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Systematic analyses of a novel lncRNA‐associated signature as the prognostic biomarker for Hepatocellular Carcinoma

Authors :
Jing Sui
Yan Miao
Jiali Han
Hongmei Nan
Bo Shen
Xiaomei Zhang
Yan Zhang
Yuan Wu
Wenjuan Wu
Tong Liu
Siyi Xu
Sheng Yang
Lihong Yin
Yuepu Pu
Geyu Liang
Source :
Cancer Medicine, Vol 7, Iss 7, Pp 3240-3256 (2018)
Publication Year :
2018
Publisher :
Wiley, 2018.

Abstract

Abstract Accumulating evidence implies that long noncoding RNAs (lncRNAs) play a crucial role in predicting survival for Hepatocellular carcinoma (HCC) patients. This study aims to capture the current research hotspots of HCC, based on the analysis of publications related to HCC research from 2013 to 2017, and to identify a novel lncRNA signature for HCC prognosis through the data mining in The Cancer Genome Atlas (TCGA). “Prognosis” and “biomarker” were located in the core of the HCC research hotspot. Moreover, long noncoding RNA was the top one research frontier in HCC research. The associations between survival outcome and the expression of lncRNAs were evaluated by the univariate and multivariate Cox proportional hazards regression analyses. Four lncRNAs (LINC00261, TRELM3P, GBP1P1, and CDKN2B‐AS1) were identified as significantly correlated with overall survival (OS). These four lncRNAs were gathered as a single prognostic signature. There was a significant positive correlation between HCC patients with low‐risk scores and overall survival (HR = 1.802, 95%CI [1.224‐2.652], P = .003). Further analysis suggested that the prognostic value of this four‐lncRNA signature was independent in clinical features. The enrichment analysis of prognostic lncRNA‐related gene was performed to find out the related pathways. Our study indicates that this novel lncRNA expression signature may be a useful biomarker of the prognosis for HCC patients, based on bioinformatics analysis.

Details

Language :
English
ISSN :
20457634
Volume :
7
Issue :
7
Database :
Directory of Open Access Journals
Journal :
Cancer Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.7c31a775b6d94bf898df530b502c5e1f
Document Type :
article
Full Text :
https://doi.org/10.1002/cam4.1541