[1]吴良银a,李文丽b,刘　俊b.基于GEO数据的病毒相关性肝癌潜在生物基因标志物的筛选及生物信息学分析[J].现代检验医学杂志,2021,36(06):106-110.[doi:10.3969/j.issn.1671-7414.2021.06.022]
　WU Liang-yin,LI Wen-li,LIU Jun.Screening and Bioinformatics Analysis of Potential Biomarkers for Virus-associated Hepatocellular Carcinoma Based on GEO Data[J].Journal of Modern Laboratory Medicine,2021,36(06):106-110.[doi:10.3969/j.issn.1671-7414.2021.06.022]
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基于GEO数据的病毒相关性肝癌潜在生物基因标志物的筛选及生物信息学分析()
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《现代检验医学杂志》[ISSN:/CN:]

卷:
第36卷
期数:
2021年06期
页码:
106-110
栏目:
论　著
出版日期:
2021-12-15

文章信息/Info

Title:
Screening and Bioinformatics Analysis of Potential Biomarkers for Virus-associated Hepatocellular Carcinoma Based on GEO Data
文章编号:
1671-7414（2021）06-106-05
作者:
吴良银a; 李文丽b; 刘　俊b
（粤北人民医院a.检验科；b.生殖医学中心，广东韶关 512025）
Author(s):
WU Liang-yin;  LI Wen-li;  LIU Jun
（a.Department of Clinical Laboratory;b. Reproductive Center,Northern Guangdong People’s Hospital,Guangdong Shaoguan 512025,China）
关键词:
肝细胞癌; 生物信息学; 生物标志物
分类号:
R735.7；R730.43
DOI:
10.3969/j.issn.1671-7414.2021.06.022
文献标志码:
A
摘要:
目的　利用生物信息学分析方法，探索在肝细胞癌预后评估中扮演重要角色的潜在生物标志物。方法　从基因表达综合数据库（gene expression omnibus database，GEO）中收集2019年1月1日～2021年1月1日三个病毒相关性肝细胞癌的转录数据集,共含有52个肝细胞癌肿瘤组织和33个肝细胞癌旁组织（对照组），通过GEO2R进行差异基因的鉴定。利用韦恩图绘制三个数据集的共同差异基因，使用DAVID数据库对共同差异基因进行基因功能富集分析，包括基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析。通过STRING数据库和Cytoscape软件构建蛋白互作网络，根据蛋白之间的连接度，筛选和鉴定出关键基因。基于Kaplan-Meier方法及cBioPortal在线工具，分析关键基因表达与生存预后的相关性。结果　基于三个芯片数据集，共筛选出423个共同差异表达的基因，这些基因主要富集到细胞分裂以及氧化还原等细胞生物学过程；蛋白互作网络共聚焦到20个关键基因，其中BUB1, BUB1B, CDC20, NCAPG, TPX2和UBE2C的表达改变与不良临床结局之间存在显著的相关性。结论　BUB1, BUB1B, CDC20, NCAPG, TPX2和UBE2C在病毒相关性肝细胞癌中异常高表达并且与临床预后相关，可作为病毒相关性肝细胞癌的潜在生物标志物及治疗靶点。
Abstract:
Objective　To explore the potential biomarkers that play an important role in the prognosis of hepatocellular carcinoma (HCC) by bioinformatics analysis. Methods　Three transcriptional data sets of virus associated hepatocellular carcinoma (HCC) from January 1, 2019 to January 1, 2021 were collected from gene expression omnibus database (GEO). There were 52 HCC tumor tissues and 33 paracancerous tissues (control group). The differential genes were identified by GEO2R.The common differential genes of the three datasets were drawn by using Wayne map.The gene function enrichment analysis of the common differential genes was carried out by using DAVID database, including gene ontology (GO) and Kyoto Encyclopedia of genes and genomes (KEGG). The protein interaction network was constructed by using string database and Cytoscape software. The key genes were screened and identified according to the connectivity between proteins. Based on Kaplan-Meier method and cbioportal online tool, the correlation between key gene expression and survival prognosis was analyzed. Results　Based on the three microarray datasets, a total of 423 differentially expressed genes were screened, which were mainly enriched in cell division, redox and other cell biological processes. Protein interaction network focused on 20 key genes, among which the expression changes of BUB1, BUB1B, CDC20, NCAPG, TPX2 and UBE2C were significantly correlated with adverse clinical outcomes. Conclusion　Bub1, BUB1B, CCDC20, NCAPG, TPX2 and UBE2C are highly expressed in viral associated hepatocellular carcinoma and associated with clinical prognosis. They can be used as potential biomarkers and therapeutic targets for viral associated hepatocellular carcinoma.

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更新日期/Last Update: 1900-01-01