Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina.
Oak Ridge Institute for Science and Education (ORISE).
Toxicol Sci. 2020 Sep 1;177(1):11-26. doi: 10.1093/toxsci/kfaa101.
Chemical-induced liver cancer occurs in rodents through well-characterized adverse outcome pathways. We hypothesized that measurement of the 6 most common molecular initiating events (MIEs) in liver cancer adverse outcome pathways in short-term assays using only gene expression will allow early identification of chemicals and their associated doses that are likely to be tumorigenic in the liver in 2-year bioassays. We tested this hypothesis using transcript data from a rat liver microarray compendium consisting of 2013 comparisons of 146 chemicals administered at doses with previously established effects on rat liver tumor induction. Five MIEs were measured using previously characterized gene expression biomarkers composed of gene sets predictive for genotoxicity and activation of 1 or more xenobiotic receptors (aryl hydrocarbon receptor, constitutive activated receptor, estrogen receptor, and peroxisome proliferator-activated receptor α). Because chronic injury can be important in tumorigenesis, we also developed a biomarker for cytotoxicity that had a 96% balanced accuracy. Characterization of the genes in each biomarker set using the unsupervised TXG-MAP network model demonstrated that the genes were associated with distinct functional coexpression modules. Using the Toxicological Priority Index to rank chemicals based on their ability to activate the MIEs showed that chemicals administered at tumorigenic doses clearly gave the highest ranked scores. Balanced accuracies using thresholds derived from either TG-GATES or DrugMatrix data sets to predict tumorigenicity in independent sets of chemicals were up to 93%. These results show that a MIE-directed approach using only gene expression biomarkers could be used in short-term assays to identify chemicals and their doses that cause tumors.
化学诱导的肝癌在啮齿动物中通过特征明确的不良结局途径发生。我们假设，在短期测定中仅使用基因表达来测量肝癌不良结局途径中的 6 种最常见的分子起始事件（MIEs），将允许早期识别可能在 2 年生物测定中导致肝脏肿瘤的化学物质及其相关剂量。我们使用由 2013 个比较组成的大鼠肝微阵列汇编中的转录数据来测试这一假设，这些比较涉及 146 种化学物质，其剂量先前已确定对大鼠肝肿瘤诱导有影响。使用先前用基因集预测的基因表达生物标志物测量了 5 个 MIEs，这些基因集预测了遗传毒性和 1 个或多个外源物受体（芳烃受体、组成激活受体、雌激素受体和过氧化物酶体增殖物激活受体 α）的激活。由于慢性损伤在肿瘤发生中可能很重要，我们还开发了一种用于细胞毒性的生物标志物，其平衡准确性为 96%。使用无监督 TXG-MAP 网络模型对每个生物标志物集中的基因进行特征描述表明，这些基因与不同的功能共表达模块相关。使用毒性优先指数根据激活 MIEs 的能力对化学物质进行排名表明，在致瘤剂量下给予的化学物质明显给出了最高的评分。基于 TG-GATES 或 DrugMatrix 数据集衍生的阈值来预测独立化学物质组的肿瘤形成能力的平衡准确性高达 93%。这些结果表明，仅使用基因表达生物标志物的 MIE 定向方法可用于短期测定中，以识别导致肿瘤的化学物质及其剂量。
