Laboratory for Health Protection Research (GBO), National Institute for Public Health and the Environment, (RIVM), Bilthoven, The Netherlands.
Toxicology. 2012 Oct 28;300(3):158-67. doi: 10.1016/j.tox.2012.06.016. Epub 2012 Jul 1.
The murine neural embryonic stem cell test (ESTn) is an in vitro model for neurodevelopmental toxicity testing. Recent studies have shown that application of transcriptomics analyses in the ESTn is useful for obtaining more accurate predictions as well as mechanistic insights. Gene expression responses due to stem cell neural differentiation versus toxicant exposure could be distinguished using the Principal Component Analysis based differentiation track algorithm. In this study, we performed a de novo analysis on combined raw data (10 compounds, 19 exposures) from three previous transcriptomics studies to identify an optimized gene set for neurodevelopmental toxicity prediction in the ESTn. By evaluating predictions of 200,000 randomly selected gene sets, we identified genes which significantly contributed to the prediction reliability. A set of 100 genes was obtained, predominantly involved in (neural) development. Further stringency restrictions resulted in a set of 29 genes that allowed for 84% prediction accuracy (area under the curve 94%). We anticipate these gene sets will contribute to further improve ESTn transcriptomics studies aimed at compound risk assessment.
鼠神经胚胎干细胞测试（ESTn）是一种用于神经发育毒性测试的体外模型。最近的研究表明，在 ESTn 中应用转录组学分析对于获得更准确的预测和机制见解非常有用。使用基于主成分分析的分化轨迹算法可以区分干细胞神经分化与有毒物质暴露引起的基因表达反应。在这项研究中，我们对来自三个先前转录组学研究的综合原始数据（10 种化合物，19 种暴露）进行了从头分析，以确定 ESTn 中用于神经发育毒性预测的优化基因集。通过评估 20 万个随机选择的基因集的预测，我们确定了对预测可靠性有重要贡献的基因。获得了一组 100 个主要涉及（神经）发育的基因。进一步的严格限制导致获得了一组 29 个基因，其预测准确率达到 84%（曲线下面积为 94%）。我们预计这些基因集将有助于进一步改进旨在评估化合物风险的 ESTn 转录组学研究。
