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Evaluation of the robustness of classification of carcinogen-modified transcriptomic responses in HepaRG cells and the interlaboratory reproducibility of the model

ABSTRACT: Efforts to develop alternatives which can at least partially replace some of the currently used in vivo tests are ongoing. The recently ended FP6 European project carcinoGENOMICS had the goal to use the combination of toxicogenomics and in vitro cell culture models for identification of genotoxic- and non-genotoxic carcinogen-specific gene signatures. In this study is presented a part of the outcome of the project and in particular the performance of the gene classifier derived after exposure of the HepaRG cell line to prototypical hepatocarcinogens. Upon analyzing the data at a gene and a pathway level by using diverse biostatistical approaches, a clear-cut separation of the genotoxic from the non-genotoxic hepatocarcinogens and non-carcinogens was achieved (up to 88% correct prediction). The most characteristic pathway for genotoxic exposure was DNA damage. Further to show the robustness of the HepaRG model, the interlaboratory reproducibility of 3 blindly tested compounds was assessed. The results showed between 20% and 35% reproducibility. The subsequent classification of the 3 blindly tested compounds resulted in correct prediction of the genotoxicant, whereas the other two compounds were misclassified. In conclusion, the combination of transcriptomics and HepaRG in vitro cell model provides a solid basis for the detection of the genotoxic potential of unknown chemicals.

ORGANISM(S): Homo sapiens

PROVIDER: GSE48990 | GEO | 2014/09/01

SECONDARY ACCESSION(S): PRJNA221339

REPOSITORIES: GEO

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Project description:Efforts to develop alternatives which can at least partially replace some of the currently used in vivo tests are ongoing. The recently ended FP6 European project carcinoGENOMICS had the goal to use the combination of toxicogenomics and in vitro cell culture models for identification of genotoxic- and non-genotoxic carcinogen-specific gene signatures. In this study is presented a part of the outcome of the project and in particular the performance of the gene classifier derived after exposure of the HepaRG cell line to prototypical hepatocarcinogens. Upon analyzing the data at a gene and a pathway level by using diverse biostatistical approaches, a clear-cut separation of the genotoxic from the non-genotoxic hepatocarcinogens and non-carcinogens was achieved (up to 88% correct prediction). The most characteristic pathway for genotoxic exposure was DNA damage. Further to show the robustness of the HepaRG model, the interlaboratory reproducibility of 3 blindly tested compounds was assessed. The results showed between 20% and 35% reproducibility. The subsequent classification of the 3 blindly tested compounds resulted in correct prediction of the genotoxicant, whereas the other two compounds were misclassified. In conclusion, the combination of transcriptomics and HepaRG in vitro cell model provides a solid basis for the detection of the genotoxic potential of unknown chemicals. HepaRG cells were exposed to 15 selected compounds for 72 hours, i.e. 5 GTX (N-nitrosomorpholine, NMP; Hydroquinone, HQO; Hydrazine dihydrochloride, HHC; 2-acetylaminofluorene, TAF; 2-amino-3-methylimidazo(4,5-f)quinoline, AMQ), 5 NGTX (Fumonisin B1, FMB; Cyclosporine A, CsA; Acetamide, ACE; Diethylhexyl Phthalate, DHP; Ethanol, ETH), 5 NC (4-acetylaminofluorene, FAF; D,L-Menthol, DLM; Benzoin, BEN; Benzyl Alcohol, BEA; Triclosan, TRI). The IC10 concentrations (reducing cell viability by 10%) were determined by a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide test (MTT test) (number of replicates n=3). Further RNA samples were generated by exposure of the HepaRG cells to the MTT-determined IC10 for a period of 24h and 72h. Complementary RNA targets were prepared and hybridized according to the manufacturer's procedures on high-density oligonucleotide microarrays (i.e. Affymetrix U133 Plus 2.0 GeneChip). Finally,alaysis was performed at a gene and pathway level. In the analysis, control (DMSO) samples were re-normalized with several sample groups and new processed data were created for each analysis. Thus, some of the Samples in this Series represent a re-analysis of other Samples and CEL files are identical.

Project description:Liver tumors in rodents are frequently induced by non-genotoxic carcinogens. These hepatocarcinogens generally activate hepatic nuclear receptors (e.g., CAR and PXR), resulting in a cascade of signals causing modifications in the expression of genes responsible for several processes involved in carcinogenesis. Evaluation of the carcinogenic potential of chemicals is a regulatory requirement but is time-consuming and expensive. Consequently, several short-term in vivo and in vitro approaches, using molecular tools, have been proposed as predictive models for non-genotoxic hepatocarcinogens. The objective of our study was to discriminate between chemicals that are either non-genotoxic hepatocarcinogens or merely hepatotoxicants and also between CAR and PXR modulators on the basis of their gene expression profiles. Thus, we treated rats for seven days with the hepatoxicants, diclofenac and diazepam, or with several CAR and PXR modulators, which were mainly hepatocarcinogens. Different hepatic gene expression profiles were obtained not only between the hepatotoxicants and the non-genotoxic hepatocarcinogens but also between the CAR activators phenobarbital, phenytoin and 1,1-bis-(4-chlorophenyl)-2,2-dichloroethene which were grouped together, and the two PXR activators pregnenolone 16Î±-carbonitrile and clotrimazole. Diethylstilbestrol had an expression profile that was quite distinct from the other PXR activators, suggesting that this compound is certainly not a classic PXR modulator. Moreover, some differences were observed between phenytoin (not considered as a hepatocarcinogen), and the other two CAR activators. Our data therefore indicate that discrimination is possible between hepatocarcinogens and hepatotoxicants, between CAR and PXR modulators and also between compounds within the same class of modulators using a short-term transcriptomic approach. CAR or PXR inducers were administered in suspension to rats (7 weeks old at start of treatment) by oral gavage at a daily dose for 7 consecutive days. Treatment-related changes in gene expression were determined in the liver using whole genome oligonucleotide microarrays.

Project description:For assessing the cancer-causing potential for humans of a chemical compound, the conventional approach is the use of the 2-year rodent carcinogenicity bioassay, thus alternatives such as in vitro toxicogenomics are highly desired. 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 HepaRG and HepG2 cell lines and the human embryonic stem cell-derived hepatocyte-like cells hES-Heps are examined and compared. The global gene expression profiles of five commonly used liver-based in vitro systems are investigated, namely conventional cultures of primary rat hepatocytes (HepsC), Trichostatin A (TSA)-stabilized cultures of primary rat hepatocytes (HepsT), human embryonic stem cell-derived hepatocyte-like cells (hES-Hep), HepG2 and HepaRG cells. These models are exposed to 15 prototypical compounds which have been carefully chosen and belong to 3 toxic classes i.e. (i) genotoxic (GTX) (aflatoxin B1, AFB1; 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, NNK; 2-nitrofluorene, 2NF; benzo(a)pyrene, BaP; cyclophosphamide, CYCLO), (ii) non-genotoxic (NGTX) (methapyrilene hydrochloride, MPH; piperonylbutoxide , PIPB; Wy-14643, WYE; phenobarbital sodium, SPB; 12-O-tetradecanoylphorbol-13-acetate, TPA) carcinogens and (iii) non-carcinogens (NC) (nifedipine, NIF; clonidine, CND; D-mannitol, MAN; tolbutamide, TOL; diclofenac sodium, SDF). For the gene- and pathway- based analysis, the raw microarray data was re-annotated to Ensembl version 61 genome and Gene Chip Robust Multi-array Average (GC-RMA) normalized (Dai et al. 2005). This resulted in 11,187 and 18,919 probe sets for the rat and the human models, respectively. For the classification analysis, the raw microarray data was annotated using the chip description files from Affymetrix and then GC-RMA normalized. In order to eliminate batch effects, data from the different studies were half-z normalized. Half-z-normalization adjusts the logarithmic expression values of transcripts within a group such that each transcript has zero mean.

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Evaluation of the robustness of classification of carcinogen-modified transcriptomic responses in HepaRG cells and the interlaboratory reproducibility of the model

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