Dataset Information

Assessment of Quantitative and Allelic MGMT Methylation Patterns as a Prognostic Marker in Glioblastoma.

ABSTRACT: Methylation of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is a predictive and prognostic marker in newly diagnosed glioblastoma patients treated with temozolomide but how MGMT methylation should be assessed to ensure optimal detection accuracy is debated. We developed a novel quantitative methylation-specific PCR (qMSP) MGMT assay capable of providing allelic methylation data and analyzed 151 glioblastomas from patients receiving standard of care treatment (Stupp protocol). The samples were also analyzed by immunohistochemistry (IHC), standard bisulfite pyrosequencing, and genotyped for the rs1690252 MGMT promoter single nucleotide polymorphism. Monoallelic methylation was observed more frequently than biallelic methylation, and some cases with monoallelic methylation expressed the MGMT protein whereas others did not. The presence of MGMT methylation was associated with better overall survival (p = 0.006; qMSP and p = 0.002; standard pyrosequencing), and the presence of the protein was associated with worse overall survival (p = 0.009). Combined analyses of qMSP and standard pyrosequencing or IHC identified additional patients who benefited from temozolomide treatment. Finally, low methylation levels were also associated with better overall survival (p = 0.061; qMSP and p = 0.02; standard pyrosequencing). These data support the use of both MGMT methylation and MGMT IHC but not allelic methylation data as prognostic markers in patients with temozolomide-treated glioblastoma.

SUBMITTER: Kristensen LS

PROVIDER: S-EPMC4777218 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Assessment of Quantitative and Allelic MGMT Methylation Patterns as a Prognostic Marker in Glioblastoma.

Kristensen Lasse S LS Michaelsen Signe R SR Dyrbye Henrik H Aslan Derya D Grunnet Kirsten K Christensen Ib J IJ Poulsen Hans S HS Grønbæk Kirsten K Broholm Helle H

Journal of neuropathology and experimental neurology 20160216 3

Methylation of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is a predictive and prognostic marker in newly diagnosed glioblastoma patients treated with temozolomide but how MGMT methylation should be assessed to ensure optimal detection accuracy is debated. We developed a novel quantitative methylation-specific PCR (qMSP) MGMT assay capable of providing allelic methylation data and analyzed 151 glioblastomas from patients receiving standard of care treatment (Stupp protocol). The sam ...[more]

PMID: 26883115

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Project description:BACKGROUND: O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation is reported to be a prognostic and predictive factor of alkylating chemotherapy for glioblastoma patients. Methylation specific PCR (MSP) has been most commonly used when the methylation status of MGMT is assessed. However, technical obstacles have hampered the implementation of MSP-based diagnostic tests. We quantitatively analyzed the methylation status of the entire MGMT promoter region and applied this information for prognostic prediction using sequencing technology. METHODS: Between 1998 and 2012, the genomic DNA of 85 tumor samples from newly diagnosed glioblastoma patients was subjected to bisulfite treatment and subdivided into a training set, consisting of fifty-three samples, and a test set, consisting of thirty-two samples. The training set was analyzed by deep Sanger sequencing with a sequencing coverage of up to 96 clones per sample. This analysis quantitatively revealed the degree of methylation of each cytidine phosphate guanosine (CpG) site. Based on these data, we constructed a prognostic prediction system for glioblastoma patients using a supervised learning method. We then validated this prediction system by deep sequencing with a next-generation sequencer using a test set of 32 samples. RESULTS: The methylation status of the MGMT promoter was correlated with progression-free survival (PFS) in our patient population in the training set. The degree of correlation differed among the CpG sites. Using the data from the top twenty CpG sites, we constructed a prediction system for overall survival (OS) and PFS. The system successfully classified patients into good and poor prognosis groups in both the training set (OS, p?=?0.0381; PFS, p?=?0.00122) and the test set (OS, p?=?0.0476; PFS, p?=?0.0376). Conventional MSP could not predict the prognosis in either of our sets. (training set: OS; p?=?0.993 PFS; p?=?0.113, test set: OS; p?=?0.326 PFS; p?=?0.342). CONCLUSIONS: The prognostic ability of our prediction system using sequencing data was better than that of methylation-specific PCR (MSP). Advances in sequencing technologies will make this approach a plausible option for diagnoses based on MGMT promotor methylation.

Dataset Information

Assessment of Quantitative and Allelic MGMT Methylation Patterns as a Prognostic Marker in Glioblastoma.

Publications

Assessment of Quantitative and Allelic MGMT Methylation Patterns as a Prognostic Marker in Glioblastoma.

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