生物信息学方法分析人肾细胞癌中潜在的miRNAs生物标志物和其调控的关键通路  

Bioinformatics analysis of human renal cell carcinoma and identification for potential biomarkers and critical pathways

作　　者：李伟[1] 李晓宇[2] 黄建华[1] 王光春[1] 彭波[1] 刘敏[1] 许云飞[1] 姚旭东[1] 郑军华[1] 

机构地区：[1]同济大学附属第十人民医院泌尿外科,上海200072 [2]同济大学附属第十人民医院普通外科

出　　处：《临床泌尿外科杂志》2015年第6期535-540,共6页Journal of Clinical Urology

基　　金：自然科学基金资助项目(编号81270831);上海市卫生系统新百人计划项目<早期肾癌微创治疗的基础和临床研究>(编号XBR2011021)

摘　　要：目的:通过对基因表达数据库(GEO)中肾细胞癌相关的基因及miRNAs进行生物信息学分析,获得肾癌相关的异常miRNAs和异常表达的生物标记物及其调控的关键通路。方法:利用GEO数据库获得肾细胞癌相关的基因表达谱大数据(GSE781,GSE6344),对肾癌和正常组织中的生物标记物表达数据进行差异性分析获得差异表达的miRNAs和其调控的mRNA;应用MiRanda公式及功能富集分析筛选异常的miRNAs,再运用基因功能分析方法(GO)进一步筛选获得肾细胞癌相关性miRNAs。结果:利用肾细胞癌相关的基因表达谱数据库分析,对两组肾癌组织和正常样本的生物标记物表达数据进行差异性分析,有437个差异表达基因下调而489个表达上调,其中两者包含104个相同的差异表达基因。应用MiRanda公式及功能富集分析筛选获得异常miRNA 10个,然后运用基因功能分析方法筛选获得肾癌相关性miRNAs,相关性较强的有miR-147a、miR-504-5p、miR-105-5p、miR-520g-3p和miR-2682-5p。结论:生物信息学方法对肿瘤的基因组的分析为发现潜在的miRNAs生物标志物和其调控的关键通路提供了一个有利工具,我们目前发现的关键基因不仅是生物标记物,也可以在基因组大数据中寻找可能的研究切入点,为后续的肾癌生物学治疗奠定基础。Objective：To screen several novel genes and miRNAs associated with renal cell carcinoma（RCC）from Gene Expression Omnibus（GEO）database,and analyze the gene functions and signal pathways which were critical to RCC.Method：The gene expression profile of GSE781 and GSE6344were downloaded from GEO database in order to obtain the differential expression miRNAs and its regulatory mRNA of biomarkers by difference analysis in RCC and normal sample.We used miRanda formula and functional enrichment analysis to screen out the abnormal miRNAs,then the similarity analysis of gene function was used to screen out RCC-related miRNAs.Result：Analysing RCC-related gene expression profile database,a total of 437 differentially expressed genes（DEGs）were down-regulated and 489 DEGs were up-regulated in RCC samples compared with healthy controls,which both contained the same 104 DEGs.Using miRanda formula and functional enrichment analysis we screened out 10 abnormal miRNAs,then using gene function analysis we screened out renal cancer-related miRNAs.Among them were miR-147 a,miR-504-5p,miR-105-5p,miR-520g-3p and miR-2682-5p which were strongly correlated with RCC.Conclusion：Using bioinformatics methods to analyze cancer genome is effective to identify potential biomarkers of miRNAs and its regulatory key pathways.The key genes we found from RCC samples are not only biomarkers,but also may provide the groundwork for a combination therapy approach to RCC.

关 键 词：肾细胞癌 生物信息学 MIRNA 生物标记物 靶向治疗 

分 类 号：R737.11[医药卫生—肿瘤]