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Background: Our group and others have recently identified four molecular groups of meningioma, with unique underlying biology and outcomes. The relevance of group-specific metabolite profiles (particularly among hypermetabolic tumours), has not been explored., Methods: We performed untargeted metabolic profiling of meningiomas representing each molecular group and WHO grade. Prognostic biochemicals were identified using Cox regression and their biological importance was explored using RNA and protein-based pathway analyses. Validation was performed using targeted high performance liquid chromatography-mass spectrometry (HPLC-MS/MS)., Results: Global metabolic profiling identified 560 unique biochemicals. We identified a 21-metabolite outcome signatures which is strongly predictive of outcome after adjusting for WHO grade, extent of resection, and receipt of adjuvant radiotherapy (HR 326.49, 95%CI 16.72-6375.48, p < 0.0001). The abundance of N6-trimethyllysine was associated with earlier time to recurrence on our whole cohort (log-rank p = 0.009) and within hypermetabolic and WHO grade 2 tumours specifically; this was validated using targeted HPLC-MS/MS on two cohorts. Consensus RNA and protein expression analysis demonstrated as association between N6-trimethyllysine abundance and activation of oxidative phosphorylation pathways, which portended worse outcomes in the hypermetabolic subgroup but, interestingly, better outcomes in the proliferative subgroup. By contrast, upregulated pyruvate and lactate transporters were associated with worse outcomes in proliferative meningiomas specifically., Conclusions: This is the first study to demonstrate a subgroup-specific prognostic role of N6-trimethyllysine in hypermetabolic meningiomas, offering increasingly granular outcome predictions using a widely accessible technique (HPLC-MS/MS). We also suggest fundamental differences in preferred energy utilization between and a potential need for subgroup-specific therapies., (© The Author(s) 2025. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Background: Meningiomas exhibit considerable clinical and biological heterogeneity. We previously identified four distinct molecular groups (immunogenic, NF2-wildtype, hypermetabolic, proliferative) that address much of this heterogeneity. Despite the utility of these groups, the stochasticity of clustering methods and the use of multi-omics data for discovery limits the potential for classifying prospective cases. We sought to address this with a dedicated classifier., Methods: Using an international cohort of 1698 meningiomas, we constructed and rigorously validated a machine learning-based molecular classifier using only DNA methylation data as input. Original and newly-predicted molecular groups were compared using DNA methylation, RNA sequencing, copy number profiles, whole exome sequencing, and clinical outcomes., Results: We show that group-specific outcomes in the validation cohort are nearly identical to those originally described, with median PFS of 7.4 (4.9-Inf) years in hypermetabolic tumors and 2.5 (2.3-5.3) years in proliferative tumors (not reached in the other groups). Tumors classified as NF2-wildtype had no NF2 mutations, and 51.4% had canonical mutations previously described in this group. RNA pathway analysis revealed upregulation of immune-related pathways in the immunogenic group, metabolic pathways in the hypermetabolic group and cell-cycle programs in the proliferative group. Bulk deconvolution similarly revealed enrichment of macrophages in immunogenic tumours and neoplastic cells in hypermetabolic and proliferative tumours with similar proportions to those originally described., Conclusions: Our DNA methylation-based classifier, which is publicly available for immediate clinical use, recapitulates the biology and outcomes of the original molecular groups as assessed using multiple metrics/platforms that were not used in its training., (© The Author(s) 2025. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Background: We previously developed a DNA methylation-based risk predictor for meningioma, which has been used locally in a prospective fashion since its original publication. As a follow-up, we validate this model using a large prospective cohort and introduce a streamlined next-generation predictor compatible with newer methylation arrays., Methods: Genome-wide methylation profiles were generated with the Illumina EPICArray. The performance of our next-generation predictor was compared with our original model and standard-of-care 2021 WHO grade using time-dependent receiver operating characteristic curves. An nomogram was generated by incorporating our methylation predictor with WHO grade and extent of resection., Results: A total of 1347 meningioma cases were utilized in the study, including 469 prospective cases from 3 institutions and an external cohort of 100 WHO grade 2 cases for model validation. Both the original and next-generation models significantly outperform 2021 WHO grade in predicting early postoperative recurrence. Dichotomizing patients into grade-specific risk subgroups was predictive of outcome within both WHO grades 1 and 2 tumours (p<0.05), while all WHO grade 3 tumours were considered high-risk. Multivariable Cox regression demonstrated benefit of adjuvant radiotherapy in high-risk cases specifically, reinforcing its informative role in clinical decision making. Finally, our next-generation predictor contains nearly 10-fold fewer features than the original model, allowing for targeted arrays., Conclusions: This next-generation DNA methylation-based meningioma outcome predictor significantly outperforms 2021 WHO grading in predicting time to recurrence. We make this available as a point-and-click tool which will improve prognostication, inform patient selection for RT, and allow for molecularly-stratified clinical trials., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Meningiomas are the most common primary intracranial tumors in adults and are increasing in incidence due to the aging population and increased access to neuroimaging. While most exhibit nonmalignant behavior, a subset of meningiomas are biologically aggressive and are associated with treatment resistance, resulting in significant neurologic morbidity and even mortality. In recent years, meaningful advances in our understanding of the biology of these tumors have led to the incorporation of molecular biomarkers into their grading and prognostication. However, unlike other central nervous system (CNS) tumors, a unified molecular taxonomy for meningiomas has not yet been established and remains an overarching goal of the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy-Not Official World Health Organization (cIMPACT-NOW) working group. Additionally, clinical equipoise still remains on how specific meningioma cases and patient populations should be optimally managed. To address these existing gaps, members of the International Consortium on Meningiomas including field-leading experts, have prepared this comprehensive consensus narrative review directed toward clinicians, researchers, and patients. Included in this manuscript are detailed overviews of proposed molecular classifications, novel biomarkers, contemporary treatment strategies, trials on systemic therapies, health-related quality-of-life studies, and management strategies for unique meningioma patient populations. In each section, we discuss the current state of knowledge as well as ongoing clinical and research challenges to road map future directions for further investigation., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Spinal meningiomas comprise 25%-46% of all primary spinal tumors. While the majority are benign and slow-growing, when left untreated, they can result in significant neurological decline. Emerging clinical, imaging, and molecular data have begun to reveal spinal meningiomas as distinct tumor subtypes compared to their intracranial counterparts. Moreover, recent studies indicate molecular and genetic subtype heterogeneity of spinal meningiomas both within and across the classically defined WHO grades. In the current review, we focus on recent advances highlighting the epidemiological, pathological, molecular/genetic, and clinical characteristics of spinal meningiomas. Furthermore, we explore patient and tumor-specific factors that predict prognosis and postoperative outcomes. We highlight areas that require further investigation, specifically efforts aimed at linking unique molecular, genetic, and imaging characteristics to distinct clinical presentations to better predict and manage patient outcomes., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Background: The World Health Organization 2021 classification introduces molecular grading criteria for anaplastic meningiomas, including TERT promoter ( TERTp ) mutations and CDKN2A/B homozygous deletion. Additional adverse prognostic factors include H3K27me3 and BAP1 loss. The aim of this study was to explore whether these molecular alterations stratified clinical outcomes in a single-center cohort of grade 3 meningiomas. Additionally, we examined whether p16 and MTAP immunohistochemistry can predict CDKN2A/B status., Methods: Clinical and histopathological information was obtained from the electronic medical records of grade 3 meningiomas resected at a tertiary center between 2007 and 2020. Molecular testing for TERTp mutations and CDKN2A/B copy-number status, methylation profiling, and immunohistochemistry for H3K27me3, BAP1, p16, and methylthioadenosine phosphorylase (MTAP) were performed. Predictors of survival were identified by Cox regression., Results: Eight of 15 cases demonstrated elevated mitotic index (≥20 mitoses per 10 consecutive high-power fields), 1 tumor exhibited BAP1 loss, 4 harbored TERTp mutations, and 3 demonstrated CDKN2A/B homozygous deletion. Meningiomas with TERTp mutations and/or CDKN2A/B homozygous deletion showed significantly reduced survival compared to anaplastic meningiomas with elevated mitotic index alone. Immunohistochemical loss of p16 and MTAP demonstrated high sensitivity (67% and 100%, respectively) and specificity (100% and 100%, respectively) for predicting CDKN2A/B status., Conclusions: Molecular alterations of grade 3 meningiomas stratify clinical outcomes more so than histologic features alone. Immunohistochemical loss of p16 and MTAP show promise in predicting CDKN2A/B status., Competing Interests: S.Y. is a member of advisory boards of Amgen, AstraZeneca, Bayer, Janssen, Pfizer, Roche, and Servier. G.Z. is the Editor-in-Chief of Neuro-Oncology Advances. The other authors have no conflicts to report., (© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Background: Diffuse gliomas represent over 80% of malignant brain tumors ranging from low-grade to aggressive high-grade lesions. Within isocitrate dehydrogenase (IDH)-mutant gliomas, there is a high variability in survival and a need to more accurately predict outcome., Methods: To identify and characterize a predictive signature of outcome in gliomas, we utilized an integrative molecular analysis (using methylation, mRNA, copy number variation (CNV), and mutation data), analyzing a total of 729 IDH-mutant samples including a test set of 99 from University Health Network (UHN) and 2 validation cohorts including the German Cancer Research Center (DKFZ) and The Cancer Genome Atlas (TCGA)., Results: Cox regression analysis of methylation data from the UHN cohort identified CpG-based signatures that split the glioma cohort into 2 prognostic groups strongly predicting survival that were validated using 2 independent cohorts from TCGA and DKFZ (all P-values < .0001). The methylation signatures that predicted poor outcomes also exhibited high CNV instability and hypermethylation of HOX gene probes. Integrated multi-platform analyses using mRNA and methylation (iRM) showed that parallel HOX gene overexpression and simultaneous hypermethylation were significantly associated with increased mutational load, high aneuploidy, and worse survival (P-value < .0001). A 7-HOX gene signature was developed and validated using the most significantly associated HOX genes with patient outcome in both 1p/19q codeleted and non-codeleted IDHmut gliomas., Conclusions: HOX gene methylation and expression provide important prognostic information in IDH-mutant gliomas that are not captured by current molecular diagnostics. A 7-HOX gene signature of outcome shows significant survival differences in both 1p/19q codeleted and non-codeleted IDH-mutant gliomas., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Competing Interests: The authors declare that they have no conflicts of interest.

Background: Resolving the differential diagnosis between brain metastases (BM), glioblastomas (GBM), and central nervous system lymphomas (CNSL) is an important dilemma for the clinical management of the main three intra-axial brain tumor types. Currently, treatment decisions require invasive diagnostic surgical biopsies that carry risks and morbidity. This study aimed to utilize methylomes from cerebrospinal fluid (CSF), a biofluid proximal to brain tumors, for reliable non-invasive classification that addresses limitations associated with low target abundance in existing approaches., Methods: Binomial GLMnet classifiers of tumor type were built, in fifty iterations of 80% discovery sets, using CSF methylomes obtained from 57 BM, GBM, CNSL, and non-neoplastic control patients. Publicly-available tissue methylation profiles (N = 197) on these entities and normal brain parenchyma were used for validation and model optimization., Results: Models reliably distinguished between BM (area under receiver operating characteristic curve [AUROC] = 0.93, 95% confidence interval [CI]: 0.71-1.0), GBM (AUROC = 0.83, 95% CI: 0.63-1.0), and CNSL (AUROC = 0.91, 95% CI: 0.66-1.0) in independent 20% validation sets. For validation, CSF-based methylome signatures reliably distinguished between tumor types within external tissue samples and tumors from non-neoplastic controls in CSF and tissue. CSF methylome signals were observed to align closely with tissue signatures for each entity. An additional set of optimized CSF-based models, built using tumor-specific features present in tissue data, showed enhanced classification accuracy., Conclusions: CSF methylomes are reliable for liquid biopsy-based classification of the major three malignant brain tumor types. We discuss how liquid biopsies may impact brain cancer management in the future by avoiding surgical risks, classifying unbiopsiable tumors, and guiding surgical planning when resection is indicated., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: With increasing molecular analyses of meningiomas, there is a need to harmonize language used to capture clinical data across centers to ensure that molecular alterations are appropriately linked to clinical variables of interest. Here the International Consortium on Meningiomas presents a set of core and supplemental meningioma-specific common data elements (CDEs) to facilitate comparative and pooled analyses., Methods: The generation of CDEs followed the 4-phase process similar to other National Institute of Neurological Disorders and Stroke (NINDS) CDE projects: discovery, internal validation, external validation, and distribution., Results: The CDEs were organized into patient- and tumor-level modules. In total, 17 core CDEs (10 patient level and 7 tumor level) as well as 14 supplemental CDEs (7 patient level and 7 tumor level) were defined and described. These CDEs are now made publicly available for dissemination and adoption., Conclusions: CDEs provide a framework for discussion in the neuro-oncology community that will facilitate data-sharing for collaborative research projects and aid in developing a common language for comparative and pooled analyses. The meningioma-specific CDEs presented here are intended to be dynamic parameters that evolve with time and The Consortium welcomes international feedback for further refinement and implementation of these CDEs., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Meningiomas are the most common primary intracranial tumor in adults. Clinical care is currently guided by the World Health Organization (WHO) grade assigned to meningiomas, a 3-tiered grading system based on histopathology features, as well as extent of surgical resection. Clinical behavior, however, often fails to conform to the WHO grade. Additional prognostic information is needed to optimize patient management., Methods: We evaluated whether chromosomal copy-number data improved prediction of time-to-recurrence for patients with meningioma who were treated with surgery, relative to the WHO schema. The models were developed using Cox proportional hazards, random survival forest, and gradient boosting in a discovery cohort of 527 meningioma patients and validated in 2 independent cohorts of 172 meningioma patients characterized by orthogonal genomic platforms., Results: We developed a 3-tiered grading scheme (Integrated Grades 1-3), which incorporated mitotic count and loss of chromosome 1p, 3p, 4, 6, 10, 14q, 18, 19, or CDKN2A. 32% of meningiomas reclassified to either a lower-risk or higher-risk Integrated Grade compared to their assigned WHO grade. The Integrated Grade more accurately identified meningioma patients at risk for recurrence, relative to the WHO grade, as determined by time-dependent area under the curve, average precision, and the Brier score., Conclusion: We propose a molecularly integrated grading scheme for meningiomas that significantly improves upon the current WHO grading system in prediction of progression-free survival. This framework can be broadly adopted by clinicians with relative ease using widely available genomic technologies and presents an advance in the care of meningioma patients., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Background: Accurate CNS tumor diagnosis can be challenging, and methylation profiling can serve as an adjunct to classify diagnostically difficult cases., Methods: An integrated diagnostic approach was employed for a consecutive series of 1258 surgical neuropathology samples obtained primarily in a consultation practice over 2-year period. DNA methylation profiling and classification using the DKFZ/Heidelberg CNS tumor classifier was performed, as well as unsupervised analyses of methylation data. Ancillary testing, where relevant, was performed., Results: Among the received cases in consultation, a high-confidence methylation classifier score (>0.84) was reached in 66.4% of cases. The classifier impacted the diagnosis in 46.7% of these high-confidence classifier score cases, including a substantially new diagnosis in 26.9% cases. Among the 289 cases received with only a descriptive diagnosis, methylation was able to resolve approximately half (144, 49.8%) with high-confidence scores. Additional methods were able to resolve diagnostic uncertainty in 41.6% of the low-score cases. Tumor purity was significantly associated with classifier score (P = 1.15e-11). Deconvolution demonstrated that suspected glioblastomas (GBMs) matching as control/inflammatory brain tissue could be resolved into GBM methylation profiles, which provided a proof-of-concept approach to resolve tumor classification in the setting of low tumor purity., Conclusions: This work assesses the impact of a methylation classifier and additional methods in a consultative practice by defining the proportions with concordant vs change in diagnosis in a set of diagnostically challenging CNS tumors. We address approaches to low-confidence scores and confounding issues of low tumor purity., (Published by Oxford University Press on behalf of the Society for Neuro-Oncology 2021.)

Background: Chordomas are rare malignant bone cancers of the skull-base and spine. Patient survival is variable and not reliably predicted using clinical factors or molecular features. This study identifies prognostic epigenetic chordoma subtypes that are detected noninvasively using plasma methylomes., Methods: Methylation profiles of 68 chordoma surgical samples were obtained between 1996 and 2018 across three international centers along with matched plasma methylomes where available., Results: Consensus clustering identified two stable tissue clusters with a disease-specific survival difference that was independent of clinical factors in a multivariate Cox analysis (HR = 14.2, 95%CI: 2.1-94.8, P = 0.0063). Immune-related pathways with genes hypomethylated at promoters and increased immune cell abundance were observed in the poor-performing "Immune-infiltrated" subtype. Cell-to-cell interaction plus extracellular matrix pathway hypomethylation and higher tumor purity were observed in the better-performing "Cellular" subtype. The findings were validated in additional DNA methylation and RNA sequencing datasets as well as with immunohistochemical staining. Plasma methylomes distinguished chordomas from other clinical differential diagnoses by applying fifty chordoma-versus-other binomial generalized linear models in random 20% testing sets (mean AUROC = 0.84, 95%CI: 0.52-1.00). Tissue-based and plasma-based methylation signals were highly correlated in both prognostic clusters. Additionally, leave-one-out models accurately classified all tumors into their correct cluster based on plasma methylation data., Conclusions: Here, we show the first identification of prognostic epigenetic chordoma subtypes and first use of plasma methylome-based biomarkers to noninvasively diagnose and subtype chordomas. These results may transform patient management by allowing treatment aggressiveness to be balanced with patient risk according to prognosis., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: There is a critical need for objective and reliable biomarkers of outcome in meningiomas beyond WHO classification. Loss of H3K27me3 has been reported as a prognostically unfavorable alteration in meningiomas. We sought to independently evaluate the reproducibility and prognostic value of H3K27me3 loss by immunohistochemistry (IHC) in a multicenter study., Methods: IHC staining for H3K27me3 and analyses of whole slides from 181 meningiomas across three centers was performed. Staining was analyzed by dichotomization into loss and retained immunoreactivity, and using a 3-tiered scoring system in 151 cases with clear staining. Associations of grouping with outcome were performed using Kaplan-Meier survival estimates., Results: A total of 21 of 151 tumors (13.9%) demonstrated complete loss of H3K27me3 staining in tumor with retained endothelial staining. Overall, loss of H3K27me3 portended a worse outcome with shorter times to recurrence in our cohort, particularly for WHO grade 2 tumors which were enriched in our study. There were no differences in recurrence-free survival (RFS) for WHO grade 3 patients with retained vs loss of H3K27me3. Scoring by a 3-tiered system did not add further insights into the prognostic value of this H3K27me3 loss. Overall, loss of H3K27me3 was not independently associated with RFS after controlling for WHO grade, extent of resection, sex, age, and recurrence status of tumor on multivariable Cox regression analysis., Conclusions: Loss of H3K27me3 identifies a subset of WHO grade 2 and possibly WHO grade 1 meningiomas with increased recurrence risk. Pooled analyses of a larger cohort of samples with standardized reporting of clinical definitions and staining patterns are warranted., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: It remains unknown how the COVID-19 pandemic has changed neuro-oncology clinical practice, training, and research efforts., Methods: We performed an international survey of practitioners, scientists, and trainees from 21 neuro-oncology organizations across 6 continents, April 24-May 17, 2020. We assessed clinical practice and research environments, institutional preparedness and support, and perceived impact on patients., Results: Of 582 respondents, 258 (45%) were US-based and 314 (55%) international. Ninety-four percent of participants reported changes in their clinical practice. Ninety-five percent of respondents converted at least some practice to telemedicine. Ten percent of practitioners felt the need to see patients in person, specifically because of billing concerns and pressure from their institutions. Sixty-seven percent of practitioners suspended enrollment for at least one clinical trial, including 62% suspending phase III trial enrollments. More than 50% believed neuro-oncology patients were at increased risk for COVID-19. Seventy-one percent of clinicians feared for their own personal safety or that of their families, specifically because of their clinical duties; 20% had inadequate personal protective equipment. While 69% reported increased stress, 44% received no psychosocial support from their institutions. Thirty-seven percent had salary reductions and 63% of researchers temporarily closed their laboratories. However, the pandemic created positive changes in perceived patient satisfaction, communication quality, and technology use to deliver care and mediate interactions with other practitioners., Conclusions: The pandemic has changed treatment schedules and limited investigational treatment options. Institutional lack of support created clinician and researcher anxiety. Communication with patients was satisfactory. We make recommendations to guide clinical and scientific infrastructure moving forward and address the personal challenges of providers and researchers., (© The Author(s) 2021. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Background: We aimed to explore gaps in the care of meningioma patients that could improve quality of care by better understanding symptoms experienced by patients at various stages of treatment, and afterwards., Methods: A novel 19-item self-administered questionnaire was provided for patients with meningiomas to complete by the American Brain Tumor Association (ABTA) over a 3-month period., Results: A total of 1852 unique respondents were included. Nearly one-third of all respondents felt they received insufficient information about meningiomas at initial diagnosis ( N = 607, 32.9%) and 28.8% ( N = 530) believed they received insufficient information about treatment options. In fact, 34.5% of respondents received the majority of their information from the internet and nonhealthcare professionals. The most common concerns after initial diagnosis were risks associated with surgery and/or treatment (36.5%) followed by how the tumor would impact daily life (25%) and the risk of tumor recurrence (12.4%). Respondents indicated that a list of resources available for patients with meningiomas ( N = 597, 32.3%) would have been most beneficial in regards to their disease experience after their initial diagnosis. Moreover, we found that a substantial proportion of patients continued to report symptoms long after treatment, with fatigue being the most common compared to before treatment (38.2% vs. 57.7%, χ 2 = 128, P < .001)., Conclusions: Patients with meningiomas exhibit symptoms that continue well after treatment with fatigue and cognitive impairments as the most bothersome. Moreover, patients report key communication gaps that can be addressed to improve their disease experience and care., (© The Author(s) 2020. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Background: Variability in standard-of-care classifications precludes accurate predictions of early tumor recurrence for individual patients with meningioma, limiting the appropriate selection of patients who would benefit from adjuvant radiotherapy to delay recurrence. We aimed to develop an individualized prediction model of early recurrence risk combining clinical and molecular factors in meningioma., Methods: DNA methylation profiles of clinically annotated tumor samples across multiple institutions were used to develop a methylome model of 5-year recurrence-free survival (RFS). Subsequently, a 5-year meningioma recurrence score was generated using a nomogram that integrated the methylome model with established prognostic clinical factors. Performance of both models was evaluated and compared with standard-of-care models using multiple independent cohorts., Results: The methylome-based predictor of 5-year RFS performed favorably compared with a grade-based predictor when tested using the 3 validation cohorts (ΔAUC = 0.10, 95% CI: 0.03-0.018) and was independently associated with RFS after adjusting for histopathologic grade, extent of resection, and burden of copy number alterations (hazard ratio 3.6, 95% CI: 1.8-7.2, P < 0.001). A nomogram combining the methylome predictor with clinical factors demonstrated greater discrimination than a nomogram using clinical factors alone in 2 independent validation cohorts (ΔAUC = 0.25, 95% CI: 0.22-0.27) and resulted in 2 groups with distinct recurrence patterns (hazard ratio 7.7, 95% CI: 5.3-11.1, P < 0.001) with clinical implications., Conclusions: The models developed and validated in this study provide important prognostic information not captured by previously established clinical and molecular factors which could be used to individualize decisions regarding postoperative therapeutic interventions, in particular whether to treat patients with adjuvant radiotherapy versus observation alone., (Published by Oxford University Press on behalf of the Society for Neuro-Oncology 2019.)

Background: We investigated prognostic models based on clinical, radiologic, and radiomic feature to preoperatively identify meningiomas at risk for poor outcomes., Methods: Retrospective review was performed for 303 patients who underwent resection of 314 meningiomas (57% World Health Organization grade I, 35% grade II, and 8% grade III) at two independent institutions, which comprised primary and external datasets. For each patient in the primary dataset, 16 radiologic and 172 radiomic features were extracted from preoperative magnetic resonance images, and prognostic features for grade, local failure (LF) or overall survival (OS) were identified using the Kaplan-Meier method, log-rank tests and recursive partitioning analysis. Regressions and random forests were used to generate and test prognostic models, which were validated using the external dataset., Results: Multivariate analysis revealed that apparent diffusion coefficient hypointensity (HR 5.56, 95% CI 2.01-16.7, P = .002) was associated with high grade meningioma, and low sphericity was associated both with increased LF (HR 2.0, 95% CI 1.1-3.5, P = .02) and worse OS (HR 2.94, 95% CI 1.47-5.56, P = .002). Both radiologic and radiomic predictors of adverse meningioma outcomes were significantly associated with molecular markers of aggressive meningioma biology, such as somatic mutation burden, DNA methylation status, and FOXM1 expression. Integrated prognostic models combining clinical, radiologic, and radiomic features demonstrated improved accuracy for meningioma grade, LF, and OS (area under the curve 0.78, 0.75, and 0.78, respectively) compared to models based on clinical features alone., Conclusions: Preoperative radiologic and radiomic features such as apparent diffusion coefficient and sphericity can predict tumor grade, LF, and OS in patients with meningioma., (© The Author(s) 2019. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

Glioblastoma (GBM) is the most common primary malignant brain tumor, with a universally poor prognosis. The emergence of molecular biomarkers has had a significant impact on histological typing and diagnosis, as well as predicting patient survival and response to treatment. The methylation status of the O6-methylguanine-DNA methyl-transferase (MGMT) gene promoter is one such molecular biomarker. Despite the strong evidence supporting the role of MGMT methylation status in prognostication, its routine implementation in clinical practice has been challenging. The methods and optimal cutoff definitions for MGMT status determination remain controversial. Variation in detection methods between laboratories presents a major challenge for consensus. Moreover, consideration of other clinical and genetic/epigenetic factors must also be incorporated into treatment decision making. In this review, we distill the available evidence to summarize our position on the optimal use of available assays, and propose strategies for resolving cases with equivocal methylation status and a framework for incorporating this important assay into research and clinical practice., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Surgery has long been established as the first-line treatment for the majority of symptomatic and enlarging meningiomas, and evidence for its success is derived from retrospective case series. Despite surgical resection, a subset of meningiomas display aggressive behavior with early recurrences that are difficult to treat. The decision to radically resect meningiomas and involved structures is balanced against the risk for neurological injury in patients. Radiation therapy has largely been used as a complementary and safe therapeutic strategy in meningiomas with evidence primarily stemming from retrospective, single-institution reports. Two of the first cooperative group studies (RTOG 0539 and EORTC 22042) evaluating the outcomes of adjuvant radiation therapy in higher-risk meningiomas have shown promising preliminary results. Historically, systemic therapy has resulted in disappointing results in meningiomas. However, several clinical trials are under way evaluating the efficacy of chemotherapies, such as trabectedin, and novel molecular agents targeting Smoothened, AKT1, and focal adhesion kinase in patients with recurrent meningiomas.

Meningiomas are the most common primary intracranial neoplasm. The current World Health Organization (WHO) classification categorizes meningiomas based on histopathological features, but emerging molecular data demonstrate the importance of genomic and epigenomic factors in the clinical behavior of these tumors. Treatment options for symptomatic meningiomas are limited to surgical resection where possible and adjuvant radiation therapy for tumors with concerning histopathological features or recurrent disease. At present, alternative adjuvant treatment options are not available in part due to limited historical biological analysis and clinical trial investigation on meningiomas. With advances in molecular and genomic techniques in the last decade, we have witnessed a surge of interest in understanding the genomic and epigenomic landscape of meningiomas. The field is now at the stage to adopt this molecular knowledge to refine meningioma classification and introduce molecular algorithms that can guide prediction and therapeutics for this tumor type. Animal models that recapitulate meningiomas faithfully are in critical need to test new therapeutics to facilitate rapid-cycle translation to clinical trials. Here we review the most up-to-date knowledge of molecular alterations that provide insight into meningioma behavior and are ready for application to clinical trial investigation, and highlight the landscape of available preclinical models in meningiomas.

Background: Few studies have evaluated the health-related quality of life (HRQoL) of patients with meningiomas. Here, we report the largest prospective, longitudinal cross-sectional cohort study of HRQoL in meningiomas to date, in order to identify possible actionable determinants of global HRQoL., Methods: Adults who had undergone resection of a grade I intracranial meningioma and were in routine follow-up at a single large tertiary center underwent HRQoL assessment using the QLQ-C30 questionnaire administered opportunistically at follow-up visits. Averaged transformed QLQ-C30 scores at 12-month intervals were compared with scores from a normative reference population, with reference to known minimal clinically meaningful difference (CMD) in scores. To evaluate for possible determinants of changes in global HRQoL, global HRQoL scores were correlated (Spearman's Rho) with subdomain and symptom scores and with interval time from surgical resection., Results: A total of 291 postoperative patients with histologically confirmed and surgically treated grade I meningiomas consented to participation and a total of 455 questionnaires were included for analysis. Patients with meningiomas reported reduced global HRQoL at nearly every 12-month interval with clinically and statistically significant impairments at 12, 48, 108, and 120 months postoperative compared with the normative population (P < 0.05). Meningioma patients at the 12-month interval also reported a reduction of each subdomain of HRQoL assessment (P < 0.05); however, a CMD was only seen in cognitive functioning. Physical, emotional, cognitive, and social subdomains, as well as fatigue and sleep/insomnia, were significantly associated with global HRQoL at the first 12-month interval. Overall, there was no significant correlation between time from surgery and global HRQoL or the subdomain functional or symptom sections of the QLQ-C30., Conclusions: Meningioma patients report considerable limitations in HRQoL for more than 120 months after surgery, particularly in cognitive, emotional, and social function, as well as suffering significant fatigue and sleep impairment compared with a normative reference population. The majority of these reported functional impairments and symptoms are strongly associated with global HRQoL and thus can be considered determinants of global HRQoL that if treated, have the potential to improve HRQoL for our meningioma patients. This hypothesis requires future study of targeted interventions to determine their efficacy.

The archetypal imaging characteristics of meningiomas are among the most stereotypic of all central nervous system (CNS) tumors. In the era of plain film and ventriculography, imaging was only performed if a mass was suspected, and their results were more suggestive than definitive. Following more than a century of technological development, we can now rely on imaging to non-invasively diagnose meningioma with great confidence and precisely delineate the locations of these tumors relative to their surrounding structures to inform treatment planning. Asymptomatic meningiomas may be identified and their growth monitored over time; moreover, imaging routinely serves as an essential tool to survey tumor burden at various stages during the course of treatment, thereby providing guidance on their effectiveness or the need for further intervention. Modern radiological techniques are expanding the power of imaging from tumor detection and monitoring to include extraction of biologic information from advanced analysis of radiological parameters. These contemporary approaches have led to promising attempts to predict tumor grade and, in turn, contribute prognostic data. In this supplement article, we review important current and future aspects of imaging in the diagnosis and management of meningioma, including conventional and advanced imaging techniques using CT, MRI, and nuclear medicine.

A phase I trial of an engineered poliovirus for the treatment of recurrent glioblastoma (GBM) has attracted attention due to 8 survivors reaching the 24-month and 5 reaching the 36-month survival landmarks.1 Genetically engineered viruses (oncolytic viruses) have been in trials for GBM for almost two decades.2 These replication-competent (tumor-selective, oncolytic, replication-conditional) viruses or replication-defective viral vectors (gene therapy) deliver cytotoxic payloads to tumors, leading to immunogenic death and intratumoral inflammatory responses. This transforms the tumor microenvironment from immunologically naïve ("cold") to inflamed ("hot"), increasing immune cell recognition of tumor antigens and the durable responses observed in virotherapy.3,4 Several current and past virotherapy trials have reported a "tail" of apparent responders at the 24-month landmark. Other modalities have also reported a "tail" of seemingly long-term survivors. These trials seem to show that these responder "tails" characterize a defined subset of GBM patients.

Spinal cord injury has a significant societal and personal impact. Although the majority of injuries involve the cervical spinal cord, few studies of cell transplantation have used clinically relevant models of cervical spinal cord injury, limiting translation into clinical trials. Given this knowledge gap, we sought to examine the effects of neural stem/precursor cell (NPC) transplants in a rodent model of bilateral cervical contusion-compression spinal cord injury. Bilateral C6-level clip contusion-compression injuries were performed in rats, which were then blindly randomized at 2 weeks after injury into groups receiving adult brain-derived NPCs, vehicle, or sham operation. Long-term survival of NPCs was evident at 10 weeks after transplant. Cell grafts were localized rostrocaudally surrounding the lesion, throughout white and gray matter. Graft-derived cells were found within regions of gliotic scar and motor tracts and deposited myelin around endogenous axons. The majority of NPCs developed an oligodendroglial phenotype with greater neuronal profiles in rostral grafts. Following NPC transplantation, white matter was significantly increased compared with control. Astrogliosis and glial scar deposition, measured by GFAP-positive and chondroitin sulfate proteoglycan-positive volume, was significantly reduced. Forelimb grip strength, fine motor control during locomotion, and axonal conduction (by in vivo electrophysiology) was greater in cell-treated animals compared with vehicle controls. Transplantation of NPCs in the bilaterally injured cervical spinal cord results in significantly improved spinal cord tissue and forelimb function, warranting further study in preclinical cervical models to improve this treatment paradigm for clinical translation., (©AlphaMed Press.)