The Clinical Implications of Inconsistently Methylated Results from Glioblastoma MGMT Testing by Replicate Methylation-Specific PCR

'The Reports of My Death Are Greatly Exaggerated'-Evaluating the Effect of Necrosis on MGMT Promoter Methylation Testing in High-Grade Glioma

(1) Background: MGMT (O-6-methylguanine-DNA methyltransferase) promoter methylation remains an important predictive biomarker in high-grade gliomas (HGGs). The influence of necrosis on the fidelity of MGMT promoter (MGMTp) hypermethylation testing is currently unknown. Therefore, our study aims to evaluate the effect of varying degrees of necrosis on MGMTp status, as determined by pyrosequencing, in a series of primary and recurrent HGGs; (2) Methods: Within each case, the most viable blocks (assigned as 'true' MGMTp status) and the most necrotic block were determined by histopathology review. MGMTp status was determined by pyrosequencing. Comparisons of MGMTp status were made between the most viable and most necrotic blocks. (3) Results: 163 samples from 64 patients with HGGs were analyzed. MGMTp status was maintained in 84.6% of primary and 78.3% of recurrent HGGs between the most viable and necrotic blocks. A threshold of ≥60% tumor cellularity was established at which MGMTp status was unaltered, irrespective of the degree of necrosis. (4) Conclusions: MGMTp methylation status, as determined by pyrosequencing, does not appear to be influenced by necrosis in the majority of cases at a cellularity of at least 60%. Further investigation into the role of intratumoral heterogeneity on MGMTp status will increase our understanding of this predictive marker.

Combining MGMT promoter pyrosequencing and protein expression to optimize prognosis stratification in glioblastoma

Pyrosequencing (PSQ) represents the golden standard for MGMT promoter status determination. Binary interpretation of results based on the threshold from the average of several CpGs tested would neglect the existence of the “gray zone”. How to define the gray zone and reclassify patients in this subgroup remains to be elucidated. A consecutive cohort of 312 primary glioblastoma patients were enrolled. CpGs 74‐81 in the promoter region of MGMT were tested by PSQ and the protein expression was assessed by immunohistochemistry (IHC). Receiver operating characteristic curves were constructed to calculate the area under the curves (AUC). Kaplan‐Meier plots were used to estimate the survival rate of patients compared by the log‐rank test. The optimal threshold of each individual CpG differed from 5% to 11%. Patients could be separated into the hypomethylated subgroup (all CpGs tested below the corresponding optimal thresholds, n = 126, 40.4%), hypermethylated subgroup (all CpGs tested above the corresponding optimal thresholds, n = 108, 34.6%), and the gray zone subgroup (remaining patients, n = 78, 25.0%). Patients in the gray zone harbored an intermediate prognosis. The IHC score instead of the average methylation levels could successfully predict the prognosis for the gray zone (AUC for overall survival, 0.653 and 0.519, respectively). Combining PSQ and IHC significantly improved the efficiency of survival prediction (AUC: 0.662, 0.648, and 0.720 for PSQ, IHC, and combined, respectively). Immunohistochemistry is a robust method to predict prognosis for patients in the gray zone defined by PSQ. Combining PSQ and IHC could significantly improve the predictive ability for clinical outcomes.

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.

MGMT Testing in Glioblastomas: Pitfalls and Opportunities

Gliomas, that do not respond to alkylating agent chemotherapy, can be made more sensitive to chemotherapy through promotor mediated epigenetic silencing of the MGMT gene. MGMT is one of the important markers in glioblastomas as it not only predicts response to therapy but may also be used as an independent prognostic marker. As such, MGMT is gaining increasing traction in diagnosis, prognostication, and therapeutic decision-making for these highly malignant gliomas. Although, MGMT promotor methylation status is becoming more commonly used in neuro-oncology; this test remains imperfect. Because of its increasing use in clinical practice and research, it is integral that we are aware of its pitfalls and complications. Currently, there are many ways to detect a patient's MGMT promotor methylation status, including: quantitative PCR, methylation-specific PCR, pyrosequencing, real time PCR with high resolution melt, and the infinitum methylation EPIC beadChip. The technical aspects, shortcomings, and optimal approach to interpreting the results of each method will be discussed. Furthermore, given that none of these methods have been prospectively validated, the challenge of equivocal cases will be discussed, and technical and logistic strategies for overcoming these challenges will be proposed. Finally, the difficulty in validating these methods, establishing standardized practice, and considerations of the cost of these competing methods will be explored.

High density DNA methylation array is a reliable alternative for PCR-based analysis of the MGMT promoter methylation status in glioblastoma

AIM

MGMT promoter methylation status is an important biomarker predicting survival and response to chemotherapy in patients suffering from glioblastoma. Since new diagnostic methods such as methylome-based classification of brain tumors are more and more frequently performed, we aimed at comparing the suitability of calculating the MGMT promoter methylation status in a quantitative manner from the methylome profiling as compared to the classic gold standard assessment by PCR.

METHODS

Our cohort consisted of 39 cases diagnosed as "glioblastoma, IDH-wildtype" of which the MGMT promoter methylation status was analyzed with both methylation-specific PCR and high density DNA methylation array using the STP-27 algorithm. Contradictory results were validated by pyrosequencing.

RESULTS

The inter-method reliability reached 77% (kappa-coefficient: 0.58) when also cases with an inconclusive result in one or the other method were taken into account. When only cases with conclusive results in both methods were considered, a very high inter-method reliability of 91% (kappa-coefficient: 0.86) could be achieved. For "methylated" cases, no contradictory results were obtained. For the remaining two cases with discrepant results subsequent pyrosequencing analyses spoke in favor of each previously applied method once.

CONCLUSION

In addition to its benefits for molecular subgrouping and copy number analysis of brain tumors, DNA-methylation based classification is a highly reliable tool for the assessment of MGMT promoter methylation status in glioblastoma patients.

A novel analytical model of MGMT methylation pyrosequencing offers improved predictive performance in patients with gliomas

The methylation status of the promoter of MGMT gene is a crucial factor influencing clinical decision-making in patients with gliomas. MGMT pyrosequencing results are often dichotomized by a cut-off value based on an average of several tested CpGs. However, this method frequently results in a "gray zone", representing a dilemma for physicians. We therefore propose a novel analytical model for MGMT methylation pyrosequencing. MGMT CpG heterogeneity was investigated in 213 glioma patients in two tested cohorts: cohort A in which CpGs 75-82 were tested and cohort B in which CpGs 72-78 were tested. The predictive performances of the novel and traditional averaging models were compared in 135 patients who received temozolomide using receiver operating characteristic curves and Kaplan-Meier curves, and in patients stratified according to isocitrate dehydrogenase gene mutation status. The results were validated in an independent cohort of 65 consecutive patients with high-grade gliomas from the Chinese Glioma Genome Atlas database. Heterogeneity of MGMT promoter CpG methylation level was observed in most gliomas. The optimal cut-off value for each individual CpG varied from 4-16%. The current analysis defined MGMT promoter methylation as occurring when at least three CpGs exceeded their respective cut-off values. This novel analysis could accurately predict the prognosis of patients in the methylation "gray zone" according to the standard averaging method, and improved the area under the curves from 0.67, 0.76, and 0.67 to 0.70, 0.84, and 0.72 in cohorts A, B, and the validation cohort, respectively, demonstrating superiority of this analytical method in all three cohorts. Furthermore, the advantages of the novel analysis were retained regardless of WHO grade and isocitrate dehydrogenase gene mutation status. In conclusion, this novel analytical model offers an improved clinical predictive performance for MGMT pyrosequencing results and is suitable for clinical use in patients with gliomas.

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

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.

An examination of critical parameters in hybridization-based epigenotyping using magnetic microparticles

Gene-specific promoter methylation is involved in gene silencing and is an important cancer biomarker. Cancer-specific methylation patterns have been observed and clinically validated for numerous gene promoters, but the knowledge gleaned from this large body of work is currently under-utilized in the clinic. Methylation-specific PCR is currently the gold standard method for clinical methylation assessment, but several research groups have proposed hybridization-based techniques which could be simpler to implement and provide more accurate results. However, the sensitivity of this easier alternative must be improved dramatically in order to compete with methylation-specific PCR. Efficient sample capture is a key step in maximizing sensitivity, so here we investigate the key parameters involved in (i) maximizing the capture of gene-specific target DNA molecules at the surfaces of functionalized, magnetic microparticles and (ii) recognizing DNA methylation using an engineered methyl-CpG-binding domain (MBD) protein. The magnetic bead density, the probe concentration, and the MBD concentration were very important for maximizing detection, and other variables such as the hybridization time also impacted the target capture efficiency but had a smaller effect on the overall methylation assay. The effect of genomic DNA on the capture of the target sequence was also investigated, and model methylated vs. unmethylated target sequences could be distinguished in the presence of 1 ng/μL genomic DNA. The findings we report related to the underlying binding events involved in hybridization-based epigenotyping can be leveraged in combination with the many signal amplification and detection approaches that are currently being developed. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1589-1595, 2018.

Brain tumor initiating cells: with great technology will come greater understanding

The discovery of the brain tumor initiating cells resulted in a paradigm shift within the cancer research community to consider brain tumors as an outcome of developmental mechanisms gone awry. This review will guide the reader through the technological advances that hold the powerful potential to allow brain cancer researchers to develop an intimate understanding of the dynamic and complex mechanism governing brain tumor behavior.

Real-Time Methylation-Specific Polymerase Chain Reaction for MGMT Promoter Methylation Clinical Testing in Glioblastoma: An Alternative Detection Method for a Heterogeneous Process

OBJECTIVES

To develop and evaluate a real-time methylation-specific polymerase chain reaction (RT-MSP) MGMT assay, with a particular focus on small biopsies and indeterminate testing results.

METHODS

We assessed formalin-fixed paraffin-embedded glioblastoma or gliosarcoma specimens (n = 641). A test-validation group (n = 51) with previously obtained reference laboratory (RL) results was used to determine performance characteristics of the RT-MSP assay. An indeterminate (equivocal) category was established for cases that could not be clearly classified as positive or negative.

RESULTS

Overall agreement of RT-MSP and RL results was 91% (41/45 nonindeterminate cases). Discordant cases were tested by pyrosequencing, and results were most concordant with RT-MSP. Among cases with limited amounts of tissue (n = 7), six yielded valid results by RT-MSP (all negative); the single invalid result consisted of a stereotactic biopsy specimen obtained 14 years prior. A subset of indeterminate cases obtained during clinical testing (n = 18/575 [3%]) was also evaluated by pyrosequencing and showed a heterogeneous pattern of methylation across the eight interrogated CpG sites.

CONCLUSIONS

The RT-MSP assay that we developed in-house is a robust clinical detection method for the heterogeneous process of MGMT promoter methylation in glioblastoma.

Novel recursive partitioning analysis classification for newly diagnosed glioblastoma: A multi-institutional study highlighting the MGMT promoter methylation and IDH1 gene mutation status

BACKGROUND AND PURPOSE

To refine the recursive partitioning analysis (RPA) classification for glioblastoma incorporating the MGMT methylation and IDH1 mutation status.

METHODS AND MATERIALS

Three-hundred forty patients were treated with radiotherapy plus concurrent and adjuvant temozolomide in three tertiary-referral hospitals. MGMT methylation and IDH1 mutation status were available in all patients. Methylation of the MGMT (MGMTmeth) and mutation of IDH1 (IDH1mut) were observed in 42.4% and 6.2% of the patients, respectively.

RESULTS

The median follow-up for survivors and all patients was 33.2 and 20.5months, respectively. The median survival (MS) was 23.6months. RPA was performed on behalf of the results of the Cox proportional hazards model. MGMT methylation generated the initial partition (MGMTmeth vs. MGMTunmeth) in the RPA. Three final RPA classes were identified; class I=MGMTmeth/IDH1mut or MGMTmeth/IDH1wt/GTR/KPS≥90 (MS, 67.2months); class II=MGMTmeth/IDH1wt/GTR/KPS<90, MGMTmeth/IDH1wt/residual disease, MGMTunmeth/age<50, or MGMTunmeth/age≥50/GTR (MS, 24.0months); class III=MGMTunmeth/age≥50/residual disease (MS, 15.2months).

CONCLUSIONS

A novel RPA classification for glioblastoma was formulated highlighting the impact of MGMTmeth and IDH1mut in the temozolomide era. This model integrating pertinent molecular information can be used effectively for the patient stratification in future clinical trials. An external validation is ongoing.