Weller, Michael

Abstract Oncogenic BRAF alterations occur in a subset of diffuse gliomas across WHO grades and are increasingly identified through modern molecular diagnostics. In addition to standard glioma therapies, targeted treatments are available for patients with BRAF-altered glioma supported by variable evidence spanning randomized trials, single-arm studies, and real-world evidence. This joint consensus review from the Society for Neuro-Oncology (SNO) and the European Association of Neuro-Oncology (EANO) synthesizes current knowledge on the diagnosis and management of BRAF-altered gliomas across age groups, tumor grades, and lines of therapy. Particular emphasis is placed on expert consensus in clinical scenarios where high-quality trial evidence remains limited. The review addresses rationale testing for BRAF alterations, selection, and monitoring of targeted therapies, management of treatment-related toxicities, approaches to resistance, and priorities for future research. It aims to provide practical, evidence-based guidance for clinicians while highlighting gaps to inform prospective studies.

PURPOSE Integrating external control data into clinical trial designs and analyses has the potential to accelerate drug development processes. We reanalyzed the three experimental arms of the Individual Screening Trial of Innovative Glioblastoma Therapy (INSIGhT), a randomized phase II platform trial in newly diagnosed O 6 -methylguanine-DNA methyltransferase-unmethylated glioblastoma (ClinicalTrials.gov identifier: NCT02977780 ). To evaluate the validity of using external data sets, we compared treatment effect estimates based on internal INSIGhT control data and matched external control data. METHODS The three experimental arms of INSIGhT (abemaciclib [n = 72], neratinib [n = 80], and CC-115 [n = 12]) did not improve survival compared with internal controls (standard chemoradiation [n = 70]). We derived external control patient-level data from multiple real-world and clinical trial data sets. We applied propensity score matching and Cox proportional hazards models to estimate treatment effects with external controls. Additionally, using this glioblastoma (GBM) data collection, we specified simulation scenarios to evaluate trial designs that integrate external controls. RESULTS After matching to external controls, no survival benefit was observed for patients receiving abemaciclib (hazard ratio [HR], 1.00 [95% CI, 0.75 to 1.34]), neratinib (HR, 0.93 [95% CI, 0.70 to 1.24]), or CC-115 (HR, 0.88 [95% CI, 0.41 to 1.88]). Simulations, together with the INSIGhT data and a collection of GBM data sets, allowed us to examine efficiencies and risks of clinical trial designs that leverage external control data. CONCLUSION The use of carefully matched external controls, to replace or augment the internal controls of INSIGhT, produced treatment effect estimates that were similar to previously published analyses. Single-arm trial designs and hybrid randomized designs incorporating propensity score–matched external control data evaluated treatment effects in the early-phase testing of experimental therapies in newly diagnosed GBM. The validity of this approach and risks of bias depended on the availability of comprehensive and accurate data on all potential confounders, in the absence of unmeasured confounding.

PURPOSE GBM AGILE (ClinicalTrials.gov identifier: NCT03970447 ) is a phase II/III Bayesian adaptive platform registration trial testing multiple arms against a common control; the primary end point is overall survival (OS). Regorafenib, a multikinase inhibitor, showed OS benefit in recurrent (RD) glioblastoma in the phase II REGOMA trial and entered GBM AGILE as the first investigational arm. METHODS Patient subtypes included in the regorafenib arm of GBM AGILE were newly diagnosed unmethylated (NDU) and RD glioblastoma. Prospective defined sets of subtypes, or arm signatures, were NDU, RD, and all (NDU + RD). As the first investigational arm in GBM AGILE, regorafenib was equally randomized to the control arm. Treatment in the control arm is temozolomide + radiotherapy (in newly diagnosed) or lomustine (in RD). Efficacy was assessed by OS hazard ratio (HR), arm/control, and demonstrated when the Bayesian probability of benefit (HR <1.00) was ≥98%. Analysis was performed monthly for limited efficacy, which occurs when the Bayesian predictive power is <25% for all signatures, and determines stopping enrollment. Follow-up continued for 12 months after accrual stopped. RESULTS When the predictive power was <25% in all predefined signatures for regorafenib, accrual stopped for limited efficacy. The final analysis did not demonstrate OS improvement in the regorafenib arm in RD nor NDU glioblastoma. Median HRs were 1.05 (NDU), 1.07 (RD), and 1.07 (all) with final probabilities of benefit (HR <1.00) of 0.421 (NDU), 0.312 (RD), and 0.296 (all). Regorafenib was associated with increased toxicity relative to control. CONCLUSION GBM AGILE did not show superiority of regorafenib over control in RD (lomustine) or NDU (temozolomide + radiotherapy) glioblastoma, yet caused increased toxicities. Regorafenib has been removed from National Comprehensive Cancer Network guidelines as a treatment option for RD.

Abstract Background DNA methylation profiling can be used to robustly predict postsurgical outcomes and response to radiotherapy (RT) for meningioma patients. To allow for seamless integration of these complementary models into clinical practice, a practical framework is needed. Methods We leveraged a cohort of nearly 2000 surgically-treated meningiomas with DNA methylation profiling and clinical outcomes data. Existing methylation-based prediction models were dichotomized to yield four risk groups: low and high recurrent risk, each with RT sensitive and resistant subgroups. Risk groups were correlated with progression-free survival in the context of existing biomarkers including extent of resection and WHO grade. Results We first demonstrated that all risk groups benefit from gross total resection. All “high-risk, RT sensitive” tumors (n = 306, 15.7%) also benefited from adjuvant RT: after GTR, median PFS increased from 4.68 (4.13-9.48) years to not reached (P = .003); after subtotal resection (STR), from 2.12 (1.59-3.02) to 4.09 (3.41-not reached) years (P = .004). “Low-risk, RT sensitive cases” (n = 1207, 61.8%) also benefited from RT after STR (median PFS 7.39 (6.66-12.8) vs. 16.53 (10.35-not reached) years, P = .03), suggesting that RT be considered in these patients. Neither “low-risk RT resistant” (n = 84, 4.3%) nor “high-risk RT resistant” (n = 356, 18.2%) cases benefited from RT, and the latter group was associated with universally poor outcomes. Conclusions We identify methylation-defined risk groups of meningioma for which additional benefit is gained from adjuvant RT, leading to a clinical decision-making framework for straightforward integration of molecular models into clinical practice.

Abstract Glioblastoma is the most common type of malignant primary brain tumor and a major cause of morbidity and mortality. In 2021, the World Health Organization updated the classification of Central Nervous System (CNS) tumors to restrict glioblastomas to isocitrate dehydrogenase-wildtype (IDHwt) tumors, improving understanding of the prognosis and optimal therapy for these tumors. This revision also enables more homogeneous populations of patients to be enrolled in clinical trials, facilitating the evaluation of novel therapies. In this updated consensus review from the Society for Neuro-Oncology (SNO) and the European Association of Neuro-Oncology (EANO), the current management of patients with glioblastoma is discussed. In addition, novel therapies such as immunotherapies, viral therapies, targeted molecular therapies, theranostics, and antibody–drug conjugates will be reviewed, as well as the current challenges and future directions for research.

Abstract This review explores the pivotal role of preanalytical variables in bringing liquid biopsy approaches into the clinic for brain tumors. Preanalytical variables encompass a range of critical issues, from blood sample collection and handling to the impact of tumor heterogeneity and patient-specific factors. These variables introduce challenges such as false positives, false negatives, and variability in the analysis of tumor signals, which can hinder the diagnostic and prognostic utility of liquid biopsies. Understanding the nuances of preanalytical variables is essential for the successful implementation of liquid biopsy in clinical settings. This paper delves into strategies aimed at mitigating the influence of preanalytical variables by emphasizing the importance of standardized sample collection protocols, optimized sample processing and storage, quality control measures, and the integration of multiple liquid biopsy modalities.

Abstract Background Instruments to assess patient-reported outcomes (PRO) should generate high-quality evidence. Reliable PRO evidence is essential to policymakers, in conjunction with outcomes such as survival and radiological response, to understand the net clinical benefit of antitumor treatments. This study aimed to establish the content validity of 215 identified PRO measures used in patients with brain tumors. Methods A survey (n = 148 items) was developed reflecting aspects of the WHO International Classification of Functioning, Disability, and Health (ICF) framework. Patients with brain tumors, their proxies, and healthcare professionals (HCPs) were asked to rate each survey item on relevance. An item was considered a relevant issue if ≥25% of the patients or proxies or ≥50% of the HCPs considered that item to be an issue. Next, all items in the identified PRO measures were linked to ICF and relevant items in the survey, and the percentage of content coverage was calculated. Results In total, 114 patients, 71 proxies, and 65 HCPs from different countries completed the survey. Fifty-six of 148 (37.8%) items in the survey were considered relevant. The most important aspects mentioned by both patients and proxies were difficulty concentrating, difficulty remembering, multitasking, and handling stress. Depending on the definition, between 35% and 49% of PRO measures were considered to have sufficient content validity (≥80% coverage). Conclusion The content validity was insufficient in more than half of the identified PRO measures, particularly multidimensional measures. Future research should investigate whether different approaches to PRO assessment better meet the needs of all stakeholders.

Abstract Background Despite advances in our understanding of the molecular underpinnings of meningioma progression and innovations in systemic and local treatments, recurrent meningiomas remain a substantial therapeutic challenge. The objective of this systematic review and meta-analysis is to provide a historical baseline, contemporary analysis, and propose a “rate of probable interest” to inform future clinical trial design and development on behalf of the Response Assessment in Neuro-Oncology meningioma group. Methods PubMed, ClinicalTrials.gov, and ASCOpubs databases were screened for clinical trials evaluating the activity of systemic therapies for adults with recurrent meningiomas. The pooled progression-free survival at 6-months and 1-year (PFS-6 and PFS-1 year) values were calculated using the random effects technique with I2 indices. Results The pooled PFS-6 and PFS-1 year rates for recurrent WHO grade 1 meningiomas were 43.6% (95% CI: 22.7-67.0%, I2 = 80%) and 21.7% (95% CI: 6.2-53.9%, I2 = 76%), and for grades 2-3 meningiomas, the PFS-6 was 38.0% (95% CI: 28.3-48.8%, I2 = 68%). In the targeted therapy group, PFS-6 and PFS-1 year rates stood at 62.0% (I2 = 58%) and 49.0% (I2 = 63%) for grade 1, while for grades 2-3 tumors, the PFS-6 rates with targeted therapy and immunotherapy were 42.1% (I² = 60%) and 46.0% (I² = 0%), respectively. The benchmarks were set at 67% and 54% for PFS-6 and PFS-1 year for grade 1 tumors, and PFS-6 of 49% for grades 2-3 tumors. Conclusions Several studies have reported outcomes in patients with recurrent meningiomas testing a variety of agents with modest, but variable and progressively increasing activity. In this context, we recommend new benchmarks for future trials to define efficacy of future investigational therapies.

Abstract GBM AGILE(NCT03970447) is a phase 2/3 Bayesian adaptive registration platform trial testing multiple therapies against a common control. Paxalisib, a PI3K/mTOR inhibitor, is the 3rd arm in the trial to conclude evaluation. METHODS Paxalisib was open to patients with newly diagnosed unmethylated (NDU) and recurrent (RD) glioblastoma, with three possible signatures: NDU, RD, and All(NDU+RD). Arm enrollment occurred Dec2020 through May2022. Control patients were enrolled from study initiation (July2019) and were treated with temozolomide(NDU) or lomustine(RD). GBM AGILE investigational arms have 1 or 2 stages, with adaptive randomization in stage 1 and fixed randomization if arms continue to stage 2. Efficacy is based on OS hazard ratio(HR) of Arm/Control. Efficacy goal is final Bayesian probability ≥ 98% for HR&lt;1.00 in combined Stages. An Arm continues to Stage 2 if Bayesian predictive power (PP) ≥ 0.8. An Arm stops accruing in Stage 1 if it reaches maximal sample size(N) or does not meet a minimum efficacy threshold (PP&lt;0.25 for all signatures when N&gt;50). Clinical cut-off is 12 months after accrual stops. The maximum N for paxalisib was approximately 150(Stage 1) and 50(Stage 2). RESULTS After paxalisib reached &gt;150 patients in Stage 1, accrual stopped [Paxalisib/control N 54/75(NDU), 100/188(RD)]. Neither PP thresholds for moving to Stage 2 nor stopping for minimum efficacy were met. Following an unplanned public disclosure that the arm did not continue to stage 2, clinical cut-off for final analysis (planned May2023) was updated to public disclosure date (August2022). At final analysis mean HRs were 0.89(NDU), 1.25(RD), 1.05(All), probabilities of HR&lt;1.00 of 0.72(NDU), 0.076(RD), 0.398(All). Model estimated median OS paxalisib/control (months) were 14.77/13.84(NDU) and 8.58/10.06(RD). CONCLUSION Paxalisib did not show survival benefit over cumulative control in final primary analysis; additional secondary analyses are being considered. GBM AGILE continues to rapidly and efficiently assess therapies in ND and RD glioblastoma.

Abstract Brain tumor diagnostics have significantly evolved with the use of positron emission tomography (PET) and advanced magnetic resonance imaging (MRI) techniques. In addition to anatomical MRI, these modalities may provide valuable information for several clinical applications such as differential diagnosis, delineation of tumor extent, prognostication, differentiation between tumor relapse and treatment-related changes, and the evaluation of response to anticancer therapy. In particular, joint recommendations of the Response Assessment in Neuro-Oncology (RANO) Group, the European Association of Neuro-oncology, and major European and American Nuclear Medicine societies highlighted that the additional clinical value of radiolabeled amino acids compared to anatomical MRI alone is outstanding and that its widespread clinical use should be supported. For advanced MRI and its steadily increasing use in clinical practice, the Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition provided more recently an updated acquisition protocol for the widely used dynamic susceptibility contrast perfusion MRI. Besides amino acid PET and perfusion MRI, other PET tracers and advanced MRI techniques (e.g. MR spectroscopy) are of considerable clinical interest and are increasingly integrated into everyday clinical practice. Nevertheless, these modalities have shortcomings which should be considered in clinical routine. This comprehensive review provides an overview of potential challenges, limitations, and pitfalls associated with PET imaging and advanced MRI techniques in patients with gliomas or brain metastases. Despite these issues, PET imaging and advanced MRI techniques continue to play an indispensable role in brain tumor management. Acknowledging and mitigating these challenges through interdisciplinary collaboration, standardized protocols, and continuous innovation will further enhance the utility of these modalities in guiding optimal patient care.