贵州医科大学学报

2020, v.45;No.233(02) 161-168

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前列腺癌差异表达基因的分析及其miRNA和lncRNA的预测
Analysis of Differentiall Expressed Genes Related to Prostate Cancer and Corresponding miRNA and LncRNA of Genes

宋咏刚,余鹏,胡文慧,石玉玲,赵雪,胡祖权,王赟,曾柱
SONG Yonggang,YU Peng,HU Wenhui,SHI Yuling,ZHAO Xue,HU Zhuquan,WANG Yun,ZENG Zhu

摘要(Abstract):

目的:筛选前列腺癌的差异表达基因及其上下游的调控分子。方法:通过TCGA数据库和GEO数据库,经RSudio软件分析得到差异基因(DEGenes);采用STRING工具构建差异基因的相互作用网络、CYTOSCAPE软件筛选核心模块,并对差异基因进行GO和KEGG分析,运用mirDIP数据库预测核心基因的miRNA,登录STARBASE对miRNA进行生存分析并预测其lncRNA。结果:筛选出前列腺癌的差异表达基因共137个,GO分析结果显示有23个富集结果,KEGG分析有20个通路被富集;对7个核心差异基因进行分析,预测出2个与总体生存率相关的miRNA,这些miRNA有4个对应的lncRNA;最后构建lncRNA-mRNA互作网络。结论:从生物信息学角度对前列腺癌的差异基因进行筛选和分析,筛选出前列腺癌发生过程中的关键基因及其上下游的调控分子。
Objective: To identify differentially expressed genes(DEGenes) in prostate cancer and the related regulation molecules within their upstream and downstream.Methods: Through TCGA and GEO databases, DEGenes were obtained from the analysis of RStudio software. An interaction network of DEGenes was constructed through STRING tool and CYTOSCAPE software to screen the core module and then carry out GO and KEGG analysis of DEGenes. The mirDIP database and STARBASE database were applied to predict miRNA and lncRNA of the core genes.Results: 137 DEGenes of prostate cancer were screened. 23 enrichment results were collected by GO analysis and 20 signaling pathways were enriched by KEGG analysis. After analysis of seven core DEGenes, two miRNAs which were related to the overall survival in prostate cancer patients and four corresponding lncRNAs were predicted. Finally an interaction network of lncRNA to mRNA was built.Conclusions: The study screens and analyzes DEGenes related to prostate cancer from the perspective of bioinformatics.Regulation molecules of upstream and downstream corresponding to the core genes are screened and predicted. It may provide a theoretical evidence for exploring potential biomarkers in the diagnosis and treatment of prostate cancer.

关键词(KeyWords): 前列腺肿瘤;基因表达调控;miRNA;计算生物学;lncRNA
prostatic neoplasms;gene expression regulation;miRNA;computational biology;lncRNA

Abstract:

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基金项目(Foundation): 国家自然科学基金(11762006,31771014,31660258,31860262);; 贵州省自然科学基金资助项目[黔科合基础(2018)1412];; 黔科合平台人才[(2016)5676],黔科合平台人才[(2017)5718];; 黔科合人才团队[(2015)4021];; 2011协同创新中心[黔教合协同创新字(2015)04];; 贵州省细胞与基因工程创新群体[黔教合KY字(2016)031]

作者(Author): 宋咏刚,余鹏,胡文慧,石玉玲,赵雪,胡祖权,王赟,曾柱
SONG Yonggang,YU Peng,HU Wenhui,SHI Yuling,ZHAO Xue,HU Zhuquan,WANG Yun,ZENG Zhu

DOI: 10.19367/j.cnki.1000-2707.2020.02.007

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