Grimm Fabian A, House John S, Wilson Melinda R, Sirenko Oksana, Iwata Yasuhiro, Wright Fred A, Ball Nicholas, Rusyn Ivan
Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, 77843, USA.
Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA; Center for Human Health and the Environment, North Carolina State University, Raleigh, NC 27695, USA.
Regul Toxicol Pharmacol. 2019 Feb;101:91-102. doi: 10.1016/j.yrtph.2018.11.011. Epub 2018 Nov 22.
High-content screening data derived from physiologically-relevant in vitro models promise to improve confidence in data-integrative groupings for read-across in human health safety assessments. The biological data-based read-across concept is especially applicable to bioactive chemicals with defined mechanisms of toxicity; however, the challenge of data-derived groupings for chemicals that are associated with little or no bioactivity has not been explored. In this study, we apply a suite of organotypic and population-based in vitro models for comprehensive bioactivity profiling of twenty E-Series and P-Series glycol ethers, solvents with a broad variation in toxicity ranging from relatively non-toxic to reproductive and hematopoetic system toxicants. Both E-Series and P-Series glycol ethers elicited cytotoxicity only at high concentrations (mM range) in induced pluripotent stem cell-derived hepatocytes and cardiomyocytes. Population-variability assessment comprised a study of cytotoxicity in 94 human lymphoblast cell lines from 9 populations and revealed differences in inter-individual variability across glycol ethers, but did not indicate population-specific effects. Data derived from various phenotypic and transcriptomic assays revealed consistent bioactivity trends between both cardiomyocytes and hepatocytes, indicating a more universal, rather than cell-type specific mode-of-action for the tested glycol ethers in vitro. In vitro bioactivity-based similarity assessment using Toxicological Priority Index (ToxPi) showed that glycol ethers group according to their alcohol chain length, longer chains were associated with increased bioactivity. While overall in vitro bioactivity profiles did not correlate with in vivo toxicity data on glycol ethers, in vitro bioactivity of E-series glycol ethers were indicative of and correlated with in vivo irritation scores.
源自生理相关体外模型的高内涵筛选数据有望提高人类健康安全评估中用于类推的基于数据整合分组的可信度。基于生物学数据的类推概念尤其适用于具有明确毒性机制的生物活性化学品；然而，对于与很少或没有生物活性相关的化学品，基于数据的分组挑战尚未得到探索。在本研究中，我们应用了一套基于器官型和群体的体外模型，对20种E系列和P系列乙二醇醚进行全面的生物活性分析，这些乙二醇醚是毒性变化范围广泛的溶剂，从相对无毒到对生殖和造血系统有毒的物质。E系列和P系列乙二醇醚仅在高浓度（毫摩尔范围）下对诱导多能干细胞衍生的肝细胞和心肌细胞产生细胞毒性。群体变异性评估包括对来自9个群体的94个人类淋巴母细胞系的细胞毒性研究，结果显示不同乙二醇醚之间个体间变异性存在差异，但未表明群体特异性效应。来自各种表型和转录组分析的数据显示，心肌细胞和肝细胞之间的生物活性趋势一致，表明所测试的乙二醇醚在体外具有更普遍而非细胞类型特异性的作用模式。使用毒理学优先级指数（ToxPi）进行的基于体外生物活性的相似性评估表明，乙二醇醚根据其醇链长度分组，链长越长，生物活性越高。虽然总体体外生物活性谱与乙二醇醚的体内毒性数据不相关，但E系列乙二醇醚的体外生物活性与体内刺激评分具有指示性且相关。
