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The optimal treatment for patients with low-grade glioma (LGG) WHO grade II remains controversial. Overall survival ranges from 2 to over 15 years depending on molecular and clinical factors. Hence, risk-adjusted treatments are required for optimizing outcome and quality of life. We aim at identifying mechanisms and associated molecular markers predictive for benefit from radiotherapy (RT) or temozolomide (TMZ) in LGG patients treated in the randomized phase III trial EORTC 22033. As candidate biomarkers for these genotoxic treatments, we considered the DNA methylome of 410 DNA damage response (DDR) genes. We first identified 62 functionally relevant CpG sites located in the promoters of 24 DDR genes, using the LGG data from The Cancer Genome Atlas. Then we tested their association with outcome [progression-free survival (PFS)] depending on treatment in 120 LGG patients of EORTC 22033, whose tumors were mutant for isocitrate dehydrogenase 1 or 2 (IDHmt), the molecular hallmark of LGG. The results suggested that seven CpGs of four DDR genes may be predictive for longer PFS in one of the treatment arms that comprised MGMT, MLH3, RAD21, and SMC4. Most interestingly, the two CpGs identified for MGMT are the same, previously selected for the MGMT-STP27 score that is used to determine the methylation status of the MGMT gene. This score was higher in the LGG with 1p/19q codeletion, in this and other independent LGG datasets. It was predictive for PFS in the TMZ, but not in the RT arm of EORTC 22033. The results support the hypothesis that a high score predicts benefit from TMZ treatment for patients with IDHmt LGG, regardless of the 1p/19q status. This MGMT methylation score may identify patients who benefit from first-line treatment with TMZ, to defer RT for long-term preservation of cognitive function and quality of life.

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 (R2 = 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.

Purpose: EORTC 26082 assessed the activity of temsirolimus in patients with newly diagnosed glioblastoma harboring an unmethylated O6 methylguanine-DNA-methyltransferase (MGMT) promoter. Experimental Design: Patients (n = 257) fulfilling eligibility criteria underwent central MGMT testing. Patients with MGMT unmethylated glioblastoma (n = 111) were randomized 1:1 between standard chemo-radiotherapy with temozolomide or radiotherapy plus weekly temsirolimus (25 mg). Primary endpoint was overall survival at 12 months (OS12). A positive signal was considered >38 patients alive at 12 months in the per protocol population. A noncomparative reference arm of 54 patients evaluated the assumptions on OS12 in a standard-treated cohort of patients. Prespecified post hoc analyses of markers reflecting target activation were performed. Results: Both therapies were administered per protocol with a median of 13 cycles of maintenance temsirolimus. Median age was 55 and 58 years in the temsirolimus and standard arms, the WHO performance status 0 or 1 for most patients (95.5%). In the per protocol population, 38 of 54 patients treated with temsirolimus reached OS12. The actuarial 1-year survival was 72.2% [95% confidence interval (CI), 58.2–82.2] in the temozolomide arm and 69.6% (95% CI, 55.8–79.9) in the temsirolimus arm [hazard ratio (HR) 1.16; 95% CI, 0.77–1.76; P = 0.47]. In multivariable prognostic analyses of clinical and molecular factors, phosphorylation of mTORSer2448 in tumor tissue (HR 0.13; 95% CI, 0.04–0.47; P = 0.002), detected in 37.6%, was associated with benefit from temsirolimus. Conclusions: Temsirolimus was not superior to temozolomide in patients with an unmethylated MGMT promoter. Phosphorylation of mTORSer2448 in the pretreatment tumor tissue may define a subgroup benefitting from mTOR inhibition. Clin Cancer Res; 22(19); 4797–806. ©2016 AACR.

International audience; This study assessed the prognostic value of several markers involved in gliomagenesis, and compared it with that of other clinical and imaging markers already used. Four-hundred and sixteen adult patients with newly diagnosed glioma were included over a 3-year period and tumour suppressor genes, oncogenes, MGMT and hTERT expressions, losses of heterozygosity, as well as relevant clinical and imaging information were recorded. This prospective study was based on all adult gliomas. Analyses were performed on patient groups selected according to World Health Organization histoprognostic criteria and on the entire cohort. The endpoint was overall survival, estimated by the Kaplan-Meier method. Univariate analysis was followed by multivariate analysis according to a Cox model. p14(ARF), p16(INK4A) and PTEN expressions, and 10p 10q23, 10q26 and 13q LOH for the entire cohort, hTERT expression for high-grade tumours, EGFR for glioblastomas, 10q26 LOH for grade III tumours and anaplastic oligodendrogliomas were found to be correlated with overall survival on univariate analysis and age and grade on multivariate analysis only. This study confirms the prognostic value of several markers. However, the scattering of the values explained by tumour heterogeneity prevents their use in individual decision-making.

[EN] Objectives To assess the combined role of tumor vascularity, estimated from perfusion MRI, andMGMTmethylation status on overall survival (OS) in patients with glioblastoma. Methods A multicentric international dataset including 96 patients from NCT03439332 clinical study were used to study the prognostic relationships betweenMGMTand perfusion markers. Relative cerebral blood volume (rCBV) in the most vascularized tumor regions was automatically obtained from preoperative MRIs using ONCOhabitats online analysis service. Cox survival regression models and stratification strategies were conducted to define a subpopulation that is particularly favored byMGMTmethylation in terms of OS. Results rCBV distributions did not differ significantly (p > 0.05) in the methylated and the non-methylated subpopulations. In patients with moderately vascularized tumors (rCBV < 10.73),MGMTmethylation was a positive predictive factor for OS (HR = 2.73,p = 0.003, AUC = 0.70). In patients with highly vascularized tumors (rCBV > 10.73), however, there was no significant effect ofMGMTmethylation (HR = 1.72,p = 0.10, AUC = 0.56). Conclusions Our results indicate the existence of complementary prognostic information provided byMGMTmethylation and rCBV. Perfusion markers could identify a subpopulation of patients who will benefit the most fromMGMTmethylation. Not considering this information may lead to bias in the interpretation of clinical studies., Open Access funding provided by University of Oslo (incl Oslo University Hospital). This study has received funding from MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R) (JMGG); H2020-SC12016-CNECT Project (No. 727560) (JMGG), H2020-SC1-BHC-20182020 (No. 825750) (JMGG), the European Research Council (ERC) under the European Union's Horizon 2020 (Grant Agreement No. 758657), the South-Eastern Norway Regional Health Authority Grants 2017073 and 2013069, the Research Council of Norway Grants 261984 (KEE). M.A.T was supported by Programa Estatal de Promocion del Talento y su Empleabilidad en I+D+i (DPI2016-80054-R). E.F.G was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement (No. 844646).

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p