胰腺癌中CDK1的表达与预后的生物信息学分析

Bioinformatics Analysis of CDK1 Expression and Pancreatic Cancer Prognosis

为探讨胰腺癌的发病机制并为胰腺癌的防治提供生物信息学依据,用GEO2R在线工具分析GSE16515中胰腺癌患者肿瘤组织和相应正常组织的差异表达基因(differentially expressed genes,DEGs),通过DAVID数据库对DEGs进行GO分析和KEGG通路富集分析,然后通过STRING数据库构建蛋白质相互作用(protein-protein interaction,PPI)网络,用Cytoscape软件进行关键基因(hub基因)筛选和功能模块分析,并在GEPIA数据库对hub基因进行验证,用CCLE数据库检测靶基因在胰腺癌组织及细胞系中的表达水平。分析结果显示胰腺癌中筛选出的376个DEGs主要涉及细胞周期、p53信号通路、蛋白质消化吸收、ECM-受体相互作用、PI3K-Akt信号通路、血小板激活信号通路。GEPIA数据库验证结果显示10个hub基因均在胰腺癌组织中高表达,其中8个hub基因与胰腺癌患者的不良预后有关。CCLE数据库检测结果显示周期蛋白依赖性激酶1(cyclin-dependent kinase 1,CDK1)在胰腺癌组织和细胞中均有较高的表达水平。本研究结果表明CDK1可能与胰腺癌的发生发展最为相关,为进一步探究胰腺癌的发病机制提供了生物信息学依据。

To explore the pathogenesis of pancreatic cancer and provide bioinformatics basis for the prevention and treatment of pancreatic cancer,the GEO2R online tool was used to analyze the differentially expressed genes(DEGs)between the tumor and normal tissues of pancreatic cancer patients in GSE16515.GO analysis and KEGG pathway enrichment analysis of DEGs were performed using DAVID database.The STRING database was used to construct a protein-protein interaction(PPI)network.The key genes(hub genes)were screened and function modules were analyzed using Cytoscape software.The hub genes were verified in the GEPIA database,and the expression levels of the target genes in pancreatic cancer tissues and cell lines were detected using CCLE database.The results showed that 376 DEGs screened from pancreatic cancer were mainly involved in cell cycle,p53 signaling pathway,protein digestion and absorption,ECM-receptor interaction,PI3K-Akt signaling pathway,and platelet activation signaling pathway.GEPIA database verification showed that 10 hub genes were highly expressed in pancreatic cancer tissues,and 8 hub genes were associated with poor prognosis of pancreatic cancer patients.The CCLE database showed that cyclin-dependent kinase 1(CDK1)had a high expression level in pancreatic cancer tissues and cells.The above results indicated that CDK1 may be the most relevant to the occurrence and development of pancreatic cancer,providing a bioinformatics basis for further exploration of the pathogenesis of pancreatic cancer.