基于GEO数据库良性前列腺增生症患者基因芯片数据的生物信息学分析  

Bioinformatics analysis of benign prostatic hyperplasia genome microarray based on GEO database

作　　者：叶妙勇 黄文杰[2] 杨荣超 温瞿华 张春和 赵凡 Ye Miaoyong;Huang Wenjie;Yang Rongchao;Wen Quhua;Zhang Chunhe;Zhao Fan(Department of Urology,The Afiliated Wenling Hospital of Wenzhou Medical University,Wenling 317500,Zhejiang,China;The Second Afiliated Hospital Zhejiang University School of Medicine,Hangzhou 310017,Zhejiang,China;Department of Andrology,Yunnan Provincial Hospital of Traditional Chinese Medicine/The First Affiliated Hospital of Yunnan University of Chinese Medicine,Kunming 650021,Yunnan,China;Department of Urology,Affiliated Hospital of Nantong University,Nantong 226001,Jiangsu,China)

机构地区：[1]温州医科大学附属温岭医院泌尿外科,浙江温岭317500 [2]浙江大学医学院附属第二医院泌尿外科,浙江温岭310017 [3]云南省中医医院/云南中医药大学第一附属医院男科,云南昆明650000 [4]南通大学附属医院泌尿外科,江苏南通226001

出　　处：《中国男科学杂志》2022年第6期60-67,93,共9页Chinese Journal of Andrology

基　　金：国家自然科学基金项目(82274533,81860853);浙江省中医药科学研究基金项目(A类,2021ZA068);台州市社会发展科技计划项目(22ywb130);云南中医药大学第一临床医学院研究生科学研究基金项目(2021Y09)。

摘　　要：目的通过生物信息学方法探讨GEO(Gene Expression Omnibus)数据库中良性前列腺增生的差异表达基因及相关信号通路。方法通过GEO数据库检索筛得包含5例人源前列腺增生组织与3例正常人前列腺组织的基因芯片数据集(GSE119195)。采用R程序工具矫正性前列腺增生组织与正常前列腺组织的基因表达量并筛选差异表达基因(differentially expressed genes,DEGs)进行可视化处理。通过clusterProfiler包对DEGs进行基因功能注释(GO)、京都基因与基因组百科全书(KEGG)通路富集分析、基因集富集分析(GSEA),利用STRING数据库构建蛋白质蛋白质相互作用(PPI)网络,并使用Cytoscape软件及Cytohubb及MCODE插件筛选出核心基因。结果通过limma包共获得186个差异基因,其中在良性前列腺增生症(BPH)组上调基因有64个,下调基因有122个。GO富集分析表明DEGs主要参与了平滑肌细胞增殖、转化生长因子β应答、细胞外基质、腺体受体激活、信号通路受体活化体活性等。KEGG信号通路富集分析主要包括了MAPK信号通路、肾素分泌、EGFR酪氨酸激酶抑制剂抵抗、PPAR信号通路等。GSEA分析得到生物通路主要包括了上皮细胞间质转化信号通路、MTORC1信号通路、脂肪酸新陈代谢(fatty acid metabolism)、氧化磷酸化等信号通路。PPI分析筛选获得10个枢纽基因,分别为FABP3、IGF1、MYL1、TTN、NEB、JUN、LPL、CD36、FABP4、DMD。结论基于GEO数据库的生物信息学分析进行多维度的富集分析以及构建的蛋白互作网络,BPH涉及的差异表达基因、生物过程及富集信号通路,筛选出的靶基因可能成为治疗BPH的潜在分子靶点。Objective To screen core genes and related signal pathways of benign prostatic hyperplasia using Gene Expression Omnibus(GEO)database and bioinformatics methods.Methods Through screening the GEO database,the gene chip data set GSE119195 containing 5 prostate hyperplasia tissues and 3 normal prostate tissues was obtained.The R tool was used to normalize the gene expression data of prostate hyperplasia tissue and prostate tissue,and the differentially expressed genes(DEGs)were screened and visualized.Gene function annotation(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis,gene set enrichment analysis(GSEA)were performed by using the cluster Profiler package and a protein-protein interaction(PPI)network was constructed by using the STRING database.The core genes were found by using Cytoscape software and cytohubb and MCODE plug-in.Results A total of 186 differential genes were obtained through the limma package,of which 64 were up-regulated genes and 122 were down-regulated genes in the BPH group.GO enrichment analysis showed that DEGs were mainly involved in smooth muscle cell proliferation,transforming growth factorβresponse,extracellular matrix,glandular receptor activation,and signal pathway receptor activator activity.The enrichment analysis of KEGG signaling pathway revealed that DEGs were enriched in MAPK signaling pathway,renin secretion,EGFR tyrosine kinase inhibitor resistance,and PPAR signaling pathway,and the biological pathways analyzed by GSEA showed that DEGs were mainly involved in epithelial mesenchymal transition,MTORC1 signaling pathway,fatty acid metabolism,oxidative phosphorylation.Ten hub genes,such as FABP3,IGF1,MYL1,TTN,NEB,JUN,LPL,CD36,FABP4,DMD were obtained in PPI analysis and screening.Conclusion The obtained target genes,from the bioinformatics analysis of GEO database including multi-dimensional enrichment analysis and construction of protein interaction network,the differentially expressed genes,biological processes and enrichment signal pathways,may becom

关 键 词：前列腺增生 基因 计算生物学 

分 类 号：R697.32[医药卫生—泌尿科学]