This study aimed to construct a long noncoding RNA (lncRNA)-based prognostic signature to improve the survival prediction for endometrial cancer (EC) patients and guide individualized treatments. mRNA and miRNA sequencing and clinical data of 526 patients with EC (randomized to training or validation set, n = 263) were collected from The Cancer Genome Atlas database. Differentially expressed genes (DEGs), differentially expressed lncRNAs (DELs), and differentially expressed miRNAs (DEMs) were identified between 263 EC samples and 33 normal controls. Univariate and multivariate Cox regression analyses identified five DELs (LINC00475, LINC01352, MIR503HG, KCNMB2-AS1, and LINC01143) that were overall survival related. The Kaplan-Meier curve showed that the risk score model established by these five DELs can significantly distinguish the survival ratio of patients at high risk from those at low risk. The receiver operating characteristic curve indicated that this risk score exhibited good survival prediction performance, with the area under the curve of 0.978. In addition, this risk score was independent of other clinical factors. Stratification analysis based on two independent prognostic clinical factors (histologic grade and recurrence status) demonstrated that the high-risk score was still a poor prognostic factor for patients with histologic grade 3, recurrence or nonrecurrence status. In nomogram model, the risk score was one of the main contributions to survival rates, and its Harrell's concordance index was higher than the other two independent clinical factors, although all lower than the combined. Furthermore, mechanism analyses showed that these lncRNAs functioned by coexpressing with DEGs (i.e., LINC00475-PTGDR, LINC01352/MIR503HG-BACH2, KCNMB2-AS1-PCSK9, LINC01143-NUF2/PTTG1) or as a competing endogenous RNA of DEMs to regulate DEGs (LINC00475-miR-4728-PTGDR, MIR503HG-miR-3170-BACH2). In conclusion, our novel risk score system may be a promising prognostic biomarker to guide personalized treatment for EC patients and it can add prognostic value for current clinical system.

中文翻译：

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子宫内膜癌患者五长期非编码RNA预后签名的鉴定和功能分析。

这项研究旨在构建基于长非编码RNA（lncRNA）的预后标志，以改善子宫内膜癌（EC）患者的生存预测并指导个体化治疗。从癌症基因组图谱数据库中收集了526例EC患者的mRNA和miRNA测序以及临床数据（随机分为训练或验证集，n = 263）。在263个EC样品和33个正常对照之间鉴定出差异表达的基因（DEG），差异表达的lncRNA（DEL）和差异表达的miRNA（DEM）。单因素和多因素Cox回归分析确定了五个与整体生存相关的DEL（LINC00475，LINC01352，MIR503HG，KCNMB2-AS1和LINC01143）。Kaplan-Meier曲线表明，由这五个DEL建立的风险评分模型可以明显地区分高危患者和低危患者的生存率。接收者的操作特征曲线表明该风险评分表现出良好的生存预测性能，曲线下面积为0.978。此外，该风险评分与其他临床因素无关。基于两个独立的预后临床因素（组织学等级和复发状态）的分层分析表明，对于组织学3级，复发或非复发状态的患者，高风险评分仍然是不良的预后因素。在列线图模型中，风险评分是存活率的主要贡献之一，其Harrell' 一致性指数高于其他两个独立的临床因素，尽管均低于综合因素。此外，机理分析表明，这些lncRNA通过与DEGs共表达而发挥作用（即LINC00475-PTGDR，LINC01352 / MIR503HG-BACH2，KCNMB2-AS1-PCSK9，LINC01143-NUF2 / PTTG1）或作为DEM的竞争性内源RNA来调控DEGs（ LINC00475-miR-4728-PTGDR，MIR503HG-miR-3170-BACH2）。总之，我们新颖的风险评分系统可能是指导EC患者个性化治疗的有前途的预后生物标志物，并且可以为当前临床系统增加预后价值。LINC01143-NUF2 / PTTG1）或作为DEM竞争性内源RNA来调节DEG（LINC00475-miR-4728-PTGDR，MIR503HG-miR-3170-BACH2）。总之，我们新颖的风险评分系统可能是指导EC患者个性化治疗的有前途的预后生物标志物，并且可以为当前临床系统增加预后价值。LINC01143-NUF2 / PTTG1）或作为DEM竞争性内源RNA来调节DEG（LINC00475-miR-4728-PTGDR，MIR503HG-miR-3170-BACH2）。总之，我们新颖的风险评分系统可能是指导EC患者个性化治疗的有前途的预后生物标志物，并且可以为当前临床系统增加预后价值。