Ni Mengwei, Liu Xinkui, Wu Jiarui, Zhang Dan, Tian Jinhui, Wang Ting, Liu Shuyu, Meng Ziqi, Wang Kaihuan, Duan Xiaojiao, Zhou Wei, Zhang Xiaomeng
Department of Clinical Chinese Pharmacy, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China.
Evidence Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China.
Front Genet. 2018 Oct 12;9:469. doi: 10.3389/fgene.2018.00469. eCollection 2018.
Non-small cell lung cancer (NSCLC) accounts for 80-85% of all patients with lung cancer and 5-year relative overall survival (OS) rate is less than 20%, so that identifying novel diagnostic and prognostic biomarkers is urgently demanded. The present study attempted to identify potential key genes associated with the pathogenesis and prognosis of NSCLC. Four GEO datasets (GSE18842, GSE19804, GSE43458, and GSE62113) were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between NSCLC samples and normal ones were analyzed using limma package, and RobustRankAggreg (RRA) package was used to conduct gene integration. Moreover, Search Tool for the Retrieval of Interacting Genes database (STRING), Cytoscape, and Molecular Complex Detection (MCODE) were utilized to establish protein-protein interaction (PPI) network of these DEGs. Furthermore, functional enrichment and pathway enrichment analyses for DEGs were performed by Funrich and OmicShare. While the expressions and prognostic values of top genes were carried out through Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan Meier-plotter (KM) online dataset. A total of 249 DEGs (113 upregulated and 136 downregulated) were identified after gene integration. Moreover, the PPI network was established with 166 nodes and 1784 protein pairs. Topoisomerase II alpha , a top gene and hub node with higher node degrees in module 1, was significantly enriched in mitotic cell cycle pathway. In addition, Interleukin-6 ) was enriched in amb2 integrin signaling pathway. The mitotic cell cycle was the most significant pathway in module 1 with the highest -value. Besides, five hub genes with high degree of connectivity were selected, including , and , and they were all correlated with worse OS in NSCLC. The results showed that , and may be potential key genes, while the mitotic cell cycle pathway may be a potential pathway contribute to progression in NSCLC. Further, it could be used as a new biomarker for diagnosis and to direct the synthesis medicine of NSCLC.
非小细胞肺癌(NSCLC)占所有肺癌患者的80 - 85%,5年相对总生存率(OS)低于20%,因此迫切需要鉴定新的诊断和预后生物标志物。本研究试图鉴定与NSCLC发病机制和预后相关的潜在关键基因。从基因表达综合数据库(GEO)中获取了四个GEO数据集(GSE18842、GSE19804、GSE43458和GSE62113)。使用limma软件包分析NSCLC样本与正常样本之间的差异表达基因(DEGs),并使用RobustRankAggreg(RRA)软件包进行基因整合。此外,利用检索相互作用基因数据库(STRING)、Cytoscape和分子复合物检测(MCODE)建立这些DEGs的蛋白质 - 蛋白质相互作用(PPI)网络。此外,通过Funrich和OmicShare对DEGs进行功能富集和通路富集分析。同时,通过基因表达谱交互式分析(GEPIA)和Kaplan Meier绘图仪(KM)在线数据集分析顶级基因的表达和预后价值。基因整合后共鉴定出249个DEGs(113个上调和136个下调)。此外,建立了包含166个节点和1784个蛋白质对的PPI网络。拓扑异构酶IIα是模块1中具有较高节点度的顶级基因和枢纽节点,在有丝分裂细胞周期途径中显著富集。此外,白细胞介素 - 6在α2整合素信号通路中富集。有丝分裂细胞周期是模块1中具有最高值的最显著途径。此外,选择了五个具有高度连通性的枢纽基因,包括……,它们均与NSCLC患者较差的OS相关。结果表明,……可能是潜在的关键基因,而有丝分裂细胞周期途径可能是促进NSCLC进展的潜在途径。此外,它可作为NSCLC诊断的新生物标志物并指导其合成药物治疗。