Stress Response and Toxicogenomics

Cells have evolved complex molecular networks, which enable them to respond to diverse environmental stresses and challenges. A variety of adverse stimuli, both genotoxic (i.e. DNA-damaging) and non-genotoxic in nature, can trigger complex transcriptional responses. Toxicogenomics seeks to exploit transcriptomics to define gene expression signatures for various types of drugs and toxicants, and to provide mechanistic insight into their cellular effects.

The development of in vitro molecular biomarkers to accurately predict toxicological effects has become a priority to advance testing strategies for human health risk assessment. Genotoxicity testing is an essential component of the safety assessment paradigm required by regulatory agencies worldwide. The current standard genotoxicity-testing battery features high incidence of positive findings for in vitro chromosome damage assays and to a lesser extent for other genotoxicity assays. The risk management of compounds with positive in vitro findings is a major challenge and requires complicated, time consuming and costly follow-up strategies including animal testing. Taking advantage of a modern toxicogenomics approach we have constructed a reference database containing global gene expression profiles of model agents with a broad range of known toxic mechanisms and identified a transcriptomic biomarker using a machine learning algorithm, the nearest shrunken centroids method. This transcriptomic biomarker, TGx-DDI (previously known as TGx-28.65), readily distinguishes DNA damage-inducing (DDI) agents from non-DDI agents. We have developed a standardized experimental and analytical protocol for our transcriptomics biomarker, and an enhancement of the application of TGx-DDI for high-throughput cell-based genotoxicity testing. The strategies and methods that are used in TGx-DDI identification and its validation can serve as a prototype for developing genomic biomarkers for other types of toxicity.