癌变·畸变·突变 ›› 2019, Vol. 31 ›› Issue (4): 300-307.doi: 10.3969/j.issn.1004-616x.2019.04.007

• 论著 • 上一篇    下一篇

胃癌基因表达谱芯片差异基因的生物信息学分析

曾蕾1, 徐雪莲1, 罗曼曼1, 张凡1, 韩志坚2, 李玉民1,2   

  1. 1. 兰州大学第二医院普外科, 甘肃 兰州 730030;
    2. 甘肃省消化系统肿瘤重点实验室, 甘肃 兰州 730030
  • 收稿日期:2019-04-08 修回日期:2019-07-02 出版日期:2019-07-30 发布日期:2019-08-23
  • 通讯作者: 李玉民,E-mail:liym@lzu.edu.cn E-mail:liym@lzu.edu.cn
  • 作者简介:曾蕾,E-mail:272956902@qq.com。
  • 基金资助:
    国家自然科学基金项目(31770537);甘肃省科技计划项目(18YF1WA113)

Bioinformatics analyses of differential genes in gastric cancer gene expression profiles

ZENG Lei1, XU Xuelian1, LUO Manman1, ZHANG Fan1, HAN Zhijian2, LI Yumin1,2   

  1. 1. Department of General Surgery, Second Hospital of Lanzhou University, Lanzhou 730030;
    2. The Key Laboratory of the Digestive System Tumors, Lanzhou University, Lanzhou 730030, Gansu, China
  • Received:2019-04-08 Revised:2019-07-02 Online:2019-07-30 Published:2019-08-23

摘要: 目的:筛选胃癌发生发展过程中的关键基因和信号通路,为寻找有价值的胃癌分子标志物提供依据。方法:从GEO数据库下载5个胃癌基因芯片数据集:GSE35809、GSE54129、GSE79973、GSE66229和GSE51105。合并5个数据集中的样本,去除数据集间的批次效应,对合并后的基因表达数据进行标准化,并通过主成分分析监测数据标准化情况。利用R语言中的limma包筛选胃癌组织和正常组织中表达差异的基因。利用DAVID数据库对胃癌发生发展过程中的差异基因进行功能富集分析,并通过STRING数据库和Cytoscape分析差异基因编码蛋白之间的相互作用网络并进行可视化。结果:总共筛选出1 205个差异基因,包括480个上调基因,725个下调基因。差异基因的生物学功能主要富集于细胞-细胞信号传导、炎症反应的调节、细胞粘附、细胞凋亡和离子的跨膜转运。KEGG信号通路分析显示差异基因主要富集于p53信号通路、PI3K-Akt信号通路、NF-κB信号通路。通过构建蛋白质相互作用网络筛选出了CENPEKIF15MELKKIF2CCENPFKIF11NUSAP1UBE2CTTKAURKBDLGAP5TOP2A等29个Hub基因。结论:通过合并不同数据集,利用生物信息学方法筛选出胃癌发生发展过程中的关键基因和信号通路,为胃癌的诊疗提供新的候选标志物。

关键词: 胃癌, 生物信息学分析, 差异表达基因, 基因芯片

Abstract: OBJECTIVE:To screen the key genes and signal pathways in the development of gastric cancer and to provide the basis for finding valuable molecular markers of gastric cancer. METHODS:Five gastric cancer gene chip datasets were downloaded from the GEO database:GSE35809,GSE54129,GSE79973,GSE66229,and GSE51105. The samples in the five data sets were combined,the batch effect between the data sets was removed,the combined gene expression data was normalized,and the data standardization was monitored by principal component analysis. The limma package in the R language was used to screen for differentially expressed genes in gastric cancer tissues and normal tissues. The DAVID database was used to analyze the differential genes in the development of gastric cancer,and the interaction network between the differentially encoded proteins was analyzed and visualized by STRING database and Cytoscape. RESULTS:A total of 1205 differential genes were screened,including 480 up-regulated genes and 725 down-regulated genes. The biological functions of differential genes are mainly enriched in cell-cell signaling,regulation of inflammatory responses,cell adhesion,apoptosis,and transmembrane transport of ions. Analysis of KEGG signaling pathway revealed that differential genes are mainly enriched in the p53,PI3K-Akt and NF-κB signaling pathways. The 29 Hub genes such as CENPE,KIF15,MELK,KIF2C,CENPF,KIF11,NUSAP1,UBE2C,TTK,AURKB,DLGAP5,TOP2A were screened by constructing a protein interaction network. CONCLUSION:By combining different data sets,key genes and signal pathways for the development of gastric cancer were screened by bioinformatics method,providing new research targets for the diagnosis and treatment of gastric cancer.

Key words: gastric cancer, bioinformatics analysis, differentially expressed genes, gene chip

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