A prognostic neural epigenetic signature in high-grade glioma.

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes.

EpiDiP/NanoDiP: a versatile unsupervised machine learning edge computing platform for epigenomic tumour diagnostics.

DNA methylation analysis based on supervised machine learning algorithms with static reference data, allowing diagnostic tumour typing with unprecedented precision, has quickly become a new standard of care. Whereas genome-wide diagnostic methylation profiling is mostly performed on microarrays, an increasing number of institutions additionally employ nanopore sequencing as a faster alternative. In addition, methylation-specific parallel sequencing can generate methylation and genomic copy number data. Given these diverse approaches to methylation profiling, to date, there is no single tool that allows (1) classification and interpretation of microarray, nanopore and parallel sequencing data, (2) direct control of nanopore sequencers, and (3) the integration of microarray-based methylation reference data. Furthermore, no software capable of entirely running in routine diagnostic laboratory environments lacking high-performance computing and network infrastructure exists. To overcome these shortcomings, we present EpiDiP/NanoDiP as an open-source DNA methylation and copy number profiling suite, which has been benchmarked against an established supervised machine learning approach using in-house routine diagnostics data obtained between 2019 and 2021. Running locally on portable, cost- and energy-saving system-on-chip as well as gpGPU-augmented edge computing devices, NanoDiP works in offline mode, ensuring data privacy. It does not require the rigid training data annotation of supervised approaches. Furthermore, NanoDiP is the core of our public, free-of-charge EpiDiP web service which enables comparative methylation data analysis against an extensive reference data collection. We envision this versatile platform as a useful resource not only for neuropathologists and surgical pathologists but also for the tumour epigenetics research community. In daily diagnostic routine, analysis of native, unfixed biopsies by NanoDiP delivers molecular tumour classification in an intraoperative time frame.

Circulating extracellular vesicles as biomarker for diagnosis, prognosis and monitoring in glioblastoma patients.

BACKGROUND: Extracellular vesicles (EVs) obtained by noninvasive liquid biopsy from patient blood can serve as biomarkers. Here, we investigated the potential of circulating plasma EVs to serve as an indicator in the diagnosis, prognosis and treatment response of glioblastoma patients. METHODS: Plasma samples were collected from glioblastoma patients at multiple timepoints before and after surgery. EV concentrations were measured by nanoparticle tracking analysis and imaging flow cytometry. Tumor burden and edema were quantified by 3D reconstruction. EVs and tumors were further monitored in glioma-bearing mice. RESULTS: Glioblastoma patients displayed a 5.5-fold increase in circulating EVs compared to healthy donors (p < 0.0001). Patients with higher EV levels had a significantly shorter overall survival and progression-free survival than patients with lower levels, and the plasma EV concentration was an independent prognostic parameter for overall survival. EV levels correlated with the extent of peritumoral FLAIR hyperintensity but not with the size of the contrast-enhancing tumor, and similar findings were obtained in mice. Postoperatively, EV concentrations decreased rapidly back to normal levels, and the magnitude of the decline was associated with the extent of tumor resection. EV levels remained low during stable disease, but increased again upon tumor recurrence. In some patients, EV resurgence preceded the magnetic resonance imaging (MRI) detectability of tumor relapse. CONCLUSIONS: Our findings suggest that leakiness of the blood-brain barrier may primarily be responsible for the high circulating EV concentrations in glioblastoma patients. Elevated EVs reflect tumor presence, and their quantification may thus be valuable in assessing disease activity.

Treatment response as surrogate to predict risk for disease progression in pediatric medulloblastoma with persistent MRI lesions after first-line treatment.

BACKGROUND: This study aims at clarifying the impact of persistent residual lesions following first-line treatment for pediatric medulloblastoma. METHODS: Data on 84 pediatric patients with medulloblastoma and persistent residual lesions on centrally reviewed MRI at the end of first-line therapy were analyzed. RESULTS: Twenty patients (23.8%) had residual lesions in the tumor bed (R+/M0), 51 (60.7%) had distant lesions (R0/M+) and 13 (15.5%) had both (R+/M+). Overall response to first-line therapy was minor or partial (≥25% reduction, MR/PR) for 64 (76.2%) and stable disease (SD) for 20 patients (23.8%). Five-year post-primary-treatment progression-free (pptPFS) and overall survival (pptOS) were superior after MR/PR (pptPFS: 62.5±7.0%[MR/PR] vs. 35.9±12.8%[SD], p=0.03; pptOS: 79.7±5.9[MR/PR] vs. 55.5±13.9[SD], p=0.04). Further, R+/M+ was associated with a higher risk for progression (5-year pptPFS: 22.9±17.9%[R+,M+] vs. 72.4±12.0%[R+,M0]; p=0.03). Watch-and-wait was pursued in 58 patients, while n=26 received additional treatments (chemotherapy only, n=19; surgery only, n=2; combined, n=3; valproic acid, n=2), and their outcomes were not superior to watch-and-wait (5-year pptPFS: 58.5±7.7% vs. 51.6±10.7% p=0.71; 5-year pptOS: 76.3±6.9% vs. 69.8±9.7%, p=0.74). For the whole cohort, five-year pptPFS by molecular subgroup (58 cases) were WNT: 100%, SHH: 50.0±35.4%, Group-4, 52.5±10.5, Group-3 54.2±13.8%; (p=0.08). CONCLUSION: Overall response and extent of lesions can function as surrogate parameters to predict outcomes in pediatric MB patients with persistent lesions after first-line therapy. Especially in case of solitary persistent medulloblastoma MRI lesion, additional therapy was not beneficial. Therefore, treatment response, extent/kind of residual lesions and further diagnostic information needs consideration for indication of additional treatments for persisting lesions.

Corrigendum: Grade 3 Meningioma Survival and Recurrence Outcomes in an International Multicenter Cohort.

[This corrects the article DOI: 10.1055/s-0044-1779888.].

SMARCA4 Loss and Mutated ß-Catenin Induce Proliferative Lesions in the Murine Embryonic Cerebellum.

Almost all medulloblastomas (MB) of the Wingless/Int-1 (WNT) type are characterized by hotspot mutations in CTNNB1, and mouse models have convincingly demonstrated the tumor-initiating role of these mutations. Additional alterations in SMARCA4 are detected in ∼20% of WNT MB, but their functional role is mostly unknown. We, therefore, amended previously described brain lipid binding protein (Blbp)-cre::Ctnnb1(ex3)fl/wt mice by the introduction of floxed Smarca4 alleles. Unexpectedly, mutated and thereby stabilized ß-catenin on its own induced severe developmental phenotypes in male and female Blbp-cre::Ctnnb1(ex3)fl/wt mice in our hands, including a thinned cerebral cortex, hydrocephalus, missing cerebellar layering, and cell accumulations in the brainstem and cerebellum. An additional loss of SMARCA4 even resulted in prenatal death for most mice. Respective Blbp-cre::Ctnnb1(ex3)fl/wt::Smarca4fl/rec mutants (male and female) developed large proliferative lesions in the cerebellum evolving from E13.5 to E16.5. Histological and molecular analysis of these lesions by DNA methylation profiling and single-cell RNA sequencing suggested an origin in early undifferentiated SOX2-positive cerebellar progenitors. Furthermore, upregulated WNT signaling, altered actin/cytoskeleton organization, and reduced neuronal differentiation were evident in mutant cells. In vitro, cells harboring alterations in both Ctnnb1 and Smarca4 were negatively selected and did not show tumorigenic potential after transplantation in adult female recipient mice. However, in cerebellar explant cultures, mutant cells displayed significantly increased proliferation, suggesting an important role of the embryonic microenvironment in the development of lesions. Altogether, these results represent an important first step toward the unraveling of tumorigenic mechanisms induced by aberrant WNT signaling and SMARCA4 deficiency.

Molecular characteristics and improved survival prediction in a cohort of 2023 ependymomas.

The diagnosis of ependymoma has moved from a purely histopathological review with limited prognostic value to an integrated diagnosis, relying heavily on molecular information. However, as the integrated approach is still novel and some molecular ependymoma subtypes are quite rare, few studies have correlated integrated pathology and clinical outcome, often focusing on small series of single molecular types. We collected data from 2023 ependymomas as classified by DNA methylation profiling, consisting of 1736 previously published and 287 unpublished methylation profiles. Methylation data and clinical information were correlated, and an integrated model was developed to predict progression-free survival. Patients with EPN-PFA, EPN-ZFTA, and EPN-MYCN tumors showed the worst outcome with 10-year overall survival rates of 56%, 62%, and 32%, respectively. EPN-PFA harbored chromosome 1q gains and/or 6q losses as markers for worse survival. In supratentorial EPN-ZFTA, a combined loss of CDKN2A and B indicated worse survival, whereas a single loss did not. Twelve out of 200 EPN-ZFTA (6%) were located in the posterior fossa, and these tumors relapsed or progressed even earlier than supratentorial tumors with a combined loss of CDKN2A/B. Patients with MPE and PF-SE, generally regarded as non-aggressive tumors, only had a 10-year progression-free survival of 59% and 65%, respectively. For the prediction of the 5-year progression-free survival, Kaplan-Meier estimators based on the molecular subtype, a Support Vector Machine based on methylation, and an integrated model based on clinical factors, CNV data, and predicted methylation scores achieved balanced accuracies of 66%, 68%, and 73%, respectively. Excluding samples with low prediction scores resulted in balanced accuracies of over 80%. In sum, our large-scale analysis of ependymomas provides robust information about molecular features and their clinical meaning. Our data are particularly relevant for rare and hardly explored tumor subtypes and seemingly benign variants that display higher recurrence rates than previously believed.

Clinically relevant molecular hallmarks of PFA ependymomas display intratumoral heterogeneity and correlate with tumor morphology.

Posterior fossa type A (PF-EPN-A, PFA) ependymoma are aggressive tumors that mainly affect children and have a poor prognosis. Histopathology shows significant intratumoral heterogeneity, ranging from loose tissue to often sharply demarcated, extremely cell-dense tumor areas. To determine molecular differences in morphologically different areas and to understand their clinical significance, we analyzed 113 PF-EPN-A samples, including 40 corresponding relapse samples. Cell-dense areas ranged from 0 to 100% of the tumor area and displayed a higher proportion of proliferating tumor cells (p < 0.01). Clinically, cell density was associated with poor progression-free and overall survival (pPFS = 0.0026, pOS < 0.01). Molecularly, tumor areas with low and high cell density showed diverging DNA methylation profiles regarding their similarity to distinct previously discovered PF-EPN-A subtypes in 9/21 cases. Prognostically relevant chromosomal changes at 1q and 6q showed spatial heterogeneity within single tumors and were significantly enriched in cell-dense tumor areas as shown by single-cell RNA (scRNA)-sequencing as well as copy number profiling and fluorescence in situ hybridization (FISH) analyses of different tumor areas. Finally, spatial transcriptomics revealed cell-dense areas of different tumors to be more similar than various different areas of the same tumor. High-density areas distinctly overexpressed genes encoding histone proteins, WNT5A, TGFB1, or IGF2. Relapsing tumors displayed a higher proportion of cell-dense areas (p = 0.036), a change in PF-EPN-A methylation subtypes (13/32 patients), and novel chromosome 1q gains and 6q losses (12/32 cases) compared to corresponding primary tumors. Our data suggest that PF-EPN-A ependymomas habor a previously unrecognized intratumoral heterogeneity with clinical implications, which has to be accounted for when selecting diagnostic material, inter alia, by histological evaluation of the proportion of cell-dense areas.

Morphology-based molecular classification of spinal cord ependymomas using deep neural networks.

Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP-EPN) and myxopapillary ependymomas (MPE(-A/B)), which differ with respect to their clinical features and prognosis. Due to the existing discrepancy between histomorphogical diagnoses and classification using methylation data, we asked whether deep neural networks can predict the DNA methylation class of spinal cord ependymomas from hematoxylin and eosin stained whole-slide images. Using explainable AI, we further aimed to prospectively improve the consistency of histology-based diagnoses with DNA methylation profiling by identifying and quantifying distinct morphological patterns of these molecular ependymoma types. We assembled a case series of 139 molecularly characterized spinal cord ependymomas (nMPE = 84, nSP-EPN = 55). Self-supervised and weakly-supervised neural networks were used for classification. We employed attention analysis and supervised machine-learning methods for the discovery and quantification of morphological features and their correlation to the diagnoses of experienced neuropathologists. Our best performing model predicted the DNA methylation class with 98% test accuracy and used self-supervised learning to outperform pretrained encoder-networks (86% test accuracy). In contrast, the diagnoses of neuropathologists matched the DNA methylation class in only 83% of cases. Domain-adaptation techniques improved model generalization to an external validation cohort by up to 22%. Statistically significant morphological features were identified per molecular type and quantitatively correlated to human diagnoses. The approach was extended to recently defined subtypes of myxopapillary ependymomas (MPE-(A/B), 80% test accuracy). In summary, we demonstrated the accurate prediction of the DNA methylation class of spinal cord ependymomas (SP-EPN, MPE(-A/B)) using hematoxylin and eosin stained whole-slide images. Our approach may prospectively serve as a supplementary resource for integrated diagnostics and may even help to establish a standardized, high-quality level of histology-based diagnostics across institutions-in particular in low-income countries, where expensive DNA-methylation analyses may not be readily available.

Unclassifiable CNS tumors in DNA methylation-based classification: clinical challenges and prognostic impact.

DNA methylation analysis has become a powerful tool in neuropathology. Although DNA methylation-based classification usually shows high accuracy, certain samples cannot be classified and remain clinically challenging. We aimed to gain insight into these cases from a clinical perspective. To address, central nervous system (CNS) tumors were subjected to DNA methylation profiling and classified according to their calibrated score using the DKFZ brain tumor classifier (V11.4) as "≥ 0.84" (score ≥ 0.84), "0.3-0.84" (score 0.3-0.84), or "< 0.3" (score < 0.3). Histopathology, patient characteristics, DNA input amount, and tumor purity were correlated. Clinical outcome parameters were time to treatment decision, progression-free, and overall survival. In 1481 patients, the classifier identified 69 (4.6%) tumors with an unreliable score as "< 0.3". Younger age (P < 0.01) and lower tumor purity (P < 0.01) compromised accurate classification. A clinical impact was demonstrated as unclassifiable cases ("< 0.3") had a longer time to treatment decision (P < 0.0001). In a subset of glioblastomas, these cases experienced an increased time to adjuvant treatment start (P < 0.001) and unfavorable survival (P < 0.025). Although DNA methylation profiling adds an important contribution to CNS tumor diagnostics, clinicians should be aware of a potentially longer time to treatment initiation, especially in malignant brain tumors.

Temporal change of DNA methylation subclasses between matched newly diagnosed and recurrent glioblastoma.

The longitudinal transition of phenotypes is pivotal in glioblastoma treatment resistance and DNA methylation emerged as an important tool for classifying glioblastoma phenotypes. We aimed to characterize DNA methylation subclass heterogeneity during progression and assess its clinical impact. Matched tissues from 47 glioblastoma patients were subjected to DNA methylation profiling, including CpG-site alterations, tissue and serum deconvolution, mass spectrometry, and immunoassay. Effects of clinical characteristics on temporal changes and outcomes were studied. Among 47 patients, 8 (17.0%) had non-matching classifications at recurrence. In the remaining 39 cases, 28.2% showed dominant DNA methylation subclass transitions, with 72.7% being a mesenchymal subclass. In general, glioblastomas with a subclass transition showed upregulated metabolic processes. Newly diagnosed glioblastomas with mesenchymal transition displayed increased stem cell-like states and decreased immune components at diagnosis and exhibited elevated immune signatures and cytokine levels in serum. In contrast, tissue of recurrent glioblastomas with mesenchymal transition showed increased immune components but decreased stem cell-like states. Survival analyses revealed comparable outcomes for patients with and without subclass transitions. This study demonstrates a temporal heterogeneity of DNA methylation subclasses in 28.2% of glioblastomas, not impacting patient survival. Changes in cell state composition associated with subclass transition may be crucial for recurrent glioblastoma targeted therapies.

Pituitary neuroendocrine tumors with PIT1/SF1 co-expression show distinct clinicopathological and molecular features.

Pituitary neuroendocrine tumors (PitNETs) are classified according to cell lineage, which requires immunohistochemistry for adenohypophyseal hormones and the transcription factors (TFs) PIT1, SF1, and TPIT. According to the current WHO 2022 classification, PitNETs with co-expression of multiple TFs are termed "plurihormonal". Previously, PIT1/SF1 co-expression was prevailingly reported in PitNETs, which otherwise correspond to the somatotroph lineage. However, little is known about such tumors and the WHO classification has not recognized their significance. We compiled an in-house case series of 100 tumors, previously diagnosed as somatotroph PitNETs. Following TF staining, histopathological features associated with PIT1/SF1 co-expression were assessed. Integration of in-house and publicly available sample data allowed for a meta-analysis of SF1-associated clinicopathological and molecular features across a total of 270 somatotroph PitNETs. The majority (74%, 52/70) of our densely granulated somatotroph PitNETs (DGST) unequivocally co-expressed PIT1 and SF1 (DGST-PIT1/SF1). None (0%, 0/30) of our sparsely granulated somatotroph PitNETs (SGST) stained positive for SF1 (SGST-PIT1). Among DGST, PIT1/SF1 co-expression was significantly associated with scarce FSH/LH expression and fewer fibrous bodies compared to DGST-PIT1. Integrated molecular analyses including publicly available samples confirmed that DGST-PIT1/SF1, DGST-PIT1 and SGST-PIT1 represent distinct tumor subtypes. Clinicopathological meta-analyses indicated that DGST-PIT1 respond more favorably towards treatment with somatostatin analogs compared to DGST-PIT1/SF1, while both these subtypes show an overall less aggressive clinical course than SGST-PIT1. In this study, we spotlight that DGST with co-expression of PIT1 and SF1 represent a common, yet underrecognized, distinct PitNET subtype. Our study questions the rationale of generally classifying such tumors as "plurihormonal", and calls for a refinement of the WHO classification. We propose the term "somatogonadotroph PitNET".

Assessing the risk to develop a growing teratoma syndrome based on molecular and epigenetic subtyping as well as novel secreted biomarkers.

In germ cell tumors (GCT), a growing teratoma during chemotherapy with decreasing tumor markers was defined as 'growing teratoma syndrome' (GTS) by Logothetis et al. in 1982. So far, its pathogenesis and specific treatment options remain elusive. We aimed at updating the GTS definition based on molecular and epigenetic features as well as identifying circulating biomarkers. We selected 50 GTS patients for clinical characterization and subsequently 12 samples were molecularly analyzed. We further included 7 longitudinal samples of 2 GTS patients. Teratomas (TER) showing no features of GTS served as controls. GTS were stratified based on growth rates into a slow (<0.5 cm/month), medium (0.5-1.5) and rapid (>1.5) group. By analyzing DNA methylation, microRNA expression and the secretome, we identified putative epigenetic and secreted biomarkers for the GTS subgroups. We found that proteins enriched in the GTS groups compared to TER were involved in proliferation, DNA replication and the cell cycle, while proteins interacting with the immune system were depleted. Additionally, GTSrapid seem to interact more strongly with the surrounding microenvironment than GTSslow. Expression of pluripotency- and yolk-sac tumor-associated genes in GTS and formation of a yolk-sac tumor or somatic-type malignancy in the longitudinal GTS samples, pointed at an additional occult non-seminomatous component after chemotherapy. Thus, updating the Logothetis GTS definition is necessary, which we propose as follows: The GTS describes a continuously growing teratoma that might harbor occult non-seminomatous components considerably reduced during therapy but outgrowing over time again.

Intraventricular SHH inhibition proves efficient in SHH medulloblastoma mouse model and prevents systemic side effects.

BACKGROUND: Medulloblastoma (MB) is the most common malignant brain tumor in children and requires intensive multimodal therapy. Long-term survival is still dissatisfying and, most importantly, survivors frequently suffer from severe treatment-associated morbidities. The sonic hedgehog pathway (SHH) in SHH MB provides a promising target for specific therapeutic agents. The small molecule Vismodegib allosterically inhibits SMO, the main upstream activator of SHH. Vismodegib has proven effective in the treatment of MB in mice and in clinical studies. However, due to irreversible premature epiphyseal growth plate fusions after systemic application to infant mice and children, its implementation to pediatric patients has been limited. Intraventricular Vismodegib application might provide a promising novel treatment strategy for pediatric medulloblastoma patients. METHODS: Infant medulloblastoma-bearing Math1-cre::Ptch1Fl/Fl mice were treated with intraventricular Vismodegib in order to evaluate efficacy on tumor growth and systemic side effects. RESULTS: We show that intraventricular Vismodegib treatment of Math1-cre::Ptch1Fl/Fl mice leads to complete or partial tumor remission only 2 days after completed treatment. Intraventricular treatment also significantly improved symptom-free survival in a dose-dependent manner. At the same time, intraventricular application prevented systemic side effects in the form of anatomical or histological bone deformities. CONCLUSIONS: We conclude that intraventricular application of a SHH pathway inhibitor combines the advantages of a specific treatment agent with precise drug delivery and might evolve as a promising new way of targeted treatment for SHH MB patients.

Classification of Brain Tumors by Nanopore Sequencing of Cell-Free DNA from Cerebrospinal Fluid.

BACKGROUND: Molecular brain tumor diagnosis is usually dependent on tissue biopsies or resections. This can pose several risks associated with anesthesia or neurosurgery, especially for lesions in the brain stem or other difficult-to-reach anatomical sites. Apart from initial diagnosis, tumor progression, recurrence, or the acquisition of novel genetic alterations can only be proven by re-biopsies. METHODS: We employed Nanopore sequencing on cell-free DNA (cfDNA) from cerebrospinal fluid (CSF) and analyzed copy number variations (CNV) and global DNA methylation using a random forest classifier. We sequenced 129 samples with sufficient DNA. These samples came from 99 patients and encompassed 22 entities. Results were compared to clinical diagnosis and molecular analysis of tumor tissue, if available. RESULTS: 110/129 samples were technically successful, and 50 of these contained detectable circulating tumor DNA (ctDNA) by CNV or methylation profiling. ctDNA was detected in samples from patients with progressive disease but also from patients without known residual disease. CNV plots showed diagnostic and prognostic alterations, such as C19MC amplifications in embryonal tumors with multilayered rosettes or Chr.1q gains and Chr.6q losses in posterior fossa group A ependymoma, respectively. Most CNV profiles mirrored the profiles of the respective tumor tissue. DNA methylation allowed exact classification of the tumor in 22/110 cases and led to incorrect classification in 2/110 cases. Only 5/50 samples with detected ctDNA contained tumor cells detectable through microscopy. CONCLUSIONS: Our results suggest that Nanopore sequencing data of cfDNA from CSF samples may be a promising approach for initial brain tumor diagnostics and an important tool for disease monitoring.

Grade 3 meningioma survival and recurrence outcomes in an international multicenter cohort.

OBJECTIVE: Grade 3 meningioma represents a rare meningioma subtype, for which limited natural history data are available. The objective of this study was to identify demographics and pathologic characteristics, clinical and functional status outcomes, and prognostic factors in an international cohort of grade 3 meningioma patients. METHODS: Clinical and histopathological data were collected for patients treated at 7 sites across North America and Europe between 1991 and 2022. RESULTS: A total of 103 patients (54% female, median age 65 [IQR 52, 72] years) were included. Sixty-seven (65%) patients had de novo grade 3 lesions, whereas 29 (28%) had malignant transformations of lower-grade meningiomas. All patients underwent initial resection of their tumor. Patients were followed for a median of 46 (IQR 24, 108) months, during which time there were 65 (73%) recurrences and 50 (49%) deaths. The 5-year overall survival (OS) and progression-free survival (PFS) rates were 66% (95% CI 56%-77%) and 37% (95% CI 28%-48%), respectively. Age ≥ 65 years and male sex were independent predictors of worse OS and PFS in multivariate regression analysis, while postoperative radiotherapy was independently associated with improved OS. Karnofsky Performance Status (KPS) remained stable relative to baseline over 5 years postdiagnosis among participants who were alive at the end of the follow-up period. CONCLUSIONS: This large multicenter study provides insight into the longitudinal outcomes of grade 3 meningioma, with respect to recurrence, survival, and functional status. This study affirms the survival benefit conferred by radiotherapy in this population and suggests good functional status outcomes for patients surviving to 5 years postoperatively.

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

BACKGROUND: The IDH-wildtype glioblastoma (GBM) patients have a devastating prognosis. Here, we analyzed the potential prognostic value of global DNA methylation of the tumors. METHODS: DNA methylation of 492 primary samples and 31 relapsed samples, each treated with combination therapy, and of 148 primary samples treated with radiation alone were compared with patient survival. We determined the mean methylation values and estimated the immune cell infiltration from the methylation data. Moreover, the mean global DNA methylation of 23 GBM cell lines was profiled and correlated to their cellular radiosensitivity as measured by colony formation assay. RESULTS: High mean DNA methylation levels correlated with improved survival, which was independent from known risk factors (MGMT promoter methylation, age, extent of resection; P = 0.009) and methylation subgroups. Notably, this correlation was also independent of immune cell infiltration, as higher number of immune cells indeed was associated with significantly better OS but lower mean methylation. Radiosensitive GBM cell lines had a significantly higher mean methylation than resistant lines (P = 0.007), and improved OS of patients treated with radiotherapy alone was also associated with higher DNA methylation (P = 0.002). Furthermore, specimens of relapsed GBM revealed a significantly lower mean DNA methylation compared to the matching primary tumor samples (P = 0.041). CONCLUSIONS: Our results indicate that mean global DNA methylation is independently associated with outcome in glioblastoma. The data also suggest that a higher DNA methylation is associated with better radiotherapy response and less aggressive phenotype, both of which presumably contribute to the observed correlation with OS.