Identification of Hub Genes Associated with Lung Adenocarcinoma Based on Bioinformatics Analysis

Comput. Math. Methods Medicine Pub Date : 2021-04-16 DOI:10.1155/2021/5550407

Shuaiqun Wang, Xiaoling Xu, Wei Kong

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引用次数: 1

Abstract

Lung adenocarcinoma (LUAD) is one of the malignant lung tumors. However, its pathology has not been fully understood. The purpose of this study is to identify the hub genes associated with LUAD by bioinformatics methods. Three gene expression datasets including GSE116959, GSE74706, and GSE85841 downloaded from the Gene Expression Omnibus (GEO) database were used in this study. The differentially expressed genes (DEGs) related to LUAD were screened by using the limma package. Gene Ontology (GO) and KEGG analysis of DEGs were carried out through the DAVID website. The protein-protein interaction (PPI) of differentially expressed genes was drawn by the STRING website, and the results were imported into Cytoscape for visualization. Then, the PPI network was analyzed by using MCODE, and the modules with a score greater than 5 were found by using cytoHubba. Finally, the GEPIA database and UALCAN database were used to verify and analyze the survival of hub genes. We identified 67 upregulated genes and 277 downregulated genes from three LUAD datasets. The results of GO analysis showed that the downregulated genes were significantly enriched in matrix adhesion and angiogenesis and upregulated differential genes were significantly enriched in cell adhesion and vascular development. KEGG pathway analysis showed that the differential genes of LUAD were significantly enriched in viral carcinogenesis and adhesion spots. The PPI network of differentially expressed genes consists of 269 nodes and 625 interactions. In addition, three modules with scores greater than 5 and seven hub genes, namely, MCM4, BIRC5, CDC20, CDC25C, FOXM1, GTSE1, and RFC4, playing an important role in the PPI network were screened out. In this study, we obtained the hub genes and pathways related to LUAD, revealing the molecular mechanism and pathogenesis of LUAD, which is helpful for the early detection of LUAD and provides a new idea for the treatment of LUAD.

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基于生物信息学分析的肺腺癌相关枢纽基因鉴定

肺腺癌(LUAD)是肺部恶性肿瘤之一。然而，其病理尚未完全了解。本研究的目的是利用生物信息学方法鉴定与LUAD相关的枢纽基因。本研究使用从gene expression Omnibus (GEO)数据库下载的GSE116959、GSE74706和GSE85841三个基因表达数据集。采用limma包筛选与LUAD相关的差异表达基因(DEGs)。通过DAVID网站对基因本体(Gene Ontology, GO)和KEGG进行分析。通过STRING网站绘制差异表达基因的蛋白-蛋白相互作用(protein-protein interaction, PPI)，并将结果导入Cytoscape进行可视化。然后利用MCODE对PPI网络进行分析，利用cytoHubba找到评分大于5的模块。最后，利用GEPIA数据库和UALCAN数据库对枢纽基因的存活情况进行验证和分析。我们从三个LUAD数据集中鉴定出67个上调基因和277个下调基因。氧化石墨烯分析结果显示，下调基因在基质粘附和血管生成中显著富集，上调差异基因在细胞粘附和血管发育中显著富集。KEGG通路分析显示，LUAD的差异基因在病毒癌变和粘附点显著富集。差异表达基因的PPI网络由269个节点和625个相互作用组成。此外，筛选出在PPI网络中发挥重要作用的3个评分大于5的模块和7个枢纽基因，即MCM4、BIRC5、CDC20、CDC25C、FOXM1、GTSE1和RFC4。本研究获得了与LUAD相关的枢纽基因和通路，揭示了LUAD的分子机制和发病机制，有助于LUAD的早期发现，为LUAD的治疗提供了新的思路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Comput. Math. Methods Medicine

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