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中华腔镜泌尿外科杂志(电子版) ›› 2023, Vol. 17 ›› Issue (03) : 270 -275. doi: 10.3877/cma.j.issn.1674-3253.2023.03.015

实验研究

基于TCGA数据库Wnt相关长链非编码RNA构建肾乳头状细胞癌预后模型
唐国军1, 洪余德1, 赵崇玉1, 李辽源1,()   
  1. 1. 510630 广州,中山大学附属第三医院泌尿外科
  • 收稿日期:2023-02-13 出版日期:2023-06-01
  • 通信作者: 李辽源
  • 基金资助:
    国家自然科学基金(81972419,81772753)

A novel prognosis model for papillary renal cell carcinoma based on Wnt-associated lncRNAs in TCGA database

Guojun Tang1, Yude Hong1, Chongyu Zhao1, Liaoyuan Li1,()   

  1. 1. Department of Urology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
  • Received:2023-02-13 Published:2023-06-01
  • Corresponding author: Liaoyuan Li
引用本文:

唐国军, 洪余德, 赵崇玉, 李辽源. 基于TCGA数据库Wnt相关长链非编码RNA构建肾乳头状细胞癌预后模型[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2023, 17(03): 270-275.

Guojun Tang, Yude Hong, Chongyu Zhao, Liaoyuan Li. A novel prognosis model for papillary renal cell carcinoma based on Wnt-associated lncRNAs in TCGA database[J/OL]. Chinese Journal of Endourology(Electronic Edition), 2023, 17(03): 270-275.

目的

构建一种Wnt通路相关的长链非编码RNA(LncRNAs)的肾乳头状细胞癌(pRCC)预后模型。

方法

经癌症基因组图谱(TCGA)获取pRCC患者的转录组数据和对应的临床信息。采用共表达网络分析、COX回归和Lasso分析方法筛选出Wnt相关的LncRNA用于构建风险预后模型。此外,通过绘制受试者工作特征(ROC)曲线验证模型的预测性能。

结果

构建了由5个Wnt相关的LncRNAs(CT66,PRECSIT,AL352984.1,AC124798.1,AC011503.2)组成的肾乳头状细胞癌预后模型。生存分析结果表明,该模型在TCGA训练组(P=0.002)、测试组(P=0.013)和完整组(P<0.001)中均具有较好的有效性。将风险评分作为独立预后指标时,完整组患者5年总生存率的ROC曲线下面积(AUC)为0.708。

结论

由5个Wnt相关lncRNA构建的新的预后模型有助于评估pRCC患者的预后。

Objective

To construct a prognostic model of Wnt associated long non-coding RNAs (LncRNAs) in papillary renal cell carcinoma (pRCC).

Methods

The data for ranscriptome and clinical information of pRCC patients were obtained by The Cancer Genome Atlas (TCGA). Wnt-associated LncRNAs were selected by co-expression network analysis, COX regression, and Lasso analysis to build the risk prognosis model. In addition, the predictive performance of this model is verified by receiver operating characteristic (ROC) curves.

Results

Five Wnt-associated LncRNAs (CT66, PRECSIT, AL352984.1, AC124798.1, and AC011503.2) were chosen to construct a prognostic model of pRCC. Survival analyses showed that the model have predictive validity in TCGA training group (P=0.002), testing group (P=0.013) and combined group (P<0.001). When the risk score was used as an independent prognostic indicator, the area under ROC curve (AUC) for 5-year overall survival in the combined group was 0.708, indicating acceptable predictive performance.

Conclusion

The prognosis model including 5 Wnt-associated LncRNAs is helpful to evaluate the prognosis of pRCC patients.

表1 肾乳头状细胞癌患者临床病理资料(例)
图1 与Wnt相关的预后LncRNAs森林图
图2 23个Wnt相关LncRNAs在肿瘤组和正常组的差异表达注:*P<0.05,**P<0.01,***P<0.001
图3 Wnt相关LncRNAs的Lasso系数的分布
图4 Lasso分析中通过10次交叉验证进行变量选择
图5 风险模型中Wnt相关LncRNAs的表达量热图
图6 不同组别Wnt相关lncRNAs风险模型的预后注:将生存风险评分(a)、生存时间和生存状态(b)、肾癌患者的Kaplan-Meier生存曲线(c)分别在完整组(左)、训练组(中)和测试组(右)之间进行比较
表2 multiCox方法建立肾乳头状细胞癌Wnt相关LncRNAs临床预测模型
图7 Wnt相关lncRNAs风险模型预测pRCC患者预后的ROC曲线
图8 Wnt相关lncRNAs风险模型与临床病理特征对完整组的预测准确性比较
表3 单因素和多因素COX回归结果
表4 肾乳头状细胞癌高低风险组差异基因GO分析和KEGG分析
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