目的

探讨血管生成相关长链非编码RNA（LncRNA）在膀胱尿路上皮癌（BLCA）中的预后作用，并建立BLCA 血管生成相关LncRNA 预后评估模型。

方法

从TCGA 数据库下载BLCA 的RNA 测序和临床数据，从分子特征数据库获取最新人类血管生成基因列表，计算每个LncRNA 与每个血管生成基因的相关系数，获得与血管生成基因显著相关的LncRNA，使用R 软件对每个LncRNA 进行单因素和多因素Cox 回归分析，结合Kaplan-Meier 法筛选与BLCA 预后相关的LncRNA，绘制相关LncRNA 与BLCA 患者生存期的Kaplan-Meier 曲线，计算每个样本的风险评分，根据评分将样本分为高风险组和低风险组，比较两组患者的生存期差异，绘制ROC 曲线评估模型预测效能，采用Cox 回归分析风险评分和患者临床特征与生存期的相关性。

结果

初筛识别了207 个与BLCA 血管生成相关的LncRNA（相关系数|R|＞0.4，P＜0.001）。进一步通过Cox 回归分析，筛选出9 个与BLCA 预后独立相关的血管生成相关LncRNA，用于建立BLCA 预后评估模型。根据该模型将患者分为高风险组和低风险组，高风险组患者生存期显著短于低风险组（P＜0.05）。模型ROC曲线下面积为0.716，表明模型具有较好的预测效能。风险评分与患者年龄、肿瘤分级、病理分期及T分期呈正相关（P＜0.05），是BLCA 的独立预后预测因子。

结论

基于血管生成相关LncRNA 的预后评估模型，可为BLCA 患者提供精准的预后判断，有助于指导BLCA 的个体化治疗方案选择和预后评估。

Objective

To investigate the prognostic role of long non-coding RNA （LncRNA）in bladder urothelial carcinoma （BLCA） and to establish a prognostic assessment model of BLCA angiogenesis-associated LncRNA.

Methods

The RNA sequencing and clinical data of BLCA were downloaded from the TCGA database， and the latest list of human angiogenesis genes was obtained from the molecular characteristics database.The correlation coefficient between each LncRNA and each angiogenesis gene was calculated， and LncRNA significantly correlated with angiogenesis genes were obtained.Univariate and multivariate Cox regression analysis was performed for each LncRNA using R software， and the LncRNA associated with BLCA prognosis was screened by Kaplan-Meier method.Kaplan-Meier curves of survival time of relevant LncRNA and BLCA patients were drawn， and the risk score of each sample was calculated.According to the score， the samples were divided into high-risk group and low-risk group， and the differences in survival between the two groups were compared.The ROC curve was drawn to evaluate the predictive ability of the model， and Cox regression was used to analyze the correlation between the risk score and patients' clinical characteristics and survival.

Results

Initial screening identified 207 LncRNA associated with BLCA angiogenesis （correlation coefficient |R|＞0.4，P＜0.001）.Cox regression analysis was used to select 9 angiogenesis-related LncRNA that independently correlated with BLCA prognosis to establish a prognostic assessment model for BLCA.According to the model， patients were divided into high-risk and low-risk groups， and the survival of patients in the high-risk group was significantly shorter than that in the low-risk group （P＜0.05）.The area under the ROC curve of the model is 0.716， indicating that the model has good predictive efficiency.The risk score was positively correlated with age， tumor grade， pathological stage and T stage （P＜0.05） and was an independent prognostic predictor of BLCA.

Conclusion

The prognostic assessment model based on LncRNA associated with angiogenesis can provide accurate prognostic assessment for BLCA patients and help guide individualized treatment selection and prognostic assessment for BLCA patients.