Key result
Specific kinase targets linked to increased cardiomyopathy and MI risk via 26 causal associations.
Why the study?
Kinase inhibitors frequently cause cardiotoxicity that limits their clinical utility, creating an urgent need for a systematic resource to explore the underlying causal mechanisms.
Meta-Analysis (n=5,291)
The KICDB database integrates transcriptomic and genetic data to identify causal mechanisms of kinase inhibitor-induced cardiotoxicity, highlighting disruption of mitotic machinery and specific kinase targets.
Answers are grounded in this paper and cite their sources.
May implicate mitotic disruption in kinase inhibitor cardiotoxicity; leaves open validation of RNF13/TIE1 targets for cardioprotection.
BACKGROUND: Kinase inhibitors (KIs) are essential in targeted cancer therapy but frequently cause cardiotoxicity, limiting their clinical utility. A systematic resource to explore the underlying causal mechanisms is urgently needed. METHODS: We developed the Kinase Inhibitor Cardiotoxicity Database (KICDB ), an interactive web platform integrating large-scale transcriptomic meta-analysis with causal inference to identify molecular determinants of KI-induced cardiotoxicity. RESULTS: Meta-analysis of 5291 samples revealed a convergent disruption of the cellular mitotic machinery, specifically chromosome segregation and nuclear division, as a shared mechanism of toxicity across multiple KI classes. Furthermore, Mendelian randomization (MR) analysis identified 26 robust causal associations, linking specific kinase targets (e.g. RING finger protein 13 [RNF13] and tyrosine kinase with immunoglobulin like and EGF like domains 1 [TIE1]) to increased risks of cardiomyopathy and myocardial infarction, while identifying TYRO3 protein tyrosine kinase [Tyro3] and Janus kinase 2 (JAK2) as potential cardioprotective factors. CONCLUSIONS: KICDB provides a mechanistic framework linking transcriptomic perturbations with genetically validated causal drivers. By linking transcriptomic perturbations with causal validation, it serves as a resource to advance biomarker discovery, mechanistic exploration and the design of cardioprotective strategies.
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Wei et al. (2026) conducted a meta-analysis in Kinase inhibitor-induced cardiotoxicity (n=5,291). Kinase inhibitors was evaluated on Causal associations with cardiomyopathy and myocardial infarction. Meta-analysis of 5,291 samples and Mendelian randomization identified 26 causal associations linking specific kinase targets to increased risks of cardiomyopathy and myocardial infarction.
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