列线图
肾透明细胞癌
比例危险模型
单变量
肿瘤科
肾细胞癌
长非编码RNA
医学
内科学
接收机工作特性
生存分析
队列
多元统计
生物
基因
核糖核酸
统计
遗传学
数学
作者
Chuanjie Zhang,Da Huang,Ao Liu,Yang Xu,Rong Na,Danfeng Xu
摘要
Abstracts Clear cell renal cell carcinoma (ccRCC) is the main subtype of renal cell carcinoma with varied prognosis. We aimed to identify and assess the possible prognostic long noncoding RNA (lncRNA) biomarkers. LncRNAs expression data and corresponding clinical information of 619 ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Differentially expressed genes analysis, univariate Cox regression, the least absolute shrinkage and selection operator Cox regression model were utilized to identify hub lncRNAs. Multivariate Cox regression was used to establish the risk model. Statistical analysis was performed using R 3.5.3. The expression value of five lncRNAs and the risk‐score levels were significantly associated with a survival prognosis of ccRCC patients (all P < .001). In the TCGA validation cohort, the area under the curve (AUC) for the integrated nomogram was 0.905 and 0.91 for 3‐, 5‐year prediction separately. The AUC reached up to 0.757 in an independent ICGC cohort. Besides, the calibration plots also illustrated well curve‐fitting between observation values and predictive values. Weighted gene co‐expression network analysis and subsequent pathway analysis revealed that the PI3K‐Akt‐mTOR and hypoxia‐inducible factor signaling crosstalk might function as the most essential mechanisms related to the five‐lncRNAs signature. Our study suggested that lncRNA AC009654.1, AC092490.2, LINC00524, LINC01234, and LINC01885 were significantly associated with ccRCC prognosis. The prognostic model based on this five lncRNA may predict the overall survival of ccRCC.
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