Carcinogenesis Modeling for Livers and Liver Tumors of Mice With DCA or TCAEPA Grant Number: R828082
Title: Carcinogenesis Modeling for Livers and Liver Tumors of Mice With DCA or TCA
Investigators: Lei, Xingye Cherry
Institution: Battelle Memorial Institute, Pacific Northwest Division
EPA Project Officer: Louie, Nica
Project Period: February 1, 2000 through April 30, 2003
Project Amount: $513,113
RFA: Mechanistic-Based Cancer Risk Assessment Methods (1999) RFA Text | Recipients Lists
Research Category: Health Effects , Human Health Risk Assessment , Health
The scope of this project is to develop mechanistic carcinogenesis models for risk assessment of byproducts such as dichloroacetate (DCA) and trichloroacetate (TCA) resulting from chlorine-treated drinking water. DCA and TCA are by-products of the disinfecting treatment of drinking water. It has been shown that DCA and TCA are potent inducers of hepatic tumors in B6C3F1 mice. Considerable research has been conducted to study the carcinogenesis of dichloroacetic acid (DCA) or trichloroacetic acid (TCA) induced tumors in rodent livers, and much experimental data have been collected. It is important to identify the mechanism of the tumor/cancer development in mice models to extrapolate the information from animals to humans. In this project, multiple path and multiple stage models will be developed for the DCA and TCA related experimental data. Numerical as well as analytical solutions will be sought for the differential equations resulting from the stochastic modeling.
The overall technical objectives of this project are to 1) develop a prototype MATLAB tool for multi-path/multi-stage mechanistic modeling; 2) gain better understanding of the mechanisms of DCA/TCA induced or promoted tumor development in mice liver; and 3) provide an insight into future experimental as well as mechanistic modeling of the carcinogenic studies.
This project will first start with data organization (from Dr. Bull's experimental work to works from literature), problem formulation, and identification of possible paths/stages from experimental results. It will then develop stochastic models for the analysis of DCA/TCA carcinogenesis data, and resolve issues in parameter estimations. MATLAB tools will be developed to facilitate the modeling processes. Statistical methods of estimation such as generalized linear mixed models and Kalman filter models will be implemented or modified to estimate the kinetic parameters, such as cell replication rate, and mutation rate from one type of intermediate cell to anther type. General methods for estimating tumor incidence through hazard function or survival function will be developed.
The expected outcomes of this project are: 1) publications of the stochastic modeling of DCA/TCA related experimental data; 2) general methods of parameter estimation for biologically based multiple path and multiple stage modeling with MATLAB implementations; 3) recommendations for future carcinogensis modeling and experimentation.