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一个用于催化精准联合治疗的高度注释的药物组合资源。

A highly annotated drug combination resource for catalyzing precision combinatorial therapy.

作者信息

You Tianyi, Wang Lili, Wang Jianhua, Xu Dongqing, Xu Xinran, Li Nan, Li Mulin Jun, Wang Haitao, Dong Xiaobao

机构信息

Department of Bioinformatics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.

Department of Oncology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.

出版信息

Sci Data. 2025 Jul 23;12(1):1284. doi: 10.1038/s41597-025-05630-4.

Abstract

Combinations of cancer drugs have the potential to overcome resistance, improve the response rate of existing drugs and reduce dose-limiting toxicity associated with single agents. Existing drug combination databases only provide response data, such as synergy scores between two drugs, without important contextual information to assist oncologists in matching their patients with these combinations in an evidence-based way. To address this gap, we developed a cancer drug combination database (named as OncoDrug+) by manually collecting and integrating drug combinations and corresponding evidences from FDA databases, clinical guidelines, clinical trials, clinical case reports, patient-derived tumor xenograft models, cell line models and bioinformatics predictions. OncoDrug+ includes 7895 data entries, covering 77 cancer types, including unique 2201 drug combination therapies, involving 1200 biomarkers, 763 published reports and seven types of evidence. Unlike many previous databases only include treatment regime and drug response data, OncoDrug+ provides detailed genetic evidences, pharmacological target information and evidence scores supporting each combination strategy, making evidence-based experimental or clinical applications of cancer drug combinations be possible.

摘要

癌症药物组合有潜力克服耐药性、提高现有药物的反应率并降低与单一药物相关的剂量限制性毒性。现有的药物组合数据库仅提供反应数据,例如两种药物之间的协同分数,而没有重要的背景信息来帮助肿瘤学家以循证方式为其患者匹配这些组合。为了填补这一空白,我们通过手动收集和整合来自FDA数据库、临床指南、临床试验、临床病例报告、患者来源的肿瘤异种移植模型、细胞系模型和生物信息学预测的药物组合及相应证据,开发了一个癌症药物组合数据库(名为OncoDrug+)。OncoDrug+包含7895条数据记录,涵盖77种癌症类型,包括独特的2201种药物联合疗法,涉及1200个生物标志物、763篇已发表报告和七种证据类型。与许多以前仅包括治疗方案和药物反应数据的数据库不同,OncoDrug+提供了详细的遗传证据、药理学靶点信息和支持每种组合策略的证据分数,使得癌症药物组合的循证实验或临床应用成为可能。

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