Patterns of intersectional tumor volumes in T2-weighted MRI and [18F]FET PET in adult glioma: a prospective, observational study.

Brain tumor volumes as assessed by magnetic resonance imaging (MRI) do not always spatially overlap with biological tumor volumes (BTV) measured by [18F]Fluoroethyltyrosine positron emission tomography ([18F]FET PET). We prospectively investigated volumetric patterns based on the extent of tumor volume overlap between the two modalities. Eighty-six patients with newly diagnosed glioma who had undergone MRI and [18F]FET PET between 2007 and 2009 were included in this prospective study and (re-)classified according to CNS WHO 2021 (Classification of Tumors of the Central Nervous System by the World Health Organization). Four different patterns of volume overlap were defined mathematically according to the extent of overlap between MRI-based T2 tumor volume (non-enhancing tumor volume, nCEV) and BTVs. Progression-free (PFS) and overall survival (OS) were determined. Seventy patients were diagnosed with isocitrate dehydrogenase wildtype (IDHwt) glioblastoma and 16 with IDH-mutant glioma, respectively. The most common pattern was characterized by a larger non-contrast-enhancing tumor volume (nCEV) that enclosed all or most of the BTV and was observed in 46 patients (54%) (pattern 1). This pattern was more frequent in IDH-mutant gliomas than in IDH-wildtype glioblastoma (81% versus 47%, p = 0.02). In multivariate analyses, pattern 1 was associated with prolonged PFS (HR 0.59; 95 CI 0.34-1.0; p = 0.05), but not OS (HR 0.66; 95 CI 0.4-1.08; p = 0.1). For OS, presence of an IDH mutation (p = 0.05) and lower age (p = 0.03) were associated with prolonged OS. The spatial relation between nCEV and BTV varies within and between glioma entities. Most frequently, a larger nCEV encases the BTV. Some patients show spatially dissociated nCEVs and BTVs. Not accounting for this phenomenon in surgery or radiotherapy planning might lead to undertreatment.

PD-1 blockade does not improve efficacy of EpCAM-directed CAR T-cell in lung cancer brain metastasis.

BACKGROUND: Lung cancer brain metastasis has a devastating prognosis, necessitating innovative treatment strategies. While chimeric antigen receptor (CAR) T-cell show promise in hematologic malignancies, their efficacy in solid tumors, including brain metastasis, is limited by the immunosuppressive tumor environment. The PD-L1/PD-1 pathway inhibits CAR T-cell activity in the tumor microenvironment, presenting a potential target to enhance therapeutic efficacy. This study aims to evaluate the impact of anti-PD-1 antibodies on CAR T-cell in treating lung cancer brain metastasis. METHODS: We utilized a murine immunocompetent, syngeneic orthotopic cerebral metastasis model for repetitive intracerebral two-photon laser scanning microscopy, enabling in vivo characterization of red fluorescent tumor cells and CAR T-cell at a single-cell level over time. Red fluorescent EpCAM-transduced Lewis lung carcinoma cells (EpCAM/tdtLL/2 cells) were implanted intracranially. Following the formation of brain metastasis, EpCAM-directed CAR T-cell were injected into adjacent brain tissue, and animals received either anti-PD-1 or an isotype control. RESULTS: Compared to controls receiving T-cell lacking a CAR, mice receiving EpCAM-directed CAR T-cell showed higher intratumoral CAR T-cell densities in the beginning after intraparenchymal injection. This finding was accompanied with reduced tumor growth and translated into a survival benefit. Additional anti-PD-1 treatment, however, did not affect intratumoral CAR T-cell persistence nor tumor growth and thereby did not provide an additional therapeutic effect. CONCLUSION: CAR T-cell therapy for brain malignancies appears promising. However, additional anti-PD-1 treatment did not enhance intratumoral CAR T-cell persistence or effector function, highlighting the need for novel strategies to improve CAR T-cell therapy in solid tumors.

Dual MAPK Inhibition Triggers Pro-inflammatory Signals and Sensitizes BRAF V600E Glioma to T Cell-Mediated Checkpoint Therapy.

BRAF V600E pediatric low-grade gliomas frequently transform into high-grade gliomas (HGG) and poorly respond to chemotherapy, resulting in high mortality. Although combined BRAF and MEK inhibition (BRAFi+MEKi) outperforms chemotherapy, ∼70% of BRAF V600E HGG patients are therapy resistant and undergo unbridled tumor progression. BRAF V600E glioma have an immune-rich microenvironment suggesting that they could be responsive to immunotherapy but effects of BRAFi+MEKi on anti-tumor immunity are unclear. Using patient tumor tissue before and after BRAFi+MEKi, two novel syngeneic murine models of BRAF V600E HGG, and patient-derived cell lines, we examined the effects of clinically relevant BRAFi+MEKi with dabrafenib and trametinib on tumor growth, cell states, and tumor-infiltrating T cells. We find that BRAFi+MEKi treatment: i) upregulated programmed cell death protein-1 (PD-1) signaling genes and PD-1 ligand (PD-L1) protein expression in murine BRAF V600E HGG by stimulating IFNγ and IL-27, ii) attenuated T cell activity by IL-23, IL-27 and IL-32 production, which can promote the expansion of regulatory T cells, and iii) induced glial differentiation linked to a therapy-resistant PD-L1+ compartment through Galectin-3 secretion by tumor cells. Murine BRAF V600E HGG shrinkage by BRAFi+MEKi is associated with the upregulation of interferon-gamma response genes, MHC class I/II expression, and antigen presentation and processing programs, indicative of increased anti-tumor immunity. Combined BRAFi+MEKi with therapeutic antibodies inhibiting the PD-1 and cytotoxic T-lymphocyte associated protein 4 (CTLA-4) immune checkpoints re-activate T cells and provide a survival benefit over single therapy in a T cell-dependent manner. The quadruple treatment overcame BRAFi+MEKi resistance by invigorating T cell-mediated anti-tumor immunity in murine BRAF V600E HGG. PD-L1 expression was elevated in human BRAF-mutant versus BRAF-wildtype glioblastoma clinical specimen, complementing experimental findings and suggesting translational relevance for patient care.

Determinants of long-term survival in patients with IDH-mutant gliomas.

BACKGROUND: Survival times of patients with IDH-mutant gliomas are variable and can extend to decades. Many studies provide progression-free rather than overall survival times and prognostic factors remain ill-defined. Here we explored characteristics of short- and long-term survivors within a cohort of patients with extended follow-up. METHODS: This single-center, case-control study included 86 patients diagnosed between 1998 and 2023 who either died within 6 years after diagnosis or survived at least 15 years. Patient characteristics and prognostic factors were stratified by short- (< 6 years) versus long-term (≥ 15 years) survival. RESULTS: Forty-seven patients (55%) diagnosed with astrocytoma and 39 patients (45%) with oligodendroglioma were included retrospectively. Median follow-up of the survivors was 16.6 years (range 15-28.9). Thirty-four deaths (40%) had been reported at database closure. Long-term survival was associated with CNS WHO grade 2 (p < 0.01), smaller tumor volumes (p = 0.01), lack of contrast enhancement (p < 0.01), wait-and-scan strategies (p < 0.01) and female sex (p = 0.04). In multivariate analyses for oligodendroglioma, larger T2 tumor volumes were associated with shorter survival (HR 1.02; 95% CI 1.01-1.05; p = 0.04). In patients with astrocytoma, lack of contrast enhancement (HR 0.38; 95% CI 0.15-0.94; p = 0.04) and wait-and-scan strategies (HR 5.75; 95% CI 1.66-26.61; p = 0.01) were associated with longer survival. CONCLUSION: Large T2 tumor volume and contrast enhancement may be important risk factors for shorter survival, while age might be of lesser importance. Wait-and-scan strategies may yield excellent long-term survival in some patients with astrocytoma.

DNA Methylation Profiling of Salivary Gland Tumors Supports and Expands Conventional Classification.

Tumors of the major and minor salivary glands histologically encompass a diverse and partly overlapping spectrum of frequent diagnostically challenging neoplasms. Despite recent advances in molecular testing and the identification of tumor-specific mutations or gene fusions, there is an unmet need to identify additional diagnostic biomarkers for entities lacking specific alterations. In this study, we collected a comprehensive cohort of 363 cases encompassing 20 different salivary gland tumor entities and explored the potential of DNA methylation to classify these tumors. We were able to show that most entities show specific epigenetic signatures and present a machine learning algorithm that achieved a mean balanced accuracy of 0.991. Of note, we showed that cribriform adenocarcinoma is epigenetically distinct from classical polymorphous adenocarcinoma, which could support risk stratification of these tumors. Myoepithelioma and pleomorphic adenoma form a uniform epigenetic class, supporting the theory of a single entity with a broad but continuous morphologic spectrum. Furthermore, we identified a histomorphologically heterogeneous but epigenetically distinct class that could represent a novel tumor entity. In conclusion, our study provides a comprehensive resource of the DNA methylation landscape of salivary gland tumors. Our data provide novel insight into disputed entities and show the potential of DNA methylation to identify new tumor classes. Furthermore, in future, our machine learning classifier could support the histopathologic diagnosis of salivary gland tumors.

Epigenetic profiling of prostate cancer reveals potential prognostic signatures.

PURPOSE: While epigenetic profiling discovered biomarkers in several tumor entities, its application in prostate cancer is still limited. We explored DNA methylation-based deconvolution of benign and malignant prostate tissue for biomarker discovery and the potential of radiomics as a non-invasive surrogate. METHODS: We retrospectively included 30 patients (63 [58-79] years) with prostate cancer (PCa) who had a multiparametric MRI of the prostate before radical prostatectomy between 2014 and 2019. The control group comprised four patients with benign prostate tissue adjacent to the PCa lesions and four patients with benign prostatic hyperplasia. Tissue punches of all lesions were obtained. DNA methylation analysis and reference-free in silico deconvolution were conducted to retrieve Latent Methylation Components (LCMs). LCM-based clustering was analyzed for cellular composition and correlated with clinical disease parameters. Additionally, PCa and adjacent benign lesions were analyzed using radiomics to predict the epigenetic signatures non-invasively. RESULTS: LCMs identified two clusters with potential prognostic impact. Cluster one was associated with malignant prostate tissue (p < 0.001) and reduced immune-cell-related signatures (p = 0.004) of CD19 and CD4 cells. Cluster one comprised exclusively malignant prostate tissue enriched for significant prostate cancer and advanced tumor stages (p < 0.03 for both). No radiomics model could non-invasively predict the epigenetic clusters. CONCLUSION: Epigenetic clusters were associated with prognostically and clinically relevant metrics in prostate cancer. Further, immune cell-related signatures differed significantly between prognostically favorable and unfavorable clusters. Further research is necessary to explore potential diagnostic and therapeutic implications.

Diagnosis of Hirschsprung disease by analyzing acetylcholinesterase staining using artificial intelligence.

OBJECTIVES: Classical Hirschsprung disease (HD) is defined by the absence of ganglion cells in the rectosigmoid colon. The diagnosis is made from rectal biopsy, which reveals the aganglionosis and the presence of cholinergic hyperinnervation. However, depending on the method of rectal biopsy, the quality of the specimens and the related diagnostic accuracy varies substantially. To facilitate and objectify the diagnosis of HD, we investigated whether software-based identification of cholinergic hyperinnervation in digitalized histopathology slides is suitable for distinguishing healthy individuals from affected individuals. METHODS: N = 190 samples of 112 patients who underwent open surgical rectal biopsy at our pediatric surgery center between 2009 and 2019 were included in this study. Acetylcholinesterase (AChE) stained slides of these samples were collected and digitalized via slide scanning and analyzed using two digital imaging software programs (HALO, QuPath). The AChE-positive staining area in the mucosal layers of the intestinal wall was determined. In the next step machine learning was employed to identify patterns of cholinergic hyperinnervation. RESULTS: The area of AChE-positive staining was greater in HD patients compared to healthy individuals (p < 0.0001). Artificial intelligence-based assessment of parasympathetic hyperinnervation identified HD with a high precision (area under the curve [AUC] 0.96). The accuracy of the prediction model increased when nonrectal samples were excluded (AUC 0.993). CONCLUSIONS: Software-assisted machine-learning analysis of AChE staining is suitable to improve the diagnostic accuracy of HD.

Disturbance in cerebral blood microcirculation and hypoxic-ischemic microenvironment are associated with the development of brain metastasis.

Brain metastases (BM) constitute an increasing challenge in oncology due to their impact on neurological function, limited treatment options, and poor prognosis. BM occur through extravasation of circulating tumor cells across the blood-brain barrier. However, the extravasation processes are still poorly understood. We here propose a brain colonization process which mimics infarction-like microenvironmental reactions, that is dependent on Angiopoietin (Ang-2) and vascular endothelial growth factor (VEGF). In this study, intracardiac BM models were used, and cerebral blood microcirculation was monitored by 2-photon microscopy through a cranial window. BM formation was observed using cranial magnetic resonance, bioluminescent imaging, and post-mortem autopsy. Ang-2/VEGF targeting strategies and Ang-2 gain-of-function (GOF) mice were employed to interfere with BM formation. In addition, vascular and stromal factors as well as clinical outcome were analyzed in BM patients. Blood vessel occlusions by cancer cells were detected, accompanied by significant disturbances of cerebral blood microcirculation, and focal stroke-like histological signs. Cerebral endothelial cells showed an elevated Ang-2 expression both in mouse and human BM. Ang-2 GOF resulted in an increased BM burden. Combined anti-Ang-2/anti-VEGF therapy led to a decrease in brain metastasis size and number. Ang-2 expression in tumor vessels of established human brain metastases negatively correlated with survival. Our observations revealed a relationship between disturbance of cerebral blood microcirculation and brain metastasis formation. This suggests that vessel occlusion by tumor cells facilitates brain metastatic extravasation and seeding, while combined inhibition of microenvironmental effects of Ang-2 and VEGF prevent the outgrowth of macrometastases.

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.

Fatty acid-binding protein 5 is a functional biomarker and indicator of ferroptosis in cerebral hypoxia.

The progression of human degenerative and hypoxic/ischemic diseases is accompanied by widespread cell death. One death process linking iron-catalyzed reactive species with lipid peroxidation is ferroptosis, which shows hallmarks of both programmed and necrotic death in vitro. While evidence of ferroptosis in neurodegenerative disease is indicated by iron accumulation and involvement of lipids, a stable marker for ferroptosis has not been identified. Its prevalence is thus undetermined in human pathophysiology, impeding recognition of disease areas and clinical investigations with candidate drugs. Here, we identified ferroptosis marker antigens by analyzing surface protein dynamics and discovered a single protein, Fatty Acid-Binding Protein 5 (FABP5), which was stabilized at the cell surface and specifically elevated in ferroptotic cell death. Ectopic expression and lipidomics assays demonstrated that FABP5 drives redistribution of redox-sensitive lipids and ferroptosis sensitivity in a positive-feedback loop, indicating a role as a functional biomarker. Notably, immunodetection of FABP5 in mouse stroke penumbra and in hypoxic postmortem patients was distinctly associated with hypoxically damaged neurons. Retrospective cell death characterized here by the novel ferroptosis biomarker FABP5 thus provides first evidence for a long-hypothesized intrinsic ferroptosis in hypoxia and inaugurates a means for pathological detection of ferroptosis in tissue.

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.

Perifocal edema is a risk factor for preoperative seizures in patients with meningioma WHO grade 2 and 3.

BACKGROUND: Patients with intracranial meningiomas frequently suffer from tumor-related seizures prior to resection, impacting patients' quality of life. We aimed to elaborate on incidence and predictors for seizures in a patient cohort with meningiomas WHO grade 2 and 3. METHODS: We retrospectively searched for patients with meningioma WHO grade 2 and 3 according to the 2021 WHO classification undergoing tumor resection. Clinical, histopathological and imaging findings were collected and correlated with preoperative seizure development. Tumor and edema volumes were quantified. RESULTS: Ninety-five patients with a mean age of 59.5 ± 16.0 years were included. Most tumors (86/95, 90.5%) were classified as atypical meningioma WHO grade 2. Nine of 95 tumors (9.5%) corresponded to anaplastic meningiomas WHO grade 3, including six patients harboring TERT promoter mutations. Meningiomas were most frequently located at the convexity in 38/95 patients (40.0%). Twenty-eight of 95 patients (29.5%) experienced preoperative seizures. Peritumoral edema was detected in 62/95 patients (65.3%) with a median volume of 9 cm3 (IR: 0-54 cm3). Presence of peritumoral edema but not age, tumor localization, TERT promoter mutation, brain invasion or WHO grading was associated with incidence of preoperative seizures, as confirmed in multivariate analysis (OR: 6.61, 95% CI: 1.18, 58.12, p = *0.049). Postoperative freedom of seizures was achieved in 91/95 patients (95.8%). CONCLUSIONS: Preoperative seizures were frequently encountered in about every third patient with meningioma WHO grade 2 or 3. Patients presenting with peritumoral edema on preoperative imaging are at particular risk for developing tumor-related seizures. Tumor resection was highly effective in achieving seizure freedom.

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.

DistSNE: Distributed computing and online visualization of DNA methylation-based central nervous system tumor classification.

The current state-of-the-art analysis of central nervous system (CNS) tumors through DNA methylation profiling relies on the tumor classifier developed by Capper and colleagues, which centrally harnesses DNA methylation data provided by users. Here, we present a distributed-computing-based approach for CNS tumor classification that achieves a comparable performance to centralized systems while safeguarding privacy. We utilize the t-distributed neighborhood embedding (t-SNE) model for dimensionality reduction and visualization of tumor classification results in two-dimensional graphs in a distributed approach across multiple sites (DistSNE). DistSNE provides an intuitive web interface (https://gin-tsne.med.uni-giessen.de) for user-friendly local data management and federated methylome-based tumor classification calculations for multiple collaborators in a DataSHIELD environment. The freely accessible web interface supports convenient data upload, result review, and summary report generation. Importantly, increasing sample size as achieved through distributed access to additional datasets allows DistSNE to improve cluster analysis and enhance predictive power. Collectively, DistSNE enables a simple and fast classification of CNS tumors using large-scale methylation data from distributed sources, while maintaining the privacy and allowing easy and flexible network expansion to other institutes. This approach holds great potential for advancing human brain tumor classification and fostering collaborative precision medicine in neuro-oncology.

The impact of referring patients with drug-resistant focal epilepsy to an epilepsy center for presurgical diagnosis.

BACKGROUND: Epilepsy surgery is an established treatment for drug-resistant focal epilepsy (DRFE) that results in seizure freedom in about 60% of patients. Correctly identifying an epileptogenic lesion in magnetic resonance imaging (MRI) is challenging but highly relevant since it improves the likelihood of being referred for presurgical diagnosis. The epileptogenic lesion's etiology directly relates to the surgical intervention's indication and outcome. Therefore, it is vital to correctly identify epileptogenic lesions and their etiology presurgically. METHODS: We compared the final histopathological diagnoses of all patients with DRFE undergoing epilepsy surgery at our center between 2015 and 2021 with their MRI diagnoses before and after presurgical diagnosis at our epilepsy center, including MRI evaluations by expert epilepsy neuroradiologists. Additionally, we analyzed the outcome of different subgroups. RESULTS: This study included 132 patients. The discordance between histopathology and MRI diagnoses significantly decreased from 61.3% for non-expert MRI evaluations (NEMRIs) to 22.1% for epilepsy center MRI evaluations (ECMRIs; p < 0.0001). The MRI-sensitivity improved significantly from 68.6% for NEMRIs to 97.7% for ECMRIs (p < 0.0001). Identifying focal cortical dysplasia (FCD) and amygdala dysplasia was the most challenging for both subgroups. 65.5% of patients with negative NEMRI were seizure-free 12 months postoperatively, no patient with negative ECMRI achieved seizure-freedom. The mean duration of epilepsy until surgical intervention was 13.6 years in patients with an initial negative NEMRI and 9.5 years in patients with a recognized lesion in NEMRI. CONCLUSIONS: This study provides evidence that for patients with DRFE-especially those with initial negative findings in a non-expert MRI-an early consultation at an epilepsy center, including an ECMRI, is important for identifying candidates for epilepsy surgery. NEMRI-negative findings preoperatively do not preclude seizure freedom postoperatively. Therefore, patients with DRFE that remain MRI-negative after initial NEMRI should be referred to an epilepsy center for presurgical evaluation. Nonreferral based on NEMRI negativity may harm such patients and delay surgical intervention. However, ECMRI-negative patients have a reduced chance of becoming seizure-free after epilepsy surgery. Further improvements in MRI technique and evaluation are needed and should be directed towards improving sensitivity for FCDs and amygdala dysplasias.

Wnt/ß-Catenin-Signaling Modulates Megakaryopoiesis at the Megakaryocyte-Erythrocyte Progenitor Stage in the Hematopoietic System.

The bone marrow (BM) hematopoietic system (HS) gives rise to blood cells originating from hematopoietic stem cells (HSCs), including megakaryocytes (MKs) and red blood cells (erythrocytes; RBCs). Many steps of the cell-fate decision remain to be elucidated, being important for cancer treatment. To explore the role of Wnt/ß-catenin for MK and RBC differentiation, we activated ß-catenin signaling in platelet-derived growth factor b (Pdgfb)-expressing cells of the HS using a Cre-lox approach (Ctnnb1BM-GOF). FACS analysis revealed that Pdgfb is mainly expressed by megakaryocytic progenitors (MKPs), MKs and platelets. Recombination resulted in a lethal phenotype in mutants (Ctnnb1BM-GOFwt/fl, Ctnnb1BM-GOFfl/fl) 3 weeks after tamoxifen injection, showing an increase in MKs in the BM and spleen, but no pronounced anemia despite reduced erythrocyte counts. BM transplantation (BMT) of Ctnnb1BM-GOF BM into lethally irradiated wildtype recipients (BMT-Ctnnb1BM-GOF) confirmed the megakaryocytic, but not the lethal phenotype. CFU-MK assays in vitro with BM cells of Ctnnb1BM-GOF mice supported MK skewing at the expense of erythroid colonies. Molecularly, the runt-related transcription factor 1 (RUNX1) mRNA, known to suppress erythropoiesis, was upregulated in Ctnnb1BM-GOF BM cells. In conclusion, ß-catenin activation plays a key role in cell-fate decision favoring MK development at the expense of erythroid production.

Molecular refinement of pilocytic astrocytoma in adult patients.

AIM: Pilocytic astrocytomas (PA) in adults are rare and may be challenging to identify based only on histomorphology. Compared to their paediatric counterparts, they are reportedly molecularly more diverse and associated with a worse prognosis. We aimed to describe the characteristics of adult PAs more precisely by comprehensively profiling a series of 79 histologically diagnosed adult cases (≥18 years). METHODS: We performed global DNA methylation profiling and DNA and RNA panel sequencing, and integrated the results with clinical data. We further compared the molecular characteristics of adult and paediatric PAs that had a significant match to one of the established PA methylation classes in the Heidelberg brain tumour classifier. RESULTS: The mean age in our cohort was 33 years, and 43% of the tumours were located supratentorially. Based on methylation profiling, only 39% of the cases received a significant match to a PA methylation class. Sixteen per cent matched a different tumour type and 45% had a Heidelberg classifier score <0.9 with an affiliation to diverse established methylation classes in t-SNE analyses. Although the KIAA1549::BRAF fusion was found in 98% of paediatric PAs, this was true for only 27% of histologically defined and 55% of adult PAs defined by methylation profiling. CONCLUSIONS: A particularly high fraction of adult tumours with histological features of PA do not match current PA methylation classes, indicating ambiguous histology and an urgent need for molecular profiling. Moreover, even in adult PAs with a match to a PA methylation class, the distribution of genetic drivers differs significantly from their paediatric counterparts (p<0.01).

Gliomatosis cerebri (GC) growth pattern: A single-center analysis of clinical, histological, and molecular characteristics of GC and non-GC glioblastoma.

Background: The biological understanding of glioblastoma (GB) with gliomatosis cerebri (GC) pattern is poor due to the absence of GC-specific studies. Here, we aimed to identify molecular or clinical parameters that drive GC growth. Methods: From our methylome database of IDH (isocitrate dehydrogenase)-wildtype GB, we identified 158 non-GC and 65 GC cases. GC cases were subdivided into diffuse-infiltrative (subtype 1), multifocal (subtype 2), or tumors with 1 solid mass (subtype 3). We compared clinical, histological, and molecular parameters and conducted a reference-free tumor deconvolution of DNA methylation data based on latent methylation components (LMC). Results: GC subtype 1 less frequently showed contrast-enhancing tumors, and more frequently lacked morphological GB criteria despite displaying GB DNA methylation profile. However, the tumor deconvolution did not deliver a specific LMC cluster for either of the GC subtypes. Employing the reference-based analysis MethylCIBERSORT, we did not identify significant differences in tumor cell composition. The majority of both GC and non-GC patients received radiochemotherapy as first-line treatment, but there was a major imbalance for resection. The entire GC cohort had significantly shorter overall survival (OS) and time to treatment failure (TTF) than the non-GC cohort. However, when filtering for cases in which only stereotactic biopsy was performed, the comparison of OS and TTF lost statistical significance. Conclusions: Our study offers clinically relevant information by demonstrating a similar outcome for GB with GC growth pattern in the surgically matched analysis. The limited number of cases in the GC subgroups encourages the validation of our DNA methylation analysis in larger cohorts.

A framework for standardised tissue sampling and processing during resection of diffuse intracranial glioma: joint recommendations from four RANO groups.

Surgical resection represents the standard of care for people with newly diagnosed diffuse gliomas, and the neuropathological and molecular profile of the resected tissue guides clinical management and forms the basis for research. The Response Assessment in Neuro-Oncology (RANO) consortium is an international, multidisciplinary effort that aims to standardise research practice in neuro-oncology. These recommendations represent a multidisciplinary consensus from the four RANO groups: RANO resect, RANO recurrent glioblastoma, RANO radiotherapy, and RANO/PET for a standardised workflow to achieve a representative tumour evaluation in a disease characterised by intratumoural heterogeneity, including recommendations on which tumour regions should be surgically sampled, how to define those regions on the basis of preoperative imaging, and the optimal sample volume. Practical recommendations for tissue sampling are given for people with low-grade and high-grade gliomas, as well as for people with newly diagnosed and recurrent disease. Sampling of liquid biopsies is also addressed. A standardised workflow for subsequent handling of the resected tissue is proposed to avoid information loss due to decreasing tissue quality or insufficient clinical information. The recommendations offer a framework for prospective biobanking studies.