Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas

Gliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expres...

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Main Authors: Zhen Chen, Zhe Zhang, Wei Ding, Jie-hui Zhang, Zi-long Tan, Yu-ran Mei, Wei He, Xiao-jing Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Neurology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2022.886246/full
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author Zhen Chen
Zhe Zhang
Wei Ding
Jie-hui Zhang
Zi-long Tan
Yu-ran Mei
Wei He
Xiao-jing Wang
Xiao-jing Wang
author_facet Zhen Chen
Zhe Zhang
Wei Ding
Jie-hui Zhang
Zi-long Tan
Yu-ran Mei
Wei He
Xiao-jing Wang
Xiao-jing Wang
author_sort Zhen Chen
collection DOAJ
description Gliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expression patterns and function of the m7G RNA methylation regulator in gliomas are yet unknown. The goal of this study was to examine the expression patterns of 31 critical regulators linked with m7G RNA methylation and their prognostic significance in gliomas. To begin, we systematically analyzed patient clinical and prognostic data and mRNA gene expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We found that 17 key regulators of m7G RNA methylation showed significantly higher expression levels in gliomas. We then divided the sample into two subgroups by consensus clustering. Cluster 2 had a poorer prognosis than cluster 1 and was associated with a higher histological grade. In addition, cluster 2 was significantly enriched for cancer-related pathways. Based on this discovery, we developed a risk model involving three m7G methylation regulators. Patients were divided into high-risk and low-risk groups based on risk scores. Overall survival (OS) was significantly lower in the high-risk group than in the low-risk group. Further analysis showed that the risk score was an independent prognostic factor for gliomas.
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spelling doaj.art-a9f9153929dc4e60baa927705f32a8202022-12-22T02:24:14ZengFrontiers Media S.A.Frontiers in Neurology1664-22952022-05-011310.3389/fneur.2022.886246886246Expression and Potential Biomarkers of Regulators for M7G RNA Modification in GliomasZhen Chen0Zhe Zhang1Wei Ding2Jie-hui Zhang3Zi-long Tan4Yu-ran Mei5Wei He6Xiao-jing Wang7Xiao-jing Wang8Department of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, ChinaDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, ChinaYifeng County People's Hospital, Yichun City, ChinaYifeng County People's Hospital, Yichun City, ChinaDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, ChinaDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, ChinaDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, ChinaDepartment of Neurosurgery, The Second Affiliated Hospital of Nanchang University, Nanchang, ChinaDepartment of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, ChinaGliomas are the most frequent primary malignant brain tumors of the central nervous system, causing significant impairment and death. There is mounting evidence that N7 methylguanosine (m7G) RNA dysmethylation plays a significant role in the development and progression of cancer. However, the expression patterns and function of the m7G RNA methylation regulator in gliomas are yet unknown. The goal of this study was to examine the expression patterns of 31 critical regulators linked with m7G RNA methylation and their prognostic significance in gliomas. To begin, we systematically analyzed patient clinical and prognostic data and mRNA gene expression data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. We found that 17 key regulators of m7G RNA methylation showed significantly higher expression levels in gliomas. We then divided the sample into two subgroups by consensus clustering. Cluster 2 had a poorer prognosis than cluster 1 and was associated with a higher histological grade. In addition, cluster 2 was significantly enriched for cancer-related pathways. Based on this discovery, we developed a risk model involving three m7G methylation regulators. Patients were divided into high-risk and low-risk groups based on risk scores. Overall survival (OS) was significantly lower in the high-risk group than in the low-risk group. Further analysis showed that the risk score was an independent prognostic factor for gliomas.https://www.frontiersin.org/articles/10.3389/fneur.2022.886246/fullN7-methylguanosinegliomasepigeneticsprognostic signaturebioinformatics
spellingShingle Zhen Chen
Zhe Zhang
Wei Ding
Jie-hui Zhang
Zi-long Tan
Yu-ran Mei
Wei He
Xiao-jing Wang
Xiao-jing Wang
Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas
Frontiers in Neurology
N7-methylguanosine
gliomas
epigenetics
prognostic signature
bioinformatics
title Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas
title_full Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas
title_fullStr Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas
title_full_unstemmed Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas
title_short Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas
title_sort expression and potential biomarkers of regulators for m7g rna modification in gliomas
topic N7-methylguanosine
gliomas
epigenetics
prognostic signature
bioinformatics
url https://www.frontiersin.org/articles/10.3389/fneur.2022.886246/full
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