Research Papers:

Circulating miR-31 as an effective biomarker for detection and prognosis of human cancer: a meta-analysis

Yingjun Ma, Yunfang Chen, Jinbo Lin, Yi Liu, Kai Luo, Yong Cao, Tieqiang Wang, Hongwei Jin, Zhan Su, Haolin Wu, Xiaoliang Chen _ and Jinquan Cheng

PDF  |  HTML  |  Supplementary Files  |  How to cite  |  Order a Reprint

Oncotarget. 2017; 8:28660-28671. https://doi.org/10.18632/oncotarget.15638

Metrics: PDF 921 views  |   HTML 1563 views  |   ?  


Yingjun Ma1,*, Yunfang Chen2,*, Jinbo Lin3,*, Yi Liu4, Kai Luo5, Yong Cao4, Tieqiang Wang4, Hongwei Jin4, Zhan Su4, Haolin Wu4, Xiaoliang Chen4, Jinquan Cheng6

1Respiratory Medicine, Guangming District People’s Hospital of Shenzhen, Shenzhen, P.R. China

2Pain Department, The Eight Affiliated Hospital, Sun Yat-sen University, Shenzhen, P.R. China

3Medical oncology, Longgang District Central Hospital of Shenzhen, Shenzhen, P.R. China

4Center for Chronic Disease Control and Prevention, Shenzhen Guangming District Center for Disease Control and Prevention, Shenzhen, P.R. China

5Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, P.R. China

6Molecular Biology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen, P.R. China

*These authors have contributed equally to this work

Correspondence to:

Xiaoliang Chen, email: 120497143@qq.com

Jinquan Cheng, email: cjinquan@szcdc.net

Keywords: miR-31, carcinoma, detection, prognosis, meta-analysis

Received: December 07, 2016     Accepted: January 29, 2017     Published: February 23, 2017


Purpose: Circulating miR-31 was found to be associated with cancers detection and prognosis. The present meta-analysis aimed to explore the effect of circulating miR-31 on cancer detection and prognosis.

Method: The studies were accessed using multiple databases. RevMan5.3, Meta-DiSc 1.4, and STATA14.0 were used to estimate the pooled effects, heterogeneity among studies, and publication bias.

Results: A total of 14 studies with 1397 cancer patients and 1039 controls were included. For the 12 prognostic tests, the adjusted pooled-AUC was 0.79 (95% CI: 0.73-0.86) as the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odd ratio (DOR) from 10 tests was 0.79 (95% CI: 0.76-0.82), 0.79 (95% CI: 0.76-0.82), 3.81 (95% CI: 2.90-5.01), 0.26 (95% CI: 0.20-0.35), and 16.81 (95% CI: 9.67-29.25), respectively. For the 5 prognosis analyses, the pooled HR (hazard ratio) of overall survival (OS) was 1.55 (95% CI 1.30-1.86) for high versus low circulating miR-31 expression. However, high expression of circulating miR-31 did not significantly increase the risk of poor differentiation (pooled OR=1.39, 95% CI: 0.56-3.47) and LNM (pooled OR=3.46, 95% CI: 0.96-12.42) in lung cancer.

Conclusion: Circulating miR-31 is an effective biomarker and could be used as a component of miRs signature for cancer detection and prognosis surveillance.

Creative Commons License All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.
PII: 15638