基于生物信息学分析的食管癌miRNA-mRNA调控网络的初步构建  

The Preliminary Construction of MiRNA-mRNA Regulatory Network in Esophageal Cancer Based on Bioinformatics Analysis

作　　者：谢玉芳 李疆芬 江辰昊 张安志 袁鑫 李范平 梁伟华[1] 李曼[1] 沈西华[1] 李丽[1] 崔晓宾[1] 杨兰[1] 张海俊 庞丽娟[1] 刘春霞[1] 李锋[1,2] 胡建明[1] XIE Yu-fang;LI Jiang-fen;JIANG Chen-hao;ZHANG An-zhi;YUAN Xin;LI Fan-ping;LIANG Wei-hua;LI Man;SHEN Xi-hua;LI Li;CUI Xiao-bin;YANG Lan;ZHANG Hai-jun;PANG Li-juan;LIU Chun-xia;LI Feng;HU Jian-ming(Department of Pathology,Shihezi University School of Medicine/Department of Pathology,the First Affiliated Hospital of Shihezi University School of Medicine,Xinjiang Shihezi,832002;Department of Pathology,Beijing Chaoyang Hospital,Capital Medical University,Beijing,100016)

机构地区：[1]石河子大学医学院病理系/石河子大学医学院第一附属医院病理科,新疆石河子832002 [2]首都医科大学附属北京朝阳医院病理科,北京100016

出　　处：《农垦医学》2020年第3期193-199,共7页Journal of Nongken Medicine

基　　金：国家自然科学基金(81760428,81960435,8146036,81860518);石河子大学高层次人才科研启动项目(RCZK2018C19);新疆生产建设兵团科技发展项目(2018AB033);国家农村地区上消化道早期发现与治疗项目(2018年);兵团青年科技创新领导人才项目(2017CB004)。

摘　　要：目的:用生物信息学分析方法初步构建食管癌mi RNA和m RNA的调控网络,探索其在食管癌中的分子调控机制。方法:从GEO下载数据集GSE114110(n10 T30),GSE59973(n3 T3)使用GEO2R进行差异表达基因分析,使用R语言软件probezsylnbol做热图分析;再通过GEOR2对食管癌差异m RNA进行分析及funrich对mi RNA靶基因预测和m RNA预测取交集,使用DAVID和Cytoscape中的插件Clu GO进行GO富集分析,最后通过下载预后数据绘制mi RNAs的Kaplan-Meier生存曲线。结果:从GSE114110和GSE59973中取交集共获得7个差异表达mi RNAs,miR-34c-5p、mi R-455-3p、mi R-455-5p、mi R-944属于高频上调表达的mi RNAs,miR-139-5p、mi R-1、mi R-133b属于高频下调表达的mi RNAs;mi RNAs主要富集于转录因子活性,转运蛋白活性等;并筛选出56个靶基因,构建了食管癌mi RNA-m RNA分子调控网络,并筛选出结合和发挥作用的m RNAs,其功能主要富集为转录抑制子活性,RNA聚合酶II转录因子结合等。其中4个与m RNAs有靶向结合的mi RNAs预后分析表明mi R-455-5p、mi R-34c-5p、mi R-455-3p的高表达及mi R-133b低表达患者的总体生存时间缩短。结论:通过数据库挖掘方法构建的mi RNA-m RNA调控网络,发现mi R-455-5p、mi R-34c-5p、mi R-455-3p及mi R-133b参与食管癌的发生和发展,且与不良预后相关,为研究食管癌发病机制、探索联合mi RNA及其靶基因m RNA作为临床诊断标志物及预后提供了可靠的研究方向。Objective:The regulation network of mi RNA and m RNA in esophageal cancer was preliminarily constructed by bioinformatics analysis to explore its molecular regulation mechanism in esophageal cancer.Methods:Downloaded data set GSE114110(N10 T30),GSE59973(N3 T3)from GEO,used GEO2 R for differential expression gene analysis,and used R language software,Probezsylnbol,for heat map analysis.By used GEOR2 to analyze the differential m RNA of esophageal cancer,and used FunRich to predict the mi RNA target genes and m RNA to obtain the intersection data.After that,used the Clu GO plug-in in DAVID and Cytoscape software for GO enrichment analysis.Finally,the Kaplan-Meier survival curve of mi RNAs was drawn by downloading the prognostic data.Results:The intersection was extracted from GSE114110 and GSE59973,and a total of 7 differential expressions were obtained:mi RNAs,mi R-34 c-5 p,mi R-455-3 p,mi R-455-5 p,mi R-944,which expression are high-frequency up-regulated mi RNAs,Mi R-139-5 p,mi R-1,and mi R-133 b belong to those expression are high frequency down-regulated mi RNAs;Screened 56 target genes,constructed a mi RNA-m RNA molecular regulatory network for esophageal cancer,and screened out m RNAs that can bind and with function.Their functions are mainly enriched in transcriptional repressor activity,RNA polymerase II transcription factor binding and so on.The prognostic analysis of 4 mi RNAs with m RNA targeted binding showed that the patients with high expression of mir-455-5 p,mir-34 c-5 p,mir-455-3 p and low expression of mi R-133 b had shorter overall survival time.Conclusion:Using the mi RNA-m RNA regulatory network constructed with database mining methods,the researchers found that mi R-455-5 p,mi R-34 c-5 p,mi R-455-3 p,and mi R-133 b are involved in the occurrence and development of esophageal cancer,and are related to the adverse prognosis of patients.The research results provide a reliable research direction for discovering the pathogenesis of esophageal cancer,exploring combined mi RNAs and their target gene

关 键 词：食管癌 GEO数据库 MIRNA MRNA 调控网络 

分 类 号：R392.3[医药卫生—免疫学]