乳腺癌关键基因的生物信息学分析

doi:10.3969/j.issn.1000-8535.2021.01.013

广州医药 ›› 2021, Vol. 52 ›› Issue (1): 65-71.DOI: 10.3969/j.issn.1000-8535.2021.01.013

乳腺癌关键基因的生物信息学分析

李淑怡, 黄玉珍, 蓝秀万

广西医科大学基础医学院(南宁 530021)

收稿日期:2020-06-18 出版日期:2021-01-20 发布日期:2021-11-22
通讯作者: 蓝秀万,E-mail:lanxiuwan@163.com

Bioinformatic analysis of key genes in breast cancer

LI Shuyi, HUANG Yuzhen, LAN Xiuwan

School of Basic Medicine, Guangxi Medical University, Nanning 530021,China

Received:2020-06-18 Online:2021-01-20 Published:2021-11-22

摘要/Abstract

摘要： 目的乳腺癌是世界范围内最常见的恶性肿瘤之一。目前,人们对乳腺癌的发病机制进行了大量的研究,但对其分子机制的认识尚不清楚。本研究采用生物信息学技术,筛选乳腺癌潜在的关键基因,最终为乳腺癌的诊断、治疗及预后判断提供潜在的生物标记物。方法从基因表达综合数据库(GEO)下载基因芯片GSE36295、GSE71053和GSE86374,通过GEO2R鉴定差异表达基因(DEGs),并进行功能富集分析。利用STRING构建了蛋白质-蛋白质相互作用网络(PPI),并采用Cytoscape进行了模块分析。结果共鉴定出95个DEGs,包括62个上调基因和33个下调基因。共鉴定出10个Hub基因:CENPF、KIF2C、TOP2A、NUSAP1、HMMR、MELK、KIF4A、ASPM、CEP55、CCNB1。结论本研究发现的Hub基因可能对乳腺癌的发展和预后存在一定影响,为乳腺癌的诊断和治疗提供候选靶点。

关键词: 乳腺癌, 差异基因, 生物信息学, 生存率

Abstract: Objective Breast cancer is one of the most common cancers worldwide. At present, a lot of researches have been carried out on the pathogenesis of breast cancer, but the molecular mechanisms of breast cancer are still not well understood. In this study, bioinformatics technology was used to screen the potential key genes of breast cancer, and ultimately to provide potential biomarkers for the diagnosis, treatment and prognosis of breast cancer. Methods The microarray datasets GSE36295、GSE71053和GSE86374 were downloaded from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified by GEO2R, and the enriched functions and pathways of the DEGs were analyzed. Protein-protein interaction network (PPI) was constructed by using String, and the module analysis was performed using Cytoscape. Results A total of 95 DEGs were identified, consisting of 62 upregulated genes and 33 downregulated genes.Ten hub genes were identified: CENPF,KIF2C,TOP2A,NUSAP1,HMMR,MELK,KIF4A,ASPM,CEP55,CCNB1. Conclusion The hub gene was found in this study may be involved in the development and prognosis of breast cancer. It may provide candidate targets for diagnosis and treatment of breast cancer.

Key words: Breast cancer, Differentially expressed genes, Bioinformatics, Survival

李淑怡, 黄玉珍, 蓝秀万. 乳腺癌关键基因的生物信息学分析[J]. 广州医药, 2021, 52(1): 65-71.

LI Shuyi, HUANG Yuzhen, LAN Xiuwan. Bioinformatic analysis of key genes in breast cancer[J]. Guangzhou Medical Journal, 2021, 52(1): 65-71.

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乳腺癌关键基因的生物信息学分析

Bioinformatic analysis of key genes in breast cancer

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