Abstract 4031: MGMT methylation based outcome prediction is associated with two CpG regions separated by a prediction minimum centred at the initiation start site
Authors: Bady Pierre , Sciuscio Davide , Stupp Roger , Delorenzi Mauro , Hegi Monika E. ,   EORTC Brain Tumor Group.
Published: August 2012

Promoter methylation of the repair gene MGMT is a predictive factor for benefit from alkylating agent therapy in glioblastoma patients. High through-put platforms for genome wide DNA methylation analysis have allowed establishing the methylome of large series of patient samples that has identified a glioma CpG methylator phenotype (G-CIMP). However, classification of samples as being methylated or unmethylated for a given gene is not obvious, since the relationship between CpG-methylation at a given site and the extent of the overall CpG island methylation, and the effect on gene silencing is strongly dependent on the location. For the MGMT gene 176 CpGs are interrogated on the 450K chip of which 18 are located in the CpG island associated with the promoter region. Correlation of MGMT methylation at these 18 CpG sites in 63 glioblastoma and 5 non tumoral brain tissues and methylation prediction established previously by methylation specific PCR (MSP) indicated 2 regions with highest association. The two areas were separated by a prediction minimum centered at the initiation start site. The correlation of MGMT expression with the methylation status of CpGs followed the same pattern with the strongest negative correlation reaching –0.5 at the 2 peaks. Subsequently we tested the predictive value of the 18 CpGs for outcome in these patients treated within clinical trials with temozolomide containing chemo-radiotherapy. Most intriguingly, correlation with gene expression, survival analyses and association with MSP displayed almost superposable images of CpGs, at the previously identified CpG regions! A model for MGMT methylation classification based on stepwise logistic regression was constructed with a kappa value close to 0.85. The model was validated in a published external data set of homogeneously treated patient cohort with anaplastic glioma for which methylation data and survival information was available, and for which MGMT methylation was reported as prognostic factor. The model was subsequently applied to the methylation data available from the The Cancer Genome Atlas (TCGA) glioblastoma data-set comprising 241 samples. Classification of the samples for their MGMT methylation status based on the predictor revealed that MGMT is frequently methylated in glioblastoma with G-CIMP (simulated p=0.001 chi-square, Monte-Carlo method), but is not a G-CIMP gene. Taken together, the location of methylated CpGs within the promoter is crucial for prediction of MGMT silencing and subsequent impact on outcome. Hence, for efficient mining of large scale methylation data we need models to identify regions of CpGs with a high impact on gene silencing or other features relevant for the understanding of tumor biology and effect on response to therapy.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4031. doi:1538-7445.AM2012-4031