Long non-coding RNA as a potential biomarker for prognosis of glioma: A protocol for systematic review and meta-analysis. Issue 33 (20th August 2021)

• Record Type: Journal Article
• Authors: Xie, Teng; Li, Bin; Liu, Huaming; Zhang, Chunwei; Wang, Yanhua; Chen, Zhijun; Yan, Junping
• Is Part Of: Medicine. Volume 100:Issue 33(2021)
• Page Start: e26921
• Publication Date: 2021-08-20
• Subjects: glioma -- long non-coding RNA -- meta-analysis -- prognosis -- protocol; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000026921
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract: Background: The molecular mechanism of Glioma is still unclear, and there are few early diagnostic markers. Therefore, it is urgent to figure out effective preventive measures, active diagnostic methods and rapid treatment measures. In recent years, relevant studies have revealed that long non-coding RNA (lncRNA) is associated with the prognosis of Glioma. However, these results have not been supported by any evidence. Therefore, this study carried out a meta-analysis method to analyze the relationship between lncRNA and the prognosis of Glioma. In addition, bioinformatics analysis was conducted to investigate the mechanism and related pathways of lncRNAs in Glioma. Methods: We performed a systematic search in electronic databases, including China National Knowledge Infrastructure, Chinese Biomedical literature Database, Chinese Scientific and Journal Database, Wan Fang database, PubMed, EMBASE, Cochrane Library and Web of Science, to investigate the potential association between lncRNA expression and prognostic significance and clinical features in glioma patients. Hazards ratios (HRs) with corresponding 95% confidence intervals (CIs) were pooled to estimate the prognosis value of lncRNA by Stata16.0 software. The online tool AnnoLnc was applied to screen the co-expressed gene related to each lncRNA, David was used for gene ontology (GO) analysis and enrichment analysis of the signal pathway, and through Starbase, the possible competitive endogenous RNA network of lncRNAs was constructed. Results: The results of this meta-analysis would be submitted to peer-reviewed journals for publication. Conclusion: This study will provide evidence-based medical evidence for lncRNA, so as to predict the prognosis of Glioma and bioinformatics analysis will provide ideas for the mechanism study on Glioma.