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Transcriptomic effect marker patterns of genotoxins - a comparative study with literature data.

Katrin Kreuzer1, Falko Frenzel1, Alfonso Lampen1

  • 1Dept. Food Safety, German Federal Institute for Risk Assessment, Berlin, Germany.

Journal of Applied Toxicology : JAT
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PubMed
Summary

Comparing gene expression data from toxicological studies reveals significant variability. However, analyzing broader biological functions shows greater consistency, highlighting the need for standardized omics data processing in risk assessment.

Keywords:
HepaRG cellsaflatoxinbenzo[a]pyrenebiomarkergene expressionhepatotoxicitymicroarraytoxicogenomics

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Area of Science:

  • Toxicogenomics
  • Molecular Toxicology
  • Biomarker Discovery

Background:

  • Microarray analysis is valuable for characterizing toxicological compound mechanisms.
  • Omics techniques are underutilized in regulatory settings due to standardization and adversity definition issues.

Purpose of the Study:

  • To determine if consensus transcript biomarker signatures for toxicological endpoints can be derived from published microarray datasets.
  • To assess the feasibility of inter-experiment comparisons of omics data.

Main Methods:

  • Re-analyzed published microarray datasets of human HepaRG cells treated with genotoxins.
  • Compared transcriptome data to identify differentially expressed genes and affected biological functions.

Main Results:

  • Considerable variation in gene expression profiles was observed even for similar compounds in the same cell line.
  • Greater concordance was found when analyzing whole datasets and associated biological functions.
  • Highlighted challenges and opportunities in comparing omics data across experiments.

Conclusions:

  • Improved standardization is crucial for routine use of omics data in risk assessment.
  • Existing omics datasets can provide valuable biological context for adverse outcome pathway development.