Identification of hub genes and potential molecular mechanisms in gastric cancer by integrated bioinformatics analysis.
Identification of hub genes and potential molecular mechanisms in gastric cancer by integrated bioinformatics analysis.
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作者：
Cao L;Chen Y;Zhang M;Xu DQ;Liu Y;Liu T;Liu SX;Wang P
胃癌(GC)是世界上第四大与癌症相关的死亡原因。在目前的研究中，我们的目标是识别HUB基因，并揭示GC的分子机制。从基因表达总览数据库中提取基因和miRNAs的表达谱。利用GEO2R对包括miRNAs在内的差异表达基因(Deg)进行鉴定。使用注释、可视化和集成发现数据库进行GO和KEGG途径富集化分析。用Cytoscape软件构建蛋白质-蛋白质相互作用(PPI)网络和miRNA-基因网络。HUB基因通过分子复合体检测(MCODE)插件、CytoHubba插件和miRNA-基因网络进行鉴定。然后，利用Kaplan-Meier数据库和定量实时聚合酶链式反应(qRT-PCR)在胃癌组织标本中验证所识别的基因。从基因表达总表(GEO)数据库中下载3个基因表达谱(、和)，分别包括69例、20例和27例。共鉴定出120个上调基因和246个下调基因。细胞外基质组织、胶原分解过程、胶原原纤维组织和细胞黏附丰富。此外，细胞外基质-受体相互作用、蛋白质消化吸收和局灶性黏附等3条KEGG途径也显著丰富。在PPI网络中，检测到5个重要的模块，这些模块中的基因主要参与ECM-受体相互作用和焦点黏附途径。结合MCODE、CytoHubba和miRNA基因网络的结果，共筛选出COL1A2、COL1A1、COL4A1、COL5A2、THBS2和ITGA5等6个HUB基因。Kaplan-Meier绘图仪数据库证实，除COL5A2外，这些基因的高表达水平与较低的总体存活率有关。实验验证表明，其余五个基因的表达趋势与预测一致。综上所述，COL1A2、COL1A1、COL4A1、THBS2和ITGA5可能是胃癌的潜在生物标志物和治疗靶点。此外，ECM-受体相互作用和焦点黏附通路在GC的进展中起着重要作用。
Gastric cancer (GC) is the fourth most common cause of cancer-related deaths in the world. In the current study, we aim to identify the hub genes and uncover the molecular mechanisms of GC. The expression profiles of the genes and the miRNAs were extracted from the Gene Expression Omnibus database. The identification of the differentially expressed genes (DEGs), including miRNAs, was performed by the GEO2R. Database for Annotation, Visualization and Integrated Discovery was used to perform GO and KEGG pathway enrichment analysis. The protein–protein interaction (PPI) network and miRNA-gene network were constructed using Cytoscape software. The hub genes were identified by the Molecular Complex Detection (MCODE) plugin, the CytoHubba plugin and miRNA-gene network. Then, the identified genes were verified by Kaplan–Meier plotter database and quantitative real-time PCR (qRT-PCR) in GC tissue samples. A total of three mRNA expression profiles (, and ) were downloaded from the Gene Expression Omnibus (GEO) database, including 69, 20 and 27cases separately. A total of 120 overlapped upregulated genes and 246 downregulated genes were identified. The majority of the DEGs were enriched in extracellular matrix organization, collagen catabolic process, collagen fibril organization and cell adhesion. In addition, three KEGG pathways were significantly enriched, including ECM-receptor interaction, protein digestion and absorption, and the focal adhesion pathways. In the PPI network, five significant modules were detected, while the genes in the modules were mainly involved in the ECM-receptor interaction and focal adhesion pathways. By combining the results of MCODE, CytoHubba and miRNA-gene network, a total of six hub genes including COL1A2, COL1A1, COL4A1, COL5A2, THBS2 and ITGA5 were chosen. The Kaplan–Meier plotter database confirmed that higher expression levels of these genes were related to lower overall survival, except for COL5A2. Experimental validation showed that the rest of the five genes had the same expression trend as predicted. In conclusion, COL1A2, COL1A1, COL4A1, THBS2 and ITGA5 may be potential biomarkers and therapeutic targets for GC. Moreover, ECM-receptor interaction and focal adhesion pathways play significant roles in the progression of GC.
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