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KICDB: A Causality-Oriented Multi-Omics Database for Kinase Inhibitor-Induced Cardiotoxicity
by
Zheng, Xinyao
, Wei, Jiamin
, Zhang, Jian
, Liu, Yin
, Fu, Huafeng
, Li, Guoyuan
, Lin, Jijin
, Wu, Miaoqing
in
Bioinformatics
2025
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Do you wish to request the book?
KICDB: A Causality-Oriented Multi-Omics Database for Kinase Inhibitor-Induced Cardiotoxicity
by
Zheng, Xinyao
, Wei, Jiamin
, Zhang, Jian
, Liu, Yin
, Fu, Huafeng
, Li, Guoyuan
, Lin, Jijin
, Wu, Miaoqing
in
Bioinformatics
2025
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KICDB: A Causality-Oriented Multi-Omics Database for Kinase Inhibitor-Induced Cardiotoxicity
Paper
KICDB: A Causality-Oriented Multi-Omics Database for Kinase Inhibitor-Induced Cardiotoxicity
2025
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Overview
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.
We present the KICDB (Kinase Inhibitor Cardiotoxicity Database), a comprehensive and interactive web server. KICDB is built upon a framework integrating large-scale transcriptomics meta-analysis with causal inference.
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.
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.
URL: https://zhang-lab-database.shinyapps.io/KICDB/
We developed KICDB, a comprehensive and publicly accessible web server, to systematically investigate the causal mechanisms of KI-induced cardiotoxicity.
KICDB integrates a large-scale meta-analysis of transcriptomic data from 26 KIs with a robust Mendelian randomization (MR) framework to move beyond correlation and infer causality.
The analysis identified 8,907 significant gene expression changes and 26 significant causal associations between KI-associated genes and 46 cardiovascular outcomes.
Publisher
Cold Spring Harbor Laboratory
Subject
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