Validation of gene expression profiles from cholestatic hepatotoxicants in vitro against human in vivo cholestasis.

Drug-induced liver injury remains the most common cause of acute liver failure and a frequently indicated reason for withdrawal of drugs. For the purpose of evaluating the relevance of liver cell models for assessing hepatotoxic risks in intact humans, we here aimed to benchmark 'omics-derived mechanistic data from three in vitro models for parenchymal liver function, intended for the investigation of drug-induced cholestasis, against 'omics data from cholestatic patients. Transcriptomic changes in HepG2 cells, primary mouse hepatocytes and primary human hepatocytes exposed to known cholestatic compounds were analyzed using microarrays. Some of the differentially expressed genes in HepG2 cells were also differentially expressed into the same direction in human cholestasis. The overlap between drug-induced transcriptomic responses in primary mouse hepatocytes and primary human hepatocytes appeared limited and no genes overlapping with in vivo cholestasis were found. Thereupon, a pathway for drug-induced cholestasis was used to map the drug-induced transcriptomic modifications involved in bile salt homeostasis. Indications of an adaptive response to prevent and reduce intracellular bile salt accumulation were observed in vivo as well as in the in vitro liver models. Furthermore, drug-specific changes were found, which may be indicative for their cholestatic properties. Furthermore, connectivity mapping was applied in order to investigate the predictive value of the in vitro models for in vivo cholestasis. This analysis resulted in a positive connection score for most compounds, which may indicate that for identifying cholestatic compounds the focus should be on gene expression signatures rather than on differentially expressed genes.

Integrative "-Omics" Analysis in Primary Human Hepatocytes Unravels Persistent Mechanisms of Cyclosporine A-Induced Cholestasis.

Cyclosporine A (CsA) is an undecapeptide with strong immunosuppressant activities and is used a lot after organ transplantation. Furthermore, it may induce cholestasis in the liver. In general, the drug-induced cholestasis (DIC) pathway includes genes involved in the uptake, synthesis, conjugation, and secretion of bile acids. However, whether CsA-induced changes in the cholestasis pathway in vitro are persistent for repeated dose toxicity has not yet been investigated. To explore this, primary human hepatocytes (PHH) were exposed to a subcytotoxic dose of 30 µM CsA daily for 3 and 5 days. To investigate the persistence of induced changes upon terminating CsA exposure after 5 days, a subset of PHH was subjected to a washout period (WO-period) of 3 days. Multiple -omics analyses, comprising whole genome analysis of DNA methylation, gene expression, and microRNA expression, were performed. The CsA-treatment resulted after 3 and 5 days, respectively, in 476 and 20 differentially methylated genes (DMGs), 1353 and 1481 differentially expressed genes (DEGs), and in 22 and 29 differentially expressed microRNAs (DE-miRs). Cholestasis-related pathways appeared induced during CsA-treatment. Interestingly, 828 persistent DEGs and 6 persistent DE-miRs but no persistent DMGs were found after the WO-period. These persistent DEGs and DE-miRs showed concordance for 22 genes. Furthermore, 29 persistent DEGs changed into the same direction as observed in livers from cholestasis patients. None of those 29 DEGs which among others relate to oxidative stress and lipid metabolism are yet present in the DIC pathway or cholestasis adverse outcome pathway (AOP) thus presenting novel findings. In summary, we have demonstrated for the first time a persistent impact of repeated dose administration of CsA on genes and microRNAs related to DIC in the gold standard human liver in vitro model with PHH.

Integrating multiple omics to unravel mechanisms of Cyclosporin A induced hepatotoxicity in vitro.

In order to improve attrition rates of candidate-drugs there is a need for a better understanding of the mechanisms underlying drug-induced hepatotoxicity. We aim to further unravel the toxicological response of hepatocytes to a prototypical cholestatic compound by integrating transcriptomic and metabonomic profiling of HepG2 cells exposed to Cyclosporin A. Cyclosporin A exposure induced intracellular cholesterol accumulation and diminished intracellular bile acid levels. Performing pathway analyses of significant mRNAs and metabolites separately and integrated, resulted in more relevant pathways for the latter. Integrated analyses showed pathways involved in cell cycle and cellular metabolism to be significantly changed. Moreover, pathways involved in protein processing of the endoplasmic reticulum, bile acid biosynthesis and cholesterol metabolism were significantly affected. Our findings indicate that an integrated approach combining metabonomics and transcriptomics data derived from representative in vitro models, with bioinformatics can improve our understanding of the mechanisms of action underlying drug-induced hepatotoxicity. Furthermore, we showed that integrating multiple omics and thereby analyzing genes, microRNAs and metabolites of the opposed model for drug-induced cholestasis can give valuable information about mechanisms of drug-induced cholestasis in vitro and therefore could be used in toxicity screening of new drug candidates at an early stage of drug discovery.

Integrative cross-omics analysis in primary mouse hepatocytes unravels mechanisms of cyclosporin A-induced hepatotoxicity.

The liver is responsible for drug metabolism and drug-induced hepatotoxicity is the most frequent reason for drug withdrawal, indicating that better pre-clinical toxicity tests are needed. In order to bypass animal models for toxicity screening, we exposed primary mouse hepatocytes for exploring the prototypical hepatotoxicant cyclosporin A. To elucidate the mechanisms underlying cyclosporin A-induced hepatotoxicity, we analyzed expression levels of proteins, mRNAs, microRNAs and metabolites. Integrative analysis of transcriptomics and proteomics showed that protein disulfide isomerase family A, member 4 was up-regulated on both the protein level and mRNA level. This protein is involved in protein folding and secretion in the endoplasmic reticulum. Furthermore, the microRNA mmu-miR-182-5p which is predicted to interact with the mRNA of this protein, was also differentially expressed, further emphasizing endoplasmic reticulum stress as important event in drug-induced toxicity. To further investigate the interaction between the significantly expressed proteins, a network was created including genes and microRNAs known to interact with these proteins and this network was used to visualize the experimental data. In total 6 clusters could be distinguished which appeared to be involved in several toxicity related processes, including alteration of protein folding and secretion in the endoplasmic reticulum. Metabonomic analyses resulted in 5 differentially expressed metabolites, indicative of an altered glucose, lipid and cholesterol homeostasis which can be related to cholestasis. Single and integrative analyses of transcriptomics, proteomics and metabonomics reveal mechanisms underlying cyclosporin A-induced cholestasis demonstrating that endoplasmic reticulum stress and the unfolded protein response are important processes in drug-induced liver toxicity.

Classification of hepatotoxicants using HepG2 cells: A proof of principle study.

With the number of new drug candidates increasing every year, there is a need for high-throughput human toxicity screenings. As the liver is the most important organ in drug metabolism and thus capable of generating relatively high levels of toxic metabolites, it is important to find a reliable strategy to screen for drug-induced hepatotoxicity. Microarray-based transcriptomics is a well-established technique in toxicogenomics research and is an ideal approach to screen for drug-induced injury at an early stage. The aim of this study was to prove the principle of classifying known hepatotoxicants and nonhepatotoxicants using their distinctive gene expression profiles in vitro in HepG2 cells. Furthermore, we undertook to subclassify the hepatotoxic compounds by investigating the subclass of cholestatic compounds. Prediction analysis for microarrays was used for classification of hepatotoxicants and nonhepatotoxicants, which resulted in an accuracy of 92% on the training set and 91% on the validation set, using 36 genes. A second model was set up with the goal of finding classifiers for cholestasis, resulting in 12 genes that appeared capable of correctly classifying 8 of the 9 cholestatic compounds, resulting in an accuracy of 93%. We were able to prove the principle that transcriptomic analyses of HepG2 cells can indeed be used to classify chemical entities for hepatotoxicity. Genes selected for classification of hepatotoxicity and cholestasis indicate that endoplasmic reticulum stress and the unfolded protein response may be important cellular effects of drug-induced liver injury. However, the number of compounds in both the training set and the validation set should be increased to improve the reliability of the prediction.