摘要
目的:侵袭性的肺腺癌(LUAD)是引起肺癌死亡的主要原因之一。因此,鉴定重要的LUAD相关基因及进一步分析其预后意义对于LUAD患者的生存率至关重要。方法:采用加权基因共表达网络分析(WGCNA)和差异基因表达分析方法,从TCGA-LUAD数据库和GEO的GSE32863筛选出有差异的共表达基因,对其进行功能富集分析和蛋白质相互作用网络(PPI)分析。此外,通过应用Cytoscape的CytoHubba插件来识别12个核心基因进行生存分析和肿瘤分期相关性的分析。结果:从TCGA和GEO数据库中共提取了358个差异共表达基因。这些基因在GO分析中主要富集于细胞外结构组织,细胞–细胞连接和DNA结合转录酶激活活性。在KEGG分析中,主要富集于药物代谢–细胞色素P450。此外,在PPI网络中鉴定了12个核心基因。在LUAD患者中,ADCY4、VIPR1和TGFBR2的表达水平与临床分期和整体生存率(OS)相对应。结论:ADCY4、VIPR1和TGFBR2可能在肿瘤发生中起重要作用,因此它们可作为LUAD的预后生物标志物和治疗靶点。
Objective: Lung cancer-related death is mainly caused by lung adenocarcinoma (LUAD), an aggressive malignant tumor. Therefore, the identification of important LUAD-related genes and the further analysis of its prognostic significance are critical for the survival of LUAD patients. Method: Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods were adopted to screen out TCGA-LUAD database and the gene expression profiles of GSE32863 from GEO. Functional annotation analysis and protein-protein interaction (PPI) network were conducted on differential co-expression genes. Furthermore, survival analysis was carried out on twelve hub genes that were identified by applying the CytoHubba plugin of Cytoscape. Results: A total of 358 differential co-expression genes were extracted from the database of TCGA and GEO. These genes were mainly enriched in extracellular structure organization, cell-cell junction and DNA-binding transcription activator activity. In the KEGG analysis, the main pathways were Drug metabolism-cytochrome P450. Moreover, in a PPI network, the 12 hub genes were identified. The expression level of ADCY4, VIPR1, and TGFBR2 was corresponded with clinical stages and overall survival (OS) in LUAD patients. Conclusion: ADCY4, VIPR1 and TGFBR2 may play an important role in the mechanism of the tumorigenesis, so they will serve as prognostic biomarkers and therapeutic targets of LUAD in the future.
出处
《临床医学进展》
2021年第7期2970-2977,共8页
Advances in Clinical Medicine