A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo.

The lack of accurate in vitro assays for predicting in vivo toxicity of chemicals together with new legislations demanding replacement and reduction of animal testing has triggered the development of alternative methods. This study aimed at developing a transcriptomics-based in vitro prediction assay for in vivo genotoxicity. Transcriptomics changes induced in the human liver cell line HepG2 by 34 compounds after treatment for 12, 24, and 48 h were used for the selection of gene-sets that are capable of discriminating between in vivo genotoxins (GTX) and in vivo nongenotoxins (NGTX). By combining transcriptomics with publicly available results for these chemicals from standard in vitro genotoxicity studies, we developed several prediction models. These models were validated by using an additional set of 28 chemicals. The best prediction was achieved after stratification of chemicals according to results from the Ames bacterial gene mutation assay prior to transcriptomics evaluation after 24h of treatment. A total of 33 genes were selected for discriminating GTX from NGTX for Ames-positive chemicals and 22 for Ames-negative chemicals. Overall, this method resulted in 89% accuracy and 91% specificity, thereby clearly outperforming the standard in vitro test battery. Transcription factor network analysis revealed HNF3a, HNF4a, HNF6, androgen receptor, and SP1 as main factors regulating the expression of classifiers for Ames-positive chemicals. Thus, the classical bacterial gene mutation assay in combination with in vitro transcriptomics in HepG2 is proposed as an upgraded in vitro approach for predicting in vivo genotoxicity of chemicals holding a great promise for reducing animal experimentations on genotoxicity.

Comparison of phenotypic and transcriptomic effects of false-positive genotoxins, true genotoxins and non-genotoxins using HepG2 cells.

The conventional in vitro assays for genotoxicity assessment of chemicals are characterised by a high false-positive rate, thus failing to correctly predict their in vivo genotoxic effects. This study aimed to identify the cellular mechanisms induced by the false-positive genotoxins quercetin, 8-Hydroxyquinoline and 17-beta oestradiol in comparison to true genotoxins and non-genotoxins, by combining in vitro phenotypic parameters with transcriptomics data from HepG2 cells. The effects of these compounds on the phosphorylation of H2AX, cell cycle distribution and whole genome gene expression following treatment for 12, 24 and 48 h were compared with the effects of true genotoxins [benzo[a]pyrene and aflatoxin B1] and non-genotoxins (2,3,7,8-tetrachlorodibenzodioxin, cyclosporin A and ampicillin C). Quercetin induced similar phenotypic effects as true genotoxins and to some extent similar gene expression alterations. Different gene expression changes were also observed, including the up-regulation of DNA repair-related genes. 8-Hydroxyquinoline and 17-beta oestradiol showed no similarities to the true genotoxins at both the phenotypic and the transcriptomic level. In a classification approach, classifiers were selected to discriminate between genotoxins and non-genotoxins. Subsequent analysis for the false-positive compounds showed quercetin to be predicted as genotoxic and 8-hydroxyquinoline and 17-beta oestradiol as non-genotoxic. Our results support that transcriptomics analysis of compound effects in HepG2 leads to similar results with phenotypic analysis and provides additional mechanistic information. Therefore, combined evaluation of gene expression alterations and relevant functional end points using HepG2 cells may contribute to the better understanding of modes-of-action of chemicals and the correct evaluation of their genotoxic properties.