心脏毒性
酪氨酸激酶抑制剂
酪氨酸激酶
转录组
激酶
癌症研究
贾纳斯激酶
生物信息学
数据库
计算生物学
机制(生物学)
生物
Janus激酶2
蛋白激酶A
医学
第1周
生物标志物
ASK1
心肌病
受体酪氨酸激酶
信号转导
基诺美
药理学
癌症
作者
Jiamin Wei,Liu Y,Miaoqing Wu,G H Li,Xinyao Zheng,Huafeng Fu,Jian Zhang,Jijin Lin
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI