Dioxin hepatic carcinogenesis: biologically motivated modeling and risk assessment

Modeling drug- and chemical-induced hepatotoxicity with systems biology approaches

We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of “toxicity pathways” is described in the context of the 2007 US National Academies of Science report, “Toxicity testing in the 21st Century: A Vision and A Strategy.” Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity) – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular “virtual tissue” model of the liver lobule that combines molecular circuits in individual hepatocytes with cell–cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the aryl hydrocarbon receptor toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsym™) to understand drug-induced liver injury (DILI), the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

Applying Mode-of-Action and Pharmacokinetic Considerations in Contemporary Cancer Risk Assessments: An Example with Trichloroethylene

The guidelines for carcinogen risk assessment recently proposed by the U.S. Environmental Protection Agency (U.S. EPA) provide an increased opportunity for the consideration of pharmacokinetic and mechanistic data in the risk assessment process. However, the greater flexibility of the new guidelines can also make their actual implementation for a particular chemical highly problematic. To illuminate the process of performing a cancer risk assessment under the new guidelines, the rationale for a state-of-the-science risk assessment for trichloroethylene (TCE) is presented. For TCE, there is evidence of increased cell proliferation due to receptor interaction or cytotoxicity in every instance in which tumors are observed, and most tumors represent an increase in the incidence of a commonly observed, species-specific lesion. A physiologically based pharmacokinetic (PBPK) model was applied to estimate target tissue doses for the three principal animal tumors associated with TCE exposure: liver, lung, and kidney. The lowest points of departure (lower bound estimates of the exposure associated with 10% tumor incidence) for lifetime human exposure to TCE were obtained for mouse liver tumors, assuming a mode of action primarily involving the mitogenicity of the metabolite trichloroacetic acid (TCA). The associated linear unit risk estimates for mouse liver tumors are 1.5 x 10(-6) for lifetime exposure to 1 microg TCE per cubic meter in air and 0.4 x 10(-6) for lifetime exposure to 1 microg TCE per liter in drinking water. However, these risk estimates ignore the evidence that the human is likely to be much less responsive than the mouse to the carcinogenic effects of TCA in the liver and that the carcinogenic effects of TCE are unlikely to occur at low environmental exposures. Based on consideration of the most plausible carcinogenic modes of action of TCE, a margin-of-exposure (MOE) approach would appear to be more appropriate. Applying an MOE of 1000, environmental exposures below 66 microg TCE per cubic meter in air and 265 microg TCE per liter in drinking water are considered unlikely to present a carcinogenic hazard to human health.

Determination of tissue-blood partition coefficients for a physiological model for humans, and estimation of dioxin concentration in tissues

The tissue-blood partition coefficients for a physiologically based pharmacokinetic (PBPK) model were determined, and the concentrations of 17 congeners of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) in tissues in Japanese people were estimated using the model. According to the PBPK model established by Lawrence and Gobas [Chemosphere 35 (1997) 427-452], we assumed a steady-state fugacity model for Japanese people in general, and set the route of PCDD/Fs exposure only from food intake. The required partition coefficients for liver, kidney, adipose, muscle, skin, bile, gut and viscera (richly perfused tissue) were calculated using available autopsy data from eight Japanese men and women who were not accidentally exposed to PCDD/Fs. For validation of the partition coefficients, estimated PCDD/F concentrations in liver, kidney, fat, blood and muscle using the model were compared to other two sets of measured concentration data in Japanese tissues. Good agreement was obtained between estimated data and measured data, and most of the measured data were within the simulated concentration range in liver, kidney, blood and muscle. From these results, our model and calculated partition coefficients seem applicable for the estimation of congener-specific concentrations in human tissues.

Human risk assessment and TEFs

The concept of toxic equivalency factors (TEFs) has been developed to facilitate risk assessment and regulatory control of exposure to complex PCDD, PCDF and PCB mixtures. Recently the European Centre for Environment and Health of the World Health Organization (WHO-ECEH) and the International Programme on Chemical Safety (IPCS) jointly re-evaluated the TEFs of PCDDs, PCDFs and dioxin-like PCBs for mammals and derived consensus TEFs for birds and fish (Stockholm, 1997). From a mechanistic point of view it can be concluded that, although the quantitative response will vary depending on the congener involved, the occurrence of a common mechanism (binding to the Ah receptor) legitimates the use of the TEF concept across species. But there also is criticism regarding the TEF concept. Pharmacokinetic differences between species can significantly influence the TEF value, and uncertainties due to additive or non-additive interactions, to differences in species responsiveness and to differences in the shape of the dose-response curve might hamper the derivation of consensus TEF values. In this context it should be noted, however, that using TCDD alone, as the only measure of exposure to dioxin-like PCDDs, PCDFs and PCBs, would severely underestimate the risk from exposure to these compounds. Therefore, it can be concluded that, for pragmatic reasons, the TEF concept remains the most feasible approach for risk assessment purposes, in spite of the uncertainties associated with its use.

Extrapolating the future: research trends in modeling

The proceedings in this volume suggest several important future research needs. Research is needed to validate modeling in toxicology in order to support the use of the general approach of modeling, either for structure-activity relationships (SAR) or physiologically based pharmacokinetics (PBPK), by regulators. Research is needed to demonstrate how SAR predictions can be integrated with the PBPK models to reduce the chemical-specific, intensive data requirements of PBPK models. Methods are needed to harmonize modeling approaches and to educate potential users. New approaches to modeling are needed which go beyond present day assumptions of flow-limited models into dynamic models of human health effects. The academic community can further these objectives by including applied mathematics of toxicology, including both SAR and PBPK modeling, in toxicology curricula.

Development of physiologically based pharmacokinetic and physiologically based pharmacodynamic models for applications in toxicology and risk assessment

Pharmacokinetics (PK) involves the study of the rates of absorption, distribution, excretion, and biotransformation of chemicals and their metabolites. PK models can be used to reconstruct extensive time-course data sets based on a small number of kinetic parameters. These models can be used to predict the results of new experiments and integrate studies on kinetics, disposition and metabolism in various animal species [1]. The 2 main approaches that have been pursued in developing PK models are: (1) data-based compartmental modeling; and (2) physiologically based compartmental modeling. Data-based models rely on the collection of time-course concentration data and fitting these data with mathematical models. Compartments in these models do not necessarily reflect the anatomy and physiology of the animal, and the kinetic constants derived from these models do not have obvious physiological or biochemical counterparts. In physiologically based pharmacokinetic (PBPK) models, compartments correspond more closely to actual anatomical structures, defined with respect to their volumes, blood flows, chemical binding (partitioning) characteristics, and ability to metabolize or excrete the compounds of interest. Because the kinetic parameters of these models reflect tissue blood flows, partitioning, and biochemical constants, these models are more readily scaled from one animal species to another [2]. PBPK models have been used to understand the disposition of chemicals in the body for almost 70 years. Their more widespread application in toxicology dates back only 15 years or so to models developed for polychlorinated biphenyls and other persistent lipophilic compounds. Quantitative applications of PBPK models in risk assessment date to the development of a number of PBPK models for methylene chloride in the mid 1980s. The burgeoning use of PBPK models in toxicology research and chemical risk assessment today is primarily related to their ability to make more accurate predictions of target tissue dose for different exposure situations in different animal species, including humans. This overview includes a discussion of the development of these PBPK models in toxicology and speculates about future applications of PBPK and physiologically based pharmacodynamic (PBPD) models in chemical risk assessment.

Biochemical mechanisms and cancer risk assessment models for dioxin

Biologically realistic mechanistic models of carcinogenesis by TCDD are composed of equations representing biochemical events leading to altered expression of proteins involved in the response or equations representing the kinetics of proliferation of clones of mutant cells. A biochemically augmented physiological dosimetry model reproduces the observed altered expression of liver proteins in female rats exposed to dioxin. The model suggests that oxidation of estradiol to DNA reactive quinones or semiquinones by CYP1A2 protein induced by TCDD may contribute to an increased mutational rate. It suggests that TCDD-stimulated production of a peptide ligand of the epidermal growth factor (EGF) receptor and subsequent activation of the receptor's tyrosine kinase activity may increase the rate of proliferation of susceptible cells. These calculated quantities can serve as indices of toxicity and can be used to predict tumor incidence as a function of exposure.

Use of mechanistic information in risk assessment for toxic chemicals

Risk assessment (RA) for toxic chemicals is assumed to be a scientific activity providing a framework of principles for the complication and evaluation of all available scientific information and the rational extrapolation to human health effects in as quantitative terms as possible and with a high degree of certainty. Sensible public health decisions are made more certain through the use of mechanistic information throughout the 4 steps in RA: hazard identification, dose-response assessment, exposure (dose) assessment and risk characterisation. Examples of the use of mechanistic information to assess risks of systemic, developmental/reproductive and neurotoxic effects show how to move away from the presently used threshold/no observable adverse effect/uncertainty factor default methodology towards an evaluation based on all available scientific data. The experience gained in cancer RA in the use of metabolic and tissue binding (receptor) models as well as physiologically based pharmacokinetic (PBPK) and pharmacodynamic (PBPD) models can be transferred to non-cancer RA. A good example is the use of a PBPK model for the hepatoxicity of chloroform. As in cancer RA, as default positions are replaced by biological data the risk assessments become less uncertain when extrapolating between species. Combining information on tissue dosimetry and response data can also provide an estimate of variability within populations, which is impossible with present default type methodology but essential for adequate risk characterisation. Unlike the cancer field there is no single hypothesis for the mechanism of action for the multitude of non-cancer end-points studied.