MGMT Promoter Methylation as a Prognostic Factor in Primary Glioblastoma: A Single-Institution Observational Study

Canadian Expert Consensus Recommendations for the Diagnosis and Management of Glioblastoma: Results of a Delphi Study

Glioblastoma is the most common and aggressive malignant brain tumor in adults, with an increasing incidence and a poor prognosis. Current challenges in glioblastoma management include rapid tumor growth, limited treatment effectiveness, high recurrence rates, and a significant impact on patients' quality of life. Given the complexity of glioblastoma care and recent advancements in diagnostic and treatment modalities, updated guidelines are needed in Canada. This Delphi study aimed to develop Canadian consensus recommendations for the diagnosis, classification, and management of newly diagnosed and recurrent glioblastoma. A multidisciplinary panel of 14 Canadian experts in glioblastoma care was convened, and a comprehensive literature review was conducted to synthesize evidence and formulate initial recommendations. Consensus was achieved through three Delphi rounds, in which panelists rated their agreement with recommendation statements on a five-point Likert scale. Statements with ≥75% agreement were accepted, and others were revised for re-voting. Final recommendations were formulated based on the consensus level, strength of evidence, clinical expertise, and consideration of the Canadian healthcare context. These recommendations aim to standardize glioblastoma diagnosis and classification across Canada, provide evidence-based guidance for optimal treatment selection, integrate novel therapies, and enhance the overall quality of care for glioblastoma patients.

Imipridones ONC201/ONC206 + RT/TMZ triple (IRT) therapy reduces intracranial tumor burden, prolongs survival in orthotopic IDH-WT GBM mouse model, and suppresses MGMT

Glioblastoma remains a lethal brain tumor in adults with limited therapeutic options. TIC10/ONC201, a first-in-class imipridone we discovered, achieved meaningful therapeutic effects in phase I/II trials in patients with diffuse gliomas (DG's) harboring H3K27M mutations, and currently the drug is in randomized phase III testing (ACTION trial; NCT05580562). ONC201 targets mitochondrial protease ClpP to disrupt oxidative phosphorylation and trigger the integrated stress response (ISR), TRAIL/DR5, and tumor cell death. While ONC201 and its analog ONC206 are undergoing clinical trials as single agents, there is limited information on their interactions with stand-of-care therapy. We show that ONC201 and ONC206 synergize with temozolomide (TMZ) and Radiotherapy (RT). ONC201 enhances TMZ- or RT-induced apoptosis, ISR and cytotoxicity. ClpP-silencing suppresses ONC201-induced cytotoxicity but not TMZ. Both ONC201 and ONC206 reduce expression of TMZ-resistance mediator MGMT observed in H3K27M-mutated DG cells following treatment with imipridones+TMZ. Cytokine profiling indicates distinct effects of ONC201 relative to TMZ treatment. These results suggest mechanisms underlying ONC201's anti-tumoral activity are distinct from those associated with TMZ or RT with potential for synergy between these three treatments. Triple ONC201+RT+TMZ (IRT) therapy prolonged median survival to 123 days with tail on survival curve (3-of-7 mice alive beyond 200-days) in orthotopic U251 GBM model versus ONC201 (44-days; p = 0.000197), RT (63-days; p = 0.0012), TMZ (78-days; p = 0.0354), ONC201+RT (55-days; p = 0.0004), ONC201+TMZ (80-days; p = 0.0041) and RT+TMZ (103-days; p > 0.05). By 231-days, the only surviving mice were in IRT group. Our results support investigation of ONC201/ONC206 in combination with RT/TMZ (IRT) in GBM or H3K27M mutated DG therapy.

LB-100 Enhances Drugs Efficacy Through Inhibition of P-Glycoprotein Expression in Multidrug-Resistant Glioblastoma and Non-Small Cell Lung Carcinoma Cellular Models

Background/Objectives: This study explores the potential of LB-100 (a protein phosphatase 2A-PP2A inhibitor) combined with adavosertib (a WEE1 kinase inhibitor) and doxorubicin (DOX), to overcome multidrug resistance (MDR) in cancer cells and enhance treatment efficacy. Methods: We evaluated LB-100 combinations with adavosertib and DOX in patient-derived glioblastoma and non-small cell lung carcinoma cells (NSCLCs) using a real-time cell analyzer. Effectiveness was also assessed through immunofluorescence assay, and interactions were analyzed via SynergyFinder+. We also examined P-glycoprotein (P-gp) expression and drug resistance genes' expression in MDR glioblastoma and NSCLCs after LB-100 treatment, as well as LB-100 sensitizing effect on DOX and DOX accumulation. Results: LB-100 significantly boosts the effectiveness of adavosertib and DOX after multiple applications. It also enhances these drugs' cytotoxicity in a single application without acting synergistically. Additionally, LB-100 reduces P-gp expression in MDR glioblastoma and NSCLCs, sensitizing them to DOX and increasing its accumulation. Conclusions: LB-100 enhances the effectiveness of drugs against MDR cancer cells, presenting a promising strategy to overcome drug resistance in glioblastoma and NSCLCs through P-gp modulation.

Validating a clinically based MS-MLPA threshold through comparison with Sanger sequencing in glioblastoma patients

BACKGROUND

Glioblastoma is the commonest malignant brain tumor and has a very poor prognosis. Reduced expression of the MGMT gene (10q26.3), influenced primarily by the methylation of two differentially methylated regions (DMR1 and DMR2), is associated with a good response to temozolomide treatment. However, suitable methods for detecting the methylation of the MGMT gene promoter and setting appropriate cutoff values are debated.

RESULTS

A cohort of 108 patients with histologically and genetically defined glioblastoma was retrospectively examined with methylation-specific Sanger sequencing (sSeq) and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) methods. The DMR2 region was methylated in 29% of samples, whereas DMR1 was methylated in 12% of samples. Methylation detected with the MS-MLPA method using probes MGMT_215, MGMT_190, and MGMT_124 from the ME012-A1 kit (located in DMR1 and DMR2) correlated with the methylation of the corresponding CpG dinucleotides detected with sSeq (p = 0.005 for probe MGMT_215; p < 0.001 for probe MGMT_190; p = 0.016 for probe MGMT_124). The threshold for methylation detection with the MS-MLPA method was calculated with a ROC curve analysis and principal components analysis of the data obtained with the MS-MLPA and sSeq methods, yielding a weighted value of 0.362. Thus, methylation of the MGMT gene promoter was confirmed in 36% of samples. These patients had statistically significantly better overall survival (p = 0.003).

CONCLUSIONS

Our results show that the threshold for methylation detection with the MS-MLPA method determined here is useful from a diagnostic perspective because it allows the stratification of patients who will benefit from specific treatment protocols, including temozolomide. Detailed analysis of the MGMT gene promoter enables the more-precise and personalized treatment of patients with glioblastoma.

Quality assessment of critical and non-critical domains of systematic reviews on artificial intelligence in gliomas using AMSTAR II: A systematic review

INTRODUCTION

Gliomas are the most common primary malignant intraparenchymal brain tumors with a dismal prognosis. With growing advances in artificial intelligence, machine learning and deep learning models are being utilized for preoperative, intraoperative and postoperative neurological decision-making. We aimed to compile published literature in one format and evaluate the quality of level 1a evidence currently available.

METHODOLOGY

Using PRISMA guidelines, a comprehensive literature search was conducted within databases including Medline, Scopus, and Cochrane Library, and records with the application of artificial intelligence in glioma management were included. The AMSTAR 2 tool was used to assess the quality of systematic reviews and meta-analyses by two independent researchers.

RESULTS

From 812 studies, 23 studies were included. AMSTAR II appraised most reviews as either low or critically low in quality. Most reviews failed to deliver in critical domains related to the exclusion of studies, appropriateness of meta-analytical methods, and assessment of publication bias. Similarly, compliance was lowest in non-critical areas related to study design selection and the disclosure of funding sources in individual records. Evidence is moderate to low in quality in reviews on multiple neuro-oncological applications, low quality in glioma diagnosis and individual molecular markers like MGMT promoter methylation status, IDH, and 1p19q identification, and critically low in tumor segmentation, glioma grading, and multiple molecular markers identification.

CONCLUSION

AMSTAR 2 is a robust tool to identify high-quality systematic reviews. There is a paucity of high-quality systematic reviews on the utility of artificial intelligence in glioma management, with some demonstrating critically low quality. Therefore, caution must be exercised when drawing inferences from these results.

Detection of O6-methylguanine-DNA methyltransferase gene methylation status in IDH-wild type glioblastomas using methylation-specific qPCR: a first report from Morocco

We tried, through this work, to highlight the first detection of the methylation status of the O6-methylguanine-DNA methyltransferase gene (MGMT) promoter in IDH-wild-type glioblastomas with observation of the expression of IDH1, ATRX, and P53 by immunohistochemistry. Across eight formalin-fixed, paraffin-embedded tissue blocks (FFPE) from glioblastoma patients, we collected tumor tissue samples. We examined the methylation status of the MGMT gene promoter using a real-time methylation-specific PCR technique (MS-qPCR). In addition, we observed the molecular alterations caused by mutations in IDH1, ATRX, and p53 using immunohistochemistry (IHC). All cases studied had a wild-type form of IDH1, loss of ATRX expression was observed in five samples. In two cases, the mutated form of p53 was expressed. The level of p53 expression ranged from intense (>80% of tumor cells) to weak (>10% of tumor cells), and less than 10% labeling was considered negative. In our study, when analyzing the methylation profiles of the MGMT gene promoter, we found that two cases, specifically sample 2 and sample 5, exhibited positive methylation. Sample 2 had a methylation rate of 6.8%, while sample 5 showed a methylation rate of 27%. In contrast, sample 6 had a methylation rate of 0.05%, which fell below the established methylation cutoff point of 0.6%. Therefore, sample 6 was considered negatively methylated because its methylation rate was significantly lower than the established threshold. This study identifies MGMT promoter methylation in a subset of glioblastomas IDH-wild-type. These findings highlight the molecular diversity of glioblastomas and suggest potential targets for tailored therapeutic strategies.

Novel tri-specific T-cell engager targeting IL-13Rα2 and EGFRvIII provides long-term survival in heterogeneous GBM challenge and promotes antitumor cytotoxicity with patient immune cells

BACKGROUND

Glioblastoma multiforme (GBM) is known for its high antigenic heterogeneity, which undermines the effectiveness of monospecific immunotherapies. Multivalent immunotherapeutic strategies that target multiple tumor antigens simultaneously could enhance clinical outcomes by preventing antigen-driven tumor escape mechanisms.

METHODS

We describe novel trivalent antibodies, DNA-encoded tri-specific T-cell engagers (DTriTEs), targeting two GBM antigens, epidermal growth factor receptor variant III (EGFRvIII) and IL-13Rα2, and engaging T cells through CD3. We engineered three DTriTE constructs, each with a unique arrangement of the antigen-binding fragments within a single-chain sequence. We assessed the binding efficiency and cytotoxic activity of these DTriTEs in vitro on target cells expressing relevant antigens. In vivo efficacy was tested in immunocompromised mice, including a longitudinal expression study post-administration and a survival analysis in an NOD scid gamma (NSG)-K mouse model under a heterogeneous tumor burden. RNA sequencing of DTriTE-activated T cells was employed to identify the molecular pathways influenced by the treatment. The antitumor cytotoxicity of patient-derived immune cells was evaluated following stimulation by DTriTE to assess its potential effectiveness in a clinical setting.

RESULTS

All DTriTE constructs demonstrated strong binding to EGFRvIII and IL-13Rα2-expressing cells, induced significant T cell-mediated cytotoxicity, and enhanced cytokine production (interferon-γ, tumor necrosis factor (TNF)-α, and interleukin(IL)-2). The lead construct, DT2035, sustained expression for over 105 days in vivo and exhibited elimination of tumor burden in a heterogeneous intracranial GBM model, outperforming monospecific antibody controls. In extended survival studies using the NSG-K model, DT2035 achieved a 67% survival rate over 120 days. RNA sequencing of DTriTE-activated T cells showed that DT2035 enhances genes linked to cytotoxicity, proliferation, and immunomodulation, reflecting potent immune activation. Finally, DT2035 effectively induced target-specific cytotoxicity in post-treatment peripheral blood mononuclear cells from patients with GBM, highlighting its potential for clinical effectiveness.

CONCLUSIONS

DTriTEs exhibit potent anti-tumor effects and durable in vivo activity, offering promising therapeutic potential against GBM. These findings support further development of such multivalent therapeutic strategies to improve treatment outcomes in GBM and potentially other antigenically heterogeneous tumors. The opportunity to advance such important therapies either through biologic delivery or direct in vivo nucleic acid production is compelling.

Updates for newly diagnosed and recurrent glioblastoma: a review of recent clinical trials

PURPOSE OF REVIEW

Glioblastoma (GBM) is the most common and devastating primary malignant brain tumor. We summarize recent advances in radiotherapy, immunotherapy, and targeted therapy approaches for the treatment of newly diagnosed and recurrent glioblastoma. We also introduce ongoing clinical trials.

RECENT FINDINGS

Recent clinical trials have explored multiple novel strategies to treat GBM including the use of oncoviruses, chimeric antigen receptor (CAR) T cell therapy, vaccines, radiotherapy, and novel drug delivery techniques to improves drug penetrance across the blood brain barrier. Approaches to improve drug delivery to brain tumors have the potential to expand treatment options of existing therapies that otherwise have poor brain tumor penetrance. Immunotherapy has been of keen interest in both newly diagnosed and recurrent glioblastoma. Vaccines SurVaxM and DCVax-L have shown initial promise in phase II and III trials, respectively. CAR T cell therapy trials are in their early phases but hold promise in both newly diagnosed and recurrent glioblastoma.

SUMMARY

Although progress to improve outcomes for GBM patients has been modest, multiple novel strategies utilizing combination therapies, focused ultrasound to improve drug delivery, and novel immunotherapies are underway.

Diagnostics and Therapy for Malignant Tumors

Malignant tumors remain one of the most significant global health challenges and contribute to high mortality rates across various cancer types. The complex nature of these tumors requires multifaceted diagnostic and therapeutic approaches. This review explores current advancements in diagnostic methods, including molecular imaging, biomarkers, and liquid biopsies. It also delves into the evolution of therapeutic strategies, including surgery, chemotherapy, radiation therapy, and novel targeted therapies such as immunotherapy and gene therapy. Although significant progress has been made in the understanding of cancer biology, the future of oncology lies in the integration of precision medicine, improved diagnostic tools, and personalized therapeutic approaches that address tumor heterogeneity. This review aims to provide a comprehensive overview of the current state of cancer diagnostics and treatments while highlighting emerging trends and challenges that lie ahead.

Multimodal MRI and 1H-MRS for Preoperative Stratification of High-Risk Molecular Subtype in Adult-Type Diffuse Gliomas

Isocitrate dehydrogenase (IDH) and O6-methylguanine-DNA methyltransferase (MGMT) genes are critical molecular markers in determining treatment options and predicting the prognosis of adult-type diffuse gliomas. Objectives: this study aimed to investigate whether multimodal MRI enables the differentiation of genotypes in adult-type diffuse gliomas. Methods: a total of 116 adult-type diffuse glioma patients (61 males, 51.5 (37, 62) years old) who underwent multimodal MRI before surgery were retrospectively analysed. Multimodal MRI included conventional MRI, proton magnetic resonance spectroscopy (1H-MRS), and diffusion tensor imaging (DTI). Conventional visual features, N-acetyl-aspartate (NAA)/Creatine (Cr), Choline (Cho)/Cr, Cho/NAA, fractional anisotropy (FA), mean diffusivity (MD), and diffusion histogram parameters were extracted on the whole tumour. Multimodal MRI parameters of IDH-mutant and IDH-wildtype gliomas were compared using the Mann-Whitney U test, Student's t-test, or Pearson chi-square tests. Logistic regression was used to select the MRI parameters to predict IDH-mutant gliomas. Furthermore, multimodal MRI parameters were selected to establish models for predicting MGMT methylation in the IDH-wildtype gliomas. The performance of models was evaluated by the receiver operating characteristics curve. Results: a total of 56 patients with IDH-mutant gliomas and 60 patients with IDH-wildtype glioblastomas (GBM) (37 with methylated MGMT and 17 with unmethylated MGMT) were diagnosed by 2021 WHO classification criteria. The enhancement degree (OR = 4.298, p < 0.001), necrosis/cyst (OR = 5.381, p = 0.011), NAA/Cr (OR = 0.497, p = 0.037), FA-Skewness (OR = 0.497, p = 0.033), MD-Skewness (OR = 1.849, p = 0.035), FAmean (OR = 1.924, p = 0.049) were independent factors for the multimodal combined prediction model in predicting IDH-mutant gliomas. The combined modal based on conventional MRI, 1H-MRS, DTI parameters, and histogram performed best in predicting IDH-wildtype status (AUC = 0.890). However, only NAA/Cr (OR = 0.17, p = 0.043) and FA (OR = 0.38, p = 0.015) were associated with MGMT methylated in IDH-wildtype GBM. The combination of NAA/Cr and FA-Median is more accurate for predicting MGMT methylation levels than using these elements alone (AUC, 0.847 vs. 0.695/0.684). Conclusions: multimodal MRI based on conventional MRI, 1H-MRS, and DTI can provide compound imaging markers for stratified individual diagnosis of IDH mutant and MGMT promoter methylation in adult-type diffuse gliomas.

The mutated in colorectal cancer (MCC) gene can serve as a potential biomarker of glioblastoma

Introduction

The mutated in colorectal cancer (MCC) gene was initially identified as a candidate tumor suppressor gene in colorectal cancer, acting as a negative regulator of cell cycle progression. However, its functional roles in brain tumors, particularly glioblastoma, remain largely unexplored. This study reveals a significant association between MCC status and glioblastoma.

Methods

We explored MCC expression in the glioblastoma database, patient samples, and cell lines. We investigated the proliferation and migration of the cell lines in MCC gene knockdown using small interfering RNA.

Results

In vitro analyses revealed elevated protein and mRNA levels of MCC in several glioblastoma cell lines (U118MG and T98G). Silencing MCC expression via siRNA-mediated knockdown resulted in increased proliferation and migration of these cell lines. Supporting these findings, analyses of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases confirmed higher MCC expression in glioblastoma tumors than in normal brain tissue. Importantly, we observed that high MCC expression was associated with poor prognosis in glioblastoma patients, highlighting its potential role in disease progression. Additionally, this study identifies a nuclear localization of MCC in the glioblastoma cell line.

Discussion

These findings indicate that MCC expression is significantly upregulated in glioblastoma and may play a role in its pathophysiology, warranting further investigation.

Transfer Learning in Cancer Genetics, Mutation Detection, Gene Expression Analysis, and Syndrome Recognition

Artificial intelligence (AI), encompassing machine learning (ML) and deep learning (DL), has revolutionized medical research, facilitating advancements in drug discovery and cancer diagnosis. ML identifies patterns in data, while DL employs neural networks for intricate processing. Predictive modeling challenges, such as data labeling, are addressed by transfer learning (TL), leveraging pre-existing models for faster training. TL shows potential in genetic research, improving tasks like gene expression analysis, mutation detection, genetic syndrome recognition, and genotype-phenotype association. This review explores the role of TL in overcoming challenges in mutation detection, genetic syndrome detection, gene expression, or phenotype-genotype association. TL has shown effectiveness in various aspects of genetic research. TL enhances the accuracy and efficiency of mutation detection, aiding in the identification of genetic abnormalities. TL can improve the diagnostic accuracy of syndrome-related genetic patterns. Moreover, TL plays a crucial role in gene expression analysis in order to accurately predict gene expression levels and their interactions. Additionally, TL enhances phenotype-genotype association studies by leveraging pre-trained models. In conclusion, TL enhances AI efficiency by improving mutation prediction, gene expression analysis, and genetic syndrome detection. Future studies should focus on increasing domain similarities, expanding databases, and incorporating clinical data for better predictions.

Genetic Prognostic Factors in Adult Diffuse Gliomas: A 10-Year Experience at a Single Institution

Gliomas are primary brain lesions involving cerebral structures without well-defined boundaries and constitute the most prevalent central nervous system (CNS) neoplasms. Among gliomas, glioblastoma (GB) is a glioma of the highest grade and is associated with a grim prognosis. We examined how clinical variables and molecular profiles may have affected overall survival (OS) over the past ten years. A retrospective study was conducted at Sina Hospital in Tehran, Iran and examined patients with confirmed glioma diagnoses between 2012 and 2020. We evaluated the correlation between OS in GB patients and sociodemographic as well as clinical factors and molecular profiling based on IDH1, O-6-Methylguanine-DNA Methyltransferase (MGMT), TERTp, and epidermal growth factor receptor (EGFR) amplification (EGFR-amp) status. Kaplan-Meier and multivariate Cox regression models were used to assess patient survival. A total of 178 patients were enrolled in the study. The median OS was 20 months, with a 2-year survival rate of 61.0%. Among the 127 patients with available IDH measurements, 100 (78.7%) exhibited mutated IDH1 (IDH1-mut) tumors. Of the 127 patients with assessed MGMT promoter methylation (MGMTp-met), 89 (70.1%) had MGMT methylated tumors. Mutant TERTp (TERTp-mut) was detected in 20 out of 127 cases (15.7%), while wildtype TERTp (wildtype TERTp-wt) was observed in 107 cases (84.3%). Analyses using multivariable models revealed that age at histological grade (p < 0.0001), adjuvant radiotherapy (p < 0.018), IDH1 status (p < 0.043), and TERT-p status (p < 0.014) were independently associated with OS. Our study demonstrates that patients with higher tumor histological grades who had received adjuvant radiotherapy exhibited IDH1-mut or presented with TERTp-wt experienced improved OS. Besides, an interesting finding showed an association between methylation of MGMTp and TERTp status with tumor location.

Effect of radiochemotherapy on peripheral immune response in glioblastoma

BACKGROUND

Glioblastoma (GBM) is a primary brain tumor with a dismal prognosis, often resistant to immunotherapy and associated with immune suppression. This study aimed to assess the impact of steroids and Stupp-regimen treatment on peripheral blood immune parameters in GBM patients and their association with outcomes.

METHODS

Using cytometry panels and bioplex assays, we analyzed the immune phenotype and serum cytokines of 54 GBM patients and 21 healthy volunteers.

RESULTS

GBM patients exhibited decreased lymphoid cell numbers (CD4, CD8 T cells, NKT cells) with heightened immune checkpoint expression and increased myeloid cell numbers (especially neutrophils), along with elevated pro-inflammatory cytokine levels. Steroid use decreased T and NK cell numbers, while radio-chemotherapy led to decreased lymphoid cell numbers, increased myeloid cell numbers, and heightened immune checkpoint expression. Certain immune cell subsets were identified as potential outcome predictors.

CONCLUSION

Overall, these findings shed light on the peripheral immune landscape in GBM, emphasizing the immunosuppressive effects of treatment. Baseline immune parameters may serve as prognostic indicators for treatment response.

Expression of molecular markers and synergistic anticancer effects of chemotherapy with antimicrobial peptides on glioblastoma cells

OBJECTIVE

Glioblastoma multiforme (GBM) is the most aggressive and fatal malignant primary brain tumor. The enhancement of the survival rate for glioma patients remains limited, even with the utilization of a combined treatment approach involving surgery, radiotherapy, and chemotherapy. This study was designed to assess the expression of IDH1, TP53, EGFR, Ki-67, GFAP, H3K27M, MGMT, VEGF, NOS, CD99, and ATRX in glioblastoma tissue from 11 patients. We investigated the anticancer impact and combined effects of cathelicidin (LL-37), protegrin-1 (PG-1), with chemotherapy-temozolomide (TMZ), doxorubicin (DOX), carboplatin (CB), cisplatin (CPL), and etoposide (ETO) in primary GBM cells. In addition, we examined the effect of LL-37, PG-1 on normal human fibroblasts and in the C6/Wistar rat intracerebral glioma model.

METHODS

For this study, 11 cases of glioblastoma were evaluated immunohistochemically for IDH1, TP53, EGFR, Ki-67, GFAP, H3K27M, MGMT, VEGF, NOS, CD99, and ATRX. The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay was used to study cells viability and to determine cytotoxic effects of LL-37, PG-1 and their combination with chemotherapy in primary GBM cells. Synergism or antagonism was determined using combination index (CI) method. Finally, we established C6 glioblastoma model in Wistar rats to investigate the antitumor activity.

RESULTS

Peptides showed a strong cytotoxic effect on primary GBM cells in the MTT test (IC50 2-16 and 1-32 μM) compared to chemotherapy. The dual-drug combinations of LL-37 + DOX, LL-37 + CB (CI 0.46-0.75) and PG-1 + DOX, PG-1 + CB, PG-1 + TMZ (CI 0.11-0.77), demonstrated a synergism in primary GBM cells. In rat C6 intracerebral GBM model, survival of rats in experimental group (66.75 ± 12.6 days) was prolonged compared with that in control cohort (26.2 ± 2.66 days, p = 0.0008). After LL-37 treatment, experimental group rats showed significantly lower tumor volumes (31.00 ± 8.8 mm3) and weight (49.4 ± 13.3 mg) compared with control group rats (153.8 ± 43.53 mg, p = 0.038; 82.50 ± 7.60 mm3, respectively).

CONCLUSIONS

The combination of antimicrobial peptides and chemical drugs enhances the cytotoxicity of chemotherapy and exerts synergistic antitumor effects in primary GBM cells. Moreover, in vivo study provided the first evidence that LL-37 could effectively inhibit brain tumor growth in rat C6 intracerebral GBM model. These results suggested a significant strategy for proposing a promising therapy for the treatment of GBM.

Principles in the Management of Glioblastoma

Glioblastoma, the most aggressive and common malignant primary brain tumour, is characterized by infiltrative growth, abundant vascularization, and aggressive clinical evolution. Patients with glioblastoma often face poor prognoses, with a median survival of approximately 15 months. Technological progress and the subsequent improvement in understanding the pathophysiology of these tumours have not translated into significant achievements in therapies or survival outcomes for patients. Progress in molecular profiling has yielded new omics data for a more refined classification of glioblastoma. Several typical genetic and epigenetic alterations in glioblastoma include mutations in genes regulating receptor tyrosine kinase (RTK)/rat sarcoma (RAS)/phosphoinositide 3-kinase (PI3K), p53, and retinoblastoma protein (RB) signalling, as well as mutation of isocitrate dehydrogenase (IDH), methylation of O6-methylguanine-DNA methyltransferase (MGMT), amplification of epidermal growth factor receptor vIII, and codeletion of 1p/19q. Certain microRNAs, such as miR-10b and miR-21, have also been identified as prognostic biomarkers. Effective treatment options for glioblastoma are limited. Surgery, radiotherapy, and alkylating agent chemotherapy remain the primary pillars of treatment. Only promoter methylation of the gene MGMT predicts the benefit from alkylating chemotherapy with temozolomide and it guides the choice of first-line treatment in elderly patients. Several targeted strategies based on tumour-intrinsic dominant signalling pathways and antigenic tumour profiles are under investigation in clinical trials. This review explores the potential genetic and epigenetic biomarkers that could be deployed as analytical tools in the diagnosis and prognostication of glioblastoma. Recent clinical advancements in treating glioblastoma are also discussed, along with the potential of liquid biopsies to advance personalized medicine in the field of glioblastoma, highlighting the challenges and promises for the future.

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.

Mean global DNA methylation serves as independent prognostic marker in IDH-wildtype glioblastoma

BACKGROUND

The IDH-wildtype glioblastoma (GBM) patients have a devastating prognosis. Here, we analyzed the potential prognostic value of global DNA methylation of the tumors.

METHODS

DNA methylation of 492 primary samples and 31 relapsed samples, each treated with combination therapy, and of 148 primary samples treated with radiation alone were compared with patient survival. We determined the mean methylation values and estimated the immune cell infiltration from the methylation data. Moreover, the mean global DNA methylation of 23 GBM cell lines was profiled and correlated to their cellular radiosensitivity as measured by colony formation assay.

RESULTS

High mean DNA methylation levels correlated with improved survival, which was independent from known risk factors (MGMT promoter methylation, age, extent of resection; P = 0.009) and methylation subgroups. Notably, this correlation was also independent of immune cell infiltration, as higher number of immune cells indeed was associated with significantly better OS but lower mean methylation. Radiosensitive GBM cell lines had a significantly higher mean methylation than resistant lines (P = 0.007), and improved OS of patients treated with radiotherapy alone was also associated with higher DNA methylation (P = 0.002). Furthermore, specimens of relapsed GBM revealed a significantly lower mean DNA methylation compared to the matching primary tumor samples (P = 0.041).

CONCLUSIONS

Our results indicate that mean global DNA methylation is independently associated with outcome in glioblastoma. The data also suggest that a higher DNA methylation is associated with better radiotherapy response and less aggressive phenotype, both of which presumably contribute to the observed correlation with OS.

Prognostic value of brain perfusion by MRI in the initial study of high grade gliomas

OBJECTIVES

To evaluate if the tumour perfusion at the initial MRI scan is a marker of prognosis for survival in patients diagnosed with High Grade Gliomas (HGG). To analyse the risk factors which influence on the mortality from HGG to quantify the overall survival to be expected in patients.

PATIENTS AND METHODS

The patients diagnosed with HGG through a MRI scan in a third-level hospital between 2017 and 2019 were selected. Clinical and tumour variables were collected. The survival analysis was used to determine the association between the tumour perfusion and the survival time. The relation between the collected variables and the survival period was assessed through Wald's statistical method, measuring the relationship via Cox's regression model. Finally, the type of relationship that exists between the tumour perfusion and the survival was analysed through the Lineal Regression method.Those statistical analysis were carried out using the software SPSS v.17.

RESULTS

38 patients were included (average age: 61.1 years old). The general average survival period was 20.6 months. A relationship between the tumour perfusion at the MRI scan and the overall survival has been identified, in detail, a group with intratumor values of relative cerebral blood volume (rCBV)>3.0 has shown a significant decline in the average survival period with regard to the average survival period of the group with values <3.0 (14.6 months vs. 22.8 months, p = 0.046). It has also been proved that variables like Karnofsky's scale and the response time since the intervention significantly influence on the survival period.

CONCLUSIONS

It has become evident that the tumour perfusion via MRI scan has a prognostic value in the initial analysis of HGG. The average survival period of patients with rCBV less than or equal to 3.0 is significantly higher than those patients whose values are higher, which allows to be more precise with the prognosis of each patient.

Postoperative NEOadjuvant TEMozolomide followed by chemoradiotherapy versus upfront chemoradiotherapy for glioblastoma multiforme (NEOTEM) trial: Interim results

Background

Glioblastoma multiforme (GBM) is an aggressive brain tumor with poor survival rates despite current treatments. The standard of care (SOC) includes surgery, followed by radiotherapy plus concurrent and adjuvant chemotherapy with temozolomide (TMZ). This phase II trial assessed the safety and efficacy of neoadjuvant TMZ (nTMZ) before and during chemoradiotherapy in newly diagnosed GBM patients.

Methods

Newly diagnosed GBM patients who underwent maximal safe resection were randomized into 2 groups. One received nTMZ before standard chemoradiotherapy and adjuvant TMZ (intervention). The other received standard chemoradiotherapy followed by adjuvant TMZ (control). Primary endpoints were progression-free survival (PFS) at 6 and 12 months. Secondary endpoints included overall survival, radiological and clinical responses, and adverse events.

Results

Of 35 patients, 16 were in the intervention group and 19 in the control group. Median PFS was 9 months (95% CI: 3.93-14.06) versus 3 months (95% confidence interval [CI]: 1.98-4.01) in the control and intervention groups (P = .737), with a high progression rate (73.4%) during nTMZ treatment. The 6-month PFS rates were 58% versus 25% (P = .042), and 12-month PFS rates were 26% versus 25% (P = .390) in the control and intervention groups, respectively. Patients with unmethylated O6-methylguanine-DNA methyltransferase (MGMT) and those with good performance status (PS) had significantly worse PFS with nTMZ.  However, those who underwent larger extent of resection exhibited significantly better PFS  with nTMZ. Adverse events were similar between groups.

Conclusions

Neoadjuvant TMZ before SOC chemoradiotherapy did not improve outcomes for newly diagnosed GBM patients and is unsuitable for those with unmethylated MGMT and good PS. However, It may benefit patients with near or gross total resection. Further research is needed to refine GBM treatment strategies.

Quantification of perineural satellitosis in pretreatment glioblastoma with structural MRI and a diffusion tensor imaging template

Background

Survival outcomes for glioblastoma (GBM) patients remain unfavorable, and tumor recurrence is often observed. Understanding the radiological growth patterns of GBM could aid in improving outcomes. This study aimed to examine the relationship between contrast-enhancing tumor growth direction and white matter, using an image registration and deformation strategy.

Methods

In GBM patients 2 pretreatment scans (diagnostic and neuronavigation) were gathered retrospectively, and coregistered to a template and diffusion tensor imaging (DTI) atlas. The GBM lesions were segmented and coregistered to the same space. Growth vectors were derived and divided into vector populations parallel (Φ = 0-20°) and perpendicular (Φ = 70-90°) to white matter. To test for statistical significance between parallel and perpendicular groups, a paired samples Student's t-test was performed. O6-methylguanine-DNA methyltransferase (MGMT) methylation status and its correlation to growth rate were also tested using a one-way ANOVA test.

Results

For 78 GBM patients (mean age 61 years ± 13 SD, 32 men), the included GBM lesions showed a predominant preference for perineural satellitosis (P < .001), with a mean percentile growth of 30.8% (95% CI: 29.6-32.0%) parallel (0° < |Φ| < 20°) to white matter. Perpendicular tumor growth with respect to white matter microstructure (70° < |Φ| < 90°) showed to be 22.7% (95% CI: 21.3-24.1%) of total tumor growth direction.

Conclusions

The presented strategy showed that tumor growth direction in pretreatment GBM patients correlated with white matter architecture. Future studies with patient-specific DTI data are required to verify the accuracy of this method prospectively to identify its usefulness as a clinical metric in pre and posttreatment settings.

Risk factors for preoperative and postoperative seizures in patients with glioblastoma according to the 2021 World Health Organization classification

OBJECTIVE

To identify risk factors for developing glioblastoma (GBM) related preoperative (PRS) and postoperative seizures (POS). Also, we aimed to analyze the impact of PRS and POS on survival in a GBM cohort according to the revised 2021 WHO glioma classification.

METHODS

We performed a single-center retrospective cohort study of patients with GBM (according to the 2021 World Health Organization Classification) treated at Mayo Clinic Florida between January 2018 and July 2022. Seizures were stratified into preoperative seizures (PRS) and postoperative seizures (POS, >7 days after surgery). Associations between patients' characteristics and overall survival with PRS and POS were assessed.

RESULTS

One hundred nineteen adults (mean =60.9 years), 49 (41.2 %) females, were identified. The rates of PRS and POS in the cohort were 35.3 % (n = 42) and 37.8 % (n = 45), respectively. Patients with PRS were younger (p = 0.035) and were likely to undergo intraoperative electrocorticography. The incidence of PRS (p = 0.049) and POS (p<0.001) was lower among patients with tumors located in the occipital location. PRS increased the risk of POS after adjusting for age and sex (RR: 2.59, CI = 1.44-4.65, p = 0.001). There was no association between PRS or POS and other patient-related factors, including several tumor molecular markers (TMMs) examined. PRS (p = 0.036), POS (p<0.001), and O6-Methylguanine-DNA Methyltransferase (MGMT) promotor methylation status (p = 0.032) were associated with longer survival time.

CONCLUSIONS

PRS and POS are associated with non-occipital tumor location and longer survival time in patients with GBM. While younger ages predicted PRS, PRS predicted POS. Well-designed prospective studies with larger sample sizes are needed to clarify the influence of TMMs in the genesis of epileptic seizures in patients with GBM.

Standardizing analysis of intra-tumoral heterogeneity with computational pathology

Many malignant cancers like glioblastoma are highly adaptive diseases that dynamically change their regional biology to survive and thrive under diverse microenvironmental and therapeutic pressures. While the concept of intra-tumoral heterogeneity has become a major paradigm in cancer research and care, systematic approaches to assess and document bio-variation in cancer are still in their infancy. Here we discuss existing approaches and challenges to documenting intra-tumoral heterogeneity and emerging computational approaches that leverage artificial intelligence to begin to overcome these limitations. We propose how these emerging techniques can be coupled with a diversity of molecular tools to address intra-tumoral heterogeneity more systematically in research and in practice, especially across larger specimens and longitudinal analyses. Systematic documentation and characterization of heterogeneity across entire tumor specimens and their longitudinal evolution has the potential to improve our understanding and treatment of cancer.

Peritumoral ADC Values Correlate with the MGMT Methylation Status in Patients with Glioblastoma

Different results have been reported concerning the relationship of the apparent diffusion coefficient (ADC) values and the status of methylation as the promoter gene for the enzyme methylguanine-DNA methyltransferase (MGMT) in patients with glioblastomas (GBs). The aim of this study was to investigate if there were correlations between the ADC values of the enhancing tumor and peritumoral areas of GBs and the MGMT methylation status. In this retrospective study, we included 42 patients with newly diagnosed unilocular GB with one MRI study prior to any treatment and histopathological data. After co-registration of ADC maps with T1-weighted sequences after contrast administration and dynamic susceptibility contrast (DSC) perfusion, we manually selected one region-of-interest (ROI) in the enhancing and perfused tumor and one ROI in the peritumoral white matter. Both ROIs were mirrored in the healthy hemisphere for normalization. In the peritumoral white matter, absolute and normalized ADC values were significantly higher in patients with MGMT-unmethylated tumors, as compared to patients with MGMT-methylated tumors (absolute values p = 0.002, normalized p = 0.0007). There were no significant differences in the enhancing tumor parts. The ADC values in the peritumoral region correlated with MGMT methylation status, confirmed by normalized ADC values. In contrast to other studies, we could not find a correlation between the ADC values or the normalized ADC values and the MGMT methylation status in the enhancing tumor parts.

MRI radiomics and potential applications to glioblastoma

MRI plays an important role in the evaluation of glioblastoma, both at initial diagnosis and follow up after treatment. Quantitative analysis via radiomics can augment the interpretation of MRI in terms of providing insights regarding the differential diagnosis, genotype, treatment response, and prognosis. The various MRI radiomic features of glioblastoma are reviewed in this article.