Toxicogenomics and cancer risk assessment: a framework for key event analysis and dose-response assessment for

Joel P Bercu1, Robert A Jolly, Kelly M Flagella

  • 1Eli Lilly and Company, Lilly Research Laboratories, Health Safety and Environmental, Indianapolis, IN 46285, USA. jsbercu@hotmail.com

Insights

This study used toxicogenomic analysis to identify a threshold for nongenotoxic carcinogens. Benchmark dose analysis of gene expression in short-term rat studies successfully identified a point of departure for risk assessment.

Area of Science:

  • Toxicology
  • Genomics
  • Risk Assessment

Background:

  • Traditional risk assessment for nongenotoxic carcinogens relies on identifying a mode of action (MOA) with a nonlinear dose-response.
  • Establishing a point of departure (POD) can be challenging due to complex MOAs and the extensive research required to elucidate them.

Purpose of the Study:

  • To determine if a POD can be identified using microarray analysis and benchmark dose analysis of gene expression data.
  • To evaluate the utility of toxicogenomic analysis in short-term rodent studies for identifying thresholds of nongenotoxic carcinogens.

Main Methods:

  • Conducted microarray analysis on rats exposed orally to fenofibrate and methapyrilene.
  • Applied benchmark dose analysis to genes aggregated in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) biological processes.
  • Evaluated temporal gene expression responses over 1, 3, and 7 days.

Main Results:

  • Gene expression patterns for fenofibrate were consistent with its known MOA and PPARα activation.
  • Methapyrilene showed complex temporal pathway responses, but benchmark dose values remained consistent.
  • Toxicogenomic POD values were slightly below observed effect levels for tumorigenesis or precursor events.

Conclusions:

  • Toxicogenomic analysis in short-term studies can effectively identify a threshold for nongenotoxic carcinogens.
  • This approach allows for the evaluation of potential key events and can be integrated into risk assessment frameworks.

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