A comprehensive histomolecular characterization of meningioangiomatosis: Further evidence for a precursor neoplastic lesion.

Meningioangiomatosis (MAM) remains a poorly understood lesion responsible for epileptic disease. In the past, MAM was primarily described in the context of neurofibromatosis type 2 before being mainly reported sporadically. Moreover, the malformative or tumoral nature is still debated. Because a subset of MAM are associated with meningiomas, some authors argue that MAM corresponds to an infiltration pattern of these tumors. For these reasons, MAM has not been added to the World Health Organization (WHO) Classification of Central Nervous System Tumors as a specific entity. In the present study, we characterized a series of pure MAM (n = 7) and MAM associated with meningiomas (n = 4) using histopathology, immunohistochemistry, genetic (fluorescent in situ and DNA sequencing analyses), and epigenetic (DNA-methylation profiling) data. We evidenced two distinct morphological patterns: MAM with a fibroblastic-like pattern having few lesional cells, and MAM with a more cellular pattern. A subset was associated with the genetic alterations previously reported in meningiomas (such as a KMT2C mutation and a hemizygous deletion of chromosome 22q including the NF2 gene). The DNA-methylation profile, using a t-distributed stochastic neighbor embedding analysis, evidenced that MAM (pure or associated with meningiomas) clustered in a separate group from pediatric meningiomas. The present results seem to suggest that MAM represents a neoplastic lesion and encourage the further study of similar additional series so that it may be included in a future WHO classification.

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.

Advancing noninvasive glioma classification with diffusion radiomics: Exploring the impact of signal intensity normalization.

Background: This study investigates the influence of diffusion-weighted Magnetic Resonance Imaging (DWI-MRI) on radiomic-based prediction of glioma types according to molecular status and assesses the impact of DWI intensity normalization on model generalizability. Methods: Radiomic features, compliant with image biomarker standardization initiative standards, were extracted from preoperative MRI of 549 patients with diffuse glioma, known IDH, and 1p19q-status. Anatomical sequences (T1, T1c, T2, FLAIR) underwent N4-Bias Field Correction (N4) and WhiteStripe normalization (N4/WS). Apparent diffusion coefficient (ADC) maps were normalized using N4 or N4/z-score. Nine machine-learning algorithms were trained for multiclass prediction of glioma types (IDH-mutant 1p/19q codeleted, IDH-mutant 1p/19q non-codeleted, IDH-wild type). Four approaches were compared: Anatomical, anatomical + ADC naive, anatomical + ADC N4, and anatomical + ADC N4/z-score. The University of California San Francisco (UCSF)-glioma dataset (n = 409) was used for external validation. Results: Naïve-Bayes algorithms yielded overall the best performance on the internal test set. Adding ADC radiomics significantly improved AUC from 0.79 to 0.86 (P = .011) for the IDH-wild-type subgroup, but not for the other 2 glioma subgroups (P > .05). In the external UCSF dataset, the addition of ADC radiomics yielded a significantly higher AUC for the IDH-wild-type subgroup (P ≤ .001): 0.80 (N4/WS anatomical alone), 0.81 (anatomical + ADC naive), 0.81 (anatomical + ADC N4), and 0.88 (anatomical + ADC N4/z-score) as well as for the IDH-mutant 1p/19q non-codeleted subgroup (P < .012 each). Conclusions: ADC radiomics can enhance the performance of conventional MRI-based radiomic models, particularly for IDH-wild-type glioma. The benefit of intensity normalization of ADC maps depends on the type and context of the used data.

CNS tumors with PLAGL1-fusion: beyond ZFTA and YAP1 in the genetic spectrum of supratentorial ependymomas.

A novel methylation class, "neuroepithelial tumor, with PLAGL1 fusion" (NET-PLAGL1), has recently been described, based on epigenetic features, as a supratentorial pediatric brain tumor with recurrent histopathological features suggesting an ependymal differentiation. Because of the recent identification of this neoplastic entity, few histopathological, radiological and clinical data are available. Herein, we present a detailed series of nine cases of PLAGL1-fused supratentorial tumors, reclassified from a series of supratentorial ependymomas, non-ZFTA/non-YAP1 fusion-positive and subependymomas of the young. This study included extensive clinical, radiological, histopathological, ultrastructural, immunohistochemical, genetic and epigenetic (DNA methylation profiling) data for characterization. An important aim of this work was to evaluate the sensitivity and specificity of a novel fluorescent in situ hybridization (FISH) targeting the PLAGL1 gene. Using histopathology, immunohistochemistry and electron microscopy, we confirmed the ependymal differentiation of this new neoplastic entity. Indeed, the cases histopathologically presented as "mixed subependymomas-ependymomas" with well-circumscribed tumors exhibiting a diffuse immunoreactivity for GFAP, without expression of Olig2 or SOX10. Ultrastructurally, they also harbored features reminiscent of ependymal differentiation, such as cilia. Different gene partners were fused with PLAGL1: FOXO1, EWSR1 and for the first time MAML2. The PLAGL1 FISH presented a 100% sensitivity and specificity according to RNA sequencing and DNA methylation profiling results. This cohort of supratentorial PLAGL1-fused tumors highlights: 1/ the ependymal cell origin of this new neoplastic entity; 2/ benefit of looking for a PLAGL1 fusion in supratentorial cases of non-ZFTA/non-YAP1 ependymomas; and 3/ the usefulness of PLAGL1 FISH.

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.

Plasma extracellular vesicles in meningioma patients following radiotherapy as liquid biopsy- a prospective explorative biomarker study (ARO 2023-05/AG-NRO-07).

BACKGROUND: While surgical resection remains the primary treatment approach for symptomatic or growing meningiomas, radiotherapy represents an auspicious alternative in patients with meningiomas not safely amenable to surgery. Biopsies are often omitted in light of potential postoperative neurological deficits, resulting in a lack of histological grading and (molecular) risk stratification. In this prospective explorative biomarker study, extracellular vesicles in the bloodstream will be investigated in patients with macroscopic meningiomas to identify a biomarker for molecular risk stratification and disease monitoring. METHODS: In total, 60 patients with meningiomas and an indication of radiotherapy (RT) and macroscopic tumor on the planning MRI will be enrolled. Blood samples will be obtained before the start, during, and after radiotherapy, as well as during clinical follow-up every 6 months. Extracellular vesicles will be isolated from the blood samples, quantified and correlated with the clinical treatment response or progression. Further, nanopore sequencing-based DNA methylation profiles of plasma EV-DNA will be generated for methylation-based meningioma classification. DISCUSSION: This study will explore the dynamic of plasma EVs in meningioma patients under/after radiotherapy, with the objective of identifying potential biomarkers of (early) tumor progression. DNA methylation profiling of plasma EVs in meningioma patients may enable molecular risk stratification, facilitating a molecularly-guided target volume delineation and adjusted dose prescription during RT treatment planning.

Heterogeneity of DNA methylation profiles and copy number alterations in 10782 adult-type glioblastomas, IDH-wildtype.

The morphological patterns leading to the diagnosis of glioblastoma may also commonly be observed in several other distinct tumor entities, which can result in a mixed bag of tumors subsumed under this diagnosis. The 2021 WHO Classification of CNS Tumors has separated several of these entities from the diagnosis of glioblastoma, IDH-wildtype. This study determines the DNA methylation classes most likely receiving the diagnosis glioblastoma, IDH wildtype according to the definition by the WHO 2021 Classification and provides comparative copy number analyses. We identified 10782 methylome datasets uploaded to the web page www.molecularneuropathology.org with a calibrated score of ≥0.9 by the Heidelberg Brain Tumor Classifier version v12.8. These methylation classes were characterized by the diagnosis glioblastoma being the most frequent classification encountered in each of the classes according to the WHO 2021 definition. Further, methylation classes selected for this study predominantly contained adult patients. Unsupervised clustering confirmed the presence of nine methylation classes containing tumors most likely receiving the diagnosis glioblastoma, IDH-wildtype according to the WHO 2021 definition. Copy number analysis and a focus on genes with typical numerical alterations in glioblastoma revealed clear differences between the nine methylation classes. Although great progress in diagnostic precision has been achieved over the last decade, our data clearly demonstrate that glioblastoma, IDH-wildtype still is a heterogeneous group in need of further stratification.

Repeat surgery of recurrent glioma for molecularly informed treatment in the age of precision oncology: A risk-benefit analysis.

PURPOSE: Surgery for recurrent glioma provides cytoreduction and tissue for molecularly informed treatment. With mostly heavily pretreated patients involved, it is unclear whether the benefits of repeat surgery outweigh its potential risks. METHODS: Patients receiving surgery for recurrent glioma WHO grade 2-4 with the goal of tissue sampling for targeted therapies were analyzed retrospectively. Complication rates (surgical, neurological) were compared to our institutional glioma surgery cohort. Tissue molecular diagnostic yield, targeted therapies and post-surgical survival rates were analyzed. RESULTS: Between 2017 and 2022, tumor board recommendation for targeted therapy through molecular diagnostics was made for 180 patients. Of these, 70 patients (38%) underwent repeat surgery. IDH-wildtype glioblastoma was diagnosed in 48 patients (69%), followed by IDH-mutant astrocytoma (n = 13; 19%) and oligodendroglioma (n = 9; 13%). Gross total resection (GTR) was achieved in 50 patients (71%). Tissue was processed for next-generation sequencing in 64 cases (91%), and for DNA methylation analysis in 58 cases (83%), while immunohistochemistry for mTOR phosphorylation was performed in 24 cases (34%). Targeted therapy was recommended in 35 (50%) and commenced in 21 (30%) cases. Postoperatively, 7 patients (11%) required revision surgery, compared to 7% (p = 0.519) and 6% (p = 0.359) of our reference cohorts of patients undergoing first and second craniotomy, respectively. Non-resolving neurological deterioration was documented in 6 cases (10% vs. 8%, p = 0.612, after first and 4%, p = 0.519, after second craniotomy). Median survival after repeat surgery was 399 days in all patients and 348 days in GBM patients after repeat GTR. CONCLUSION: Surgery for recurrent glioma provides relevant molecular diagnostic information with a direct consequence for targeted therapy under a reasonable risk of postoperative complications. With satisfactory postoperative survival it can therefore complement a multi-modal glioma therapy approach.

A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1.

Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. However, the determination of TM-interconnectivity in individual tumors is challenging and the impact on patient survival unresolved. Here, we establish a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells using a dye uptake methodology, and validate it with recording of cellular calcium epochs and clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, TM-network connectivity correlates with the mesenchymal subtype and dismal patient survival. CHI3L1 gene expression serves as a robust molecular marker of connectivity and functionally influences TM networks. The connectivity signature allows insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients' prognosis, and serves as a robust prognostic biomarker.

Pineal anlage tumor: clinical and diagnostic features, and rationales for treatment.

PURPOSE: To provide a treatment-focused review and develop basic treatment guidelines for patients diagnosed with pineal anlage tumor (PAT). METHODS: Prospectively collected data of three patients with pineal anlage tumor from Germany was combined with clinical details and treatment information from 17 published cases. RESULTS: Overall, 20 cases of PAT were identified (3 not previously reported German cases, 17 cases from published reports). Age at diagnosis ranged from 0.3 to 35.0 (median: 3.2 ± 7.8) years. All but three cases were diagnosed before the age of three years. For three cases, metastatic disease at initial staging was described. All patients underwent tumor surgery (gross-total resection: 9, subtotal resection/biopsy: 9, extent of resection unknown: 2). 15/20 patients were alive at last follow-up. Median follow-up for 10/15 surviving patients with available follow-up and treatment data was 2.4 years (0.3-6.5). Relapse was reported for 3 patients within 0.8 years after diagnosis. Five patients died, 3 after relapse and 2 from early postoperative complications. Two-year-progression-free- and -overall survival were 65.2 ± 12.7% and 49.2 ± 18.2%, respectively. All 4 patients who received intensive chemotherapy including high-dose chemotherapy combined with radiotherapy (2 focal, 2 craniospinal [CSI]) had no recurrence. Focal radiotherapy- and CSI-free survival rates in 13 evaluable patients were 46.2% (6/13) and 61.5% (8/13), respectively. CONCLUSION: PAT is an aggressive disease mostly affecting young children. Therefore, adjuvant therapy using intensive chemotherapy and considering radiotherapy appears to comprise an appropriate treatment strategy. Reporting further cases is crucial to evaluate distinct treatment strategies.

Cerebrospinal fluid cfDNA sequencing for classification of central nervous system glioma.

PURPOSE: Primary central nervous system (CNS) gliomas can be classified by characteristic genetic alterations. In addition to solid tissue obtained via surgery or biopsy, cell-free DNA (cfDNA) from cerebrospinal fluid (CSF) is an alternative source of material for genomic analyses. EXPERIMENTAL DESIGN: We performed targeted next-generation sequencing (NGS) of CSF cfDNA in a representative cohort of 85 patients presenting at two neurooncological centers with suspicion of primary or recurrent glioma. Copy-number variation (CNV) profiles, single nucleotide variants (SNVs), and small insertions/ deletions (indels) were combined into a molecular-guided tumor classification. Comparison with the solid tumor was performed for 38 cases with matching solid tissue available. RESULTS: Cases were stratified into four groups: glioblastoma (n = 32), other glioma (n = 19), non-malignant (n = 17) and non-diagnostic (n = 17). We introduced a molecular-guided tumor classification, which enabled identification of tumor entities and/ or cancer specific alterations in 75.0 % (n = 24) of glioblastoma and 52.6 % (n = 10) of other glioma cases. The overlap between CSF and matching solid tissue was highest for CNVs (26-48 %) and SNVs at pre-defined gene loci (44 %), followed by SNVs/ indels identified via uninformed variant calling (8-14 %). A molecular-guided tumor classification was possible for 23.5 % (n = 4) of non-diagnostic cases. CONCLUSIONS: We developed a targeted sequencing workflow for CSF cfDNA as well as a strategy for interpretation and reporting of sequencing results based on a molecular-guided tumor classification in glioma.

LOGGIC/FIREFLY-2: a phase 3, randomized trial of tovorafenib vs. chemotherapy in pediatric and young adult patients with newly diagnosed low-grade glioma harboring an activating RAF alteration.

BACKGROUND: Pediatric low-grade glioma (pLGG) is essentially a single pathway disease, with most tumors driven by genomic alterations affecting the mitogen-activated protein kinase/ERK (MAPK) pathway, predominantly KIAA1549::BRAF fusions and BRAF V600E mutations. This makes pLGG an ideal candidate for MAPK pathway-targeted treatments. The type I BRAF inhibitor, dabrafenib, in combination with the MEK inhibitor, trametinib, has been approved by the United States Food and Drug Administration for the systemic treatment of BRAF V600E-mutated pLGG. However, this combination is not approved for the treatment of patients with tumors harboring BRAF fusions as type I RAF inhibitors are ineffective in this setting and may paradoxically enhance tumor growth. The type II RAF inhibitor, tovorafenib (formerly DAY101, TAK-580, MLN2480), has shown promising activity and good tolerability in patients with BRAF-altered pLGG in the phase 2 FIREFLY-1 study, with an objective response rate (ORR) per Response Assessment in Neuro-Oncology high-grade glioma (RANO-HGG) criteria of 67%. Tumor response was independent of histologic subtype, BRAF alteration type (fusion vs. mutation), number of prior lines of therapy, and prior MAPK-pathway inhibitor use. METHODS: LOGGIC/FIREFLY-2 is a two-arm, randomized, open-label, multicenter, global, phase 3 trial to evaluate the efficacy, safety, and tolerability of tovorafenib monotherapy vs. current standard of care (SoC) chemotherapy in patients < 25 years of age with pLGG harboring an activating RAF alteration who require first-line systemic therapy. Patients are randomized 1:1 to either tovorafenib, administered once weekly at 420 mg/m2 (not to exceed 600 mg), or investigator's choice of prespecified SoC chemotherapy regimens. The primary objective is to compare ORR between the two treatment arms, as assessed by independent review per RANO-LGG criteria. Secondary objectives include comparisons of progression-free survival, duration of response, safety, neurologic function, and clinical benefit rate. DISCUSSION: The promising tovorafenib activity data, CNS-penetration properties, strong scientific rationale combined with the manageable tolerability and safety profile seen in patients with pLGG led to the SIOPe-BTG-LGG working group to nominate tovorafenib for comparison with SoC chemotherapy in this first-line phase 3 trial. The efficacy, safety, and functional response data generated from the trial may define a new SoC treatment for newly diagnosed pLGG. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05566795. Registered on October 4, 2022.

PerSurge (NOA-30) phase II trial of perampanel treatment around surgery in patients with progressive glioblastoma.

BACKGROUND: Glioblastoma is the most frequent and a particularly malignant primary brain tumor with no efficacy-proven standard therapy for recurrence. It has recently been discovered that excitatory synapses of the AMPA-receptor subtype form between non-malignant brain neurons and tumor cells. This neuron-tumor network connectivity contributed to glioma progression and could be efficiently targeted with the EMA/FDA approved antiepileptic AMPA receptor inhibitor perampanel in preclinical studies. The PerSurge trial was designed to test the clinical potential of perampanel to reduce tumor cell network connectivity and tumor growth with an extended window-of-opportunity concept. METHODS: PerSurge is a phase IIa clinical and translational treatment study around surgical resection of progressive or recurrent glioblastoma. In this multicenter, 2-arm parallel-group, double-blind superiority trial, patients are 1:1 randomized to either receive placebo or perampanel (n = 66 in total). It consists of a treatment and observation period of 60 days per patient, starting 30 days before a planned surgical resection, which itself is not part of the study interventions. Only patients with an expected safe waiting interval are included, and a safety MRI is performed. Tumor cell network connectivity from resected tumor tissue on single cell transcriptome level as well as AI-based assessment of tumor growth dynamics in T2/FLAIR MRI scans before resection will be analyzed as the co-primary endpoints. Secondary endpoints will include further imaging parameters such as pre- and postsurgical contrast enhanced MRI scans, postsurgical T2/FLAIR MRI scans, quality of life, cognitive testing, overall and progression-free survival as well as frequency of epileptic seizures. Further translational research will focus on additional biological aspects of neuron-tumor connectivity. DISCUSSION: This trial is set up to assess first indications of clinical efficacy and tolerability of perampanel in recurrent glioblastoma, a repurposed drug which inhibits neuron-glioma synapses and thereby glioblastoma growth in preclinical models. If perampanel proved to be successful in the clinical setting, it would provide the first evidence that interference with neuron-cancer interactions may indeed lead to a benefit for patients, which would lay the foundation for a larger confirmatory trial in the future. TRIAL REGISTRATION: EU-CT number: 2023-503938-52-00 30.11.2023.

Efficacy and toxicity of bimodal radiotherapy in WHO grade 2 meningiomas following subtotal resection with carbon ion boost: prospective phase 2 MARCIE trial.

BACKGROUND: Novel radiotherapeutic modalities using carbon ions provide an increased relative biological effectiveness (RBE) compared to photons, delivering a higher biological dose while reducing the radiation exposure for adjacent organs. This prospective phase 2 trial investigated bimodal radiotherapy using photons with carbon-ion (C12)-boost in patients with WHO grade 2 meningiomas following subtotal resection (Simpson grade 4 or 5). METHODS: A total of 33 patients were enrolled from July 2012 until July 2020. Study treatment comprised a C12-boost (18 Gy [RBE] in 6 fractions) applied to the macroscopic tumor in combination with photon radiotherapy (50 Gy in 25 fractions). Primary endpoint was the 3-year progression-free survival (PFS) , and secondary endpoints included overall survival, safety and treatment toxicities. RESULTS: With a median follow-up of 42 months, the 3-year estimates of PFS, local PFS and overall survival were 80.3%, 86.7% and 89.8%, respectively. Radiation-induced contrast enhancement (RICE) was encountered in 45%, particularly in patients with periventricularly-located meningiomas. Patients exhibiting RICE were mostly either asymptomatic (40%) or presented immediate neurological and radiological improvement (47%) after the administration of corticosteroids or bevacizumab in case of radiation necrosis (3/33). Treatment-associated complications occurred in one patient with radiation necrosis who died due to postoperative complications after resection of radiation necrosis. The study was prematurely terminated after recruiting 33 of the planned 40 patients. CONCLUSIONS: Our study demonstrates a bimodal approach utilizing photons with C12-boost may achieve an superior local PFS to conventional photon RT, but must be balanced against the potential risks of toxicities.

Cluster-based prognostication in glioblastoma: Unveiling heterogeneity based on diffusion and perfusion similarities.

BACKGROUND: While the association between diffusion and perfusion MRI and survival in glioblastoma is established, prognostic models for patients are lacking. This study employed clustering of functional imaging to identify distinct functional phenotypes in untreated glioblastomas, assessing their prognostic significance for overall survival. METHODS: A total of 289 patients with glioblastoma who underwent preoperative multimodal MR imaging were included. Mean values of apparent diffusion coefficient (ADC) normalized relative cerebral blood volume (nrCBV), and relative cerebral blood flow (rCBF) were calculated for different tumor compartments and the entire tumor. Distinct imaging patterns were identified using Partition Around Medoids (PAM) clustering on the training dataset, and their ability to predict overall survival was assessed. Additionally, tree-based machine-learning models were trained to ascertain the significance of features pertaining to cluster membership. RESULTS: Using the training dataset (231/289) we identified two stable imaging phenotypes through PAM clustering with significantly different overall survival (OS). Validation in an independent test set revealed a high-risk group with a median OS of 10.2 months and a low-risk group with a median OS of 26.6 months (p=0.012). Patients in the low-risk cluster had high diffusion and low perfusion values throughout, while the high-risk cluster displayed the reverse pattern. Including cluster membership in all multivariate Cox regression analyses improved performance (p≤ 0.004 each). CONCLUSIONS: Our research demonstrates that data-driven clustering can identify clinically relevant, distinct imaging phenotypes, highlighting the potential role of diffusion and perfusion MRI in predicting survival rates of glioblastoma patients.

Concurrent gliomas in patients with multiple sclerosis.

BACKGROUND: Concurrent malignant brain tumors in patients with multiple sclerosis (MS) constitute a rare but paradigmatic phenomenon for studying neuroimmunological mechanisms from both molecular and clinical perspectives. METHODS: A multicenter cohort of 26 patients diagnosed with both primary brain tumors and multiple sclerosis was studied for disease localization, tumor treatment-related MS activity, and molecular characteristics specific for diffuse glioma in MS patients. RESULTS: MS neither predisposes nor protects from the development of gliomas. Patients with glioblastoma WHO grade 4 without isocitratdehydrogenase (IDH) mutations have a longstanding history of MS, whereas patients diagnosed with IDH-mutant astrocytoma WHO grade 2 receive multiple sclerosis diagnosis mostly at the same time or later. Concurrent MS is associated with a lesser extent of tumor resection and a worse prognosis in IDH-mutant glioma patients (PFS 32 vs. 64 months, p = 0.0206). When assessing tumor-intrinsic differences no distinct subgroup-defining methylation pattern is identified in gliomas of MS patients compared to other glioma samples. However, differential methylation of immune-related genetic loci including human leukocyte antigen locus on 6p21 and interleukin locus on 5q31 is found in MS patients vs. matched non-MS patients. In line, inflammatory disease activity increases in 42% of multiple sclerosis patients after brain tumor radiotherapy suggesting a susceptibility of multiple sclerosis brain tissue to pro-inflammatory stimuli such as ionizing radiation. CONCLUSIONS: Concurrent low-grade gliomas should be considered in multiple sclerosis patients with slowly progressive, expansive T2/FLAIR lesions. Our findings of typically reduced extent of resection in MS patients and increased MS activity after radiation may inform future treatment decisions.

Brain tumors such as gliomas can evade attacks by the immune system. In contrast, some diseases of the central nervous system such as multiple sclerosis (MS) are caused by an overactive immune system. Our study looks at a cohort of rare patients with both malignant glioma and concurrent MS and examines how each disease and their treatments affect each other. Our data suggest that even in patients with known MS, if medical imaging findings are unusual, a concurrent brain tumor should be excluded at an early stage. Radiotherapy, as is the standard of care for malignant brain tumors, may worsen the inflammatory disease activity in MS patients, which may be associated with certain genetic risk factors. Our findings may help to inform treatment of patients with brain tumors and MS.

Generation of patient-derived pediatric pilocytic astrocytoma in-vitro models using SV40 large T: evaluation of a modeling workflow.

PURPOSE: Although pediatric low-grade gliomas (pLGG) are the most common pediatric brain tumors, patient-derived cell lines reflecting pLGG biology in culture are scarce. This also applies to the most common pLGG subtype pilocytic astrocytoma (PA). Conventional cell culture approaches adapted from higher-grade tumors fail in PA due to oncogene-induced senescence (OIS) driving tumor cells into arrest. Here, we describe a PA modeling workflow using the Simian Virus large T antigen (SV40-TAg) to circumvent OIS. METHODS: 18 pLGG tissue samples (17 (94%) histological and/or molecular diagnosis PA) were mechanically dissociated. Tumor cell positive-selection using A2B5 was perfomed in 8/18 (44%) cases. All primary cell suspensions were seeded in Neural Stem Cell Medium (NSM) and Astrocyte Basal Medium (ABM). Resulting short-term cultures were infected with SV40-TAg lentivirus. Detection of tumor specific alterations (BRAF-duplication and BRAF V600E-mutation) by digital droplet PCR (ddPCR) at defined time points allowed for determination of tumor cell fraction (TCF) and evaluation of the workflow. DNA-methylation profiling and gene-panel sequencing were used for molecular profiling of primary samples. RESULTS: Primary cell suspensions had a mean TCF of 55% (+/- 23% (SD)). No sample in NSM (0/18) and ten samples in ABM (10/18) were successfully transduced. Three of these ten (30%) converted into long-term pLGG cell lines (TCF 100%), while TCF declined to 0% (outgrowth of microenvironmental cells) in 7/10 (70%) cultures. Young patient age was associated with successful model establishment. CONCLUSION: A subset of primary PA cultures can be converted into long-term cell lines using SV40-TAg depending on sample intrinsic (patient age) and extrinsic workflow-related (e.g. type of medium, successful transduction) parameters. Careful monitoring of sample-intrinsic and extrinsic factors optimizes the process.

Reference on copy number variations in pleomorphic xanthoastrocytoma: Implications for diagnostic approach.

Pleomorphic xanthoastrocytoma (PXA) poses a diagnostic challenge. The present study relies on methylation-based predictions and focuses on copy number variations (CNV) in PXA. We identified 551 tumors from patients having received the histologic diagnosis or differential diagnosis pleomorphic xanthoastrocytoma (PXA) uploaded to the web page www.molecularneuropathology.org. Of these 551 tumors, 165 received the prediction "methylation class (anaplastic) pleomorphic xanthoastrocytoma" with a calibrated score >=0.9 by the brain tumor classifier version v12.8 and, therefore, were defined the PXA reference set designated mcPXAref. In addition to these 165 mcPXAref, 767 other tumors received the prediction mcPXA with a calibrated score >=0.9 but without a histological PXA diagnosis. The total number of individual tumors predicted by histology and/or by methylome based classification as PXA, mcPXA or both was 1318, and these were designated the study cohort. The selection of a control cohort was guided by methylation-based predictions recurrently observed for the other 386/551 tumors diagnosed as histologic PXA. 131/386 received predictions for another entity besides PXA with a score >=0.9. Control tumors corresponding to the 11 most common other predictions were selected, adding up to 1100 reference cases. CNV profiles were calculated from all methylation datasets of the study and control cohorts. Special attention was given to the 7/10 signature, gene amplifications and homozygous deletion of CDKN2A/B. Comparison of CNV in the subsets of the study cohort and the control cohort were used to establish relations independent of histological diagnoses. Tumors in mcPXA were highly homogenous in regard to CNV alterations, irrespective of the histological diagnoses. The 7/10 signature commonly present in glioblastoma, IDH-wildtype, was present in 15-20% of mcPXA, whereas amplification of oncogenes (likewise common in glioblastoma) was very rare in mcPXA (<1%). In contrast, the histology-based PXA group exhibited high variance in regard to methylation classes as well as to CNVs. Our data add to the notion, that histologically defined PXA likely only represent a subset of the biological disease.