MGMT Promoter Methylation Cutoff with Safety Margin for Selecting Glioblastoma Patients into Trials Omitting Temozolomide: A Pooled Analysis of Four Clinical Trials.
- Hegi ME Neurosurgery & Neuroscience Research Center, Lausanne University Hospital, Lausanne, Switzerland. monika.hegi@chuv.ch.
- Genbrugge E European Organisation for Treatment and Research of Cancer (EORTC) Data Centre, Brussels, Belgium.
- Gorlia T European Organisation for Treatment and Research of Cancer (EORTC) Data Centre, Brussels, Belgium.
- Stupp R Malnati Brain Tumor Institute of the Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
- Gilbert MR NCI, NIH, Bethesda, Maryland.
- Chinot OL Aix-Marseille University, AP-HM, Hôpital de la Timone, Marseille, France.
- Nabors LB University of Alabama at Birmingham, Birmingham, Alabama.
- Jones G MDxHealth, Irvine, California.
- Van Criekinge W Department of Mathematical Modeling, Statistics and Bio-Informatics, Ghent University, Ghent, Belgium.
- Straub J Merck KGaA, Darmstadt, Germany.
- Weller M Department of Neurology, University Hospital Zurich, Zurich, Switzerland.
- 2018-12-06
Published in:
- Clinical cancer research : an official journal of the American Association for Cancer Research. - 2019
Antineoplastic Agents, Alkylating
Brain Neoplasms
Clinical Trials as Topic
DNA Methylation
DNA Modification Methylases
DNA Repair Enzymes
Datasets as Topic
Drug Resistance, Neoplasm
Female
Glioblastoma
Humans
Male
Middle Aged
Patient Selection
Promoter Regions, Genetic
Reference Values
Temozolomide
Tumor Suppressor Proteins
English
PURPOSE
The methylation status of the O6-methylguanine DNA methyltransferase (MGMT) gene promoter is predictive for benefit from temozolomide in glioblastoma (GBM). A clinically optimized cutoff was sought allowing patient selection for therapy without temozolomide, while avoiding to withhold it from patients who may potentially benefit.Experimental Design: Quantitative MGMT methylation-specific PCR data were obtained for newly diagnosed patients with GBM screened or treated with standard radiotherapy and temozolomide in four randomized trials. The pooled dataset was randomly split into a training and test dataset. The unsupervised cutoff was obtained at a 50% probability to be (un)methylated. ROC analysis identified an optimal cutoff supervised by overall survival (OS).
RESULTS
For 4,041 patients valid MGMT results were obtained, whereof 1,725 were randomized. The unsupervised cutoff in the training dataset was 1.27 (log2[1,000 × (MGMT+1)/ACTB]), separating unmethylated and methylated patients. The optimal supervised cutoff for unmethylated patients was -0.28 (AUC = 0.61), classifying "truly unmethylated" (≤-0.28) and "gray zone" patients (>-0.28, ≤1.27), the latter comprising approximately 10% of cases. In contrast, for patients with MGMT methylation (>1.27) more methylation was not related to better outcome. Both methylated and gray zone patients performed significantly better for OS than truly unmethylated patients [HR = 0.35, 95% confidence interval (CI), 0.27-0.45, P < 0.0001; HR = 0.58, 95% CI, 0.43-0.78, P < 0.001], validated in the test dataset. The MGMT assay was highly reproducible upon retesting of 218 paired samples (R 2 = 0.94).
CONCLUSIONS
Low MGMT methylation (gray zone) may confer some sensitivity to temozolomide treatment, hence the lower safety margin should be considered for selecting patients with unmethylated GBM into trials omitting temozolomide.
The methylation status of the O6-methylguanine DNA methyltransferase (MGMT) gene promoter is predictive for benefit from temozolomide in glioblastoma (GBM). A clinically optimized cutoff was sought allowing patient selection for therapy without temozolomide, while avoiding to withhold it from patients who may potentially benefit.Experimental Design: Quantitative MGMT methylation-specific PCR data were obtained for newly diagnosed patients with GBM screened or treated with standard radiotherapy and temozolomide in four randomized trials. The pooled dataset was randomly split into a training and test dataset. The unsupervised cutoff was obtained at a 50% probability to be (un)methylated. ROC analysis identified an optimal cutoff supervised by overall survival (OS).
RESULTS
For 4,041 patients valid MGMT results were obtained, whereof 1,725 were randomized. The unsupervised cutoff in the training dataset was 1.27 (log2[1,000 × (MGMT+1)/ACTB]), separating unmethylated and methylated patients. The optimal supervised cutoff for unmethylated patients was -0.28 (AUC = 0.61), classifying "truly unmethylated" (≤-0.28) and "gray zone" patients (>-0.28, ≤1.27), the latter comprising approximately 10% of cases. In contrast, for patients with MGMT methylation (>1.27) more methylation was not related to better outcome. Both methylated and gray zone patients performed significantly better for OS than truly unmethylated patients [HR = 0.35, 95% confidence interval (CI), 0.27-0.45, P < 0.0001; HR = 0.58, 95% CI, 0.43-0.78, P < 0.001], validated in the test dataset. The MGMT assay was highly reproducible upon retesting of 218 paired samples (R 2 = 0.94).
CONCLUSIONS
Low MGMT methylation (gray zone) may confer some sensitivity to temozolomide treatment, hence the lower safety margin should be considered for selecting patients with unmethylated GBM into trials omitting temozolomide.
- Language
-
- English
- Open access status
- bronze
- Identifiers
-
- DOI 10.1158/1078-0432.CCR-18-3181
- PMID 30514777
- Persistent URL
- https://sonar.ch/global/documents/30259
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