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Development of a Quantitative Model Incorporating Key Events in a Hepatoxic Mode of Action to Predict Tumor Incidence
Citation:
LUKE, N. S., M. J. DEVITO, R. CONOLLY, AND H. A. EL-MASRI. Development of a Quantitative Model Incorporating Key Events in a Hepatoxic Mode of Action to Predict Tumor Incidence. Presented at Annual Society of Toxicology, Baltimore, MD, March 15 - 19, 2009.
Impact/Purpose:
This work develops a quantitative model to examine the role of cytotoxicity and cellular proliferation as key events in a hepatoxic mode of action. A physiologically based pharmacokinetic model predicts chemical metabolism and is linked to a pharmacodynamic cytotoxicity model which predicts cytotoxicity and regenerative proliferation. This is then linked to a clonal growth model which predicts tumor incidence.
Description:
Biologically-Based Dose Response (BBDR) modeling of environmental pollutants can be utilized to inform the mode of action (MOA) by which compounds elicit adverse health effects. Chemicals that produce tumors are typically described as either genotoxic or non-genotoxic. One commonly proposed MOA for non-genotoxic carcinogens is characterized by the key events of cytotoxicity and regenerative proliferation. The increased division rate associated with such proliferation causes an increase in the probability of mutations, which can result in tumor formation. In this presentation, three carcinogens which are thought to induce tumors in mice through a cytotoxic mode of action (chloroform, carbon tetrachloride, and dimethyl formamide) are quantitatively compared using a generalized BBDR quantitative model for tumor incidences. For each compound, a physiologically based pharmacokinetic (PBPK) model is developed and linked to a pharmacodynamic model of cytolethality and cellular proliferation. The rate of proliferation is then linked to a clonal growth model which predicts tumor incidences. Comparisons of the BBDR simulations and parameterizations suggested that the only significant variation among the models for the three chemicals arise in a few parameters expected to be chemical specific (such as metabolism and cellular injury rate constants). The BBDR model was used to quantitatively indentify limits of cellular injury and proliferation that would result in a significant increase in tumor incidence. Results of the generalized BBDR model simulations provide evidence to inform the use of cytoxicity and cellular proliferation as key events within this MOA for these chemicals. This BBDR model or subsequent versions in this iterative process may prove useful in testing if cytotoxicity and cellular proliferation can be considered a cancer MOA for chemicals that produce liver tumors when their chemical specific parameters are available. (This abstract does not reflect USEPA policy.)