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.

中文翻译：

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基于生物信息学分析鉴定与肺腺癌相关的Hub基因

肺腺癌（LUAD）是恶性肺肿瘤之一。但是，其病理尚未完全了解。这项研究的目的是通过生物信息学方法鉴定与LUAD相关的中枢基因。本研究使用了从基因表达综合总线（GEO）数据库下载的三个基因表达数据集，包括GSE116959，GSE74706和GSE85841。使用limma软件包筛选与LUAD相关的差异表达基因（DEG）。通过DAVID网站进行了DEG的基因本体论（GO）和KEGG分析。STRING网站绘制了差异表达基因的蛋白质相互作用（PPI），并将结果导入Cytoscape以进行可视化。然后，使用MCODE对PPI网络进行分析，并使用cytoHubba找到得分大于5的模块。最后，使用GEPIA数据库和UALCAN数据库验证和分析中枢基因的存活。我们从三个LUAD数据集中确定了67个上调基因和277个下调基因。GO分析的结果表明，下调的基因在基质粘附和血管生成中显着富集，而上调的差异基因在细胞粘附和血管发育中显着富集。KEGG通路分析表明，LUAD的差异基因在病毒致癌作用和粘附点上明显丰富。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，得分大于5的三个模块和七个中枢基因，即MCM4，BIRC5，CDC20，CDC25C，FOXM1，GTSE1，筛选出了在PPI网络中起重要作用的RFC4和RFC4。在本研究中，我们获得了与LUAD相关的中枢基因和途径，揭示了LUAD的分子机制和发病机理，这有助于LUAD的早期发现，并为LUAD的治疗提供了新的思路。