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A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design validation and optimization for histone deacetylase inhibitors

机译:基于转录组的分类器可通过干细胞测试鉴定发育毒性:组蛋白脱乙酰基酶抑制剂的设计验证和优化

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摘要

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 materialThe online version of this article (doi:10.1007/s00204-015-1573-y) contains supplementary material, which is available to authorized users.
机译:迫切需要测试系统来识别发育性毒物。人类干细胞技术和转录组分析的结合提供了一种概念证明,即可以识别具有相关作用方式的毒物并进行交叉阅读。我们选择了发育毒性测试系统,该系统与多能干细胞(UKN1)产生神经外胚层有关,并将细胞暴露于组蛋白脱乙酰基酶抑制剂(HDACi)丙戊酸,曲古抑素A,伏立诺他,贝利诺司他,泛obinostat和entinostat 。为了深入了解其毒性作用,我们鉴定了HDACi共有基因,将其分配给上级生物学过程,并将其映射到由数百个转录组数据集构建的人类转录因子网络中。我们还测试了一组异构的“汞”(甲基汞,硫柳汞,氯化汞(II),溴化汞(II),4-氯汞苯甲酸,苯基汞)。在所有12种有毒物质的最高非细胞毒性浓度下对微阵列数据进行了比较。基于支持向量机(SVM)的分类器可正确预测所有HDACi。为了进行验证,将分类器应用于HDACi的旧数据集,对于每种暴露情况,SVM预测与发育毒性相关。最后,基于100个探针集的分类器优化表明,八个基因(F2RL2,TFAP2B,EDNRA,FOXD3,SIX3,MT1E,ETS1和LHX2)足以将HDACi与汞分离。我们的数据证明了如何将人类干细胞和转录组分析结合起来用于机理分组和毒物预测。将这一概念扩展到HDACi以外的机制将可以使用UKN1测试系统预测未知化合物对人类发育的危害。电子补充材料本文的在线版本(doi:10.1007 / s00204-015-1573-y)包含补充材料,可供授权用户使用。

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