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A predictive toxicogenomics signature to classify genotoxic versus non-genotoxic chemicals in human TK6 cells.

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.

SUBMITTER: Williams A

PROVIDER: S-EPMC4564388 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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A predictive toxicogenomics signature to classify genotoxic versus non-genotoxic chemicals in human TK6 cells.

Williams Andrew A Buick Julie K JK Moffat Ivy I Swartz Carol D CD Recio Leslie L Hyduke Daniel R DR Li Heng-Hong HH Fornace Albert J AJ Aubrecht Jiri J Yauk Carole L CL

Data in brief 20150824

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- ...[more]

PMID: 26425668

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Project description:The use of integrated approaches in genetic toxicology, including the incorporation of gene expression data to determine the molecular pathways involved in the response, is becoming more common. In a companion paper, a genomic biomarker was developed in human TK6 cells to classify chemicals as genotoxic or non-genotoxic. Because TK6 cells are not metabolically competent, we set out to broaden the utility of the biomarker for use with chemicals requiring metabolic activation. Specifically, chemical exposures were conducted in the presence of rat liver S9. The ability of the biomarker to classify genotoxic (benzo[a]pyrene, BaP; aflatoxin B1, AFB1) and non-genotoxic (dexamethasone, DEX; phenobarbital, PB) agents correctly was evaluated. Cells were exposed to increasing chemical concentrations for 4h and collected 0h, 4h and 20h post-exposure. Relative survival, apoptosis, and micronucleus frequency were measured at 24h. Transcriptome profiles were measured with Agilent microarrays. Statistical modeling and bioinformatics tools were applied to classify each chemical using the genomic biomarker. BaP and AFB1 were correctly classified as genotoxic at the mid- and high concentrations at all three time points, whereas DEX was correctly classified as non-genotoxic at all concentrations and time points. The high concentration of PB was misclassified at 24h, suggesting that cytotoxicity at later time points may cause misclassification. The data suggest that the use of S9 does not impair the ability of the biomarker to classify genotoxicity in TK6 cells. Finally, we demonstrate that the biomarker is also able to accurately classify genotoxicity using a publicly available dataset derived from human HepaRG cells. This experiment examined the whole genome transcriptional response of TK6 cells exposed to DMSO (+S9) and 10 μg/ml BaP (-S9) (both compared to DMSO (-S9)) for 4 hours followed by a 20h in fresh media (24h time point), in addition to 7.5 mM dexamethasone (+S9) (compared to DMSO (+S9)). Each condition had 3 biological replicates, which were pooled for gene expression analysis. There were a total 3 samples (6 arrays) included in the final analysis using a two-colour dye swap design.

Dataset Information

A predictive toxicogenomics signature to classify genotoxic versus non-genotoxic chemicals in human TK6 cells.

Publications

A predictive toxicogenomics signature to classify genotoxic versus non-genotoxic chemicals in human TK6 cells.

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