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利用基因表达标志物鉴定潜在的内分泌干扰化学物质。

Identification of potential endocrine disrupting chemicals using gene expression biomarkers.

机构信息

Integrated Systems Toxicology Division, National Health and Environmental Effects Research Laboratory, US Environmental Protection Agency, Research Triangle Park, 109 T.W. Alexander Dr, MD-B105-03, NC 27711, United States.

National Toxicology Program Interagency Center for the Evaluation of Alternative Toxicological Methods, National Institute of Environmental Health Sciences, Research Triangle Park, NC, United States.

出版信息

Toxicol Appl Pharmacol. 2019 Oct 1;380:114683. doi: 10.1016/j.taap.2019.114683. Epub 2019 Jul 17.

Abstract

Recent technological advances have moved the field of toxicogenomics from reliance on microarray platforms to high-throughput transcriptomic (HTTr) technologies that measure global gene expression. Gene expression biomarkers are emerging as useful tools for interpreting gene expression profiles to identify perturbations of targets of xenobiotic chemicals including those that act as endocrine disrupting chemicals (EDCs). Gene expression biomarkers are lists of similarly-regulated genes identified in global gene expression comparisons of cells or tissues 1) exposed to known agonists or antagonists of the transcription factor (TF) and 2) after expression of the TF itself is knocked down/knocked out or overexpressed. Estrogen receptor α (ERα) and androgen receptor (AR) biomarkers have been shown to be very accurate at identifying both agonists (94-97%) and antagonists (93-98%) in microarray data derived from human breast or prostate cancer cell lines. Importantly, the biomarkers have been shown to accurately replicate the results of computational models that predict ERα or AR modulation using multiple ToxCast HT screening assays. An integrated screening strategy using sets of biomarkers that simultaneously predict various EDC targets in relevant cell lines should simplify chemical screening without sacrificing accuracy. The biomarker predictions can be put into the context of the adverse outcome pathway framework to help prioritize chemicals with the greatest risk of potential adverse outcomes in the endocrine systems of animals and people.

摘要

近年来,毒理基因组学领域的技术进步已经摆脱了对微阵列平台的依赖,转而采用高通量转录组(HTTr)技术来测量全基因组的基因表达。基因表达生物标志物正逐渐成为一种有用的工具,可以用来解释基因表达谱,以识别外源化学物质(包括那些作为内分泌干扰化学物质(EDCs)的物质)靶标的干扰。基因表达生物标志物是一组在细胞或组织的全基因组表达比较中识别出的相似调控基因,这些基因受到 1)已知转录因子(TF)激动剂或拮抗剂的暴露,以及 2)TF 自身的表达被敲低/敲除或过表达的影响。已经证明,雌激素受体 α(ERα)和雄激素受体(AR)生物标志物非常准确地识别微阵列数据中来自人类乳腺癌或前列腺癌细胞系的激动剂(94-97%)和拮抗剂(93-98%)。重要的是,这些生物标志物已经被证明可以准确地复制使用多个 ToxCast HT 筛选测定来预测 ERα 或 AR 调节的计算模型的结果。使用同时预测相关细胞系中各种 EDC 靶标的生物标志物集的综合筛选策略,应该可以简化化学筛选而不牺牲准确性。生物标志物预测可以纳入不良结局途径框架,以帮助优先考虑那些在动物和人群内分泌系统中具有最大潜在不良结局风险的化学品。

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