Defining the cutoff value of MGMT gene promoter methylation and its predictive capacity in glioblastoma

Autor: Dino Amadori, Giovanni Brigliadori, Monia Dall'Agata, Flavia Foca, Elisabetta Melegari, Marina Faedi, Serenella Cerasoli, Claudia Rengucci, Daniele Calistri
Rok vydání: 2016
Předmět:
Zdroj: Journal of Neuro-Oncology. 128:333-339
ISSN: 1573-7373
0167-594X
Popis: Despite advances in the treatment of glioblastoma (GBM), median survival is 12-15 months. O6-methylguanine-DNA methyltransferase (MGMT) gene promoter methylation status is acknowledged as a predictive marker for temozolomide (TMZ) treatment. When MGMT promoter values fall into a "methylated" range, a better response to chemotherapy is expected. However, a cutoff that discriminates between "methylated" and "unmethylated" status has yet to be defined. We aimed to identify the best cutoff value and to find out whether variability in methylation profiles influences the predictive capacity of MGMT promoter methylation. Data from 105 GBM patients treated between 2008 and 2013 were analyzed. MGMT promoter methylation status was determined by analyzing 10 CpG islands by pyrosequencing. Patients were treated with radiotherapy followed by TMZ. MGMT promoter methylation status was classified into unmethylated 0-9 %, methylated 10-29 % and methylated 30-100 %. Statistical analysis showed that an assumed methylation cutoff of 9 % led to an overestimation of responders. All patients in the 10-29 % methylation group relapsed before the 18-month evaluation. Patients with a methylation status ≥30 % showed a median overall survival of 25.2 months compared to 15.2 months in all other patients, confirming this value as the best methylation cutoff. Despite wide variability among individual profiles, single CpG island analysis did not reveal any correlation between single CpG island methylation values and relapse or death. Specific CpG island methylation status did not influence the predictive value of MGMT. The predictive role of MGMT promoter methylation was maintained only with a cutoff value ≥30 %.
Databáze: OpenAIRE