Optimal qMSP cutoff value for MGMT promoter methylation in glioblastoma and its validation for clinical significance


Huseyinoglu Z., Uysal E., İnan M. A., Demirci T., Gokay G., Aras F. K., ...Daha Fazla

BMC CANCER, cilt.25, sa.1, ss.1-9, 2025 (SCI-Expanded, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Sayı: 1
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1186/s12885-025-15225-2
  • Dergi Adı: BMC CANCER
  • Derginin Tarandığı İndeksler: Scopus, Science Citation Index Expanded (SCI-EXPANDED), CINAHL, EMBASE, MEDLINE, Directory of Open Access Journals
  • Sayfa Sayıları: ss.1-9
  • Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Evet

Özet

Background

Glioblastoma (GBM) is the most common and aggressive primary brain tumor, with limited survival despite multimodal treatment strategies. O6-Methylguanine-DNA Methyltransferase (MGMT) promoter methylation is a well-established predictive biomarker for response to temozolomide (TMZ) therapy. However, determining an optimal quantitative methylation-specific PCR (qMSP) cut-off value remains a challenge in clinical practice.

Objective

This study aimed to establish an optimal qMSP cut-off value for MGMT promoter methylation and validate its prognostic significance in GBM patients. The impact of MGMT methylation status on survival outcomes was analyzed concerning surgical extent, tumor localization, and white matter tract involvement.

Methods

A retrospective analysis of 101 GBM patients (IDH-wildtype) diagnosed between 2008 and 2022 was performed. All patients underwent surgical resection (total/partial excision or stereotactic biopsy) followed by standard chemoradiotherapy. MGMT promoter methylation status was assessed using real-time qMSP. The optimal cut-off value was determined via receiver operating characteristic curve analysis. Kaplan-Meier survival analysis and Cox regression models evaluated the association between MGMT methylation levels, clinical characteristics, and overall survival (OS).

Results

Among 101 patients with IDH-wildtype glioblastoma, a qMSP cut-off value of 0.242% demonstrated strong diagnostic performance for MGMT methylation status (AUC = 0.875), with 78% sensitivity and 86% specificity. Patients with high methylation levels (≥ 0.242%) showed significantly longer median overall survival compared to those with low methylation (24 vs. 12 months; p = 0.006). This prognostic relevance persisted across surgical and anatomical subgroups. Multivariable Cox regression identified high qMSP methylation (HR ≈ 0.45, p < 0.001) and extent of resection ≥ 90% (HR ≈ 0.30, p = 0.002) as independent predictors of improved survival, whereas TERT promoter mutation (HR ≈ 1.9, p = 0.017) was associated with worse survival. Stratified analysis revealed that TERTp-mutant tumors with low methylation had the worst outcomes. Additionally, excisional surgery and neocortical tumor involvement were associated with significantly better survival (p = 0.0010 and p = 0.0218, respectively). These findings validate within our institutional setting the clinical utility of the 0.242% qMSP threshold for prognostic stratification in glioblastoma, although external multicenter validation is warranted before generalization to routine clinical practice.

Conclusion

The identified qMSP cut-off value (0.242) based on the procedure described in this study provides a robust prognostic stratification tool for GBM patients. High MGMT methylation correlates with improved survival, supporting its integration into clinical decision-making. Further multi-center validation studies are warranted to establish standardized MGMT assessment methodologies.