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The toxic mechanisms of cisplatin have been frequently studied in many species and in vitro cell models. The Netherlands Toxicogenomics Centre focuses on developing in vitro alternatives using genomics technologies for animal-based assays on, e.g. genotoxic hazards. Models such as human hepatocellular carcinoma cell line (HepG2) cells, mouse primary hepatocytes (PMH) and mouse embryonic stem cells (mESC) are used. Our aim was to identify possibly robust conserved mechanisms between these models using cisplatin as model genotoxic agent. Transcriptomic data newly generated from HepG2 cells and PMH exposed to 7 µM cisplatin for 12, 24 and 48h and 24 and 48h, respectively, were compared with published data from mESC exposed to 5 µM cisplatin for 2-24h. Due to differences in response time between models and marginal changes after shorter exposure periods, we focused on 24 and 48h. At gene level, 44 conserved differentially expressed genes (DEG), involved in processes such as apoptosis, cell cycle, DNA damage response and DNA repair, were found. Functional analysis shows that limited numbers of pathways are conserved. Transcription factor (TF) network analysis indicates 12 common TF networks responding among all models and time points. Four TF, HNF4-α, SP1, c-MYC and p53, capable of regulating ±50% of all DEG, seem of equal importance in all models and exposure periods. Here we showed that transcriptomic responses across several in vitro cell models following exposure to cisplatin are mainly determined by a conserved complex network of 4 TFs. These conserved responses are hypothesised to provide most relevant information for human toxicity prediction and may form the basis for new in vitro alternatives of risk assessment.

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 designed to evaluate developmental toxicity based on compound-induced inhibition of embryonic stem cell (ESC) differentiation into cardiomyocytes. The addition of transcriptomic evaluation within the EST may result in enhanced predictability and improved characterization of the applicability domain, therefore improving usage of the EST for regulatory testing strategies. Transcriptomic analyses assessing factors critical for risk assessment (i.e. dose) are needed to determine the value of transcriptomic evaluation in the EST. Here, using the developmentally toxic compound, flusilazole, we investigated the effect of compound concentration on gene expression regulation and toxicity prediction in ESC differentiation cultures. Cultures were exposed for 24 h to multiple concentrations of flusilazole (0.54-54 μM) and RNA was isolated. In addition, we sampled control cultures 0, 24, and 48 h to evaluate the transcriptomic status of the cultures across differentiation. Transcriptomic profiling identified a higher sensitivity of development-related processes as compared to cell division-related processes in flusilazole-exposed differentiation cultures. Furthermore, the sterol synthesis-related mode of action of flusilazole toxicity was detected. Principal component analysis using gene sets related to normal ESC differentiation was used to describe the dynamics of ESC differentiation, defined as the 'differentiation track'. The concentration-dependent effects on development were reflected in the significance of deviation of flusilazole-exposed cultures from this transcriptomic-based differentiation track. Thus, the detection of developmental toxicity in EST using transcriptomics was shown to be compound concentration-dependent. This study provides further insight into the possible application of transcriptomics in the EST as an improved alternative model system for developmental toxicity testing., (Copyright © 2010 Elsevier Inc. All rights reserved.)

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.

The embryonic stem cell test (EST) has been designed to predict developmental toxicity based upon compound-induced inhibition of embryonic stem cell (ESC) differentiation. The end point scoring, the test duration, and the definition of the predictivity and the applicability domain require improvements to facilitate implementation of the EST into regulatory testing strategies. The use of transcriptomics to study compound-induced differentiation modulation may improve the EST in each of these aspects. ESC differentiation was induced, and cell samples were collected after 0, 24, and 48 h of differentiation. Additionally, samples were collected that were 24 h exposed to one of five developmentally toxic compounds or a nondevelopmentally toxic compound. All samples were hybridized to Affymetrix GeneChips, and analyses revealed that 26 genes were significantly regulated both during ESC differentiation and by exposure to each of the developmentally toxic compounds tested. Using principal component analysis, we defined a "differentiation track" on the basis of this gene list, which represents ESC differentiation. We showed that significant deviation from the differentiation track was in line with the developmental toxic properties of the compounds. The significance of deviation was analyzed using the leave-one-out cross-validation, which showed a favorable prediction of toxicity in the system. Our findings show that gene expression signatures can be used to identify developmental toxicant-induced differentiation modulation. In addition, studying compound-induced effects at an early stage of differentiation combined with transcriptomics leads to increased objectivity in determining differentiation inhibition and to a reduction of the test duration. Furthermore, this approach may improve the predictivity and applicability domain of the EST.

As the conventional approach to assess the potential of a chemical to cause cancer in humans still includes the 2-year rodent carcinogenicity bioassay, development of alternative methodologies is needed. In the present study, the transcriptomics responses following exposure to genotoxic (GTX) and non-genotoxic (NGTX) hepatocarcinogens and non-carcinogens (NC) in five liver-based in vitro models, namely conventional and epigenetically stabilized cultures of primary rat hepatocytes, the human hepatoma-derived cell lines HepaRG and HepG2 and human embryonic stem cell-derived hepatocyte-like cells, are examined. For full characterization of the systems, several bioinformatics approaches are employed including gene-based, ConsensusPathDB-based and classification analysis. They provide convincingly similar outcomes, namely that upon exposure to carcinogens, the HepaRG generates a gene classifier (a gene classifier is defined as a selected set of characteristic gene signatures capable of distinguishing GTX, NGTX carcinogens and NC) able to discriminate the GTX carcinogens from the NGTX carcinogens and NC. The other in vitro models also yield cancer-relevant characteristic gene groups for the GTX exposure, but some genes are also deregulated by the NGTX carcinogens and NC. Irrespective of the tested in vitro model, the most uniformly expressed pathways following GTX exposure are the p53 and those that are subsequently induced. The NGTX carcinogens triggered no characteristic cancer-relevant gene profiles in all liver-based in vitro systems. In conclusion, liver-based in vitro models coupled with transcriptomics techniques, especially in the case when the HepaRG cell line is used, represent valuable tools for obtaining insight into the mechanism of action and identification of GTX carcinogens. [ABSTRACT FROM PUBLISHER]