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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.

DOI:10.1038/s41597-025-05630-4
PMID:40701981
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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本文引用的文献

1
Large-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug Combinations.大规模泛癌种细胞系筛查鉴定出潜在可用药和有效药物组合。
Cancer Discov. 2024 May 1;14(5):846-865. doi: 10.1158/2159-8290.CD-23-0388.
2
DGIdb 5.0: rebuilding the drug-gene interaction database for precision medicine and drug discovery platforms.DGIdb 5.0:为精准医学和药物发现平台重建药物-基因相互作用数据库。
Nucleic Acids Res. 2024 Jan 5;52(D1):D1227-D1235. doi: 10.1093/nar/gkad1040.
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A landscape of response to drug combinations in non-small cell lung cancer.
非小细胞肺癌药物联合治疗反应的全景。
Nat Commun. 2023 Jun 28;14(1):3830. doi: 10.1038/s41467-023-39528-9.
4
The NCI-MATCH trial: lessons for precision oncology.NCI-MATCH 试验:精准肿瘤学的经验教训。
Nat Med. 2023 Jun;29(6):1349-1357. doi: 10.1038/s41591-023-02379-4. Epub 2023 Jun 15.
5
A Transcriptome-Based Precision Oncology Platform for Patient-Therapy Alignment in a Diverse Set of Treatment-Resistant Malignancies.基于转录组学的精准肿瘤学平台,用于在一组多样化的耐药性恶性肿瘤中进行患者治疗匹配。
Cancer Discov. 2023 Jun 2;13(6):1386-1407. doi: 10.1158/2159-8290.CD-22-1020.
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New Paradigms in Pharmaceutical Development.药物研发的新范式
Life (Basel). 2022 Sep 15;12(9):1433. doi: 10.3390/life12091433.
7
Paclitaxel with or without pazopanib for ovarian cancer relapsing during bevacizumab maintenance therapy: The GINECO randomized phase II TAPAZ study.紫杉醇联合或不联合帕唑帕尼治疗贝伐珠单抗维持治疗期间复发的卵巢癌:GINECO 随机 II 期 TAPAZ 研究。
Gynecol Oncol. 2022 Sep;166(3):389-396. doi: 10.1016/j.ygyno.2022.06.022. Epub 2022 Jul 26.
8
Addition of Bevacizumab to Erlotinib as First-Line Treatment of Patients With EGFR-Mutated Advanced Nonsquamous NSCLC: The BEVERLY Multicenter Randomized Phase 3 Trial.贝伐珠单抗联合厄洛替尼作为 EGFR 突变型晚期非鳞状 NSCLC 患者一线治疗的研究:BEVERLY 多中心随机 3 期试验。
J Thorac Oncol. 2022 Sep;17(9):1086-1097. doi: 10.1016/j.jtho.2022.05.008. Epub 2022 Jun 1.
9
CDCDB: A large and continuously updated drug combination database.CDCDB:一个大型且不断更新的药物组合数据库。
Sci Data. 2022 Jun 2;9(1):263. doi: 10.1038/s41597-022-01360-z.
10
Precision Combination Therapies Based on Recurrent Oncogenic Coalterations.基于复发致癌重排的精准联合治疗。
Cancer Discov. 2022 Jun 2;12(6):1542-1559. doi: 10.1158/2159-8290.CD-21-0832.