深入的机制分析,包括使用hiPSC心肌细胞预测功能和结构心脏毒物的高通量RNA测序。

Alicia Rosell-Hidalgo, Christopher Bruhn, Emma Shardlow, Ryan Barton, Stephanie Ryder, Timur Samatov, Alexandra Hackmann, Gerald Ryan Aquino, Micael Fernandes Dos Reis, Vladimir Galatenko, Ruediger Fritsch, Cord Dohrmann, Paul A Walker
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引用次数: 0

摘要

背景:在临床前和临床药物开发过程中,心脏毒性仍然是报道最多的导致药物损耗的药物不良反应之一。药物诱导的心脏毒性可发展为心脏电生理功能改变(心肌机械功能的急性改变)和/或结构改变,导致心脏组织活力丧失和形态损伤。研究设计与方法:建立具有较好预测价值的非临床模型,提高心脏安全药理学水平。为此,高通量RNA测序(ScreenSeq)与高含量成像(HCI)和Ca2+瞬变(CaT)相结合,分析化合物处理的人诱导的多能干细胞来源的心肌细胞(hiPSC-CMs)。结果:对33种心脏毒性药物和9种混合治疗适应症的非心脏毒性药物治疗的hiPSC-CMs进行分析,通过作用机制、心肌细胞收缩性、线粒体完整性、代谢状态、多种应激反应的相关途径活性评分和心脏毒性风险预测,促进了复合聚类。ScreenSeq、HCI和CaT的组合提供了高的心脏毒性预测性能,特异性为89%,灵敏度为91%,准确度为90%。结论:总的来说,本研究引入了结合结构、功能和分子高通量方法的机制驱动风险评估方法,用于新化合物的临床前风险评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
In-depth mechanistic analysis including high-throughput RNA sequencing in the prediction of functional and structural cardiotoxicants using hiPSC cardiomyocytes.

Background: Cardiotoxicity remains one of the most reported adverse drug reactions that lead to drug attrition during pre-clinical and clinical drug development. Drug-induced cardiotoxicity may develop as a functional change in cardiac electrophysiology (acute alteration of the mechanical function of the myocardium) and/or as a structural change, resulting in loss of viability and morphological damage to cardiac tissue.

Research design and methods: Non-clinical models with better predictive value need to be established to improve cardiac safety pharmacology. To this end, high-throughput RNA sequencing (ScreenSeq) was combined with high-content imaging (HCI) and Ca2+ transience (CaT) to analyze compound-treated human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs).

Results: Analysis of hiPSC-CMs treated with 33 cardiotoxicants and 9 non-cardiotoxicants of mixed therapeutic indications facilitated compound clustering by mechanism of action, scoring of pathway activities related to cardiomyocyte contractility, mitochondrial integrity, metabolic state, diverse stress responses and the prediction of cardiotoxicity risk. The combination of ScreenSeq, HCI and CaT provided a high cardiotoxicity prediction performance with 89% specificity, 91% sensitivity and 90% accuracy.

Conclusions: Overall, this study introduces mechanism-driven risk assessment approach combining structural, functional and molecular high-throughput methods for pre-clinical risk assessment of novel compounds.

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