Considerations for strategic use of high-throughput transcriptomics chemical screening data in regulatory decisions
Considerations for strategic use of high-throughput transcriptomics chemical screening data in regulatory decisions
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DOI：
10.1016/j.cotox.2019.05.004
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发表时间：
2019-06-01
影响因子：
4.6
通讯作者：
Thomas, Russell S.
中科院分区：
文献类型：
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作者：
Harrill, Joshua;Shah, Imran;Thomas, Russell S.
最近，包括美国和国外的政府监管机构在内的许多组织都建议使用新方法(NAMS)的数据来加强和加快化学评估的速度。NAMS被广泛地定义为可用于提供有关化学危害和风险评估的信息以避免使用完整动物的任何技术、方法、方法或其组合。高通量转录组学(HTTR)是一种使用基因表达谱作为终点的NAM，用于快速评估大量化学物质对体外细胞培养系统的影响。与测量化学X对靶Y的影响的靶向高通量筛选方法相比，HTTR是一种非靶向的方法，它允许研究人员更广泛地描述完整的生物系统对在一组确定的处理条件(时间、浓度等)下可能影响特定生物靶点或多个生物靶点的化学品的综合反应。在浓度-反应模式下进行的htr筛选可以为在细胞反应途径中产生扰动的化学物质的浓度提供效力估计。在这里，我们讨论了httr浓度-反应筛选的研究设计考虑因素，并提出了在筛选水平、基于风险的化学优先方法中使用基于httr的生物途径改变浓度的框架。该框架包括HTTR数据的浓度-反应模型，绘制生物途径的基因水平反应图，确定改变生物途径的浓度，体外到体内的外推，以及与人类暴露预测的比较。
Recently, numerous organizations, including governmental regulatory agencies in the US and abroad, have proposed using data from new approach methodologies (NAMs) for augmenting and increasing the pace of chemical assessments. NAMs are broadly defined as any technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. High-throughput transcriptomics (HTTr) is a type of NAM that uses gene expression profiling as an endpoint for rapidly evaluating the effects of large numbers of chemicals on in vitro cell culture systems. As compared to targeted high-throughput screening approaches that measure the effect of chemical Xon target Y, HTTr is a non-targeted approach that allows researchers to more broadly characterize the integrated response of an intact biological system to chemicals that may affect a specific biological target or many biological targets under a defined set of treatment conditions (time, concentration, etc.). HTTr screening performed in concentration-response mode can provide potency estimates for the concentrations of chemicals that produce perturbations in cellular response pathways. Here, we discuss study design considerations for HTTr concentration-response screening and present a framework for the use of HTTr-based biological pathway-altering concentrations in a screening-level, risk-based chemical prioritization approach. The framework involves concentration-response modeling of HTTr data, mapping gene level responses to biological pathways, determination of biological pathway-altering concentrations, in vitro-to-in vivo extrapolation, and comparison to human exposure predictions.