Yang Jingyu, Wang Meng, Dönitz Jürgen, Chapuy Björn, Beißbarth Tim
Medical Bioinformatics, University Medical Center Göttingen, Göttingen, 37077, Germany.
Department of Hematology, Oncology, and Cancer Immunology, Charité-University Medical Center Berlin, Campus Benjamin Franklin, Berlin, 12203, Germany.
NAR Genom Bioinform. 2025 Jan 31;7(1):lqaf004. doi: 10.1093/nargab/lqaf004. eCollection 2025 Mar.
Identifying and validating genotype-guided drug combinations for a specific molecular subtype in cancer therapy represents an unmet medical need and is important in enhancing efficacy and reducing toxicity. However, the exponential increase in combinatorial possibilities constrains the ability to identify and validate effective drug combinations. In this context, we have developed Onko_DrugCombScreen, an innovative tool aiming at advancing precision medicine based on identifying significant drug combination candidates in a target cancer cohort compared to a comparison cohort. Onko_DrugCombScreen, inspired by the molecular tumor board process, synergizes drug knowledgebase analysis with various statistical methodologies and data visualization techniques to pinpoint drug combination candidates. Validated through a TCGA-BRCA case study, Onko_DrugCombScreen has demonstrated its proficiency in discerning established drug combinations in a specific cancer type and in revealing potential novel drug combinations. By enhancing the capability of drug combination discovery through drug knowledgebases, Onko_DrugCombScreen represents a significant advancement in personalized cancer treatment by identifying promising drug combinations, setting the stage for the development of more precise and potent combination treatments in cancer care. The Onko_DrugCombScreen Shiny app is available at https://rshiny.gwdg.de/apps/onko_drugcombscreen/. The Git repository can be accessed at https://gitlab.gwdg.de/MedBioinf/mtb/onko_drugcombscreen.
识别并验证针对癌症治疗中特定分子亚型的基因型指导药物组合,是一项尚未满足的医学需求,对于提高疗效和降低毒性至关重要。然而,组合可能性呈指数级增长,限制了识别和验证有效药物组合的能力。在此背景下,我们开发了Onko_DrugCombScreen,这是一种创新工具,旨在通过与对照队列相比,在目标癌症队列中识别重要的药物组合候选物,推动精准医学发展。Onko_DrugCombScreen受分子肿瘤委员会流程启发,将药物知识库分析与各种统计方法和数据可视化技术相结合,以确定药物组合候选物。通过一项TCGA - BRCA病例研究验证,Onko_DrugCombScreen已证明其在识别特定癌症类型中已确立的药物组合以及揭示潜在新药物组合方面的能力。通过药物知识库增强药物组合发现能力,Onko_DrugCombScreen通过识别有前景的药物组合,在个性化癌症治疗方面取得了重大进展,为癌症护理中更精确、有效的联合治疗发展奠定了基础。Onko_DrugCombScreen Shiny应用程序可在https://rshiny.gwdg.de/apps/onko_drugcombscreen/获取。Git仓库可在https://gitlab.gwdg.de/MedBioinf/mtb/onko_drugcombscreen访问。