Methylation Status Of The O6-methylguanine-DNA Methyltransferase Research Articles

Accurate and comprehensive evaluation of O6-methylguanine-DNA methyltransferase promoter methylation by nanopore sequencing.

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter region is essential in evaluating the prognosis and predicting the drug response in patients with glioblastoma. In this study, we evaluated the utility of using nanopore long-read sequencing as a method for assessing methylation levels throughout the MGMT CpG-island, compared its performance to established techniques and demonstrated its clinical applicability. We analysed 165 samples from CNS tumours, focusing on the MGMT CpG-island using nanopore sequencing. Oxford Nanopore Technologies (ONT) MinION and PromethION flow cells were employed for single sample or barcoded assays, guided by a CRISPR/Cas9 protocol, adaptive sampling or as part of a whole genome sequencing assay. Methylation data obtained through nanopore sequencing were compared to results obtained via pyrosequencing and methylation bead arrays. Hierarchical clustering was applied to nanopore sequencing data for patient stratification. Nanopore sequencing displayed a strong correlation (R2 = 0.91) with pyrosequencing results for the four CpGs of MGMT analysed by both methods. The MGMT-STP27 algorithm's classification was effectively reproduced using nanopore data. Unsupervised hierarchical clustering revealed distinct patterns in methylated and unmethylated samples, providing comparable survival prediction capabilities. Nanopore sequencing yielded high-confidence results in a rapid timeframe, typically within hours of sequencing, and extended the analysis to all 98 CpGs of the MGMT CpG-island. This study presents nanopore sequencing as a valid and efficient method for determining MGMT promotor methylation status. It offers a comprehensive view of the MGMT promoter methylation landscape, which enables the identification of potentially clinically relevant subgroups of patients. Further exploration of the clinical implications of patient stratification using nanopore sequencing of MGMT is warranted.

Epigenetic modification and characterization of the MGMT promoter region using CRISPRoff in glioblastoma cells.

The methylation status of the O6-methylguanine DNA methyltransferase (MGMT) promoter region is a critical predictor of response to alkylating agents in glioblastoma. However, current approaches to study the MGMT status focus on analyzing models with non-identical backgrounds. Here, we present an epigenetic editing approach using CRISPRoff to introduce site-specific CpG methylation in the MGMT promoter region of glioma cell lines. Sanger sequencing revealed successful introduction of methylation, effectively generating differently methylated glioma cell lines with an isogenic background. The introduced methylation resulted in reduced MGMT mRNA and protein levels. Furthermore, the cell lines with MGMT promoter region methylation exhibited increased sensitivity to temozolomide, consistent with the impact of methylation on treatment outcomes in patients with glioblastoma. This precise epigenome-editing approach provides valuable insights into the functional relevance of MGMT promoter regional methylation and its potential for prognostic and predictive assessments, as well as epigenetic-targeted therapies.

The power of integrating multiple data sources in medical imaging: A study of MGMT methylation status

The integration of multiple data sources is becoming increasingly important in the field of medical imaging for the purpose of improving predictions. In this study, we investigated the use of a unique combination of imaging and genomic data to predict the methylation status of the O6-methylguanine-DNA methyltransferase (MGMT). Utilizing a stacking generalization approach, our model achieved promising results. The classification report from the stacking ensemble shows a precision of 0.82, recall of 0.81, and an F1-score of 0.80. These findings demonstrate the potential of integrating diverse data sources in medical imaging to enhance predictive capabilities, specifically in the context of MGMT methylation status. Our study highlights the importance of ongoing research to refine and optimize the integration of multiple data sources, ultimately leading to more accurate predictions and tailored treatment strategies. This research has the potential to significantly impact patient outcomes by facilitating personalized interventions based on precise predictions of MGMT methylation status.

Downregulation of MGMT expression by targeted editing of DNA methylation enhances temozolomide sensitivity in glioblastoma

Glioblastoma is the most common and aggressive primary tumor of the central nervous system with poor outcome. Current gold standard treatment is surgical resection followed by a combination of radio- and chemotherapy. Efficacy of temozolomide (TMZ), the primary chemotherapeutic agent, depends on the DNA methylation status of the O6-methylguanine DNA methyltransferase (MGMT), which has been identified as a prognostic biomarker in glioblastoma patients. Clinical studies revealed that glioblastoma patients with hypermethylated MGMT promoter have a better response to TMZ treatment and a significantly improved overall survival. In this study, we thus used the CRISPRoff genome editing tool to mediate targeted DNA methylation within the MGMT promoter region. The system carrying a CRISPR-deactivated Cas9 (dCas9) fused with a methyltransferase (Dnmt3A/3L) domain downregulated MGMT expression in TMZ-resistant human glioblastoma cell lines through targeted DNA methylation. The reduction of MGMT expression levels reversed TMZ resistance in TMZ-resistant glioblastoma cell lines resulting in TMZ induced dose-dependent cell death rates. In conclusion, we demonstrate targeted RNA-guided methylation of the MGMT promoter as a promising tool to overcome chemoresistance and improve the cytotoxic effect of TMZ in glioblastoma.

DISTRIBUTION AND IMAGING CHARACTERISTICS OF HIGH-GRADE GLIOMAS ACCORDING TO METHYLATION STATUS OF MGMT GENE PROMOTER

Background: Many molecular investigations have identified that the methylation status of the O-6-methylguanine-DNA methyl transferase (MGMT) gene promoter in patients with high grade glioma is associated with a improved prognosis and survival when treated with temozolamide (TMZ). Aims and Objective: The aim of the study was to find out the distribution of methylation status and imaging characteristics in patients with High Grade Gliomas. Method: The study included forty consecutive patients who presented with neurological symptoms and were subsequently diagnosed as having a primary brain tumour on conventional MRI scan. MR-perfusion imaging was performed to determine the grade of the tumor which was subsequently compared with histopathological grade of the tumor after brain biopsy. The biopsy or surgical specimens were further analysed for determining the MGMT promoter methylation status using Methylation-specific PCR (MSP). Results: The mean age of patients was 50.3 years in the methylated group and 49.1 years in the unmethylated group (p value = 0.671). Out of 40 patients, 18 had methylated MGMT promoters while 22 had unmethylated MGMT promoters. We found that ring-like enhancement was seen more frequently in the unmethylated tumours (72.7%) than in methylated ones (61.1%). The presence of T2 heterogeneous signal intensity was seen more in the methylated group (77.8%) than unmethylated group (68.2%). Severe necrosis (affecting >50% of the tumour) was seen more in the methylated tumours (61.1%) than in the unmethylated tumours (40.09%). However, these differences were found to be statistically insignificant. Conclusion: The distribution and imaging characteristics may provide some information about methylation of high-grade gliomas but a multicentric large data maybe required to reach a consensus about its reliability when biopsy of the methylation status of the tumour is not available.

Ascorbate content of clinical glioma tissues is related to tumour grade and to global levels of 5-hydroxymethyl cytosine

Gliomas are incurable brain cancers with poor prognosis, with epigenetic dysregulation being a distinctive feature. 5-hydroxymethylcytosine (5-hmC), an intermediate generated in the demethylation of 5-methylcytosine, is present at reduced levels in glioma tissue compared with normal brain, and that higher levels of 5-hmC are associated with improved patient survival. DNA demethylation is enzymatically driven by the ten–eleven translocation (TET) dioxygenases that require ascorbate as an essential cofactor. There is limited data on ascorbate in gliomas and the relationship between ascorbate and 5-hmC in gliomas has never been reported. Clinical glioma samples (11 low-grade, 26 high-grade) were analysed for ascorbate, global DNA methylation and hydroxymethylation, and methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) promoter. Low-grade gliomas contained significantly higher levels of ascorbate than high-grade gliomas (p = 0.026). Levels of 5-hmC were significantly higher in low-grade than high-grade glioma (p = 0.0013). There was a strong association between higher ascorbate and higher 5-hmC (p = 0.004). Gliomas with unmethylated and methylated MGMT promoters had similar ascorbate levels (p = 0.96). One mechanism by which epigenetic modifications could occur is through ascorbate-mediated optimisation of TET activity in gliomas. These findings open the door to clinical intervention trials in patients with glioma to provide both mechanistic information and potential avenues for adjuvant ascorbate therapy.

Clinical strategies to manage adult glioblastoma patients without MGMT hypermethylation.

Glioblastoma (GBM) is a highly malignant brain tumor with a dismal prognosis. Standard therapy for GBM comprises surgical resection, followed by radiotherapy plus concomitant and adjuvant temozolomide (TMZ) therapy. The methylation status of the O6-methylguanine DNA methyltransferase (MGMT) promoter is one of the most essential predictive biomarkers for patients with GBM treated with TMZ. Patients with an unmethylated MGMT promoter (umMGMT), who comprise 60% of patients with GBM, present an even worse prognosis because of TMZ resistance. Radiotherapy with various fractionation, chemotherapy compensating for TMZ, targeted therapy against diverse oncogenic pathways, immunotherapy of vaccine or immune checkpoint inhibitor, and tumor treating fields have been studied in umMGMT GBM patients. However, most efforts have yielded negative results or merely minimal improvements. Therefore, effective patient subgroup selection concerning precision medicine has become the focus. By assigning different treatments to the corresponding patient subgroups, a better curative effect and subsequently prolonged survival can be achieved. In this review, we re-evaluate the value of standard TMZ therapy and summarize the new clinical strategies and attempts to treat patients with umMGMT, which yielded positive and negative results, to provide alternative treatment options and discuss future directions of umMGMT GBM treatment.

Association of MGMT Gene Promoter Methylation With Clinicopathological Parameters in Patients With Wild-type IDH Glioblastoma.

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter plays a key role in response to temozolomide chemotherapy and disease prognosis in patients with wild-type isocitrate dehydrogenase (IDH) glioblastoma (GBM). The MGMT promoter methylation status and its association with clinicopathological parameters were retrospectively analysed in a cohort of 316 patients with GBM with wild-type IDH. MGMT methylation was significantly associated with ATRX chromatin remodeler (ATRX) loss and completion of the standard Stupp protocol. The median durations of overall and progression-free survival for the unmethylated, low-methylated (10-39%), and hypermethylated (≥40%) groups were 15, 23, and 30 months and 11, 18, and 21 months, respectively. However, the improvement in the survival of the hypermethylated group was not statistically significant. We suggest a possible association between MGMT methylation status and ATRX mutations in GBM with wild-type IDH.

Diagnostic performance of radiomics using machine learning algorithms to predict MGMT promoter methylation status in glioma patients: a meta-analysis.

We aimed to assess the diagnostic performance of radiomics using machine learning algorithms to predict the methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter in glioma patients. A comprehensive literature search of PubMed, EMBASE, and Web of Science until 27 July 2021 was performed to identify eligible studies. Stata SE 15.0 and Meta-Disc 1.4 were used for data analysis. A total of fifteen studies with 1663 patients were included: five studies with training and validation cohorts and ten with only training cohorts. The pooled sensitivity and specificity of machine learning for predicting MGMT promoter methylation in gliomas were 85% (95% CI 79%-90%) and 84% (95% CI 78%-88%) in the training cohort (n=15) and 84% (95% CI 70%-92%) and 78% (95% CI 63%-88%) in the validation cohort (n=5). The AUC was 0.91 (95% CI 0.88-0.93) in the training cohort and 0.88 (95% CI 0.85-0.91) in the validation cohort. The meta-regression demonstrated that magnetic resonance imaging sequences were related to heterogeneity. The sensitivity analysis showed that heterogeneity was reduced by excluding one study with the lowest diagnostic performance. This meta-analysis demonstrated that machine learning is a promising, reliable and repeatable candidate method for predicting MGMT promoter methylation status in glioma and showed a higher performance than non-machine learning methods.

Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas

PurposeThe methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter has been proven to be a prognostic and predictive biomarker for lower grade glioma (LGG). This study aims to build a radiomics model to preoperatively predict the MGMT promoter methylation status in LGG. Method122 pathology-confirmed LGG patients were retrospectively reviewed, with 87 local patients as the training dataset, and 35 from The Cancer Imaging Archive as independent validation. A total of 1702 radiomics features were extracted from three-dimensional contrast-enhanced T1 (3D-CE-T1)-weighted and T2-weighted MRI images, including 14 shape, 18 first order, 75 texture, and 744 wavelet features respectively. The radiomics features were selected with the least absolute shrinkage and selection operator algorithm, and prediction models were constructed with multiple classifiers. Models were evaluated using receiver operating characteristic (ROC). ResultsFive radiomics prediction models, namely, 3D-CE-T1-weighted single radiomics model, T2-weighted single radiomics model, fusion radiomics model, linear combination radiomics model, and clinical integrated model, were built. The fusion radiomics model, which constructed from the concatenation of both series, displayed the best performance, with an accuracy of 0.849 and an area under the curve (AUC) of 0.970 (0.939-1.000) in the training dataset, and an accuracy of 0.886 and an AUC of 0.898 (0.786-1.000) in the validation dataset. Linear combination of single radiomics models and integration of clinical factors did not improve. ConclusionsConventional MRI radiomics models are reliable for predicting the MGMT promoter methylation status in LGG patients. The fusion of radiomics features from different series may increase the prediction performance.

18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma

BackgroundThe methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) promoter has emerged as a favorable independent prognostic and predictive biomarker in glioma. This study aimed to build a radiomics signature based on 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) for noninvasive measurement of the MGMT promoter methylation status in glioma.MethodsOne hundred and seven pathology-confirmed primary diffuse glioma patients were retrospectively included and randomly assigned to the primary (n = 71) or validation cohort (n = 36). The MGMT promoter methylation status was measured by pyrosequencing. A total of 1561 radiomics features were extracted from the three-dimensional region of interest (ROI) on the standard uptake value (SUV) maps that were generated from the original 18F-FDG PET data. A radiomics signature, a clinical signature and a fusion signature that combined the clinical and radiomics features together were generated. The performance of the three signatures was evaluated by receiver operating characteristic (ROC) curve analysis, and the patient prognosis was stratified based on the MGMT promoter methylation status and the signature with the best performance.ResultsFive radiomics features were selected to construct the radiomics signature, and displayed the best performance with area under the receiver operating characteristic (ROC) curve (AUC) reaching 0.94 and 0.86 in the primary and validation cohorts, respectively, which outweigh the performances of clinical signature and fusion signature. With a median follow-up time of 32.4 months, the radiomics signature stratified the glioma patients into two risk groups with significantly different prognoses (p = 0.04).Conclusions18F-FDG-PET-based radiomics is a promising approach for preoperatively evaluating the MGMT promoter methylation status in glioma and predicting the prognosis of glioma patients noninvasively.

Abstract 1392: Machine Learning Radiomic Biomarkers Non-invasively Assess Genetic Characteristics of Glioma Patients

Abstract Genetic heterogeneity of gliomas, both across and within patients, is a significant challenge in precision diagnostics and treatment planning. The emerging field of radiogenomics focuses on imaging signatures reflecting underlying genomic characteristics. In this study, we use advanced radiomic analysis of clinically acquired multi-parametric MRI (mpMRI) sequences to non-invasively detect clinically-relevant genetic alterations in gliomas, including isocitrate dehydrogenase (IDH1), epidermal growth factor receptor variant-III (EGFRvIII), and promoter methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene. Such non-invasive, in vivo determination of tumor genetic alterations could assist in assessing spatial heterogeneity (currently not captured via single-specimen analyses), as well as prognostic stratification, and treatment planning. We delineated all tumors, from a retrospective cohort of 202 glioma patients with available pre-operative mpMRI (T1, T1-Gd, T2, T2-FLAIR, DTI, DSC-MRI), into sub-regions of enhancement, non-enhancement, and peritumoral edema/invasion. We used CaPTk (www.cbica.upenn.edu/captk) to extract quantitative imaging phenomic (QIP) features across sub-regions from all mpMRI, describing size, morphology, texture, and intensity. Cross-validated (CV) sequential feature selection determined the most discriminative QIP features. The predicted classifications, following a 10-fold CV, were compared with the results of a next-generation sequencing panel performed on specimens from the patients in our cohort, as well as pyrosequencing for MGMT. The CV accuracy of the radiomic assessment was 85% (spec = 86%, sens = 83%, area under the curve [AUC] = 0.85), 87% (spec = 90%, sens = 79%, AUC = 0.86), and 83% (spec = 85%, sens = 83%, AUC = 0.84) for mutations in IDH1, EGFRvIII, and MGMT methylation, respectively. These signatures were consistent with EGFRvIII-mutated, IDH1-wildtype, and MGMT-methylated tumors having increased neovascularization and cell density, as well as a distinctive spatial pattern involving relatively more frontal and parietal regions in EGFRvIII-mutants, more frontal regions in IDH1-mutants, and relatively right spherical regions in MGMT-methylated tumors. These detections were independent of age, gender, and additional genetic changes. By non-invasively capturing the tumor in its entirety, our proposed QIP signatures can assist in evaluating the tumor’s spatial heterogeneity, hence overcoming common sampling limitations of tissue-based analyses. These signatures can non-invasively stratify patients for therapies targeting specific genes, and potentially monitor the dynamic mutational changes during treatment. Given the routine use of imaging in clinical practice, our QIP signatures may provide an unprecedented opportunity to improve decision-support in cancer treatment at low cost. Citation Format: saima rathore, Spyridon Bakas, Hamed Akbari, MacLean P. Nasrallah, Stephen Bagley, Christos Davatzikos. Machine Learning Radiomic Biomarkers Non-invasively Assess Genetic Characteristics of Glioma Patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1392.

Novel predictive epigenetic signature for temozolomide in non-G-CIMP glioblastomas

ObjectiveTo identify novel epigenetic signatures that could provide predictive information that is complementary to promoter methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) gene for predicting temozolomide (TMZ) response, among glioblastomas (GBMs) without glioma-CpGs island methylator phenotype (G-CIMP)MethodsDifferent cohorts of primary non-G-CIMP GBMs with genome-wide DNA methylation microarray data were included for discovery and validation of a multimarker signature, combined using a RISK score model. Different statistical analyses and functional experiments were performed for clinical and biological validation.ResultsBy employing discovery cohorts with radiotherapy (RT) and TMZ versus RT alone and a strict multistep selection strategy, we identified seven CpGs, each of which was significantly correlated with overall survival (OS) of non-G-CIMP GBMs with RT/TMZ, independent of age, MGMT promoter methylation status, and other identified CpGs. A RISK score signature of the 7 CpGs was developed and validated to distinguish non-G-CIMP GBMs with differential survival outcomes to RT/TMZ, but not to RT alone. The interaction analyses also showed differential outcomes to RT/TMZ versus RT alone within the RISK score-based subgroups. The signature could also improve the risk classification by age and MGMT promoter methylation status. Functional experiments showed that HSBP2 appeared to be epigenetically regulated by one identified CpG and was associated with TMZ resistance, but it was not associated with cell proliferation or apoptosis in GBM cell lines. The predictive value of the single CpG methylation of HSBP2 by pyrosequencing was observed in a local cohort of isocitrate dehydrogenase 1 (IDH1) R132H wild-type GBMs.ConclusionsThis novel epigenetic signature might be a promising predictive (but not a general prognostic) biomarker and be helpful for refining the MGMT-based guiding approach to TMZ usage in non-G-CIMP GBMs.

MGMT Promoter Methylation Cutoff with Safety Margin for Selecting Glioblastoma Patients into Trials Omitting Temozolomide: A Pooled Analysis of Four Clinical Trials.

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). 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). 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.

MGMT promoter methylation in patients with glioblastoma: is methylation-sensitive high-resolution melting superior to methylation-sensitive polymerase chain reaction assay?

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene promoter is a prognostic factor in adults with glioblastoma (GBM); it also yields information that is useful for clinical decision-making in elderly GBM patients. While pyrosequencing is the gold standard for the evaluation of the methylation status of MGMT, methylation-sensitive polymerase chain reaction (MS-PCR) assay continues to be used widely. Although MS-PCR results exhibited a good correlation with the prognosis of patients with GBM treated under the Stupp protocol, interpretation of the bands is based on subjective judgment, and the assay cannot be used to analyze heterogeneously methylated samples. We assessed whether methylation-sensitive high-resolution melting (MS-HRM) is an alternative to MS-PCR. The authors prepared 3 primer sets that covered CpG 72–89 for MS-HRM analysis to determine the methylation levels of 6 human glioma cell lines. The results were validated by bisulfite sequencing of cloned alleles. The authors also subjected surgical samples from 75 GBM patients treated with temozolomide (TMZ) to MS-HRM to assess the MGMT methylation status and compared the findings with MS-PCR results using receiver operating characteristic (ROC), univariate, and multivariate analyses. There was a strong correlation between the methylation levels of the 6 glioma cell lines evaluated by MSHRM and by bisulfite sequencing; with primers 1 and 2, the correlation was significant (r = 0.959 and r = 0.960, respectively, p < 0.01). Based on log-rank analysis, MS-HRM was significantly better than MS-PCR for predicting progressionfree survival (PFS) and overall survival (OS) based on the methylation status of the MGMT promoter (PFS predicted by MS-HRM and MS-PCR = 0.00023 and 0.0035, respectively; OS = 0.00019 and 0.00028, respectively). ROC analysis showed that the area under the curve was larger with MS-HRM than with MS-PCR (PFS: 0.723 vs 0.635; OS: 0.716 vs 0.695). Based on multivariate Cox regression analysis, MS-HRM was significantly better than MS-PCR for predicting the treatment outcome (MS-HRM vs MS-PCR: PFS, p = 0.001 vs 0.207; OS, p = 0.013 vs 0.135). The authors’ findings show that MS-HRM is superior to MS-PCR for the detection of MGMT promoter methylation. They suggest MS-HRM as an alternative to MS-PCR for assessing the prognosis of patients with GBM.

The Impact of MGMT Promoter Methylation and Temozolomide Treatment in Serbian Patients with Primary Glioblastoma.

Background and objective: Despite recent advances in treatment, glioblastoma (GBM) remains the most lethal and aggressive brain tumor. A continuous search for a reliable molecular marker establishes the methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene promoter as a key prognostic factor in primary glioblastoma. The aim of our study was to screen Serbian patients with primary glioblastoma for an MGMT promoter hypermethylation and to evaluate its associations with overall survival (OS) and sensitivity to temozolomide (TMZ) treatment. Materials and methods: A cohort of 30 Serbian primary glioblastoma patients treated with radiation therapy and chemotherapy were analyzed for MGMT promoter methylation and correlated with clinical data. Results: MGMT methylation status was determined in 25 out of 30 primary glioblastomas by methylation-specific PCR (MSP). MGMT promoter hypermethylation was detected in 12 out of 25 patients (48%). The level of MGMT promoter methylation did not correlate with patients’ gender (p = 0.409), age (p = 0.536), and OS (p = 0.394). Treatment with TMZ significantly prolonged the median survival of a patient (from 5 to 15 months; p < 0.001). Conclusions: Due to a small cohort of primary GBM patients, our study is not sufficient for definitive conclusions regarding the prognostic value of MGMT methylation for the Serbian population. Our preliminary data suggest a lack of association between MGMT promoter methylation and overall survival and a significant correlation of TMZ treatment with overall survival. Further population-based studies are needed to assess the prognostic value of the MGMT promoter methylation status for patients with primary glioblastoma.

Predictive markers for MGMT promoter methylation in glioblastomas.

The promoter methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene has been described as the most important predictor of chemotherapeutic response and patients' survival in glioblastomas (GBs). Therefore, prediction of the MGMT promoter methylation status by imaging would help to preoperatively decide the overall treatment strategy as well as surgical strategy. This study aimed to detect imaging parameters to predict MGMT promoter methylation in GBs by using a commercially available software. We investigated three imaging features (ring enhancement, tumor location, and laterality) and apparent diffusion coefficient (ADC) parameters in 48 newly diagnosed GBs treated at Keio University Hospital in 2006 or later. For ADC, texture analyses were performed. Regions of interest (ROIs) were drawn manually with reference to contrast-enhanced areas, excluding necrotic and cystic regions. Mean ADC value and ADC histogram parameters, including kurtosis, skewness, and entropy, were compared with MGMT promoter methylation. Each parameter was evaluated to determine correlation with MGMT promoter methylation, and the parameters with significant associations with the methylation status were correlated with the MGMT-positive cell ratio determined by immunohistochemistry (IHC) analysis. The mean ADC value and ADC entropy were significantly associated with MGMT promoter methylation. The combination of mean ADC value and ADC entropy predicted MGMT promoter methylation, with a PPV of 81.2% and specificity of 88.9%. The mean ADC value and ADC entropy were negatively correlated with the MGMT-positive cell ratio in the IHC analysis. This study demonstrated that texture analyses of ADC histograms in GBs were predictive of MGMT promoter methylation.

MGMT promoter methylation status testing to guide therapy for glioblastoma: refining the approach based on emerging evidence and current challenges.

Glioblastoma (GBM) is the most common primary malignant brain tumor, with a universally poor prognosis. The emergence of molecular biomarkers has had a significant impact on histological typing and diagnosis, as well as predicting patient survival and response to treatment. The methylation status of the O6-methylguanine-DNA methyl-transferase (MGMT) gene promoter is one such molecular biomarker. Despite the strong evidence supporting the role of MGMT methylation status in prognostication, its routine implementation in clinical practice has been challenging. The methods and optimal cutoff definitions for MGMT status determination remain controversial. Variation in detection methods between laboratories presents a major challenge for consensus. Moreover, consideration of other clinical and genetic/epigenetic factors must also be incorporated into treatment decision making. In this review, we distill the available evidence to summarize our position on the optimal use of available assays, and propose strategies for resolving cases with equivocal methylation status and a framework for incorporating this important assay into research and clinical practice.

Real-time methylation-specific PCR for the evaluation of methylation status of MGMT gene in glioblastoma.

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene is a strong predictor for the efficacy of temozolomide chemotherapy and survival periods. However, the correlation between the extent of methylation and the difference in survival times has not been fully clarified. Simple and quantitative evaluations of the methylation status in the promotor region of the MGMT gene are expected to be worldwide standardized diagnostics. We applied real-time semi-quantitative methylation-specific polymerase chain reaction (SQ-MSP) of the MGMT gene promoter region to 84 glioblastoma patients. The SQ-MSP result showed that the ΔCt value, which represents the difference between uCt and mCt (uCt value – mCt value), is inversely correlated with overall survival. With adequate cutoff setting, this assay showed that those patients suffering from a tumor with low ΔCt (methylated) survived significantly longer than those having tumors with high ΔCt (un-methylated). The most significant difference was observed when the cutoff was set at a ΔCt of 2. Using this cutoff point, the result of MGMT immunohistochemical analysis was also significantly correlated with the methylation status examined with real-time SQ-MSP. These results collectively show that MGMT promoter methylation status actually affects patients’ survival and protein expression depending on its methylation level, and the extent of methylated CpGs would be better assessed with real-time SQ-MSP than with the standard gel-based MSP. This method is cost- and labor-saving compared with pyrosequencing, and significantly contributes to the accurate and objective prediction of patient survival.

Glioblastoma Multiforme: Fewer Tumor Copy Number Segments of the SGK1 Gene Are Associated with Poorer Survival.

Glioblastoma multiforme (GBM) is the most common primary tumor of the central nervous system. The serum and glucocorticoid-regulated kinase SGK1 gene is required for the growth and survival of GBM stem-like cells under both normoxic and hypoxic conditions. It has been reported that oxygenation significantly affects cellular genetic expression; 30% of the genes required in hypoxia were not required under normoxic conditions. Therefore, we examined SGK1 expression to determine if it may be a novel potential drug target for GBM. We assessed the association between SGK1 and glioblastoma patient overall survival using the GBM cohort in TCGA (The Cancer Genome Atlas) database (TCGA-GBM). To access and analyze the data we used the UCSC Xena browser (https://xenabrowser.net). Survival data of the GBM subgroup were extracted for analysis and generation of Kaplan-Meier curves for overall survival. The best cut-off was identified by methods described in the R2 web-based application (http://r2.amc.nl). We analyzed patient survival by tumor SGK1 copy number segments after removal of common germ-line copy-number variants (CNVs). Copy number segments (log2 tumor/normal) ≤0.009700 were associated with significantly poorer survival (p=0.016). Increased median overall survival associated with increased SGK1 copy number segments may be a reflection of better tumor oxygenation. Therefore, besides being a drug target, SGK1 may also be a prognostic marker. Among molecular tumor markers, only the methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) gene has shown a significant association with survival in patients with GBM.