Department of Breast Surgery, Guilin TCM Hospital of China, Affiliated to Guang Xi University of Chinese Medicine, Guilin, 541000 Guangxi, China.
Department of Clinical Laboratory, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Chongming Branch, Shanghai 202150, China.
Biomed Res Int. 2020 Sep 3;2020:9081852. doi: 10.1155/2020/9081852. eCollection 2020.
The purpose of this study was to investigate the regulatory mechanisms of ceRNAs in breast cancer (BC) and construct a new five-mRNA prognostic signature.
The ceRNA network was constructed by different RNAs screened by the edgeR package. The BC prognostic signature was built based on the Cox regression analysis. The log-rank method was used to analyse the survival rate of BC patients with different risk scores. The expression of the 5 genes was verified by the GSE81540 dataset and CPTAC database.
A total of 41 BC-adjacent tissues and 473 BC tissues were included in this study. A total of 2,966 differentially expressed lncRNAs, 5,370 differentially expressed mRNAs, and 359 differentially expressed miRNAs were screened. The ceRNA network was constructed using 13 lncRNAs, 267 mRNAs, and 35 miRNAs. Kaplan-Meier (K-M) methods showed that two lncRNAs (AC037487.1 and MIR22HG) are related to prognosis. Five mRNAs (, , , , and ) in the ceRNA network were used to establish a prognostic signature. Survival analysis showed that the prognosis of patients in the low-risk group was significantly better than that in the high-risk group ( = 0.0022). ROC analysis showed that this signature has a good diagnostic ability (AUC = 0.77). Compared with clinical features, this signature was also an independent prognostic factor (HR: 1.206, 95% CI 1.108-1.311; < 0.001). External verification results showed that the expression of the 5 mRNAs differed between the normal and tumour groups at the chip and protein levels ( < 0.001).
These ceRNAs may play a key role in the development of BC, and the new 5-mRNA prognostic signature can improve the prediction of survival for BC patients.
本研究旨在探讨 ceRNA 在乳腺癌（BC）中的调控机制，并构建新的五信使 RNA 预后标志。
采用 edgeR 软件包筛选不同的 RNA 构建 ceRNA 网络。基于 Cox 回归分析构建 BC 预后标志。对数秩方法用于分析不同风险评分 BC 患者的生存率。通过 GSE81540 数据集和 CPTAC 数据库验证 5 个基因的表达。
本研究共纳入 41 例 BC 旁组织和 473 例 BC 组织。筛选出 2966 个差异表达的 lncRNA、5370 个差异表达的 mRNA 和 359 个差异表达的 miRNA。利用 13 个 lncRNA、267 个 mRNA 和 35 个 miRNA 构建 ceRNA 网络。Kaplan-Meier（K-M）方法显示 2 个 lncRNA（AC037487.1 和 MIR22HG）与预后相关。ceRNA 网络中的 5 个 mRNA（、、、、和）被用于建立预后标志。生存分析显示，低风险组患者的预后明显优于高风险组（=0.0022）。ROC 分析表明该标志具有良好的诊断能力（AUC=0.77）。与临床特征相比，该标志也是独立的预后因素（HR：1.206，95%CI 1.108-1.311；<0.001）。外部验证结果表明，芯片和蛋白水平正常组织和肿瘤组织中 5 个 mRNAs 的表达存在差异（<0.001）。
这些 ceRNA 可能在 BC 的发展中起关键作用，新的 5-mRNA 预后标志可提高 BC 患者生存预测的准确性。
