Department of Urology, The Second Affiliated Hospital of 107652Shaanxi University of Traditional Chinese Medicine, Xianyang, Shaanxi, China.
Department of General Surgery, 107652Chinese PLA General Hospital, Beijing, China.
Technol Cancer Res Treat. 2020 Jan-Dec;19:1533033820963578. doi: 10.1177/1533033820963578.
Prostate cancer (PCa) is a highly malignant tumor, with increasing incidence and mortality rates worldwide. The aim of this study was to identify the prognostic lncRNAs and construct an lncRNA signature for PCa diagnosis by the interaction network between lncRNAs and protein-coding genes (PCGs). The differentially expressed lncRNAs (DElncRNAs) and PCGs (DEPCGs) between PCa and normal prostate tissues were screened from The Cancer Genome Atlas (TCGA) database. The DEPCGs were functionally annotated in terms of the enriched pathways. Weighted gene co-expression network analysis (WGCNA) of 104 PCa samples identified 15 co-expression modules, of which the Turquoise module was negatively correlated with cancer and included 5 key lncRNAs and 47 PCGs. KEGG pathway analyses of the core 47 PCGs showed significant enrichment in classic PCa-related pathways, and overlapped with the enriched pathways of the DEPCGs. LINC00857, LINC00900, LINC00908, LINC00900, SNHG3 and FENDRR were significantly associated with the survival of PCa and have not been reported previously. Finally, Multivariable Cox regression analysis was used to establish a prognostic risk formula, and the patients were accordingly stratified into the low- and high-risk groups. The latter had significantly worse OS compared to the low-risk group (P < 0.01), and the area under the receiver operating characteristic curve (ROC) of 14-year OS was 0.829. The accuracy of our prediction model was determined by calculating the corresponding concordance index (C-index) and risk curves. In conclusion, we established a 5-lncRNA prognostic signature that provides insights into the biological and clinical relevance of lncRNAs in PCa.
前列腺癌（PCa）是一种高度恶性肿瘤，全球发病率和死亡率呈上升趋势。本研究旨在通过长链非编码 RNA（lncRNA）与蛋白质编码基因（PCG）之间的相互作用网络，鉴定用于 PCa 诊断的预后 lncRNA 并构建 lncRNA 特征。从癌症基因组图谱（TCGA）数据库中筛选出 PCa 与正常前列腺组织之间差异表达的 lncRNA（DElncRNA）和 PCG（DEPCG）。对 104 个 PCa 样本进行加权基因共表达网络分析（WGCNA），鉴定出 15 个共表达模块，其中绿松石模块与癌症呈负相关，包含 5 个关键 lncRNA 和 47 个 PCG。核心 47 个 PCG 的 KEGG 通路分析显示，其在经典 PCa 相关通路中显著富集，并与 DEPCG 的富集通路重叠。LINC00857、LINC00900、LINC00908、LINC00900、SNHG3 和 FENDRR 与 PCa 的生存显著相关，且以前未被报道过。最后，采用多变量 Cox 回归分析建立预后风险公式，并根据该公式将患者分为低危组和高危组。后者的 OS 明显差于低危组（P < 0.01），14 年 OS 的 ROC 曲线下面积为 0.829。通过计算相应的一致性指数（C-index）和风险曲线确定我们的预测模型的准确性。总之，我们建立了一个 5-lncRNA 预后特征，为 lncRNA 在 PCa 中的生物学和临床相关性提供了新的见解。
