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中华细胞与干细胞杂志(电子版) ›› 2018, Vol. 08 ›› Issue (03) : 146 -151. doi: 10.3877/cma.j.issn.2095-1221.2018.03.004

所属专题: 文献

论著

肾透明细胞癌预后相关miRNAs的生物信息学分析
付军明1, 肖招兰1, 何富强1, 郭君其1, 谭建明1, 朱凌峰1,()   
  1. 1. 350025 福州,福州总医院泌尿外科
  • 收稿日期:2017-11-10 出版日期:2018-06-01
  • 通信作者: 朱凌峰
  • 基金资助:
    福建省自然科学基金项目(2016J0105)

Bioinformatics analysis of prognosis-related miRNAs in clear cell renal cell carcinoma

Junming Fu1, Zhaolan Xiao1, Fuqiang He1, Junqi Guo1, Jianming Tan1, Lingfeng Zhu1,()   

  1. 1. Department of Urology, Fuzhou General Hospital, Fuzhou 350025, China
  • Received:2017-11-10 Published:2018-06-01
  • Corresponding author: Lingfeng Zhu
  • About author:
    Corresponding: Zhu Lingfeng, Email:
引用本文:

付军明, 肖招兰, 何富强, 郭君其, 谭建明, 朱凌峰. 肾透明细胞癌预后相关miRNAs的生物信息学分析[J/OL]. 中华细胞与干细胞杂志(电子版), 2018, 08(03): 146-151.

Junming Fu, Zhaolan Xiao, Fuqiang He, Junqi Guo, Jianming Tan, Lingfeng Zhu. Bioinformatics analysis of prognosis-related miRNAs in clear cell renal cell carcinoma[J/OL]. Chinese Journal of Cell and Stem Cell(Electronic Edition), 2018, 08(03): 146-151.

目的

寻找可作为肾透明细胞癌(ccRCC)生物标志物的miRNA,以及ccRCC与正常组织间miRNA差异表达情况。

方法

利用TCGA数据库下载ccRCC中miRNA表达数据,分析肿瘤与正常组织间差异表达miRNA。使用Kaplan-Meier曲线对患者进行生存分析,筛选出表达情况与临床预后相关的miRNA。通过生物信息学对miRNA的靶基因进行预测,然后运用FunRich软件和ClueGO对靶基因进行GO和KEGG富集分析。

结果

通过TCGA数据库分析发现,ccRCC较正常组织差异表达miRNA共54个,其中上调33个,下调21个。通过生存分析发现hsa-miR-21和hsa-miR-155与患者预后相关,P≤0.05。进一步通过Perl软件在Targetscan、miRDB、miRTarBase、miRPath这四个数据库中预测miRNA靶基因并将结果取交集,共发现129个靶基因。GO和KEGG分析结果表明,这些靶基因主要与转录因子活性、信号转导以及FoxO、TNF等信号通路密切相关。

结论

通过生物信息学分析发现了ccRCC与正常组织的差异表达miRNA;其中hsa-miR-21和hsa-miR-155与患者总体生存率相关,并通过调控靶基因参与相关的信号通路进而影响ccRCC的发生发展进程,提示hsa-miR-21和hsa-miR-155可能是ccRCC潜在的生物标志物。

Objective

To discover miRNAs which can be used as biomarkers of clear cell renal cell carcinoma (ccRCC) as well as ravel differentially expressed miRNAs between ccRCC and normal tissues.

Methods

The miRNAs expression data of ccRCC was used to analyze differentially expressed miRNAs between tumors and normal tissues according to TCGA database. Survival analysis was performed using Kaplan-Meier curves to screen out miRNAs, which the expression was correlated with clinical prognosis. The target genes of miRNAs were predicted by bioinformatics, then GO and KEGG enrichment analyses of target genes were carried out by using FunRich software and ClueGO software.

Results

According to TCGA database analysis, there were 54 miRNAs found differentially expressed in ccRCC compared with normal tissues, of which 33 were up-regulated and 21 were down-regulated. Survival analysis found that hsa-miR-21 and hsa- miR-155 were associated with the prognosis of patients (P≤0.05). A total of 129 target genes were found by using Perl software to predict miRNA target genes in four databases: Targetscan, miRDB, miRTarBase and miRPath. The results of GO and KEGG analysis showed that these target genes were closely related to transcription factor activity, signal transduction, FoxO, TNF and other signaling pathways.

Conclusion

Differentially expressed miRNAs between ccRCC and normal tissues were found by bioinformatics analysis. Among them, the hsa-miR-21 and hsa-miR-155 may be associated with patient overall survival and influence the development and progression of ccRCC by regulating the target genes involved in the relevant signaling pathways, suggesting that hsa-miR-21 and hsa-miR-155 could be potential biomarkers for ccRCC.

表1 差异表达的miRNA(TOP 5)
图1 差异表达miRNA热图
图2 差异表达miRNA火山图
图3 hsa-miR-21与hsa-miR-155在ccRCC中的生存曲线
图4 miRNA-Target Genes网络图
图5 靶基因GO分析
图6 靶基因KEGG分析
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