A predictive toxicogenomics signature to classify genotoxic versus non-genotoxic chemicals in human TK6 cells
Andrew Williams1, Julie K Buick1, Ivy Moffat2
1Environmental Health Science and Research Bureau, Health Canada, Ottawa, Ontario, Canada K1A 0K9.
Abstract:
Genotoxicity testing is a critical component of chemical assessment. The use of integrated approaches in genetic toxicology, including the incorporation of gene expression data to determine the DNA damage response pathways involved in response, is becoming more common. In companion papers previously published in Environmental and Molecular Mutagenesis, Li et al. (2015) [6] developed a dose optimization protocol that was based on evaluating expression changes in several well-characterized stress-response genes using quantitative real-time PCR in human lymphoblastoid TK6 cells in culture. This optimization approach was applied to the analysis of TK6 cells exposed to one of 14 genotoxic or 14 non-genotoxic agents, with sampling 4 h post-exposure. Microarray-based transcriptomic analyses were then used to develop a classifier for genotoxicity using the nearest shrunken centroids method. A panel of 65 genes was identified that could accurately classify toxicants as genotoxic or non-genotoxic. In Buick et al. (2015) [1], the utility of the biomarker for chemicals that require metabolic activation was evaluated. In this study, TK6 cells were exposed to increasing doses of four chemicals (two genotoxic that require metabolic activation and two non-genotoxic chemicals) in the presence of rat liver S9 to demonstrate that S9 does not impair the ability to classify genotoxicity using this genomic biomarker in TK6cells.
Insights
This study developed a gene expression classifier to accurately identify genotoxic chemicals. The genomic biomarker effectively classified toxicants, even those requiring metabolic activation.
Area of Science:
- Toxicology
- Genetics
- Molecular Biology
Background:
- Genotoxicity testing is crucial for chemical safety assessment.
- Integrated approaches using gene expression data are increasingly used to understand DNA damage response pathways.
- Previous work established a dose optimization protocol using quantitative real-time PCR in TK6 cells.
Purpose of the Study:
- To develop and validate a gene expression-based classifier for genotoxicity assessment.
- To evaluate the utility of this genomic biomarker for chemicals requiring metabolic activation.
- To confirm the reliability of the classifier in the presence of rat liver S9 fraction.
Main Methods:
- Quantitative real-time PCR for stress-response gene expression analysis.
- Microarray-based transcriptomic analysis to identify a gene panel.
- Nearest shrunken centroids method for classifier development.
- Exposure of TK6 cells to genotoxic and non-genotoxic agents, with and without S9 fraction.
Main Results:
- A panel of 65 genes was identified that accurately classifies toxicants.
- The genomic biomarker successfully classified genotoxicity in TK6 cells.
- Rat liver S9 fraction did not impair the classification of genotoxicity.
Conclusions:
- A robust gene expression classifier for genotoxicity testing has been developed.
- This approach is effective for a wide range of chemicals, including those needing metabolic activation.
- The findings support the use of integrated genomic approaches in chemical safety evaluation.
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