基于基因芯片数据的精原细胞瘤生物信息学分析  

Bioinformatics analysis of differentially expressed genes and their key pathways in seminoma tumor

作　　者：瞿根义 汤乘 徐勇 阳光 段红桃 王佳威 向茂林 Qu Genyi;Tang Cheng;Xu Yong;Yang Guang;Duan Hongtao;Wang Jiawei;Xiang Maolin(Department of Urology;Department of Ultrasound,The Affiliated Zhuzhou Hospital XiangYa Medical College CSU,Hunan Zhuzhou 412007,China)

机构地区：[1]中南大学湘雅医学院附属株洲医院泌尿外科 [2]中南大学湘雅医学院附属株洲医院超声科,湖南株洲412007

出　　处：《中国男科学杂志》2020年第4期21-25,31,共6页Chinese Journal of Andrology

基　　金：湖南省科技创新计划项目(S2018SFYLJS0466)。

摘　　要：目的利用生物信息学分析精原细胞瘤基因表达芯片,探索用于精原细胞瘤诊断、治疗和预后的潜在候选基因。方法从GEO database下载精原细胞瘤相关的基因芯片数据GSE8607,利用R软件及affy、limma、ggplot2等R程序包筛选差异表达基因,结合DAVID和STRING在线生物信息学工具对差异表达基因进行调控网络分析,并构建蛋白质-蛋白质相互作用(PPI)网络,进一步利用Cytoscape软件中的Cytohubba进行Hub基因筛选。结果共筛选出精原细胞瘤相关的差异表达基因1142个,其中表达上调基因687个,表达下调基因455个,对差异表达基因进行GO富集分析和KEGG通路富集分析,获取关键通路,利用在线生物信息学工具STRING构建PPI网络,使用Cytoscape软件中的Cytohubba获取PPI网络中前10位Hub基因,分别是C3AR1、PENK、ADORA1、P2RY14、ADCY7、CCL5、CCR5、CCL4、CCL19、CCR7。对这些关键基因进行文献挖掘,发现这些基因可能与精原细胞瘤的发生发展有关。结论应用生物信息学能有效分析基因芯片数据,寻找到精原细胞瘤相关的关键基因,为精原细胞瘤的早期诊断、治疗以及疾病预后提供了新的线索。Objective By bioinformatics analysis of gene expression microarray,we explored potential candidate genes or molecules for diagnosis,treatment and prognosis of seminoma.Methods The data about seminoma gene expression microarray GSE8607 was downloaded from the GEO database.Limma,ggplot2 and other R software packages were used for differentially expressed gene screening,and DAVID combining with STRING online bioinformatics tools for analyzing the regulatory network of differentially expressed genes and constructing a protein-protein interaction(PPI)network,and Cytohubba in Cytoscape software for performing Hub gene screening.Results A total of 1142 differentially expressed genes for testicular seminoma were screened,of which 687 were up-regulated and 455 were down-regulated.GO enrichment analysis and KEGG pathway enrichment analysis were performed on the differentially expressed genes,and accessing to critical pathways.An online bioinformatics tool was used to construct the PPI network.Cytohubba in Cytoscape software was used to obtain the top 10 Hub genes in the PPI network,including C3 AR1、PENK、ADORA1、P2 RY14、ADCY7、CCL5、CCR5、CCL4、CCL19、CCR7.Literature mining indicated that these genes might be related to the pathogenesis of seminoma.Conclusion Bioinformatic methods can effectively analyze the data of gene microarray and obtain the key genes related to seminoma,which provides a new clue for the early diagnosis,treatments and prognosis of seminoma.

关 键 词：精原细胞瘤 基因 生物信息学 

分 类 号：R737.23[医药卫生—肿瘤] Q811.4[医药卫生—临床医学]