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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. [ABSTRACT FROM AUTHOR]

This article explores the distribution and composition of the ferritin complex in the adult brain and its connection to neuroferritinopathy (NF), a type of neurodegeneration with brain iron accumulation (NBIA). NF is characterized by symptoms like movement disturbances and tremors. The study identifies a novel variant in the ferritin heavy chain gene (FTH1) that is associated with NF and provides insights into the role of ferritin in both healthy and diseased brains. The authors, a diverse group of researchers, present their findings in a respectful and culturally sensitive manner, making this report a valuable resource for library patrons researching this topic. [Extracted from the article]

The nucleolus, the largest subcompartment of the nucleus, stands out from the nucleoplasm due to its exceptionally high local RNA and low DNA concentrations. Within this central hub of nuclear RNA metabolism, ribosome biogenesis is the most prominent ribonucleoprotein (RNP) biogenesis process, critically determining the structure and function of the nucleolus. However, recent studies have shed light on other roles of the nucleolus, exploring the interplay with various noncoding RNAs that are not directly involved in ribosome synthesis. This review focuses on this intriguing topic and summarizes the techniques to study and the latest findings on nucleolar long noncoding RNAs (lncRNAs) as well as microRNAs (miRNAs) in the context of nucleolus biology beyond ribosome biogenesis. We particularly focus on the multifaceted roles of the nucleolus and noncoding RNAs in physiology and tumor biology. [ABSTRACT FROM AUTHOR]

Simple Summary: Meningioma is the most common primary intracranial tumor. DNA methylation-based subtyping, while highly useful for diagnosis and treatment planning, is costly and not widely available. Therefore, the identification of methylation classes based on histological sections would be highly beneficial as it could greatly support and accelerate diagnostic and treatment decisions. We developed and systematically evaluated an AI framework to perform the classification of the most prevalent methylation subtypes based on histological sections. The model achieved a balanced accuracy of 0.870 for benign-1 vs benign-2 and 0.749 for benign-1 vs. intermediate-A in a narrow validation set. Combined with the network's assessed focus on key tumor regions these results provide a promising proof-of-concept of such an AI-driven classification approach in precision medicine. Convolutional neural networks (CNNs) are becoming increasingly valuable tools for advanced computational histopathology, promoting precision medicine through exceptional visual decoding abilities. Meningiomas, the most prevalent primary intracranial tumors, necessitate accurate grading and classification for informed clinical decision-making. Recently, DNA methylation-based molecular classification of meningiomas has proven to be more effective in predicting tumor recurrence than traditional histopathological methods. However, DNA methylation profiling is expensive, labor-intensive, and not widely accessible. Consequently, a digital histology-based prediction of DNA methylation classes would be advantageous, complementing molecular classification. In this study, we developed and rigorously assessed an attention-based multiple-instance deep neural network for predicting meningioma methylation classes using tumor methylome data from 142 (+51) patients and corresponding hematoxylin-eosin-stained histological sections. Pairwise analysis of sample cohorts from three meningioma methylation classes demonstrated high accuracy in two combinations. The performance of our approach was validated using an independent set of 51 meningioma patient samples. Importantly, attention map visualization revealed that the algorithm primarily focuses on tumor regions deemed significant by neuropathologists, offering insights into the decision-making process of the CNN. Our findings highlight the capacity of CNNs to effectively harness phenotypic information from histological sections through computerized images for precision medicine. Notably, this study is the first demonstration of predicting clinically relevant DNA methylome information using computer vision applied to standard histopathology. The introduced AI framework holds great potential in supporting, augmenting, and expediting meningioma classification in the future. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) is a disease with an inflammatory phenotype with increasing prevalence in the elderly. Expanded population of mutant blood cells carrying somatic mutations is termed clonal hematopoiesis of indeterminate potential (CHIP). The association between CHIP and COPD and its relevant effects on DNA methylation in aging are mainly unknown. Analyzing the deep-targeted amplicon sequencing from 125 COPD patients, we found enhanced incidence of CHIP mutations (~20%) with a predominance of DNMT3A CHIP-mediated hypomethylation of Phospholipase D Family Member 5 (PLD5), which in turn is positively correlated with increased levels of glycerol phosphocholine, pro-inflammatory cytokines, and deteriorating lung function. [ABSTRACT FROM AUTHOR]

Summary In the era of next generation sequencing and beyond, the Sanger technique is still widely used for variant verification of inconclusive or ambiguous high-throughput sequencing results or as a low-cost molecular genetical analysis tool for single targets in many fields of study. Many analysis steps need time-consuming manual intervention. Therefore, we present here a pipeline-capable high-throughput solution with an optional Shiny web interface, that provides a binary mutation decision of hotspots together with plotted chromatograms including annotations via flat files. Availability and implementation SangeR is freely available at https://github.com/Neuropathology-Giessen/SangeR and https://hub.docker.com/repository/docker/kaischmid/sange%5fr Contact Kai.Schmid@patho.med.uni-giessen.de or Daniel.Amsel@patho.med.uni-giessen.de Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

We previously reported on the first neuropathological round robin trials operated together with Quality in Pathology (QuIP) GmbH in 2018 and 2019 in Germany, i.e., the trials on IDH mutational testing and MGMT promoter methylation analysis [1]. For 2020 and 2021, the spectrum of round robin trials has been expanded to cover the most commonly used assays in neuropathological institutions. In addition to IDH mutation and MGMT promoter methylation testing, there is a long tradition for 1p/19q codeletion testing relevant in the context of the diagnosis of oligodendroglioma. With the 5 th edition of the World Health Organization (WHO) classification of the central nervous system tumors, additional molecular markers came into focus: TERT promoter mutation is often assessed as a molecular diagnostic criterion for IDH-wildtype glioblastoma. Moreover, several molecular diagnostic markers have been introduced for pediatric brain tumors. Here, trials on KIAA1549::BRAF fusions (common in pilocytic astrocytomas) and H3-3A mutations (in diffuse midline gliomas, H3-K27-altered and diffuse hemispheric gliomas, H3-G34-mutant) were most desired by the neuropathological community. In this update, we report on these novel round robin trials. In summary, success rates in all four trials ranged from 75 to 96%, arguing for an overall high quality level in the field of molecular neuropathological diagnostics.

Purpose: Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established ( CDKN2A/B and TERT ), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma., Methods: DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 multicenter cases., Results: Both CNV- and methylation family-based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively)., Conclusion: Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction., Competing Interests: Elisabeth J. RushingConsulting or Advisory Role: Bayer Suisse Stefan M. PfisterResearch Funding: Lilly, Bayer, Roche, PharmaMar, PfizerPatents, Royalties, Other Intellectual Property: patent on using DNA methylation profiling for tumor classification Michael WellerHonoraria: Merck Serono, MSD, Philogen, Nerviano Medical Sciences, Adastra PharmaceuticalsConsulting or Advisory Role: Bristol Myers Squibb, Orbus Therapeutics, Tocagen, Karyopharm Therapeutics, Ymabs Therapeutics Inc, MedacResearch Funding: Merck Serono, Novocure, Merck Sharp & Dohme, Apogenix, Quercegen Pharmaceuticals Matthias PreusserHonoraria: Roche, GlaxoSmithKline, Bayer, Bristol Myers Squibb, Novartis, Gerson Lehrman Group, CMC Contrast, Mundipharma, BMJ Journals, MedMedia, AstraZeneca, AbbVie, Lilly, MEDahead, Daiichi Sankyo, Sanofi, Merck Sharp & Dome, Tocagen, Adastra PharmaceuticalsConsulting or Advisory Role: Roche, Bristol Myers Squibb, Novartis, Gerson Lehrman Group, CMC Contrast, GlaxoSmithKline, Mundipharma, AbbVieResearch Funding: Roche, GlaxoSmithKline, Boehringer Ingelheim, Merck Sharp & Dohme, Bristol Myers Squibb, Daiichi Sankyo, AbbVieTravel, Accommodations, Expenses: Roche, GlaxoSmithKline, Bristol Myers Squibb, MSD, Mundipharma Andreas von DeimlingConsulting or Advisory Role: Bristol Myers SquibbResearch Funding: BayerPatents, Royalties, Other Intellectual Property: Patent for IDH1R132H antibody H09 administered by the German Cancer Center (DKFZ), Patent for BRAFV600E antibody VE1 administered by the German Cancer Center (DKFZ), DNA methylation–based method for classifying tumor species EP16710700Travel, Accommodations, Expenses: Roche Felix SahmHonoraria: Illumina, AbbVie, BayerNo other potential conflicts of interest were reported.

Ependymomas encompass a heterogeneous group of central nervous system (CNS) neoplasms that occur along the entire neuroaxis. In recent years, extensive (epi-)genomic profiling efforts have identified several molecular groups of ependymoma that are characterized by distinct molecular alterations and/or patterns. Based on unsupervised visualization of a large cohort of genome-wide DNA methylation data, we identified a highly distinct group of pediatric-type tumors (n = 40) forming a cluster separate from all established CNS tumor types, of which a high proportion were histopathologically diagnosed as ependymoma. RNA sequencing revealed recurrent fusions involving the pleomorphic adenoma gene-like 1 (PLAGL1) gene in 19 of 20 of the samples analyzed, with the most common fusion being EWSR1:PLAGL1 (n = 13). Five tumors showed a PLAGL1:FOXO1 fusion and one a PLAGL1:EP300 fusion. High transcript levels of PLAGL1 were noted in these tumors, with concurrent overexpression of the imprinted genes H19 and IGF2, which are regulated by PLAGL1. Histopathological review of cases with sufficient material (n = 16) demonstrated a broad morphological spectrum of tumors with predominant ependymoma-like features. Immunohistochemically, tumors were GFAP positive and OLIG2- and SOX10 negative. In 3/16 of the cases, a dot-like positivity for EMA was detected. All tumors in our series were located in the supratentorial compartment. Median age of the patients at the time of diagnosis was 6.2 years. Median progression-free survival was 35 months (for 11 patients with data available). In summary, our findings suggest the existence of a novel group of supratentorial neuroepithelial tumors that are characterized by recurrent PLAGL1 fusions and enriched for pediatric patients., (© 2021. The Author(s).)

Objective: Precursors of peptide hormones undergo posttranslational modifications within the trans-Golgi network (TGN). Dysfunction of proteins involved at different steps of this process cause several complex syndromes affecting the central nervous system (CNS). We aimed to clarify the genetic cause in a group of patients characterized by hypopituitarism in combination with brain atrophy, thin corpus callosum, severe developmental delay, visual impairment, and epilepsy., Methods: Whole exome sequencing was performed in seven individuals of six unrelated families with these features. Postmortem histopathological and HID1 expression analysis of brain tissue and pituitary gland were conducted in one patient. Functional consequences of the homozygous HID1 variant p.R433W were investigated by Seahorse XF Assay in fibroblasts of two patients., Results: Bi-allelic variants in the gene HID1 domain-containing protein 1 (HID1) were identified in all patients. Postmortem examination confirmed cerebral atrophy with enlarged lateral ventricles. Markedly reduced expression of pituitary hormones was found in pituitary gland tissue. Colocalization of HID1 protein with the TGN was not altered in fibroblasts of patients compared to controls, while the extracellular acidification rate upon stimulation with potassium chloride was significantly reduced in patient fibroblasts compared to controls., Interpretation: Our findings indicate that mutations in HID1 cause an early infantile encephalopathy with hypopituitarism as the leading presentation, and expand the list of syndromic CNS diseases caused by interference of TGN function. ANN NEUROL 2021;90:149-164., (© 2021 The Authors. Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)