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内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者机构:Univ Texas Austin Inst Computat Engn & Sci Austin TX 78712 USA Univ Texas Austin Ctr Syst & Synthet Biol Austin TX 78712 USA Univ Texas Austin Dept Mol Biosci Austin TX 78712 USA Univ Texas SW Med Ctr Dallas Hamon Ctr Therapeut Oncol Res Dallas TX 75390 USA Yonsei Univ Coll Med Severance Biomed Sci Inst Seoul South Korea Univ Texas SW Med Ctr Dallas Dept Cell Biol Dallas TX 75390 USA
出 版 物:《BIOINFORMATICS》 (生物信息学)
年 卷 期:2016年第32卷第9期
页 面:1373-1379页
核心收录:
学科分类:0710[理学-生物学] 08[工学] 0714[理学-统计学(可授理学、经济学学位)] 0836[工学-生物工程] 0812[工学-计算机科学与技术(可授工学、理学学位)]
基 金:Cancer Prevention and Research Institute of Texas (CPRIT) National Institutes of Health National Science Foundation Welch Foundation [F1515]
主 题:Lungs -- Cancer Cancer genetics Cancer patients Cell lines Computer algorithms
摘 要:Motivation: Novel approaches are needed for discovery of targeted therapies for non-small-cell lung cancer (NSCLC) that are specific to certain patients. Whole genome RNAi screening of lung cancer cell lines provides an ideal source for determining candidate drug targets. Results: Unsupervised learning algorithms uncovered patterns of differential vulnerability across lung cancer cell lines to loss of functionally related genes. Such genetic vulnerabilities represent candidate targets for therapy and are found to be involved in splicing, translation and protein folding. In particular, many NSCLC cell lines were especially sensitive to the loss of components of the LSm2-8 protein complex or the CCT/TRiC chaperonin. Different vulnerabilities were also found for different cell line subgroups. Furthermore, the predicted vulnerability of a single adenocarcinoma cell line to loss of the Wnt pathway was experimentally validated with screening of small-molecule Wnt inhibitors against an extensive cell line panel.