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

Pierre Bady, Davide Sciuscio, Annie Claire Diserens, Jocelyne Bloch, Martin J. Van Den Bent, Christine Marosi, Pierre Yves Dietrich, Michael Weller, Luigi Mariani, Frank L. Heppner, David R. Mcdonald, Denis Lacombe, Roger Stupp, Mauro Delorenzi, Monika E. Hegi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

171 Scopus citations

Abstract

The methylation status of the O6-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 CIMPnegative 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.

Original languageEnglish (US)
Pages (from-to)547-560
Number of pages14
JournalActa Neuropathologica
Volume124
Issue number4
DOIs
StatePublished - Oct 2012

Keywords

  • DNA methylation
  • Infinium methylation platform
  • MGMT
  • MSP
  • Prediction model

ASJC Scopus subject areas

  • Pathology and Forensic Medicine
  • Clinical Neurology
  • Cellular and Molecular Neuroscience

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