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Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma

Background: Glioma is the most common primary intracranial tumor, accounting for the vast majority of intracranial malignant tumors. Aberrant expression of RNA:5-methylcytosine(m(5)C) methyltransferases have recently been the focus of research relating to the occurrence and progression of tumors. Ho...

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Autores principales: Wang, Peng, Wu, Miaojing, Tu, Zewei, Tao, Chuming, Hu, Qing, Li, Kuangxun, Zhu, Xingen, Huang, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7466433/
https://www.ncbi.nlm.nih.gov/pubmed/32974125
http://dx.doi.org/10.3389/fonc.2020.01119
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author Wang, Peng
Wu, Miaojing
Tu, Zewei
Tao, Chuming
Hu, Qing
Li, Kuangxun
Zhu, Xingen
Huang, Kai
author_facet Wang, Peng
Wu, Miaojing
Tu, Zewei
Tao, Chuming
Hu, Qing
Li, Kuangxun
Zhu, Xingen
Huang, Kai
author_sort Wang, Peng
collection PubMed
description Background: Glioma is the most common primary intracranial tumor, accounting for the vast majority of intracranial malignant tumors. Aberrant expression of RNA:5-methylcytosine(m(5)C) methyltransferases have recently been the focus of research relating to the occurrence and progression of tumors. However, the prognostic value of RNA:m(5)C methyltransferases in glioma remains unclear. This study investigated RNA: m(5)C methyltransferase expression and defined its clinicopathological signature and prognostic value in gliomas. Methods: We obtained the RNA-sequence and Clinicopathological data of RNA:m(5)C methyltransferases underlying gliomas from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets. We analyzed the expression of RNA:m(5)C methyltransferase genes in gliomas with different clinicopathological characteristics and identified different subtypes using Consensus clustering analysis. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) was used to annotate the function of these genes. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm analyses were performed to construct the risk signature. Kaplan-Meier method and Receiver operating characteristic (ROC) curves were used to assess the overall survival of glioma patients. Additionally, Cox proportional regression model analysis was developed to address the connections between the risk scores and clinical factors. Results: We revealed the differential expression of RNA:m(5)C methyltransferase genes in gliomas with different clinicopathological features. Consensus clustering of RNA:m(5)C methyltransferases identified three clusters of gliomas with different prognostic and clinicopathological features. Meanwhile, functional annotations demonstrated that RNA:m(5)C methyltransferases were significantly associated with the malignant progression of gliomas. Thereafter, five RNA:m(5)C methyltransferase genes were screened to construct a risk signature that can be used to predict not only overall survival but also clinicopathological features in gliomas. ROC curves revealed the significant prognostic ability of this signature. In addition, Multivariate Cox regression analyses indicated that the risk score was an independent prognostic factor for glioma outcome. Conclusion: We demonstrated the prognostic role of RNA:m(5)C methyltransferases in the initiation and progression of glioma. We have expanded on the understanding of the molecular mechanism involved, and provided a unique approach to predictive biomarkers and targeted therapy for gliomas.
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spelling pubmed-74664332020-09-23 Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma Wang, Peng Wu, Miaojing Tu, Zewei Tao, Chuming Hu, Qing Li, Kuangxun Zhu, Xingen Huang, Kai Front Oncol Oncology Background: Glioma is the most common primary intracranial tumor, accounting for the vast majority of intracranial malignant tumors. Aberrant expression of RNA:5-methylcytosine(m(5)C) methyltransferases have recently been the focus of research relating to the occurrence and progression of tumors. However, the prognostic value of RNA:m(5)C methyltransferases in glioma remains unclear. This study investigated RNA: m(5)C methyltransferase expression and defined its clinicopathological signature and prognostic value in gliomas. Methods: We obtained the RNA-sequence and Clinicopathological data of RNA:m(5)C methyltransferases underlying gliomas from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets. We analyzed the expression of RNA:m(5)C methyltransferase genes in gliomas with different clinicopathological characteristics and identified different subtypes using Consensus clustering analysis. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) was used to annotate the function of these genes. Univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm analyses were performed to construct the risk signature. Kaplan-Meier method and Receiver operating characteristic (ROC) curves were used to assess the overall survival of glioma patients. Additionally, Cox proportional regression model analysis was developed to address the connections between the risk scores and clinical factors. Results: We revealed the differential expression of RNA:m(5)C methyltransferase genes in gliomas with different clinicopathological features. Consensus clustering of RNA:m(5)C methyltransferases identified three clusters of gliomas with different prognostic and clinicopathological features. Meanwhile, functional annotations demonstrated that RNA:m(5)C methyltransferases were significantly associated with the malignant progression of gliomas. Thereafter, five RNA:m(5)C methyltransferase genes were screened to construct a risk signature that can be used to predict not only overall survival but also clinicopathological features in gliomas. ROC curves revealed the significant prognostic ability of this signature. In addition, Multivariate Cox regression analyses indicated that the risk score was an independent prognostic factor for glioma outcome. Conclusion: We demonstrated the prognostic role of RNA:m(5)C methyltransferases in the initiation and progression of glioma. We have expanded on the understanding of the molecular mechanism involved, and provided a unique approach to predictive biomarkers and targeted therapy for gliomas. Frontiers Media S.A. 2020-08-19 /pmc/articles/PMC7466433/ /pubmed/32974125 http://dx.doi.org/10.3389/fonc.2020.01119 Text en Copyright © 2020 Wang, Wu, Tu, Tao, Hu, Li, 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 Oncology
Wang, Peng
Wu, Miaojing
Tu, Zewei
Tao, Chuming
Hu, Qing
Li, Kuangxun
Zhu, Xingen
Huang, Kai
Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma
title Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma
title_full Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma
title_fullStr Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma
title_full_unstemmed Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma
title_short Identification of RNA: 5-Methylcytosine Methyltransferases-Related Signature for Predicting Prognosis in Glioma
title_sort identification of rna: 5-methylcytosine methyltransferases-related signature for predicting prognosis in glioma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7466433/
https://www.ncbi.nlm.nih.gov/pubmed/32974125
http://dx.doi.org/10.3389/fonc.2020.01119
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