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用于胚胎干细胞试验中定量预测发育毒性的基因集组装。

Gene set assembly for quantitative prediction of developmental toxicity in the embryonic stem cell test.

机构信息

Laboratory for Health Protection Research, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.

出版信息

Toxicology. 2011 Jun 18;284(1-3):63-71. doi: 10.1016/j.tox.2011.03.017. Epub 2011 Apr 5.

DOI:10.1016/j.tox.2011.03.017
PMID:21473898
Abstract

The embryonic stem cell test (EST) is an in vitro method for predicting developmental toxicity based on compound-induced inhibition of embryonic stem cell (ESC) differentiation. We previously described how gene expression analysis in the EST can be used to describe normal ESC differentiation as well as identify compound developmental toxicity, by means of our differentiation track algorithm. In this study, we combined raw data from our three previous studies in a new integrated analysis, to identify a gene set that allows for improved prediction. By evaluating predictions of 100,000 randomly selected gene sets, we identified which genes contribute significantly to the prediction reliability. By additional cross-validation, we identified a set of 52 genes that allows for improved prediction of toxicity. The correlation between the predictions using this gene set and the magnitude of the EST endpoint was 0.85, and the gene set predicted developmental toxicity with 83% accuracy (area under the curve 89%). If compounds with ineffective data because of a too low tested concentration or too much variation between samples were excluded, even 100% accuracy could be reached based on 15 compounds. This novel gene set consists mainly of genes involved in the stem cell differentiation or other developmental processes. We expect that this set can be of use in future studies aimed at improving the EST for risk assessment, thus making a next step towards regulatory implementation of this method.

摘要

胚胎干细胞测试(EST)是一种基于化合物诱导胚胎干细胞(ESC)分化抑制的体外方法,用于预测发育毒性。我们之前描述了如何通过我们的分化跟踪算法,利用 EST 中的基因表达分析来描述正常 ESC 分化,并识别化合物的发育毒性。在这项研究中,我们将之前三项研究的原始数据结合起来进行了新的综合分析,以确定一组能够提高预测准确性的基因。通过评估 10 万个随机选择的基因集的预测,我们确定了哪些基因对预测可靠性有显著贡献。通过进一步的交叉验证,我们确定了一组 52 个基因,可用于提高毒性预测的准确性。使用该基因集进行预测与 EST 终点之间的相关性为 0.85,该基因集预测发育毒性的准确率为 83%(曲线下面积为 89%)。如果排除由于测试浓度太低或样本之间差异太大而导致数据无效的化合物,则基于 15 种化合物甚至可以达到 100%的准确率。这个新的基因集主要由参与干细胞分化或其他发育过程的基因组成。我们期望该基因集可用于未来旨在改善 EST 进行风险评估的研究,从而朝着该方法的监管实施迈出下一步。

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