Suchergebnisse

One of the main challenges of toxicology is the accurate prediction of compound carcinogenicity. The default test model for assessing chemical carcinogenicity, the 2 year rodent cancer bioassay, is currently criticized because of its limited specificity. With increased societal attention and new legislation against animal testing, toxicologists urgently need an alternative to the current rodent bioassays for chemical cancer risk assessment. Toxicogenomics approaches propose to use global high-throughput technologies (transcriptomics, proteomics and metabolomics) to study the toxic effect of compounds on a biological system. Here, we demonstrate the improvement of transcriptomics assay consisting of primary human hepatocytes to predict the putative liver carcinogenicity of several compounds by applying the connectivity map methodology. Our analyses underline that connectivity mapping is useful for predicting compound carcinogenicity by connecting in vivo expression profiles from human cancer tissue samples with in vitro toxicogenomics data sets. Furthermore, the importance of time and dose effect on carcinogenicity prediction is demonstrated, showing best prediction for low dose and 24 h exposure of potential carcinogens.