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A New Approach Methodology for the Prediction of Tumorigenesis (NCSOT 23)
Citation:
Ledbetter, V., S. Auerbach, L. Everett, B. Vallanat, A. Lowit, G. Akerman, M. Devito, AND Jon Corton. A New Approach Methodology for the Prediction of Tumorigenesis (NCSOT 23). North Carolina Society of Toxicology (NCSOT) Annual Meeting, Durham, NC, September 14, 2023. https://doi.org/10.23645/epacomptox.25757916
Impact/Purpose:
Presentation to the North Carolina Society of Toxicology (NCSOT) Annual Meeting September 2023
Description:
Current methods for cancer risk assessment are resource-intensive and not practical for thousands of untested chemicals in the environment. 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 confirmed that our approach could be used to identify liver tumorigens at only one time point/dose based on targeted RNA-seq data. 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 databases, 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 demonstrated 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 would induce liver tumors. This NAM approach will significantly reduce the time and cost to generate 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 (NCSOT 23)
A NEW APPROACH METHODOLOGY (NAM) TO THE PREDICTION OF TUMORIGENESIS_NCSOT 2023 (44X70).PDF (PDF, NA pp, 789.24 KB, about PDF)