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MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status
The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and ep...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3444709/ https://www.ncbi.nlm.nih.gov/pubmed/22810491 http://dx.doi.org/10.1007/s00401-012-1016-2 |
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author | Bady, Pierre Sciuscio, Davide Diserens, Annie-Claire Bloch, Jocelyne van den Bent, Martin J. Marosi, Christine Dietrich, Pierre-Yves Weller, Michael Mariani, Luigi Heppner, Frank L. Mcdonald, David R. Lacombe, Denis Stupp, Roger Delorenzi, Mauro Hegi, Monika E. |
author_facet | Bady, Pierre Sciuscio, Davide Diserens, Annie-Claire Bloch, Jocelyne van den Bent, Martin J. Marosi, Christine Dietrich, Pierre-Yves Weller, Michael Mariani, Luigi Heppner, Frank L. Mcdonald, David R. Lacombe, Denis Stupp, Roger Delorenzi, Mauro Hegi, Monika E. |
author_sort | Bady, Pierre |
collection | PubMed |
description | The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00401-012-1016-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-3444709 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-34447092012-09-25 MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status Bady, Pierre Sciuscio, Davide Diserens, Annie-Claire Bloch, Jocelyne van den Bent, Martin J. Marosi, Christine Dietrich, Pierre-Yves Weller, Michael Mariani, Luigi Heppner, Frank L. Mcdonald, David R. Lacombe, Denis Stupp, Roger Delorenzi, Mauro Hegi, Monika E. Acta Neuropathol Original Paper The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00401-012-1016-2) contains supplementary material, which is available to authorized users. Springer-Verlag 2012-07-19 2012 /pmc/articles/PMC3444709/ /pubmed/22810491 http://dx.doi.org/10.1007/s00401-012-1016-2 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Original Paper Bady, Pierre Sciuscio, Davide Diserens, Annie-Claire Bloch, Jocelyne van den Bent, Martin J. Marosi, Christine Dietrich, Pierre-Yves Weller, Michael Mariani, Luigi Heppner, Frank L. Mcdonald, David R. Lacombe, Denis Stupp, Roger Delorenzi, Mauro Hegi, Monika E. MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status |
title | MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status |
title_full | MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status |
title_fullStr | MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status |
title_full_unstemmed | MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status |
title_short | MGMT methylation analysis of glioblastoma on the Infinium methylation BeadChip identifies two distinct CpG regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and CIMP-status |
title_sort | mgmt methylation analysis of glioblastoma on the infinium methylation beadchip identifies two distinct cpg regions associated with gene silencing and outcome, yielding a prediction model for comparisons across datasets, tumor grades, and cimp-status |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3444709/ https://www.ncbi.nlm.nih.gov/pubmed/22810491 http://dx.doi.org/10.1007/s00401-012-1016-2 |
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