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A New Approach Methodology for the Prediction of Tumorigenesis in the Rat
Citation:
Ledbetter, V., S. Auerbach, L. Everett, B. Vallanat, A. Lowit, G. Akerman, M. Devito, AND C. Corton. A New Approach Methodology for the Prediction of Tumorigenesis in the Rat. North Carolina Society of Toxicology 2022 annual meeting, Durham, NC, October 19, 2022. https://doi.org/10.23645/epacomptox.21372006
Impact/Purpose:
Poster presented to the NC Society of Toxicology Meeting October 2022. Cancer is the 2nd leading cause of death in the U.S., putting tremendous pressure on the economy. Tens of thousands of chemicals on the market have not been adequately tested for cancer hazard. Testing using the “gold standard” 2-year cancer bioassay is not feasible to fill this data gap. Thus, new approach methodologies (NAMs) are necessary to assess potential carcinogenicity of uncharacterized chemicals. The present study shows how a NAM can be used to identify chemicals and their doses that could cause liver cancer in rats without having to conduct a 2-year bioassay. The NAM uses 6 previously established gene expression biomarkers and tumorigenic activation levels (TALs) to interpret transcript profiles derived from the livers of treated rats. The NAM can identify the chemical mode of action and (non)tumorigenic doses. While this NAM cannot completely replace rodent bioassays, this approach can be used to determine if the 2-year bioassay is necessary potentially reducing cost, time, and resources needed.
Description:
Current methods for cancer risk assessment are resource-intensive and not feasible for the vast majority of the thousands of untested chemicals. In earlier studies, we developed a new approach methodology (NAM) to identify liver tumorigens using gene expression biomarkers and associated tumorigenic activation levels (TALs) after short-term exposures in rats. The biomarkers are used to predict the six most common rodent liver cancer molecular initiating events (MIE). In the present study, we wished to confirm that our approach could be used to identify liver tumorigens at only one time point/dose and if the approach could be applied to (targeted) RNA-Seq analyses. Male rats were exposed by daily gavage for 4d to 15 chemicals at doses with known chronic outcomes; liver transcript profiles were generated using Affymetrix arrays. Our approach had 75% or 85% predictive accuracy using TALs derived from the TG-GATES or DrugMatrix studies, respectively. In a dataset generated from the livers of male rats exposed to 16 chemicals at up to 10 doses, we found that our NAM coupled with targeted RNA-Seq (TempO-Seq) could be used to identify tumorigenic chemicals with predictive accuracies of up to 91%. Overall, these results demonstrate that our NAM can be applied to both microarray and (targeted) RNA-Seq data generated from short-term rat exposures to identify chemicals and their doses that could induce liver tumors, one of the most common endpoints in rodent bioassays. (This abstract does not represent EPA policy.)
URLs/Downloads:
DOI: A New Approach Methodology for the Prediction of Tumorigenesis in the Rat
LEDBETTER_POSTER_A NEW APPROACH METHODOLOGY (NAM) TO THE PREDICTION OF TUMORIGENESIS_2022_10_16_22.PDF (PDF, NA pp, 792.02 KB, about PDF)