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整合分析微小RNA与基因相互作用以揭示前列腺癌的候选特征

Integrative Analysis of MicroRNA and Gene Interactions for Revealing Candidate Signatures in Prostate Cancer.

作者信息

Wei Jingchao, Yin Yinghao, Deng Qiancheng, Zhou Jun, Wang Yong, Yin Guangming, Yang Jianfu, Tang Yuxin

机构信息

Department of Urology, The Third Xiangya Hospital of Central South University, Changsha, China.

Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China.

出版信息

Front Genet. 2020 Feb 27;11:176. doi: 10.3389/fgene.2020.00176. eCollection 2020.

Abstract

MicroRNA (miRNA)-gene interactions are well-recognized as involved in the progression of almost all cancer types including prostate cancer, which is one of the most common cancers in men. This study explored the significantly dysregulated genes and miRNAs and elucidated the potential miRNA-gene regulatory network in prostate cancer. Integrative analysis of prostate cancer and normal prostate transcriptomic data in The Cancer Genome Atlas dataset was conducted using both differential expression analysis and weighted correlation network analysis (WGCNA). Thirteen genes () were potentially correlated with prostate cancer based on functional enrichment analyses. MiRNAs targeting these genes were predicted and eight miRNAs were intersections between those miRNAs and the hub miRNAs obtained from miRNA WGCNA analysis. Three genes () and four miRNAs () were key factors according to the interaction network. and were significantly related to survival. These findings partially elucidated the dysregulation of gene expressions in prostate cancer. Efficient manipulations of the miRNA-gene interactions in prostate cancer may be exploited as promising therapeutics.

摘要

微小RNA(miRNA)与基因的相互作用被公认为几乎参与了包括前列腺癌在内的所有癌症类型的进展,前列腺癌是男性最常见的癌症之一。本研究探讨了显著失调的基因和miRNA,并阐明了前列腺癌中潜在的miRNA-基因调控网络。利用差异表达分析和加权相关网络分析(WGCNA)对癌症基因组图谱数据集中的前列腺癌和正常前列腺转录组数据进行了综合分析。基于功能富集分析,13个基因与前列腺癌潜在相关。预测了靶向这些基因的miRNA,8个miRNA是这些miRNA与从miRNA WGCNA分析中获得的枢纽miRNA的交集。根据相互作用网络,3个基因和4个miRNA是关键因素。和与生存显著相关。这些发现部分阐明了前列腺癌中基因表达的失调。对前列腺癌中miRNA-基因相互作用的有效调控可能被开发为有前景的治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2545/7057858/958d54cfab88/fgene-11-00176-g001.jpg

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