A novel genotoxin-specific qPCR array based on the metabolically competent human HepaRG™ cell line as a rapid and reliable tool for improved in vitro hazard assessment
Ates, Gamze ; ; Heymans, Anja ; Verschaeve, Luc ; Milushev, Dimiter ; Vanparys, Philippe ; ; ; Rogiers, Vera ; Doktorova, Tatyana Y.
Citations
Abstract
Although the value of the regulatory accepted batteries for in vitro genotoxicity testing is recognized, they result in a high
;number of false positives. This has a major impact on society and industries developing novel compounds for pharmaceutical,
;chemical, and consumer products, as afflicted compounds have to be (prematurely) abandoned or further tested on
;animals. Using the metabolically competent human HepaRG
;™ cell line and toxicogenomics approaches, we have developed
;an upgraded, innovative, and proprietary gene classifier. This gene classifier is based on transcriptomic changes induced by
;12 genotoxic and 12 non-genotoxic reference compounds tested at sub-cytotoxic concentrations, i.e., IC10 concentrations
;as determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. The resulting gene classifier
;was translated into an easy-to-handle qPCR array that, as shown by pathway analysis, covers several different cellular
;processes related to genotoxicity. To further assess the predictivity of the tool, a set of 5 known positive and 5 known negative
;test compounds for genotoxicity was evaluated. In addition, 2 compounds with debatable genotoxicity data were tested
;to explore how the qPCR array would classify these. With an accuracy of 100%, when equivocal results were considered
;positive, the results showed that combining HepaRG
;™ cells with a genotoxin-specific qPCR array can improve (geno)toxicological
;hazard assessment. In addition, the developed qPCR array was able to provide additional information on compounds
;for which so far debatable genotoxicity data are available. The results indicate that the new in vitro tool can improve human
;safety assessment of chemicals in general by basing predictions on mechanistic toxicogenomics information.
