Quantitative proteomic analysis of rat liver for carcinogenicity prediction in a 28-day repeated dose study

The potential of quantitative proteomic analysis to predict carcinogenicity of chemical compounds was investigated. Using 2D-DIGE, we analyzed the effects of 63 chemical compounds on protein expression in the rat liver after 28 daily doses. Types of carcinogens were categorized depending on the species and organ specificity. The carcinogen characteristic proteins for each classification were identified by Welch's t value. For evaluation of the predictive concordance we used support vector machines. The rat hepatic carcinogen-specific classification gave higher concordance than the other classification. The generalization performance was measured by leave-one-out cross-validation. For genotoxic and non-genotoxic compounds, a concordance of 79.3 and 76.5%, respectively, was obtained by the top 30 ranked proteins with Welch's t value. Furthermore, we found that the increase of the expression level of the stress response proteins as the common feature of poorly predicted chemical compounds in the leave-20%-out cross-validation. Quantitative proteomics could be promising technique for developing biomarker panels that can be used for carcinogenicity prediction. The list of proteins identified in this study and the zoomed gel images of the top ranked proteins in statistic analysis are provided in Supplementary Data.