al., 2004). Thus, these compounds cannot be excluded as
additional mediators of the necrotic cytotoxicity in the bladder of rats exposed to DMAV.
The Panel thought that there are not sufficient data to invoke reactive oxygen
species (ROS)-induced DNA damage as a key event in the carcinogenic process
associated with exposures to DMAV or DMA111 for the reasons discussed in the following
paragraphs.
Chemically, neither oxidation of As111 to Asv nor reduction of Asv to As111 can
produce an oxygen radical in the absence of other reactants. Arsenic can only undergo
two-electron reduction (no free electron or radical to donate to oxygen). Although there
are indirect sources of ROS that can participate in arsenite-stimulated cell signaling (e.g.
stimulation of NADPH oxidase; Smith et al., 2001) or arsenic trioxide-mediated
apoptosis via mitochondrial collapse (Jing et al., 1999), these have not been demonstrated
for DMA. Arsenic compounds could also increase ROS by promoting an inflammatory
response in many tissues. This may contribute to carcinogenesis, but it is not likely to be
the primary MO A for carcinogenesis.
Much of the argument suggesting that the mode of action of DMAv-induced
bladder cancer involves ROS-induced chromosome damage derives from studies on
DMAIH-induced DNA damage. Very high cytotoxic concentrations of DMA111 have been
shown to induce DNA damage in cell-free systems and in intact cells (Mass et al., 2001),
possibly via an ROS-mediated mechanism or by dimethylarsine (Yamanaka et al., 2003;
Kitchin and Ahmad, 2003; Nesnow et al, 2002; Andrews et al., 2003). However, cellular
genetic toxicology assays of DMA do not support an ROS-dependent mechanism.
Neither DMAV nor DMA111 is significantly mutagenic at loci which are known to detect
oxidant DNA damage. Neither compound was mutagenic in the Ames Salmonella strain
TA104, a strain developed primarily to aid in the detection of oxidative mutagens, nor
were • 'prophage induced (Kligerman et al., 2003). Prophage induction (which depends
on theE1. coli SOS system, a system responsive to DNA damage) was readily detectable
after treatment with other agents acting by oxidant mechanisms, such as bleomycin,
carbon tetrachloride (+S9), hydrogen peroxide, and iron compounds (Rossman et al.,
1991).
DMAV was either negative or very weakly positive at extremely high doses in a
number of other test systems which can detect oxidative mutagens (Moore et al., 1997,
Kligerman et al., 2003; Oya-Ohta et al., 1996). Treatment of Muta™mouse with DMAV
(10.6 mg/kg per day) IP for 5 days caused only a (not significant) 1.3-fold increase in
lacZ mutations in the lung, but not in the bladder or bone marrow (Noda et al., 2002).
DMAV presumably could be c<
negative results in this assay.)
DMAV presumably could be converted to DMA111 in mouse liver. (Arsenite also gave
The single study of DMA in the mouse lymphoma assay (Kligerman et al.,
2003), which detects clastogens as well as point mutagens at the TK locus, showed no
significant effect on mutant fraction at concentrations <1.5 jiM (38% survival) in the agar
assay. "Significant" was defined as at least a 2-fold increase over control, but no
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statistical analysis was done, only a single assay is shown, and there is only one
"significant" response, at 1.51 jiM. (This assumes a background mutant fraction of
between 38 and 50 X 10"6). A microwell assay using the same cells showed a
"significant" effect at 2.56 |iM (9% survival).
Kligerman et al. (2003) argued that DMA111 (and MMA111) are basically clastogens
and not point mutagens. The clastogenesis studies suffer from the same problems as the
mutagenesis studies: no statistical analysis and single data points at some doses.
"Significant" (defined as a 2-fold increase) effects are seen only at toxic doses (toxicity
data are not given but can be inferred from other mammalian cell data). In addition, since
cytogenetic assays do not require cell survival for scoring, when clastogenic effects are
seen in a population of cells with low survival, it is not possible to determine whether
those cells with chromosome aberrations would be among the survivors, and thus capable
of resulting in a tumor. Examination of chromosomes in tumor and pre-tumor tissues in
the rat bladder model might establish whether specific chromosome aberrations are
associated with DMAv-induced bladder cancers.
Even model clastogens such as ionizing radiation can also be detected as
mutagens at single gene loci such as HPRT, a useful locus for studying mutations in vitro
as well as in vivo (unlike TK). Thus, if DMA111 was really a clastogen acting by ROS, it
should cause increased deletion mutagenesis at the HPRT locus. More research on the
ability of arsenic metabolites to induce gene mutations in vivo should be carried out.
The fact that (some) antioxidants blocked DMAv-induced bladder cancer in the
rat does not provide evidence as to the origin of the oxidants nor where they act.
Activation of NADPH oxidase (Smith et al., 2001) or inhibition of GSH reductase
(Styblo et al., 1997) could increase oxidants. Tissues subjected to continuing cellular
assault produce a number of cytokines whose signaling may be modulated by oxidants
(even in the absence of frank inflammation). Nuclear factor-kappaB (NFkB), which is
activated by low-dose arsenite via oxidants (Barchowsky et al., 1996), is thought to
provide a link between inflammatory signaling and carcinogenesis, as well as providing
survival signaling to block apoptosis in damaged cells that might otherwise die. NFkB is
a transcriptional regulator of genes including cyclooxygenase-2 (COX-2), which is also
induced by arsenite (Trouba and Germolec, 2004). Research is needed to determine
whether bladder cells undergoing stress-related proliferation in the rat DMAV
carcinogenesis model show effects on NFkB and other signaling pathways, similar to
those seen with arsenite.
Given the preponderance of scientific evidence to date (which is reviewed above
in this section), the principal MOA for DMAV does not appear to be mediated via the
ROS-induced DNA damage pathway. Rather, the MOA is likely to be sustained
cytotoxicity followed by genomic instability as a result of stress-related proliferation.
Permanent genetic change is necessary for carcinogenesis, and it is unlikely that
increased proliferation alone in the absence of increased genomic instability will result in
the multiple changes needed to transform a normal cell into a tumor cell. The mechanism
of cell killing by DMAV or DMA111 is not known. Regardless of how the cells die, there
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is substantial evidence supporting the hypothesis that continual proliferation of surviving
cells under conditions of stress results in genomic instability (Karpinets and Foy, 2005).
For example, in the case of arsenite this would involve such factors as:
a) Inducing intracellular proliferative signals and over-riding cell cycle
checkpoints (reviewed in Rossman, 2003),
b) Blocking DNA repair (reviewed in Rossman, 2003),
c) Inhibiting GSH reductase (Styblo et al., 1997) and thioredoxin reductase (Lin et
al., 2001),
d) Inducing stress-related survival signals to block apoptosis (Pi et al., 2005; Wu et
al. 2005),
e) Effects on thiols in tubulin and cytoskeletal proteins, interfering with
microfilament function and cytoskeletal changes (Li et al., 1992; Ling et al.,
2002; Ochi et al., 1999),
f) Affecting DNA methylation levels, (Chen et al., 2004),
g) Inducing oxidant signaling (Barchowsky et al., 1999), and
h) Effects on hormone function (Bodwell et al., 2004).
More research should be carried out on cells undergoing stress-related proliferation
in the rat bladder model to determine whether these same programs have come into play
for DMAV. Changes in DNA methylation patterns have just been demonstrated in
arsenic-associated human bladder cancers (Marsit et al. 2006), making this a priority for
study in the rat model.
Live cells exposed to the contents of necrotic cells may experience additional stress
signals similar to that seen in the "bystander effect" after ionizing radiation (Iyer and
Lehnert, 2000) or via cytokines from inflammatory cells. Although there is no direct
evidence to support this mechanism in the rat bladder cancer model, it is of interest that
heat-killed E. coli instilled into the bladder was found to increase bladder carcinogenesis
by N-methyl-N-Nitrosourea (Yamamoto et al., 1992), presumably by an inflammatory
mechanism. Research on this topic should be carried out both in vivo and in vitro.
Further, generation of low levels of oxidants from enzymatic sources (Smith et al., 2001)
or possibly by uncoupling of mitochondrial oxidations (if DMAV can act in a manner
similar to arsenate) may contribute to effects on cell signaling and transcriptional
activation, as well as increase oxidant DNA damage.
In summary, the Panel postulates that the mode of action for DMAV involves the
following key events:
a) Reductive metabolism of DMAV to DMA111.
b) High concentrations of DMA111 in urine cause urothelial cytotoxicity. Some
toxicity may also be caused by DMAV itself.
c) Continuous exposure and persistent stress associated regenerative cell
proliferation leads to genomic instability, acquisition of genetic alterations,
clonal expansion of altered cells and eventually tumors.
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This MO A, as well as the original MO A suggested by EPA, depends upon
prolonged extensive cytotoxicity in the bladder. Without the continual cytotoxicity,
sustained stress-associated proliferation would not occur. The tumor response in the rat
bladder system is non-linear, as is the key event (i.e. the necessity for necrotic
cytotoxicity). Since the MOA involves cytotoxicity, doses below those causing
cytotoxicity would not be expected to cause tumors. The other events mentioned above
would not be sufficient to cause tumors in the absence of the cytotoxicity and the
resulting proliferative response.
3.3.2 Human relevance of animal DMAV MOA (Charge Question B2)
EPA states that, "There are little or no scientific data to suggest that if sufficient
DMA111 were present, key precursor events and ultimately tumor formation would not
occur in humans directly exposed to DMAV" Charge Question B2 asks the SAB to
" ...comment on the relevance of the postulated key events (see Bl) to tumors in
humans... "and to comment on how, if at all, differences in the human population vs.
experimental animals should be accounted for in the risk assessment for DMAV.
If high enough (cytotoxic) concentrations of DMAV or DMA111 were present in the
human urine or bladder after exposure to DMAV, it is plausible that a similar response
(necrosis followed by regenerative, stress-associated proliferation) would take place.
However, no data are available to support or reject this assumption. No studies have
been carried out on DMAv-induced bladder cancer in humans, so it is not known at this
time whether there have been any cases. Concentrations high enough to cause necrosis in
the bladder might be achievable in an industrial accident or deliberate poisoning. It is not
clear whether a repeated or chronic exposure to DMAV from the environment could
produce cytotoxic concentrations of critical metabolites in human urine. Even in the case
of high exposure, the exposures would probably have to be repeated often enough to
produce persistent necrosis and regeneration in order to cause cancer.
As already mentioned in Charge Question Al above, DMAV is converted to
TMAVO, and possibly TMA111, more efficiently by rats than by humans. TMAVO is a
hepatocarcinogen in rats (Shen et al., 2003). TMA111 is more potent than DMA111 in
damaging DNA in in vitro systems (Andrews et al, 2003). Thus, although acute toxicities
of TMAVO and TMA111 are lower than that of DMA111 (Ochi et al., 1994; Sakurai and
Kaise, 1998; Yamauchi et al., 1990), these metabolites could contribute to the MOA for
DMAv-induced bladder cancer in rats. The extent of this contribution is unknown.
However, it is possible that the rat data overestimates the human risk for bladder cancers
from DMAV.
No studies have been done in either animal models or in human populations to
determine whether the young are at greater or lesser risk with regard to DMAv-induced
carcinogenesis, or whether there is greater or lesser risk during any other life stages.
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3.3.3 Modes of carcinogenic action from exposures to inorganic
arsenic (Charge Question B3)
EPA stated that, "Inorganic arsenic (iAs) undergoes successive methylation steps
in humans, resulting in the intermediate production of iAs In, MMAV, MMA111, DMAV,
and DMA111. Each arsenical metabolite exhibits its own toxicity." Charge Question B3
asks the SAB to "...comment on the conclusion that the available data support the
hypothesis that multiple modes of action may be operational following exposure to
inorganic arsenic."
The Panel agrees that multiple modes of action may operate in carcinogenesis
induced by inorganic arsenic. This is because there is simultaneous exposure to multiple
metabolic products as well as multiple target organs. There are differences in metabolic
capability and probably transport into and out of different organs for different metabolic
products, so that the composition of the metabolites can differ in different organs as well.
Each of the metabolites has its own cytotoxic and genotoxic capability. In general, the
pentavalent compounds are less cytotoxic and genotoxic than are the trivalent
compounds.
In the remainder of this section of the report, the Panel discusses studies of
indirect genotoxic effects associated with iAs and/or its metabolites, as well as the notion
that iAs might have some beneficial effects at very low doses. Taken together, these
studies suggest the possibility of a threshold. However, the Panel does not identify what
the threshold might be, nor does it describe the shape of the dose-response curve, rather it
leaves that to be addressed by EPA in its final assessment based on the outcome of EPA's
evaluation of the relevant literature. The Panel identifies this as an extremely important
area for research attention.
In the strictest (and original) definition, genotoxic carcinogens, i.e., direct
carcinogens (or their metabolites) damage DNA by covalently binding to DNA or
intercalating into the DNA-helix. Indirect genotoxicity occurs through interactions with
non-DNA targets leading to genotoxic effects. Non-DNA targets, (e.g. proteins) exist in
many copies per cell, thus a single event is unlikely to have any significant consequences.
This suggests a threshold for effects associated with such events. The modes of action of
"non-genotoxic" carcinogens are numerous, and can include regenerative cell growth
following cytotoxic effects, modulation of metabolizing enzymes, inhibition of DNA
repair, induction of peroxisome proliferation, stimulation of oxidative stress or other
signaling resulting in suppression of apoptosis, loss of cell cycle control, and stimulation
of proliferation. A number of indirect genotoxic events are listed in Table 1.
The genetic toxicology of iAs111 has been previously reviewed (Rossman, 1998,
2003; Basu et al., 2001). The interpretation of the genotoxicity of arsenic compounds is
difficult because of the very high cytotoxic concentrations used in many studies and the
lack of analysis for statistical significance in many studies. Another part of the problem
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Table 1. Some potential mechanisms for indirect genotoxicity of
Inorganic Arsenic (iAs)
Potential Mechanisms
Interference with DNA repair
Interference with cell cycle control proteins
Interference with DNA replication
Blocking apoptosis of cells with DNA damage
Interaction with nuclear proteins such as topoisomerases or spindle
proteins
Nuclease and protease release from lysosomes or dead cells
Protein denaturation leading to genomic instability
Production of or change in reactive oxygen species leading to altered
signaling
Other changes in gene expression (e.g., COX-2; Trouba and
Germolec, 2004)
Interference with oxidative phosphorylation
Changes in ionic concentration, pH, or osmolarity
Altered DNA methylation
stems from inappropriate (or absent) assessment of toxicity of arsenic compounds
(Komissarova et al., 2005). Low concentrations (even 1 jiM) of iAs111 can cause
apoptosis in human cells that can only be detected 48 hours (or more) after exposure and
cytotoxicity assays (other than clonal survival) are usually performed too soon after
exposure to enable identification of apoptotic cells after arsenite exposure. Thus, many
"positive" genotoxicity results (especially in cytogenetic assays) could have been
conducted too soon and thus they could be reported for dead or dying cells. In such
cases, they would only be useful in describing a MO A if the cells continued to live and if
the genotoxic effect noticed was consistent with effects seen in tumorigenesis studies in
animals and in human tumors. In the absence of such tumorigenesis data, cell
transformation studies can yield some insight into MOA.
in
Arsenite, i.e., iAs (and other arsenicals) does not exhibit direct DNA binding
and the inability of iAs111 to induce the SOS system in E. coli is consistent with its lack of
reaction with DNA (Rossman et al., 1984). In mammalian cells, highly toxic
concentrations of both inorganic and organic arsenic compounds in vitro cause
chromosome breakage, which some have attributed to ROS-induced DNA strand breaks
but which might be caused directly by other free radical species (Yamanaka and Okada,
1994; Andrews, et al. 2003). Cellular DNA strand breakage and clastogenicity are
limited almost exclusively to trivalent species. Unlike many other carcinogens, iAs111 is
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an extremely weak (or insignificant) mutagen at single gene loci such as HPRT or TK in
mammalian cells (Rossman, 1998, 2003). However, iAsm (but not MMA111) at low
(nontoxic) concentrations can induce delayed indirect mutagenesis at the HPRT locus
after >15 generations as a secondary result of genomic instability (Mure et al., 2003).
The argument has been made that arsenite is a clastogen that causes
predominantly multilocus deletions, and that such deletions near the HPRT locus (which
is located on a single active X chromosome) may be lethal, accounting for the lack of (or
extremely weak) mutagenesis by arsenicals at the HPRT locus (Hei et al., 1998).
However, molecular analysis of mutations in the HPRT gene shows that large deletions
(up to -3.5 Mb) can be tolerated in the HPRT region of the human X chromosome
(Nelson et al., 1995; Lippert et al., 1995). Despite this, attempts have been made to find
genetic markers more likely to detect large deletions. Also, iAs111 was an insignificant
mutagen, and only at toxic doses, in transgenic Chinese hamster G12 cells (a derivative
of V79 cells) (Li and Rossman, 1991). These cells can detect clastogens causing
deletions in the single copy of the E. coli gpt gene inserted into Chinese hamster
chromosome 1. Similar results (extremely weak mutagenesis at toxic arsenite
concentrations) are seen in mouse lymphoma cells, which can tolerate deletions at the TK
locus due to its autosomal location (Moore et al., 1997), at the transgenic gpt locus of
AS52 Chinese hamster ovary cells (Meng and Hsie, 1996) and in AL cells, which are
CHO-K1 cells containing a single copy of human chromosome 11 (Hei et al., 1998).
In vivo, iAs111 induced micronuclei (MN) in mouse peripheral blood lymphocytes
and in mouse bone marrow (Tinwell et al., 1991; Noda et al., 2002). Humans exposed to
iAs111 show increased MN and sometimes chromosome aberrations in lymphocytes,
exfoliated bladder epithelial cells, and buccal epithelial cells (reviewed in Basu et al.,
2001). In vivo studies on genotoxic activity of methylated arsenic species are limited to a
small number of studies in rodents. IP injections of high doses of DMAV induced a slight
but insignificant increase in mutagenesis in the Muta™Mouse lung, but not in bladder or
bone marrow. Also, iAs111 was negative in this assay (Noda et al., 2002). High
concentrations of DMAV administered orally to mice caused oxidative damage and DNA
strand breaks in the lung (not a target organ for DMAV carcinogenesis). The strand
breaks were attributed to dimethylarsine, via the dimethylarsenic peroxy radical
(CH3)2AsOO- (Yamanaka and S. Okada, 1994). DMAV also induced aneuploidy in
mouse bone marrow cells (Kashiwada et al., 1998).
As noted in the previous paragraph, micronuclei are induced by iAs111 in vivo, and
MN frequency is increased in humans exposed to iAs111 in drinking water. Because of
this, it is important to consider the significance of MN for MOA. MN are defined as
small, round, DNA-containing cytoplasmic bodies formed during cell division by loss of
either acentric chromatin fragments or whole chromosomes. The two basic phenomena
leading to the formation of MN are chromosome breakage (double strand breaks
associated with clastogenesis) and dysfunction of the mitotic apparatus leading to
aneuploidy (change in chromosome number from the normal diploid or haploid number
other than an exact multiple). MN as a result of clastogenesis contain acentric
chromosome or chromatid fragments while MN associated with aneuploidy contain
29
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whole chromosomes. Currently, the most widespread and reliable assay to identify whole
chromosomes in MN is by fluorescent label of their kinetochores (with antibodies) or
their centromeres (with DNA probes). However, only a few laboratories routinely use
these techniques because they are very costly. In most studies, there is not enough
information to determine whether the MN result from: 1) toxicity, 2) clastogenicity, or 3)
non-dysjunction (leading to aneuplody). Also, MN in cells trigger apoptosis, so many
cells with MN will have no progeny.
In a study of 18 arsenic-exposed individuals (average 1,312 jig arsenic/L drinking
water) and 18 matched controls (16 |ig/L), the exposed group had a 1.65-fold increase in
MN with acentric fragments (p=0.07) and a 1.37-fold increase in MN with whole
chromosomes (p=0.15) (Moore et al., 1996). The combined difference (1.8-fold) was
significant. Thus, exposure to iAsm induces MN by multiple mechanisms. In normal
human fibroblasts, low dose, long term exposure to iAsm is aneugenic, inducing MN with
whole chromosomes, but high dose, short term exposure is clastogenic, inducing MN
with chromosome fragments (Yih and Lee, 1999). Evidence supports an aneugenic role
for iAs111 in many other cells at concentrations lower than those causing chromosome
aberrations (Kochhar et al., 1996; Vega et al., 1995; Ramirez et al., 1997; Huang and Lee,
1998; Moore et al., 1997; Sciandrello et al., 2002). Of importance is the association of
aneuploidy with malignant transformation induced by arsenite and DMA111 (Ochi et al.,
2004; Chien et al., 2004). Aneuploidy is an event that has a threshold (Kirsch-Volders et
al., 2002), whereas many people assume that clastogenesis does not (at least for ionizing
radiation) even though repair of radiation-induced DNA damage exists. The
development of aneuploidy is a marker of genomic instability and is typical of many
tumors. IP injection of DMAV in mice induced aneuploidy, but no chromosome
aberrations, in bone marrow (Kashiwada et al., 1998). (DMA would be converted to
DMA111 in the mouse, so the active a
with high iAs111 exposure showed hiŁ
bladder tumors (Moore et al., 2002).
DMA111 in the mouse, so the active agent may be DMA111). Bladder tumors in patients
with high iAs111 exposure showed higher levels of aneuploidy compared with other
Genomic instability can result from changes in DNA methylation in iAs111-treated
cells. The first report of arsenite inducing DNA methylation changes was the increased
cytosine methylation in the p53 promoter in human adenocarcinoma A549 cells (Mass
and Wang, 1997). Later it was found that there was both hypo- and hypermethylation (of
different genes) in human kidney UOK cells treated with iAs111 (Zhong and Mass, 2001).
When SHE cells or rat liver TRL1215 cells were transformed by iAs111, specific
oncogenes were more highly expressed due to hypomethylation (Zhao et al., 1997;
Takahashi et al., 2002) and there was evidence of decreased DNA methyltransferase
activity (Zhao et al., 1997). These findings are consistent with the usual DNA
methylation changes observed in cancer, in which global methylation is reduced but some
gene specific promoter methylation is increased (Baylin and Herman, 2000). Arsenite
(iAsin)-induced DNA hypomethylation and altered gene expression has been
demonstrated in mouse liver (Chen et al., 2004), in hepatocellular carcinoma derived
from transplacental iAs111 exposure (Waalkes et al., 2003), and in prostate epithelium
where the hypomethylation was shown to activate K-ras (Benbrahim-Tallaa, et al., 2005).
In a study of iAs111 exposed individuals in India, increased levels of hypermethylated p!6
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and p53 gene promoters were seen in blood DNA (Chanda et al., 2006). Methylated CpG
sites are mutational hotspots (e.g. by a second agent), methylation changes affect gene
expression, and hypomethylation leads to genomic instability. Low concentrations of
iAsm induce delayed mutagenesis and chromosome aberrations that might be mediated
by hypomethylation (Mure et al. 2003; Sciandrello et al., 2004). This is a mechanism
that might also explain transplacental carcinogenesis.
There are a number of non-genotoxic actions of arsenite (and perhaps MMA111 and
DMA111) that can contribute to the carcinogenic process. The role of ROS in (low dose)
arsenic carcinogenesis is probably via signaling changes rather than as a genotoxicant
(otherwise, one would expect more mutagenesis). This may contribute to carcinogenesis,
but it is not likely the primary MOA for arsenic carcinogenesis. Cell signaling can be
affected by arsenite via low levels of oxidants that do not cause DNA damage (reviewed
in Simeonova and Luster, 2004). Low iAs111 concentrations increased oxidant signaling
and oxidant-dependent activation of nuclear factor kappaB (NFkB) in the absence of
DNA damage in human endothelial cells (Barchowsky et al., 1999). The increased
oxidants appear to result from activation of membrane-bound NAD(P)H oxidase.
Arsenite (iAsin)-induced signaling results in expression of inflammatory cytokines such
as IL-8 that can mediate atherogenesis (Simeonova and Luster, 2004). Arsenite (iAs111)
also increases ROS by promoting an inflammatory response in many tissues. In addition,
there is redox chemistry involved in iAsm-dependent signaling in that arsenite binds to
protein thiols (particularly vicinal thiols) to stimulate signaling cascades or affect DNA
repair. Arsenite (iAs111) interaction with thiols is a redox reaction, but oxygen radicals are
not involved.
Exposure to low, non-toxic doses of iAs111 enhances positive growth signaling
(reviewed in Rossman 2003), which can readily contribute to hyperplastic pre-cancerous
skin growth. Arsenite (iAs111) can disrupt glucocorticoid receptor (GR) and other steroid
signaling at very low doses, and it has been suggested that these effects on GR may affect
carcinogenesis (Kaltreider et al., 2001). This may also affect other disease processes,
such as cardiovascular disease, diabetes and other diseases that have been associated with
iAs exposure, since GR and other steroid receptors have been shown to be important in
these diseases as well.
Animal studies indicate that for some organs, transplacental carcinogenesis after
maternal exposure to iAs111 occurs. This includes the formation in C3H mice of tumors of
the lung and liver, target sites of potential human relevance, after exposure to arsenic in
utero. In addition, in utero arsenic induces tumors of the ovary and adrenal, sites not
observed in humans to date. The C3H mouse was selected in these studies because it is,
in general, sensitive to chemical carcinogenesis, although this strain shows spontaneous
tumor formation in several tissues. Recent work has shown that with gestational
exposure to CD1 mice, inorganic arsenic is a complete carcinogen in the female offspring
(Waalkes, et. al., 2006). The CD1 mouse strain is noteworthy as having a well defined,
low rate of spontaneous tumors. EPA's revised assessment document should take note of
this important development. Other studies indicate that in skin, neither iAs111 nor iAsv is
a complete carcinogen, but they act as enhancers (cocarcinogens, sometimes mistakenly
-------
called "promoters") with other agents. Arsenite (iAs111) acts as a cocarcinogen with solar
UV light (Rossman et al. 2001; Burns et al., 2004) and arsenate is cocarcinogenic with
9,10 dimethyl 1-2-benzanthracene (Motiwale et al., 2005). This leaves open the
possibility that a cocarcinogenic MOA may also operate for other organs, but this
remains to be investigated.
Arsenite (iAsin)-enhanced UV carcinogenesis could result from acquired
resistance to UV-induced apoptosis. Such resistance was recently demonstrated in
human keratinocytes (HaCaT) treated with 0.1 |jM arsenite for 28 weeks (Pi et al., 2005).
In mouse keratinocytes, the repair of UV-induced 6-4 photoproducts was slowed by acute
5.0 |jM (24 hr) arsenite exposure, which also inhibited the UV-induced apoptosis as
indicated by TUNEL flow cytometry and by reduction of caspase 3/7 activities (Wu, et
al., 2005). Arsenite (iAs111) also blocked UVB-induced apoptosis in human keratinocytes
(Chen et al., 2005). One mechanism by which iAs111 may perturb apoptotic pathways is
by PBK-mediated phosphorylation of PKB (Akt). When PI3K activity was inhibited by
Wortmannin or LY294002, arsenic-induced apoptotic resistance was also blocked (Pi et
al., 2005).
Table 2 lists some activities of iAs111 (or its metabolites) that might explain how
iAs111 can act as a transplacental carcinogen and a cocarcinogen but not a complete
carcinogen in neonatal and older animals.
In the future, it will be important to determine whether the trivalent arsenic
metabolites can induce tumors in vivo or transform or mutate keratinocytes and other
major target cells of arsenic at biologically relevant concentrations. The mechanism of
iAs-induced carcinogenesis is likely to be different in different tissues, with contributions
from all the various arsenic species present in that tissue.
There have been a number of reports claiming an essential role for iAs in various
animal species (chick, goat, hamster, pig, rat), but many of these reports exist only in
abstracts or in meeting reports (reviewed in Uthus, 1992; Nielson, 1996). Reports in the
peer-reviewed literature follow. A study of arsenic-deprived goats found muscle atrophy,
reduction in oxidative enzymes and abnormal mitochondria in muscle, possibly via
disturbance of calcium metabolism (Schmidt et al., 1984). Studies by Uthus (1990, 1992)
suggest that iAs has a role in methionine/methyl metabolism. Arsenic (iAs)-deprived rats
had decreased plasma taurine, hepatic polyamines, and S-adenosylmethionine
decarboxylase (needed for polyamine synthesis). Arsenic (iAs)-deprivation as well as
iAs excess caused DNA hypomethylation in rat liver. The same effect was seen in Caco-
2 cells. Arsenic (iAs) deprivation or excess also increased the formation of aberrant
colon crypts in rats treated with dimethyl hydrazine (Uthus and Davis, 2005), suggesting
a cocarcinogenic effect. So far, no exact biochemical mechanism linking any iAs species
with methionine/methyl metabolism has been found, but the fact that many laboratories
have reported effects of iAs111 on DNA methylation makes this an important area of study.
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Table 2. Activities of iASm that may contribute to its cocarcinogenic
and/or transplacental carcinogenic action
Activities
DNA repair inhibition
Increased oxidants (signaling changes)
Gene dosage effects (aneuploidy, amplification)
Altered DNA methylation
Proliferative response
Increased angiogenesis
Effects on immune system (not discussed; see Vega etal., 2004)
Inhibition of apoptosis
Hormonal effects
Delayed mutagenesis (not enough generations in vivo but maybe
enough if transplacental or added to a genotoxic agent?)
Hormetic effects of iAs (beneficial effects at very low doses) have also been
suggested and need further investigation even if arsenic should not be essential. In cell
culture, subtoxic concentrations of iAsm reduced the levels of ROS in keratinocytes and
fibroblasts by upregulating thioredoxin and glutathione reductase (Snow et al., 2005).
Some DNA repair proteins are also upregulated. The same paper also describes
protection of mice from skin tumors induced by dimethylbenzanthracine + phorbol 12-
tetradecanoate 13-acetate if the mice were given drinking water containing 0.2-2 ppb
arsenate. Inorganic arsenic (iAs) has both positive and negative effects on the growth
and function of blood vessels (Soucy et al., 2003, 2005; Kamat et al., 2005). Low
concentrations fuel angiogenesis, while higher concentrations injure endothelial cells and
promote the vessel dysfunctions seen in ischemic diseases and peripheral vascular
diseases. Thus, iAs may provide improved vascularization and growth of normal tissues,
which could reduce cardiovascular risks. However, this process could also pose risks for
iAs increasing the vascularization and growth of both atherosclerotic lesions (Simeonova
and Luster, 2004) and tumors from a secondary source (Kamat et al., 2005). Mice
drinking 10-250 ppb iAs111 had increased metastases from transplacental tumors (Kamat
et al., 2005). However, iAs at high doses has been used to destroy the tumor vasculature
(Griffin et al., 2003).
While mechanistic studies suggest that there should be a threshold for iAs bladder
cancer, available data, and data from epidemiological studies, are lacking or problematic
with regard to low-dose effects. This critically important issue should be the subject of
additional mechanistic and epidemiologic research. This research should attempt to
determine whether the suggested hermetic or beneficial effects of arsenic, for several
endpoints at very low doses, exist more broadly and whether they apply to all life stages.
If iAs is shown to be essential, i.e., necessary for certain life-sustaining functions or
processes, then a threshold would not be at zero. If iAs would be shown to have hormetic
effects, then the issue of a threshold would be less clear and while a threshold might be
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possible for one health endpoint, it might not exist for another iAs associated health
endpoint. Research should also further illuminate the shape of the dose response curve at
low doses for the biological effects of arsenic.
3.4 Selection of Data for Dose-Response Assessment
3.4.1 Use of animal data for DMAV (Charge Question Cl)
EPA's Charge stated that, "A number of different rodent bioassays (standard
bioassay, transgenic animals, susceptible rodent strains, initiation and promotion studies)
are available on DMAV." Charge Question Cl asks the SAB to "...commenton the use of
the bladder tumor data from the DMAV rat bioassay as the most suitable datasetfor quantifying
potential human cancer risk to DMAV, including the weight of evidence to support this
conclusion.
The consensus of the panel is that, given the lack of human data, the bladder
tumor data from the DMAV rat bioassay is the most suitable data set for quantifying
potential human cancer risk to DMAV. Given the differences in metabolic fates of
DMAV and iAs, the use of human data from iAs exposure to predict risk from DMAV is
not recommended. In this case, reliance on interspecies extrapolation using the rat
bioassay data is the best alternative.
This question indirectly raises the issue as to the largest source of uncertainty for
DMAV risk assessment—conventional interspecies extrapolation or extrapolation across
various forms of arsenic. The available material suggests that extrapolation across
various forms of arsenic would lead to the greatest degree of uncertainty in a risk
assessment. Although the panel agreed that use of the rat DMAV bioassay data is the
preferred method, the panel also felt strongly that a discussion of the key uncertainties
with using data from testing in rats to conduct human risk assessment should be included
in EPA's Office of Pesticide Programs report "Science Issue Paper: Model of
Carcinogenic Action for Cacodylic Acid (Dimethylarsinic Acid, DMAV) and
Recommendations for Dose Response Extrapolation." Issues that panel members
consider important to discuss in EPA's Science Issue Paper are discussed in more detail
below and in Section 3.2.1. These issues include the pharmacokinetic and
pharmacodynamic similarities and differences between rats and humans in response to
arsenic exposure (e.g., the role of TMAIII/V species); the use of rodent bladder tumor
models in general; shared MO As with iAs due to the possibility of DMAV demethylation
by intestinal bacteria (see section 3.2.1); and issues related to in the use of rodent data for
human risk assessment. The panel also recommends that the EPA consider applying the
Human Relevance Framework (HRF) proposed by the International Life Sciences
Institute-Risk Science Institute (ILSI-RSI) (Seed, et al, 2005) to the mode of action.
Application of the framework or its elements may assist EPA in evaluating the human
relevance of the DMAV rat data. This framework has been used to assess the relevance of
rodent liver tumors to human cancer risk (Holsapple et al, 2006).
Several pharmacokinetic differences between rats and humans have been reported
after arsenic exposure. For example, arsenic methylation in rat hepatocytes proceeds at a
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faster rate than in human hepatocytes (Styblo, et al., 1999). Additionally, rats have a
considerably slower whole body clearance of DMAV compared with humans. This
slower whole body clearance in rats results from a significant portion of DMA being
retained in the erythrocytes of rats (Vahter, et al., 1984). The affinity of rat hemoglobin
to bind DMA111 is 15 to 20 fold higher than that of human hemoglobin (Lu, et al, 2004).
These differences in metabolism and pharmacokinetics may be consistent with a greater
sensitivity of the rat to induction of bladder tumors by DMAV. However, without a more
complete data set demonstrating that exposure of the bladder epithelium (urothelial cells)
to DMAV metabolites (particularly DMA111) is greater in rats than in humans for a given
dose, the data are not sufficient to support reduction of interspecies uncertainty factors
based on differences in pharmacokinetics. Clearly, this is a high priority area of research
with the potential to reduce uncertainty in the risk assessment of DMAV.
In the EPA Science Issue Paper consideration should be given to the
pharmacodynamic similarities and differences between rats and humans and the
relevance of the rat response to human risk assessment. Although data illustrating the
mode of action for DMAV as a bladder carcinogen in rats seem quite convincing, it
should be noted that rats are more sensitive to DMAV in carcinogenicity testing than are
mice (Rossman, 2003; Arnold, et al., 2003). While the relative in vivo sensitivities of rats
and humans to DMA111 are unknown, it has been shown that in vitro rat and human
urothelial cell lines are equally sensitive in terms of acute toxicity to DMA111 in the
micromolar range (Cohen et al., 2002). For arsenite, however, the rat MYP3 urothelial
cell line showed toxicity at about one tenth (LCso of 0.4 jiM) the concentration as did the
human 1T1 urothelial cell line (LC50 of 4.8 jiM). As a result of the Panel's analysis of
the information on this key pharmacodynamic response, urothelial cell cytotoxicity, the
consensus was the EPA could explore a case for pharmacodynamic equivalency between
the test species, rats, and humans from existing experimental data. Pharmacodynamic
equivalency could be incorporated into the assessment as a reduction of the
pharmacodynamic component of the interspecies uncertainty factor, which is 3, to a value
of one. However, as discussed in the response to question Dl, there remains considerable
uncertainty due to limited comparative in vivo data across species. The final EPA risk
assessment should fully discuss the interspecies similarities and differences and the
implications for risk assessment as well as explore opportunities to reduce uncertainty
factors.
EPA's Science Issue Paper should discuss similarities and differences between
rats and humans in the development of bladder tumors and how these differences impact
interspecies extrapolation. Studies suggest that in rats it takes two or more years of
continuous high dose exposure to DMAV to induce these tumors. Human bladder tumors
are also late occurring. The Science Issue Paper should specifically discuss the
similarities and differences in the time for induction of DMAV related tumors in rats with
the pattern observed with humans and arsenic associated urinary bladder cancer.
EPA's Science Issue Paper should also discuss general issues associated with rat
urinary bladder cancer. One such issue is the relationship between the induction of
tumors and high concentrations of arsenic in the urine. Also, there is a need to address
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evidence that simple enhancement of proliferation is not associated with carcinogenesis
in many tissues. Studies by Gur et al. (cited on page 97 of the DMA MOA Science Issue
Paper, US EPA OPP, 2005) on the carcinogenicity of DMAV were never published and
thus cannot be critically evaluated by the Panel. The Science Issue Paper notes that the
Gur studies in rats and mice are key bioassay studies. Reliance on these studies would be
stronger if the studies had the benefit of peer review.
The EPA's Science Issue Paper expresses concern with the mouse transplacental
model for inorganic arsenic because the strain of mice used (namely C3H) in the original
two studies had a significant rate of spontaneous tumors in several tissues that are also
targets of arsenic. Recent follow-up work has shown that gestational exposure to
inorganic arsenic in CD1 mice is a complete carcinogen in the female offspring
(Waalkes, et al., 2006). The CD1 mouse strain is noteworthy as having a well defined,
low rate of spontaneous tumors. The Science Issue Paper should take note of this
important development.
Charge Question Cl.B also asks the SAB to "...comment on whether the iAs
epidemiology data can be used to inform the DMAV dose-response assessment derived
from rat data with DMAV. If so, please discuss how such information might be used."
(See Appendix A).
The panel consensus was that without more detailed information on target tissue
dosimetry of arsenic species the iAs epidemiology data would be of limited use to inform
the DMAV dose-response assessment derived from rat data with DMAV. Direct exposure
to iAs elicits a different cascade of metabolite concentrations with related differential
kinetics compared to direct exposure to DMAV, therefore the iAs epidemiology data
cannot reasonably be used to inform the DMAV dose-response assessment derived from
rat data with DMAV. In the absence of specific information on target tissue levels,
assumptions would have to be made regarding the proportion of the iAs for human and
DMAV for rodents that reaches the bladder tissue as the toxic DMA species.
In principle, epidemiology data from iAs exposed humans could be used to
inform the DMA assessment to the extent that the data might be able to address the
appropriateness of interspecies extrapolation, specifically the relative sensitivities of rat
and human to bladder cancer following arsenic exposure. However, as noted above, in
order to be useful some information on target tissue dose of DMA following human
exposure to iAs and rodent exposure to DMAV would be necessary. With both in vivo
tumor indices (human and rodent) expressed in terms of the same tissue dose of relevant
metabolites, rather than iAs or DMAV exposure levels, the relative sensitivities of the
human and rodent could be assessed.
3.4.2. Use of human epidemiological data from direct iAs exposure
(Charge Question C2)
EPA's Charge states that, "Since the NRC (2001) report on iAs, an additional
body of literature has developed describing epidemiology data from populations in the
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U.S. exposed to iAs in drinking water" (USEPA, 2005a). Charge Question 2 asks,
"Does the SAB agree that the Taiwanese dataset remains the most appropriate choice for
estimating cancer risk in humans? Please discuss the rationale for your response. "
For reasons noted below in this section, it is the Panel's view that, at this time, the
Taiwanese database remains the most appropriate choice for EPA's use in deriving the
cancer unit risk for iAs. However, the Panel suggests that EPA also conduct adjunct analyses
to test the robustness of results against their assumptions, determine the impact of variability in
some parameters, compare the results against those from other data sets, and provide a transparent
assessment of the available epidemiological data using a consistent set of criteria.
The Taiwanese dataset consists of population and mortality data from 42 villages
in southwest Taiwan for the years 1973-1986. Arsenic levels in wells from these villages
were measured in 1964-1966. The database is one of the largest that has been evaluated
for cancer risk relative to arsenic exposures. A total of almost 900,000 person years of
follow-up were included, with 1,152 cancer deaths (637 males, 515 females). Among the
cancer deaths were 181 due to bladder cancer (85 males, 96 females), 268 lung cancer
(147 males, 121 females), and several hundred due to other types of cancer. These data
have been subject to several ecologic analyses, starting with the original publications by
Chen et al. (1988) and Wu et al. (1989), followed by further analyses by Morales et al.
(2000) and by the National Research Council (1999 and 2001).
Among the 42 villages, the arsenic concentration ranged from 10 to 934 ppb
(ug/L). Twenty of these 42 villages used a single well. Among many of the 22 villages
with multiple wells, many had wide variability in the measured arsenic level in their
wells. Analyses using the full dataset give results comparable to results from a reduced
dataset including only the villages with single wells, providing some confidence in the
stability of the overall results (National Research Council, 1999). The Panel recognizes
the limitations of the southwest Taiwan database, including its ecologic character, lack of
smoking information, limited precision of exposure estimates, especially among villages
with multiple wells, and the possible issue of compromised nutrition among segments of
the exposed population. However, in view of the size and statistical stability of the
database relative to other studies, the reliability of the population and mortality counts,
the stability of residential patterns, and the inclusion of long-term exposures, it is the
Panel's view that this database remains, at this time, the most appropriate choice for
estimating cancer risk among humans. Supporting this view is the fact that the datasets
from Taiwan have been subjected to many years of peer review as part of published
studies.
Given the concerns regarding the use of the median well water concentrations in
some of the 42 villages in southwest Taiwan that have more than a single measurement,
the Panel recommends that EPA conduct a sensitivity analysis. This should include the
range of exposures in said villages to provide a range of risk estimates. One alternative
(suggested in response to D-3) is a full Monte Carlo analysis in which the individual well
concentrations for 22 villages with multiple wells are taken into account. The Panel
recognizes the difficulties with this approach including the issue of how to allocate cases
to wells within villages. A simpler, but useful first approach would be to test the
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sensitivity of the model fitting when arsenic concentrations for multiple-well villages are
set to: 1) a low level concentration from the range for the village (10 percentile, 20th
percentile); 2) the median (current procedure); and 3) a high level concentration from the
village range (90th percentile, 80th percentile).
New studies have been published since the NRC report in 2001 and the Panel
considered some of these (and additional information provided by the public during this
review process) in its evaluation regarding the Taiwanese data sets that are the focus of
this charge question. To be clear, the panel did not do an exhaustive review of all
possible toxicologic and epidemiologic literature during its review. That was beyond the
scope of the Panel's charge. The Panel recognizes that this must be done in EPA's final
assessment and calls on the Agency to do so.
In view of the limitations of this database, the Panel recommends that the other
relevant epidemiologic databases from studies of arsenic-exposed populations be used to
compare the unit risks at high exposure levels that emerge from the Taiwan data. Several
of these studies had the advantage of data with excellent exposure assessment. In
addition, some populations likely differed from the Taiwanese population with regard to
their nutritional status. The accuracy and precision of exposure assessment is a major
issue in all environmental epidemiologic studies, and in particular, in studies of arsenic in
drinking water. Misclassification of exposure in such studies (when non-differential) can
have a profound effect in attenuating the magnitude of the observed risk. The excellence
of exposure assessment is an especially strong aspect of several studies from northern
Chile, and the Panel recommends that the findings of Smith et al. (1998) and of Ferreccio
et al. (2000) be included by EPA in evaluation of other datasets as described below. In
addition, arsenic exposures appear to be well characterized in cohort studies of Chiou et
al.(2001) of transitional cell carcinoma (mostly bladder cancers) and Chen et al. (2004) of
lung cancer, from arsenic-exposed cohorts in southwest and northeast Taiwan. The latter
study also provides data on the joint effects of arsenic and cigarette smoking in the
Taiwanese population.
The accuracy of estimated long-term exposures to arsenic is of concern for recent
studies with water concentrations below 100 ppb. Misclassification of exposure may
compromise their overall utility in assessing concordance with risk estimates obtained
from the Taiwan study. The Panel suggests that results on bladder cancer risk from
published epidemiology studies of U.S. and other populations chronically exposed to
arsenic levels ranging from 0.5 to 160 |ig/L inorganic arsenic in drinking water, be
critically evaluated. A sensitivity analysis to evaluate the potential impact of sources of
bias in the low level case control and cohort studies could be informative. Several
arsenic epidemiology studies have the advantage of data with drinking water arsenic
exposure levels ostensibly most relevant to the U.S. population [Bates, et al., 1995;
Karagas et al., 2004; Lewis et al., 1999; Kurttio et al., 1999; Steinmaus, et al., 2003;
Bates et al., 2004; Michaud et al., 2004; Chiou et al, 2001; Ferreccio et al., 2000]. Most
of these populations have a nutritional and genetic background similar to that of the U.S.
or the studies were conducted in a U.S. population. EPA should determine the potential
utility of these studies in exploring overall concordance of the cancer risk estimates
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derived from their data with risk estimates obtained from extrapolation of the Taiwan
data. The Panel suggests that if findings from a critical review of "low-level" studies
indicate that some or all studies are potentially of value in further analyses, that results
from these studies should be explored in secondary analyses, particularly on bladder
cancer risk, and compared with the main analysis for concordance. Analyses integrating
health outcome information from a number of epidemiology studies can result in
improved statistical power and precision of the estimates; these factors represent an
additional advantage of utilizing a larger dataset.
When reviewing these "low-level" studies (and the "high level" studies as well),
EPA should consider at least the following issues: estimates of the level of exposure
misclassification; temporal variability in assigning past arsenic levels from recent
measurements; the extent of reliance on imputed exposure levels; the number of persons
exposed at various estimated levels of waterborne arsenic; study response/participation
rates; estimates of exposure variability; control selection methods in case-control studies;
and the resulting influence of these factors on the magnitude and statistical stability of
risk estimates. Most populations in the U.S. and many other countries differ from the
Taiwanese population of interest in genetic background (e.g., genetic polymorphisms),
dietary intake, and background exposure concentrations to inorganic arsenic, and if one
or more of these studies are shown to be of potential utility, comparative analyses of the
U.S. and Taiwan data may lead to further insights into the possible influence of these
differences on population responses to arsenic in drinking water. For compounds such as
arsenic for which there are human data beyond the Taiwanese study on which human
cancer risk has been based, data from the other investigations at high exposure levels
(>150 ng/L) can be used to gauge the Taiwanese findings [Smith et al.(1998), Ferreccio
et al.(2000), Chen et al.(2004), Chiou et al.(2001)].
All of these studies, including those from Taiwan, Chile, Argentina and the U.S.
as described above, should be judged by the same set of criteria, with the comparative
assessment of those criteria across studies clearly laid out in a tabular format. Some of
the criteria have been listed in the previous paragraph. The relative strengths and
weaknesses of each study need to be described in relation to each criterion. The caveats
and assumptions used should be presented so that they are apparent to anyone who uses
these data. Included in the risk assessment background document should be a complete
and transparent treatment of variability within and among studies and how it affects risk
estimates. The present lack of transparency in the application of the criteria in the
process of study selection was pointed out by several panel members.
Charge Question C2 also asks, "Do these data provide adequate characterization
of the impact of childhood exposure to iAs? Please discuss the rationale for your
response."
The Taiwanese data are inadequate to characterize the impact of childhood
exposure to inorganic arsenic with respect to carcinogenesis. That is, it is not clear
whether children differ from adults with regard to their sensitivity to the carcinogenic
effects of arsenic in drinking water. More data are needed to fully characterize the
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impact of transplacental exposures. However, data from the studies in southwestern
Taiwan which include childhood exposures in the calculation of lifetime dose show that
in the population under 30 years of age there were no bladder cancer cases, and only 5
lung cancer cases but few cases are actually expected in that age group. Childhood
exposures are included in the lifetime dose estimates. Smith et al (1998) report the
highest excessive risk for male lung cancer in the 30-39 year old age group, suggesting
the importance of childhood exposure and risk and perhaps smoking behavior as young
adults. For 533 women exposed to arsenic in drinking water from tube wells at greater
than 50 jig/L compared with those exposed at 50|ig/L or less, findings suggest that there
are significantly increased odds ratios for spontaneous abortion, stillbirth and neonatal
death (Milton et al., 2005). Another reproductive study in Chile, which followed over
800 pregnancies, found that pregnant women drinking water containing 40 |ig/L gave
birth to infants of lower birth weight than a comparable group drinking water containing
very low arsenic concentrations (<1 |ig/L) (Hopenhayn et al, 2003). Thus maternal
exposure at moderately high levels may have toxic effects; the issue of childhood
carcinogenic susceptibility has had only limited study.
3.5 Approaches to Low-Dose Extrapolation for Inorganic Arsenic and DMAV
3.5.1 Mode of carcinogenic action understanding for DMAv/m and
implications for dose-response extrapolation to estimate human
cancer risk (Charge Question Dl)
EPA's Charge stated that, "The use of mode of action data in the assessment of
potential carcinogens is a main focus of EPA's 2005 cancer guidelines. As stated in
th[o]se guidelines 'The approach to dose-response assessment for a particular agent is
based on the conclusion reached as to its potential mode(s) of action.' Although a
biologically-based model is the preferred approach to estimating cancer risk, there are
insufficient data on DMAV to support development of such a model." Charge Question
Dl asks the SAB to " ...comment on the scientific evidence and biological rationale in
support of nonlinear versus linear low dose extrapolation approaches, which approach is
more consistent with the available data on DMAV and current concepts of chemical
carcinogenesis, and how scientific uncertainty should most appropriately be
incorporated into low-dose extrapolation. "
3.5.1.1 Please comment on the scientific evidence and biological
rationale in support of the nonlinear versus linear low dose
extrapolation approaches
The Panel believes, based on the review of EPA's analyses, that there are
adequate data to support much of the EPA-postulated MOA for bladder carcinogenesis
induced by high doses of DMAV in the rat. The MOA involves cytotoxicity of the bladder
epithelium and increased, sustained regenerative proliferation, as key events. However,
the Panel concluded that there are insufficient data to invoke ROS-induced DNA damage
as a key event in the carcinogenic process, associated with exposures to DMAV or
DMA111 (see Charge Question Bl).
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The postulated MOA for DMAV is:
a) Reductive metabolism of DMAV to DMA111.
b) High concentrations of DMA111 in urine cause urothelial cytotoxicity. Some
toxicity may also be caused by DMAV itself.
c) Continuous exposure and persistent, stress associated, regenerative cell
proliferation leads to genomic instability, acquisition of genetic alterations,
clonal expansion of altered cells and eventually tumors.
Neither the MOA postulated here, nor those postulated by ORD or OPP (USEPA
OPP, 2005; USEPA ORD, 2005), contain key events expected to be a linear function of
dose. Reductive metabolism of DMAV is likely to be saturable and therefore non-linear
but this does not necessarily imply a threshold-based response. In vitro cytotoxicity of
uroepithelial cells, using rat (MYP3) and human (1T1) bladder cell lines, occurs only at
concentrations greater than -0.35 uM (rat, 0.38 uM DMA111; human 1T1 0.35 uM
DMA111) (unpublished data1). In vivo, cytotoxicity of the uroepithelium occurred at the
lowest tested dietary DMAV concentration (2 ppm), but the incidence and severity
increased, and the latency decreased significantly as a function of dose. Statistically
significant increases in regenerative cell proliferation only occur in rats at DMAV dietary
concentrations greater than 40 ppm, again, a nonlinear or apparent threshold response.
Even ROS production, and its interaction with DNA, would be expected to be
linear at some low dose, but nonlinear across the larger dose range. Formation of
heritable alterations in DNA by ROS is believed to be a nonlinear or curvilinear effect
(USEPA ORD, 2005) best represented by a quadratic function with a low-dose linear
component (USEPA OPP, 2005). The formation rate of heritable alterations is a function
of the rate of DNA damage and the rates the various DNA repair processes and finally the
rate of DNA misreplication (USEPA OPP, 2005). The latter being a function of
cytotoxicity and regenerative cell proliferation which in the case of DMAV, are also
highly nonlinear functions of dose (USEPA ORD, 2005). With respect to repair of
postulated ROS induced DNA damage, highly specific enzymatic systems that exist for
1 Personal communication from L. Arnold of Dr. Cohen's Lab with the EPA SAB Designated Federal
Officer; 4.4.2006. Samuel M. Cohen, M.D., Ph.D. Professor and Chair, Pathology and Microbiology
Havlik-Wall Professor of Oncology University of Nebraska Medical Center, Text of the email is provided
below: "During the process of determining the LC50 for the various arsenicals we did develop some data
concerning the no effect level especially in the MYP3 rat bladder cell line. We do not have as much data
for the IT 1 human bladder cell line since we used concentrations that we had already determined caused
cytotoxicity in the MYP3 cell line. We do have detailed data for DMA111 for both cell lines since there was
a very sharp drop between concentrations which had no effect on the cell viability and concentrations
which were cytotoxic. In the MYP3 rat bladder cell line, DMA111 concentrations of 0.38 uM and below had
no effect on the viability of MYP3 cells but at a concentration of 0.39 uM DMA111 the cell viability dropped
to 69%. In the 1T1 human bladder cell line, DMA111 concentrations of 0.35 uM and below had no effect on
viability but at 0.40 uM the viability dropped to 76%. The following data show doses for other arsenicals
at which there was no effect on cell viability however, the no effect dose may be somewhat higher but we
do not have enough data points to determine an exact concentration.
MYP3 rat bladder cell line:
Arsenite-0.05 uM; Arsenate-1 uM; MMAm-0.5uM; MMAv-lmM; DMAv-0.05mM;
TMAO-O.lmM
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their repair (Slupphaug et al., 2003) protect the genome, whether from exogenous
chemicals or the high levels of endogenous ROS induced DNA damage. These
enzymatic repair processes are expected to be nonlinear processes. EPA's position on a
linear oxidative stress MOA induced by DMAV is likely not defensible and should not be
used. The state of the science is overwhelmingly in favor of a nonlinear approach for the
risk assessment of DMAV. In summary, the Panel's opinion is that the available data
support the nonlinear approach for the low dose extrapolation of DMAV.
The linear approach would be consistent with evidence for direct genotoxicity of
DMAIII/V. There are no compelling data demonstrating that DMAIII/V are directly
genotoxic. It is generally accepted that DMAV is not directly genotoxic (not DNA
reactive). This conclusion is well supported by the data presented in the Science Issue
Paper: Model of Carcinogenic Action for Cacodylic Acid (Dimethylarsinic Acid, DMAV)
and Recommendations for Dose Response Extrapolation, and in section 3.3.1 of this
report.
v
3.5.1.2 Charge Question Dl further asks the SAB, '•''Which
approach is more consistent with the available data on DMA
and current concepts of chemical carcinogenesis,"
The non-linear approach is more consistent with the available data and current concepts of
chemical carcinogenesis (see section 3.5.1.1, above).
3.5.1.3 Charge Question Dl asks the SAB, "How [should]
scientific uncertainty most appropriately be incorporated into
low-dose extrapolation?"
After some discussion, the Panel viewed this question from the perspective of the
EPA's RfC guidelines (USEPA, 1994). Similar guidelines for the derivation of chemical
specific uncertainty factors have been developed by the International Program for
Chemical Safety (IPCS 2001). These guidelines provide an approach for incorporating
uncertainty into risk assessments in the form of uncertainty factors. Uncertainties in the
interspecies extrapolation of the rat dose-response data can be broadly grouped into a)
those related to interspecies differences in pharmacokinetics, b) those related to
interspecies differences in pharmacodynamics, and c) those associated with sensitive
populations such as children and the elderly. The default value for interspecies
differences in pharmacokinetics is 3, the default for interspecies differences in
pharmacodynamics is 3, and the default for sensitive populations is 10, made up of two
factors of 3 each, one for pharmacokinetic differences and one for pharmacodynamic
differences.
While it was the opinion of the Panel that rats might deliver a higher dose of the
proximate toxicant, DMA111 to the bladder for a given dose of DMAV than humans, the
Panel recognized that there was insufficient data on the comparative dosimetry in rats and
humans to make any conclusive statements about species differences in
pharmacokinetics. The possible role of microbial demethylation in humans is another
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potential issue for consideration. Therefore, the uncertainty factor for interspecies
differences in pharmacokinetics should be 3, the default value. However, there appears to
be emerging data on DMAV kinetics which might be brought to bear on the question and
the agency is encouraged to consider these data with respect to pharmacokinetic
differences between the species and the characterization of this component of uncertainty
in the dose response assessment.
As a result of the Panel's analysis of the data for the key pharmacodynamic
response, uroepithelial cell cytotoxicity, the consensus was the EPA could assemble a
case for pharmacodynamic equivalency between the test species, rats, and humans from
existing experimental data. Cohen et al. showed LCsos of 0.5 and 0.8 uM DMA111 for rat
and human bladder epithelial cells lines (Cohen, 2002). In the context of EPA and
International Program on Chemical Safety (IPCS) guidelines, this finding could be
incorporated in the assessment as a reduction of the pharmacodynamic component of the
interspecies uncertainty factor (typically a default value of 3), to a value of one.
However, this suggestion is based upon limited comparative in vitro data. The
application of uncertainty factors has also been addressed in the Panel's response to
question Cl. There is presently no arsenic-specific information that can inform the choice
of uncertainty factors for sensitive human populations. For now, the choice of these
factors must be based on more general considerations, including EPA's science policy
judgment of the degree of precaution that it deems appropriate.
3.5.2 Implementation of the recommendations of the NRC (2001)(Charge
Question D2)
EPA believes that the most prudent approach for modeling cancer risk from
exposure to iAs is to use a linear model because there are significant remaining
uncertainties regarding which of the metabolite(s) may be the ultimate carcinogenic
moiety and whether or not mixtures of toxic metabolites interact at the site(s) of action"
(USEPA, 2005 A). EPA asked if the SAB concurs, for now, with the selection of a linear
model to estimate cancer risk for inorganic arsenic [i.e., following the recommendations
of the NRC (2001)]. EPA also asked that the SAB discuss its response in light of the
highly complex mode of action for iAs.
The Panel recognizes the potential for a highly complex mode of action of iAs
and its metabolites, and until more is learned about the complex PK and PD properties of
iAs and its metabolites there is not a sufficient justification for the choice of a specific
nonlinear form of the dose-response relationship. Therefore, based on information in this
section and on the Panel's understanding of the EPA's 2005 Guidelines for Cancer Risk
Assessment, the final recommendation of NRC (2001) to base current risk assessments
on a linear dose response model that includes the SW Taiwan population as a comparison
group, seems to be the most appropriate approach. Below, the Panel suggests that EPA
conduct sensitivity analyses to address uncertainties in this issue.
Existing epidemiologic studies have been mentioned in the response to charge
question C2. These studies of different populations across different countries seem to
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support a possible linear dose-response between exposure from drinking water and
internal cancer risks (particularly in Taiwan, Chile and Argentina). These dose-response
relationships are observed at higher exposure levels (>100 ppb). The Panel believes that
because of limitations in the epidemiologic studies conducted to date, that adequate
human data at the lower range of iAs exposure is lacking.
Some recent studies have included populations with exposures in the lower range
(<100 ppb), but they tend to be problematic for use in dose-response analysis for lower
exposure levels. In particular, when studies are based almost exclusively on low dose
exposure populations (Lamm et al, 2004; Bates et al, 2003; Steinmaus et al, 2003), they
lack statistical power and the estimations of low dose risk tend to be unstable and to have
a high degree of uncertainty. Some of these studies also have problems related to study
design. For example, in the Lamm et al. (2004) ecological study, exposure assessment is
highly problematic given that a single median county-level exposure value is assigned to
all the person-years contributed by each county in the analysis, even though it is not clear
that these are the arsenic exposure values for a large number of residents within each
county. A recent follow-up of the Taiwanese cohort reports a monotonic trend in lung
cancer risk for exposure to arsenic levels ranging from <10 to 700 ug/L, however this
study also has limited power to examine the form of the dose-response relationship
within the 10-100 ug/L range (Chen et al 2004). There are no human data available that
is adequate to characterize the shape of the dose response curve below a given point of
departure.
At present the experimental evidence on mode of action of inorganic arsenic
supports a possible nonlinear dose-response at low exposure levels yet there is no clear
indication of what shape a nonlinear dose-response would take for application to human
cancer risks at low exposures (<50 or < 100 ppb). In examining the dose-response
relationships of arsenicals in inducing direct or indirect mutagenic responses (including
effects thought to be clastogenic in nature), it is clear that effects are only seen at doses
that induce cytotoxicity. This implies a threshold (Rossman, T.G. 2003). Until more is
learned about the complex properties and MO As of iAs and its metabolites there is
insufficient justification for the choice of a specific nonlinear form of the dose-response
relationship. Under these circumstances, the EPA's 2005 Guidelines for Cancer Risk
Assessment are clear that linear extrapolation below the point of departure is the method
to be used.
Although the EPA has chosen a linear model for the arsenic dose component of
the hazard model for lung and bladder cancer, the Panel encourages the Agency to test
the sensitivity of the assumption of linearity by comparing its corresponding estimate of
excess life risk to an alternative hazard model that has a dose contribution that is
multiplicative and nonlinear in form (see question D3 for additional information).
In summary, the Panel recognizes the potential for a highly complex mode of
action of iAs and its metabolites, but until more is learned about the complex PK and PD
properties of iAs and its metabolites there is not sufficient justification for the choice of a
specific nonlinear form of the dose-response relationship. Based on this and the EPA's
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2005 Guidelines for Cancer Risk Assessment, the final recommendation of NRC (2001)
to base current risk assessments on a linear dose response model that includes the
southwest Taiwan population as a comparison group seems the most appropriate
approach. However, the Panel also recommends performing a sensitivity analysis with
different exposure metrics with the subgroup of villages with more than one well
measurement (as discussed in responses to charge questions C2 and D3) and using a
multiplicative model that includes a quadratic term for dose, as performed by NRC
(2001) and as discussed in charge question D3.
3.5.3 EPA Model Re-Implementation (Charge Question D3)
The Charge states that, "EPA re-implemented the model presented in the NRC
(2001) in the language R as well as in an Excel spreadsheet format. In addition,
extensive testing of the resulting code was conducted" (USEPA, 2005a). Charge
Question D3 asks the SAB to "... comment upon precision and accuracy of the re-
implementation of the model."
Question D3 suggests that the estimation of the dose-response model and the
hazard assessment were originally programmed in the R language. Page 63 of the issue
paper indicates that the Poisson hazard model was originally estimated in the R language
(optim routine) but neither the main text of the paper nor its appendices provided any
additional information. A clarifying question from the panel through the Designated
Federal Officer provided clarifying information, stating that:
"The reference to the implementation in R in question D.3 is outdated, and should
have been removed. This was an oversight on EPA's part. The model
implementation in Excel is our implementation of record, and was used to prepare
the results in the draft toxicological review. We would ask the Panel to please
review and comment only on the implementation in Excel. (Background: EPA
did originally implement its model in R. However we found that version to be not
very transparent, and hard to debug. We then re-implemented the model in Excel,
found and corrected some errors, and used that corrected version to prepare the
tox review. While Excel may not be the best choice from the standpoint of
numerical accuracy, it is greatly superior in the transparency of the
implementation, and is powerful enough to perform the entire model calculation
from start to finish, even including the nonlinear optimization. Once the Panel is
satisfied that the implementation in Excel is correct and appropriate, then the
model can be re-implemented in R or some other numerically superior
language.)"
The Agency staff is to be commended for deciding to test its original R-language
version of the model program through a separate implementation in Excel. The Excel
version serves as a check of programming performed in alternative systems (e.g. R, S)
and provides transparency for review by non-specialists. For the calculations required in
this model of hazard and excess risk, the Excel computations should provide sufficient
numerical accuracy. If the EPA returns to another model program, it should begin with
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the original model formulas and not simply transcribe the programming from the existing
Excel version of the model. As a debugging and error-checking tool, comparisons of
intermediate results from the two model implementations should be performed to verify
the equivalence of the two model systems.
Overview of the EXCEL spreadsheet implementation of the model: The Excel
model implementation is described in Appendix B (pages 105-106) of the Issue Paper.
The Issue Paper (page 65) referenced a URL, www.epa.gov/waterscience.sab: however
this proved to be not available. EPA staff notified the panel of the correct address,
http ://epa. gov/waterscience/sab/. The Issue Paper suggests that a listing of the variable
and parameter input field is provided in Table B-3 but the current draft of the Issue Paper
did not include this table. (The fields in the spreadsheet model were interpreted by the
Panel based on the description provided in the text of the Issue Paper and general
understanding of the model fitting procedure employed.)
The spreadsheet model requires two Excel files and associated macros. The first
of these is MCCancerfit.XLS. This workbook component of the model consists of eight
worksheets in four pairs (e.g. fblad and MC fblad for female bladder cancer) that cover
the two cancers of interest (lung and bladder) and gender (male, female). The initial
worksheet (e.g. fblad) in each of the four cancer/gender pairs contains the input data for
fitting the hazard model. The first step in the model fitting algorithm is to employ the
Excel Solver to find initial values of al, a2, a3 and P (Cells G2:G5) that maximize the
Poisson likelihood under the following model:
\dose = exP(«i + «2' <*get + a3 • agef )•(! + /?• dose)
where:
agei = the midpoint of a five-year age range, e.g. 22.5 for 20-24;
dose = the arsenic dose in ppb.
This is the model described by the EPA in the Issue Paper and is one of two models that
appeared to provide best fit to the data based on the Akaike Information Criterion (NRC,
2001).
The second worksheet in each the four disease/gender pairs (e.g. MC fblad) is
used in conjunction with the initial starting values, generated by Solver and stored in Cell
N2, to simulate the empirical Bayes posterior distribution of the model parameters based
on a set of 1000 random perturbations of the coefficient vector (al,a2,a3, P) about the
maximum likelihood estimates produced by Solver. The perturbation involves
independent, random (uniform) dispersion of the coefficient estimates in a relative range
of+/- 10% about the point estimates generated by Solver. Parameter draws outside this
range are not performed since the posterior likelihood takes on a near zero value outside
the boundaries +/- 10% of MLE. The corresponding macro (e.g. mcfblad) is then
invoked to apply the observed data and these perturbed coefficient values to establish the
value of the posterior log-likelihood for each of the 1000 draws. The empirical Bayes
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estimate of the slope parameter and its lower confidence limit are then estimated based on
the mean and standard deviation of the simulated posterior distribution:
1000
I»,
L,
b = •
1000 T
—
j=l Anax
sd(b) = sqrt
1000
z
1000 Ł1
999
J (h h\2
T ^j ° >
^max
1000 T
^ LJ
^ r
j=l ^max
and,
= b+2-sd(b)
The estimated UCL(b) is then carried forward to the BEIR.IV computation of the
excess lifetime risk in the BEIR.xls spreadsheet.
Based on its review, the Panel noted that for the given data inputs, the empirical
Bayes estimation algorithm programmed in the MCCancerFit.xls spreadsheet does match
the form of the model and the general description of the parameter fitting algorithm
outlined in the Issue Paper.
As described in the Issue Paper, the EPA data inputs for at risk populations and
cancer deaths agree with Morales, et al. (2000). In general, the panel recommends that
all tables of inputs for these models be published in appendices to the Issue Paper or final
risk assessment so that reviewers can independently reference and verify the critical
inputs to the hazard and excess risk analysis.
The MCCancerft.xls spreadsheet includes an adjustment of 50 ug/day of arsenic
from food intake. Based on the formula provided on page 103 of the Issue Paper, the
current model assumes a combined daily intake of 2 liters/day of cooking and drinking
water. The Issue Paper suggests that the current analysis uses 30 ug/day. Although the
Issue Paper notes the NRC (2001) finding that dietary intake had no significant effect on
the estimated cancer slope factor, the apparent discrepancy between the value of 30
ug/day cited in the Issue Paper and the 50 ug/day value used in the spreadsheet model
should be resolved. The model does not allocate a food input of arsenic to the control
population. This is a decision that presumes food-based intake of arsenic originates from
cooking water only.
The second Excel workbook in the risk assessment model employs estimates of
the dose response model parameter, p, and its upper bound to evaluate excess lifetime
risk under the BEIR-IV formula. The BEIR.xls workbook includes four worksheets, one
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for each cancer type by gender combination (flung, mlung, fblad, mblad). The estimates
of the linear dose response parameter and its estimated 95% UCL (see above) are
manually pasted from the corresponding worksheet in MCCancerFit.xls. The excess risk
is computed in cell T15. Solver can be applied to the dose value in Cell Tl 1 (not U10 as
indicated on Page 105 in the Issue Paper) to establish the dose level required to produce a
user-specified values of excess risk (i.e., ED0i).
The columns of each worksheet in the BEIR.xls spreadsheet incorporate data for a
specific age range of the U.S. population. These columns are not labeled with the
corresponding age range. Identifying labels should be applied to all rows and columns in
these worksheets. By deduction, column 3 applies to individuals age 20-24, column 4 to
age 25-29, etc. If this is correct, the Panel recommends that the entry in cell B3 of each
of the four BEIR.xls spreadsheets be verified. It appears that this mortality figure may
apply to more than just the 20-24 year old population represented in Column 3. Referring
to the data inputs for 20-24 year olds in the flung spreadsheet in BEIR.xls, the population
value is 9,423,000, all deaths are 18,121 and the baseline hazard is .00192. Moving over
one column to the 25-29 year olds, the population is nearly the same at 9,491,000, all
deaths are 1580 and the baseline hazard is .00017—less than 1710th that for the previous
five year age group.
The BEIR.xls spreadsheet implementation of the BEIR-IV excess risk calculation
includes a 3-fold divisor to transform the risk to a U.S. population base (assuming
exposure per kg is 3-fold higher in the SW Taiwanese population). This scaling occurs in
the calculation of the age-specific cancer hazard (Row 11). It should be documented and
also should be a target for future sensitivity studies. Since this is a model parameter it
should identified as a distinct input on the spreadsheet instead of simply embedded in the
calculations.
The notation for the BEIR-IV formula on Page 102 in the Issue Paper does not
distinguish between total survivorship (S;) and survivorship adjusted for the added risk of
cancer. However, the spreadsheet implementation of the model decomposes survival into
the product of baseline survival and a survival factor that reflects excess cancer deaths
due to the prior age group's exposure to arsenic. Based on a version of the spreadsheet
downloaded from the Office of Water website, calculation of cancer-specific survival
(Row 13) appears to incorporate mortality through age interval I, not interval 1-1 as it
should. This should be checked. The calculation of baseline survival appears to be
correct - the survival parameter at age interval I includes only mortality through the end
of time period 1-1. With this exception, calculation of Excess Risk follows the BEIRIV
formula.
Following the series of checks and corrections to the model listed above, the
Panel encourages the Agency to extend its testing of the model sensitivity to alternative
models forms and model assumptions. Specific areas where the Panel felt additional
sensitivity testing is warranted include:
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a) A Monte Carlo analysis in which the individual well concentrations for 22
villages with multiple wells are taken into account. The Panel recognizes the
difficulties with this approach including the issue of how to allocate cases to
wells within villages.
b) MCCancerFit.xls:
a. A test of the sensitivity of the model to the choice of the reference
population (SW Taiwan).
b. A test of the sensitivity of model results to the assumption that the
reference population has 0 intake of arsenic via food.
c. A contrast of results for the linear dose model employed in this program
to alternative hazard models that are multiplicative and nonlinear in
form. For example, the following multiplicative, quadratic model is one
of several that NRC(2001) found to have best fit to the data based on the
Akaike Information Criterion (AIC):
A. c = exp(aj + a2 • aget + a3 • agef ) • exp(/?0 + /?, • dose + /?2 • dose2)
c) BEIKxls
a. The Panel recommends a sensitivity analysis be conducted to
investigate the effect of the age groupings used to estimate the baseline
hazard and excess lifetime risk. In addition to the current practice of
using 5-year intervals (e.g. 20-24, 25-29, etc.), a logical choice is to
test the sensitivity of the model results to using 10-year groupings (e.g.
20-29,30-39...).
b. The exposure/kg parameter used to transfer the dose/response model
from the original SW Taiwanese population to a U.S. general
population is a major driver in the computation of excess lifetime risk.
In preparing its final risk assessment, the EPA should conduct a
sensitivity analysis to determine precisely how much the choice of a
factor of 3 impacts the final estimates of excess lifetime risk.
3.5.4 Available literature describing drinking water consumption
rates for the Southwestern Taiwanese study population (Charge
Question D4)
EPA, as well as the NRC (2001) state that the drinking water consumption rate, as
well as variability of that rate in both U.S. and Taiwanese populations, are important
factors to consider. EPA notes that in calculating risk estimates for U.S. populations
exposed to arsenic through drinking water, NRC used a drinking water consumption rate
of 1 L/day for the U.S. population and two possible consumption rates for the Taiwanese
population: 1 L/day (identical to the U.S. population) and 2.2 L/day with little or no
supporting rationale. Since publication of NRC 2001, a number of new studies have
become available and are summarized in the Cancer Slope Factor Workgroup Issue
Paper. Agency reviews of the relevant literature suggest that the mean drinking water
49
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(for the Taiwanese study population) consumption rate is between 1 to 4.6 L/day. EPA's
current cancer modeling includes water intake adjustments for 2.0 and 3.5 L/day"
(USEPA, 2005a). Charge Question D4 asks what drinking water value the panel
recommended for use in deriving the cancer slope factor for inorganic arsenic?
The Panel agrees that assumptions about water consumption levels in the U.S. and
in Taiwan have a substantial impact on the risk assessment. Relative to U.S.
consumption, overestimating water consumption in Taiwan decreases potency estimates
and underestimating consumption increases potency estimates. Evidence for gender
differences in consumption is limited, but considerable within-population variability in
consumption occurs (NRC, 2001). EPA should evaluate the impact of drinking water
consumption rates associated with more highly exposed population groups with
potentially different exposures and susceptibilities (e.g., children, pregnant women) in its
arsenic exposure estimates as the Agency determines the overall affects of drinking water
consumption rates on arsenic risk.
U.S. water consumption data are obtained from comprehensive U.S. surveys
including surveys by the U.S. Department of Agriculture (USDA) and as part of the
National Health and Nutrition Examination Survey (NHANES) (as cited in USEPA,
2005), among others. These studies provide information on tap water consumption as
well as water consumption attributable to other beverage consumption and consumption
of food prepared with water containing arsenic. Estimates of mean daily drinking water
consumption and total water consumption (including water used in food preparation)
range from 1.0 to 2.8 L/day and from 1.2 to 3.2 L/day respectively.
In comparison, information on water-consumption in Taiwan derives from a small
study by Yang and Blackwell and an EPA informal, anecdotal assessment (as cited in
USEPA, 2005) that include only information on drinking water consumption.
Information on water consumption in South Asia, another world region with high arsenic
levels in the water supply, is available from a large population based survey in India
(Chowdhury et al., 2001 cited in EPA 2005) and a small study from Bangladesh
(Watanabe et al., 2004). The South Asian studies include information on water
consumption associated with food preparation. Although similar in socioeconomic
characteristics, the diet and climate differ in Taiwan and South Asia, with temperatures
higher in South Asia. These studies report mean daily drinking water intake of 1 to 3.5 L,
with an additional 1 L associated with food preparation.
The Panel recommends that:
a) EPA incorporate variability parameters for individual water consumption into
their analysis for the Taiwanese population as they have done for the U.S.
population estimates as NRC recommended;
b) Because assumptions about water consumption are an important source of
variability in the risk estimates, EPA should conduct sensitivity analyses of
the impact of using a range of consumption values for the Taiwanese
population.
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c) Because data on gender differences in consumption in Taiwan are limited, a
better justification for assuming different consumption levels by gender is
needed, particularly given the lack of sex difference in consumption in U.S.
and observed in studies from other countries (Watanabe et al., 2004). In the
absence of such a justification, the panel recommends an additional sensitivity
analysis to examine the impact of equalizing the gender-specific consumption
level.
d) The source of data for intake from other beverages and cooking water needs to
be more fully discussed and documented. Specifically, the document should
more clearly articulate how different sources of water intake are incorporated
into the risk model including beverages other than water (e.g. green tea) and
water used in food preparation. Clarification of both the assumed
consumption level and how water consumption and consumption variability is
introduced within the model is needed.
3.5.5 Selection of an estimate of dietary intake of arsenic from food
(Charge Question D5)
EPA stated that, "The issue of intake of arsenic from food (e.g., dry rice, sweet
potatoes) has been distinguished from the issue of intake of arsenic from drinking water.
The NRC addressed the issue of arsenic in food by determining how sensitive the
calculation of ED0i was to the consumption rate. NRC found that changing the
consumption rate from 50 |ig/day to 30 |ig/day did not change the calculated EDoi
significantly (about 1% difference). Since the publication of NRC 2001, a number of
new studies have become available, summarized in the Cancer Slope Factor Workgroup
Issue Paper. EPA's current cancer modeling includes dietary intake adjustments for 0,
10, 30, and 50 jig/day" (USEPA, 2005a)." Charse Question D5 asks the SAB "... what
background dietary arsenic intake value it recommends for both the control population
and study population of Southwestern Taiwan (which is used in deriving the cancer slope
factor for inorganic arsenic?) "
The Panel did not recommend a specific value for EPA to use; however, it did
recommend a sensitivity analysis to assess the impact of a range of dietary intakes on risk
from lung and bladder cancer risk associated with arsenic in drinking water used by this
population (e.g. 50 to as high as 200 jig/day). The Panel stated that an intake of zero
arsenic from food should not be assumed.
Three studies that summarize daily arsenic consumption as derived from food in
areas of high arsenic intake are listed in Table 4 (USEPA OPP, 2005). Based on the
NRC's recommendations, EPA used a range of 30-50 jig per day total arsenic intake from
dry rice (uncooked) and dried yams in the diet of southeastern Taiwan that also was
based on the work of Schoof et al. (1998) as listed in this table. In materials presented
and submitted to the Panel (Schoof, 2005), Dr. Schoof, stated her belief that the field had
not been recently treated given the levels she found (7 to 8 ppm) but that seasonality and
recent application of arsenicals should influence the levels of arsenic found in the field
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and in plants grown on those fields. Thus the Schoof et al. (1998) data cited in Table 4
may underestimate the dietary arsenic intake from food in this population.
In the following paragraphs, the term total arsenic indicates the sum of all
inorganic and organic arsenic species. The term inorganic arsenic as stated in published
literature on analysis of arsenic in food generally refers to the sum of the inorganic
arsenic species (iAs In and iAsv). Unless specifically stated otherwise, the term organic
arsenic indicates total organic arsenic compounds in food. In reference to seafood,
arsenobetaine is generally the major organic arsenic compound present when organic
arsenic compounds are specifically identified in the analysis; other minor organic
arsenicals may also be present. The methylated arsenic metabolites (MMA111 MMAV,
DMA111, DMAV) are organic arsenic compounds, however, they are not generally
determined in food.
Daily intake of arsenic from food observed by Chowdhury et al. (2001) and
Watanabe et al., (2004) suggest total arsenic intakes ranging from a mean of 120 to 285
jig/day from food in Bangladeshi and Indian populations exposed to high levels of
naturally occurring arsenic. Mean total arsenic intakes for males were shown to be 214
jig /day and for females 120 jig /day (Watanabe et al., 2004). In studies conducted in
West Bengal in which both chemical analysis of food items and interviews for food
intake were conducted to assess exposure, Roychowdhury et al., (2002) show daily
dietary intakes from food for adults (based on 34 families in 5 villages) ranging from
171-189 |ig/day and for children of about 10 years ranging from 91-101 jig/day. These
figures are ranges of means for two different geographic areas - standard deviations were
not published. Although these data are not derived specifically from the area of Taiwan
studied, they indicate along with ancillary information presented here and elsewhere that
dietary exposure from food in this geographic area may be higher than previously
thought. Raw rice, a staple of the area, has been shown in other studies to contain among
the highest iAs values in food (Schoof, et al., 1999) while for vegetables approximately
95% of total arsenic is organic arsenic (Chowdhury et al., 2001). Variation in arsenic
concentration and speciation occurs relative to rice cultivar (Williams et al., 2005).
Duxbury et al. (2003) estimates that 30-85% of arsenic in rice is inorganic arsenic.
Diet is the largest source of total arsenic exposure in the U.S. relative to water and
air exposures. Average intake is about 40 |ig/day total arsenic (ATSDR, 2006) compared
with the approximately five-fold higher total dietary arsenic intake observed in Asian
studies cited in the foregoing paragraph. The estimated range of daily intake of total
arsenic from food in the U.S. is reported at 2-92 |ig/day (Tao and Bolger, 1999) while
U.S. daily total intake of iAs at the 10th and 90th percentiles is estimated to be 1.8 to 11.4
jig/day for males and 1.3 to 9.4 |ig/day for females (Meacher, et al, 2002). The U.S.
dietary intake of inorganic arsenic is estimated to range from 1 to 20 |ig/day (ATSDR,
2006). U.S. shellfish and other marine foods contain the highest total arsenic
concentrations and are the largest dietary source (76% - 96%) of arsenic, however, most
of the arsenic in seafood is present as the organic arsenic compound arsenobetaine, which
is excreted rapidly and unchanged and does not appear to be harmful to humans
(ATSDR, 2006). It is known, however, that fish may contain some portion of iAs further
52
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pointing to the need for the sensitivity analysis described below. Certain seafood may
also contain DMA that may also contribute to background exposure from food relative to
water sources (Huang, et al., 2003).
It is clear that the adjustment for background iAs intake from food is extremely
important given that the total exposure dose from all sources does likely matter in terms
of toxicity and cancer induction and that the U.S. population likely has a considerably
lower total arsenic intake from food than do populations in Asia.
The Panel recommends that a range of values from at least 50 to 100 |ig/day and
up to perhaps as high as 200 |ig/day be run in a sensitivity analysis to assess the impact of
this range of dietary intakes on risk of lung and bladder cancer from exposure via
drinking water in this population. The cancer risk model needs to be evaluated using a
wider range of iAs food values above 50 |ig/day to determine if there is a change in the
arsenic cancer exposure-response slope as a result. It also cannot be assumed that the
control population has an intake of zero arsenic from food.
Such a sensitivity analysis of the impact of dietary arsenic uptake using a range of
data from high arsenic-exposed populations is unlikely to introduce larger uncertainly
than the myriad dietary differences - protein deficiency, Se, Zn, folate deficiency etc. -
between this Taiwanese population and the U.S. population
Much greater rigor needs to be applied in discussing and presenting documented
data sources and making clear the basis on which assumptions are being made and the
relative strength of those assumptions. Comparisons of the impact of differing levels of
iAs intake from food between the exposed and reference population need to be made on
the basis of comparative relative risk. Clearer statements are needed on the data
limitations of past daily dietary arsenic intake for the Blackfoot endemic area of Taiwan
and for the reference population(s).
EPA needs to be aware of and include a discussion of methodological and
analytical issues related to reported arsenic concentrations in food, because these values
are dependent upon differential extraction processes and analytical procedures applied by
diverse laboratories on a variety of food stuffs. Only the arsenic extracted from food can
be measured. More importantly, laboratory extraction procedures are not designed to
equate with that portion of arsenic in food that is bioavailable. Thus, the arsenic value
resulting from extraction and measurement is not necessarily related to the concentration
that is bioavailable to humans from specific sample sources. There is an immediate need
for thorough research on the bioavailability of arsenic from food.
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potent genotoxins in vitro. Chem. Res. Toxicol. 16:994-1003
Apostoli, P. Alessio, L. Romeo, L. Buchet, J.P., Leone, R. (1997) Metabolism of arsenic
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Ramirez, D., Morgan, D.L., Avram, D., and Aposhian, M.M. (2000) Occurrence
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(2003) Oxidation and detoxification of trivalent arsenic species. Toxicol. Appl.
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Arnold, L. L., Eldan, M., van Gemert, M., Capen, C., and Cohen, S. (2003) Chronic
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APPENDIX A
Charge to EPA Science Advisory Board Arsenic Review Panel
July 25, 2005
Background: There are both natural and anthropogenic sources of arsenic and arsenic
containing compounds (or arsenicals). Exposure to arsenicals can be through different
environmental media including drinking water, food, soil, and air. EPA assesses and
regulates the potential exposure and health risks associated with exposure to arsenic and
arsenic containing compounds through several statutory authorities. The Safe Drinking
Water Act (SDWA), directs EPA to establish national standards for contaminants
including arsenical compounds in public drinking water supplies. EPA's Superfund and
Resource Conservation and Recovery Act (RCRA) programs evaluate exposure to arsenic
compounds at sites selected for clean up or remediation. Under the Clean Air Act, EPA's
Office of Air and Radiation sets emissions standards for sources of arsenic to air. These
include standards based on control technology and those based on risks to human health
from inhalation of airborne arsenic or ingestion of arsenic arising from air sources.
EPA's Office of Pesticide Programs (OPP) evaluates the exposure and health risks
associated with arsenicals used as pesticides in the U.S. Under the mandate of the Food
Quality Protection Agency (FQPA), EPA must reevaluate all pesticide food tolerances
(the legal limits of pesticides on/in food or animal feed) in the U.S. by August, 2006.
There are several organic arsenic herbicides that are undergoing reregi strati on and/or
tolerance reassessment including cacodylic acid (referred to as dimethylarsinic acid or
DMAV), monosodium, disodium, and calcium salts of methanearsonate acid (MSMA,
DSMA, and CAMA, collectively as referred as MMAV). In 2003, most residential uses
of chromated copper arsenate (CCA) as a wood preservative were cancelled.
The health effects of arsenicals have been the subject of two reviews by the
National Research Council (NRC) of the National Academy of Sciences (NAS) (NRC
1999; 2001). Since the 2001 NAS review, there has been substantial new information
developed on the mode of carcinogenic action and metabolism and toxicokinetics for
arsenic and its methylated species, and new epidemiology on inorganic arsenic. The
Agency has considered this new science in regards to the hazard characterization required
for tolerance assessment of DMAV (and MMAV) as described in the draft OPP Science
Issue Paper: Mode of Action for Cacodylic Acid (Dimethylarsinic Acid) and
Recommendations for Dose Response Extrapolation, and also in the ORD Issue Paper -
Cancer Risk Assessment for Organic Arsenical Herbicides: Comments on Mode of
Action, Human Relevance and Implications for Quantitative Dose-Response Assessment
(See Appendix E). In addition, the Agency has developed a revised hazard and dose
response assessment/characterization of inorganic Arsenic (Toxicological review of
inorganic arsenic in Support of Summary Information on the Integrated Risk Information
System (IRIS)) which relies on the two NRC reviews and provides an updated human
health effects and dose-response assessment for inorganic arsenic. The Agency seeks
comment and advice from the SAB on the scientific soundness of major science
conclusions drawn in these two documents regarding the carcinogenic assessments of
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DMAV and inorganic arsenic and the appropriateness of the Agency's application of its
own Guidelines for Carcinogen Risk Assessment for arsenicals.
Overview of Science and Assessment Issues: Ingestion of inorganic arsenic has been
demonstrated to cause cancer of the skin, lung, and urinary bladder in humans.
Historically, standard chronic bioassays with exposure to inorganic arsenic in rodents
have been negative for increased tumor formation. There are, however, more recent
studies at high doses, in transgenic animals, and following transplacental exposures
which have demonstrated cancer potential in rodent studies following exposure to
inorganic arsenic. The NRC 1999 report advises that the bladder and lung cancer human
mortality data, particularly from the southwestern Taiwanese studies provide the best
dose-response data for evaluating the long-term effects of ingestion of inorganic arsenic.
In the 2001 NRC report, a number of recommendations were made to EPA to revise the
oral cancer slope for inorganic arsenic. Given the available database, and recognizing that
the mode(s) of action by which inorganic arsenic causes cancer has not been fully
established, the draft Toxicological Review of Arsenic, consistent with advice from the
NRC uses linear low dose extrapolation to estimate cancer risks from ingestion of arsenic
at low dose and has addressed many of the NRC recommendations.
In approaching the cancer assessment on the pesticide cacodylic acid (DMAV), an
organic arsenical, EPA has confronted a number of challenging issues. No human
epidemiological information is available for DMAV. Rodent cancer bioassay data have
shown that dietary administration of DMAV can result in bladder carcinogenesis in the
rat. DMA, however, is a key urinary metabolite from exposure to inorganic arsenic.
Thus, the question is raised regarding the extent the cancer epidemiology on inorganic
arsenic may provide an appropriate dataset or may inform the low dose extrapolation for
the cancer risk associated with direct exposure to DMAV. Available in vivo and in vitro
pharmacokinetic, metabolism studies, and toxicology studies were reviewed to address
this issue. The draft OPP Science Issue Paper states that the evidence indicates inorganic
arsenic and DMAV have different pharmacokinetic and pharmacodynamic
characteristics, EPA proposes to use the rat bioassay data on DMAV to estimate its cancer
risk. The ORD Issue Paper (Appendix E of the OPP Science Issue Paper: Cancer Mode of
Action of Cacodylic Acid (Dimethylarsinic Acid) and Recommendations for Dose
Response Extrapolation) provides additional discussion on the MOA issues and
perspective on the nexus between science issues for organic and inorganic arsenicals.
The use of mode of action data in the assessment of potential carcinogens is a main focus
of EPA's 2005 cancer guidelines. Mode of action data are available on DMA and were
evaluated to guide the low dose extrapolation.
The Agency seeks comments and advice from the SAB on key science issues
concerning (A) the metabolism and toxic responses of arsenic species, (B) the mode of
action for carcinogenesis and implications for dose-response extrapolation for DMAV and
inorganic arsenic, (C) the selection of data for dose-response, and (D) approaches to low-
dose extrapolation. In addition, the Agency is requesting comment on the implications of
newer epidemiology and the incorporation of the 2001 NRC recommendation on
modeling the human cancer data for inorganic arsenic.
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Issues and Charge Questions
A. Metabolism and Toxic Responses of Arsenic Species
Al. Metabolism and pharmacokinetics: Evidence from in vivo and in vitro
metabolism and pharmacokinetic studies with humans and laboratory animals
suggests that the efficiency of the methylation reaction(s) and cellular uptake
varies based on which arsenical compound is administered exogenously. Most
available studies suggest that the metabolic process in most mammals is primarily
a one-way process and that following direct exposure to DMAV significant
amounts of iAsm, iAsv, MMAm, or MMAV at the target tissue are not expected.
Please comment on how pharmacokinetic processes are best considered regarding the
use of data derived from direct DMAV exposure versus direct iAs exposure for cancer risk
assessment.
A2. Response to mixtures of metabolites: Tumorigenic profiles vary based on
which arsenical compound is administered exogenously. In vivo and in vitro studies
indicate that each of the arsenical compounds exhibit similarities and differences in their
profiles of biological activities. Direct exposure to iAs111 or iAs v is expected to result in
more of a mixture of toxic metabolites than for direct exposure to DMAv; the mixture of
metabolites is expected to vary based on which chemical is administered exogenously.
The potential mixture of metabolites following direct exposure to DMAV appears less
complex as compared to iAs.
Given the toxicological response profiles observed following direct exposures to iAs
versus MMAV and DMA1\ and the differences in human and rodent toxicologic responses
to arsenicals, please comment on the use of data derived from rodent exposures to the
organic arsenicals versus use of data derived from direct iAs human exposure, in the
DMA v assessment.
B. Modes of Carcinogenic Action for DMAV and Inorganic Arsenic
Bl. Mode of action of DMAV: When relying on laboratory animal data, two
critical assumptions are made: (i) data on animal tumors are predictive of human
cancer, and (ii) animal tumor effects found at high experimental doses predict
human risk at lower exposures. An understanding of a chemical mode of
carcinogenic action can help inform the above assumptions. In the case of
DMAV, mode of action (MOA) data are available and were evaluated using the
framework described in EPA's cancer guidelines.
Please comment on the sufficiency of evidence to establish the animal mode of
carcinogenic action forDMA1'. Are the scientific conclusions sound and consistent with
the available evidence on DMAV and the current state of knowledge for chemical
carcinogenesis.
Please comment on whether the key events in DMA 's mode of action are supported by the
available data. Specifically comment on the role of: a) reactive oxygen species in
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producing chromosomal damage and the strength of the evidence supporting oxidative
damage as a causal key event in DMAV/DMAUI s mode of carcinogenic action versus an
associative event or a secondary consequence ofcytotoxicity; b) cell proliferation and
cytotoxicity and the strength of the evidence as causal key events in DMAV/DMAIU s mode
of carcinogenic action versus associative or secondary events, and c) other potential
modes of action that have substantial scientific support that may be contributing to the
carcinogenicity of DMA.
B2. Human relevance of animal DMAV MOA: There are little or no
scientific data to suggest that if sufficient DMA111 were present, key precursor
events and ultimately tumor formation would not occur in humans directly
exposed to DMAV.
Please comment on the relevance of the postulated key events (see Bl) to tumors in
humans.
Please comment on how, if at all, differences in the human population vs. experimental
animals should be accounted for in the risk assessment for DMAV.
There are little to no chemical specific data regarding an increased susceptibility
of humans for bladder tumor development during different life stages.
Please comment on the Agency's conclusion that the young are likely to respond like the
adult to the formation of bladder tumors following exposure to DMA.
B3. Modes of carcinogenic action from exposure to inorganic arsenic:
Inorganic arsenic (iAs) undergoes successive methylation steps in humans,
resulting in the intermediate production of iAs111, MMAV, MMA111, DMAV, and
DMA111. Each arsenical metabolite exhibits its own toxicity.
Please comment on the conclusion that the available data support the hypothesis that
multiple modes of action may be operational following exposure to inorganic arsenic.
C. Selection of Data for Dose-Response Assessment
Cl. Use of animal data for DMAV : A number of different rodent bioassays
(standard bioassay, transgenic animals, susceptible rodent strains, initiation and
promotion studies) are available on DMAV.
Please comment on the use of the bladder tumor data from the DMAV rat bioassay
as the most suitable datasetfor quantifying potential human cancer risk to DMA1\
including the weight of evidence to support this conclusion.
Please comment on whether the iAs epidemiology data can be used to inform the DMAV
dose-response assessment derived from rat data with DMAV. If so, please discuss how
such information might be used. (See Appendix).
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C2. Use of human epidemiological data from direct iAs exposure: Since the
NRC (2001) report on iAs, an additional body of literature has developed
describing epidemiology data from populations in the US exposed to iAs in
drinking water.
Does the SAB agree that the Taiwanese dataset remains the most appropriate choice for
estimating cancer risk in humans? Please discuss the rationale for your response.
Do these data provide adequate characterization of the impact of childhood exposure to
iAs? Please discuss the rationale for your response.
D. Approaches to Low-Dose Extrapolation for Inorganic Arsenic and DMAV
Dl. Mode of carcinogenic action understanding for DMAv/m and
implications for dose response extrapolation to estimate human cancer risk: The
use of mode of action data in the assessment of potential carcinogens is a main
focus of EPA's 2005 cancer guidelines. As stated in these guidelines "The
approach to dose-response assessment for a particular agent is based on the
conclusion reached as to its potential mode(s) of action". Although a biological-
based model is the preferred approach to estimating cancer risk, there are
insufficient data on DMAV to support development of such a model.
Please comment on the scientific evidence and biological rationale in support of
nonlinear versus linear low dose extrapolation approaches, which approach is
more consistent with the available data on DMAVand current concepts of
chemical carcinogenesis, and how scientific uncertainty should most
appropriately be incorporated into low-dose extrapolation.
D2. Implementation of the recommendations of the NRC (2001): EPA has
determined that the most prudent approach for modeling cancer risk from
exposure to iAs is to use a linear model because there are significant remaining
uncertainties regarding which of the metabolite(s) may be the ultimate
carcinogenic moiety and whether or not mixtures of toxic metabolites interact at
the site(s) of action.
Does the panel concur with the selection of a linear model following the
recommendations of the NRC (2001) to estimate cancer risk at this time? Please discuss
your response in light of the highly complex mode of action for iAs with its metabolites.
D3. EPA re-implemented the model presented in the NRC (2001) in the
language R as well as in an Excel spreadsheet format. In addition, extensive
testing of the resulting code was conducted.
Please comment upon precision and accuracy of the re-implementation of the model.
D4. Available literature describing drinking water consumption rates for
the southwestern Taiwanese study population: NRC (2001) stated that the
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drinking water consumption rate, as well as variability of that rate in both US and
Taiwanese populations, are important factors to consider. In calculating risk
estimates for U.S. populations exposed to arsenic through drinking water, NRC
used a drinking water consumption rate of 1 L/day for the US population and two
possible consumption rates for the Taiwanese population: 1 L/day (identical to
the US population) and 2.2 L/day with little or no supporting rationale. Since
publication of NRC 2001, a number of new studies have become available and are
summarized in the Cancer Slope Factor Workgroup Issue Paper. Agency reviews
of the relevant literature suggests that the mean drinking water (for the Taiwanese
study population) consumption rate is between 1 to 4.6 L/day. EPA's current
cancer modeling includes water intake adjustments for 2.0 and 3.5 L/day.
What drinking water value does the panel recommend for use in deriving the cancer
slope factor for inorganic arsenic?
D5. Selection of an estimate of dietary intake of arsenic from food: The
issue of intake of arsenic from food (e.g., dry rice, sweet potatoes) has been
distinguished from the issue of intake of arsenic from drinking water. The NRC
addressed the issue of arsenic in food by determining how sensitive the
calculation of ED0i was to the consumption rate. NRC found that changing the
consumption rate from 50 |ig/day to 30 |ig/day did not change the calculated ED0i
significantly (about 1% difference). Since the publication of NRC 2001, a
number of new studies have become available, summarized in the Cancer Slope
Factor Workgroup Issue Paper. EPA's current cancer modeling includes dietary
intake adjustments for 0, 10, 30, and 50 jig/day.
What background dietary intake (of arsenic) value does the panel recommend for both
the control population and study population of Southwestern Taiwan used in deriving the
cancer slope factor for inorganic arsenic?
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APPENDIX B
Assignments to Charge-Specific Groups (revised on 8/24/05)
Issue A: Metabolism and Toxic Responses of Arsenic Species
Question Al: Metabolism and Pharmacokinetics
Dr. Aposhian Dr. Rosen
Dr. Medinsky Dr. Styblo
Dr. Le Dr. Hopenhayn
Question A2: Response to mixtures of metabolites
Dr. Aposhian Dr. Rosen
Dr. Medinsky Dr. Styblo
Dr. Le Dr. Hopenhayn
Issue B: Modes of Carcinogenic Action for DMA and iAs
Question Bl: Mode of Action of DMAV
Dr. Barchowsky Dr. Rossman
Dr. Brusick Dr. Styblo
Dr. Dragan Dr. Waalkes
Dr. Klaunig
Question B2: Human relevance of animal DMAV MOA
Dr. Barchowsky Dr. Rossman
Dr. Brusick Dr. Styblo
Dr. Dragan Dr. Waalkes
Dr. Klaunig
Question B3: Modes of carcinogenic action from exposure to inorganic
arsenic
Dr. Barchowsky Dr. Klaunig
Dr. Brusick Dr. Rossman
Dr. Dragan Dr. Waalkes
Issue C: Selection of Data for Dose-Response Assessment
Question Cl: Use of animal data for DMAV
Dr. Cantor Dr. Teeguarden
Dr. Green Dr. Waalkes
Dr. Medinsky Dr. Yager
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Question C2: Use of human epidemiological data from direct iAs exposure
Dr. Cantor Dr. Rosen
Dr. Colford Dr. Rossman
Dr. Harlow Dr. Yager
Dr. Hopenhayn
Issue D: Approaches to Low-Dose Extrapolation for iAs and DMAV
Question Dl: Mode of Carcinogenic action understanding for DMAV/III and
implications for dose response extrapolation to estimate human cancer risk
Dr. Cantor Dr. Medinsky
Dr. Colford Dr. Teeguarden
Dr. Green Dr. Waalkes
Dr. Klaunig
Question D2: Implementation of the recommendations of the NRC (2001)
Dr. Colford Dr. Portier
Dr. Harlow Dr. Rosen
Dr. Hopenhayn Dr. Rossman
Dr. Heeringa
Question D3: EPA re-implementation of the NRC (2001) model in language
R and Excel spreadsheet.
Dr. Heeringa
Dr. Portier
Dr. Teeguarden
Question D4: Literature describing drinking water consumption rates for
the southwestern Taiwanese study population
Dr. Barchowsky
Dr. Harlow
Dr. Colford
Dr. Yager
Question D5: Selection of an estimate for dietary intake of arsenic
Dr. Aposhian
Dr. Barchowsky
Dr. Harlow
Dr. Styblo
Dr. Yager
B-2
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APPENDIX C
ABBREVIATIONS
Abbreviations
ARP
As
BEIR
CAMA
CCA
DMA111
DMAV
DSMA
EPA
FIFRA
FQPA
GPO
iAs
iAs111
NFkB
iAsv
MLE
MMA111
MMAV
MN
MOA
MSMA
NAS
NHANES
NRC
OPP
ORD
OW
PBPK
PD
PK
RCRA
ROS
SAB
TMA111
TMAVO
Meaning
US EPA SAB Arsenic Review Panel
Arsenic
Biological Effects of Ionizing Radiation
Calcium salt of MMAV
Chromated copper arsenate
Dimethylarsinous acid
Dimethylarsinic acid, Cacodylic Acid
Di sodium salt of MMAV
US Environmental Protection Agency
Federal Insecticide, Fungicide, and Rodenticide Act
The Food Quality Protection Act
US Government Printing Office
Inorganic arsenic
Arsenite, Trivalent inorganic arsenic
Nuclear factor-kappa B
Arsenate, Pentavalent inorganic arsenic
Maximum Likelihood Estimates
Methylarsonous acid
Methanearsonate acid, methylarsenic acid
Micronuclei
Mode of Action
Monosodium salt of MMA
National Academy of Sciences
National Health and Nutrition Examination Survey
National Research Council of the NAS
US EPA Office of Pesticide Programs
US EPA Office of Research & Development
US EPA Office of Water
Physiologically Based Pharmacokinetic Models
Pharmacodynamics
Pharmacokinetics
Resource Conservation and Recovery Act
Reactive Oxygen Species
US EPA Science Advisory Board
Trimethylarsine
Trimethylarsine oxide
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