通过竞争性内源RNA网络特征分析揭示三阴性乳腺癌潜在的预后生物标志物

Characterization of ceRNA network to reveal potential prognostic biomarkers in triple-negative breast cancer.

作者信息

Song Xiang, Zhang Chao, Liu Zhaoyun, Liu Qi, He Kewen, Yu Zhiyong

机构信息

School of Medicine and Life Sciences, University of Jinan-Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.

Department of Oncology, Shandong Cancer Hospital Affiliated to Shandong University, Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.

出版信息

PeerJ. 2019 Sep 9;7:e7522. doi: 10.7717/peerj.7522. eCollection 2019.

Abstract

Triple-negative breast cancer (TNBC) is a particular subtype of breast malignant tumor with poorer prognosis than other molecular subtypes. Previous studies have demonstrated that some abnormal expression of non-coding RNAs including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) were closely related to tumor cell proliferation, apoptosis, invasion, migration and drug sensitivity. However, the role of non-coding RNAs in the pathogenesis of TNBC is still unclear. In order to characterize the molecular mechanism of non-coding RNAs in TNBC, we downloaded RNA data and miRNA data from the cancer genome atlas database. We successfully identified 686 message RNAs (mRNAs), 26 miRNAs and 50 lncRNAs as key molecules for high risk of TNBC. Then, we hypothesized that the lncRNA-miRNA-mRNA regulatory axis positively correlates with TNBC and constructed a competitive endogenous RNA (ceRNA) network of TNBC. Our series of analyses has shown that five molecules (TERT, TRIML2, PHBP4, mir-1-3p, mir-133a-3p) were significantly associated with the prognosis of TNBC, and there is a prognostic ceRNA sub-network between those molecules. We mapped the Kaplan-Meier curve of RNA on the sub-network and also suggested that the expression level of the selected RNA is related to the survival rate of breast cancer. Reverse transcription-quantitative polymerase chain reaction showed that the expression level of TRIML2 in TNBC cells was higher than normal. In general, our findings have implications for predicting metastasis, predicting prognosis and discovering new therapeutic targets for TNBC.

摘要

三阴性乳腺癌(TNBC)是乳腺恶性肿瘤的一种特殊亚型,其预后比其他分子亚型更差。先前的研究表明,包括微小RNA(miRNA)和长链非编码RNA(lncRNA)在内的一些非编码RNA的异常表达与肿瘤细胞的增殖、凋亡、侵袭、迁移及药物敏感性密切相关。然而,非编码RNA在TNBC发病机制中的作用仍不清楚。为了阐明非编码RNA在TNBC中的分子机制,我们从癌症基因组图谱数据库下载了RNA数据和miRNA数据。我们成功鉴定出686个信使RNA(mRNA)、26个miRNA和50个lncRNA作为TNBC高风险的关键分子。然后,我们假设lncRNA-miRNA-mRNA调控轴与TNBC呈正相关,并构建了TNBC的竞争性内源性RNA(ceRNA)网络。我们的一系列分析表明,五个分子(TERT、TRIML2、PHBP4、mir-1-3p、mir-133a-3p)与TNBC的预后显著相关,并且这些分子之间存在一个预后ceRNA子网。我们在该子网上绘制了RNA的Kaplan-Meier曲线,也表明所选RNA的表达水平与乳腺癌的生存率相关。逆转录定量聚合酶链反应表明,TRIML2在TNBC细胞中的表达水平高于正常水平。总体而言,我们的研究结果对预测TNBC的转移、预后及发现新的治疗靶点具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc69/6741283/06e3dd915267/peerj-07-7522-g001.jpg

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