通过生物信息学方法筛选胃癌潜在关键基因

Identification of Potential Critical Genes in Gastric Cancer by Bioinformatic Analysis

目的:从公共数据库获取数据,分析胃癌及正常胃组织差异表达基因,初步筛选出潜在生物标志物。方法:从GEO数据库下载与胃癌相关的数据集GSE54129、GSE13911、GSE19826;通过GEO2R 筛选出差异表达基因(DEGs),韦恩图绘制出3个基因表达谱的交集,从而得出共同DEGs;利用DAVID、String、KM-Plot等网站对DEGs进行功能分析、构建蛋白质互作网络(PPI)以及与胃癌预后的关系,利用Cytoscape对分析结果进行可视化处理,得出候选核心基15个;进而用GEPIA软件验证核心基因的表达情况以及与临床分期的关系,并使用cBioPortal探索胃癌靶点基因的基因组变化,最终筛选出6个与胃癌预后、分期相关的核心基因。结果:获得106个DEGs,功能富集分析显示这些DEGs的作用以蛋白降解、细胞粘附为主;在细胞组分中主要影响胞外间隙;在分子功能中主要影响相同蛋白结合;通路富集分析主要集中于胃酸分泌、蛋白质消化吸收、细胞色素P450的药物代谢等,12个基因(COL1A1, COL1A2, COL11A1, COL10A1, BGN, TFF2, MUC6, ATP4A, THBS2, SULF1, CLDN18, ATP4B)与GC总生存期相关,其中6个关键基因(COL1A1, COL1A2, THBS2, BGN, TFF2, COL11A1)与胃癌的分期密切相关。结论:通过生物信息学筛选差异表达基因和信号通路可能有助于胃癌的分子机制研究,并获得与胃癌生存预后相关的关键基因,为癌症的诊断和治疗提供了新的思路。

Objective: Data were obtained from public databases to analyze differentially expressed genes in gastric cancer (GC) and normal gastric tissue, and preliminarily explore potential biomarkers. Method: Gene expression profiles (GSE54129, GSE13911, GSE19826) were obtained from GEO da-tabase. Differentially expressed genes were screened out by GEO2R, and the Venndiagram plotted the intersection of three gene expression profiles to obtain common differentially expressed Genes;using online analysis websites such as DAVID, String, KM-Plot to analyze the functions of DEGs, con-struct protein interaction network (PPI) and the relationship with GC prognosis, and visualize the analysis results with Cytoscape, 15 candidate core genes were obtained;furthermore, GEPIA online software was used to verify the expression of core genes and the relationship with clinical stage, and the genomic changes of GC target genes were explored by using cBioPortal, and finally six core genes related to GC prognosis and stage were screened. Results: A total of 106 DEGs were obtained, and functional enrichment analysis showed that the effects of these DEGs were mainly protein degrada-tion and cell adhesion. Predominantly affects the extracellular space in cellular components;mainly affects the same protein binding in molecular function;pathway enrichment analysis mainly fo-cused on gastric acid secretion, protein digestion and absorption, cytochrome P450 drug metabo-lism, etc, 12 genes (COL1A1, COL1A2, COL11A1, COL10A1, BGN, TFF2, MUC6, ATP4A, THBS2, SULF1, CLDN18, ATP4B) were associated with GC overall survival, of which 6 key genes (COL1A1, COL1A2, THBS2, BGN, TFF2, COL11A1) is closely related to the staging of gastric cancer. Conclusion: Screen-ing of differentially expressed genes and signalling pathways by bioinformatics may contribute to the study of the molecular mechanism of gastric cancer and obtain key genes related to the survival and prognosis of gastric cancer, providing new ideas for cancer diagnosis and treatment.