细胞外基质
化学
基底细胞
药品
癌症研究
细胞外
药物发现
肺
肺癌
腺癌
药物重新定位
计算生物学
药理学
治疗方法
细胞培养
细胞
精密医学
细胞生长
鳞癌
癌
肿瘤微环境
转录组
细胞凋亡
生物信息学
蛋白质组学
流式细胞术
作者
Bin Yang,Yuna Shao,Ziyun Zhou,Shuo Wang,Zeyi Liu,Guang Hu
标识
DOI:10.1021/acs.jmedchem.5c01495
摘要
High Resolution Image Download MS PowerPoint Slide Systematic proteomic comparisons across cancer subtypes provide insights into tumor heterogeneity and accelerate discovery of therapeutic targets and drug repositioning. Here, we present a novel computational framework, signature-network-perturbation- based drug repositioning (SnpDR), integrating proteomic and pharmacogenomic data through differential modular analysis, drug response network construction, and multiscale perturbation response scanning. Applying SnpDR to compare the proteomic landscapes of lung adenocarcinoma and lung squamous cell carcinoma (LSCC), we identified the extracellular matrix (ECM) module as a central hub in LSCC, while LAMA1 emerged as a novel drug target. In vitro and in vivo experiments validated two repositioned drugs, Fingolimod and Piperlongumine, both targeting ECM components, significantly inhibited LSCC cell growth, proliferation and migration at concentrations below 10 μM. These results provide compelling evidence for the power of systems biology to identify subtype-specific therapeutic vulnerabilities. Our findings highlight a promising framework for precision oncology and underscore the potential of ECM-targeted interventions in LSCC.
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