肝癌相关基因的生物信息学分析及功能预测  

Bioinformatic analysis and functional prediction of liver cancer related genes

作　　者：陈林波 李先鹏 姜昊 曾丽丽 郑静蕾 许丰 CHen Linbo;Li Xianpeng;Jiang Hao;Zeng Lili;ZHeng Jinglei;Xu Feng(Department of gastroenterology,ningbo Yinzhou People＇s Hospital,ningbo,315040;Department of infectious Diseases,ningbo Yinzhou People＇s Hospital,ningbo,315040;Department of endoscopy Center,ningbo Yinzhou People＇s Hospital,ningbo,315040)

机构地区：[1]宁波市鄞州人民医院消化内科,浙江宁波315040 [2]宁波市鄞州人民医院,感染科浙江宁波315040 [3]宁波市鄞州人民医院内镜中心,浙江宁波315040

出　　处：《温州医科大学学报》2018年第11期828-832,共5页Journal of Wenzhou Medical University

摘　　要：目的:应用生物信息学技术探索肝癌发病机制。方法:从公共数据库(GEO)下载肝癌相关基因芯片并用R语言筛选差异表达基因,用GO分析和KEGG信号通路分析对差异表达基因进行功能注释,之后构建蛋白质相互作用网络筛选关键基因,最后在GEPIA数据库对关键基因进行验证。结果:共筛选出154个在肝癌中差异表达的基因,GO分析显示差异表达基因生物学功能主要涉及端粒合成、DNA复制和基因表达调控,KEGG分析显示差异表达基因主要和矿物质吸收、系统性红斑狼疮、肿瘤细胞碳代谢等通路有关。蛋白质相互作用网络筛选出TOP2A、CENPF、ASPM、NEK2、CCNA2、PRC1、MELK、CCNB2、RACGAP1、NUSAP1 10个关键基因。GEPIA数据库验证结果显示10个基因均在肝癌组织中高表达,并和肝癌患者的不良预后有关。结论:生物信息学能有效筛选和分析肝癌相关差异表达基因,并为进一步探索肝癌发病机制提供理论依据。Objective： To explore the mechanism of liver cancer based on bioinformatics. Methods： Mi-croarray data of Liver cancer related genes were obtained from Gene Expression Omnibus （GEO） database and DEGs were identifed using R software. Functional annotations of DEGs were conducted by gene ontology （GO） and Kyoto encyclopedia of genes and genomes （KEGG）. Then, a protein-protein interaction （PPI） network was constructed to screen hub genes. Finally, the hub genes were verifed by GEPIA. Results： A total of 154 differ-entially expressed genes were identifed in liver cancer. GO enrichment analysis revealed that DEGs were mainly involved in telomere organization, DNA replication and regulation of gene expression. KEGG pathway analysis was mainly related to mineral absorption, systemic lupus erythematosus and carbon metabolism in cancer. Ten hub genes including TOP2a, CenPF, aSPM, neK2, CCna2, PRC1, MeLK, CCnB2, RaCgaP1 and nuSaP1 were screened out by constructing PPI network. Subsequent validation in GEPIA database showed that all these 10 genes were up-regulated in liver cancer and associated with the prognosis of liver cancer patients. Conclu-sion： Bioinformatics can effectively screen and analyze liver cancer related DEGs, which may provide theoretical reference for further exploration of the liver cancer mechanism.

关 键 词：肝肿瘤 关键基因 生物信息学 

分 类 号：R735.7[医药卫生—肿瘤]