The Second Clinical Medical College, Guangdong Medical University, Dongguan, China.
Department of Respiratory, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Biomed Res Int. 2023 Jan 18;2023:2152432. doi: 10.1155/2023/2152432. eCollection 2023.
To analyze and identify the core genes related to the expression and prognosis of lung cancer including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by bioinformatics technology, with the aim of providing a reference for clinical treatment.
Five sets of gene chips, GSE7670, GSE151102, GSE33532, GSE43458, and GSE19804, were obtained from the Gene Expression Omnibus (GEO) database. After using GEO2R to analyze the differentially expressed genes (DEGs) between lung cancer and normal tissues online, the common DEGs of the five sets of chips were obtained using a Venn online tool and imported into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein-protein interaction (PPI) network was constructed by STRING online software for further study, and the core genes were determined by Cytoscape software and KEGG pathway enrichment analysis. The clustering heat map was drawn by Excel software to verify its accuracy. In addition, we used the University of Alabama at Birmingham Cancer (UALCAN) website to analyze the expression of core genes in P53 mutation status, confirmed the expression of crucial core genes in lung cancer tissues with Gene Expression Profiling Interactive Analysis (GEPIA) and GEPIA2 online software, and evaluated their prognostic value in lung cancer patients with the Kaplan-Meier online plotter tool.
CHEK1, CCNB1, CCNB2, and CDK1 were selected. The expression levels of these four genes in lung cancer tissues were significantly higher than those in normal tissues. Their increased expression was negatively correlated with lung cancer patients (including LUAD and LUSC) prognosis and survival rate.
CHEK1, CCNB1, CCNB2, and CDK1 are the critical core genes of lung cancer and are highly expressed in lung cancer. They are negatively correlated with the prognosis of lung cancer patients (including LUAD and LUSC) and closely related to the formation and prediction of lung cancer. They are valuable predictors and may be predictive biomarkers of lung cancer.
通过生物信息学技术分析和鉴定与肺癌（包括肺腺癌 [LUAD] 和肺鳞状细胞癌 [LUSC]）表达和预后相关的核心基因，为临床治疗提供参考。
从基因表达综合数据库（GEO）中获取了 GSE7670、GSE151102、GSE33532、GSE43458 和 GSE19804 共 5 套基因芯片。在线使用 GEO2R 分析癌症与正常组织之间的差异表达基因（DEGs）后，使用 Venn 在线工具获取 5 套芯片的共有 DEGs，将其导入 DAVID 数据库进行基因本体论（GO）富集和京都基因与基因组百科全书（KEGG）通路分析。使用 STRING 在线软件构建蛋白质-蛋白质相互作用（PPI）网络，进一步研究核心基因。通过 Cytoscape 软件和 KEGG 通路富集分析确定核心基因。使用 Excel 软件绘制聚类热图以验证其准确性。此外，我们使用阿拉巴马大学伯明翰分校癌症数据库（UALCAN）网站分析 P53 突变状态下核心基因的表达，使用在线软件基因表达谱分析交互式分析（GEPIA）和 GEPIA2 验证关键核心基因在肺癌组织中的表达，并使用 Kaplan-Meier 在线绘图器工具评估其在肺癌患者中的预后价值。
筛选出 CHEK1、CCNB1、CCNB2 和 CDK1。这四个基因在肺癌组织中的表达水平明显高于正常组织。它们的高表达与肺癌患者（包括 LUAD 和 LUSC）的预后和生存率呈负相关。
CHEK1、CCNB1、CCNB2 和 CDK1 是肺癌的关键核心基因，在肺癌中高表达。它们与肺癌患者（包括 LUAD 和 LUSC）的预后呈负相关，与肺癌的发生和预测密切相关。它们是有价值的预测因子，可能是肺癌的预测生物标志物。
