Methylation Status Of MGMT Gene Promoter Research Articles

Abstract 7395: Histology-based prognosis prediction using deep learning outperforms and is independent of the MGMT methylation status in patients with glioblastoma

Abstract Introduction: MGMT gene promoter methylation status is today the only biomarker of survival for GBM patients and predicts favorable response to temozolomide (TMZ). Here we propose a deep learning-based model using histology data (H&E slides) to predict the prognosis of patients with Glioblastoma (GBM) treated by standard of care (SOC). Methods: We included TCGA GBM patients and selected only patients treated after 2005 (Stupp protocol start); compliant to WHO 2021 classification; treated by surgery and adjuvant therapy; with a follow-up superior to median overall survival (OS) (14.5 months). Short and long survivor labels were defined based on median OS cut-off. A deep learning pipeline was trained to predict these labels from the H&E slides (baseline surgery samples). First, the slides were automatically segmented into tissue and background, divided into a regular grid of tiles (112 × 112µm), and tiles were vectorized using a vision transformer-based feature extractor trained on H&E slides of 5,500 patients with 16 cancer subtypes (GBM excluded). In the second step, ABMIL deep learning model was trained to predict the survival category using the bag of tile features available from step 1 for each patient. The cohort was divided into five folds with even numbers of short and long survivors. For each fold, 50 ABMIL models were trained on the remaining folds and ensembled to predict the category of the patients in the fold. Training hyperparameters were tuned on a separated cohort excluding GBM patients. Results: After filtering, we analyzed n = 192 TCGA GBM patients including 154 patients with a known MGMT promoter methylation status. Our histology-based model had an accuracy of 0.661 and a ROC AUC of 0.706. It stratified the population into short and long survivors with an Hazard Ratio (HR) of 0.48 (95% CI 0.34-0.69). Our model outperformed the MGMT methylation status that had an HR of 0.57 (95% CI 0.40-0.83). Moreover, our model was independent of MGMT methylation status and the combination of both was able to further improve prognosis prediction: we applied our model independently to the 91 patients with an unmethylated MGMT status (predicted: 43 low, 48 high) and to the 63 patients with a methylated MGMT status (predicted: 30 low, 33 high), and obtained HR of 0.42 (95% CI 0.27-0.67) and 0.49 (95% CI 0.28-0.86) respectively. Conclusion: Having selected patients treated by the latest SOC and classified as GBM by the latest WHO criteria, we propose a model predicting survival based on histological specimens available in routine care, which outperformed the current unique biomarker MGMT methylation status. The combination of this status and our model improves prognosis predictions compared to each strategy alone. Citation Format: Lucas Fidon, Celine Thiriez, Alexandre Grimaldi, Omar Darwiche Domingues, Charles Maussion, Caroline Hoffmann. Histology-based prognosis prediction using deep learning outperforms and is independent of the MGMT methylation status in patients with glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7395.

Deep DNA sequencing of MGMT, TP53 and AGT in Mexican astrocytoma patients identifies an excess of genetic variants in women and a predictive biomarker.

Astrocytomas are a type of malignant brain tumor with an unfavorable clinical course. The impact of AGT and MGMT somatic variants in the prognosis of astrocytoma is unknown, and it is controversial for TP53. Moreover, there is a lack of knowledge regarding the molecular characteristics of astrocytomas in Mexican patients. We studied 48 Mexican patients, men and women, with astrocytoma (discovery cohort). We performed DNA deep sequencing in tumorsamples, targeting AGT, MGMT and TP53, and we studied MGMT gene promoter methylation status. Then we compared our findings to a cohort which included data from patients with astrocytoma from The Cancer Genome Atlas (validation cohort). In the discovery cohort, we found a higher number of somatic variants in AGT and MGMT than in the validation cohort (10.4% vs < 1%, p < 0.001), and, in both cohorts, we observed only women carried variants AGT variants. We also found that the presence of either MGMT variant or promoter methylation was associated to better survival and response to chemotherapy, and, in conjunction with TP53 variants, to progression-free survival. The occurrence of AGT variants only in women expands our knowledge about the molecular differences in astrocytoma between men and women. The increased prevalence of AGT and MGMT variants in the discovery cohort also points towards possible distinctions in the molecular landscape of astrocytoma among populations. Our findings warrant further study.

Influence of Intratumor Heterogeneity on the Predictivity of MGMT Gene Promoter Methylation Status in Glioblastoma.

Glioblastoma is the most aggressive tumor of the central nervous system. Prognosis is poor, even in the presence of a methylated state of MGMT gene promoter, which represents the biomarker with the highest prognostic/predictive value for the standard treatment of patients. Among patients with a methylated MGMT status, we identified an intermediate range of methylation above the standard 9% cut-off (gray zone) in which the predictive strength of the marker was lost. In an effort to improve the evaluation of the biomarker in clinical decision-making, we are carrying out a retrospective study, performing an in-depth analysis of samples used for diagnosis to understand how molecular heterogeneity, a hallmark of glioblastoma, impacts the evaluation of MGMT gene promoter methylation. Preliminary data from samples belonging to the “gray zone” tend to confirm the hypothesis of a mismatch between methylation values used for clinical decision-making and those included in our in-depth analysis. Confirmation of these data would help to better define the predictive power of MGMT promoter methylation status and greatly facilitate clinical decision-making.

Abstract 3186: Methylation MGMT gene promoter analysis based on a high throughput method combines bisulfite conversion with amplicon sequencing

Abstract Background: Methylation of the MGMT gene promoter was observed in approximately 50% of glioblastoma multiforme (GBM). Epigenetic silencing of the MGMT gene by promoter methylation results in decreased MGMT protein expression, reduced DNA repair activity, and potential increased sensitivity to alkylating agent-based chemotherapy. Although MGMT promoter methylation status has been widely evaluated by methylation-specific PCR and bisulfite pyrosequencing. The limitations to these methods include low quantitative accuracy and low sample throughput. Here, we developed a high throughput method (in-house One-Step Seq Method, Genetron) which combines bisulfite conversion with amplicon sequencing of MGMT gene promoter. Methods: DNA was extracted from 144 FFPE or fresh frozen glioma tissues. For bisulfite pyrosequencing, MGMT promoter methylation status was analyzed using the MGMT Pyro Kit (Qiagen 970061) following the manufacturer's protocol. At the same time,the MGMT promoter methylation status was also analyzed by in-house One-Step Seq Methodfollowing bisulfite conversion. In briefly, the DNA was pre-treated by sodium bisulfite. Then Exon 1 of human MGMT gene was amplified from bisulfite conversed DNA. And library was constructed at the same time. High-throughput sequencing was performed on Ion GeneStudio S5. Reads mapping and methylation calling was handled by Bismark. The DNA sample was identified as MGMT methylation, if average methylation level of all CpG sites in exon 1 of MGMT was more than 21 %. Results: Currently, bisulfite pyrosequencing was considered as the gold standard for DNA methylation analysis. Comparing the result of bisulfite pyrosequencing analysis with the result of in-house methylation status analysis, 94.4% of DNA samples from 144 glioma tissues showed consistent methylation status of MGMT gene promotor. 5 DNA samples were identified as non-methylation in bisulfite pyrosequencing, but with methylation in in-house methylation status analysis. While 3 DNA samples were identified as methylation in bisulfite pyrosequencing, but not in in-house methylation status analysis. Meanwhile, by in-house One-Step Seq Method following bisulfite conversion, both the bisulfite conversion and library construction could be completed injust 4 hours using 10 ng DNA, and MGMT gene promoter methylation status could be estimated in two days. Conclusions: We developed a High-throughput sequencing based method to analyze MGMT status accurately combines bisulfite conversion with amplicon sequencing. This method shows high accuracy, high throughput, and easy manipulation for molecular classification of brain cancer. Citation Format: Yukun Zhang, Min Shi, Qiaosong Zheng, Xiao Shi, Min Chen, Le Li, Huiming Zhu, Liping Jiang, Tonghui Ma, Sumin Geng. Methylation MGMT gene promoter analysis based on a high throughput method combines bisulfite conversion with amplicon sequencing [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3186.

Weak MGMT gene promoter methylation confers a clinically significant survival benefit in patients with newly diagnosed glioblastoma: a retrospective cohort study.

Quantitative methylation specific PCR (qMSP) is a frequently used technique to assess MGMT gene promoter methylation in glioblastoma patients. The optimal technical cut-off value to distinguish methylated from unmethylated samples is nevertheless still undetermined. In literature, a "grey zone" of diagnostic uncertainty has been described. We performed a retrospective analysis of newly diagnosed glioblastoma patients treated according to the Stupp protocol. Epidemiological data were gathered from the individual patient files. MGMT gene promoter methylation status was determined on stored tumour samples using qMSP. A strong, weak or absent promoter methylation was determined based on Cq values (quantification value) of the MGMT and ACTB primers as well as a positive control sample. In total, 181 patient files were reviewed and included for statistical analysis. MGMT promoter hypermethylation was detected in 38.7% of glioblastoma patients. The median overall survival of unmethylated and strongly methylated patients was 10.1months and 19.7months respectively. Furthermore, 11% of the total patient cohort had a weak MGMT gene promoter methylation. The median OS in this subgroup was 15.4months, significantly better compared to the unmethylated cohort (P < 0.001). Multivariate Cox regression analysis showed weak MGMT promoter methylation as an independent prognostic parameter for overall survival. Glioblastoma patients with weak promoter methylation show a statistically significant longer overall survival when compared to clearly unmethylated patients. Patients with grey zone qMSP test results should receive additional molecular analysis in future to further direct individual therapy strategies.

Potential influence of IDH1 mutation and MGMT gene promoter methylation on glioma-related preoperative seizures and postoperative seizure control

PurposeTo examine the occurrence of glioma-related preoperative seizures (GPS) and post-operative seizure control (PSC) with respect to patients characteristics including five commonly tested tumor molecular markers (TMMs). MethodsA single-center retrospective cohort study of patients with glioma evaluated at the Mayo Clinic, Florida between 2016 and 2018. Results68 adult patients (mean age = 51-years, 45-males) were included. 46 patients had GPS. 57 patients underwent intra-operative electrocorticography during awake craniotomy-assisted glioma resection. All patients underwent glioma resection (53, gross-total resection) with histologies of pilocytic astrocytoma (n = 2), diffuse astrocytoma (n = 4), oligodendroglioma (n = 14), anaplastic astrocytoma (n = 16), anaplastic oligodendroglioma (n = 1), and glioblastoma (n = 31). 31 (67%) patients had PSC (median follow-up = 14.5 months; IQR = 7–16.5 months). IDH1 mutation (IDH1mut) was present in 32, ARTX retention in 53, MGMT gene promotor methylation in 15, 1p/19q co-deletion in 15, and over-expression of p53 in 19 patients. Patients with IDH1mut were more likely to have GPS (p = 0.037) and PSC (p = 0.035) compared to patients with IDH1 wild-type. Patients with MGMT gene promoter methylation were also likely to have PSC (p = 0.032). GPS or PSC did not differ by age, sex, extent of surgery, glioma grade, location, and histopathological subtype, p53 expression, ARTX retention, or 1p/19q co-deletion status. ConclusionsGPS and PSC may be associated with IDH1 mutation and MGMT gene promoter methylation status but not other glioma characteristics including tumor grade, location, or histopathology. Prospective studies with larger sample size are needed to clarify the exact mechanisms of GPS and PSC by the various TMMs to identify new treatment targets.

Dose-intensified rechallenge with temozolomide: One week on/one week off versus 3 weeks on/one week off in patients with progressive or recurrent glioblastoma (DIRECTOR).

TPS2103 Background: No standard of care has been defined for patients with glioblastoma who relapse or progress on or after standard temozolomide (TMZ)-based radiochemotherapy. Rechallenge with TMZ using various dose-intensified regimens is a common approach for recurrent glioblastoma. O6-methylguanylmethyltransferase (MGMT) promoter methylation is a strong prognostic marker in newly diagnosed glioblastoma. However, in recurrent glioblastoma, the prognostic value of the MGMT status has remained unclear. Methods: The DIRECTOR trial is an open-label prospectively randomized phase II trial investigating 2 different TMZ rechallenge regimens, i.e. 1 week on/1 week off (Arm A, 120-150 mg/m2 per day for 7 days) versus 3 weeks on/1 week off (Arm B, 80-100 mg/m2 per day for 21 days) in recurrent glioblastoma. Patients were enrolled at first progression after having completed the first-line TMZ radiochemotherapy and at least 2 adjuvant TMZ cycles. At randomization, MGMT gene promoter methylation status from the primary or recurrent tumor was mandatory. The study treatment was monitored every 2 months by MRI using MacDonald criteria. Translational studies included blood biomarker (e.g. regulatory T cell counts, MGMT activity in peripheral blood). In addition, quality-of-life was evaluated by QLQ-C30 and QLQ-BN20 EORTC scores. Neurocognitive testing using the NeuroCogFx was optional. The primary endpoint is median time-to-treatment failure that was defined as progression, toxicity or death from any cause. Secondary endpoints are progression-free survival, overall survival, response and MGMT correlations. The trial was performed in 16 sites in Austria, Germany, and Switzerland. 105 of 166 patients have been enrolled (53 patients in Arm A and 52 patients in Arm B) before the enrollment was prematurely stopped on 30 June 2012. The database will be closed on 30 June 2013. Clinical trial information: NCT00941460.

Survival in Patients with Newly Diagnosed Conventional Glioblastoma: A Modified Prognostic Score Based on a Single-Institution Series

Recursive partioning analysis (RPA) is commonly used to define the stratification of patients with glioblastoma. Epigenetic silencing of the O6-methylguanine methyltransferase (MGMT) gene by promoter methylation plays an important role in regulating MGMT expression in gliomas and this is an established independent prognostic factor. We tested a prognostic scoring system including all clinical variables used by RPA classification (age, ECOG performance status and type of surgery) and MGMT gene promoter methylation status. Seventy-eight consecutive patients with newly diagnosed, histopathologically confirmed conventional glioblastoma were included. Information about MGMT promoter methylation status was available for all of them. Based on the patients' age (<50 vs ≥50 years), ECOG performance status (0 vs ≥1), type of surgery (gross tumor resection versus partial resection/biopsy) and MGMT promoter methylation status (methylated versus unmethylated), three classes of risk were generated where the prognostic score was defined assigning 1 point to every favorable parameter (Class I: ≥3; Class II: 2; Class III: 0-1). All classes were correlated with overall survival. The median survival times were 32.4, 8.6 and 8.8 months for Class I, II and III, respectively, corresponding to 2-year survival rates of 69%, 13.5% and <1%. The same analysis was performed on 54 patients treated with postoperative concomitant chemoradiotherapy. The median survival times were 32.5, 13.4 and 8.9 months for Class I, II and III, respectively, corresponding to 2-year survival rates of 68.6%, 26.9% and <1%. In both groups of 78 and 54 patients the differences in survival between Class I and III were statistically significant ( P <0.0001). The proposed prognostic scoring system including clinical variables and MGMT promoter methylation status proved valuable in patients with primary conventional glioblastoma, especially those treated with postoperative chemoradiotherapy.

MGMT Gene Promoter Methylation Status as a Potent Prognostic Factor in Glioblastoma Treated with Temozolomide Chemo-irradiation

MGMT Gene Promoter Methylation Status as a Potent Prognostic Factor in Glioblastoma Treated with Temozolomide Chemo-irradiation

INI1 immunohistochemical expression in glioblastoma: correlation with MGMT gene promoter methylation status and patient survival

INI1 expression and its correlation with MGMT gene promoter methylation status and follow-up was investigated in 77 surgically removed glioblastomas then treated with radiotherapy (RT) or RT plus temozolomide (TMZ). INI1 was determined by immunohistochemistry and MGMT by methylation-specific PCR. INI1 was expressed in 83.1% of cases. The median overall survival (OS) was 13.6 months in INI1+ tumours and 7.2 months in INI1- tumours. 31.3% of patients with INI1+ tumours were alive compared with 15.4% of patients with INI1- tumours. MGMT methylation was detected in 31.2% of cases. OS was significantly different between patients with methylated tumours and un-methylated tumours (p < 0.04), and between patients with RT+ TMZ and RT alone (p < 0.001). Considering both treatment and MGMT, the difference in OS was significant (p < 0.002). The difference in OS according to MGMT and INI1 was significant (p < 0.04). The longest median OS was recorded among methylated and INI1+ tumours. Among un-methylated tumours, the median OS was 11.1 months in INI1+ and 6.5 months in INI1- tumours. No patients were alive with un-methylated and INI1- tumours. Loss of INI1 immunohistochemical expression in glioblastoma may be indicating an underlying molecular aberration accounting for the more aggressive clinical behaviour.