Classification of cholestatic and necrotic hepatotoxicants using transcriptomics on human precision-cut liver slices

Human toxicity screening is an important stage in the development of safe drug candidates. Hepatotoxicity is one of the major reasons for withdrawal of drugs from the market because the liver is the major organ involved in drug metabolism and it can generate toxic metabolites. There is a need to screen molecules for drug-induced hepatotoxicity in humans at an earlier stage. Transcriptomics is a technique widely used to screen molecules for toxicity and to unravel toxicity mechanisms. To date the majority of such studies were performed using animals or animal cells, with concomitant difficulty in interpretation due to species differences, or in human hepatoma cell lines or cultured hepatocytes, suffering from the lack of physiological expression of enzymes and transporters and lack of non-parenchymal cells. The aim of this study was to classify known hepatotoxicants on their phenotype of toxicity in man using gene expression profiles ex vivo in human precision-cut liver slices (PCLS). Hepatotoxicants known to induce either necrosis (n=5) or cholestasis (n=5) were used at concentrations inducing low (<30%) and medium (30-50%) cytotoxicity, based on ATP content. Random Forest and Support Vector Machine algorithms were used to classify hepatotoxicants using a leave-one-compound-out cross-validation method. Optimized biomarkers sets were compared to derive a consensus list of markers. Classification correctly predicted the toxicity phenotype with an accuracy of 70-80%. The classification is slightly better for the low than for the medium cytotoxicity. The consensus list of markers includes endoplasmic reticulum stress genes such as C2ORF30, DNAJB9, DNAJC12, SRP72, TMED7 and UBA5, and a bile acid transporter (SLC10A7). This study shows that human PCLS are a useful model to predict the phenotype of drug-induced hepatotoxicity. Additional compounds should be included to confirm the consensus list of markers, which could then be used to develop a biomarker PCR-array for hepatotoxicity screening.