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A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients
RNA binding proteins (RBPs) have been reported to be involved in cancer malignancy but related functions in glioma have been less studied. Herein, we screened 14 prognostic RBP genes and constructed a risk signature to predict the prognosis of glioma patients. Univariate Cox regression was used to i...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901892/ https://www.ncbi.nlm.nih.gov/pubmed/33634092 http://dx.doi.org/10.3389/fcell.2020.588368 |
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author | Tu, Zewei Shu, Lei Li, Jingying Wu, Lei Tao, Chuming Ye, Minhua Zhu, Xingen Huang, Kai |
author_facet | Tu, Zewei Shu, Lei Li, Jingying Wu, Lei Tao, Chuming Ye, Minhua Zhu, Xingen Huang, Kai |
author_sort | Tu, Zewei |
collection | PubMed |
description | RNA binding proteins (RBPs) have been reported to be involved in cancer malignancy but related functions in glioma have been less studied. Herein, we screened 14 prognostic RBP genes and constructed a risk signature to predict the prognosis of glioma patients. Univariate Cox regression was used to identify overall survival (OS)-related RBP genes. Prognostic RBP genes were screened and used to establish the RBP-signature using the least absolute shrinkage and selection operator (Lasso) method in The Cancer Genome Atlas (TCGA) cohort. The 14 RBP genes signature showed robust and stable prognostic value in the TCGA training (n = 562) cohort and in three independent validation cohorts (Chinese Glioma Genome Atlas [CGGA]seq1, CGGAseq2, and GSE16011 datasets comprising 303, 619, and 250 glioma patients, respectively). Risk scores were calculated for each patient and high-risk gliomas were defined by the median risk score in each cohort. Survival analysis in subgroups of glioma patients showed that the RBP-signature retained its prognostic value in low-grade gliomas (LGGs) and glioblastomas (GBM)s. Univariate and multivariate Cox regression analysis in each dataset and the meta cohort revealed that the RBP-signature stratification could efficiently recognize high-risk gliomas [Hazard Ratio (HR):3.662, 95% confidence interval (CI): 3.187–4.208, p < 0.001] and was an independent prognostic factor for OS (HR:1.594, 95% CI: 1.244–2.043, p < 0.001). Biological process and KEGG pathway analysis revealed the RBP gene signature was associated with immune cell activation, the p53 signaling pathway, and the PI3K-Akt signaling pathway and so on. Moreover, a nomogram model was constructed for clinical application of the RBP-signature, which showed stable predictive ability. In summary, the RBP-signature could be a robust indicator for prognostic evaluation and identifying high-risk glioma patients. |
format | Online Article Text |
id | pubmed-7901892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79018922021-02-24 A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients Tu, Zewei Shu, Lei Li, Jingying Wu, Lei Tao, Chuming Ye, Minhua Zhu, Xingen Huang, Kai Front Cell Dev Biol Cell and Developmental Biology RNA binding proteins (RBPs) have been reported to be involved in cancer malignancy but related functions in glioma have been less studied. Herein, we screened 14 prognostic RBP genes and constructed a risk signature to predict the prognosis of glioma patients. Univariate Cox regression was used to identify overall survival (OS)-related RBP genes. Prognostic RBP genes were screened and used to establish the RBP-signature using the least absolute shrinkage and selection operator (Lasso) method in The Cancer Genome Atlas (TCGA) cohort. The 14 RBP genes signature showed robust and stable prognostic value in the TCGA training (n = 562) cohort and in three independent validation cohorts (Chinese Glioma Genome Atlas [CGGA]seq1, CGGAseq2, and GSE16011 datasets comprising 303, 619, and 250 glioma patients, respectively). Risk scores were calculated for each patient and high-risk gliomas were defined by the median risk score in each cohort. Survival analysis in subgroups of glioma patients showed that the RBP-signature retained its prognostic value in low-grade gliomas (LGGs) and glioblastomas (GBM)s. Univariate and multivariate Cox regression analysis in each dataset and the meta cohort revealed that the RBP-signature stratification could efficiently recognize high-risk gliomas [Hazard Ratio (HR):3.662, 95% confidence interval (CI): 3.187–4.208, p < 0.001] and was an independent prognostic factor for OS (HR:1.594, 95% CI: 1.244–2.043, p < 0.001). Biological process and KEGG pathway analysis revealed the RBP gene signature was associated with immune cell activation, the p53 signaling pathway, and the PI3K-Akt signaling pathway and so on. Moreover, a nomogram model was constructed for clinical application of the RBP-signature, which showed stable predictive ability. In summary, the RBP-signature could be a robust indicator for prognostic evaluation and identifying high-risk glioma patients. Frontiers Media S.A. 2021-01-28 /pmc/articles/PMC7901892/ /pubmed/33634092 http://dx.doi.org/10.3389/fcell.2020.588368 Text en Copyright © 2021 Tu, Shu, Li, Wu, Tao, Ye, Zhu and Huang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cell and Developmental Biology Tu, Zewei Shu, Lei Li, Jingying Wu, Lei Tao, Chuming Ye, Minhua Zhu, Xingen Huang, Kai A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients |
title | A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients |
title_full | A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients |
title_fullStr | A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients |
title_full_unstemmed | A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients |
title_short | A Novel Signature Constructed by RNA-Binding Protein Coding Genes to Improve Overall Survival Prediction of Glioma Patients |
title_sort | novel signature constructed by rna-binding protein coding genes to improve overall survival prediction of glioma patients |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901892/ https://www.ncbi.nlm.nih.gov/pubmed/33634092 http://dx.doi.org/10.3389/fcell.2020.588368 |
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