Multiscale mapping of transcriptomic signatures for cardiotoxic drugs

Abstract

Drug-induced gene expression profiles can identify potential mechanisms of toxicity. We focused on obtaining signatures for cardiotoxicity of FDA-approved tyrosine kinase inhibitors (TKIs) in human induced pluripotent stem cell-derived cardiomyocytes. Using bulk transcriptomics profiles, we applied singular value decomposition to identify drug-selective patterns in cell lines obtained from multiple healthy human subjects. Cellular pathways affected by highly cardiotoxic TKIs include energy metabolism, contractile, and extracellular matrix dynamics. Projecting these pathways to single cell expression profiles indicates that TKI responses can be evoked in both cardiomyocytes and fibroblasts. Whole genome sequences of the cell lines, using outlier responses enabled us to correctly reidentify a genomic variant associated with anthracycline cardiotoxicity and predict genomic variants potentially associated with TKI cardiotoxicity. We conclude that mRNA expression profiles when integrated with publicly available genomic, pathway, and single cell transcriptomic datasets, provide multiscale predictive understanding of cardiotoxicity for drug development and patient stratification. One sentence summaryGenes, pathways, and cell types of the human heart associated with antineoplastic drug cardiotoxicity.