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A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors
Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was to provide a proof of concept that toxicants with a related mode of action can be identified and grouped for read-across. We chose a test system of develop...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4551554/ https://www.ncbi.nlm.nih.gov/pubmed/26272509 http://dx.doi.org/10.1007/s00204-015-1573-y |
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author | Rempel, Eugen Hoelting, Lisa Waldmann, Tanja Balmer, Nina V. Schildknecht, Stefan Grinberg, Marianna Das Gaspar, John Antony Shinde, Vaibhav Stöber, Regina Marchan, Rosemarie van Thriel, Christoph Liebing, Julia Meisig, Johannes Blüthgen, Nils Sachinidis, Agapios Rahnenführer, Jörg Hengstler, Jan G. Leist, Marcel |
author_facet | Rempel, Eugen Hoelting, Lisa Waldmann, Tanja Balmer, Nina V. Schildknecht, Stefan Grinberg, Marianna Das Gaspar, John Antony Shinde, Vaibhav Stöber, Regina Marchan, Rosemarie van Thriel, Christoph Liebing, Julia Meisig, Johannes Blüthgen, Nils Sachinidis, Agapios Rahnenführer, Jörg Hengstler, Jan G. Leist, Marcel |
author_sort | Rempel, Eugen |
collection | PubMed |
description | Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was to provide a proof of concept that toxicants with a related mode of action can be identified and grouped for read-across. We chose a test system of developmental toxicity, related to the generation of neuroectoderm from pluripotent stem cells (UKN1), and exposed cells for 6 days to the histone deacetylase inhibitors (HDACi) valproic acid, trichostatin A, vorinostat, belinostat, panobinostat and entinostat. To provide insight into their toxic action, we identified HDACi consensus genes, assigned them to superordinate biological processes and mapped them to a human transcription factor network constructed from hundreds of transcriptome data sets. We also tested a heterogeneous group of ‘mercurials’ (methylmercury, thimerosal, mercury(II)chloride, mercury(II)bromide, 4-chloromercuribenzoic acid, phenylmercuric acid). Microarray data were compared at the highest non-cytotoxic concentration for all 12 toxicants. A support vector machine (SVM)-based classifier predicted all HDACi correctly. For validation, the classifier was applied to legacy data sets of HDACi, and for each exposure situation, the SVM predictions correlated with the developmental toxicity. Finally, optimization of the classifier based on 100 probe sets showed that eight genes (F2RL2, TFAP2B, EDNRA, FOXD3, SIX3, MT1E, ETS1 and LHX2) are sufficient to separate HDACi from mercurials. Our data demonstrate how human stem cells and transcriptome analysis can be combined for mechanistic grouping and prediction of toxicants. Extension of this concept to mechanisms beyond HDACi would allow prediction of human developmental toxicity hazard of unknown compounds with the UKN1 test system. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00204-015-1573-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4551554 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-45515542015-09-01 A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors Rempel, Eugen Hoelting, Lisa Waldmann, Tanja Balmer, Nina V. Schildknecht, Stefan Grinberg, Marianna Das Gaspar, John Antony Shinde, Vaibhav Stöber, Regina Marchan, Rosemarie van Thriel, Christoph Liebing, Julia Meisig, Johannes Blüthgen, Nils Sachinidis, Agapios Rahnenführer, Jörg Hengstler, Jan G. Leist, Marcel Arch Toxicol In Vitro Systems Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was to provide a proof of concept that toxicants with a related mode of action can be identified and grouped for read-across. We chose a test system of developmental toxicity, related to the generation of neuroectoderm from pluripotent stem cells (UKN1), and exposed cells for 6 days to the histone deacetylase inhibitors (HDACi) valproic acid, trichostatin A, vorinostat, belinostat, panobinostat and entinostat. To provide insight into their toxic action, we identified HDACi consensus genes, assigned them to superordinate biological processes and mapped them to a human transcription factor network constructed from hundreds of transcriptome data sets. We also tested a heterogeneous group of ‘mercurials’ (methylmercury, thimerosal, mercury(II)chloride, mercury(II)bromide, 4-chloromercuribenzoic acid, phenylmercuric acid). Microarray data were compared at the highest non-cytotoxic concentration for all 12 toxicants. A support vector machine (SVM)-based classifier predicted all HDACi correctly. For validation, the classifier was applied to legacy data sets of HDACi, and for each exposure situation, the SVM predictions correlated with the developmental toxicity. Finally, optimization of the classifier based on 100 probe sets showed that eight genes (F2RL2, TFAP2B, EDNRA, FOXD3, SIX3, MT1E, ETS1 and LHX2) are sufficient to separate HDACi from mercurials. Our data demonstrate how human stem cells and transcriptome analysis can be combined for mechanistic grouping and prediction of toxicants. Extension of this concept to mechanisms beyond HDACi would allow prediction of human developmental toxicity hazard of unknown compounds with the UKN1 test system. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00204-015-1573-y) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2015-08-14 2015 /pmc/articles/PMC4551554/ /pubmed/26272509 http://dx.doi.org/10.1007/s00204-015-1573-y Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | In Vitro Systems Rempel, Eugen Hoelting, Lisa Waldmann, Tanja Balmer, Nina V. Schildknecht, Stefan Grinberg, Marianna Das Gaspar, John Antony Shinde, Vaibhav Stöber, Regina Marchan, Rosemarie van Thriel, Christoph Liebing, Julia Meisig, Johannes Blüthgen, Nils Sachinidis, Agapios Rahnenführer, Jörg Hengstler, Jan G. Leist, Marcel A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors |
title | A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors |
title_full | A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors |
title_fullStr | A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors |
title_full_unstemmed | A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors |
title_short | A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors |
title_sort | transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors |
topic | In Vitro Systems |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4551554/ https://www.ncbi.nlm.nih.gov/pubmed/26272509 http://dx.doi.org/10.1007/s00204-015-1573-y |
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