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The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis
BACKGROUND: Cancer has been a worldwide health problem with a high risk of morbidity and mortality, however ideal biomarkers for effective screening and diagnosis of cancer patients are still lacking. Small nucleolar RNA host gene 16 (SNHG16) is newly identified lncRNA with abnormal expression in se...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6788067/ https://www.ncbi.nlm.nih.gov/pubmed/31632195 http://dx.doi.org/10.1186/s12935-019-0971-2 |
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author | Zhang, Chenghao Ren, Xiaolei He, Jieyu Wang, Wanchun Tu, Chao Li, Zhihong |
author_facet | Zhang, Chenghao Ren, Xiaolei He, Jieyu Wang, Wanchun Tu, Chao Li, Zhihong |
author_sort | Zhang, Chenghao |
collection | PubMed |
description | BACKGROUND: Cancer has been a worldwide health problem with a high risk of morbidity and mortality, however ideal biomarkers for effective screening and diagnosis of cancer patients are still lacking. Small nucleolar RNA host gene 16 (SNHG16) is newly identified lncRNA with abnormal expression in several human malignancies. However, its prognostic value remains controversial. This meta-analysis aimed to synthesize available data to clarify the association between SNHG16 expression levels and clinical prognosis value in multiple cancers. METHODS: Extensive literature retrieval was conducted to identify eligible studies, and data regarding SNHG16 expression levels on survival outcomes and clinicopathological features were extracted and pooled for calculation of the hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs). Forest plots were applied to show the association between SNHG16 expression and survival prognosis. Additionally, The Cancer Genome Atlas (TCGA) dataset was screened and extracted for validation of the results in this meta-analysis. RESULTS: A total of eight studies comprising 568 patients were included in the final meta-analysis according to the inclusion and exclusion criteria. In the pooled analysis, high SNHG16 expression significantly predicted worse overall survival (OS) in various cancers (HR = 1.87, 95% CI 1.54–2.26, P < 0.001), and recurrence-free survival (RFS) in bladder cancer (HR = 1.68, 95% CI 1.01–2.79, P = 0.045). Meanwhile, stratified analyses revealed that the survival analysis method, tumor type, sample size, and cut-off value did not alter the predictive value of SNHG16 for OS in cancer patients. In addition, compared to the low SNHG16 expression group, patients with high SNHG16 expression were more prone to worse clinicopathological features, such as larger tumor size, advanced clinical stage, lymph node metastasis (LNM) and distant metastasis (DM). Exploration of TCGA dataset further validated that the upregulated SNHG16 expression predicted unfavorable OS and disease-free survival (DFS) in cancer patients. CONCLUSIONS: The present study implicated that aberrant expression of lncRNA SNHG16 was strongly associated with clinical survival outcomes in various cancers, and therefore might serve as a promising biomarker for predicting prognosis of human cancers. |
format | Online Article Text |
id | pubmed-6788067 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-67880672019-10-18 The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis Zhang, Chenghao Ren, Xiaolei He, Jieyu Wang, Wanchun Tu, Chao Li, Zhihong Cancer Cell Int Primary Research BACKGROUND: Cancer has been a worldwide health problem with a high risk of morbidity and mortality, however ideal biomarkers for effective screening and diagnosis of cancer patients are still lacking. Small nucleolar RNA host gene 16 (SNHG16) is newly identified lncRNA with abnormal expression in several human malignancies. However, its prognostic value remains controversial. This meta-analysis aimed to synthesize available data to clarify the association between SNHG16 expression levels and clinical prognosis value in multiple cancers. METHODS: Extensive literature retrieval was conducted to identify eligible studies, and data regarding SNHG16 expression levels on survival outcomes and clinicopathological features were extracted and pooled for calculation of the hazard ratios (HRs) or odds ratios (ORs) with 95% confidence intervals (CIs). Forest plots were applied to show the association between SNHG16 expression and survival prognosis. Additionally, The Cancer Genome Atlas (TCGA) dataset was screened and extracted for validation of the results in this meta-analysis. RESULTS: A total of eight studies comprising 568 patients were included in the final meta-analysis according to the inclusion and exclusion criteria. In the pooled analysis, high SNHG16 expression significantly predicted worse overall survival (OS) in various cancers (HR = 1.87, 95% CI 1.54–2.26, P < 0.001), and recurrence-free survival (RFS) in bladder cancer (HR = 1.68, 95% CI 1.01–2.79, P = 0.045). Meanwhile, stratified analyses revealed that the survival analysis method, tumor type, sample size, and cut-off value did not alter the predictive value of SNHG16 for OS in cancer patients. In addition, compared to the low SNHG16 expression group, patients with high SNHG16 expression were more prone to worse clinicopathological features, such as larger tumor size, advanced clinical stage, lymph node metastasis (LNM) and distant metastasis (DM). Exploration of TCGA dataset further validated that the upregulated SNHG16 expression predicted unfavorable OS and disease-free survival (DFS) in cancer patients. CONCLUSIONS: The present study implicated that aberrant expression of lncRNA SNHG16 was strongly associated with clinical survival outcomes in various cancers, and therefore might serve as a promising biomarker for predicting prognosis of human cancers. BioMed Central 2019-10-11 /pmc/articles/PMC6788067/ /pubmed/31632195 http://dx.doi.org/10.1186/s12935-019-0971-2 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Primary Research Zhang, Chenghao Ren, Xiaolei He, Jieyu Wang, Wanchun Tu, Chao Li, Zhihong The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis |
title | The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis |
title_full | The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis |
title_fullStr | The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis |
title_full_unstemmed | The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis |
title_short | The prognostic value of long noncoding RNA SNHG16 on clinical outcomes in human cancers: a systematic review and meta-analysis |
title_sort | prognostic value of long noncoding rna snhg16 on clinical outcomes in human cancers: a systematic review and meta-analysis |
topic | Primary Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6788067/ https://www.ncbi.nlm.nih.gov/pubmed/31632195 http://dx.doi.org/10.1186/s12935-019-0971-2 |
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