Identification of an lncRNA‑miRNA‑mRNA interaction mechanism in breast cancer based on bioinformatic analysis.
Identification of an lncRNA‑miRNA‑mRNA interaction mechanism in breast cancer based on bioinformatic analysis.
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DOI：
10.3892/mmr.2017.7304
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发表时间：
2017-10
影响因子：
3.4
通讯作者：
Ding X
中科院分区：
文献类型：
--
作者：
Zhang Y;Li Y;Wang Q;Zhang X;Wang D;Tang HC;Meng X;Ding X
非编码RNA在调节某些基因的表达中起重要作用，并参与乳腺癌的主要生物学过程。大多数研究集中在定义长非编码RNA（lncRNA）和microRNA（miRNAs/miRs）的调控功能，很少有研究探讨lncRNA和miRNAs是如何转录调控的。在本研究中，基于cBioPortal的癌症基因组图谱的乳腺浸润性癌数据集，并使用生物信息学计算方法，构建lncRNA-miRNA-mRNA网络。该网络由601个节点和706条边组成，代表了lncRNA、miRNAs和靶基因之间复杂的调控网络。本研究的结果表明，miR-510是许多靶基因的最有效的miRNA控制器和调节器。此外，观察到lncRNA PVT 1、CCAT 1和linc 00861表现出与临床生物标志物的可能的相互作用，包括受体酪氨酸-蛋白激酶erbB-2、雌激素受体和孕酮受体，使用RNA-蛋白质相互作用预测软件证明。lncRNA-miRNA-mRNA相互作用的网络将促进进一步的实验研究，并可用于改进生物标志物预测，以开发乳腺癌的新治疗方法。
Non-coding RNAs serve important roles in regulating the expression of certain genes and are involved in the principal biological processes of breast cancer. The majority of studies have focused on defining the regulatory functions of long non-coding RNAs (lncRNAs) and microRNAs (miRNAs/miRs), and few studies have investigated how lncRNAs and miRNAs are transcriptionally regulated. In the present study, based on the breast invasive carcinoma dataset from The Cancer Genome Atlas at cBioPortal, and using a bioinformatics computational approach, an lncRNA-miRNA-mRNA network was constructed. The network consisted of 601 nodes and 706 edges, which represented the complex web of regulatory effects between lncRNAs, miRNAs and target genes. The results of the present study demonstrated that miR-510 was the most potent miRNA controller and regulator of numerous target genes. In addition, it was observed that the lncRNAs PVT1, CCAT1 and linc00861 exhibited possible interactions with clinical biomarkers, including receptor tyrosine-protein kinase erbB-2, estrogen receptor and progesterone receptor, demonstrated using RNA-protein interaction prediction software. The network of lncRNA-miRNA-mRNA interactions will facilitate further experimental studies and may be used to refine biomarker predictions for developing novel therapeutic approaches in breast cancer.
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