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Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma
BACKGROUND: Glioma is the most common form of primary malignant intracranial tumor. METHODS: In the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNA...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528815/ https://www.ncbi.nlm.nih.gov/pubmed/33062427 http://dx.doi.org/10.7717/peerj.9943 |
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author | Ji, Baowei Chen, Lihua Cai, Qiang Guo, Qiao Chen, Zhibiao He, Du |
author_facet | Ji, Baowei Chen, Lihua Cai, Qiang Guo, Qiao Chen, Zhibiao He, Du |
author_sort | Ji, Baowei |
collection | PubMed |
description | BACKGROUND: Glioma is the most common form of primary malignant intracranial tumor. METHODS: In the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNAs and multivariate Cox regression analysis was applied to establish a miRNA signature for predicting overall survival (OS) of glioma. The signature was assessed with the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and validated by data from Gene Expression Omnibus (GEO). RESULTS: Eight miRNAs (miR-1246, miR-148a, miR-150, miR-196a, miR-338-3p, miR-342-5p, miR-548h and miR-645) were included in the miRNA signature. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. The AUC in both the CGGA and GEO datasets was similar to that based on WHO 2007 classification (0.736 and 0.799) and WHO 2016 classification (0.663 and 0.807). Additionally, Kaplan–Meier plot revealed that high-risk score patients had a poorer clinical outcome. Multivariate Cox regression analysis suggested that the miRNA signature was an independent prognosis-related factor [HR: 6.579, 95% CI [1.227−35.268], p = 0.028]. CONCLUSION: On the whole, in the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. The results may be conducive to predict the precise prognosis of glioma and to elucidate the underlying molecular mechanisms. However, further experimental researches of miRNAs are needed to validate the findings of this study. |
format | Online Article Text |
id | pubmed-7528815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75288152020-10-13 Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma Ji, Baowei Chen, Lihua Cai, Qiang Guo, Qiao Chen, Zhibiao He, Du PeerJ Bioinformatics BACKGROUND: Glioma is the most common form of primary malignant intracranial tumor. METHODS: In the current study, miRNA matrix were obtained from the Chinese Glioma Genome Atlas (CGGA), and then univariate Cox regression analysis and Lasso regression analysis were utilized to select candidate miRNAs and multivariate Cox regression analysis was applied to establish a miRNA signature for predicting overall survival (OS) of glioma. The signature was assessed with the area under the curve (AUC) of the receiver operating characteristic curve (ROC) and validated by data from Gene Expression Omnibus (GEO). RESULTS: Eight miRNAs (miR-1246, miR-148a, miR-150, miR-196a, miR-338-3p, miR-342-5p, miR-548h and miR-645) were included in the miRNA signature. The AUC of ROC analysis for 1- and 3-year OS in the CGGA dataset was 0.747 and 0.905, respectively. In the GEO dataset, The AUC for 1- and 3-year was 0.736 and 0.809, respectively. The AUC in both the CGGA and GEO datasets was similar to that based on WHO 2007 classification (0.736 and 0.799) and WHO 2016 classification (0.663 and 0.807). Additionally, Kaplan–Meier plot revealed that high-risk score patients had a poorer clinical outcome. Multivariate Cox regression analysis suggested that the miRNA signature was an independent prognosis-related factor [HR: 6.579, 95% CI [1.227−35.268], p = 0.028]. CONCLUSION: On the whole, in the present study, based on eight miRNAs, a novel prognostic signature was developed for predicting the 1- and 3- year survival rate in glioma. The results may be conducive to predict the precise prognosis of glioma and to elucidate the underlying molecular mechanisms. However, further experimental researches of miRNAs are needed to validate the findings of this study. PeerJ Inc. 2020-09-28 /pmc/articles/PMC7528815/ /pubmed/33062427 http://dx.doi.org/10.7717/peerj.9943 Text en ©2020 Ji et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Ji, Baowei Chen, Lihua Cai, Qiang Guo, Qiao Chen, Zhibiao He, Du Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma |
title | Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma |
title_full | Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma |
title_fullStr | Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma |
title_full_unstemmed | Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma |
title_short | Identification of an 8-miRNA signature as a potential prognostic biomarker for glioma |
title_sort | identification of an 8-mirna signature as a potential prognostic biomarker for glioma |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528815/ https://www.ncbi.nlm.nih.gov/pubmed/33062427 http://dx.doi.org/10.7717/peerj.9943 |
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