Identification of classifier genes for hepatotoxicity prediction in non steroidal anti inflammatory drugs

Abstract

Toxicogenomics has the potential to be used for the regulatory decision making to predict toxicity in developing new drugs. We have identified the classifiers for hepatotoxicity prediction in nonsteroidal anti inflammatory drugs (NSAIDs) through analyzing differential gene expression profiles of hepatotoxic and nonhepatotoxic compounds using HepG2 cell. 100 μM of 8 hepatotoxic and 8 nonhepatotoxic NSAIDs were treated to HepG2 cell and the analysis of gene expression changes after 24 h allowed a set of genes to be identified differentiating hepatotoxicants from nonhepatotoxicants by statistical method. The hepatotoxicity prediction model was built using the selected 77 genes. These genes and pathways, commonly regulated by hepatotoxicants, may be indicative of the early characterization of hepatotoxicity and possibly predictive of later hepatotoxicity onset. 4 test compounds including hepatotoxic and nonhepatotoxic NSAIDs were used for validating the prediction model and the accuracy was 100%. Given that the specificity and sensitivity showed 100%, these are the most precise classifiers identified until now.