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DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival
DNA methylation is an epigenetic change to the genome that impacts gene activities without modification to the DNA sequence. Alteration in the methylation pattern is a naturally occurring event throughout the human life cycle which may result in the development of diseases such as cancer. In this st...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864199/ https://www.ncbi.nlm.nih.gov/pubmed/33498463 http://dx.doi.org/10.3390/ijms22031020 |
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author | Weng, Jing Yin Salazar, Nicole |
author_facet | Weng, Jing Yin Salazar, Nicole |
author_sort | Weng, Jing Yin |
collection | PubMed |
description | DNA methylation is an epigenetic change to the genome that impacts gene activities without modification to the DNA sequence. Alteration in the methylation pattern is a naturally occurring event throughout the human life cycle which may result in the development of diseases such as cancer. In this study, we analyzed methylation data from The Cancer Genome Atlas, under the Lower-Grade Glioma (LGG) and Glioblastoma Multiforme (GBM) projects, to identify methylation markers that exhibit unique changes in DNA methylation pattern along with tumor grade progression, to predict patient survival. We found ten glioma grade-associated Cytosine-phosphate-Guanine (CpG) sites that targeted four genes (SMOC1, KCNA4, SLC25A21, and UPP1) and the methylation pattern is strongly associated with glioma specific molecular alterations, primarily isocitrate dehydrogenase (IDH) mutation and chromosome 1p/19q codeletion. The ten CpG sites collectively distinguished a cohort of diffuse glioma patients with remarkably poor survival probability. Our study highlights genes (KCNA4 and SLC25A21) that were not previously associated with gliomas to have contributed to the poorer patient outcome. These CpG sites can aid glioma tumor progression monitoring and serve as prognostic markers to identify patients diagnosed with less aggressive and malignant gliomas that exhibit similar survival probability to GBM patients. |
format | Online Article Text |
id | pubmed-7864199 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-78641992021-02-06 DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival Weng, Jing Yin Salazar, Nicole Int J Mol Sci Article DNA methylation is an epigenetic change to the genome that impacts gene activities without modification to the DNA sequence. Alteration in the methylation pattern is a naturally occurring event throughout the human life cycle which may result in the development of diseases such as cancer. In this study, we analyzed methylation data from The Cancer Genome Atlas, under the Lower-Grade Glioma (LGG) and Glioblastoma Multiforme (GBM) projects, to identify methylation markers that exhibit unique changes in DNA methylation pattern along with tumor grade progression, to predict patient survival. We found ten glioma grade-associated Cytosine-phosphate-Guanine (CpG) sites that targeted four genes (SMOC1, KCNA4, SLC25A21, and UPP1) and the methylation pattern is strongly associated with glioma specific molecular alterations, primarily isocitrate dehydrogenase (IDH) mutation and chromosome 1p/19q codeletion. The ten CpG sites collectively distinguished a cohort of diffuse glioma patients with remarkably poor survival probability. Our study highlights genes (KCNA4 and SLC25A21) that were not previously associated with gliomas to have contributed to the poorer patient outcome. These CpG sites can aid glioma tumor progression monitoring and serve as prognostic markers to identify patients diagnosed with less aggressive and malignant gliomas that exhibit similar survival probability to GBM patients. MDPI 2021-01-20 /pmc/articles/PMC7864199/ /pubmed/33498463 http://dx.doi.org/10.3390/ijms22031020 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Weng, Jing Yin Salazar, Nicole DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival |
title | DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival |
title_full | DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival |
title_fullStr | DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival |
title_full_unstemmed | DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival |
title_short | DNA Methylation Analysis Identifies Patterns in Progressive Glioma Grades to Predict Patient Survival |
title_sort | dna methylation analysis identifies patterns in progressive glioma grades to predict patient survival |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7864199/ https://www.ncbi.nlm.nih.gov/pubmed/33498463 http://dx.doi.org/10.3390/ijms22031020 |
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