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.

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.

Predictive role of intracranial PD-L1 expression in a real-world cohort of NSCLC patients treated with immune checkpoint inhibition following brain metastasis resection.

BACKGROUND: Emerging evidence suggests that treatment of NSCLC brain metastases with immune checkpoint inhibitors (ICIs) is associated with response rates similar to those of extracranial disease. Programmed death-ligand 1 (PD-L1) tumor proportion score (TPS) serves as a predictive biomarker for ICI response. However, the predictive value of brain metastasis-specific (intracranial) PD-L1 TPS is not established. We investigated the role of intra- and extracranial PD-L1 TPS in NSCLC patients treated with ICI following brain metastasis resection. METHODS: Clinical data from NSCLC patients treated with ICI following brain metastasis resection (n = 64) were analyzed. PD-L1 TPS of brain metastases (n = 64) and available matched extracranial tumor tissue (n = 44) were assessed via immunohistochemistry. Statistical analyses included cut point estimation via maximally selected rank statistics, Kaplan-Meier estimates, and multivariable Cox regression analysis for intracranial progression-free survival (icPFS), extracranial progression-free survival (ecPFS), and overall survival (OS). RESULTS: PD-L1 expression was found in 54.7% of brain metastases and 68.2% of extracranial tumor tissues, with a median intra- and extracranial PD-L1 TPS of 7.5% (0 - 50%, IQR) and 15.0% (0 - 80%, IQR), respectively. In matched tissue samples, extracranial PD-L1 TPS was significantly higher than intracranial PD-L1 TPS (p = 0.013). Optimal cut points for intracranial and extracranial PD-L1 TPS varied according to outcome parameter assessed. Notably, patients with a high intracranial PD-L1 TPS (> 40%) exhibited significantly longer icPFS as compared to patients with a low intracranial PD-L1 TPS (≤ 40%). The cut point of 40% for intracranial PD-L1 TPS was independently associated with OS, icPFS and ecPFS in multivariable analyses. CONCLUSION: Our study highlights the potential role of intracranial PD-L1 TPS in NSCLC, which could be used to predict ICI response in cases where extracranial tissue is not available for PD-L1 assessment as well as to specifically predict intracranial response.

Validation of a methylation-based signature for subventricular zone involvement in glioblastoma.

PURPOSE: Glioblastomas (GBM) with subventricular zone (SVZ) contact have previously been associated with a specific epigenetic fingerprint. We aim to validate a reported bulk methylation signature to determine SVZ contact. METHODS: Methylation array analysis was performed on IDHwt GBM patients treated at our institution. The v11b4 classifier was used to ensure the inclusion of only receptor tyrosine kinase (RTK) I, II, and mesenchymal (MES) subtypes. Methylation-based assignment (SVZM ±) was performed using hierarchical cluster analysis. Magnetic resonance imaging (MRI) (T1ce) was independently reviewed for SVZ contact by three experienced readers. RESULTS: Sixty-five of 70 samples were classified as RTK I, II, and MES. Full T1ce MRI-based rater consensus was observed in 54 cases, which were retained for further analysis. Epigenetic SVZM classification and SVZ were strongly associated (OR: 15.0, p = 0.003). Thirteen of fourteen differential CpGs were located in the previously described differentially methylated LRBA/MAB21L2 locus. SVZ + tumors were linked to shorter OS (hazard ratio (HR): 3.80, p = 0.02) than SVZM + at earlier time points (time-dependency of SVZM, p < 0.05). Considering the SVZ consensus as the ground truth, SVZM classification yields a sensitivity of 96.6%, specificity of 36.0%, positive predictive value (PPV) of 63.6%, and negative predictive value (NPV) of 90.0%. CONCLUSION: Herein, we validated the specific epigenetic signature in GBM in the vicinity of the SVZ and highlighted the importance of methylation of a part of the LRBA/MAB21L2 gene locus. Whether SVZM can replace MRI-based SVZ assignment as a prognostic and diagnostic tool will require prospective studies of large, homogeneous cohorts.

AHRR and SFRP2 in primary versus recurrent high-grade serous ovarian carcinoma and their prognostic implication.

BACKGROUND: The aim of this study was to analyse transcriptomic differences between primary and recurrent high-grade serous ovarian carcinoma (HGSOC) to identify prognostic biomarkers. METHODS: We analysed 19 paired primary and recurrent HGSOC samples using targeted RNA sequencing. We selected the best candidates using in silico survival and pathway analysis and validated the biomarkers using immunohistochemistry on a cohort of 44 paired samples, an additional cohort of 504 primary HGSOCs and explored their function. RESULTS: We identified 233 differential expressed genes. Twenty-three showed a significant prognostic value for PFS and OS in silico. Seven markers (AHRR, COL5A2, FABP4, HMGCS2, ITGA5, SFRP2 and WNT9B) were chosen for validation at the protein level. AHRR expression was higher in primary tumours (p < 0.0001) and correlated with better patient survival (p < 0.05). Stromal SFRP2 expression was higher in recurrent samples (p = 0.009) and protein expression in primary tumours was associated with worse patient survival (p = 0.022). In multivariate analysis, tumour AHRR and SFRP2 remained independent prognostic markers. In vitro studies supported the anti-tumorigenic role of AHRR and the oncogenic function of SFRP2. CONCLUSIONS: Our results underline the relevance of AHRR and SFRP2 proteins in aryl-hydrocarbon receptor and Wnt-signalling, respectively, and might lead to establishing them as biomarkers in HGSOC.

Conumee 2.0: enhanced copy-number variation analysis from DNA methylation arrays for humans and mice.

MOTIVATION: Copy-number variations (CNVs) are common genetic alterations in cancer and their detection may impact tumor classification and therapeutic decisions. However, detection of clinically relevant large and focal CNVs remains challenging when sample material or resources are limited. This has motivated us to create a software tool to infer CNVs from DNA methylation arrays which are often generated as part of clinical routines and in research settings. RESULTS: We present our R package, conumee 2.0, that combines tangent normalization, an adjustable genomic binning heuristic, and weighted circular binary segmentation to utilize DNA methylation arrays for CNV analysis and mitigate technical biases and batch effects. Segmentation results were validated in a lung squamous cell carcinoma dataset from TCGA (n = 367 samples) by comparison to segmentations derived from genotyping arrays (Pearson's correlation coefficient of 0.91). We further introduce a segmented block bootstrapping approach to detect focal alternations that achieved 60.9% sensitivity and 98.6% specificity for deletions affecting CDKN2A/B (60.0% and 96.9% for RB1, respectively) in a low-grade glioma cohort from TCGA (n = 239 samples). Finally, our tool provides functionality to detect and summarize CNVs across large sample cohorts. AVAILABILITY AND IMPLEMENTATION: Conumee 2.0 is available under open-source license at: https://github.com/hovestadtlab/conumee2.

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.

A prospective observational study of real-world treatment and outcome in secondary CNS lymphoma.

BACKGROUND: Secondary central nervous system lymphoma (SCNSL) confers a dismal prognosis and treatment advances are constrained by the lack of prospective studies and real-world treatment evidence. METHODS: Patients with SCNSL of all entities were included at first diagnosis and patient characteristics, treatment data, and outcomes were prospectively collected in the Secondary CNS Lymphoma Registry (SCNSL-R) (NCT05114330). FINDINGS: 279 patients from 47 institutions were enrolled from 2011 to 2022 and 243 patients (median age: 66 years; range: 23-86) were available for analysis. Of those, 49 (20 %) patients presented with synchronous (cohort I) and 194 (80 %) with metachronous SCNSL (cohort II). The predominant histology was diffuse large B-cell lymphoma (DLBCL, 68 %). Median overall survival (OS) from diagnosis of CNS involvement was 17·2 months (95 % CI 12-27·5), with longer OS in cohort I (60·6 months, 95 % CI 45·5-not estimable (NE)) than cohort II (11·4 months, 95 % CI 7·8-17·7, log-rank test p < 0.0001). Predominant induction regimens included R-CHOP/high-dose MTX (cohort I) and high-dose MTX/cytarabine (cohort II). Rituximab was used in 166 (68 %) of B-cell lymphoma. Undergoing consolidating high-dose therapy and autologous hematopoietic stem cell transplantation (HDT-ASCT) in partial response (PR) or better was associated with longer OS (HR adjusted 0·47 (95 % CI 0·25-0·89), p = 0·0197). INTERPRETATION: This study is the largest prospective cohort of SCNSL patients providing a comprehensive overview of an international real-world treatment landscape and outcomes. Prognosis was better in patients with SCNSL involvement at initial diagnosis (cohort I) and consolidating HDT-ASCT was associated with favorable outcome in patients with PR or better.

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.

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.

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.

A Novel Type of IDH-wildtype Glioma Characterized by Gliomatosis Cerebri-like Growth Pattern, TERT Promoter Mutation, and Distinct Epigenetic Profile.

Diffuse gliomas in adults encompass a heterogenous group of central nervous system neoplasms. In recent years, extensive (epi-)genomic profiling has identified several glioma subgroups characterized by distinct molecular characteristics, most importantly IDH1/2 and histone H3 mutations. A group of 16 diffuse gliomas classified as "adult-type diffuse high-grade glioma, IDH-wildtype, subtype F (HGG-F)" was identified by the DKFZ v12.5 Brain Tumor Classifier . Histopathologic characterization, exome sequencing, and review of clinical data was performed in all cases. Based on unsupervised t -distributed stochastic neighbor embedding and clustering analysis of genome-wide DNA methylation data, HGG-F shows distinct epigenetic profiles separate from established central nervous system tumors. Exome sequencing demonstrated frequent TERT promoter (12/15 cases), PIK3R1 (11/16), and TP53 mutations (5/16). Radiologic characteristics were reminiscent of gliomatosis cerebri in 9/14 cases (64%). Histopathologically, most cases were classified as diffuse gliomas (7/16, 44%) or were suspicious for the infiltration zone of a diffuse glioma (5/16, 31%). None of the cases demonstrated microvascular proliferation or necrosis. Outcome of 14 patients with follow-up data was better compared to IDH-wildtype glioblastomas with a median progression-free survival of 58 months and overall survival of 74 months (both P <0.0001). Our series represents a novel type of adult-type diffuse glioma with distinct molecular and clinical features. Importantly, we provide evidence that TERT promoter mutations in diffuse gliomas without further morphologic or molecular signs of high-grade glioma should be interpreted in the context of the clinicoradiologic presentation as well as epigenetic profile and may not be suitable as a standalone marker for glioblastoma, IDH-wildtype.

Primary brain tumours in adults.

The most frequent adult-type primary CNS tumours are diffuse gliomas, but a large variety of rarer CNS tumour types exists. The classification of these tumours is increasingly based on molecular diagnostics, which is reflected in the extensive molecular foundation of the recent WHO 2021 classification of CNS tumours. Resection as extensive as is safely possible is the cornerstone of treatment in most gliomas, and is now also recommended early in the treatment of patients with radiological evidence of histologically low-grade tumours. For the adult-type diffuse glioma, standard of care is a combination of radiotherapy and chemotherapy. Although treatment with curative intent is not available, combined modality treatment has resulted in long-term survival (>10-20 years) for some patients with isocitrate dehydrogenase (IDH) mutant tumours. Other rarer tumours require tailored approaches, best delivered in specialised centres. Targeted treatments based on molecular alterations still only play a minor role in the treatment landscape of adult-type diffuse glioma, and today are mainly limited to patients with tumours with BRAFV600E (ie, Val600Glu) mutations. Immunotherapy for CNS tumours is still in its infancy, and so far, trials with checkpoint inhibitors and vaccination studies have not shown improvement in patient outcomes in glioblastoma. Current research is focused on improving our understanding of the immunosuppressive tumour environment, the molecular heterogeneity of tumours, and the role of tumour microtube network connections between cells in the tumour microenvironment. These factors all appear to play a role in treatment resistance, and indicate that novel approaches are needed to further improve outcomes of patients with CNS tumours.

Epigenetic neural glioblastoma enhances synaptic integration and predicts therapeutic vulnerability.

Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is nascent. We present an epigenetically defined neural signature of glioblastoma that independently affects 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 high abundance of stem cell-like malignant cells classified as oligodendrocyte precursor and neural precursor cell-like in high-neural glioblastoma. 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 associates with decreased survival as well as increased functional connectivity and can be detected via DNA analytes and brain-derived neurotrophic factor in plasma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant.

Diffuse paediatric-type high-grade glioma, H3-wildtype and IDH-wildtype: case series of a new entity.

Diffuse paediatric-type high-grade glioma, H3-wildtype and IDH-wildtype (pHGG) is a rare and aggressive brain tumor characterized by a specific DNA methylation profile. It was recently introduced in the 5th World Health Organization classification of central nervous system tumors of 2021. Clinical data on this tumor is scarce. This is a case series, which presents the first clinical experience with this entity. We compiled a retrospective case series on pHGG patients treated between 2015 and 2022 at our institution. Data collected include patients' clinical course, surgical procedure, histopathology, genome-wide DNA methylation analysis, imaging and adjuvant therapy. Eight pHGG were identified, ranging in age from 8 to 71 years. On MRI tumors presented with an unspecific intensity profile, T1w hypo- to isointense and T2w hyperintense, with inhomogeneous contrast enhancement, often with rim enhancement. Three patients died of the disease, with overall survival of 19, 28 and 30 months. Four patients were alive at the time of the last follow-up, 4, 5, 6 and 79 months after the initial surgery. One patient was lost to follow-up. Findings indicate that pHGG prevalence might be underestimated in the elderly population.

MAPK inhibitor sensitivity scores predict sensitivity driven by the immune infiltration in pediatric low-grade gliomas.

Pediatric low-grade gliomas (pLGG) show heterogeneous responses to MAPK inhibitors (MAPKi) in clinical trials. Thus, more complex stratification biomarkers are needed to identify patients likely to benefit from MAPKi therapy. Here, we identify MAPK-related genes enriched in MAPKi-sensitive cell lines using the GDSC dataset and apply them to calculate class-specific MAPKi sensitivity scores (MSSs) via single-sample gene set enrichment analysis. The MSSs discriminate MAPKi-sensitive and non-sensitive cells in the GDSC dataset and significantly correlate with response to MAPKi in an independent PDX dataset. The MSSs discern gliomas with varying MAPK alterations and are higher in pLGG compared to other pediatric CNS tumors. Heterogenous MSSs within pLGGs with the same MAPK alteration identify proportions of potentially sensitive patients. The MEKi MSS predicts treatment response in a small set of pLGG patients treated with trametinib. High MSSs correlate with a higher immune cell infiltration, with high expression in the microglia compartment in single-cell RNA sequencing data, while low MSSs correlate with low immune infiltration and increased neuronal score. The MSSs represent predictive tools for the stratification of pLGG patients and should be prospectively validated in clinical trials. Our data supports a role for microglia in the response to MAPKi.

Molecular diagnostic tools for the World Health Organization (WHO) 2021 classification of gliomas, glioneuronal and neuronal tumors; an EANO guideline.

In the 5th edition of the WHO CNS tumor classification (CNS5, 2021), multiple molecular characteristics became essential diagnostic criteria for many additional CNS tumor types. For those tumors, an integrated, "histomolecular" diagnosis is required. A variety of approaches exists for determining the status of the underlying molecular markers. The present guideline focuses on the methods that can be used for assessment of the currently most informative diagnostic and prognostic molecular markers for the diagnosis of gliomas, glioneuronal and neuronal tumors. The main characteristics of the molecular methods are systematically discussed, followed by recommendations and information on available evidence levels for diagnostic measures. The recommendations cover DNA and RNA next-generation-sequencing, methylome profiling, and select assays for single/limited target analyses, including immunohistochemistry. Additionally, because of its importance as a predictive marker in IDH-wildtype glioblastomas, tools for the analysis of MGMT promoter methylation status are covered. A structured overview of the different assays with their characteristics, especially their advantages and limitations, is provided, and requirements for input material and reporting of results are clarified. General aspects of molecular diagnostic testing regarding clinical relevance, accessibility, cost, implementation, regulatory, and ethical aspects are discussed as well. Finally, we provide an outlook on new developments in the landscape of molecular testing technologies in neuro-oncology.