ArticleNature communications2020
Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
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Who cites it
33 citing papers in PubMed, 50 citations in OpenAlex.
- A Ponatinib-Associated Transcriptomic Signature: Implications for Cardiovascular Toxicity.International journal of molecular sciences · 2026Article
- Metabolomic Profiling of Tyrosine Kinase Inhibitor-Induced Endothelial Dysfunction and Cardiovascular Toxicity.Metabolites · 2026Review
- A self-adaptive and versatile tool for eliminating multiple undesirable variations from large-scale transcriptomes.Nature biomedical engineering · 2026Article
- predicTox: an integrated database of clinical risk frequencies and human gene expression signatures for cardiotoxic drugs.Database : the journal of biological databases and curation · 2026Article
- Peripheral and central nervous system toxicities of Bruton tyrosine kinase Inhibitors: a real-world pharmacovigilance study.Frontiers in medicine · 2026Article
- Review
- Drug Discovery and Development for Heart Failure Using Multi-Omics Approaches.International journal of molecular sciences · 2025Review
- Safety evaluation of irinotecan: a real-world disproportionality analysis using FAERS and JADER databases during the time period 2004-2024.Frontiers in pharmacology · 2025Article
- Real-world safety profile of elexacaftor/tezacaftor/ivacaftor: a disproportionality analysis using the U.S. FDA adverse event reporting system.Frontiers in pharmacology · 2025Article
- Multiscale mapping of transcriptomic signatures for cardiotoxic drugs.Nature communications · 2024Article
- Informing Hazard Identification and Risk Characterization of Environmental Chemicals by Combining Transcriptomic and Functional Data from Human-Induced Pluripotent Stem-Cell-Derived Cardiomyocytes.Chemical research in toxicology · 2024Article
- Computational approaches identify a transcriptomic fingerprint of drug-induced structural cardiotoxicity.Cell biology and toxicology · 2024Article
- A real-world pharmacovigilance analysis of adverse events associated with irbesartan using the FAERS and JADER databases.Frontiers in pharmacology · 2024Article
- DOSE-L1000: unveiling the intricate landscape of compound-induced transcriptional changes.Bioinformatics (Oxford, England) · 2023Article
- Circulating biomarkers for management of cancer therapeutics-related cardiac dysfunction.Cardiovascular research · 2023Review
- Three tyrosine kinase inhibitors cause cardiotoxicity by inducing endoplasmic reticulum stress and inflammation in cardiomyocytes.BMC medicine · 2023Article
- Whole-exome sequencing identifies a set of genes as markers of hepatocellular carcinoma early recurrence.Hepatology international · 2023Article
- Ponatinib Drives Cardiotoxicity by S100A8/A9-NLRP3-IL-1β Mediated Inflammation.Circulation research · 2023Article
- Spinal cord injury regulates circular RNA expression in axons.Frontiers in molecular neuroscience · 2023Article
- Pneumocystis jirovecii pneumonia associated with immune checkpoint inhibitors: A systematic literature review of published case reports and disproportionality analysis based on the FAERS database.Frontiers in pharmacology · 2023Article
Corrections and comments
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Authors and funding
17 authors at 4 institutions in 2 countries.
Funding
Abstract
Kinase inhibitors (KIs) represent an important class of anti-cancer drugs. Although cardiotoxicity is a serious adverse event associated with several KIs, the reasons remain poorly understood, and its prediction remains challenging. We obtain transcriptional profiles of human heart-derived primary cardiomyocyte like cell lines treated with a panel of 26 FDA-approved KIs and classify their effects on subcellular pathways and processes. Individual cardiotoxicity patient reports for these KIs, obtained from the FDA Adverse Event Reporting System, are used to compute relative risk scores. These are then combined with the cell line-derived transcriptomic datasets through elastic net regression analysis to identify a gene signature that can predict risk of cardiotoxicity. We also identify relationships between cardiotoxicity risk and structural/binding profiles of individual KIs. We conclude that acute transcriptomic changes in cell-based assays combined with drug substructures are predictive of KI-induced cardiotoxicity risk, and that they can be informative for future drug discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.