HOTAIR as a Prognostic Predictor for Diverse Human Cancers: A Meta- and Bioinformatics Analysis

Several studies suggest that upregulated expression of the long non-coding RNA ( ) is a negative predictive biomarker for numerous cancers. Herein, we performed a meta-analysis to further investigate the prognostic value of expression in diverse human cancers. To this end, a systematic literature re...

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Bibliographic Details
Published in:Cancers 2019-06, Vol.11 (6), p.778
Main Authors: Toy, Halil Ibrahim, Okmen, Didem, Kontou, Panagiota I, Georgakilas, Alexandros G, Pavlopoulou, Athanasia
Format: Article
Language:English
Subjects:
Antisense RNA
Bioinformatics
Biomarkers
Cancer
Cell growth
Cervical cancer
Clinical trials
Epigenetics
Gene expression
Genomes
Leukemia
Literature reviews
Medical Subject Headings-MeSH
Meta-analysis
Metastases
Metastasis
Non-coding RNA
Proteins
RNA polymerase
Survival
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Summary:Several studies suggest that upregulated expression of the long non-coding RNA ( ) is a negative predictive biomarker for numerous cancers. Herein, we performed a meta-analysis to further investigate the prognostic value of expression in diverse human cancers. To this end, a systematic literature review was conducted in order to select scientific studies relevant to the association between expression and clinical outcomes, including overall survival (OS), recurrence-free survival (RFS)/disease-free survival (DFS), and progression-free survival (PFS)/metastasis-free survival (MFS) of cancer patients. Collectively, 53 eligible studies including a total of 4873 patients were enrolled in the current meta-analysis. Pooled hazard ratios (HRs) with their corresponding 95% confidence intervals (CIs) were calculated to assess the relationship between and cancer patients' survival. Elevated expression was found to be significantly associated with OS, RFS/DFS and PFS/MFS in diverse types of cancers. These findings were also corroborated by the results of bioinformatics analysis on overall survival. Therefore, based on our findings, could serve as a potential biomarker for the prediction of cancer patient survival in many different types of human cancers.
ISSN:2072-6694
2072-6694
DOI:10.3390/cancers11060778