游路宽, 郑轩, 胡毅. 肺鳞癌潜在关键基因的生物信息学分析[J]. 解放军医学院学报, 2018, 39(10): 903-909,918. DOI: 10.3969/j.issn.2095-5227.2018.10.017
引用本文: 游路宽, 郑轩, 胡毅. 肺鳞癌潜在关键基因的生物信息学分析[J]. 解放军医学院学报, 2018, 39(10): 903-909,918. DOI: 10.3969/j.issn.2095-5227.2018.10.017
YOU Lukuan, ZHENG Xuan, HU Yi. Bioinformatics analysis of potential crucial genes in lung squamous cell cancer[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2018, 39(10): 903-909,918. DOI: 10.3969/j.issn.2095-5227.2018.10.017
Citation: YOU Lukuan, ZHENG Xuan, HU Yi. Bioinformatics analysis of potential crucial genes in lung squamous cell cancer[J]. ACADEMIC JOURNAL OF CHINESE PLA MEDICAL SCHOOL, 2018, 39(10): 903-909,918. DOI: 10.3969/j.issn.2095-5227.2018.10.017

肺鳞癌潜在关键基因的生物信息学分析

Bioinformatics analysis of potential crucial genes in lung squamous cell cancer

  • 摘要: 目的 初步探索肺鳞癌发生发展相关差异表达基因,筛选肺鳞癌治疗潜在药物靶点。 方法 从公共基因表达数据库(GEO)下载肺鳞癌相关芯片数据,利用R语言Limma程序包筛选差异表达基因,对差异表达基因进行GO和KEGG富集分析、蛋白相互作用网络分析及网络关键基因生存分析。 结果 筛选出共有差异表达基因628个,其中上调基因263个,下调基因365个。对共有差异基因进行生物信息学相关分析,发现细胞周期、p53信号通路、ECM分子相关作用、DNA错配修复、PPAR信号通路、细胞黏附分子等信号通路与肺鳞癌发生发展有关。同时筛选出了MAD2L1、CCNB1、DLGAP5、CDC20、TOP2A、MELK、BUB1B、CCNA2、CDK1、CCNB2 10个关键基因,这些关键基因在肺鳞癌组织中全部表达上调且与患者预后相关。 结论 筛选出的差异基因和信号通路有助于加深对肺鳞癌发病分子机制的理解,同时为临床靶向治疗的研究提供一定的理论依据。

     

    Abstract: Objective To explore the differentially expressed genes related to the occurrence and development of squamous cell lung cancer along with screening out potential drug targets. Methods The microarray data associated with squamous cell lung cancer were obtained from GEO database and identified differentially expressed genes (DEGs) based on Limma package of R statistical software.Gene ontology (GO) and KEGG enrichment analysis, protein-protein interaction (PPI) network analysis, and survival analysis for network hub genes were performed. Results A total of 628 DEGs (263 up-regulated and 365 down-regulated) were identified. Based on these DEGs, a number of bio-pathways appeared to be altered in squamous cell lung cancer, including cell cycle, p53 signaling pathway, ECM-receptor interaction, Mismatch repair, PPAR signaling pathway and Cell adhesion molecules (CAMs). The top 10 centrality hub genes MAD2L1, CCNB1, DLGAP5, CDC20, TOP2A, MELK, BUB1B, CCNA2, CDK1 and CCNB2 were identified from the PPI network and they were associated with prognosis of patients. Conclusion The present study identifies hub genes and signal pathways, which benefits us to get insight into the molecular mechanisms of carcinogenesis and development of the disease, and it may provide a theoretical basis for the study of clinical targeted therapy.

     

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