Wang Rongsheng, Chen Xiaohong, Huang Cuilan, Yang Xiaogang, He Huiwei, OuYang Chenghong, Li Hainan, Guo Jinghua, Yang Chunli, Lin Zhiying
Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Front Genet. 2022 Aug 30;13:958213. doi: 10.3389/fgene.2022.958213. eCollection 2022.
Gastric cancer (GC) is a digestive system tumor with high morbidity and mortality. It is urgently required to identify genes to elucidate the underlying molecular mechanisms. The aim of this study is to identify the key genes which may affect the prognosis of GC patients and be a therapeutic strategy for GC patients by bioinformatic analysis. The significant prognostic differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. The protein-protein interaction (PPI) network was established by STRING and screening key genes by MCODE and CytoNCA plug-ins in Cytoscape. Functional enrichment analysis, construction of a prognostic risk model, and nomograms verify key genes as potential therapeutic targets. In total, 997 genes and 805 genes were related to the prognosis of GC in the GSE84437 and TCGA datasets, respectively. We define the 128 genes shared by the two datasets as prognostic DEGs (P-DEGs). Then, the first four genes (, , , and ) with great node importance in the PPI network of P-DEGs were identified as key genes. Independent prognostic risk analysis found that patients with high key gene expression had a poor prognosis, excluding their age, gender, and TNM stage. GO and KEGG enrichment analyses showed that key genes may exert influence through the PI3K-Akt pathway, in which extracellular matrix organization and focal adhesion may play important roles in key genes influencing the prognosis of GC patients. We found that , , , and are potential and reliable prognostic key genes that affect the invasion and migration of gastric cancer.
胃癌（GC）是一种发病率和死亡率都很高的消化系统肿瘤。迫切需要鉴定相关基因以阐明其潜在的分子机制。本研究的目的是通过生物信息学分析鉴定可能影响GC患者预后的关键基因，并为GC患者提供一种治疗策略。从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）数据集中筛选出具有显著预后差异的表达基因（DEGs）。通过STRING建立蛋白质-蛋白质相互作用（PPI）网络，并在Cytoscape中使用MCODE和CytoNCA插件筛选关键基因。功能富集分析、构建预后风险模型和列线图验证关键基因作为潜在的治疗靶点。在GSE84437和TCGA数据集中，分别有997个基因和805个基因与GC的预后相关。我们将两个数据集共有的128个基因定义为预后DEGs（P-DEGs）。然后，在P-DEGs的PPI网络中，将节点重要性高的前四个基因（、、和）鉴定为关键基因。独立预后风险分析发现，关键基因高表达的患者预后较差，且不受其年龄、性别和TNM分期的影响。基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析表明，关键基因可能通过PI3K-Akt信号通路发挥作用，其中细胞外基质组织和粘着斑可能在关键基因影响GC患者预后过程中发挥重要作用。我们发现，、、和是影响胃癌侵袭和迁移的潜在且可靠的预后关键基因。
