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使用转录学评估适应性应激反应基因签名
1Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA.
Computational toxicology (Amsterdam, Netherlands)
|October 13, 2023
概括
这项研究开发了一种使用基因组丰富分析 (GSEA) 的计算方法,从转录组数据评估细胞应激反应途径 (SRPs),改进化学安全评估.
科学领域:
- 计算生物学是一种计算生物学.
- 毒素基因组学 毒素基因组学
- 分子毒理学分子毒理学
背景情况:
- 应激反应通路 (SRPs) 对于细胞防御化学攻击至关重要.
- 过度的SRP激活可能导致细胞不良结果,需要强有力的评估方法.
- 转录组数据为评估细胞对化学扰动的反应提供了一个强大的工具.
研究的目的:
- 开发和评估一个计算方法来评估SRP活动使用转录数据.
- 为了比较新的共识SRP签名与现有的已发布签名的性能.
- 建立一种可靠的方法来描述SRP活动,以应对新的化学实体.
主要方法:
- 从MSigDB中提取了六个关键SRP (DDR,UPR,HSR,HPX,MTL,OSR) 的已发表的基因签名.
- 使用基因频率方法构建共识SRP签名.
- 利用基因组丰富分析 (GSEA) 和在参考转录基因数据集上的受体运营者特征 (ROC) 分析.
主要成果:
- 在6个SRP中,共识SRP签名在4个SRP中表现得与已公布的签名相当或优于公布的签名.
- 在共识签名中实现了高的曲线下面面积 (AUC) 值,特别是DDR和HPX的1.00.
- 通过转录基因配置匹配,成功地以高准确度分类扰素 (分别为78%和88%在第一和第二排).
结论:
- 开发的计算方法有效地从转录基因数据中描述SRP活动.
- 共识SRP签名为有毒性评估提供了对现有签名的有希望的替代方案或补充.
- 这种方法具有评估新化学品SRP活性的潜力,有助于安全分析.
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