Acetaminophen-induced gene expression profiles in sandwich-cultured primary human hepatocytes
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE13430 | GEO | 2009/01/01
SECONDARY ACCESSION(S): PRJNA110013
REPOSITORIES: GEO
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Project description: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. Conclusion: 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. Gene expression profiles of sandwich-cutlured primary rat hepatocytes exposed to 5 mM and 10 mM acetaminophen were used in a parallelogram approach in order to compare gene expression responses between rat and human using in vitro cellular models, heaptocytes, and between rat in vitro and in vivo Keywords: Toxicogenomics, dose response
2009-01-01 | GSE13465 | GEO
Project description:To improve prediction accuracy of read-across, we compared biological similarities between triclosan and its structurally similar chemicals including diclosan and 1-chloro-3-(4-chlorophenoxy) benzene. To elucidate and compare the potential mechanisms between them, we performed in vitro toxicogenomics with rat primary hepatocytes.
2022-11-01 | GSE186659 | GEO
Project description:The Toxicogenomics Project was a 5-year collaborative project (2002-2007) by a consortium comprising the Japanese government and several pharmaceutical companies. The project produced the 'Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system' (TG-GATEs), a large-scale database of transcriptomics and pathology data potentially useful for predicting the toxicity of new chemical entities. Conventional in vivo toxicology data was collected from single dose and repeat dosing studies on rats, and gene expression measured for the liver (and kidney in some cases). To provide information on species differences, gene expression was also measured in rat and human hepatocytes treated with the chemicals in vitro. Approximately 130 chemicals, primarily medicinal compounds, were tested at multipe doses. Gene expression was analysed using Affymetrix GeneChip arrays. The gene expression data has been submitted in four parts: in vivo single dose (E-MTAB-799), in vivo repeat dosing (E-MTAB-800), in vitro rat (E-MTAB-797) and in vitro human. This submission comprises the in vitro human studies. If publishing results based on this data, please cite the full project name 'Toxicogenomics Project and Toxicogenomics Informatics Project', the database name 'Open TG-GATEs' and the URL 'http://toxico.nibio.go.jp'. Please note that the European Bioinformatics Institute (EBI) was not involved in the Toxicogenomics Project in any way, acting only to submit the transcriptomics data to Array Express. Queries about the project can be addressed to the consortium directly via 'opentggates@nibio.go.jp'.
2012-02-10 | E-MTAB-798 | biostudies-arrayexpress
Project description:The Toxicogenomics Project was a 5-year collaborative project (2002-2007) by a consortium comprising the Japanese government and several pharmaceutical companies. The project produced the 'Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system' (TG-GATEs), a large-scale database of transcriptomics and pathology data potentially useful for predicting the toxicity of new chemical entities. Conventional in vivo toxicology data was collected from single dose and repeat dosing studies on rats, and gene expression measured for the liver (and kidney in some cases). To provide information on species differences, gene expression was also measured in rat and human hepatocytes treated with the chemicals in vitro. Approximately 130 chemicals, primarily medicinal compounds, were tested at multipe doses. Gene expression was analysed using Affymetrix GeneChip arrays. The gene expression data has been submitted in four parts: in vivo single dose (E-MTAB-799), in vivo repeat dosing, in vitro rat (E-MTAB-797) and in vitro human (E-MTAB-798). This submission comprises the in vivo, repeat dosing studies. If publishing results based on this data, please cite the full project name 'Toxicogenomics Project and Toxicogenomics Informatics Project', the database name 'Open TG-GATEs' and the URL 'http://toxico.nibio.go.jp'. Please note that the European Bioinformatics Institute (EBI) was not involved in the Toxicogenomics Project in any way, acting only to submit the transcriptomics data to Array Express. Queries about the project can be addressed to the consortium directly via 'opentggates@nibio.go.jp'. This dataset is part of the TransQST collection.
2012-02-10 | E-MTAB-800 | biostudies-arrayexpress
Project description:The Toxicogenomics Project was a 5-year collaborative project (2002-2007) by a consortium comprising the Japanese government and several pharmaceutical companies. The project produced the 'Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system' (TG-GATEs), a large-scale database of transcriptomics and pathology data potentially useful for predicting the toxicity of new chemical entities. Conventional in vivo toxicology data was collected from single dose and repeat dosing studies on rats, and gene expression measured for the liver (and kidney in some cases). To provide information on species differences, gene expression was also measured in rat and human hepatocytes treated with the chemicals in vitro. Approximately 130 chemicals, primarily medicinal compounds, were tested at multipe doses. Gene expression was analysed using Affymetrix GeneChip arrays. The gene expression data has been submitted in four parts: in vivo single dose (E-MTAB-799), in vivo repeat dosing, in vitro rat (E-MTAB-797) and in vitro human (E-MTAB-798). This submission comprises the in vivo, repeat dosing studies. If publishing results based on this data, please cite the full project name 'Toxicogenomics Project and Toxicogenomics Informatics Project', the database name 'Open TG-GATEs' and the URL 'http://toxico.nibio.go.jp'. Please note that the European Bioinformatics Institute (EBI) was not involved in the Toxicogenomics Project in any way, acting only to submit the transcriptomics data to Array Express. Queries about the project can be addressed to the consortium directly via 'opentggates@nibio.go.jp'.
2012-02-10 | E-MTAB-797 | biostudies-arrayexpress
Project description:The Toxicogenomics Project was a 5-year collaborative project (2002-2007) by a consortium comprising the Japanese government and several pharmaceutical companies. The project produced the 'Toxicogenomics Project-Genomics Assisted Toxicity Evaluation system' (TG-GATEs), a large-scale database of transcriptomics and pathology data potentially useful for predicting the toxicity of new chemical entities. Conventional in vivo toxicology data was collected from single dose and repeat dosing studies on rats, and gene expression measured for the liver (and kidney in some cases). To provide information on species differences, gene expression was also measured in rat and human hepatocytes treated with the chemicals in vitro. Approximately 130 chemicals, primarily medicinal compounds, were tested at multipe doses. Gene expression was analysed using Affymetrix GeneChip arrays. The gene expression data has been submitted in four parts: in vivo single dose (E-MTAB-799), in vivo repeat dosing, in vitro rat (E-MTAB-797) and in vitro human (E-MTAB-798). This submission comprises the in vivo, repeat dosing studies. If publishing results based on this data, please cite the full project name 'Toxicogenomics Project and Toxicogenomics Informatics Project', the database name 'Open TG-GATEs' and the URL 'http://toxico.nibio.go.jp'. Please note that the European Bioinformatics Institute (EBI) was not involved in the Toxicogenomics Project in any way, acting only to submit the transcriptomics data to Array Express. Queries about the project can be addressed to the consortium directly via 'opentggates@nibio.go.jp'. This dataset is part of the TransQST collection.
2012-02-10 | E-MTAB-799 | biostudies-arrayexpress
Project description:Transcriptomics is developing into an invaluable tool in toxicology. The aim of this study was, using a transcriptomics approach, to identify genes that respond similarly to chemicals (including drugs and industrial compounds) in both rat liver in vivo and in cultivated hepatocytes, which are up- or downregulated by many different test compounds. For this purpose, we analyzed Affymetrix gene array data from 162 compounds that were previously tested in a concentration-dependent manner in rat livers in vivo and rat hepatocytes cultivated in sandwich culture. These data were obtained from the Japanese Toxicogenomics (TGP) and North-Rhine-Westphalian (NRW) data sets, which consist of 138 and 29 compounds, respectively, and have 5 mutual compounds between them. The in vitro gene array data from the NRW data set were generated in the present study, while TGP is publicly available. For each of the data sets, the overlap between up- or down-regulated genes in vitro and in vivo was identified, further named in vitro-in vivo consensus genes. Interestingly, an overlap of in vivo-in vitro consensus genes was obtained between both data sets, which were 21-times (up-regulated genes) or 12-times (down-regulated genes) en-riched compared to random expectation. This is remarkable since the TGP and NRW data sets contained only five mutual compounds. Finally, the genes in the TGP and NRW overlap were used to identify the upregulated genes with the highest com-pound coverage, resulting in a 7-gene set of Cyp1a1, Ugt2b1, Cdkn1a, Mdm2, Aldh1a1, Cyp4a3, and Ehhad. This 7-gene set was then successfully tested with structural analogues of valproic acid that are not present in the TGP and NRW data sets. In conclusion, the 7-gene set identified in the present study responds similarly in vitro and in vivo and is induced by a wide range of different chemicals. Despite these results, transcriptomics with cultivated rat hepatocytes remains a challenge, because many genes are up- or downregulated by the culture conditions, respond differently to test compounds in vitro and in vivo, and shows a higher variability in the in vitro system compared to the corresponding in vivo data. The raw data for the TGP study are available at https://toxico.nibiohn.go.jp/ For the normalization of the entire set of expression arrays, the RMA algorithm was used. The results are summarized in the publicly available toxicotranscriptomics directory (http://wiki.toxbank.net/toxicogenomics-map/).
2018-09-14 | GSE119933 | GEO
Project description:Toxicogenomics directory of rat hepatotoxicants in vivo and in cultivated hepatocytes
| PRJNA490737 | ENA
Project description:The effect of drugs, disease and other perturbations on mRNA levels are studied using gene expression microarrays or RNA-seq, with the goal of understanding molecular effects arising from the perturbation. Previous comparisons of reproducibility across laboratories have been limited in scale and focused on a single model. The use of model systems, such as cultured primary cells or cancer cell lines, assumes that mechanistic insights derived with would have been observed via in vivo studies. We examined the concordance of compound-induced transcriptional changes using data from several sources: rat liver and rat primary hepatocytes (RPH) from Drug Matrix (DM) and open TG-GATEs (TG), primary human hepatocytes (HPH) from TG, and mouse liver / HepG2 results from the Gene Expression Omnibus (GEO) repository. Gene expression changes for treatments were normalized to controls and analyzed with three methods: 1) gene level for 9071 high expression genes in rat liver, 2) gene set analysis (GSA) using canonical pathways and gene ontology sets, 3) weighted gene co-expression network analysis (WGCNA). Co-expression networks performed better than genes or GSA on a quantitative metric when comparing treatment effects within rat liver and rat vs. mouse liver. Genes and modules performed similarly at Connectivity Map-style analyses, where success at identifying similar treatments among a collection of reference profiles is the goal. Comparisons between rat liver and RPH, and those between RPH, HPH and HepG2 cells reveal low concordance for all methods. We investigate differences in the baseline state of cultured cells in the context of drug-induced perturbations in rat liver and highlight the striking similarity between toxicant-exposed cells in vivo and untreated cells in vitro. Gene expression studies in model systems are widely used for understanding the mechanism of drugs and other perturbations in biological systems. Other researchers have examined the reproducibility of microarray studies between laboratories, or comparing microarrays and/or RNA sequencing. However, no large scale studies have compared results from protocols which differ in minor details, or results generated in vivo vs. in vitro culture system thought to serve as useful models. The rat liver is by far the most extensively studied model evaluating effects of drugs and other perturbations, and existing data allowed us to assess the level of concordance between rat liver and rat primary hepatocytes cultured in collagen-coated plates (i.e. âflatâ culture) for hundreds of drugs. We found that the mouse liver serves as a better model of the rat liver than do rat primary hepatocytes, even after allowing for differences due to pharmacokinetics. The low concordance observed between rat liver and rat hepatocytes suggests that validating the utility of âomics data generated on emerging cell culture approaches (e.g. âorgan-on-a-chipâ, 3D-printed tissues) using rat cells and comparison to the rat liver may be necessary in order to gain confidence these approaches substantially improve on traditional culture models of human cells. To identify transcriptional changes in culture, rat primary hepatocytes (RPH) were isolated from three male Sprague Dawley rats. During the isolation and prior to perfusion, a lobe of liver was tied off to serve as the liver in situ reference sample. Cells were isolated and samples from the cell pellet (time zero) and cells cultured for 4, 24 and 48 hours. Three biological replicates were generated for each group (one from each rat). Each biological replicate was analyzed via 3 technical replicates, for a total of 9 array hybridizations per group.
2015-11-12 | E-GEOD-74903 | biostudies-arrayexpress
Project description:The effect of drugs, disease and other perturbations on mRNA levels are studied using gene expression microarrays or RNA-seq, with the goal of understanding molecular effects arising from the perturbation. Previous comparisons of reproducibility across laboratories have been limited in scale and focused on a single model. The use of model systems, such as cultured primary cells or cancer cell lines, assumes that mechanistic insights derived with would have been observed via in vivo studies. We examined the concordance of compound-induced transcriptional changes using data from several sources: rat liver and rat primary hepatocytes (RPH) from Drug Matrix (DM) and open TG-GATEs (TG), primary human hepatocytes (HPH) from TG, and mouse liver / HepG2 results from the Gene Expression Omnibus (GEO) repository. Gene expression changes for treatments were normalized to controls and analyzed with three methods: 1) gene level for 9071 high expression genes in rat liver, 2) gene set analysis (GSA) using canonical pathways and gene ontology sets, 3) weighted gene co-expression network analysis (WGCNA). Co-expression networks performed better than genes or GSA on a quantitative metric when comparing treatment effects within rat liver and rat vs. mouse liver. Genes and modules performed similarly at Connectivity Map-style analyses, where success at identifying similar treatments among a collection of reference profiles is the goal. Comparisons between rat liver and RPH, and those between RPH, HPH and HepG2 cells reveal low concordance for all methods. We investigate differences in the baseline state of cultured cells in the context of drug-induced perturbations in rat liver and highlight the striking similarity between toxicant-exposed cells in vivo and untreated cells in vitro. Gene expression studies in model systems are widely used for understanding the mechanism of drugs and other perturbations in biological systems. Other researchers have examined the reproducibility of microarray studies between laboratories, or comparing microarrays and/or RNA sequencing. However, no large scale studies have compared results from protocols which differ in minor details, or results generated in vivo vs. in vitro culture system thought to serve as useful models. The rat liver is by far the most extensively studied model evaluating effects of drugs and other perturbations, and existing data allowed us to assess the level of concordance between rat liver and rat primary hepatocytes cultured in collagen-coated plates (i.e. “flat” culture) for hundreds of drugs. We found that the mouse liver serves as a better model of the rat liver than do rat primary hepatocytes, even after allowing for differences due to pharmacokinetics. The low concordance observed between rat liver and rat hepatocytes suggests that validating the utility of ‘omics data generated on emerging cell culture approaches (e.g. “organ-on-a-chip”, 3D-printed tissues) using rat cells and comparison to the rat liver may be necessary in order to gain confidence these approaches substantially improve on traditional culture models of human cells.
2015-11-12 | GSE74903 | GEO