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The liver plays an important role in xenobiotic metabolism and represents a primary target for toxic substances. Many different in vitro cell models have been developed in the past decades. In this study, we used RNA-sequencing (RNA-Seq) to analyze the following human in vitro liver cell models in comparison to human liver tissue: cancer-derived cell lines (HepG2, HepaRG 3D), induced pluripotent stem cell-derived hepatocyte-like cells (iPSC-HLCs), cancerous human liver-derived assays (hPCLiS, human precision cut liver slices), non-cancerous human liver-derived assays (PHH, primary human hepatocytes) and 3D liver microtissues. First, using CellNet, we analyzed whether these liver in vitro cell models were indeed classified as liver, based on their baseline expression profile and gene regulatory networks (GRN). More comprehensive analyses using non-differentially expressed genes (non-DEGs) and differential transcript usage (DTU) were applied to assess the coverage for important liver pathways. Through different analyses, we noticed that 3D liver microtissues exhibited a high similarity with in vivo liver, in terms of CellNet (C/T score: 0.98), non-DEGs (10,363) and pathway coverage (highest for 19 out of 20 liver specific pathways shown) at the beginning of the incubation period (0 h) followed by a decrease during long-term incubation for 168 and 336 h. PHH also showed a high degree of similarity with human liver tissue and allowed stable conditions for a short-term cultivation period of 24 h. Using the same metrics, HepG2 cells illustrated the lowest similarity (C/T: 0.51, non-DEGs: 5623, and pathways coverage: least for 7 out of 20) with human liver tissue. The HepG2 are widely used in hepatotoxicity studies, however, due to their lower similarity, they should be used with caution. HepaRG models, iPSC-HLCs, and hPCLiS ranged clearly behind microtissues and PHH but showed higher similarity to human liver tissue than HepG2 cells. In conclusion, this study offers a resource of RNA-Seq data of several biological replicates of human liver cell models in vitro compared to human liver tissue.

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.

Benzo(a)pyrene (BaP) is a ubiquitous carcinogen resulting from incomplete combustion of organic compounds and also present at high levels in cigarette smoke. A wide range of biological effects has been attributed to BaP and its genotoxic metabolite BPDE, but the contribution to BaP toxicity of intermediary metabolites generated along the detoxification path remains unknown. Here, we report for the first time how 3-OH–BaP, 9,10-diol and BPDE, three major BaP metabolites, temporally relate to BaP-induced transcriptomic alterations in HepG2 cells. Since BaP is also known to induce AhR activation, we additionally evaluated TCDD to source the expression of non-genotoxic AhR-mediated patterns. 9,10-Diol was shown to activate several transcription factor networks related to BaP metabolism (AhR), oxidative stress (Nrf2) and cell proliferation (HIF-1α, AP-1) in particular at early time points, while BPDE influenced expression of genes involved in cell energetics, DNA repair and apoptotic pathways. Also, in order to grasp the role of BaP and its metabolites in chemical hepatocarcinogenesis, we compared expression patterns from BaP(-metabolites) and TCDD to a signature set of approximately nine thousand gene expressions derived from hepatocellular carcinoma (HCC) patients. While transcriptome modulation by TCDD appeared not significantly related to HCC, BaP and BPDE were shown to deregulate metastatic markers via non-genotoxic and genotoxic mechanisms and activate inflammatory pathways (NF-κβ signaling, cytokine–cytokine receptor interaction). BaP also showed strong repression of genes involved in cholesterol and fatty acid biosynthesis. Altogether, this study provides new insights into BaP-induced toxicity and sheds new light onto its mechanism of action as a hepatocarcinogen.Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-015-1572-z) contains supplementary material, which is available to authorized users.

The frequent use of rodent hepatic in vitro systems in pharmacological and toxicological investigations challenges extrapolation of in vitro results to the situation in vivo and interspecies extrapolation from rodents to humans. The toxicogenomics approach may aid in evaluating relevance of these model systems for human risk assessment by direct comparison of toxicant-induced gene expression profiles and infers mechanisms between several systems. In the present study, acetaminophen (APAP) was used as a model compound to compare gene expression responses between rat and human using in vitro cellular models, hepatocytes, and between rat in vitro and in vivo. Comparison at the level of modulated biochemical pathways and biological processes rather than at that of individual genes appears preferable as it increases the overlap between various systems. Pathway analysis by T-profiler revealed similar biochemical pathways and biological processes repressed in rat and human hepatocytes in vitro, as well as in rat liver in vitro and in vivo. Repressed pathways comprised energy-consuming biochemical pathways, mitochondrial function, and oxidoreductase activity. The present study is the first that used a toxicogenomics-based parallelogram approach, extrapolating in vitro to in vivo and interspecies, to reveal relevant mechanisms indicative of APAP-induced liver toxicity in humans in vivo.