Utilization of a one-dimensional score for surveying chemical-induced changes in expression levels of multiple biomarker gene sets using a large-scale toxicogenomics database.

A large-scale toxicogenomcis database has now been constructed in the Toxicogenomics Project in Japan (TGP). To facilitate the analytical procedures for such large-scale microarray data, we developed a simple one-dimensional score, named TGP1 which expresses the trend of the changes in expression of biomarker genes as a whole. To evaluate the usefulness of the TGP1 score, microarray data of rat liver and rat hepatocytes deposited in the TGP database were scored for three biomarker gene sets, i.e., carcinogenesis-related, PPARalpha-regulated and glutathione depletion-related gene sets. The TGP1 scoring system gave reasonable results, i.e., the scores for carcinogenesis-related genes were high in omeprazole-, chlorpromazine-, hexachlorobenzene-, sulfasalazine- and Wy-14,643-treated rat livers, that for PPARalpha-regulated genes were high in clofibrate-, Wy-14,643-, gemfibrozil-, benzbromarone- and aspirin-treated rat livers as well as rat hepatocytes, and for glutathione deficiency-related genes were high in omeprazole-, bromobenzene-, acetaminophen- and coumarin-treated rat liver. We concluded that the TGP1 score is useful for surveying the expression changes in multiple biomarker gene sets for a large-scale toxicogenomics database, which would reduce the time of doing conventional multivariate statistical analysis. In addition, the TGP1 score can be applied to screening of compatible biomarker gene sets between rat liver and rat hepatocytes, like PPARalpha-regulated gene sets, which will allow us to develop an appropriate in vitro system for drug safety assessment in vivo.