Cargando…

Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors

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 inte...

Descripción completa

Detalles Bibliográficos
Autores principales: Shim, Jaehee V., Xiong, Yuguang, Dhanan, Priyanka, Dariolli, Rafael, Azeloglu, Evren U., Hu, Bin, Jayaraman, Gomathi, Schaniel, Christoph, Birtwistle, Marc R., Iyengar, Ravi, Dubois, Nicole C., Sobie, Eric A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123273/
https://www.ncbi.nlm.nih.gov/pubmed/37101545
http://dx.doi.org/10.3389/fphar.2023.1158222
_version_ 1785029638282543104
author Shim, Jaehee V.
Xiong, Yuguang
Dhanan, Priyanka
Dariolli, Rafael
Azeloglu, Evren U.
Hu, Bin
Jayaraman, Gomathi
Schaniel, Christoph
Birtwistle, Marc R.
Iyengar, Ravi
Dubois, Nicole C.
Sobie, Eric A.
author_facet Shim, Jaehee V.
Xiong, Yuguang
Dhanan, Priyanka
Dariolli, Rafael
Azeloglu, Evren U.
Hu, Bin
Jayaraman, Gomathi
Schaniel, Christoph
Birtwistle, Marc R.
Iyengar, Ravi
Dubois, Nicole C.
Sobie, Eric A.
author_sort Shim, Jaehee V.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10123273
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-101232732023-04-25 Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors Shim, Jaehee V. Xiong, Yuguang Dhanan, Priyanka Dariolli, Rafael Azeloglu, Evren U. Hu, Bin Jayaraman, Gomathi Schaniel, Christoph Birtwistle, Marc R. Iyengar, Ravi Dubois, Nicole C. Sobie, Eric A. Front Pharmacol Pharmacology 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. Frontiers Media S.A. 2023-04-10 /pmc/articles/PMC10123273/ /pubmed/37101545 http://dx.doi.org/10.3389/fphar.2023.1158222 Text en Copyright © 2023 Shim, Xiong, Dhanan, Dariolli, Azeloglu, Hu, Jayaraman, Schaniel, Birtwistle, Iyengar, Dubois and Sobie. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Shim, Jaehee V.
Xiong, Yuguang
Dhanan, Priyanka
Dariolli, Rafael
Azeloglu, Evren U.
Hu, Bin
Jayaraman, Gomathi
Schaniel, Christoph
Birtwistle, Marc R.
Iyengar, Ravi
Dubois, Nicole C.
Sobie, Eric A.
Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors
title Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors
title_full Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors
title_fullStr Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors
title_full_unstemmed Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors
title_short Predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors
title_sort predicting individual-specific cardiotoxicity responses induced by tyrosine kinase inhibitors
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10123273/
https://www.ncbi.nlm.nih.gov/pubmed/37101545
http://dx.doi.org/10.3389/fphar.2023.1158222
work_keys_str_mv AT shimjaeheev predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT xiongyuguang predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT dhananpriyanka predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT dariollirafael predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT azelogluevrenu predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT hubin predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT jayaramangomathi predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT schanielchristoph predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT birtwistlemarcr predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT iyengarravi predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT duboisnicolec predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors
AT sobieerica predictingindividualspecificcardiotoxicityresponsesinducedbytyrosinekinaseinhibitors