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![Chemical-Induced Skin Carcinogenesis Model Using Dimethylbenz[a]Anthracene and 12-O-Tetradecanoyl Phorbol-13-Acetate DMBA-TPA](/_next/image?url=https%3A%2F%2Fcloudfront.jove.com%2FCDNSource%2Fteasers%2F60445.jpg&w=3840&q=50)
Chemical-Induced Skin Carcinogenesis Model Using Dimethylbenz[a]Anthracene and 12-O-Tetradecanoyl Phorbol-13-Acetate DMBA-TPA
Published on: December 19, 2019
Editor's Highlight: Negative Predictors of Carcinogenicity for Environmental Chemicals
Thomas Hill1, Mark D Nelms1, Stephen W Edwards2
1Oak Ridge Institute for Science and Education participant at the National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina.
Abstract:
Recent international efforts have led to proposals for modified carcinogenicity testing paradigms based on data from shorter-term studies. The main goal of the current study was to evaluate the negative predictive value (NPV) of short-term toxicity indicators on carcinogenicity study outcomes and cancer classifications for chemicals previously reviewed by the U.S. Environmental Protection Agency (EPA). Pathology data were analyzed from over 900 acceptable 2-sex guideline subchronic (3-month) and carcinogenicity studies in the U.S. EPA Toxicity Reference Database. Chemical cancer classifications were obtained from annual reports of the U.S. EPA Office of Pesticide Programs. Histopathologic risk signals and evidence of hormonal perturbation in subchronic rat studies provided 56% NPV for any tumor outcome in the rat or mouse and 75% NPV for cancer classifications not requiring quantitative risk assessment (qRA). In comparison, lack of activity in a battery of 35 in vitro cytotoxicity assays from the U.S. EPA ToxCast library provided 49% NPV for any tumor outcome and 80% NPV for cancer classifications not requiring qRA. These findings support the idea that the absence of short-term bioactivity may provide useful information for prioritizing chemicals based on potential carcinogenic risk. Additional data streams are needed to further refine these models.
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