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In depth mechanistic analysis including high-throughput RNA sequencing in the prediction of functional and structural cardiotoxicants using hiPSC cardiomyocytes

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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE244740
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Background: Cardiotoxicity remains as one of the most reported adverse drug reactions that lead to drug attrition during pre-clinical and clinical drug development. Drug-induced cardiotoxicity can affect all components of the cardiovascular system and 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 the 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 (ScreenSeqTM) combined with high-content imaging (HCI) and Ca2+ transience (CaT) was used to analyse 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 and diverse stress responses, and the prediction of cardiotoxicity risk. Combination of ScreenSeqTM, HCI and CaT, provided a high cardiotoxicity prediction performance with 89% specificity, 91% sensitivity and 90% accuracy. Conclusions: Overall, this study introduces a mechanism driven risk assessment approach combining structural, functional and molecular high-throughput methods for the pre-clinical risk assessment of novel compounds. human iPSC-derived cardiomyocytes (hiPSC-CMs) were cultured on 384 well plates and treated with 42 different compounds at 8 concentrations per compound in triplicate for 24h. DMSO wells were included as treatment controls. We applied plate RNA-Seq analysis with well barcode labelling (ScreenSeqTM). Barcodes were stripped from the sequencing files, and one sequencing file per well is provided.
创建时间:
2023-10-10
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