DNA damage response in brain tumors: A Society for Neuro-Oncology consensus review on mechanisms and translational efforts in neuro-oncology.

DNA damage response (DDR) mechanisms are critical to maintenance of overall genomic stability, and their dysfunction can contribute to oncogenesis. Significant advances in our understanding of DDR pathways have raised the possibility of developing therapies that exploit these processes. In this expert-driven consensus review, we examine mechanisms of response to DNA damage, progress in development of DDR inhibitors in IDH-wild-type glioblastoma and IDH-mutant gliomas, and other important considerations such as biomarker development, preclinical models, combination therapies, mechanisms of resistance and clinical trial design considerations.

Clinical and Genomic Predictors of Adverse Events in Newly Diagnosed Glioblastoma.

PURPOSE: Adverse clinical events cause significant morbidity in patients with GBM (GBM). We examined whether genomic alterations were associated with AE (AE) in patients with GBM. EXPERIMENTAL DESIGN: We identified adults with histologically confirmed IDH-wild-type GBM with targeted next-generation sequencing (OncoPanel) at Dana Farber Cancer Institute from 2013 to 2019. Seizure at presentation, lymphopenia, thromboembolic events, pseudoprogression, and early progression (within 6 months of diagnosis) were identified as AE. The biologic function of genetic variants was categorized as loss-of-function (LoF), no change in function, or gain-of-function (GoF) using a somatic tumor mutation knowledge base (OncoKB) and consensus protein function predictions. Associations between functional genomic alterations and AE were examined using univariate logistic regressions and multivariable regressions adjusted for additional clinical predictors. RESULTS: Our study included 470 patients diagnosed with GBM who met the study criteria. We focused on 105 genes that had sequencing data available for ≥ 90% of the patients and were altered in ≥10% of the cohort. Following false-discovery rate (FDR) correction and multivariable adjustment, the TP53, RB1, IGF1R, and DIS3 LoF alterations were associated with lower odds of seizures, while EGFR, SMARCA4, GNA11, BRD4, and TCF3 GoF and SETD2 LoF alterations were associated with higher odds of seizures. For all other AE of interest, no significant associations were found with genomic alterations following FDR correction. CONCLUSIONS: Genomic biomarkers based on functional variant analysis of a routine clinical panel may help identify AE in GBM, particularly seizures. Identifying these risk factors could improve the management of patients through better supportive care and consideration of prophylactic therapies.

Re-irradiation of recurrent IDH-wildtype glioblastoma in the bevacizumab and immunotherapy era: Target delineation, outcomes and patterns of recurrence.

Introduction and background: While recurrent glioblastoma patients are often treated with re-irradiation, there is limited data on the use of re-irradiation in the setting of bevacizumab (BEV), temozolomide (TMZ) re-challenge, or immune checkpoint inhibition (ICI). We describe target delineation in patients with prior anti-angiogenic therapy, assess safety and efficacy of re-irradiation, and evaluate patterns of recurrence. Materials and methods: Patients with a histologically confirmed diagnosis of glioblastoma treated at a single institution between 2013 and 2021 with re-irradiation were included. Tumor, treatment and clinical data were collected. Logistic and Cox regression analysis were used for statistical analysis. Results: One hundred and seventeen recurrent glioblastoma patients were identified, receiving 129 courses of re-irradiation. In 66 % (85/129) of cases, patients had prior BEV. In the 80 patients (62 %) with available re-irradiation plans, 20 (25 %) had all T2/FLAIR abnormality included in the gross tumor volume (GTV). Median overall survival (OS) for the cohort was 7.3 months, and median progression-free survival (PFS) was 3.6 months. Acute CTCAE grade ≥ 3 toxicity occurred in 8 % of cases. Concurrent use of TMZ or ICI was not associated with improved OS nor PFS. On multivariable analysis, higher KPS was significantly associated with longer OS (p < 0.01). On subgroup analysis, patients with prior BEV had significantly more marginal recurrences than those without (26 % vs. 13 %, p < 0.01). Conclusion: Re-irradiation can be safely employed in recurrent glioblastoma patients. Marginal recurrence was more frequent in patients with prior BEV, suggesting a need to consider more inclusive treatment volumes incorporating T2/FLAIR abnormality.

External validation of three prognostic scores for brain metastasis velocity in patients treated with intracranial stereotactic radiotherapy.

BACKGROUND AND INTRODUCTION: Brain metastasis velocity (BMV) has been proposed as a prognostic factor for overall survival (OS) in patients with brain metastases (BMs). In this study, we conducted an external validation and comparative assessment of the performance of all three BMV scores. MATERIALS AND METHODS: Patients treated with intracranial stereotactic radiotherapy (SRT) for BM at a single center between 2014 and 2018 were identified. Where possible, all three BMV scores were calculated. Log-rank tests and linear, logistic and Cox regression analysis were used for validation and predictor identification of OS. RESULTS: For 333 of 384 brain metastasis patients, at least one BMV score could be calculated. In a sub-group of 187 patients, "classic" BMV was validated as categorical (p < 0.0001) and continuous variable (HR 1.02; 95% CI 1.02-1.03; p < 0.0001). In a sub-group of 284 patients, "initial" BMV was validated as categorical variable (high-risk vs. low-risk; p < 0.01), but not as continuous variable (HR 1.02; 95% CI 0.99-1.04; p = 0.224). "Volume-based" BMV could not be validated in a sub-group of 104 patients. On multivariable Cox regression analysis, iBMV (HR 1.85; 95% CI 1.01-3.38; p < 0.05) and cBMV (HR 2.32; 95% CI 1.15 4.68; p < 0.05) were predictors for OS for intermediate-risk patients after first SRT and first DBFs, respectively. cBMV proved to be the dominant predictor for OS for high-risk patients (HR 2.99; 95% CI 1.30-6.91; p < 0.05). CONCLUSION: This study externally validated cBMV and iBMV as prognostic scores for OS in patients treated with SRT for BMs whereas validation of vBMV was not achieved.

RANO 2.0: Update to the Response Assessment in Neuro-Oncology Criteria for High- and Low-Grade Gliomas in Adults.

PURPOSE: The Response Assessment in Neuro-Oncology (RANO) criteria for high-grade gliomas (RANO-HGG) and low-grade gliomas (RANO-LGG) were developed to improve reliability of response assessment in glioma trials. Over time, some limitations of these criteria were identified, and challenges emerged regarding integrating features of the modified RANO (mRANO) or the immunotherapy RANO (iRANO) criteria. METHODS: Informed by data from studies evaluating the different criteria, updates to the RANO criteria are proposed (RANO 2.0). RESULTS: We recommend a standard set of criteria for both high- and low-grade gliomas, to be used for all trials regardless of the treatment modalities being evaluated. In the newly diagnosed setting, the postradiotherapy magnetic resonance imaging (MRI), rather than the postsurgical MRI, will be used as the baseline for comparison with subsequent scans. Since the incidence of pseudoprogression is high in the 12 weeks after radiotherapy, continuation of treatment and confirmation of progression during this period with a repeat MRI, or histopathologic evidence of unequivocal recurrent tumor, are required to define tumor progression. However, confirmation scans are not mandatory after this period nor for the evaluation of treatment for recurrent tumors. For treatments with a high likelihood of pseudoprogression, mandatory confirmation of progression with a repeat MRI is highly recommended. The primary measurement remains the maximum cross-sectional area of tumor (two-dimensional) but volumetric measurements are an option. For IDH wild-type glioblastoma, the nonenhancing disease will no longer be evaluated except when assessing response to antiangiogenic agents. In IDH-mutated tumors with a significant nonenhancing component, clinical trials may require evaluating both the enhancing and nonenhancing tumor components for response assessment. CONCLUSION: The revised RANO 2.0 criteria refine response assessment in gliomas.

Inaugural Results of the Individualized Screening Trial of Innovative Glioblastoma Therapy: A Phase II Platform Trial for Newly Diagnosed Glioblastoma Using Bayesian Adaptive Randomization.

PURPOSE: The Individualized Screening Trial of Innovative Glioblastoma Therapy (INSIGhT) is a phase II platform trial that uses response adaptive randomization and genomic profiling to efficiently identify novel therapies for phase III testing. Three initial experimental arms (abemaciclib [a cyclin-dependent kinase [CDK]4/6 inhibitor], neratinib [an epidermal growth factor receptor [EGFR]/human epidermal growth factor receptor 2 inhibitor], and CC-115 [a deoxyribonucleic acid-dependent protein kinase/mammalian target of rapamycin inhibitor]) were simultaneously evaluated against a common control arm. We report the results for each arm and examine the feasibility and conduct of the adaptive platform design. PATIENTS AND METHODS: Patients with newly diagnosed O6-methylguanine-DNA methyltransferase-unmethylated glioblastoma were eligible if they had tumor genotyping to identify prespecified biomarker subpopulations of dominant glioblastoma signaling pathways (EGFR, phosphatidylinositol 3-kinase, and CDK). Initial random assignment was 1:1:1:1 between control (radiation therapy and temozolomide) and the experimental arms. Subsequent Bayesian adaptive randomization was incorporated on the basis of biomarker-specific progression-free survival (PFS) data. The primary end point was overall survival (OS), and one-sided P values are reported. The trial is registered with ClinicalTrials.gov (identifier: NCT02977780). RESULTS: Two hundred thirty-seven patients were treated (71 control; 73 abemaciclib; 81 neratinib; 12 CC-115) in years 2017-2021. Abemaciclib and neratinib were well tolerated, but CC-115 was associated with ≥ grade 3 treatment-related toxicity in 58% of patients. PFS was significantly longer with abemaciclib (hazard ratio [HR], 0.72; 95% CI, 0.49 to 1.06; one-sided P = .046) and neratinib (HR, 0.72; 95% CI, 0.50 to 1.02; one-sided P = .033) relative to the control arm but there was no PFS benefit with CC-115 (one-sided P = .523). None of the experimental therapies demonstrated a significant OS benefit (P > .05). CONCLUSION: The INSIGhT design enabled efficient simultaneous testing of three experimental agents using a shared control arm and adaptive randomization. Two investigational arms had superior PFS compared with the control arm, but none demonstrated an OS benefit. The INSIGhT design may promote improved and more efficient therapeutic discovery in glioblastoma. New arms have been added to the trial.

Evaluating hematologic parameters in newly diagnosed and recurrent glioblastoma: Prognostic utility and clinical trial implications of myelosuppression.

Background: Glioblastoma (GBM) patients are treated with radiation therapy, chemotherapy, and corticosteroids, which can cause myelosuppression. To understand the relative prognostic utility of blood-based biomarkers in GBM and its implications for clinical trial design, we examined the incidence, predictors, and prognostic value of lymphopenia, neutrophil-to-lymphocyte ratio (NLR), and platelet count during chemoradiation (CRT) and recurrence. Methods: This cohort study included 764 newly diagnosed glioblastoma patients treated from 2005 to 2019 with blood counts prior to surgery, within 6 weeks of CRT, and at first recurrence available for automatic extraction from the medical record. Logistic regression was used to evaluate exposures and Kaplan-Meier was used to evaluate outcomes. Results: Among the cohort, median age was 60.3 years; 87% had Karnofsky performance status ≥ 70, 37.5% had gross total resection, and 90% received temozolomide (TMZ). During CRT, 37.8% (248/656) of patients developed grade 3 or higher lymphopenia. On multivariable analysis (MVA), high NLR during CRT remained an independent predictor for inferior survival (Adjusted Hazard Ratio [AHR] = 1.57, 95% CI = 1.14-2.15) and shorter progression-free survival (AHR = 1.42, 95% CI = 1.05-1.90). Steroid use was associated with lymphopenia (OR = 2.66,1.20-6.00) and high NLR (OR = 3.54,2.08-6.11). Female sex was associated with lymphopenia (OR = 2.33,1.03-5.33). At first recurrence, 28% of patients exhibited grade 3 or higher lymphopenia. High NLR at recurrence was associated with worse subsequent survival on MVA (AHR = 1.69, 95% CI = 1.25-2.27). Conclusions: High NLR is associated with worse outcomes in newly diagnosed and recurrent glioblastoma. Appropriate eligibility criteria and accounting and reporting of blood-based biomarkers are important in the design and interpretation of newly diagnosed and recurrent glioblastoma trials.

Dendritic cell vaccine trials in gliomas: Untangling the lines.

Glioblastoma is a deadly brain tumor without any significantly successful treatments to date. Tumor antigen-targeted immunotherapy platforms including peptide and dendritic cell (DC) vaccines, have extended survival in hematologic malignancies. The relatively "cold" tumor immune microenvironment and heterogenous nature of glioblastoma have proven to be major limitations to translational application and efficacy of DC vaccines. Furthermore, many DC vaccine trials in glioblastoma are difficult to interpret due to a lack of contemporaneous controls, absence of any control comparison, or inconsistent patient populations. Here we review glioblastoma immunobiology aspects that are relevant to DC vaccines, review the clinical experience with DC vaccines targeting glioblastoma, discuss challenges in clinical trial design, and summarize conclusions and directions for future research for the development of effective DC vaccines for patients.

Evaluation of Standard Response Assessment in Neuro-Oncology, Modified Response Assessment in Neuro-Oncology, and Immunotherapy Response Assessment in Neuro-Oncology in Newly Diagnosed and Recurrent Glioblastoma.

PURPOSE: The Response Assessment in Neuro-Oncology (RANO) criteria are widely used in high-grade glioma clinical trials. We compared the RANO criteria with updated modifications (modified RANO [mRANO] and immunotherapy RANO [iRANO] criteria) in patients with newly diagnosed glioblastoma (nGBM) and recurrent GBM (rGBM) to evaluate the performance of each set of criteria and inform the development of the planned RANO 2.0 update. MATERIALS AND METHODS: Evaluation of tumor measurements and fluid-attenuated inversion recovery (FLAIR) sequences were performed by blinded readers to determine disease progression using RANO, mRANO, iRANO, and other response assessment criteria. Spearman's correlations between progression-free survival (PFS) and overall survival (OS) were calculated. RESULTS: Five hundred twenty-six nGBM and 580 rGBM cases were included. Spearman's correlations were similar between RANO and mRANO (0.69 [95% CI, 0.62 to 0.75] v 0.67 [95% CI, 0.60 to 0.73]) in nGBM and rGBM (0.48 [95% CI, 0.40 to 0.55] v 0.50 [95% CI, 0.42 to 0.57]). In nGBM, requirement of a confirmation scan within 12 weeks of completion of radiotherapy to determine progression was associated with improved correlations. Use of the postradiation magnetic resonance imaging (MRI) as baseline scan was associated with improved correlation compared with use of the pre-radiation MRI (0.67 [95% CI, 0.60 to 0.73] v 0.53 [95% CI, 0.42 to 0.62]). Evaluation of FLAIR sequences did not improve the correlation. Among patients who received immunotherapy, Spearman's correlations were similar among RANO, mRANO, and iRANO. CONCLUSION: RANO and mRANO demonstrated similar correlations between PFS and OS. Confirmation scans were only beneficial in nGBM within 12 weeks of completion of radiotherapy, and there was a trend in favor of the use of postradiation MRI as the baseline scan in nGBM. Evaluation of FLAIR can be omitted. The iRANO criteria did not add significant benefit in patients who received immune checkpoint inhibitors.

Current drug development and trial designs in neuro-oncology: report from the first American Society of Clinical Oncology and Society for Neuro-Oncology Clinical Trials Conference.

Successful drug development for people with cancers of the CNS has been challenging. There are multiple barriers to successful drug development including biological factors, rarity of the disease, and ineffective use of clinical trials. Based upon a series of presentations at the First Central Nervous System Clinical Trials Conference hosted by the American Society of Clinical Oncology and the Society for Neuro-Oncology, we provide an overview on drug development and novel trial designs in neuro-oncology. This Review discusses the challenges of therapeutic development in neuro-oncology and proposes strategies to improve the drug discovery process by enriching the pipeline of promising therapies, optimising trial design, incorporating biomarkers, using external data, and maximising efficacy and reproducibility of clinical trials.

Accessible Data Collections for Improved Decision Making in Neuro-Oncology Clinical Trials.

Drug development can be associated with slow timelines, particularly for rare or difficult-to-treat solid tumors such as glioblastoma. The use of external data in the design and analysis of trials has attracted significant interest because it has the potential to improve the efficiency and precision of drug development. A recurring challenge in the use of external data for clinical trials, however, is the difficulty in accessing high-quality patient-level data. Academic research groups generally do not have access to suitable datasets to effectively leverage external data for planning and analyses of new clinical trials. Given the need for resources to enable investigators to benefit from existing data assets, we have developed the Glioblastoma External (GBM-X) Data Platform which will allow investigators in neuro-oncology to leverage our data collection and obtain analyses. GBM-X strives to provide an uncomplicated process to use external data, contextualize single-arm trials, and improve inference on treatment effects early in drug development. The platform is designed to welcome interested collaborators and integrate new data into the platform, with the expectation that the data collection can continue to grow and remain updated. With such features, GBM-X is designed to help to accelerate evaluation of therapies, to grow with collaborations, and to serve as a model to improve drug discovery for rare and difficult-to-treat tumors in oncology.

Validation of Predictive Analyses for Interim Decisions in Clinical Trials.

PURPOSE: Adaptive clinical trials use algorithms to predict, during the study, patient outcomes and final study results. These predictions trigger interim decisions, such as early discontinuation of the trial, and can change the course of the study. Poor selection of the Prediction Analyses and Interim Decisions (PAID) plan in an adaptive clinical trial can have negative consequences, including the risk of exposing patients to ineffective or toxic treatments. METHODS: We present an approach that leverages data sets from completed trials to evaluate and compare candidate PAIDs using interpretable validation metrics. The goal is to determine whether and how to incorporate predictions into major interim decisions in a clinical trial. Candidate PAIDs can differ in several aspects, such as the prediction models used, timing of interim analyses, and potential use of external data sets. To illustrate our approach, we considered a randomized clinical trial in glioblastoma. The study design includes interim futility analyses on the basis of the predictive probability that the final analysis, at the completion of the study, will provide significant evidence of treatment effects. We examined various PAIDs with different levels of complexity to investigate if the use of biomarkers, external data, or novel algorithms improved interim decisions in the glioblastoma clinical trial. RESULTS: Validation analyses on the basis of completed trials and electronic health records support the selection of algorithms, predictive models, and other aspects of PAIDs for use in adaptive clinical trials. By contrast, PAID evaluations on the basis of arbitrarily defined ad hoc simulation scenarios, which are not tailored to previous clinical data and experience, tend to overvalue complex prediction procedures and produce poor estimates of trial operating characteristics such as power and the number of enrolled patients. CONCLUSION: Validation analyses on the basis of completed trials and real world data support the selection of predictive models, interim analysis rules, and other aspects of PAIDs in future clinical trials.

Phase I study of a novel glioblastoma radiation therapy schedule exploiting cell-state plasticity.

BACKGROUND: Glioblastomas comprise heterogeneous cell populations with dynamic, bidirectional plasticity between treatment-resistant stem-like and treatment-sensitive differentiated states, with treatment influencing this process. However, current treatment protocols do not account for this plasticity. Previously, we generated a mathematical model based on preclinical experiments to describe this process and optimize a radiation therapy fractionation schedule that substantially increased survival relative to standard fractionation in a murine glioblastoma model. METHODS: We developed statistical models to predict the survival benefit of interventions to glioblastoma patients based on the corresponding survival benefit in the mouse model used in our preclinical study. We applied our mathematical model of glioblastoma radiation response to optimize a radiation therapy fractionation schedule for patients undergoing re-irradiation for glioblastoma and developed a first-in-human trial (NCT03557372) to assess the feasibility and safety of administering our schedule. RESULTS: Our statistical modeling predicted that the hazard ratio when comparing our novel radiation schedule with a standard schedule would be 0.74. Our mathematical modeling suggested that a practical, near-optimal schedule for re-irradiation of recurrent glioblastoma patients was 3.96 Gy × 7 (1 fraction/day) followed by 1.0 Gy × 9 (3 fractions/day). Our optimized schedule was successfully administered to 14/14 (100%) patients. CONCLUSIONS: A novel radiation therapy schedule based on mathematical modeling of cell-state plasticity is feasible and safe to administer to glioblastoma patients.

The design and evaluation of hybrid controlled trials that leverage external data and randomization.

Patient-level data from completed clinical studies or electronic health records can be used in the design and analysis of clinical trials. However, these external data can bias the evaluation of the experimental treatment when the statistical design does not appropriately account for potential confounders. In this work, we introduce a hybrid clinical trial design that combines the use of external control datasets and randomization to experimental and control arms, with the aim of producing efficient inference on the experimental treatment effects. Our analysis of the hybrid trial design includes scenarios where the distributions of measured and unmeasured prognostic patient characteristics differ across studies. Using simulations and datasets from clinical studies in extensive-stage small cell lung cancer and glioblastoma, we illustrate the potential advantages of hybrid trial designs compared to externally controlled trials and randomized trial designs.

Novel Clinical Trial Designs in Neuro-Oncology.

Scientific and technologic advances have led to a boon of candidate therapeutics for patients with malignancies of the central nervous system. The path from drug development to clinical use has generally followed a regimented order of sequential clinical trial phases. The recent increase in novel therapies, however, has strained the regulatory process and unearthed limitations of the current system, including significant cost, prolonged development time, and difficulties in testing therapies for rarer tumors. Novel clinical trial designs have emerged to increase efficiencies in clinical trial conduct to better evaluate and bring impactful drugs to patients in a timely manner. In order to better capture meaningful benefits for brain tumor patients, new endpoints to complement or replace traditional endpoints are also an increasingly important consideration. This review will explore the current challenges in the current clinical trial landscape and discuss novel clinical trial concepts, including consideration of limitations and risks of novel trial designs, within the context of neuro-oncology.

DICER1 mutations in primary central nervous system tumors: new insights into histologies, mutations, and prognosis.

PURPOSE: We sought to characterize clinical outcomes for adult and pediatric patients with primary CNS tumors harboring DICER1 mutations or loss of DICER1. METHODS: We conducted a retrospective cohort study of 98 patients who were treated between 1995 and 2020 for primary CNS tumors containing DICER1 mutations or loss of DICER1 on chromosome 14q, identified by targeted next generation sequencing. Kaplan-Meier plots and log rank tests were used to analyze survival. Cox proportional-hazards model was used for univariate and multivariable analyses for all-cause mortality (ACM). RESULTS: Within our cohort, the most common malignancies were grade 3/4 glioma (61%), grade 1/2 glioma (17%), and CNS sarcoma (6%). Sarcoma and non-glioma histologies, and tumors with biallelic DICER1 mutations or deletions were common in the pediatric population. Mutations occurred throughout DICER1, including missense mutations in the DexD/H-box helicase, DUF283, RNaseIIIa, and RNaseIIIb domains. For patients with grade 3/4 glioma, MGMT methylation (Hazard ratio [HR] 0.35, 95% Confidence Interval [CI] 0.16-0.73, p = 0.005), IDH1 R132 mutation (HR 0.11, 95% CI 0.03-0.41, p = 0.001), and missense mutation in the DexD/H-box helicase domain (HR 0.06, 95% CI 0.01-0.38, p = 0.003) were independently associated with longer time to ACM on multivariable analyses. CONCLUSION: DICER1 mutations or loss of DICER1 occur in diverse primary CNS tumors, including previously unrecognized grade 3/4 gliomas as the most common histology. While prior studies have described RNaseIIIb hotspot mutations, we document novel mutations in additional DICER1 functional domains. Within the grade 3/4 glioma cohort, missense mutation in the DexD/H-box helicase domain was associated with prolonged survival.