Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors

Frontiers in Pharmacology

Pharmacology

Nicole C. Dubois¹  Priyanka Dhanan¹  Yuguang Xiong²  Bin Hu²  Jaehee V. Shim²  Rafael Dariolli²  Eric A. Sobie²  Gomathi Jayaraman²  Ravi Iyengar²  Christoph Schaniel³  Evren U. Azeloglu⁴  Marc R. Birtwistle⁵ 

[1] Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, United States;Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States;Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States;Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States;Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States;Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States;null;

关键词: mathematical model;    cardiotoxicity;    IPSC-CM cardiomyocytes;    mRNASeq;    mRNA sequencing;    kinase inhibitor;   

DOI  :  10.3389/fphar.2023.1158222

 received in 2023-02-03, accepted in 2023-03-27,  发布年份 2023

来源: Frontiers

【 摘 要 】

Introduction: Tyrosine kinase inhibitor drugs (TKIs) are highly effective cancer drugs, yet many TKIs are associated with various forms of cardiotoxicity. The mechanisms underlying these drug-induced adverse events remain poorly understood. We studied mechanisms of TKI-induced cardiotoxicity by integrating several complementary approaches, including comprehensive transcriptomics, mechanistic mathematical modeling, and physiological assays in cultured human cardiac myocytes.Methods: Induced pluripotent stem cells (iPSCs) from two healthy donors were differentiated into cardiac myocytes (iPSC-CMs), and cells were treated with a panel of 26 FDA-approved TKIs. Drug-induced changes in gene expression were quantified using mRNA-seq, changes in gene expression were integrated into a mechanistic mathematical model of electrophysiology and contraction, and simulation results were used to predict physiological outcomes.Results: Experimental recordings of action potentials, intracellular calcium, and contraction in iPSC-CMs demonstrated that modeling predictions were accurate, with 81% of modeling predictions across the two cell lines confirmed experimentally. Surprisingly, simulations of how TKI-treated iPSC-CMs would respond to an additional arrhythmogenic insult, namely, hypokalemia, predicted dramatic differences between cell lines in how drugs affected arrhythmia susceptibility, and these predictions were confirmed experimentally. Computational analysis revealed that differences between cell lines in the upregulation or downregulation of particular ion channels could explain how TKI-treated cells responded differently to hypokalemia.Discussion: Overall, the study identifies transcriptional mechanisms underlying cardiotoxicity caused by TKIs, and illustrates a novel approach for integrating transcriptomics with mechanistic mathematical models to generate experimentally testable, individual-specific predictions of adverse event risk.

【 授权许可】

Unknown   
Copyright © 2023 Shim, Xiong, Dhanan, Dariolli, Azeloglu, Hu, Jayaraman, Schaniel, Birtwistle, Iyengar, Dubois and Sobie.