Background: Several studies demonstrated that long non-coding RNA differentiation antagonizing non-protein coding RNA (lncRNA DANCR) expression might have the potential capacity to predict the cancer prognosis, however, definite conclusion has not been obtained. The aim of this meta-analysis was to evaluate the prognostic value of lncRNA DANCR expression in cancers. Methods: PubMed, Web of Science, Scopus and Embase were comprehensively searched for relevant studies. Studies meeting all inclusion standards were included into this meta-analysis. The analysis of overall survival (OS), disease-free survival (DFS) or clinicopathological features was conducted. Results: Eleven studies containing 1,154 cancer patients were analyzed in this meta-analysis. The results showed, compared with low lncRNA DANCR expression, high lncRNA DANCR expression was significantly associated with shorter OS (HR=1.85, 95%CI=1.52-2.26, P<0.01) and DFS (HR=1.82, 95%=1.43-2.32, P<0.01) in cancers. Besides, high lncRNA DANCR expression predicted deeper tumor invasion (P<0.01), earlier lymph node metastasis (P<0.01), earlier distant metastasis (P<0.01) and more advanced clinical stage (P<0.01) compared with low lncRNA DANCR expression in cancer populations. Conclusion: High lncRNA DANCR expression was associated with worse prognosis compared with low lncRNA DANCR expression in cancers. LncRNA DANCR expression could serve as a prognostic factor of human cancers.
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Research Article|
March 25 2019
Prognostic significance of long non-coding RNA DANCR expression in human cancers: A systematic review and meta-analysis
Qin-Peng Wang
;
Qin-Peng Wang
Lanzhou University, Lanzhou, China
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Jia Guo
Lanzhou University, Lanzhou, China
* Corresponding Author; email: lanzhou_guojia@hotmail.com
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Biosci Rep (2019) BSR20181627.
Article history
Received:
September 15 2018
Revision Received:
January 20 2019
Accepted:
February 07 2019
Citation
Wei Liu, Qin-Peng Wang, Jia Guo; Prognostic significance of long non-coding RNA DANCR expression in human cancers: A systematic review and meta-analysis
. Biosci Rep 2019; BSR20181627. doi: https://doi.org/10.1042/BSR20181627Download citation file:
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