摘要
目的:通过生物信息学方法挖掘膀胱癌(BLCA)致病的关键基因。方法:从TCGA公共数据库中提取19例正常膀胱组织、409例BLCA组织以及患者的临床信息。利用R 4.4.0软件及Limma、DESeq2和edgeR包进行分析筛选差异表达基因(DEGs),并使用VennDiagram包绘制韦恩图,取交集得到最终数据集,再用DAVID数据库对DEGs进行信号通路富集基因本体(GO)和京都基因组与基因组百科全书(KEGG)分析,然后进一步使用STRING数据库进行构建蛋白质相互作用网络(PPI),并应用Cytoscape(3.8.2版本)进行共表达关系的可视化和筛选最终的关键基因。最后应用GEPIA 2.0等数据库对最终的关键基因进行进一步验证分析。结果:对TCGA数据库中的BLCA数据进行分析的结果表明CENPA、CDK1、HJURP三个关键基因在BLCA组织中远高于膀胱正常组织,并在多个通路中起到关键作用。结论:本研究利用生物信息学分析出CENPA、CDK1、HJURP三个关键基因,为后续BLCA的基础研究与临床治疗提供了新靶点。
Objective To identify key genes involved in the pathogenesis of bladder cancer(BLCA)through bioinformatics approaches.Methods Clinical data and gene expression profiles from 19 normal bladder tissues and 409 BLCA tissues were extracted from the TCGA public database.Differentially expressed genes(DEGs)were identified using R 4.4.0 software with the Limma,DESeq2,and edgeR packages.A Venn diagram was generated using the VennDiagram package to obtain the intersection of the DEGs,forming the final dataset.Subsequently,Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses were performed using the DAVID database.A protein-protein interaction(PPI)network was constructed using the STRING database,and Cytoscape(version 3.8.2)was used for visualization and selection of the key genes based on co-expression relationships.Finally,further analysis of the key genes was conducted using data from GEPIA 2.0.Results Analysis of the BLCA data from the TCGA database revealed that the key genes CENPA,CDK1,and HJURP were significantly over-expressed in BLCA tissues compared to normal bladder tissues and may play critical roles in multiple pathways.Conclusion This study identified CENPA,CDK1,and HJURP as key genes involved in bladder cancer,providing new targets for further basic research and clinical treatment of BLCA.
作者
李琳
汤磊
赵亚伟
马柳疆
李前跃
LI Lin;TANG Lei;ZHAO Yawei;MA Liujiang;LI Qianyue(Medical School of Shihezi University,Xinjiang Shihezi 832000;Department of Urology,The Second Affiliated Hospital of Shihezi University,Xinjiang Production and Construction Corps Hospital,Xinjiang Urumqi 830000)
出处
《兵团医学》
2024年第4期1-5,73,共6页
Journal of BingTuan Medicine
基金
兵团重点领域科技攻关计划(2021AB036)
关键词
膀胱癌
生物信息学
差异表达基因
靶点
Bladder cancer
Bioinformatics
Differentially expressed gene
Target point
