MGMT promoter methylation is predictive of response to radiotherapy and prognostic in the absence of adjuvant alkylating chemotherapy for glioblastoma

Genomic, epigenomic and transcriptomic landscape of glioblastoma

The mostly aggressive and extremely malignant type of central nervous system is Glioblastoma (GBM), which is characterized by an extremely short average survival time of lesser than 16 months. The primary cause of this phenomenon can be attributed to the extensively altered genome of GBM, which is characterized by the dysregulation of numerous critical signaling pathways and epigenetics regulations associated with proliferation, cellular growth, survival, and apoptosis. In light of this, different genetic alterations in critical signaling pathways and various epigenetics regulation mechanisms are associated with GBM and identified as distinguishing markers. Such GBM prognostic alterations are identified in PI3K/AKT, p53, RTK, RAS, RB, STAT3 and ZIP4 signaling pathways, metabolic pathway (IDH1/2), as well as alterations in epigenetic regulation genes (MGMT, CDKN2A-p16INK4aCDKN2B-p15INK4b). The exploration of innovative diagnostic and therapeutic approaches that specifically target these pathways is utmost importance to enhance the future medication for GBM. This study provides a comprehensive overview of dysregulated epigenetic mechanisms and signaling pathways due to mutations, methylation, and copy number alterations of in critical genes in GBM with prevalence and emphasizing their significance.

Predictors of Tumor Dynamics Over a 6-Week Course of Concurrent Chemoradiotherapy for Glioblastoma and the Effect on Survival

PURPOSE

We present the final analyses of tumor dynamics and their prognostic significance during a 6-week course of concurrent chemoradiotherapy for glioblastoma in the Glioblastoma Longitudinal Imaging Observational study.

METHODS AND MATERIALS

This is a prospective serial magnetic resonance imaging study in 129 patients with glioblastoma who had magnetic resonance imaging obtained at radiation therapy (RT) planning (F0), fraction 10 (F10), fraction 20 (F20), and 1-month post-RT. Tumor dynamics assessed included gross tumor volume relative to F0 (Vrel) and tumor migration distance (dmigration). Covariables evaluated included: corpus callosum involvement, extent of surgery, O6-methylguanine-DNA-methyltransferase methylation, and isocitrate dehydrogenase mutation status.

RESULTS

The median Vrel were 0.85 (range, 0.25-2.29) at F10, 0.79 (range, 0.09-2.22) at F20, and 0.78 (range, 0.13-4.27) at 1 month after completion of RT. The median dmigration were 4.7 mm (range, 1.1-20.4 mm) at F10, 4.7 mm (range, 0.8-20.7 mm) at F20, and 6.1 mm (range, 0.0-45.5 mm) at 1 month after completion of RT. Compared with patients who had corpus callosum involvement (n = 26), those without corpus callosum involvement (n = 103) had significant Vrel reduction at F20 (P = .03) and smaller dmigration at F20 (P = .007). Compared with patients who had biopsy alone (n = 19) and subtotal resection (n = 71), those who had gross total resection (n = 38) had significant Vrel reduction at F10 (P = .001) and F20 (P = .001) and a smaller dmigration at F10 (P = .03) and F20 (P = .002). O6-Methylguanine-DNA-methyltransferase methylation and isocitrate dehydrogenase mutation status were not significantly associated with tumor dynamics. The median progression-free survival and overall survival (OS) were 8.5 months (95% CI, 6.9-9.9) and 20.4 months (95% CI, 17.6-25.2). In multivariable analyses, patients with Vrel ≥ 1.33 at F10 had worse OS (hazard ratio [HR], 4.6; 95% CI, 1.8-11.4; P = .001), and patients with dmigration ≥ 5 mm at 1-month post-RT had worse progression-free survival (HR, 1.76; 95% CI, 1.08-2.87) and OS (HR, 2.2; 95% CI, 1.2-4.0; P = .007).

CONCLUSIONS

Corpus callosum involvement and extent of surgery are independent predictors of tumor dynamics during RT and can enable patient selection for adaptive RT strategies. Significant tumor enlargement at F10 and tumor migration 1-month post-RT were associated with poorer OS.

Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice

Technological advancements have enabled the extended investigation, development, and application of computational approaches in various domains, including health care. A burgeoning number of diagnostic, predictive, prognostic, and monitoring biomarkers are continuously being explored to improve clinical decision making in neuro-oncology. These advancements describe the increasing incorporation of artificial intelligence (AI) algorithms, including the use of radiomics. However, the broad applicability and clinical translation of AI are restricted by concerns about generalisability, reproducibility, scalability, and validation. This Policy Review intends to serve as the leading resource of recommendations for the standardisation and good clinical practice of AI approaches in health care, particularly in neuro-oncology. To this end, we investigate the repeatability, reproducibility, and stability of AI in response assessment in neuro-oncology in studies on factors affecting such computational approaches, and in publicly available open-source data and computational software tools facilitating these goals. The pathway for standardisation and validation of these approaches is discussed with the view of trustworthy AI enabling the next generation of clinical trials. We conclude with an outlook on the future of AI-enabled neuro-oncology.

Is modulation of immune checkpoints on glioblastoma-infiltrating myeloid cells a viable therapeutic strategy?

The field of immunology has traditionally focused on immune checkpoint modulation of adaptive immune cells. However, many malignancies such as glioblastoma are mostly devoid of T cells and rather are enriched with immunosuppressive myeloid cells of the innate immune system. While some immune checkpoint targets are shared between adaptive and innate immunity, myeloid-specific checkpoints could also serve as potential therapeutics. To better understand the impact of immune checkpoint blockade on myeloid cells, we systematically summarize the current literature focusing on the direct immunological effects of PD-L1/PD-1, CD24/Siglec-10, collagen/LAIR-1, CX3CL1/CX3CR1, and CXCL10/CXCR3. By synthesizing the molecular mechanisms and the translational implications, we aim to prioritize agents in this category of therapeutics for glioblastoma.

DDX3X dynamics, glioblastoma's genetic landscape, therapeutic advances, and autophagic interplay

Glioblastoma is one of the most aggressive and deadly forms of cancer, posing significant challenges for the medical community. This review focuses on key aspects of Glioblastoma, including its genetic differences between primary and secondary types. Temozolomide is a major first-line treatment for Glioblastoma, and this article explores its development, how it works, and the issue of resistance that limits its effectiveness, prompting the need for new treatment strategies. Gene expression profiling has greatly advanced cancer research by revealing the molecular mechanisms of tumors, which is essential for creating targeted therapies for Glioblastoma. One important protein in this context is DDX3X, which plays various roles in cancer, sometimes promoting it or otherwise suppressing it. Additionally, autophagy, a process that maintains cellular balance, has complex implications in cancer treatment. Understanding autophagy helps to identify resistance mechanisms and potential treatments, with Chloroquine showing promise in treating Glioblastoma. This review covers the interplay between Glioblastoma, DDX3X, and autophagy, highlighting the challenges and potential strategies in treating this severe disease.

Unraveling the mysteries of MGMT: Implications for neuroendocrine tumors

Neuroendocrine tumors (NETs) are a diverse group of tumors that arise from neuroendocrine cells and are commonly found in various organs. A considerable proportion of NET patients were diagnosed at an advanced or metastatic stage. Alkylating agents are the primary treatment for NET, and O6-methylguanine methyltransferase (MGMT) remains the first-line of defense against DNA damage caused by these agents. Clinical trials have indicated that MGMT promoter methylation or its low/lacked expression can predict a favorable outcome with Temozolomide in NETs. Its status could help select NET patients who can benefit from alkylating agents. Therefore, MGMT status serves as a biomarker to guide decisions on the efficacy of Temozolomide as a personalized treatment option. Additionally, delving into the regulatory mechanisms of MGMT status can lead to the development of MGMT-targeted therapies, benefiting individuals with high levels of MGMT expression. This review aims to explore the polymorphism of MGMT regulation and summarize its clinical implications in NETs, which would help establish the role of MGMT as a biomarker and its potential as a therapeutic target in NETs. Additionally, we explore the benefits of combining Temozolomide and immunotherapy in MGMT hypermethylated subgroups. Future studies can focus on optimizing Temozolomide administration to induce specific immunomodulatory changes.

Radiomics analysis of cerebral blood flow suggests a possible link between perfusion homogeneity and poor glioblastoma multiforme prognosis

Objectives. This study investigates the association between cerebral blood flow (CBF) and overall survival (OS) in glioblastoma multiforme (GBM) patients receiving chemoradiation. Identifying CBF biomarkers could help predict patient response to this treatment, facilitating the development of personalized therapeutic strategies.Materials and Methods. This retrospective study analyzed CBF data from dynamic susceptibility contrast (DSC) MRI in 30 newly diagnosed GBM patients (WHO grade IV). Radiomics features were extracted from CBF maps, tested for robustness, and correlated with OS. Kaplan-Meier analysis was used to assess the predictive value of radiomic features significantly associated with OS, aiming to stratify patients into groups with distinct post-treatment survival outcomes.Results. While mean relative CBF and CBV failed to serve as independent prognostic markers for OS, the prognostic potential of radiomic features extracted from CBF maps was explored. Ten out of forty-three radiomic features with highest intraclass correlation coefficients (ICC > 0.9), were selected for characterization. While Correlation and Zone Size Variance (ZSV) features showed significant OS correlations, indicating prognostic potential, Kaplan-Meier analysis did not significantly stratify patients based on these features. Visual analysis of the graphs revealed a predominant association between the identified radiomic features and OS under two years. Focusing on this subgroup, Correlation, ZSV, and Gray-Level Nonuniformity (GLN) emerged as significant, suggesting that a lack of heterogeneity in perfusion patterns may be indicative of a poorer outcome. Kaplan-Meier analysis effectively stratified this cohort based on the features mentioned above. Receiver operating characteristic (ROC) analysis further validated their prognostic value, with ZSV demonstrating the highest sensitivity and specificity (0.75 and 0.85, respectively).Conclusion. Our findings underscored radiomics features sensitive to CBF heterogeneity as pivotal predictors for patient stratification. Our results suggest that these markers may have the potential to identify patients who are unlikely to benefit from standard chemoradiation therapy.

George EJ, Subramanian P, Sundaresan V, Sweeney K, Tan BH, Turnbull N, Tao Y, Thorne L, Tweedie R, Tzatzidou A, Vaqas B, Venturini S, Whitehouse K, Whitfield P, Wildman J, Williams I, Williams K, Wykes V, Ye TTS, Yap KS, Yousuff M, Zulfiqar A, Bandyopadhyay S, Ooi SZY, Clynch A, Burton O, Steinruecke M, Bolton W, Touzet AY, Redpath H, Lee SH, Erhabor J, Mantle O, Gillespie CS, Bligh ES, Kolias A, Woodfield J, Chari A, Borchert R, Piper R, Fountain DM, Poon MTC, Islim AI. Imaging timing after surgery for glioblastoma: an evaluation of practice in Great Britain and Ireland (INTERVAL-GB)- a multi-centre, cohort study

PURPOSE

Post-operative MRI is used to assess extent of resection, monitor treatment response and detect progression in high-grade glioma. However, compliance with accepted guidelines for follow-up MRI, and impact on management/outcomes is unclear.

METHODS

Multi-center, retrospective observational cohort study of patients with confirmed WHO grade 4 glioma (August 2018-February 2019) receiving oncological treatment.

PRIMARY OBJECTIVE

investigate follow-up MRI surveillance practice and compliance with recommendations from NICE (Post-operative scan < 72h, MRI every 3-6 months) and EANO (Post-operative scan < 48h, MRI every 3 months).

RESULTS

There were 754 patients from 26 neuro-oncology centers with a median age of 63 years (IQR 54-70), yielding 10,100 (median, 12.5/person, IQR 5.2-19.4) person-months of follow-up. Of patients receiving debulking surgery, most patients had post-operative MRI within 72 h of surgery (78.0%, N = 407/522), and within 48 h of surgery (64.2%, N = 335/522). The median number of subsequent follow-up MRI scans was 1 (IQR 0-4). Compliance with NICE and EANO recommendations for follow-up MRI was 52.8% (N = 398/754) and 24.9% (N = 188/754), respectively. On multivariable Cox regression analysis, increased time spent in recommended follow-up according to NICE guidelines was associated with longer OS (HR 0.56, 95% CI 0.46-0.66, P < 0.001), but not PFS (HR 0.93, 95% CI 0.79-1.10, P = 0.349). Increased time spent in recommended follow-up according to EANO guidelines was associated with longer OS (HR 0.54, 95% CI 0.45-0.63, P < 0.001) but not PFS (HR 0.99, 95% CI 0.84-1.16, P = 0.874).

CONCLUSION

Regular surveillance follow-up for glioblastoma is associated with longer OS. Prospective trials are needed to determine whether regular or symptom-directed MRI influences outcomes.

Biomarkers of immunotherapy in glioblastoma

Glioblastoma (GBM) is the most common primary brain cancer, comprising half of all malignant brain tumors. Patients with GBM have a poor prognosis, with a median survival of 14-15 months. Current therapies for GBM, including chemotherapy, radiotherapy, and surgical resection, remain inadequate. Novel therapies are required to extend patient survival. Although immunotherapy has shown promise in other cancers, including melanoma and non-small lung cancer, its efficacy in GBM has been limited to subsets of patients. Identifying biomarkers of immunotherapy response in GBM could help stratify patients, identify new therapeutic targets, and develop more effective treatments. This article reviews existing and emerging biomarkers of clinical response to immunotherapy in GBM. The scope of this review includes immune checkpoint inhibitor and antitumoral vaccination approaches, summarizing the variety of molecular, cellular, and computational methodologies that have been explored in the setting of anti-GBM immunotherapies.

Unveiling the role of O(6)-methylguanine-DNA methyltransferase in cancer therapy: insights into alkylators, pharmacogenomics, and others

Cancer chemotherapy is advancing as we understand how cellular mechanisms and drugs interact, particularly involving the enzyme MGMT, which repairs DNA damage that can cause cancer. This review examines MGMT's role in DNA repair, its impact on chemotherapy, and its complex interaction with radiation therapy. MGMT activity can both protect against mutations and cause drug resistance. Modulating MGMT could improve treatment efficacy and tailoring therapy to MGMT status may enhance patient outcomes. Understanding MGMT is crucial for developing precise cancer treatments and advancing patient care.

Role of artificial intelligence in brain tumour imaging

Artificial intelligence (AI) is a rapidly evolving field with many neuro-oncology applications. In this review, we discuss how AI can assist in brain tumour imaging, focusing on machine learning (ML) and deep learning (DL) techniques. We describe how AI can help in lesion detection, differential diagnosis, anatomic segmentation, molecular marker identification, prognostication, and pseudo-progression evaluation. We also cover AI applications in non-glioma brain tumours, such as brain metastasis, posterior fossa, and pituitary tumours. We highlight the challenges and limitations of AI implementation in radiology, such as data quality, standardization, and integration. Based on the findings in the aforementioned areas, we conclude that AI can potentially improve the diagnosis and treatment of brain tumours and provide a path towards personalized medicine and better patient outcomes.

What Changed in CNS5? A Mini-Review on General Changes and Adult Diffuse Gliomas

The fifth edition of the WHO classification of tumors of the central nervous system (WHO CNS5) was published in 2021 which is the sixth version of the international standard for the diagnostics of CNS tumors. Regular updates of the consortium to inform molecular and practical approaches to CNS tumor taxonomy (cIMPACT-NOW) shaped the WHO CNS5 which continues the trend of incorporating the molecular characteristics of tumors into the histological and immunohistochemical findings. The various updates can be classified into general changes across all tumors and specific changes within the tumor groups. This mini-review highlights the general changes and the major changes in adult diffuse gliomas.

Prognostic Factors for Recurrent Glioma: A Population-Based Analysis

Background

The overall survival (OS) for patients with recurrent glioma is meager. Also, the effect of radionecrosis and prognostic factors for recurrent glioma remains controversial. In this regard, developing effective predictive models and guiding clinical care is crucial for these patients.

Methods

We screened patients with recurrent glioma after radiotherapy and those who received surgery between August 1, 2013, and December 31, 2020. Univariate and multivariate Cox regression analyses determined the independent prognostic factors affecting the prognosis of recurrent glioma. Moreover, nomograms were constructed to predict recurrent glioma risk and prognosis. Statistical methods were used to determine the prediction accuracy and discriminability of the nomogram prediction model based on the area under the curve (AUC), the C-index, the decision curve analysis (DCA), and the calibration curve. In order to distinguish high-risk and low-risk groups for OS, the X-Tile and Kaplan-Meier (K-M) survival curves were employed, and the nomogram prediction model was further validated by the X-Tile and K-M survival curves.

Results

According to a Cox regression analysis, independent prognostic factors of recurrent glioma after radiotherapy with radionecrosis were World Health Organization (WHO) grade and gliosis percentage. We utilized a nomogram prediction model to analyze results visually. The C-index was 0.682 (95% CI: 0.616-0.748). According to receiver operating characteristic (ROC) analysis, calibration plots, and DCA, the nomogram prediction model was found to have a high-performance ability, and all patients were divided into low-risk and high-risk groups based on OS (P < .001).

Conclusion

WHO grade and gliosis percentage are prognostic factors for recurrent glioma with radionecrosis, and a nomogram prediction model was established based on these two variables. Patients could be divided into high- and low-risk groups with different OS by this model, and it will provide individualized clinical decisions for future treatment.

Safety and Efficacy of Laser Interstitial Thermal Therapy as Upfront Therapy in Primary Glioblastoma and IDH-Mutant Astrocytoma: A Meta-Analysis

Although primary studies have reported the safety and efficacy of LITT as a primary treatment in glioma, they are limited by sample sizes and institutional variation in stereotactic parameters such as temperature and laser power. The current literature has yet to provide pooled statistics on outcomes solely for primary brain tumors according to the 2021 WHO Classification of Tumors of the Central Nervous System (WHO CNS5). In the present study, we identify recent articles on primary CNS neoplasms treated with LITT without prior intervention, focusing on relationships with molecular profile, PFS, and OS. This meta-analysis includes the extraction of data from primary sources across four databases using the Covidence systematic review manager. The pooled data suggest LITT may be a safe primary management option with tumor ablation rates of 94.8% and 84.6% in IDH-wildtype glioblastoma multiforme (GBM) and IDH-mutant astrocytoma, respectively. For IDH-wildtype GBM, the pooled PFS and OS were 5.0 and 9.0 months, respectively. Similar to rates reported in the prior literature, the neurologic and non-neurologic complication rates for IDH-wildtype GBM were 10.3% and 4.8%, respectively. The neurologic and non-neurologic complication rates were somewhat higher in the IDH-mutant astrocytoma cohort at 33% and 8.3%, likely due to a smaller cohort size.

Microarray-Based DNA Methylation Profiling: Validation Considerations for Clinical Testing

Microarray-based methylation profiling has emerged as a valuable tool for refining diagnoses and revealing novel tumor subtypes, particularly in central nervous system tumors. Despite the increasing adoption of this technique in clinical genomic laboratories, no technical standards have been published in establishing minimum criteria for test validation. A working group with experience and expertise in DNA-based methylation profiling tests on central nervous system tumors collaborated to develop practical discussion points and focus on important considerations for validating this test in clinical laboratory settings. The experience in validating this methodology in a clinical setting is summarized. Specifically, the advantages and challenges associated with utilizing an in-house classifier compared with a third-party classifier are highlighted. Additionally, experiences in demonstrating the assay's sensitivity and specificity, establishing minimum sample criteria, and implementing quality control metrics are described. As methylation profiling for tumor classification expands to other tumor types and continues to evolve for various other applications, the critical considerations described here are expected to serve as a guidance for future efforts in establishing professional guidelines for this assay.

The Role of Mesenchymal Reprogramming in Malignant Clonal Evolution and Intra-Tumoral Heterogeneity in Glioblastoma

Glioblastoma (GBM) is the most common yet uniformly fatal adult brain cancer. Intra-tumoral molecular and cellular heterogeneities are major contributory factors to therapeutic refractoriness and futility in GBM. Molecular heterogeneity is represented through molecular subtype clusters whereby the proneural (PN) subtype is associated with significantly increased long-term survival compared to the highly resistant mesenchymal (MES) subtype. Furthermore, it is universally recognized that a small subset of GBM cells known as GBM stem cells (GSCs) serve as reservoirs for tumor recurrence and progression. The clonal evolution of GSC molecular subtypes in response to therapy drives intra-tumoral heterogeneity and remains a critical determinant of GBM outcomes. In particular, the intra-tumoral MES reprogramming of GSCs using current GBM therapies has emerged as a leading hypothesis for therapeutic refractoriness. Preventing the intra-tumoral divergent evolution of GBM toward the MES subtype via new treatments would dramatically improve long-term survival for GBM patients and have a significant impact on GBM outcomes. In this review, we examine the challenges of the role of MES reprogramming in the malignant clonal evolution of glioblastoma and provide future perspectives for addressing the unmet therapeutic need to overcome resistance in GBM.

Network Analyses of Brain Tumor Patients' Multiomic Data Reveals Pharmacological Opportunities to Alter Cell State Transitions

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e. phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte- like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein-protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

Network Analyses of Brain Tumor Patients' Multiomic Data Reveals Pharmacological Opportunities to Alter Cell State Transitions

Glioblastoma Multiforme (GBM) remains a particularly difficult cancer to treat, and survival outcomes remain poor. In addition to the lack of dedicated drug discovery programs for GBM, extensive intratumor heterogeneity and epigenetic plasticity related to cell-state transitions are major roadblocks to successful drug therapy in GBM. To study these phenomenon, publicly available snRNAseq and bulk RNAseq data from patient samples were used to categorize cells from patients into four cell states (i.e. phenotypes), namely: (i) neural progenitor-like (NPC-like), (ii) oligodendrocyte progenitor-like (OPC-like), (iii) astrocyte-like (AC-like), and (iv) mesenchymal-like (MES-like). Patients were subsequently grouped into subpopulations based on which cell-state was the most dominant in their respective tumor. By incorporating phosphoproteomic measurements from the same patients, a protein-protein interaction network (PPIN) was constructed for each cell state. These four-cell state PPINs were pooled to form a single Boolean network that was used for in silico protein knockout simulations to investigate mechanisms that either promote or prevent cell state transitions. Simulation results were input into a boosted tree machine learning model which predicted the cell states or phenotypes of GBM patients from an independent public data source, the Glioma Longitudinal Analysis (GLASS) Consortium. Combining the simulation results and the machine learning predictions, we generated hypotheses for clinically relevant causal mechanisms of cell state transitions. For example, the transcription factor TFAP2A can be seen to promote a transition from the NPC-like to the MES-like state. Such protein nodes and the associated signaling pathways provide potential drug targets that can be further tested in vitro and support cell state-directed (CSD) therapy.

DNA Adducts in Cancer Chemotherapy

DNA adducting drugs, including alkylating agents and platinum-containing drugs, are prominent in cancer chemotherapy. Their mechanisms of action involve direct interaction with DNA, resulting in the formation of DNA addition products known as DNA adducts. While these adducts are well-accepted to induce cancer cell death, understanding of their specific chemotypes and their role in drug therapy response remain limited. This perspective aims to address this gap by investigating the metabolic activation and chemical characterization of DNA adducts formed by the U.S. FDA-approved drugs. Moreover, clinical studies on DNA adducts as potential biomarkers for predicting patient responses to drug efficacy are examined. The overarching goal is to engage the interest of medicinal chemists and stimulate further research into the use of DNA adducts as biomarkers for guiding personalized cancer treatment.

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.

Zika Virus: A Neurotropic Warrior against High-Grade Gliomas-Unveiling Its Potential for Oncolytic Virotherapy

Gliomas account for approximately 75-80% of all malignant primary tumors in the central nervous system (CNS), with glioblastoma multiforme (GBM) considered the deadliest. Despite aggressive treatment involving a combination of chemotherapy, radiotherapy, and surgical intervention, patients with GBM have limited survival rates of 2 to 5 years, accompanied by a significant decline in their quality of life. In recent years, novel management strategies have emerged, such as immunotherapy, which includes the development of vaccines or T cells with chimeric antigen receptors, and oncolytic virotherapy (OVT), wherein wild type (WT) or genetically modified viruses are utilized to selectively lyse tumor cells. In vitro and in vivo studies have shown that the Zika virus (ZIKV) can infect glioma cells and induce a robust oncolytic activity. Consequently, interest in exploring this virus as a potential oncolytic virus (OV) for high-grade gliomas has surged. Given that ZIKV actively circulates in Colombia, evaluating its neurotropic and oncolytic capabilities holds considerable national and international importance, as it may emerge as an alternative for treating highly complex gliomas. Therefore, this literature review outlines the generalities of GBM, the factors determining ZIKV's specific tropism for nervous tissue, and its oncolytic capacity. Additionally, we briefly present the progress in preclinical studies supporting the use of ZIKV as an OVT for gliomas.

A systematic review of high impact CpG sites and regions for MGMT methylation in glioblastoma [A systematic review of MGMT methylation in GBM]

BACKGROUND

MGMT (O 6 -methylguanine-DNA methyltransferase) promoter methylation is a commonly assessed prognostic marker in glioblastoma (GBM). Epigenetic silencing of the MGMT gene by promoter methylation is associated with greater overall and progression free survival with alkylating agent regimens. To date, there is marked heterogeneity in how MGMT promoter methylation is tested and which CpG sites are interrogated.

METHODS

To further elucidate which MGMT promoter CpG sites are of greatest interest, we performed comprehensive searches in PubMed, Web of Science, and Embase and reviewed 2,925 article abstracts. We followed the GRADE scoring system to assess risk of bias and the quality of the studies we included.

RESULTS

We included articles on adult glioblastoma that examined significant sites or regions within MGMT promoter for the outcomes: overall survival, progression free survival, and/or MGMT expression. We excluded systemic reviews and articles on lower grade glioma. fifteen articles met inclusion criteria with variable overlap in laboratory and statistical methods employed, as well as CpG sites interrogated. Pyrosequencing or BeadChip arrays were the most popular methods utilized, and CpG sites between CpG's 70-90 were most frequently investigated. Overall, there was moderate concordance between the CpG sites that the studies reported to be highly predictive of prognosis. Combinations or means of sites between CpG's 73-89 were associated with improved OS and PFS. Six studies identified CpG sites associated with prognosis that were closer to the transcription start site: CpG's 8, 19, 22, 25, 27, 32,38, and CpG sites 21-37, as well as low methylation level of the enhancer regions.

CONCLUSION

The following systematic review details a comprehensive investigation of the current literature and highlights several potential key CpG sites that demonstrate significant association with OS, PFS, and MGMT expression. However, the relationship between extent of MGMT promoter methylation and survival may be non-linear and could be influenced by potential CpG hotspots, the extent of methylation at each CpG site, and MGMT enhancer methylation status. There were several limitations within the studies such as smaller sample sizes, variance between methylation testing methods, and differences in the various statistical methods to test for association to outcome. Further studies of high impact CpG sites in MGMT methylation is warranted.

Predominance of MGMT promoter methylation among Pakistani glioblastoma patients

BACKGROUND

Glioblastoma multiforme (GBM), the most prevalent subgroup of neuroepithelial tumors, is characterized by dismal overall survival (OS). Several studies have linked O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation to OS in GBM patients. However, MGMT methylation frequencies vary geographically and across ethnicities, with limited data for South Asian populations, including Pakistan. This study aimed to analyze MGMT promoter methylation in Pakistani GBM patients.

METHODS

Consecutive primary GBM patients diagnosed ≥ 18 years-of-age, with no prior chemotherapy or radiotherapy history, were retrospectively selected. DNA was isolated from formalin-fixed-paraffin-embedded tissues. MGMT promoter methylation was analyzed using methylation-specific PCR. Clinical, pathological, and treatment data were assessed using Fisher's exact/Chi-squared tests. OS was calculated using Kaplan-Meier analysis in SPSS 27.0.1.

RESULTS

The study included 48 GBM patients, comprising 38 (79.2%) males and 10 (20.8%) females. The median diagnosis age was 49.5 years (range 18-70). MGMT methylation was observed in 87.5% (42/48) of all cases. Patients with MGMT methylation undergoing radiotherapy or radiotherapy plus chemotherapy exhibited significantly improved median OS of 7.2 months (95% CI, 3.7-10.7; P < 0.001) and 16.9 months (95% CI, 15.9-17.9; P < 0.001), respectively, compared to those undergoing surgical resection only (OS: 2.2 months, 95% CI, 0.8-3.6).

CONCLUSION

This is the first comprehensive study highlighting a predominance of MGMT methylation in Pakistani GBM patients. Furthermore, our findings underscore the association of MGMT methylation with improved OS across diverse treatment modalities. Larger studies are imperative to validate our findings for better management of Pakistani GBM patients.

Genetic and epigenetic alterations in DNA repair genes and treatment outcome of chemoradiotherapy in cervical cancer

Cervical cancer (CaCx) is the deadliest malignancy among women which is caused by human papillomavirus (HPV) and anthro-demographical/clinicopathological factors. HPV oncoproteins E6 and E7 target p53 and RB (retinoblastoma) protein degradation, Ataxia telangiectasia mutated (ATM), ATM-RAD3-related (ATR) inactivation and subsequent impairment of non-homologous end joining (NHEJ), homologous recombination, and base excision repair pathways. There is also an accumulation of genetic and epigenetic alterations in Tumor Growth Suppressors (TGS), oncogenes, and DNA repair genes leading to increased genome instability and CaCx development. These alterations might be responsible for differential clinical response to Cisplatin-based chemoradiotherapy (CRT) in patients. This review explores HPV-mediated DNA damage as a risk factor in CaCx development, the mechanistic role of genetic and epigenetic alterations in DNA repair genes and their association with CRT and outcome, It also explores new possibilities for the development of genetic and epigenetic-based biomarkers for diagnostic, prognostic, and molecular therapeutic interventions.

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

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

Magnetic Resonance Imaging of Iron Metabolism with T2* Mapping Predicts an Enhanced Clinical Response to Pharmacologic Ascorbate in Patients with GBM

PURPOSE

Pharmacologic ascorbate (P-AscH-) is hypothesized to be an iron (Fe)-dependent tumor-specific adjuvant to chemoradiation in treating glioblastoma (GBM). This study determined the efficacy of combining P-AscH- with radiation and temozolomide in a phase II clinical trial while simultaneously investigating a mechanism-based, noninvasive biomarker in T2* mapping to predict GBM response to P-AscH- in humans.

PATIENTS AND METHODS

The single-arm phase II clinical trial (NCT02344355) enrolled 55 subjects, with analysis performed 12 months following the completion of treatment. Overall survival (OS) and progression-free survival (PFS) were estimated with the Kaplan-Meier method and compared across patient subgroups with log-rank tests. Forty-nine of 55 subjects were evaluated using T2*-based MRI to assess its utility as an Fe-dependent biomarker.

RESULTS

Median OS was estimated to be 19.6 months [90% confidence interval (CI), 15.7-26.5 months], a statistically significant increase compared with historic control patients (14.6 months). Subjects with initial T2* relaxation < 50 ms were associated with a significant increase in PFS compared with T2*-high subjects (11.2 months vs. 5.7 months, P < 0.05) and a trend toward increased OS (26.5 months vs. 17.5 months). These results were validated in preclinical in vitro and in vivo model systems.

CONCLUSIONS

P-AscH- combined with temozolomide and radiotherapy has the potential to significantly enhance GBM survival. T2*-based MRI assessment of tumor iron content is a prognostic biomarker for GBM clinical outcomes. See related commentary by Nabavizadeh and Bagley, p. 255.

GTP Signaling Links Metabolism, DNA Repair, and Responses to Genotoxic Stress

How cell metabolism regulates DNA repair is incompletely understood. Here, we define a GTP-mediated signaling cascade that links metabolism to DNA repair and has significant therapeutic implications. GTP, but not other nucleotides, regulates the activity of Rac1, a guanine nucleotide-binding protein, which promotes the dephosphorylation of serine 323 on Abl-interactor 1 (Abi-1) by protein phosphatase 5 (PP5). Dephosphorylated Abi-1, a protein previously not known to activate DNA repair, promotes nonhomologous end joining. In patients and mouse models of glioblastoma, Rac1 and dephosphorylated Abi-1 mediate DNA repair and resistance to standard-of-care genotoxic treatments. The GTP-Rac1-PP5-Abi-1 signaling axis is not limited to brain cancer, as GTP supplementation promotes DNA repair and Abi-1-S323 dephosphorylation in nonmalignant cells and protects mouse tissues from genotoxic insult. This unexpected ability of GTP to regulate DNA repair independently of deoxynucleotide pools has important implications for normal physiology and cancer treatment.

SIGNIFICANCE

A newly described GTP-dependent signaling axis is an unexpected link between nucleotide metabolism and DNA repair. Disrupting this pathway can overcome cancer resistance to genotoxic therapy while augmenting it can mitigate genotoxic injury of normal tissues. This article is featured in Selected Articles from This Issue, p. 5.

dCas9/CRISPR-based methylation of O-6-methylguanine-DNA methyltransferase enhances chemosensitivity to temozolomide in malignant glioma

BACKGROUND

Malignant 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.

METHODS

Via 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.

RESULTS

We 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.

CONCLUSION

dCas9/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.

Pan-cancer ion transport signature reveals functional regulators of glioblastoma aggression

Ion channels, transporters, and other ion-flux controlling proteins, collectively comprising the "ion permeome", are common drug targets, however, their roles in cancer remain understudied. Our integrative pan-cancer transcriptome analysis shows that genes encoding the ion permeome are significantly more often highly expressed in specific subsets of cancer samples, compared to pan-transcriptome expectations. To enable target selection, we identified 410 survival-associated IP genes in 33 cancer types using a machine-learning approach. Notably, GJB2 and SCN9A show prominent expression in neoplastic cells and are associated with poor prognosis in glioblastoma, the most common and aggressive brain cancer. GJB2 or SCN9A knockdown in patient-derived glioblastoma cells induces transcriptome-wide changes involving neuron projection and proliferation pathways, impairs cell viability and tumor sphere formation in vitro, perturbs tunneling nanotube dynamics, and extends the survival of glioblastoma-bearing mice. Thus, aberrant activation of genes encoding ion transport proteins appears as a pan-cancer feature defining tumor heterogeneity, which can be exploited for mechanistic insights and therapy development.

A multi-institutional phase I study of acetazolamide with temozolomide in adults with newly diagnosed MGMT-methylated malignant glioma

Background

A significant unmet need exists for the treatment of glioblastoma, IDH-wildtype (GBM). Preclinical work shows that acetazolamide sensitizes GBM to temozolomide (TMZ) by overcoming TMZ resistance due to BCL-3-dependent upregulation of carbonic anhydrase. Acetazolamide is Food and Drug Administration-approved for the treatment of altitude sickness. Drug repurposing enables the application of drugs to diseases beyond initial indications. This multi-institutional, open-label, phase I trial examined a combination of acetazolamide and TMZ in patients with MGMT promoter-methylated high-grade glioma.

Methods

A total of 24 patients (GBM, IDH-wildtype = 22; Grade 4 astrocytoma, IDH-mutant = 1; Grade 3 astrocytoma, IDH-mutant = 1) were accrued over 17 months. All patients received oral acetazolamide (250 mg BID for 7 days increased to 500 mg BID for Days 8-21 of each 28-day cycle) during the adjuvant phase of TMZ for up to 6 cycles.

Results

No patient had a dose-limiting toxicity. Adverse events were consistent with known sequelae of acetazolamide and TMZ. In the 23 WHO Grade 4 patients, the median overall survival (OS) was 30.1 months and the median progression-free survival was 16.0 months. The 2-year OS was 60.9%. In total 37% of the study population had high BCL-3 staining and trended toward shorter OS (17.2 months vs N.R., P = .06).

Conclusions

The addition of acetazolamide is safe and tolerable in GBM patients receiving standard TMZ. Survival results compare favorably to historical data from randomized trials in patients with MGMT promoter-methylated GBM and support examination of acetazolamide in a randomized trial. BCL-3 expression is a potential biomarker for prognosis in GBM or for patients more likely to benefit from TMZ.

Variant allelic frequencies of driver mutations can identify gliomas with potentially false-negative MGMT promoter methylation results

MGMT promoter methylation testing is required for prognosis and predicting temozolomide response in gliomas. Accurate results depend on sufficient tumor cellularity, but histologic estimates of cellularity are subjective. We sought to determine whether driver mutation variant allelic frequency (VAF) could serve as a more objective metric for cellularity and identify possible false-negative MGMT samples. Among 691 adult-type diffuse gliomas, MGMT promoter methylation was assessed by pyrosequencing (N = 445) or DNA methylation array (N = 246); VAFs of TERT and IDH driver mutations were assessed by next generation sequencing. MGMT results were analyzed in relation to VAF. By pyrosequencing, 56% of all gliomas with driver mutation VAF ≥ 0.325 had MGMT promoter methylation, versus only 37% with VAF < 0.325 (p < 0.0001). The mean MGMT promoter pyrosequencing score was 19.3% for samples with VAF VAF ≥ 0.325, versus 12.7% for samples with VAF < 0.325 (p < 0.0001). Optimal VAF cutoffs differed among glioma subtypes (IDH wildtype glioblastoma: 0.12-0.18, IDH mutant astrocytoma: ~0.33, IDH mutant and 1p/19q co-deleted oligodendroglioma: 0.3-0.4). Methylation array was more sensitive for MGMT promoter methylation at lower VAFs than pyrosequencing. Microscopic examination tended to overestimate tumor cellularity when VAF was low. Re-testing low-VAF cases with methylation array and droplet digital PCR (ddPCR) confirmed that a subset of them had originally been false-negative. We conclude that driver mutation VAF is a useful quality assurance metric when evaluating MGMT promoter methylation tests, as it can help identify possible false-negative cases.

Genetic and epigenetic alterations in MGMT gene and correlation with concomitant chemoradiotherapy (CRT) in cervical cancer

PURPOSE

The MGMT (O6-methylguanine-DNA methyltransferase) gene plays a crucial role in repairing DNA damage caused by alkylating agents, including those used in chemotherapy. Genetic and epigenetic alterations can influence the regulation of MGMT gene, which in turn may impact the response to concomitant chemoradiotherapy (CRT) in cervical cancer. The present study was undertaken to evaluate the correlation of such variations in MGMT gene with the treatment outcome of concomitant chemoradiotherapy (CRT) in cervical cancer.

METHODS

A total of 460 study subjects (240 controls and 220 patients) were subjected to genotypic analysis of MGMT gene variants rs12917(T/C) and rs2308327(A/G) by Amplification Refractory Mutation System-Polymerase Chain Reaction (ARMS-PCR). Out of them, 48 each of controls and patients were analyzed for promoter methylation and expression by methylation-specific PCR and real-time PCR, respectively. Patients (n = 48) were followed up and evaluated for treatment (CRT) outcome. Statistical analyses were done using GraphPad (9.0) and SPSS version 18.0.

RESULTS

Individuals with GG genotype, G allele of rs2308327, and haplotype 'TA' of both variants showed a significant increase in the development of cervical cancer (P ≤ 0.05). In epigenetic regulation, there was a significant hypermethylation of MGMT gene and down-regulation of their expression in patients compared to control individuals. In treatment outcome of CRT, GG genotype of rs2308327(A/G) gene variant showed better response and GG + AG was significantly associated with vital status (alive). Unmethylated MGMT gene showed better median overall survival up to 25 months significant in comparison to methylated MGMT promoter.

CONCLUSION

Gene variant rs2308327(A/G) and promoter hypermethylation regulated MGMT gene can be a good prognostic for treatment response in cervical cancer patients.

Expression of TMEM59L associated with radiosensitive in glioblastoma

Radiotherapy is one of the cornerstone of the glioblastoma treatment paradigm. However, the resistance of tumor cells to radiation results in poor survival. The mechanism of radioresistance has not been fully elucidated. This study aimed to screen the differential expressed genes related with radiosensitivity. The differentially expressed genes were screened based on RNA sequencing in 15 pairs of primary and recurrent glioblastoma that have undergone radiotherapy. Candidate genes were validated in 226 primary and 134 recurrent glioblastoma (GBM) obtained from the Chinese Glioma Genome Atlas (CGGA) database. RNA and protein expression were verified by Quantitative Real-time PCR (qPCR) and western blot in irradiated GBM cell lines. The candidate gene was investigated to explore the relationship between mRNA levels and clinical characteristics in the CGGA and The Cancer Genome Atlas dataset. Kaplan-Meier survival analysis and Cox regression analysis were used for survival analysis. Gene ontology and KEGG pathway analysis were used for bioinformatics analysis. Four genes (TMEM59L, Gelsolin, ZBTB7A and ATX) were screened. TMEM59L expression was significantly elevated in recurrent glioblastoma and lower in normal brain tissue. We selected TMEM59L as the target gene for further study. The increasing of TMEM59L expression induced by radiation was confirmed by mRNA and western blot in irradiated GBM cell. Further investigation revealed that high expression of TMEM59L was enriched in IDH mutant and MGMT methylated gliomas and associated with a better prognosis. Gene ontology and KEGG pathway analysis revealed that TMEM59L was closely related to the DNA damage repair and oxidative stress respond process. We speculated that the high expression of TMEM59L might enhance radiotherapy sensitivity by increasing ROS-induced DNA damage and inhibiting DNA damage repair process.

AHR, a novel inhibitory immune checkpoint receptor, is a potential therapeutic target for chemoresistant glioblastoma

PURPOSE

This study aims to elucidate the mechanism underlying temozolomide resistance in patients with MGMT promoter hypomethylated glioblastoma, which is correlated with poor prognosis. The objective is to identify therapeutic targets and drugs suitable for temozolomide-resistant glioblastoma patients using big data analysis.

METHODS

In this retrospective study, transcriptome sequencing data from 457 glioblastoma patients, multi-omics data, and single-cell sequencing data were employed to assess the expression pattern, prognostic value, and biological functions of AHR in glioblastoma. The HERB database was utilized to screen for AHR-targeted drugs for glioblastoma treatment. Validation of our findings was conducted using multiplex immunofluorescence staining of clinical samples and T cells and tumor cells co-culture models.

RESULTS

Our findings demonstrated that patients with MGMT promoter unmethylation did not benefit from postoperative temozolomide chemotherapy due to resistance arising from DNA repair function and tumor immune response. AHR was found to be expressed in immune cells and exhibited an immunomodulatory role in glioblastoma with MGMT promoter unmethylation. AHR was identified as a potential novel inhibitory immune checkpoint receptor, serving as a therapeutic target for temozolomide-resistant glioblastoma. Furthermore, targeting AHR with Semen aesculi markedly enhanced the cytotoxic effect of T cells on glioma cells.

CONCLUSIONS

In addition to DNA repair function, the tumor immune response plays a pivotal role in temozolomide resistance of glioblastoma. Herbal compounds targeting AHR may offer an effective treatment for temozolomide-resistant glioblastoma.

Prognostic evaluation of patients with glioblastoma using a new score prediction model

Despite the wide reportage of prognostic factors for glioblastoma (GBM), it is difficult to determine how these factors interact to affect patients' survival. To determine the combination of prognostic factors, we retrospectively analyzed the clinic data of 248 IDH wild-type GBM patients and built a novel prediction model. The survival variables of patients were identified via univariate and multivariate analyses. In addition, the score prediction models were constructed by combining classification and regression tree (CART) analysis with Cox regression analysis. Finally, the prediction model was internally validated using the bootstrap method. Patients were followed for a median of 34.4 (interquartile range, 26.1-46.0) months. Multivariate analysis identified gross total resection (GTR) (HR 0.50, 95% CI: 0.38-0.67), unopened ventricles (HR 0.75 [0.57-0.99]), and MGMT methylation (HR 0.56 [0.41-0.76]) as favorable independent prognostic factors for PFS. GTR (HR 0.67 [0.49-0.92]), unopened ventricles (HR 0.60 [0.44-0.82]), and MGMT methylation (HR 0.54 [0.38-0.76]) were favorable independent prognostic factors for OS. In the process of building the model, we incorporated GTR, ventricular opening, MGMT methylation status, and age. The model had six and five terminal nodules in PFS and OS respectively. We grouped terminal nodes with similar hazard ratios together to form three sub-groups with different PFS and OS (P < 0.001). After the internal verification of bootstrap method, the model had a good fitting and calibration. GTR, unopened ventricles, and MGMT methylation were independently associated with more satisfactory survival. The novel score prediction model which we construct can provide a prognostic reference for GBM.

TUG1-mediated R-loop resolution at microsatellite loci as a prerequisite for cancer cell proliferation

Oncogene-induced DNA replication stress (RS) and consequent pathogenic R-loop formation are known to impede S phase progression. Nonetheless, cancer cells continuously proliferate under such high-stressed conditions through incompletely understood mechanisms. Here, we report taurine upregulated gene 1 (TUG1) long noncoding RNA (lncRNA), which is highly expressed in many types of cancers, as an important regulator of intrinsic R-loop in cancer cells. Under RS conditions, TUG1 is rapidly upregulated via activation of the ATR-CHK1 signaling pathway, interacts with RPA and DHX9, and engages in resolving R-loops at certain loci, particularly at the CA repeat microsatellite loci. Depletion of TUG1 leads to overabundant R-loops and enhanced RS, leading to substantial inhibition of tumor growth. Our data reveal a role of TUG1 as molecule important for resolving R-loop accumulation in cancer cells and suggest targeting TUG1 as a potent therapeutic approach for cancer treatment.

Association of Tumor Treating Fields (TTFields) therapy with survival in newly diagnosed glioblastoma: a systematic review and meta-analysis

PURPOSE

Tumor Treating Fields (TTFields) therapy, an electric field-based cancer treatment, became FDA-approved for patients with newly diagnosed glioblastoma (GBM) in 2015 based on the randomized controlled EF-14 study. Subsequent approvals worldwide and increased adoption over time have raised the question of whether a consistent survival benefit has been observed in the real-world setting, and whether device usage has played a role.

METHODS

We conducted a literature search to identify clinical studies evaluating overall survival (OS) in TTFields-treated patients. Comparative and single-cohort studies were analyzed. Survival curves were pooled using a distribution-free random-effects method.

RESULTS

Among nine studies, seven (N = 1430 patients) compared the addition of TTFields therapy to standard of care (SOC) chemoradiotherapy versus SOC alone and were included in a pooled analysis for OS. Meta-analysis of comparative studies indicated a significant improvement in OS for patients receiving TTFields and SOC versus SOC alone (HR: 0.63; 95% CI 0.53-0.75; p < 0.001). Among real-world post-approval studies, the pooled median OS was 22.6 months (95% CI 17.6-41.2) for TTFields-treated patients, and 17.4 months (95% CI 14.4-21.6) for those not receiving TTFields. Rates of gross total resection were generally higher in the real-world setting, irrespective of TTFields use. Furthermore, for patients included in studies reporting data on device usage (N = 1015), an average usage rate of ≥ 75% was consistently associated with prolonged survival (p < 0.001).

CONCLUSIONS

Meta-analysis of comparative TTFields studies suggests survival may be improved with the addition of TTFields to SOC for patients with newly diagnosed GBM.

Significance of O6-methyl guanine methyltransferase promoter methylation in high grade glioma patients: optimal cutoff point, CpG locus, and genetic assay

PURPOSE

To evaluate O6-methyl guanine methyltransferase (MGMT) promoter methylation status in high grade glioma patients and to identify the best cutoff point as well as the most predictive CpG loci for patients survival.

METHOD

Consecutive high grade glioma patients treated with surgical gross total resection followed by concomitant radiochemotherapy and adjuvant chemotherapy were included in this retrospective observational study. Methylation status of MGMT promoter CpG island of resected tumor tissue were evaluated using next generation sequencing assay. The outcomes were grouped as CpG 70-78, CpG 79-83, CpG 84-87, CpG 70-87, and whole promoter. Quantitative analyses were dichotomized as methylated or unmethylated based on the cutoff points set to %10, and methylation was further graded as <%10 unmethylated, %10-30 low-methylated, and %30-100 high-methylated.

RESULTS

Total of 95 patients with the mean age of 51.50 ± 12.36 years were included in the study. Overall survival (OS) and progression free survival (PFS) were 14.53 ± 1.92 (95% CI 10.77-18.30) and 10.90 ± 2.05 (95% CI 6.89-14.92) months, respectively. MGMT promoter was methylated in 38.2% of cases and high-methylated in 10.5% of cases. Methylation status of MGMT promoter was recognized as a very powerful predictor of OS and PFS. In particular, high-methylation of CpG 79-83 and CpG 84-87 islands at promoter region were strongly associated with better survival outcomes (p < 0.05).

CONCLUSION

Our outcomes support the prognostic value of MGMT promoter methylation in patients with high grade glioma. Sequencing of whole promoter CpG islands demonstrated that methylation of particular CpG sites might predict clinical outcomes more precisely.

Predicting glioblastoma molecular subtypes and prognosis with a multimodal model integrating convolutional neural network, radiomics, and semantics

OBJECTIVE

The aim of this study was to build a convolutional neural network (CNN)-based prediction model of glioblastoma (GBM) molecular subtype diagnosis and prognosis with multimodal features.

METHODS

In total, 222 GBM patients were included in the training set from Sun Yat-sen University Cancer Center (SYSUCC) and 107 GBM patients were included in the validation set from SYSUCC, Xuanwu Hospital Capital Medical University, and the First Hospital of Jilin University. The multimodal model was trained with MR images (pre- and postcontrast T1-weighted images and T2-weighted images), corresponding MRI impression, and clinical patient information. First, the original images were segmented using the Multimodal Brain Tumor Image Segmentation Benchmark toolkit. Convolutional features were extracted using 3D residual deep neural network (ResNet50) and convolutional 3D (C3D). Radiomic features were extracted using pyradiomics. Report texts were converted to word embedding using word2vec. These three types of features were then integrated to train neural networks. Accuracy, precision, recall, and F1-score were used to evaluate the model performance.

RESULTS

The C3D-based model yielded the highest accuracy of 91.11% in the prediction of IDH1 mutation status. Importantly, the addition of semantics improved precision by 11.21% and recall in MGMT promoter methylation status prediction by 14.28%. The areas under the receiver operating characteristic curves of the C3D-based model in the IDH1, ATRX, MGMT, and 1-year prognosis groups were 0.976, 0.953, 0.955, and 0.976, respectively. In external validation, the C3D-based model showed significant improvement in accuracy in the IDH1, ATRX, MGMT, and 1-year prognosis groups, which were 88.30%, 76.67%, 85.71%, and 85.71%, respectively (compared with 3D ResNet50: 83.51%, 66.67%, 82.14%, and 70.79%, respectively).

CONCLUSIONS

The authors propose a novel multimodal model integrating C3D, radiomics, and semantics, which had a great performance in predicting IDH1, ATRX, and MGMT molecular subtypes and the 1-year prognosis of GBM.

ZNF480 influences the prognosis, pathogenesis, and immune microenvironment in patients with lower-grade glioma

ZNF480 has not yet attracted attention in the study of malignant tumors. Therefore, this study attempts to explain the significance of ZNF480 in the pathological process of lower-grade gliomas (LGG) based on large-scale samples from public database sources and in vitro experiments. Reverse transcription quantitative real-time polymerase chain reaction and immunohistochemistry confirmed that ZNF480 was highly expressed at both the mRNA and protein levels in LGG. Prognostic correlation analysis confirmed that the high expression of ZNF480, as an independent pathogenic gene, significantly correlates with poor survival in patients. Furthermore, the expression level of ZNF480 was significantly inhibited in SHG-44 cells treated with ademetionine disulfate tosylate. Gene set enrichment analysis showed that ZNF480 exists in multiple tumor-related signaling pathways, including the Notch signaling pathway. Immunological correlation analysis showed that ZNF480 can promote the LGG microenvironment to a high immune state and significantly enhance the infiltration of various immune cells, such as M2 macrophages. Finally, Spearman analysis showed a positive correlation of ZNF480 with many immune checkpoints, such as PD-L1. Overall, this study reveals for the first time the adverse effects of ZNF480 on the prognosis of tumor patients, which expands our understanding of the molecular mechanisms behind the regulation of ZNF480. We believe that the high expression of ZNF480 in LGG may be valuable for molecular targeted therapy or combined immunotherapy.

A Novel Isotope-labeled Small Molecule Probe CC12 for Anti-glioma via Suppressing LYN-mediated Progression and Activating Apoptosis Pathways

Background: Glioblastoma multiforme (GBM) is the most lethal malignancy in brain, which is surrounded by the blood-brain barrier (BBB), which limits the efficacy of standard treatments. Developing an effective drug that can penetrate the blood-brain barrier (BBB) remains a critical challenge in the fight against GBM. CC12 (NSC749232) is an anthraquinone tetraheterocyclic homolog with a lipophilic structure that may facilitate penetration of the brain area. Methods: We used temozolomide sensitive and resistance GBM cells and animal model to identify the CC12 delivery, anti-tumor potential and its underlying mechanism. Results: Importantly, toxicity triggered by CC12 was not associated with the methyl guanine-DNA methyl transferase (MGMT) methylation status which revealed a greater application potential compared to temozolomide. Alexa F488 cadaverine-labelled CC12 successfully infiltrated into the GBM sphere; in addition, ⁶⁸Ga-labeled CC12 was also found in the orthotopic GBM area. After passing BBB, CC12 initiated both caspase-dependent intrinsic/extrinsic apoptosis pathways and apoptosis-inducing factor, EndoG-related caspase-independent apoptosis signaling in GBM. RNA sequence analysis from The Cancer Genome Atlas indicated that LYN was overexpressed in GBM is associated with poorer overall survival. We proved that targeting of LYN by CC12 may diminish GBM progression and suppress it downstream factors such as signal transduction and activator of extracellular signal-regulated kinases (ERK)/transcription 3 (STAT3)/nuclear factor (NF)-κB. CC12 was also found to participate in suppressing GBM metastasis and dysregulation of the epithelial-mesenchymal transition (EMT) through inactivation of the LYN axis. Conclusion: CC12, a newly developed BBB-penetrating drug, was found to possess an anti-GBM capacity via initiating an apoptotic mechanism and disrupting LYN/ERK/STAT3/NF-κB-regulated GBM progression.

MGMT Promoter Methylation: Prognostication beyond Treatment Response

MGMT promoter methylation is related to the increased sensitivity of tumour tissue to chemotherapy with temozolomide (TMZ) and thus to improved patient survival. However, it is unclear how the extent of MGMT promoter methylation affects outcomes. In our study, a single-centre retrospective study, we explore the impact of MGMT promoter methylation in patients with glioblastoma who were operated upon with 5-ALA. Demographic, clinical and histology data, and survival rates were assessed. A total of 69 patients formed the study group (mean age 53.75 ± 15.51 years old). Positive 5-ALA fluorescence was noted in 79.41%. A higher percentage of MGMT promoter methylation was related to lower preoperative tumour volume (p = 0.003), a lower likelihood of 5-ALA positive fluorescence (p = 0.041) and a larger extent of resection EoR (p = 0.041). A higher MGMT promoter methylation rate was also related to improved progression-free survival (PFS) and overall survival (OS) (p = 0.008 and p = 0.006, respectively), even when adjusted for the extent of resection (p = 0.034 and p = 0.042, respectively). A higher number of adjuvant chemotherapy cycles was also related to longer PFS and OS (p = 0.049 and p = 0.030, respectively). Therefore, this study suggests MGMT promoter methylation should be considered as a continuous variable. It is a prognostic factor that goes beyond sensitivity to chemotherapy treatment, as a higher percentage of methylation is related not only to increased EoR and increased PFS and OS, but also to lower tumour volume at presentation and a lower likelihood of 5-ALA fluorescence intraoperatively.

From Theory to Practice: Implementing the WHO 2021 Classification of Adult Diffuse Gliomas in Neuropathology Diagnosis

Diffuse gliomas are the most common type of primary central nervous system (CNS) neoplasm to affect the adult population. The diagnosis of adult diffuse gliomas is dependent upon the integration of morphological features of the tumour with its underlying molecular alterations, and the integrative diagnosis has become of increased importance in the fifth edition of the WHO classification of CNS neoplasms (WHO CNS5). The three major diagnostic entities of adult diffuse gliomas are as follows: (1) astrocytoma, IDH-mutant; (2) oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and (3) glioblastoma, IDH-wildtype. The aim of this review is to summarize the pathophysiology, pathology, molecular characteristics, and major diagnostic updates encountered in WHO CNS5 of adult diffuse gliomas. Finally, the application of implementing the necessary molecular tests for diagnostic workup of these entities in the pathology laboratory setting is discussed.

GTP signaling links metabolism, DNA repair, and responses to genotoxic stress

How cell metabolism regulates DNA repair is incompletely understood. Here, we define a GTP-mediated signaling cascade that links metabolism to DNA repair and has significant therapeutic implications. GTP, but not other nucleotides, regulates the activity of Rac1, a G protein, that promotes the dephosphorylation of serine 323 on Abl-interactor 1 (Abi-1) by protein phosphatase 5 (PP5). Dephosphorylated Abi-1, a protein previously not known to activate DNA repair, promotes non-homologous end joining. In patients and mouse models of glioblastoma, Rac1 and dephosphorylated Abi-1 mediate DNA repair and resistance to standard of care genotoxic treatments. The GTP-Rac1-PP5-Abi-1 signaling axis is not limited to brain cancer, as GTP supplementation promotes DNA repair and Abi-1-S323 dephosphorylation in non-malignant cells and protects mouse tissues from genotoxic insult. This unexpected ability of GTP to regulate DNA repair independently of deoxynucleotide pools has important implications for normal physiology and cancer treatment.

National-level overall survival patterns for molecularly-defined diffuse glioma types in the United States

BACKGROUND

Molecularly-defined diffuse glioma types-including IDH-wildtype glioblastoma, IDH-mutant astrocytoma, IDH-mutant 1p/19q-codeleted oligodendroglioma, and H3 K27M-mutant diffuse midline glioma-were incorporated into U.S. cancer registry reporting for individuals with brain tumors beginning in 2018. We leveraged these new data to estimate the national-level overall survival (OS) patterns associated with glioma integrated diagnoses.

METHODS

Individuals diagnosed with diffuse gliomas in 2018 and had brain molecular marker data were identified within the U.S. National Cancer Database. OS was estimated using Kaplan-Meier methods and stratified by WHO CNS grade, age, sex, tumor size, treatment, extent of resection, and MGMT promoter methylation. Additionally, the effects of WHO CNS grade were examined among individuals with IDH-wildtype astrocytic gliomas.

RESULTS

8651 individuals were identified. One-year OS was 53.7% for WHO grade 4 IDH-wildtype glioblastomas; 98.0%, 92.4%, and 76.3% for WHO grade 2, 3, and 4 IDH-mutant astrocytomas, respectively; 97.9% and 94.4% for WHO grade 2 and 3 IDH-mutant 1p/19q-codeleted oligodendrogliomas, respectively; and 55.9% for H3 K27M-mutant diffuse midline gliomas. Among IDH-wildtype glioblastomas, median OS was 17.1 months and 12.4 months for methylated and unmethylated MGMT promoters. Additionally, IDH-wildtype diffuse astrocytic gliomas reported as WHO grade 2 or 3 demonstrated longer OS compared to grade 4 tumors (both P < .001).

CONCLUSIONS

Our findings provide the initial national OS estimates for molecularly-defined diffuse gliomas in the United States and illustrate the importance of incorporating such data into cancer registry reporting.

The predictive value of partial MGMT promoter methylation for IDH-wild-type glioblastoma patients

Background

Glioblastoma patients with hypermethylation of the O6-methylguanine-methyltransferase (MGMT) gene promoter have significantly improved survival when treated with temozolomide compared to patients with unmethylation of the MGMT promoter. However, the prognostic and predictive significance of partial MGMT promoter methylation is unclear.

Methods

The National Cancer Database was queried for patients newly diagnosed in 2018 with histopathologically confirmed isocitrate dehydrogenase (IDH)-wildtype glioblastoma. The overall survival (OS) associated with MGMT promoter methylation status was assessed using multivariable Cox regression with Bonferroni correction for multiple testing (P < .008 was significant).

Results

Three thousand eight hundred twenty-five newly diagnosed IDH-wildtype glioblastoma patients were identified. The MGMT promoter was unmethylated in 58.7% (n = 2245), partially methylated in 4.8% (n = 183), hypermethylated in 3.5% (n = 133), and methylated not otherwise specified (NOS; likely consisting predominantly of hypermethylated cases) in 33.0% (n = 1264) of cases. Among patients that received first-line single-agent chemotherapy (ie likely temozolomide), compared to partial methylation (referent), MGMT promoter unmethylation was associated with worse OS (hazard ratio [HR] 1.94; 95% confidence interval [95 CI]: 1.54-2.44; P < .001) in multivariable Cox regression adjusted for major prognostic confounders. In contrast, a significant OS difference was not observed between partially methylated promoters and either hypermethylated (HR 1.02; 95 CI: 0.72-1.46; P = .90) or methylated NOS (HR 0.99; 95 CI: 0.78-1.26; P = .93) promoters. Among IDH-wildtype glioblastoma patients who did not receive first-line chemotherapy, MGMT promoter methylation status was not associated with significant differences in OS (P = 0.39-0.83).

Conclusions

Compared to MGMT promoter unmethylation, partial methylation was predictive of improved OS among IDH-wildtype glioblastoma patients treated with first-line single-agent chemotherapy-supporting the use of temozolomide therapy in these patients.

Exploring Novel Therapeutic Opportunities for Glioblastoma Using Patient-Derived Cell Cultures

Glioblastomas (GBM) are the most common, primary brain tumors in adults. Despite advances in neurosurgery and radio- and chemotherapy, the median survival of GBM patients is 15 months. Recent large-scale genomic, transcriptomic and epigenetic analyses have shown the cellular and molecular heterogeneity of GBMs, which hampers the outcomes of standard therapies. We have established 13 GBM-derived cell cultures from fresh tumor specimens and characterized them molecularly using RNA-seq, immunoblotting and immunocytochemistry. Evaluation of proneural (OLIG2, IDH1^R132H, TP53 and PDGFRα), classical (EGFR) and mesenchymal markers (CHI3L1/YKL40, CD44 and phospho-STAT3), and the expression of pluripotency (SOX2, OLIG2, NESTIN) and differentiation (GFAP, MAP2, β-Tubulin III) markers revealed the striking intertumor heterogeneity of primary GBM cell cultures. Upregulated expression of VIMENTIN, N-CADHERIN and CD44 at the mRNA/protein levels suggested increased epithelial-to-mesenchymal transition (EMT) in most studied cell cultures. The effects of temozolomide (TMZ) or doxorubicin (DOX) were tested in three GBM-derived cell cultures with different methylation status of the MGMT promoter. Amongst TMZ- or DOX-treated cultures, the strongest accumulation of the apoptotic markers caspase 7 and PARP were found in WG4 cells with methylated MGMT, suggesting that its methylation status predicts vulnerability to both drugs. As many GBM-derived cells showed high EGFR levels, we tested the effects of AG1478, an EGFR inhibitor, on downstream signaling pathways. AG1478 caused decreased levels of phospho-STAT3, and thus inhibition of active STAT3 augmented antitumor effects of DOX and TMZ in cells with methylated and intermediate status of MGMT. Altogether, our findings show that GBM-derived cell cultures mimic the considerable tumor heterogeneity, and that identifying patient-specific signaling vulnerabilities can assist in overcoming therapy resistance, by providing personalized combinatorial treatment recommendations.

Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans

Accurate radiogenomic classification of brain tumors is important to improve the standard of diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we propose a novel two-stage MGMT Promoter Methylation Prediction (MGMT-PMP) system that extracts latent features fused with radiomic features predicting the genetic subtype of glioblastoma. A novel fine-tuned deep learning architecture, namely Deep Learning Radiomic Feature Extraction (DLRFE) module, is proposed for latent feature extraction that fuses the quantitative knowledge to the spatial distribution and the size of tumorous structure through radiomic features: (GLCM, HOG, and LBP). The application of the novice rejection algorithm has been found significantly effective in selecting and isolating the negative training instances out of the original dataset. The fused feature vectors are then used for training and testing by k-NN and SVM classifiers. The 2021 RSNA Brain Tumor challenge dataset (BraTS-2021) consists of four structural mpMRIs, viz. fluid-attenuated inversion-recovery, T1-weighted, T1-weighted contrast enhancement, and T2-weighted. We evaluated the classification performance, for the very first time in published form, in terms of measures like accuracy, F₁-score, and Matthews correlation coefficient. The Jackknife tenfold cross-validation was used for training and testing BraTS-2021 dataset validation. The highest classification performance is (96.84 ± 0.09)%, (96.08 ± 0.10)%, and (97.44 ± 0.14)% as accuracy, sensitivity, and specificity respectively to detect MGMT methylation status for patients suffering from glioblastoma. Deep learning feature extraction with radiogenomic features, fusing imaging phenotypes and molecular structure, using rejection algorithm has been found to perform outclass capable of detecting MGMT methylation status of glioblastoma patients. The approach relates the genomic variation with radiomic features forming a bridge between two areas of research that may prove useful for clinical treatment planning leading to better outcomes.

Cellular and molecular features related to exceptional therapy response and extreme long-term survival in glioblastoma

Glioblastoma Multiforme (GBM) remains the most common malignant primary brain tumor with a dismal prognosis that rarely exceeds beyond 2 years despite extensive therapy, which consists of maximal safe surgical resection, radiotherapy, and/or chemotherapy. Recently, it has become clear that GBM is not one homogeneous entity and that both intra-and intertumoral heterogeneity contributes significantly to differences in tumoral behavior which may consequently be responsible for differences in survival. Strikingly and in spite of its dismal prognosis, small fractions of GBM patients seem to display extremely long survival, defined as surviving over 10 years after diagnosis, compared to the large majority of patients. Although the underlying mechanisms for this peculiarity remain largely unknown, emerging data suggest that still poorly characterized both cellular and molecular factors of the tumor microenvironment and their interplay probably play an important role. We hereby give an extensive overview of what is yet known about these cellular and molecular features shaping extreme long survival in GBM.