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KICDB: A Causality-Oriented Multi-Omics Database for Kinase Inhibitor-Induced Cardiotoxicity
Abstract
Background: Kinase inhibitors (KIs) are mainstays of targeted cancer therapy, but their clinical utility is frequently limited by cardiotoxicity. A systematic resource to explore the underlying causal mechanisms is urgently needed. Methods: We present the KICDB ( K inase I nhibitor C ardiotoxicity D ata b ase), a comprehensive and interactive web server. KICDB is built upon a framework integrating large-scale transcriptomics meta-analysis with causal inference. Results: This database centralizes the findings from a comprehensive meta-analysis of 26 kinase inhibitors (KIs) across 7 studies (n=5291) identified 8,907 significant gene expression changes in human cardiomyocytes. To establish causality, we performed a two-pronged Mendelian randomization (MR) analysis testing hundreds of downstream genes and a panel of 43 key kinase proteins against 46 cardiovascular outcomes. This large-scale analysis revealed 26 significant causal associations, implicating novel molecular mediators in KI-induced cardiotoxicity. Conclusions: KICDB serves as a valuable and accessible platform for the cardio-oncology community. By integrating transcriptomic signatures with causal inference data, the database empowers researchers to formulate mechanistic hypotheses, accelerate biomarker validation, and guide the design of future cardioprotective strategies.
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Jiamin Wei, Yin Liu, Miaoqing Wu, et al.
KICDB: A Causality-Oriented Multi-Omics Database for Kinase Inhibitor-Induced Cardiotoxicity. Authorea. 21 August 2025.
DOI: https://doi.org/10.22541/au.175580534.45247880/v1
DOI: https://doi.org/10.22541/au.175580534.45247880/v1
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