Research Papers:
Long noncoding RNA MEG3, a potential novel biomarker to predict the clinical outcome of cancer patients: a meta-analysis
Metrics: PDF 1956 views | HTML 2737 views | ?
Abstract
Xiangrong Cui1,2,3,*, Xuan Jing5,*, Chunlan Long1,2,3, Jie Tian4, Jing Zhu1,2,3
1Pediatric Research Institute, Children's Hospital of Chongqing Medical University, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, 400014, China
2China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Chongqing, 400014, China
3Chongqing Key Laboratory of Pediatrics, Chongqing, 400014, China
4Cardiovascular Department (Internal Medicine), Children's Hospital of Chongqing Medical University, Chongqing, 400014, China
5Clinical Laboratory, Shanxi Province People’s Hospital, Shanxi, 030000, China
*These authors contributed equally to this work
Correspondence to:
Jing Zhu, email: [email protected]
Keywords: lncRNA, MEG3, clinical outcome, carcinoma, meta-analysis
Received: December 05, 2016 Accepted: January 11, 2017 Published: February 01, 2017
ABSTRACT
Numerous studies have demonstrated that the expression level of maternally expressed gene 3 (MEG3) was lost in various cancers. Low expression of MEG3 is associated with an increased risk of metastasis and a poor prognosis in cancer patients. This meta-analysis investigated the association between MEG3 levels and distant metastasis (DM), lymph node metastasis (LNM), overall survival (OS), and recurrence-free survival (RFS) of cancer patients. A total of 536 participants from 9 articles were finally enrolled. The results showed a significant negative association between MEG3 levels and DM (OR = 2.16, 95% CI = 0.99–4.71, P = 0.05, fixed-effect), and it could also predict poor OS (HR = 0.43, 95% CI = 0.15–1.24, P = 0.006, fixed-effect) and RFS (HR = 0.52, 95% CI = 0.29–0.92, P = 0.02, fixed-effect) in cancer patients. In conclusion, this meta-analysis indicated that MEG3 might serve as a potential novel biomarker for indicating the clinical outcomes in human cancers.
![Creative Commons License](/images/80x15.png)
PII: 14987