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基于生物信息学分析鉴定胰腺癌的关键生物标志物

Identification of Key Biomarkers in Pancreatic Cancer Via Bioinformatic Analysis
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摘要 针对胰腺癌临床症状隐匿、诊断及治疗困难等特点,利用生物信息学技术,旨在鉴定可能参与PC发生或发展的差异表达基因(differentially expressed genes,DEGs),为该疾病的早期诊断和预防提供理论支持。从GEO数据库下载3个与PC相关的mRNA微阵列数据集(GSE41368、GSE91035、GSE43795),并通过GEO2R筛选DEGs,筛选条件为校正后的p值<0.05和|log 2 fold change|>1.5。对DEGs进行GO和KEGG通路富集分析,构建蛋白质-蛋白质互作网络并进行模块分析,利用Cytoscape的MCODE插件识别中心基因,并进行生存分析,在其他数据库中对感兴趣的中心基因进行组分表达和临床相关性分析,以探索和验证基因表达与疾病的关系,共鉴定出236个DEGs,揭示其涉及的生物学功能和过程,其中20个基因被鉴定为中心基因。生存分析显示:PSAT1、CYB5A、GMNN、DDX60、CCL20、ALB、PDIA2高表达、F8低表达的胰腺癌患者总生存期较差,CTRC、CLPS、DDX60、CCL20、SYCN、CELA2A、PNLIPRP1、CELA2B高表达的胰腺癌患者无复发生存期较差。DDX60、CCL20在癌组织与正常组织之间的差异表达分析显示,总生存期和无复发生存期分析均存在显著相关性,提示它们可能在PC的发生或发展中起重要作用。 Given that pancreatic cancer(PC)has insidious clinical symptoms and is difficult to diagnose and treat,this study aimed to identify differentially expressed genes(DEGs)that may be involved in the occurrence or development of PC using bioinformatics technology to provide theoretical support for the early diagnosis and prevention of this disease.Three PC-related mRNA microarray datasets(GSE41368,GSE91035,GSE43795)were downloaded from the GEO database,and DEGs were screened by GEO2R with adjusted P value<0.05 and|log 2 fold change|>1.5.GO and KEGG pathway enrichment analyses,construction of protein-protein interaction network and modular analysis were performed for DEGs.The hub genes were identified using Cytoscape's MCODE plugin,and survival analysis was performed.In addition,component expression and oncomine analyses of hub genes of interest were performed in different databases to explore and validate the relationship between gene expression and disease.A total of 236 DEGs were identified and revealed the biological functions and processes involved.20 genes were identified as hub genes.Survival analysis showed that PC patients with high expression of PSAT1,CYB5A,GMNN,DDX60,CCL20,ALB,PDIA2 and low expression of F8 had poorer overall survival,and PC patients with high expression of CTRC,CLPS,DDX60,CCL20,SYCN,CELA2A,PNLIPRP1 and CELA2B had worse relapse free survival.Analysis of the differential expression of DDX60 and CCL20 between cancerous and normal tissues showed significant correlations in both overall and relapse free survival analyses,suggesting that they may play an important role in the development or progression of PC.The identified DEGs and hub genes in this study may provide insight into the molecular mechanisms of PC,which could be useful for early diagnosis and treatment of PC.
作者 邓颖 刘迪 杨宁 邓文文 王军 DENG Ying;LIU Di;YANG Ning;DENG Wenwen;WANG Jun(School of Life Science and Health Engineering,Hubei Univ.of Tech.,Wuhan 430068,China)
出处 《湖北工业大学学报》 2024年第4期41-49,共9页 Journal of Hubei University of Technology
基金 湖北省教育厅创新团队计划项目(6101/12267)。
关键词 生物信息学分析 胰腺癌 差异表达基因 bioinformatic analysis pancreatic cancer differentially expressed genes
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