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A prognostic signature based on three non‐coding RNAs for prediction of the overall survival of glioma patients
Recent studies have identified certain non‐coding RNAs (ncRNAs) as biomarkers of disease progression. Glioma is the most common primary intracranial cancer, with high mortality. Here, we developed a prognostic signature for prediction of overall survival (OS) of glioma patients by analyzing ncRNA ex...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6443874/ https://www.ncbi.nlm.nih.gov/pubmed/30984542 http://dx.doi.org/10.1002/2211-5463.12602 |
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author | Xian, Junmin Zhang, Quanzhong Guo, Xiwen Liang, Xiankun Liu, Xinhua Feng, Yugong |
author_facet | Xian, Junmin Zhang, Quanzhong Guo, Xiwen Liang, Xiankun Liu, Xinhua Feng, Yugong |
author_sort | Xian, Junmin |
collection | PubMed |
description | Recent studies have identified certain non‐coding RNAs (ncRNAs) as biomarkers of disease progression. Glioma is the most common primary intracranial cancer, with high mortality. Here, we developed a prognostic signature for prediction of overall survival (OS) of glioma patients by analyzing ncRNA expression profiles. We downloaded gene expression profiles of glioma patients along with their clinical information from the Gene Expression Omnibus and extracted ncRNA expression profiles via a microarray annotation file. Correlations between ncRNAs and glioma patients’ OS were first evaluated through univariate Cox regression analysis and a permutation test, followed by random survival forest analysis for further screening of valuable ncRNA signatures. Prognostic signatures could be established as a risk score formula by including ncRNA signature expression values weighted by their estimated regression coefficients. Patients could be divided into high risk and low risk subgroups by using the median risk score as cutoff. As a result, glioma patients with a high risk score tended to have shorter OS than those with low risk scores, which was confirmed by analyzing another set of glioma patients in an independent dataset. Additionally, gene set enrichment analysis showed significant enrichment of cancer development‐related biological processes and pathways. Our study may provide further insights into the evaluation of glioma patients’ prognosis. |
format | Online Article Text |
id | pubmed-6443874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-64438742019-04-12 A prognostic signature based on three non‐coding RNAs for prediction of the overall survival of glioma patients Xian, Junmin Zhang, Quanzhong Guo, Xiwen Liang, Xiankun Liu, Xinhua Feng, Yugong FEBS Open Bio Research Articles Recent studies have identified certain non‐coding RNAs (ncRNAs) as biomarkers of disease progression. Glioma is the most common primary intracranial cancer, with high mortality. Here, we developed a prognostic signature for prediction of overall survival (OS) of glioma patients by analyzing ncRNA expression profiles. We downloaded gene expression profiles of glioma patients along with their clinical information from the Gene Expression Omnibus and extracted ncRNA expression profiles via a microarray annotation file. Correlations between ncRNAs and glioma patients’ OS were first evaluated through univariate Cox regression analysis and a permutation test, followed by random survival forest analysis for further screening of valuable ncRNA signatures. Prognostic signatures could be established as a risk score formula by including ncRNA signature expression values weighted by their estimated regression coefficients. Patients could be divided into high risk and low risk subgroups by using the median risk score as cutoff. As a result, glioma patients with a high risk score tended to have shorter OS than those with low risk scores, which was confirmed by analyzing another set of glioma patients in an independent dataset. Additionally, gene set enrichment analysis showed significant enrichment of cancer development‐related biological processes and pathways. Our study may provide further insights into the evaluation of glioma patients’ prognosis. John Wiley and Sons Inc. 2019-03-07 /pmc/articles/PMC6443874/ /pubmed/30984542 http://dx.doi.org/10.1002/2211-5463.12602 Text en © 2019 The Authors. Published by FEBS Press and John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Articles Xian, Junmin Zhang, Quanzhong Guo, Xiwen Liang, Xiankun Liu, Xinhua Feng, Yugong A prognostic signature based on three non‐coding RNAs for prediction of the overall survival of glioma patients |
title | A prognostic signature based on three non‐coding RNAs for prediction of the overall survival of glioma patients |
title_full | A prognostic signature based on three non‐coding RNAs for prediction of the overall survival of glioma patients |
title_fullStr | A prognostic signature based on three non‐coding RNAs for prediction of the overall survival of glioma patients |
title_full_unstemmed | A prognostic signature based on three non‐coding RNAs for prediction of the overall survival of glioma patients |
title_short | A prognostic signature based on three non‐coding RNAs for prediction of the overall survival of glioma patients |
title_sort | prognostic signature based on three non‐coding rnas for prediction of the overall survival of glioma patients |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6443874/ https://www.ncbi.nlm.nih.gov/pubmed/30984542 http://dx.doi.org/10.1002/2211-5463.12602 |
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