共 30 条
Long non-coding RNAs as prognostic biomarkers in papillary renal cell carcinoma
被引:22
作者:

Yang, Feilong
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机构:
Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China

Song, Yimeng
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Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China

Ge, Liyuan
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机构:
Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China

Zhao, Guojiang
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机构:
Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China

Liu, Cheng
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h-index: 0
机构:
Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China

Ma, Lulin
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h-index: 0
机构:
Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China
机构:
[1] Peking Univ, Hosp 3, Dept Urol, 49 North Garden Rd, Beijing 100191, Peoples R China
基金:
中国国家自然科学基金;
关键词:
long non-coding RNAs;
prognostic biomarker;
papillary renal cell carcinoma;
bioinformatics;
POOR-PROGNOSIS;
CANCER;
LNCRNA;
EXPRESSION;
PROMOTES;
PREDICTS;
PROLIFERATION;
PROGRESSION;
PANDAR;
D O I:
10.3892/ol.2019.10684
中图分类号:
R73 [肿瘤学];
学科分类号:
100214 ;
摘要:
The aim of the present study was to identify long non-coding RNA (lncRNA)-based prognostic biomarkers in papillary renal cell carcinoma (pRCC). lncRNA expression data and corresponding clinical data from patients with pRCC were obtained from The Cancer Genome Atlas. R software and packages were used for data analysis. Univariate Cox regression analysis and least absolute shrinkage and selection operator regression were performed to identify key lncRNAs, which were then used to construct a prognostic model using multivariate Cox regression analysis. Patients were divided into high- and low-risk groups, and Kaplan-Meier (KM) survival curves and time-dependent receiver operating characteristic (ROC) curves were plotted. The C-index was calculated to estimate the model's prognostic power. The hazard ratio (HR), 95% confidence interval (CI), and statistical significance of each key lncRNA were also calculated by multivariate Cox regression. Based on the result of the multivariate Cox regression analysis, KM survival plots were plotted for each significantly associated lncRNA. The subcellular locations of the prognostic biomarkers were predicted using lncRNAMap and lncLocator. A total of 17 lncRNA signatures were identified as key lncRNAs. Overall survival rate was significantly higher in the low-risk group compared with the high-risk group. The areas under the ROC curve were 0.93 (3-year ROC) and 0.902 (5-year ROC), and the C-index was 0.915. A forest plot was used to illustrate the HR and 95% CI of key lncRNAs. KM survival analysis revealed the prognostic significance of two protective biomarkers, AC024022.1 and GAS6-AS1, and three adverse biomarkers, AC087379.2, AL352984.1, and AL499627.1. It was predicted that AC024022.1 and AC087379.2 may be located in the cytoplasm and GAS6-AS1 may be located in the cytosol. The present study may contribute to the management of pRCC and serve as a foundation for further investigations into the underlying mechanism of tumorigenesis and progression of pRCC.
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收藏
页码:3691 / 3697
页数:7
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