A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes
A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes
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DOI：
10.1093/jamia/ocw007
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发表时间：
2016-07-01
影响因子：
6.4
通讯作者：
Zhao, Zhongming
中科院分区：
文献类型：
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作者：
Cheng, Feixiong;Zhao, Junfei;Zhao, Zhongming
目的开发有效整合多域数据的计算方法和工具，以开发新的靶向癌症治疗方法。方法我们提出了一种基于网络的综合基础设施，通过靶向人类癌症基因组中发现的显著突变基因（SMG），为现有药物确定新的可药物靶点和抗癌适应症。基本假设是，如果连接性地图中的上调/下调基因往往是SMG或其在人类蛋白质相互作用网络中的邻居，则该药物将具有很高的抗癌适应症潜力。结果我们在29种癌症类型中组装和策划了693个SMG，并发现了已知抗癌或非癌症（重新利用）药物目前靶向的121种蛋白质。我们发现，批准的或实验性的癌症药物可能在33.3%的突变癌症样本中靶向这些SMG，通过调查来自癌症基因组图谱的大约5000个正常肿瘤对的外显子组测序数据，通过药物重新定位，这一数字增加到68.0%。此外，我们确定了284种潜在的新适应症，将28种癌症类型和48种现有药物联系起来（调整后P < .05），文献数据验证的成功率为66.7%。现有的几种药物（例如，氯硝柳胺、丙戊酸、巯甲丙脯酸和白藜芦醇）被预测对多种癌症类型具有潜在的适应症。最后，我们使用综合分析来展示白藜芦醇在乳腺癌和肺癌治疗中的潜在作用机制，即它靶向几种SMG（ARNTL、ASPM、CTTN、EIF 4G 1、FOXP 1和STIP 1）。我们证明了我们的综合网络-基础设施是一个有前途的战略，以确定潜在的药物靶点，并发现新的适应症，现有的药物，以加快分子靶向癌症治疗学
Objective Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics.Methods We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network.Results We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1).Conclusions In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics.