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Hepatocyte-like cells derived from the differentiation of human embryonic stem cells (hES-Hep) have potential to provide a human relevant in vitro test system in which to evaluate the carcinogenic hazard of chemicals. In this study, we have investigated this potential using a panel of 15 chemicals classified as noncarcinogens, genotoxic carcinogens, and nongenotoxic carcinogens and measured whole-genome transcriptome responses with gene expression microarrays. We applied an ANOVA model that identified 592 genes highly discriminative for the panel of chemicals. Supervised classification with these genes achieved a cross-validation accuracy of > 95%. Moreover, the expression of the response genes in hES-Hep was strongly correlated with that in human primary hepatocytes cultured in vitro. In order to infer mechanistic information on the consequences of chemical exposure in hES-Hep, we developed a computational method that measures the responses of biochemical pathways to the panel of treatments and showed that these responses were discriminative for the three toxicity classes and linked to carcinogenesis through p53, mitogen-activated protein kinases, and apoptosis pathway modules. It could further be shown that the discrimination of toxicity classes was improved when analyzing the microarray data at the pathway level. In summary, our results demonstrate, for the first time, the potential of human embryonic stem cell--derived hepatic cells as an in vitro model for hazard assessment of chemical carcinogenesis, although it should be noted that more compounds are needed to test the robustness of the assay.

The murine embryonic stem cell test (EST) is an alternative testing method designed to assess potential developmental toxicity of compounds. The implementation of transcriptomics in the EST has been shown to reduce the culture duration and improve endpoint evaluation and is expected to result in an enhanced predictability and definition of the applicability domain. We evaluated the identification of developmental toxicity in the EST using two gene sets (‘‘Van_Dartel_heartdiff_24h’’ and ‘‘EST biomarker genes’’) defined in our earlier studies. Nonexposed embryonic stem cells (ESC) differentiation cultures were sampled 0, 24, and 48 h after initiation of differentiation. Additionally, cultures exposed to 12 diverse well-characterized positive and negative developmental toxicants were isolated 24 h after the onset of exposure. Inhibition of ESC differentiation was evaluated in parallel by morphological scoring on culture day 10. Transcriptomics analysis was conducted using the Affymetrix Gene Chips platform. We applied principal component analysis on the basis of the two predefined gene sets to define the ‘‘differentiation track’’ that represents ESC differentiation. The significance of derivations in the gene expression‐based differentiation track because of compound exposures were evaluated to determine developmental toxicity of tested compounds. We successfully predicted developmental toxicity using transcriptomics for 83% (10/12) and 67% (8/12) of the compounds, respectively, using the two predefined gene sets (‘‘Van_Dartel_heartdiff_24h’’ and ‘‘EST biomarker genes’’). Our study suggests that the application of transcriptomics may improve the applicability of the EST for the prediction of the developmental toxicity of chemicals.

Unexpected hepatotoxicity is one of the major reasons of drugs failing in clinical trials. This emphasizes the need for new screening methods that address toxicological hazards early in the drug discovery process. Here, proteomics techniques were used to gain further insight into the mechanistic processes of the hepatotoxic compounds. Drug-induced hepatotoxicity is mainly divided in hepatic steatosis, cholestasis, or necrosis. For each class, a compound was selected, respectively amiodarone, cyclosporin A, and acetaminophen. The changes in protein expressions in HepG2, after exposure to these test compounds, were studied using quantitative two-dimensional differential gel electrophoresis. Identification of differentially expressed proteins was performed by Maldi-TOF/TOF MS and liquid chromatography-tandem mass spectrometry. In this study, 254 differentially expressed protein spots were detected in a two-dimensional proteome map from which 86 were identified, showing that the proteome of HepG2 cells is responsive to hepatotoxic compounds. cyclosporin A treatment was responsible for most differentially expressed proteins and could be discriminated in the hierarchical clustering analysis. The identified differential proteins show that cyclosporin A may induce endoplasmic reticulum (ER) stress and disturbs the ER-Golgi transport, with an altered vesicle-mediated transport and protein secretion as result. Moreover, the differential protein pattern seen after cyclosporin A treatment can be related to cholestatic mechanisms. Therefore, our findings indicate that the HepG2 in vitro cell system has distinctive characteristics enabling the assessment of cholestatic properties of novel compounds at an early stage of drug discovery. Netherlands Genomics Initiative/Netherlands Organisation for Scientific Research (NWO), (050-060-510).

Investigating the immunotoxic effects of exposure to chemicals usually comprises evaluation of weight and histopathology of lymphoid tissues, various lymphocyte parameters in the circulation, and immune function. Immunotoxicity assessment is time consuming in humans or requires a high number of animals, making it expensive. Furthermore, reducing the use of animals in research is an important ethical and political issue. Immunotoxicogenomics represents a novel approach to investigate immunotoxicity able of overcoming these limitations. The current research, embedded in the European Union project NewGeneris, aimed to retrieve gene expression profiles that are indicative of exposure to immunotoxicants. To this end, whole-genome gene expression was investigated in human peripheral blood mononuclear cells in response to in vitro exposure to a range of immunotoxic chemicals (4-hydroxy-2-nonenal, aflatoxin B1, benzo[a]pyrene, deoxynivalenol, ethanol, malondialdehyde, polychlorinated biphenyl 153, and 2,3,7,8-tetrachlorodibenzo-p-dioxin) and nonimmunotoxic chemicals (acrylamide, dimethylnitrosamine, 2-amino-3-methyl-3H-imidazo[4,5-F]quinoline, and 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine). Using Agilent oligonucleotide microarrays, whole-genome gene expression profiles were generated, which were analyzed using Genedata's Expressionist software. Using Recursive Feature Elimination and Support Vector Machine, a set of 48 genes was identified that distinguishes the immunotoxic from the nonimmunotoxic compounds. Analysis for enrichment of biological processes showed the gene set to be highly biologically and immunologically relevant. We conclude that we have identified a promising transcriptomic profile indicative of immunotoxic exposure.

Assessing the potential carcinogenicity of chemicals for humans represents an ongoing challenge. Chronic rodent bioassays predict human cancer risk at only limited reliability and are simultaneously expensive and long lasting. In order to seek for alternatives, the ability of a transcriptomics-based primary mouse hepatocyte model to classify carcinogens by their modes of action was evaluated. As it is obvious that exposure will induce a cascade of gene expression modifications, in particular, the influence of exposure time in vitro on discriminating genotoxic (GTX) carcinogens from nongenotoxic (NGTX) carcinogens class discrimination was investigated. Primary mouse hepatocytes from male C57Bl6 mice were treated for 12, 24, 36, and 48 h with two GTX and two NGTX carcinogens. For validation, two additional GTX compounds were studied at 24 and 48 h. Immunostaining of gammaH2AX foci was applied in order to phenotypically verify DNA damage. It confirmed significant induction of DNA damage after treatment with GTX compounds but not with NGTX compounds. Whole-genome gene expression modifications were analyzed by means of Affymetrix microarrays. When using differentially expressed genes from data sets normalized by Robust Multi-array Average, the two classes and various compounds were better separated from each other by hierarchical clustering when increasing the treatment period. Discrimination of GTX and NGTX carcinogens by Prediction Analysis of Microarray improved with time and resulted in correct classification of the validation compounds. The present study shows that gene expression profiling in primary mouse hepatocytes is promising for discriminating GTX from NGTX compounds and that this discrimination improves with increasing treatment period.

Whole-genome transcriptome measurements are pivotal for characterizing molecular mechanisms of chemicals and predicting toxic classes, such as genotoxicity and carcinogenicity, from in vitro and in vivo assays. In recent years, deep sequencing technologies have been developed that hold the promise of measuring the transcriptome in a more complete and unbiased manner than DNA microarrays. Here, we applied this RNA-seq technology for the characterization of the transcriptomic responses in HepG2 cells upon exposure to benzo[a]pyrene (BaP), a well-known DNA damaging human carcinogen. Based on EnsEMBL genes, we demonstrate that RNA-seq detects ca 20% more genes than microarray-based technology but almost threefold more significantly differentially expressed genes. Functional enrichment analyses show that RNA-seq yields more insight into the biology and mechanisms related to the toxic effects caused by BaP, i.e., two- to fivefold more affected pathways and biological processes. Additionally, we demonstrate that RNA-seq allows detecting alternative isoform expression in many genes, including regulators of cell death and DNA repair such as TP53, BCL2 and XPA, which are relevant for genotoxic responses. Moreover, potentially novel isoforms were found, such as fragments of known transcripts, transcripts with additional exons, intron retention or exon-skipping events. The biological function(s) of these isoforms remain for the time being unknown. Finally, we demonstrate that RNA-seq enables the investigation of allele-specific gene expression, although no changes could be observed. Our results provide evidence that RNA-seq is a powerful tool for toxicology, which, compared with microarrays, is capable of generating novel and valuable information at the transcriptome level for characterizing deleterious effects caused by chemicals.