Meta-Analysis:
lncRNAs as prognostic molecular biomarkers in hepatocellular carcinoma: a systematic review and meta-analysis
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Abstract
Chuqian Zheng1,2,3, Xiuxia Liu2, Leifeng Chen1,2,3, Zheng Xu1,2,3 and Jianghua Shao1,2,3
1Department of General Surgery, Second Affiliated Hospital of Nanchang University, Nanchang, 330000, China
2Jiangxi Province Key Laboratory of Molecular Medicine, Nanchang, 330000, China
3Jiangxi Province Engineering Research Center of Hepatobiliary Disease, Nanchang, 330000, China
Correspondence to:
Jianghua Shao, email: [email protected]
Keywords: lncRNA, hepatocellular carcinoma (HCC), survival, prognostic, meta-analysis
Received: April 07, 2017 Accepted: July 12, 2017 Published: July 25, 2017
ABSTRACT
The latest studies have shown that long non-coding RNAs (lncRNAs) may be considered markers as their expression levels were abnormal in cancer and can be used as a molecular biomarker for the potential assessment of cancer prognosis. In this study, we aimed to assess the prognostic value of lncRNA as marker of patients with hepatocellular carcinoma. We performed a detailed search of the PubMed and Embase databases for articles on the prognostic value of various lncRNAs in HCC. We then carefully extracted the relevant data from the articles, and we used the meta-analysis method to analyze these results; heterogeneity and publication bias were also evaluated. With 40 associative studies included, we found that high expression of 27 types of lncRNA was associated with a poor prognosis in HCC patients, and low expression of 18 types of lncRNAs was associated with a worse prognosis. Patients with higher lncRNA expression had significantly poor overall survival (OS; pooled HR, 1.25; 95% confidence interval [CI], 1.03–1.52) as well as significantly poor recurrence-free survival (RFS; pooled HR, 1.66; 95% CI, 1.26–2.17). Overexpression of lncRNAs may not meaningfully predict disease-free survival (DFS; pooled HR, 1.04; 95% CI, 0.52–2.07; p = 0.91). Our meta-analysis demonstrated that lncRNAs may serve as predictive biomarkers for cancer prognosis.
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