Szabo Brigitta R, Stein Jeroen, Savchenko Anna, Hutschalik Thomas, Van Nieuwerburgh Filip, Meese Tim, Kosmidis Georgios, Volders Paul G A, Matsa Elena
Ncardia Services B.V., Leiden, Netherlands.
Department of Cardiology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center, Maastricht, Netherlands.
Front Toxicol. 2025 Aug 21;7:1644119. doi: 10.3389/ftox.2025.1644119. eCollection 2025.
Efficient preclinical prediction of cardiovascular side effects poses a pivotal challenge for the pharmaceutical industry. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are becoming increasingly important in this field due to inaccessibility of human native cardiac tissue. Current preclinical hiPSC-CMs models focus on functional changes such as electrophysiological abnormalities, however other parameters, such as structural toxicity, remain less understood.
This study utilized hiPSC-CMs from three independent donors, cultured in serum-free conditions, and treated with a library of 17 small molecules with stratified cardiac side effects. High-content imaging (HCI) targeting ten subcellular organelles, combined with multi-electrode array data, was employed to profile drug responses. Dimensionality reduction and clustering of the data were performed using principal component analysis (PCA) and sparse partial least squares discriminant analysis (sPLS-DA).
Both supervised and unsupervised clustering revealed patterns associated with known clinical side effects. In supervised clustering, morphological features outperformed electrophysiological data alone, and the combined data set achieved a 76% accuracy in recapitulating known clinical cardiotoxicity classifications. RNA-sequencing of all drugs vehicle conditions was used to support the mechanistic insights derived from morphological profiling, validating the former as a valuable cardiotoxicity tool.
Results demonstrate that a combined approach of analyzing morphology and electrophysiology enhances prediction and understanding of drug cardiotoxicity. Our integrative approach introduces a potential framework that is accessible, scalable and better aligned with clinical outcomes.
对心血管副作用进行高效的临床前预测是制药行业面临的一项关键挑战。由于无法获取人体天然心脏组织，人诱导多能干细胞衍生的心肌细胞（hiPSC-CMs）在该领域正变得越来越重要。当前的临床前hiPSC-CMs模型主要关注功能变化，如电生理异常，然而其他参数，如结构毒性，仍了解较少。
本研究使用了来自三个独立供体的hiPSC-CMs，在无血清条件下培养，并用一组包含17种具有分层心脏副作用的小分子进行处理。采用针对十个亚细胞器的高内涵成像（HCI），结合多电极阵列数据，来描绘药物反应。使用主成分分析（PCA）和稀疏偏最小二乘判别分析（sPLS-DA）对数据进行降维和聚类。
监督聚类和非监督聚类均揭示了与已知临床副作用相关的模式。在监督聚类中，形态学特征比单独的电生理数据表现更好，并且组合数据集在重现已知临床心脏毒性分类方面的准确率达到了76%。对所有药物载体条件进行RNA测序，以支持从形态学分析中获得的机制见解，验证了前者作为一种有价值的心脏毒性工具。
结果表明，分析形态学和电生理学的联合方法可增强对药物心脏毒性的预测和理解。我们的综合方法引入了一个潜在的框架，该框架易于使用、可扩展且与临床结果更相符。
