荟萃分析
仿形(计算机编程)
免疫疗法
医学
计算机科学
限制
肿瘤科
癌症
数据科学
数据挖掘
计算生物学
内科学
生物
机械工程
操作系统
工程类
作者
Chongxuan Lu,Mingxiao Li,Hong Yang,Zaoqu Liu,Jian Zhang,Quan Cheng,Anqi Lin,Shixiang Wang,Peng Luo
出处
期刊:
[Wiley]
日期:2025-06-01
卷期号:4 (2)
摘要
ABSTRACT Immune checkpoint inhibitors (ICIs) have transformed cancer immunotherapy, but their clinical efficacy varies significantly due to tumor heterogeneity and patient‐specific factors. Existing databases lack comprehensive integration of ICI efficacy data and fail to explore biomarkers across pan‐cancer contexts, limiting their utility in precision oncology. To address this gap, we developed ImmunoCheckDB, a systematic platform that curates 173 studies on cancer ICI treatment, integrating survival outcomes for traditional and network meta‐analyses with multiomic data sets from public repositories, including over 93,000+ individuals across 18 cancer types and 30 ICI regimens to provide a robust resource for pan‐cancer biomarker discovery. Equipped with online tools for meta‐analysis, network meta‐analysis, and multiomic profiling, ImmunoCheckDB enables researchers to investigate correlations between ICI efficacy and molecular biomarkers, featuring key functionalities such as real‐time visualization of forest plots, funnel plots, and network diagrams, as well as association analyses linking multiomic data to clinical outcomes. Uniquely combining meta‐analytical with multiomic exploration, our platform offers insights into optimal patient populations for ICI therapy, thereby bridging the gap between clinical data and molecular research to empower researchers in advancing precision immunotherapy, with access available at https://smuonco.shinyapps.io/ImmunoCheckDB/ to democratize data‐driven insights for personalized cancer treatment.
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