Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors

Jaehee V Shim; Yuguang Xiong; Priyanka Dhanan; Rafael Dariolli; Evren U Azeloglu; Bin Hu; Gomathi Jayaraman; Christoph Schaniel; Marc R Birtwistle; Ravi Iyengar; Nicole C Dubois; Eric A Sobie

doi:10.3389/fphar.2023.1158222

Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors

Front Pharmacol. 2023 Apr 10:14:1158222. doi: 10.3389/fphar.2023.1158222. eCollection 2023.

Authors

Jaehee V Shim^{1

2}, Yuguang Xiong^{1

2}, Priyanka Dhanan³, Rafael Dariolli^{1

2}, Evren U Azeloglu^{2

4}, Bin Hu^{1

2}, Gomathi Jayaraman^{1

2}, Christoph Schaniel², Marc R Birtwistle^{1

2

3

4}, Ravi Iyengar^{1

2}, Nicole C Dubois³, Eric A Sobie^{1

2}

Affiliations

¹ Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
² Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
³ Department of Cell, Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
⁴ Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.

Abstract

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.

Keywords: IPSC-CM cardiomyocytes; cardiotoxicity; kinase inhibitor; mRNA sequencing; mRNASeq; mathematical model.

Grants and funding

The work was supported by U54 HG008098, “Drug Combination Signatures for Prediction and Mitigation of Toxicity,” to RI, ES, and MB. All remaining authors are members of the Drug Toxicity Signature Generation Center at Mount Sinai, supported by U54 HG008098 and part of the NIH LINCS program.