British journal of pharmacology · 2026
Kinase Inhibitor Cardiotoxicity Database (KICDB): a causality-oriented multi-omics database for kinase inhibitor-induced cardiotoxicity.
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Wei Jiamin, Liu Yin, Wu Miaoqing, Li Guoyuan, Zheng Xinyao, Fu Huafeng, Zhang Jian, Lin Jijin
Аннотация
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.
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.