MGMT Promoter Methylation Status Research Articles

MGMT ProFWise: Unlocking a New Application for Combined Feature Selection and the Rank-Based Weighting Method to Link MGMT Methylation Status to Serum Protein Expression in Patients with Glioblastoma.

Glioblastoma (GBM) is a fatal brain tumor with limited treatment options. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is the central molecular biomarker linked to both the response to temozolomide, the standard chemotherapy drug employed for GBM, and to patient survival. However, MGMT status is captured on tumor tissue which, given the difficulty in acquisition, limits the use of this molecular feature for treatment monitoring. MGMT protein expression levels may offer additional insights into the mechanistic understanding of MGMT but, currently, they correlate poorly to promoter methylation. The difficulty of acquiring tumor tissue for MGMT testing drives the need for non-invasive methods to predict MGMT status. Feature selection aims to identify the most informative features to build accurate and interpretable prediction models. This study explores the new application of a combined feature selection (i.e., LASSO and mRMR) and the rank-based weighting method (i.e., MGMT ProFWise) to non-invasively link MGMT promoter methylation status and serum protein expression in patients with GBM. Our method provides promising results, reducing dimensionality (by more than 95%) when employed on two large-scale proteomic datasets (7k SomaScan® panel and CPTAC) for all our analyses. The computational results indicate that the proposed approach provides 14 shared serum biomarkers that may be helpful for diagnostic, prognostic, and/or predictive operations for GBM-related processes, given further validation.

CDPNet: a radiomic feature learning method with epigenetic application to estimating MGMT promoter methylation status in glioblastoma.

Radiomics has been widely recognized for its effectiveness in decoding tumor phenotypes through the extraction of quantitative imaging features. However, the robustness of radiomic methods to estimate clinically relevant biomarkers non-invasively remains largely untested. In this study, we propose Cascaded Data Processing Network (CDPNet), a radiomic feature learning method to predict tumor molecular status from medical images. We apply CDPNet to an epigenetic case, specifically targeting the estimation of O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation from Magnetic Resonance Imaging (MRI) scans of glioblastoma patients. CDPNet has three components: 1) Principal Component Analysis (PCA), 2) Fisher Linear Discriminant (FLD), and 3) a combination of hashing and blockwise histograms. The outlined architectural framework capitalizes on PCA to reconstruct input image patches, followed by FLD to extract discriminative filter banks, and finally using binary hashing and blockwise histogram module for indexing, pooling, and feature generation. To validate the effectiveness of CDPNet, we conducted an exhaustive evaluation on a comprehensive retrospective cohort comprising 484 IDH-wildtype glioblastoma patients with pre-operative multi-parametric MRI scans (T1, T1-Gd, T2, and T2-FLAIR). The prediction of MGMT promoter methylation status was cast as a binary classification problem. The developed model underwent rigorous training via 10-fold cross-validation on a discovery cohort of 446 patients. Subsequently, the model's performance was evaluated on a distinct and previously unseen replication cohort of 38 patients. Our method achieved an accuracy of 70.11% and an area under the curve of 0.71 (95% CI: 0.65 - 0.74).

MGMT Methylation and Differential Survival Impact by Sex in Glioblastoma.

Introduction: Sex differences in glioblastoma (GBM) have been observed in incidence, genetic and epigenetic alterations, and immune response. These differences have extended to the methylation of the MGMT promoter, which critically impacts temozolomide resistance. However, the association between sex, MGMT methylation, and survival is poorly understood, which this study sought to evaluate. Methods: A retrospective cohort study was conducted and reported following STROBE guidelines, based on adults with newly diagnosed GBM who received their first surgical intervention at Cleveland Clinic (Ohio, USA) between 2012 and 2018. Kaplan-Meier and multivariable Cox proportional hazards models were used to analyze the association between sex and MGMT promoter methylation status on overall survival (OS). MGMT was defined as methylated if the mean of CpG 1-5 ≥ 12. Propensity score matching was performed on a subset of patients to evaluate the effect of individual CpG site methylation. Results: A total of 464 patients had documented MGMT methylation status with a mean age of 63.4 (range 19-93) years. A total of 170 (36.6%) were female, and 133 (28.7%) received gross total resection as a first intervention. A total of 42.5% were MGMT methylated, with females more often having MGMT methylation than males (52.1% vs. 37.4%, p = 0.004). In univariable analysis, OS was significantly longer for MGMT promoter methylated than un-methylated groups for females (2 yr: 36.8% vs. 11.1%; median: 18.7 vs. 9.5 months; p = 0.001) but not for males (2 yr: 24.3% vs. 12.2%; median: 12.4 vs. 11.3 months; p = 0.22, p for MGMT-sex interaction = 0.02). In multivariable analysis, MGMT un-methylated versus methylated promoter females (2.07; 95% CI, 1.45-2.95; p < 0.0001) and males (1.51; 95% CI, 1.14-2.00; p = 0.004) had worse OS. Within the MGMT promoter methylated group, males had significantly worse OS than females (1.42; 95% CI: 1.01-1.99; p = 0.04). Amongst patients with data on MGMT CpG promoter site methylation values (n = 304), the median (IQR) of CpG mean methylation was 3.0% (2.0, 30.5). Females had greater mean CpG methylation than males (11.0 vs. 3.0, p < 0.002) and higher per-site CpG methylation with a significant difference at CPG 1, 2, and 4 (p < 0.008). After propensity score matching, females maintained a significant survival benefit (18.7 vs. 10.0 months, p = 0.004) compared to males (13.0 vs. 13.6 months, p = 0.76), and the pattern of difference was significant (P for CpG-sex interaction = 0.03). Conclusions: In this study, females had higher mean and individual CpG site methylation and received a greater PFS and OS benefit by MGMT methylation that was not seen in males despite equal degrees of CpG methylation.

Hypofractionated re-irradiation with bevacizumab for relapsed chemorefractory glioblastoma after prior high dose radiotherapy: a feasible option for patients with large-volume relapse.

There remains no standard of care for patients with recurrent and chemorefractory glioblastoma. Re-irradiation (reRT) provides an additional management option. However, published series predominantly focus on small reRT volumes utilizing stereotactic hypofractionated regimens. Concerns regarding toxicity have limited utilisation of reRT for larger recurrences, however this may be mitigated with use of bevacizumab (BEV). A prospective database of patients managed with the EORTC-NCIC (Stupp) protocol 60Gy chemoradiotherapy protocol for glioblastoma between 2007 and 2021 was reviewed for those patients receiving reRT for chemorefractory relapse. Serial MRI and PET were used to establish true progression and exclude patients with pseudoprogression or radionecrosis from reRT. The primary endpoint was overall survival (OS) from date of reRT. Prognostic factors were also assessed. 447 patients managed for glioblastoma under the Stupp protocol were identified, of which 372 had relapsed and were thus eligible for reRT. 71 patients underwent reRT. Median relapse-free survival from diagnosis for the reRT and overall cohorts were similar at 11.6 months (95%CI:9.4-14.2) and 11.8 months (95%CI:9.4-14.2) respectively. 60/71 (85%) reRT patients had received BEV prior to reRT and continued concurrent BEV during reRT. Of the 11 patients not managed with BEV during reRT, 10 required subsequent salvage BEV. ReRT patients were younger (median 53 vs. 59 years, p < 0.001), had better performance status (86% vs. 69% ECOG 0-1, p = 0.002) and more commonly had MGMT promoter-methylated tumours (54% vs. 40%, p = 0.083) compared to non-reRT patients. Median reRT PTV volume was 135cm3 (IQR: 69-207cm3). Median OS from reRT to death was 7.1 months (95%CI:6.3-7.9). Patients aged < 50, 50-70 and > 70 years had post-reRT median OS of 7.7, 6.4 and 6.0 months respectively (p = 0.021). Median post-reRT survival was longer for patients with ECOG performance status 0-1 compared to 2-3 (8.1 vs. 6.3 months, p = 0.039). PTV volume, site of relapse, MGMT promoter-methylation status and extent of initial surgical resection were not associated with post-reRT survival. ReRT was well-tolerated. Out of the 6 patients (8%) admitted to hospital after reRT, only one was for reRT toxicity. This was a CTCAE grade 3 radiation necrosis event in a patient managed without prior BEV. Patients with recurrent glioblastoma who have been previously treated with 60Gy radiotherapy have a meaningful survival benefit from large volume re-irradiation which is well tolerated. ReRT should not be ignored as a salvage treatment option in patients with chemorefractory progressive disease.

Adjuvant re-irradiation vs. no early re-irradiation of resected recurrent glioblastoma: pooled comparative cohort analysis from two tertiary centers.

The optimal management strategy for recurrent glioblastoma (rGBM) remains uncertain, and the impact of re-irradiation (Re-RT) on overall survival (OS) is still a matter of debate. This study included patients who achieved gross total resection (GTR) after a second surgery after recurrence, following the GlioCave criteria. Inclusion criteria include being 18 years or older, having histologically confirmed locally recurrent IDHwt or IDH unknown GBM, achieving MRI-proven GTR after the second surgery, having a Karnofsky performance status of at least 60% after the second surgery, having a minimum interval of 6 months between the first radiotherapy and the second surgery, and a maximum of 8 weeks from second surgery to the start of Re-RT. A total of 44 patients have met the inclusion criteria. The median OS after the second surgery was 14 months. All patients underwent standard treatment after initial diagnosis, including maximum safe resection, adjuvant radiochemotherapy and adjuvant chemotherapy. Re-RT did not significantly impact OS. However, MGMT promoter methylation status and a longer interval (> 12 months) between treatments were associated with better OS. Multivariate analysis revealed the MGMT status as the only significant predictor of OS. Factors such as MGMT promoter methylation status and treatment interval play crucial roles in determining patient outcomes after second surgery. Personalized treatment strategies should consider these factors to optimize the management of rGBM. Prospective research is needed to define the value of re-RT after second surgery and to inform decision making in this situation.

Abstract 6897: Defining critical features for successful preclinical use of glioblastoma patient-derived xenografts (PDX) models for therapeutic assessment and clinical trial development

Abstract Mayo Clinic has developed 111 GBM PDXs from newly diagnosed (72 PDX) and recurrent (39 PDX) patients. This large collection of PDXs provides a broad representation of genetic heterogeneity seen in patients. GBM PDXs that perform well in both in vitro and in vivo settings can be extensively utilized in the preclinical setting for downstream analysis. Based on 20 years of experience, we have defined the attributes that best enable preclinical use of our GBM PDX models. Among them are short-term in vitro culturing performance, large scale genomic evaluation data, benchmarked responses to standards of care, and median time to moribund for untreated orthotopic tumors. PDXs with prolonged survival timelines delay study readouts and, in some situations, confound efficacy results due to age-related animal decline. Setting median survival thresholds as part of the upfront experimental design allows for more timely study readouts that are unaffected by these confounding variables. Our preferred cutoff for the Mayo GBM PDX collection is 70 days median survival (n=64). Using this 64 PDX line panel, regimens expected to double survival would produce results within 4-5 months. This timeframe is well within the range of robust health for athymic nude mice. This 64-line collection features both newly diagnosed (nGBM; n=42) and recurrent (rGBM; n=22) tumors. MGMT promoter methylation status was determined by qMS-PCR (25 methylated, 37 unmethylated, 2 indeterminate). Available WES (n=62) and RNAseq (n=42) data, along with our tissue microarray (n=42), are critical resources for biomarker-based evaluations aimed at defining patient populations that are most likely to benefit from a given therapeutic. From these data, the molecular subtypes available include 26 classical, 14 proneural, and 3 mesenchymal. Twenty-seven of these 64 PDX models have also been successfully cultured from fresh as well as cryopreserved cell stocks to further expand their experimental value. Correlative clinical data including diagnosis and treatments are also available (n=61). Current standards of care for GBM include radiation, temozolomide, and bevacizumab. Defining sensitivity to these therapies is an important first step for evaluating the integration of novel therapeutics with these standards. Since the creation of our GBM PDX collection, efficacy of these therapies has been evaluated as follows: RT 26 PDXs, TMZ 20 PDXs, and Avastin 23 PDXs. The Mayo Clinic GBM PDX collection provides an important platform for preclinical evaluation of novel therapeutics. Through careful selection of PDX lines with favorable growth characteristics and known genetic features, researchers can select the most relevant models for their study. This approach will enable more meaningful preclinical work in the hopes of providing more tangible clinical benefits for GBM patients. Citation Format: Danielle M. Burgenske, Ann C. Mladek, Katrina K. Bakken, Zeng Hu, Brett L. Carlson, Paul A. Decker, Jeanette E. Eckel-Passow, Jann N. Sarkaria. Defining critical features for successful preclinical use of glioblastoma patient-derived xenografts (PDX) models for therapeutic assessment and clinical trial development [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 6897.

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&amp;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&amp;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&amp;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.

Abstract 5287: Ex vivo pharmacologic inhibition of STAT3 effectively targets tumor and tumor associated suppressor cells in high-grade glioma 3D spheroids

Abstract Gliomas, a type of brain tumor originating from glial cells, comprise a heterogenous group of neoplasms. High-grade gliomas, in particular, present significant therapeutic challenges in the clinic. Unlike other solid tumors, the heterogenous glioma microenvironment is heavily enriched with tumor associated suppressor cells including myeloid-derived suppressor cells (MDSCs) and tumor-associated macrophages (TAMs), which can account for 30-40% of the cellular composition1. These pro-tumorigenic myeloid cells are thought to contribute to the resistance of glioma to immunotherapy. Efforts to target the suppressive nature of these dominating cell types are in development to yield more therapeutic options for patients with these devastating diseases. Constitutive activation of STAT3 in gliomas has been associated with increased tumor progression and reduced immune response. We have observed in other cancer models that a phenotypic switch occurs from STAT3 pathway activation in 3D spheroid culture to STAT3 inactivation when cultured in 2D. Therefore, we sought to determine the role of STAT3 activation and its role in the interplay between glioma and their immune suppressive environment using a 3D spheroid model. We modified our commercially available test platform, 3D-Predict™ Glioma, such that it is conducive to monitoring immune cell function. Newly diagnosed treatment naive primary samples from HGG patients were dissociated and cryogenically preserved and banked. Samples were profiled for the abundance of tumor associated suppressive myeloid cells using flow cytometry. We determined that relative proportions of tumor suppressor cells were detectable and varied across HGG primary patient samples with TAMs being the predominate immune cell type identified. Pro-tumorigenic TAM markers including CD163 and CD206 were correlated with temozolomide response and were associated with poor patient prognosis. When we evaluated the role of p-STAT in HGG primary samples, p-STAT was detected at baseline and abundance was related back to the presence of tumor associated immune suppressor cells. The impact of STAT3 signaling blockade by the inhibitor WP1066 was determined ex vivo, and efficacy was related back to MGMT promotor methylation status and patient clinical outcome. We detected shifts in cytokine signatures following treatment of HGG 3D spheroid models with WP1066 which are known to target tumor associated suppressor cell functions. This work demonstrates the critical role suppressive immune cells play in HGG clinical response. Given p-STAT can be altered in 2D culture compared to 3D culture, ex vivo therapeutic response profiling of HGG samples is necessary using the more physiologically relevant spheroid culture model. 1.Hambardzumyan et al. The role of microglia and macrophages in glioma maintenance and progression. Nat. Neurosci. 19, 20-27 (2016). Citation Format: Katy A. Lassahn, Ashley K. Elrod, Teresa M. DesRochers, Kathryn M. Appleton. Ex vivo pharmacologic inhibition of STAT3 effectively targets tumor and tumor associated suppressor cells in high-grade glioma 3D spheroids [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 5287.

Prognosis of glioblastoma patients improves significantly over time interrogating historical controls

BackgroundGlioblastoma (GBM) is the most common devastating primary brain cancer in adults. In our clinical practice, median overall survival (mOS) of GBM patients seems increasing over time. MethodsTo address this observation, we have retrospectively analyzed the prognosis of 722 newly diagnosed GBM patients, aged below 70, in good clinical conditions (i.e. Karnofsky Performance Status –KPS- above 70%) and treated in our department according to the standard of care (SOC) between 2005 and 2018. Patients were divided into two groups according to the year of diagnosis (group 1: from 2005 to 2012; group 2: from 2013 to 2018). ResultsCharacteristics of patients and tumors of both groups were very similar regarding confounding factors (age, KPS, MGMT promoter methylation status and treatments). Follow-up time was fixed at 24 months to ensure comparable survival times between both groups. Group 1 patients had a mOS of 19 months ([17.3–21.3]) while mOS of group 2 patients was not reached. The recent period of diagnosis was significantly associated with a longer mOS in univariate analysis (HR=0.64, 95% CI [0.51 – 0.81]), p < 0.001). Multivariate Cox analysis showed that the period of diagnosis remained significantly prognostic after adjustment on confounding factors (adjusted Hazard Ratio (aHR) 0.49, 95% CI [0.36–0.67], p < 0.001). ConclusionThis increase of mOS over time in newly diagnosed GBM patients could be explained by better management of potentially associated non-neurological diseases, optimization of validated SOC, better management of treatments side effects, supportive care and participation in clinical trials.

Development of a rapid and comprehensive genomic profiling test supporting diagnosis and research for gliomas.

A prompt and reliable molecular diagnosis for brain tumors has become crucial in precision medicine. While Comprehensive Genomic Profiling (CGP) has become feasible, there remains room for enhancement in brain tumor diagnosis due to the partial lack of essential genes and limitations in broad copy number analysis. In addition, the long turnaround time of commercially available CGPs poses an additional obstacle to the timely implementation of results in clinics. To address these challenges, we developed a CGP encompassing 113 genes, genome-wide copy number changes, and MGMT promoter methylation. Our CGP incorporates not only diagnostic genes but also supplementary genes valuable for research. Our CGP enables us to simultaneous identification of mutations, gene fusions, focal and broad copy number alterations, and MGMT promoter methylation status, with results delivered within a minimum of 4days. Validation of our CGP, through comparisons with whole-genome sequencing, RNA sequencing, and pyrosequencing, has certified its accuracy and reliability. We applied our CGP for 23 consecutive cases of intracranial mass lesions, which demonstrated its efficacy in aiding diagnosis and prognostication. Our CGP offers a comprehensive and rapid molecular profiling for gliomas, which could potentially apply to clinical practices and research primarily in the field of brain tumors.

Improved prognostic stratification of patients with isocitrate dehydrogenase-mutant astrocytoma

Prognostic factors and standards of care for astrocytoma, isocitrate dehydrogenase (IDH)-mutant, CNS WHO grade 4, remain poorly defined. Here we sought to explore disease characteristics, prognostic markers, and outcome in patients with this newly defined tumor type. We determined molecular biomarkers and assembled clinical and outcome data in patients with IDH-mutant astrocytomas confirmed by central pathology review. Patients were identified in the German Glioma Network cohort study; additional cohorts of patients with CNS WHO grade 4 tumors were identified retrospectively at two sites. In total, 258 patients with IDH-mutant astrocytomas (114 CNS WHO grade 2, 73 CNS WHO grade 3, 71 CNS WHO grade 4) were studied. The median age at diagnosis was similar for all grades. Karnofsky performance status at diagnosis inversely correlated with CNS WHO grade (p < 0.001). Despite more intensive treatment upfront with higher grade, CNS WHO grade was strongly prognostic: median overall survival was not reached for grade 2 (median follow-up 10.4 years), 8.1 years (95% CI 5.4–10.8) for grade 3, and 4.7 years (95% CI 3.4–6.0) for grade 4. Among patients with CNS WHO grade 4 astrocytoma, median overall survival was 5.5 years (95% CI 4.3–6.7) without (n = 58) versus 1.8 years (95% CI 0–4.1) with (n = 12) homozygous CDKN2A deletion. Lower levels of global DNA methylation as detected by LINE-1 methylation analysis were strongly associated with CNS WHO grade 4 (p < 0.001) and poor outcome. MGMT promoter methylation status was not prognostic for overall survival. Histomolecular stratification based on CNS WHO grade, LINE-1 methylation level, and CDKN2A status revealed four subgroups of patients with significantly different outcomes. In conclusion, CNS WHO grade, global DNA methylation status, and CDKN2A homozygous deletion are prognostic in patients with IDH-mutant astrocytoma. Combination of these parameters allows for improved prediction of outcome. These data aid in designing upcoming trials using IDH inhibitors.

DCas9/CRISPR-based methylation of O-6-methylguanine-DNA methyltransferase enhances chemosensitivity to temozolomide in malignant glioma

BackgroundMalignant glioma carries a poor prognosis despite current therapeutic modalities. Standard of care therapy consists of surgical resection, fractionated radiotherapy concurrently administered with temozolomide (TMZ), a DNA-alkylating chemotherapeutic agent, followed by adjuvant TMZ. O-6-methylguanine-DNA methyltransferase (MGMT), a DNA repair enzyme, removes alkylated lesions from tumor DNA, thereby promoting chemoresistance. MGMT promoter methylation status predicts responsiveness to TMZ; patients harboring unmethylated MGMT (~60% of glioblastoma) have a poorer prognosis with limited treatment benefits from TMZ.MethodsVia lentiviral-mediated delivery into LN18 glioma cells, we employed deactivated Cas9-CRISPR technology to target the MGMT promoter and enhancer regions for methylation, as mediated by the catalytic domain of the methylation enzyme DNMT3A. Methylation patterns were examined at a clonal level in regions containing Differentially Methylation Regions (DMR1, DMR2) and the Methylation Specific PCR (MSP) region used for clinical assessment of MGMT methylation status. Correlative studies of genomic and transcriptomic effects of dCas9/CRISPR-based methylation were performed via Illumina 850K methylation array platform and bulk RNA-Seq analysis.ResultsWe used the dCas9/DNMT3A catalytic domain to achieve targeted MGMT methylation at specific CpG clusters in the vicinity of promoter, enhancer, DMRs and MSP regions. Consequently, we observed MGMT downregulation and enhanced glioma chemosensitivity in survival assays in vitro, with minimal off-target effects.ConclusiondCas9/CRISPR is a viable method of epigenetic editing, using the DNMT3A catalytic domain. This study provides initial proof-of-principle for CRISPR technology applications in malignant glioma, laying groundwork for subsequent translational studies, with implications for future epigenetic editing-based clinical applications.

Prediction of MGMT promotor methylation status in glioblastoma by contrast-enhanced T1-weighted intensity image.

The study aims to explore MRI phenotypes that predict glioblastoma's (GBM) methylation status of the promoter region of MGMT gene (pMGMT) by qualitatively assessing contrast-enhanced T1-weighted intensity images. A total of 193 histologically and molecularly confirmed GBMs at the Kansai Network for Molecular Diagnosis of Central Nervous Tumors (KANSAI) were used as an exploratory cohort. From the Cancer Imaging Archive/Cancer Genome Atlas (TCGA) 93 patients were used as validation cohorts. "Thickened structure" was defined as the solid tumor component presenting circumferential extension or occupying >50% of the tumor volume. "Methylated contrast phenotype" was defined as indistinct enhancing circumferential border, heterogenous enhancement, or nodular enhancement. Inter-rater agreement was assessed, followed by an investigation of the relationship between radiological findings and pMGMT methylation status. Fleiss's Kappa coefficient for "Thickened structure" was 0.68 for the exploratory and 0.55 for the validation cohort, and for "Methylated contrast phenotype," 0.30 and 0.39, respectively. The imaging feature, the presence of "Thickened structure" and absence of "Methylated contrast phenotype," was significantly predictive of pMGMT unmethylation both for the exploratory (p = .015, odds ratio = 2.44) and for the validation cohort (p = .006, odds ratio = 7.83). The sensitivities and specificities of the imaging feature, the presence of "Thickened structure," and the absence of "Methylated contrast phenotype" for predicting pMGMT unmethylation were 0.29 and 0.86 for the exploratory and 0.25 and 0.96 for the validation cohort. The present study showed that qualitative assessment of contrast-enhanced T1-weighted intensity images helps predict GBM's pMGMT methylation status.

10126-ACT-10 FACTORS AFFECTING THE PATTERN OF RECURRENCE OF IDH-WILDTYPE GLIOBLASTOMA

Abstract INTRODUCTION IDH-wildtype glioblastoma is a quite poor prognosis disease with which almost all cases recur in spite of postoperative radiation and chemotherapy. Survival rates are particularly low after dissemination. METHODS We included 120 patients with IDH-wild type glioblastoma treated at our hospital from January 2015 to December 2019. Patient backgrounds, MGMT promotor methylation status, imaging findings, and recurrence patterns were analyzed. Subependymal, subarachnoid, and spinal dissemination, plus distant metastasis, were defined as non-local recurrence. RESULTS Of 105 patients with a single lesion at diagnosis, 65 had local recurrence and 15 had non-local recurrence. 36 of 65 patients had local recurrence and 12 had non-local recurrence in the second recurrence. 17 of 36 patients had local recurrence and 8 had non-local recurrence in the third recurrence. The cumulative number of non-local recurrences was 54 (45.0%). Surgical ventricular opening and tumor proximity to the ventricles were associated with non-local recurrence (p=0.006, p=0.019). The patients with tumor proximity to the ventricle had non-local recurrence at the first recurrence and those with non-proximity to the ventricle had non-local recurrence at the second or later recurrence (p=0.038). MGMT promotor methylation status and postoperative ischemia were not significantly different from non-local recurrence (p=0.122, p=0.088), but MGMT promotor unmethylation was a risk factor for early non-local recurrence, especially within 1 year (p=0.033). Frontal lobe lesions were less frequently disseminated and more frequently MGMT promotor methylated (p=0.032, p=0.024). Parietal lobe lesions had more MGMT promotor methylation (p=0.006), and temporal lobe lesions had more dissemination (p=0.023). Distant metastasis commonly occurred from the frontal lobe to the ipsilateral or contralateral, and the frontal lobe was frequently associated. CONCLUSION IDH-wildtype glioblastoma is characterized by repeated local recurrence and cumulative non-local recurrence. The pattern of recurrence differs depending on the tumor localization, especially adjacent to ventricle, and MGMT promotor methylation status.

Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI

Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences. However, redundant information exists across sequences, which interferes with mining efficient representations by learning-based models. To handle various clinical scenarios, we propose a sequence-to-sequence generation framework (Seq2Seq) for imaging-differentiation representation learning. In this study, not only do we propose arbitrary 3D/4D sequence generation within one model to generate any specified target sequence, but also we are able to rank the importance of each sequence based on a new metric estimating the difficulty of a sequence being generated. Furthermore, we also exploit the generation inability of the model to extract regions that contain unique information for each sequence. We conduct extensive experiments using three datasets including a toy dataset of 20,000 simulated subjects, a brain MRI dataset of 1251 subjects, and a breast MRI dataset of 2101 subjects, to demonstrate that (1) top-ranking sequences can be used to replace complete sequences with non-inferior performance; (2) combining MRI with our imaging-differentiation map leads to better performance in clinical tasks such as glioblastoma MGMT promoter methylation status prediction and breast cancer pathological complete response status prediction. Our code is available at https://github.com/fiy2W/mri_seq2seq.

PATH-19. PROGNOSTIC FACTORS, RESPONSE TO TREATMENT, AND OUTCOME OF PATIENTS WITH ISOCITRATE DEHYDROGENASE (IDH)-MUTANT ASTROCYTOMA, CNS WHO GRADE 4

Abstract PURPOSE To study disease characteristics, prognostic markers and outcome in patients with isocitrate dehydrogenase (IDH)-mutant astrocytoma by CNS WHO grade. EXPERIMENTAL DESIGN We determined molecular biomarkers and assembled clinical and outcome data in a cohort of 258 patients with IDH-mutant astrocytomas (114 CNS WHO grade 2, 73 CNS WHO grade 3, 71 CNS WHO grade 4) confirmed by central pathology review. RESULTS The median age for astrocytoma, IDH mutant, CNS WHO grade 4, was 37 (range: 23-79 years) and similar to patients with CNS WHO grade 2 or 3 tumors. Karnofsky performance status at diagnosis inversely correlated with CNS WHO grade (p&amp;lt; 0.001). Despite more intensive treatment upfront with higher grade, CNS WHO grade was strongly prognostic: median overall survival was 22.2 years (95% n.a.) for grade 2, 8.1 years (95% 5.4-10.8) for grade 3 and 4.7 years (95% 3.4-6.0) for grade 4. Among patients with CNS WHO grade 4 astrocytoma, median overall survival was 5.5 years (95% 4.3-6.7) without (n=58) versus 1.8 years (95% 0-4.1) with (n=12) homozygous CDKN2A homozygous deletion. Reduced global DNA methylation as indicated by LINE-1 methylation levels was strongly associated with CNS WHO grade 4 (p&amp;lt; 0.001) and poor outcome among IDH-mutant astrocytoma patients. MGMT promoter methylation status was not prognostic for overall survival. CONCLUSIONS The CNS WHO grade is prognostic in patients with IDH-mutant astrocytoma. CDKN2A homozygous deletion and reduced LINE-1 methylation levels are linked to CNS WHO grade 4 and associate with shorter survival. These data serve to inform on clinical trial designs, e.g., using IDH inhibitors, in this patient population.

BIOM-17. WHOLE GAIN OF CHROMOSOME 19, NOT CO-GAIN OF CHROMOSOMES 19 AND 20, IS A FAVORABLE PROGNOSTIC BIOMARKER IN IDH-WILDTYPE GLIOBLASTOMA

Abstract BACKGROUND IDH-wildtype glioblastoma carries an abysmal prognosis, but long-term survivors exist. Previous studies have suggested that co-gain of chromosomes 19 and 20 (+19/+20) is a favorable prognostic marker. We sought to validate this claim and investigate whether gain of chromosome 19 (+19) is a superior prognostic indicator. METHODS We collected somatic copy number alteration data for primary glioblastoma tumors from TCGA (N = 356) and paired primary (N = 169) and recurrent (N = 167) glioblastoma tumors from GLASS. We assessed the frequency of these events and conducted survival analyses with univariate and multivariate Cox proportional hazard models to examine the association between +19/+20 and +19 and patient outcomes. RESULTS Among primary glioblastomas, the frequency of +19/+20 (20.8% vs. 23.7%) and +19 (34.6% vs. 36.7%) did not differ between TCGA and GLASS. However, the presence of +19/+20 was significantly reduced in GLASS recurrent tumors compared to primary tumors (14.3%, p = 0.04), while +19 without +19/+20 was unchanged (13.8%), indicating that +19/+20 is selected against in recurrent glioblastoma. Tumors harboring +19/+20 did not exhibit improved overall survival (OS) or progression-free survival (PFS) in TCGA (p = 0.21 and p = 0.14, respectively), nor did they demonstrate improved OS in GLASS (p = 0.32). Conversely, tumors with +19 showed significantly better OS and PFS in TCGA (HR = 1.4, p&amp;lt; 0.01; HR = 1.5, p&amp;lt; 0.01, respectively) and improved OS in GLASS (HR = 1.6, p&amp;lt; 0.01). In multivariate survival analyses, +19 remained a prognostic factor independent of +19/+20, patient sex, age, MGMT promoter methylation status, and KPS in TCGA (p&amp;lt; 0.05) and +19/+20 and age in GLASS (p = 0.01). CONCLUSION Although previous studies have suggested that +19/+20 is a positive prognostic biomarker in glioblastoma, our findings indicate that this assertion should be reevaluated. Our results demonstrate that +19 is associated with favorable outcomes in the TCGA and GLASS datasets, whereas +19/+20, while possibly selected against in recurrent glioblastomas, is not.

CTNI-66. DECODING GLIOBLASTOMA SURVIVAL: UNRAVELING THE PROGNOSTIC POTENTIAL OF OLFACTORY FUNCTION IN A PROSPECTIVE OBSERVATIONAL STUDY

Abstract BACKGROUND Olfactory impairment is a common neurologic deficit among glioblastoma patients. We have previously shown that glioblastoma patients with reduced smell sensitivity had lower overall survival rates compared to those with normal olfactory function. A notable limitation in that study was the unequal distribution of prognostic factors between the two groups, and the absence of continuous olfactory assessments during treatment to investigate if therapy-associated neurotoxicity could be a contributing factor to diminished olfactory acuity. Question: Can Olfactory Function Serve as an Independent Prognostic Indicator in Glioblastoma Patients? METHODS This prospective, multicenter study is set to recruit 64 glioblastoma patients alongside 64 healthy controls. Stratification of participants will be based on prognostically relevant variables such as resection status, MGMT promoter methylation status, radiographic involvement of olfactory brain areas, olfactory function, age, and Karnofsky performance status scale. We will utilize Sniffing Sticks to evaluate olfactory function through identification and threshold tests, and this assessment will be carried out longitudinally throughout the therapy starting from tumor diagnosis. Infiltration of the olfactory brain areas will be scrutinized using coronal T2 and T1 MRI sequences. MRI images will be independently reviewed by two board-certified radiologists from distinct institutions, who are blinded to the patients' olfactory function status. Furthermore, quality of life data, neuropsychological testing, and psychosomatic screening will be performed at specific intervals throughout the study. Also, we'll examine next-generation sequencing results to investigate potential genetic associations with hyposmia in glioblastoma patients. RESULTS The first participant was enrolled in May 2023. Plans are underway to open a second study site in 2024, with the aim to complete recruitment by December 2025. Follow-up assessments will continue until December 2027. We anticipate that the final results of the study will be available in 2028.

SURG-03. SURVIVAL STRATIFICATION OF IDH-WILDTYPE GLIOBLASTOMA IN THE MOLECULAR ERA: A RECURSIVE PARTITIONING ANALYSIS INCORPORATING EXTENT OF RESECTION OF CONTRAST-ENHANCING AND NON-ENHANCING TUMORS

Abstract METHODS This multicenter cohort study included a development cohort of 622 IDH-wildtype glioblastoma patients from a single institution (diagnosed between 2001 and 2021) and 445 patients as validation cohorts from two institutions. All patients completed radiotherapy plus concurrent temozolomide and had complete information on IDH mutation and MGMT promoter methylation status. EOR of CE and NE tumors were evaluated. A RPA analysis was performed on behalf of results of the Cox proportional hazards model. The RPA model was compared with a previous RTOG RPA model. RESULTS In the developmental cohort, older age (hazard ratio [HR] = 1.02, P &amp;lt; 0.001), MGMT methylation (HR = 0.51, P &amp;lt; 0.001), KPS (HR = 0.98, P &amp;lt; 0.001), and EOR of CE and NE tumors (GTR of CE tumor and non-GTR of NE tumor, HR = 1.82, P &amp;lt; 0.001; non-GTR of both CE and NE tumor, HR = 2.05, P &amp;lt; 0.001; reference group as GTR of both CE and NE tumor) were independent prognostic factors on multivariable analysis. The novel RPA consisting of age, MGMT methylation, KPS, and EOR of CE and NE tumors revealed greater separation of prognostic classes compared with the previous RTOG RPA model. The prognostic significance of the novel RPA model was subsequently confirmed in the validation cohorts. CONCLUSION The RPA model in IDH-wildtype glioblastoma patients incorporating EOR of CE and NE tumors is a valid model. This simple RPA model has the potential to contribute to improving the accurate assessment of prognostic groups in IDH-wildtype glioblastoma patients and to influence clinical decision-making.

NIMG-69. LEPTOMENINGEAL METASTASES IN IDH-WILDTYPE GLIOBLASTOMAS REVISITED: COMPREHENSIVE ANALYSIS OF INCIDENCE, RISK FACTORS, AND PROGNOSIS BASED ON POSTCONTRAST FLAIR IMAGING

Abstract BACKGROUND To comprehensively investigate the incidence, risk factors, and prognosis of leptomeningeal metastases (LM) in isocitrate dehydrogenase (IDH)-wildtype glioblastoma patients. METHODS Total 913 IDH-wildtype glioblastoma patients with complete molecular information on IDH mutation and MGMT promoter methylation status were enrolled between 2004 and 2022. LM diagnosis was performed with MRI including postcontrast FLAIR and CSF cytology. Logistic regression analysis for LM development at initial diagnosis and recurrence was performed with clinical, surgical, imaging, and molecular data. The overall survival (OS) was compared between patients with and without LM. RESULTS The incidence of LM was 21.8% (199 patients) among patients with IDH-wildtype glioblastoma, with 11.5% (105 patients) at initial diagnosis, and 10.3% (94 patients) at recurrence. Male sex (odds ratio [OR]: 1.74, P = 0.017), MGMT promoter unmethylation (OR: 1.48, P = 0.048), nonlobar location (OR: 2.27, P &amp;lt; 0.001), and presence of necrosis (OR: 3.64, P &amp;lt; 0.001) were independent predictors of LM at initial diagnosis, whereas ventricular opening during surgery (OR: 2.96, P &amp;lt; 0.001) was the only independent predictor of LM at recurrence. The median OS was 16.2 months (interquartile range [IQR]: 9.6-30.4) in patients with LM and 19.3 months (IQR: 12.1-38.5) in patients without LM (log-rank test; P = 0.001). CONCLUSION The incidence of LM is high in patients with IDH-wildtype glioblastoma. Aggressive clinical, imaging, and molecular factors are correlated with LM at initial diagnosis, whereas ventricular entry warrant imaging surveillance for LM at recurrence. The prognosis of LM is not discouraging as expected, and promote reconsideration of focused clinical trials.