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PMID: 29163187 Published · epublish English Journal Article

Prognostic Values of Long Noncoding RNA GAS5 in Various Carcinomas: An Updated Systematic Review and Meta-Analysis.

Frontiers in physiology ·Vol. 8 ·2017-00-00 ·Pages 814

Gao Q, Xie H, Zhan H, Li J, Liu Y, Huang W

Abstract

The growth arrest-specific transcript 5 (GAS5) is a long noncoding RNA with low expression in multiple cancers. This meta-analysis aims to explore the association between GAS5 expression levels and cancer patients' prognosis. We collected all the relevant literatures about GAS5 expression levels associated with overall survival (OS), lymph node metastasis (LNM) and high tumor stage (II/III/IV) (HTS) from the PubMed and Web of Science. The hazard ratio (HR) and the corresponding 95% confidence interval (CI) were calculated to evaluate the link strength between GAS5 and cancer prognosis. A total of 934 patients from 14 studies were included to the present meta-analysis, according to the inclusion and exclusion criteria. The results demonstrated that low expression of GAS5 could predict poor OS in cancer patients (HR = 1.955, 95% CI: 1.551-2.465, P < 0.001). Meanwhile we also analyzed the following cancers independently: hepatocellular carcinoma (HR = 1.893, 95% CI: 1.103-3.249, P = 0.021) and urothelial carcinoma (HR = 1.653, 95% CI: 1.185-2.306, P = 0.003). Compared to the high GAS5 expression group, additionally, patients with low GAS5 expression in tumor tissues were more prone to lymph node metastasis (OR = 0.234, 95%CI: 0.153-0.358, P < 0.001) and high tumor stage (OR = 0.185, 95% CI:0.102-0.333, P < 0.001). In conclusion, this meta-analysis showed that GAS5 might be served as a novel biomarker for predicting prognosis in various types of cancers.

Keywords
GAS5 cancer high tumor stage lncRNA lymph node metastasis meta-analysis prognosis
Authors & Affiliations
6 authors, click to expand affiliations / ORCID
Gao Qunjun
Key Laboratory of Medical Reprogramming Technology, Shenzhen Second People's Hospital, Graduate School of Guangzhou Medical University, Shenzhen, China. | Guangzhou Medical University, Guangzhou, China.
Xie Haibiao
Key Laboratory of Medical Reprogramming Technology, Shenzhen Second People's Hospital, Graduate School of Guangzhou Medical University, Shenzhen, China. | Shantou University Medical College, Shantou, China.
Zhan Hengji
Key Laboratory of Medical Reprogramming Technology, Shenzhen Second People's Hospital, Graduate School of Guangzhou Medical University, Shenzhen, China. | Shenzhen University, Shenzhen, China.
Li Jianfa
Key Laboratory of Medical Reprogramming Technology, Shenzhen Second People's Hospital, Graduate School of Guangzhou Medical University, Shenzhen, China.
Liu Yuchen
Key Laboratory of Medical Reprogramming Technology, Shenzhen Second People's Hospital, Graduate School of Guangzhou Medical University, Shenzhen, China.
Huang Weiren
Key Laboratory of Medical Reprogramming Technology, Shenzhen Second People's Hospital, Graduate School of Guangzhou Medical University, Shenzhen, China.
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Article Info
Journal
Frontiers in physiology
Abbr.
Front Physiol
ISSN
1664-042X
DOI
10.3389/fphys.2017.00814
Published
2017-00-00
Epub
2017-00-02
Pages
814
Language
English
Region
Switzerland
NLM ID
101549006
PMCID
PMC5673644
External Links
PubMed source DOI: 10.3389/fphys.2017.00814 PMC Full Text View journal details
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