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关于选择一组最小的体外检测方法来可靠地确定雌激素激动剂活性。

On selecting a minimal set of in vitro assays to reliably determine estrogen agonist activity.

机构信息

U.S. Environmental Protection Agency, RTP, NC, United States.

U.S. Environmental Protection Agency, RTP, NC, United States.

出版信息

Regul Toxicol Pharmacol. 2017 Dec;91:39-49. doi: 10.1016/j.yrtph.2017.09.022. Epub 2017 Oct 6.

Abstract

The US EPA is charged with screening chemicals for their ability to be endocrine disruptors through interaction with the estrogen, androgen and thyroid axes. The agency is exploring the use of high-throughput in vitro assays to use in the Endocrine Disruptor Screening Program (EDSP), potentially as replacements for lower-throughput in vitro and in vivo tests. The first replacement is an integrated computational and experimental model for estrogen receptor (ER) activity, to be used as an alternative to the EDSP Tier 1 in vitro ER binding and transactivation assays and the in vivo uterotrophic bioassay. The ER agonist model uses a set of 16 in vitro assays that incorporate multiple technologies and cell lines and probe multiple points in the ER pathway. Here, we demonstrate that subsets of assays with as few as 4 assays can predict the activity of all 1811 chemicals tested with accuracy equivalent to that of the full 16-assay model. The prediction accuracy against reference chemicals is higher than that of the full chemical set, partly because the larger set contains many chemicals that can cause a variety of types of assay interference There are multiple accurate assay subsets, allowing flexibility in the construction of a multiplexed assay battery. We also discuss the issue of challenging chemicals, i.e. those that can give false positive results in certain assays, and could hence be more problematic when only a few assays are used.

摘要

美国环保署负责通过与雌激素、雄激素和甲状腺轴的相互作用,筛选具有内分泌干扰潜力的化学物质。该机构正在探索使用高通量体外检测方法来应用于内分泌干扰物筛选计划(EDSP),这些方法可能替代低通量的体外和体内测试。第一个替代品是雌激素受体(ER)活性的综合计算和实验模型,可作为 EDSP 第 1 层体外 ER 结合和转激活检测以及体内子宫增重生物检测的替代方法。ER 激动剂模型使用了一组 16 种体外检测方法,这些方法结合了多种技术和细胞系,并探测了 ER 途径中的多个点。在这里,我们证明了具有多达 4 种检测方法的子集中,可以准确预测所有 1811 种经过测试的化学物质的活性,其准确性与完整的 16 种检测方法模型相当。与参考化学物质相比,该预测方法的准确性更高,部分原因是较大的集合包含许多可能引起各种类型检测干扰的化学物质。有多个准确的检测子集,可以灵活构建多重检测电池。我们还讨论了具有挑战性的化学物质的问题,即那些在某些检测中可能产生假阳性结果的化学物质,因此当只使用少数检测方法时,这些化学物质可能会更成问题。

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