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Genome-Wide Methylation Analyses in Glioblastoma Multiforme
Few studies had investigated genome-wide methylation in glioblastoma multiforme (GBM). Our goals were to study differential methylation across the genome in gene promoters using an array-based method, as well as repetitive elements using surrogate global methylation markers. The discovery sample set...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3931727/ https://www.ncbi.nlm.nih.gov/pubmed/24586730 http://dx.doi.org/10.1371/journal.pone.0089376 |
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author | Lai, Rose K. Chen, Yanwen Guan, Xiaowei Nousome, Darryl Sharma, Charu Canoll, Peter Bruce, Jeffrey Sloan, Andrew E. Cortes, Etty Vonsattel, Jean-Paul Su, Tao Delgado-Cruzata, Lissette Gurvich, Irina Santella, Regina M. Ostrom, Quinn Lee, Annette Gregersen, Peter Barnholtz-Sloan, Jill |
author_facet | Lai, Rose K. Chen, Yanwen Guan, Xiaowei Nousome, Darryl Sharma, Charu Canoll, Peter Bruce, Jeffrey Sloan, Andrew E. Cortes, Etty Vonsattel, Jean-Paul Su, Tao Delgado-Cruzata, Lissette Gurvich, Irina Santella, Regina M. Ostrom, Quinn Lee, Annette Gregersen, Peter Barnholtz-Sloan, Jill |
author_sort | Lai, Rose K. |
collection | PubMed |
description | Few studies had investigated genome-wide methylation in glioblastoma multiforme (GBM). Our goals were to study differential methylation across the genome in gene promoters using an array-based method, as well as repetitive elements using surrogate global methylation markers. The discovery sample set for this study consisted of 54 GBM from Columbia University and Case Western Reserve University, and 24 brain controls from the New York Brain Bank. We assembled a validation dataset using methylation data of 162 TCGA GBM and 140 brain controls from dbGAP. HumanMethylation27 Analysis Bead-Chips (Illumina) were used to interrogate 26,486 informative CpG sites in both the discovery and validation datasets. Global methylation levels were assessed by analysis of L1 retrotransposon (LINE1), 5 methyl-deoxycytidine (5m-dC) and 5 hydroxylmethyl-deoxycytidine (5hm-dC) in the discovery dataset. We validated a total of 1548 CpG sites (1307 genes) that were differentially methylated in GBM compared to controls. There were more than twice as many hypomethylated genes as hypermethylated ones. Both the discovery and validation datasets found 5 tumor methylation classes. Pathway analyses showed that the top ten pathways in hypomethylated genes were all related to functions of innate and acquired immunities. Among hypermethylated pathways, transcriptional regulatory network in embryonic stem cells was the most significant. In the study of global methylation markers, 5m-dC level was the best discriminant among methylation classes, whereas in survival analyses, high level of LINE1 methylation was an independent, favorable prognostic factor in the discovery dataset. Based on a pathway approach, hypermethylation in genes that control stem cell differentiation were significant, poor prognostic factors of overall survival in both the discovery and validation datasets. Approaches that targeted these methylated genes may be a future therapeutic goal. |
format | Online Article Text |
id | pubmed-3931727 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39317272014-02-25 Genome-Wide Methylation Analyses in Glioblastoma Multiforme Lai, Rose K. Chen, Yanwen Guan, Xiaowei Nousome, Darryl Sharma, Charu Canoll, Peter Bruce, Jeffrey Sloan, Andrew E. Cortes, Etty Vonsattel, Jean-Paul Su, Tao Delgado-Cruzata, Lissette Gurvich, Irina Santella, Regina M. Ostrom, Quinn Lee, Annette Gregersen, Peter Barnholtz-Sloan, Jill PLoS One Research Article Few studies had investigated genome-wide methylation in glioblastoma multiforme (GBM). Our goals were to study differential methylation across the genome in gene promoters using an array-based method, as well as repetitive elements using surrogate global methylation markers. The discovery sample set for this study consisted of 54 GBM from Columbia University and Case Western Reserve University, and 24 brain controls from the New York Brain Bank. We assembled a validation dataset using methylation data of 162 TCGA GBM and 140 brain controls from dbGAP. HumanMethylation27 Analysis Bead-Chips (Illumina) were used to interrogate 26,486 informative CpG sites in both the discovery and validation datasets. Global methylation levels were assessed by analysis of L1 retrotransposon (LINE1), 5 methyl-deoxycytidine (5m-dC) and 5 hydroxylmethyl-deoxycytidine (5hm-dC) in the discovery dataset. We validated a total of 1548 CpG sites (1307 genes) that were differentially methylated in GBM compared to controls. There were more than twice as many hypomethylated genes as hypermethylated ones. Both the discovery and validation datasets found 5 tumor methylation classes. Pathway analyses showed that the top ten pathways in hypomethylated genes were all related to functions of innate and acquired immunities. Among hypermethylated pathways, transcriptional regulatory network in embryonic stem cells was the most significant. In the study of global methylation markers, 5m-dC level was the best discriminant among methylation classes, whereas in survival analyses, high level of LINE1 methylation was an independent, favorable prognostic factor in the discovery dataset. Based on a pathway approach, hypermethylation in genes that control stem cell differentiation were significant, poor prognostic factors of overall survival in both the discovery and validation datasets. Approaches that targeted these methylated genes may be a future therapeutic goal. Public Library of Science 2014-02-21 /pmc/articles/PMC3931727/ /pubmed/24586730 http://dx.doi.org/10.1371/journal.pone.0089376 Text en © 2014 Lai et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Lai, Rose K. Chen, Yanwen Guan, Xiaowei Nousome, Darryl Sharma, Charu Canoll, Peter Bruce, Jeffrey Sloan, Andrew E. Cortes, Etty Vonsattel, Jean-Paul Su, Tao Delgado-Cruzata, Lissette Gurvich, Irina Santella, Regina M. Ostrom, Quinn Lee, Annette Gregersen, Peter Barnholtz-Sloan, Jill Genome-Wide Methylation Analyses in Glioblastoma Multiforme |
title | Genome-Wide Methylation Analyses in Glioblastoma Multiforme |
title_full | Genome-Wide Methylation Analyses in Glioblastoma Multiforme |
title_fullStr | Genome-Wide Methylation Analyses in Glioblastoma Multiforme |
title_full_unstemmed | Genome-Wide Methylation Analyses in Glioblastoma Multiforme |
title_short | Genome-Wide Methylation Analyses in Glioblastoma Multiforme |
title_sort | genome-wide methylation analyses in glioblastoma multiforme |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3931727/ https://www.ncbi.nlm.nih.gov/pubmed/24586730 http://dx.doi.org/10.1371/journal.pone.0089376 |
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