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Functional Module Connectivity Map (FMCM): A Framework for Searching Repurposed Drug Compounds for Systems Treatment of Cancer and an Application to Colorectal Adenocarcinoma

机译:功能模块连接图(FMCM):一种用于系统治疗癌症的搜索重新定位的药物化合物的框架及其在结直肠腺癌中的应用

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摘要

Drug repurposing has become an increasingly attractive approach to drug development owing to the ever-growing cost of new drug discovery and frequent withdrawal of successful drugs caused by side effect issues. Here, we devised Functional Module Connectivity Map (FMCM) for the discovery of repurposed drug compounds for systems treatment of complex diseases, and applied it to colorectal adenocarcinoma. FMCM used multiple functional gene modules to query the Connectivity Map (CMap). The functional modules were built around hub genes identified, through a gene selection by trend-of-disease-progression (GSToP) procedure, from condition-specific gene-gene interaction networks constructed from sets of cohort gene expression microarrays. The candidate drug compounds were restricted to drugs exhibiting predicted minimal intracellular harmful side effects. We tested FMCM against the common practice of selecting drugs using a genomic signature represented by a single set of individual genes to query CMap (IGCM), and found FMCM to have higher robustness, accuracy, specificity, and reproducibility in identifying known anti-cancer agents. Among the 46 drug candidates selected by FMCM for colorectal adenocarcinoma treatment, 65% had literature support for association with anti-cancer activities, and 60% of the drugs predicted to have harmful effects on cancer had been reported to be associated with carcinogens/immune suppressors. Compounds were formed from the selected drug candidates where in each compound the component drugs collectively were beneficial to all the functional modules while no single component drug was harmful to any of the modules. In cell viability tests, we identified four candidate drugs: GW-8510, etacrynic acid, ginkgolide A, and 6-azathymine, as having high inhibitory activities against cancer cells. Through microarray experiments we confirmed the novel functional links predicted for three candidate drugs: phenoxybenzamine (broad effects), GW-8510 (cell cycle), and imipenem (immune system). We believe FMCM can be usefully applied to repurposed drug discovery for systems treatment of other types of cancer and other complex diseases.
机译:由于新药发现的成本不断增加以及由副作用引起的成功药物的频繁撤回,重新利用药物已成为药物开发中越来越有吸引力的方法。在这里,我们设计了功能模块连接图(FMCM),用于发现用于复杂疾病的系统治疗的改用药物化合物,并将其应用于结直肠腺癌。 FMCM使用多个功能基因模块来查询连接图(CMap)。这些功能模块围绕毂基因而构建,这些毂基因是通过疾病发展趋势(GSToP)程序通过基因选择而确定的,而该条件是从由队列基因表达微阵列组构建的条件特异性基因-基因相互作用网络中获得的。候选药物化合物仅限于表现出预计的最小细胞内有害副作用的药物。我们针对以单一基因组为代表的基因组特征来查询CMap(IGCM)的基因组签名选择药物的常规做法,对FMCM进行了测试,发现FMCM在识别已知抗癌药物方面具有更高的鲁棒性,准确性,特异性和可重复性。在FMCM选择用于结直肠腺癌的46种候选药物中,有65%的文献支持与抗癌活性相关,据报道,据预测对癌症有害的药物中有60%与致癌物/免疫抑制剂有关。由选定的候选药物形成化合物,其中每种化合物中的成分药物共同有益于所有功能模块,而没有单一成分的药物对任何模块均有害。在细胞生存力测试中,我们确定了四种候选药物:GW-8510,依他克酸,银杏内酯A和6-氮杂嘧啶,对癌细胞具有高抑制活性。通过微阵列实验,我们证实了三种候选药物的预测新功能链接:苯氧基苯扎明(广泛作用),GW-8510(细胞周期)和亚胺培南(免疫系统)。我们认为,FMCM可以有效地应用于针对其他类型的癌症和其他复杂疾病的系统治疗的改发药物发现。

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