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      ATRT–SHH comprises three molecular subgroups with characteristic clinical and histopathological features and prognostic significance

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      Acta Neuropathologica
      Springer Berlin Heidelberg
      Atypical teratoid/rhabdoid tumor, Sonic hedgehog, DNA methylation profiling, Gene expression, OLIG2, GFAP, ASCL1, Neuroradiology, Prognosis, Overall survival

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          Abstract

          Atypical teratoid/rhabdoid tumor (ATRT) is an aggressive central nervous system tumor characterized by loss of SMARCB1/INI1 protein expression and comprises three distinct molecular groups, ATRT–TYR, ATRT–MYC and ATRT–SHH. ATRT–SHH represents the largest molecular group and is heterogeneous with regard to age, tumor location and epigenetic profile. We, therefore, aimed to investigate if heterogeneity within ATRT–SHH might also have biological and clinical importance. Consensus clustering of DNA methylation profiles and confirmatory t-SNE analysis of 65 ATRT–SHH yielded three robust molecular subgroups, i.e., SHH-1A, SHH-1B and SHH-2. These subgroups differed by median age of onset (SHH-1A: 18 months, SHH-1B: 107 months, SHH-2: 13 months) and tumor location (SHH-1A: 88% supratentorial; SHH-1B: 85% supratentorial; SHH-2: 93% infratentorial, often extending to the pineal region). Subgroups showed comparable SMARCB1 mutational profiles, but pathogenic/likely pathogenic SMARCB1 germline variants were over-represented in SHH-2 (63%) as compared to SHH-1A (20%) and SHH-1B (0%). Protein expression of proneural marker ASCL1 (enriched in SHH-1B) and glial markers OLIG2 and GFAP (absent in SHH-2) as well as global mRNA expression patterns differed, but all subgroups were characterized by overexpression of SHH as well as Notch pathway members. In a Drosophila model, knockdown of Snr1 (the fly homologue of SMARCB1) in hedgehog activated cells not only altered hedgehog signaling, but also caused aberrant Notch signaling and formation of tumor-like structures. Finally, on survival analysis, molecular subgroup and age of onset (but not ASCL1 staining status) were independently associated with overall survival, older patients (> 3 years) harboring SHH-1B experiencing relatively favorable outcome. In conclusion, ATRT–SHH comprises three subgroups characterized by SHH and Notch pathway activation, but divergent molecular and clinical features. Our data suggest that molecular subgrouping of ATRT–SHH has prognostic relevance and might aid to stratify patients within future clinical trials.

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          The online version contains supplementary material available at 10.1007/s00401-022-02424-5.

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          The 2021 WHO Classification of Tumors of the Central Nervous System: a summary

          The fifth edition of the WHO Classification of Tumors of the Central Nervous System (CNS), published in 2021, is the sixth version of the international standard for the classification of brain and spinal cord tumors. Building on the 2016 updated fourth edition and the work of the Consortium to Inform Molecular and Practical Approaches to CNS Tumor Taxonomy, the 2021 fifth edition introduces major changes that advance the role of molecular diagnostics in CNS tumor classification. At the same time, it remains wedded to other established approaches to tumor diagnosis such as histology and immunohistochemistry. In doing so, the fifth edition establishes some different approaches to both CNS tumor nomenclature and grading and it emphasizes the importance of integrated diagnoses and layered reports. New tumor types and subtypes are introduced, some based on novel diagnostic technologies such as DNA methylome profiling. The present review summarizes the major general changes in the 2021 fifth edition classification and the specific changes in each taxonomic category. It is hoped that this summary provides an overview to facilitate more in-depth exploration of the entire fifth edition of the WHO Classification of Tumors of the Central Nervous System.
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            DNA methylation-based classification of central nervous system tumours

            Summary Accurate pathological diagnosis is crucial for optimal management of cancer patients. For the ~100 known central nervous system (CNS) tumour entities, standardization of the diagnostic process has been shown to be particularly challenging - with substantial inter-observer variability in the histopathological diagnosis of many tumour types. We herein present the development of a comprehensive approach for DNA methylation-based CNS tumour classification across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that availability of this method may have substantial impact on diagnostic precision compared with standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility we have designed a free online classifier tool (www.molecularneuropathology.org) requiring no additional onsite data processing. Our results provide a blueprint for the generation of machine learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.
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              Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age Groups.

              Ependymal tumors across age groups are currently classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patients' outcome. We aimed at establishing a uniform molecular classification using DNA methylation profiling. Nine molecular subgroups were identified in a large cohort of 500 tumors, 3 in each anatomical compartment of the CNS, spine, posterior fossa, supratentorial. Two supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification and thus might serve as a basis for the next World Health Organization classification of CNS tumors.
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                Author and article information

                Contributors
                hasselblatt@uni-muenster.de
                Journal
                Acta Neuropathol
                Acta Neuropathol
                Acta Neuropathologica
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0001-6322
                1432-0533
                30 April 2022
                30 April 2022
                2022
                : 143
                : 6
                : 697-711
                Affiliations
                [1 ]GRID grid.510964.f, Hopp Children’s Cancer Center (KiTZ), ; Heidelberg, Germany
                [2 ]GRID grid.7497.d, ISNI 0000 0004 0492 0584, Division of Paediatric Neurooncology, , German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), ; Heidelberg, Germany
                [3 ]GRID grid.16149.3b, ISNI 0000 0004 0551 4246, Institute of Neuropathology, , University Hospital Münster, ; Pottkamp 2, 48149 Münster, Germany
                [4 ]Pediatric and Adolescent Medicine, Swabian Childrens’ Cancer Center, University Childrens’ Hospital Medical Center Augsburg and EU-RHAB Registry, Augsburg, Germany
                [5 ]GRID grid.239546.f, ISNI 0000 0001 2153 6013, Department of Pathology and Laboratory Medicine, , Children’s Hospital Los Angeles, ; Los Angeles, CA USA
                [6 ]GRID grid.410712.1, ISNI 0000 0004 0473 882X, Institute of Human Genetics, , Ulm University and Ulm University Medical Center, ; Ulm, Germany
                [7 ]GRID grid.13648.38, ISNI 0000 0001 2180 3484, Department of Pediatric Hematology and Oncology, , University Medical Center, ; Hamburg-Eppendorf, Hamburg, Germany
                [8 ]GRID grid.14709.3b, ISNI 0000 0004 1936 8649, Department of Pathology, , McGill University, ; Montreal, QC Canada
                [9 ]GRID grid.8664.c, ISNI 0000 0001 2165 8627, Department of Neuropathology, , University Giessen, ; Giessen, Germany
                [10 ]GRID grid.11804.3c, ISNI 0000 0001 0942 9821, Department of Pediatric Oncology, 2nd Department of Pediatrics, , Semmelweis University, ; Budapest, Hungary
                [11 ]GRID grid.5718.b, ISNI 0000 0001 2187 5445, Institute of Neuropathology, , University of Duisburg-Essen, ; Essen, Germany
                [12 ]GRID grid.17089.37, ISNI 0000 0001 2190 316X, Division of Anatomical Pathology, Neuropathology Specialty Group, Department of Laboratory Medicine and Pathology, , University of Alberta, ; Edmonton, Canada
                [13 ]GRID grid.475435.4, Department of Pathology, , Rigshospitalet, ; Copenhagen, Denmark
                [14 ]GRID grid.5807.a, ISNI 0000 0001 1018 4307, Department of Neuropathology, , University Magdeburg, ; Magdeburg, Germany
                [15 ]GRID grid.8379.5, ISNI 0000 0001 1958 8658, Department of Neuropathology, Institute for Pathology, , University of Würzburg, ; 97080 Würzburg, Germany
                [16 ]GRID grid.154185.c, ISNI 0000 0004 0512 597X, Department of Pathology, , Aarhus University Hospital, ; Aarhus, Denmark
                [17 ]GRID grid.15090.3d, ISNI 0000 0000 8786 803X, Department of Neuropathology, , University of Bonn Medical Centre, ; Bonn, Germany
                [18 ]Asklepios Kinderklinik Sankt Augustin, Sankt Augustin, Germany
                [19 ]GRID grid.411941.8, ISNI 0000 0000 9194 7179, Department of Neuropathology, , Regensburg University Hospital, ; Regensburg, Germany
                [20 ]GRID grid.5254.6, ISNI 0000 0001 0674 042X, Department of Paediatrics and Adolescent Medicine, , University of Copenhagen, ; Copenhagen, Denmark
                [21 ]GRID grid.412826.b, ISNI 0000 0004 0611 0905, Department of Pediatric Hematology and Oncology, , University Hospital Motol, ; Prague, Czech Republic
                [22 ]GRID grid.487647.e, Princess Máxima Center for Pediatric Oncology, ; Utrecht, The Netherlands
                Author information
                http://orcid.org/0000-0003-2707-8484
                Article
                2424
                10.1007/s00401-022-02424-5
                9107423
                35501487
                cfd780c9-1324-44e1-aa94-5382531450ff
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 30 March 2022
                : 21 April 2022
                : 21 April 2022
                Funding
                Funded by: IZKF Münster
                Award ID: Ha3/017/20
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100005972, Deutsche Krebshilfe;
                Award ID: DKH 70113981
                Award ID: 70114040
                Award Recipient :
                Funded by: Westfälische Wilhelms-Universität Münster (1056)
                Categories
                Original Paper
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2022

                Neurology
                atypical teratoid/rhabdoid tumor,sonic hedgehog,dna methylation profiling,gene expression,olig2,gfap,ascl1,neuroradiology,prognosis,overall survival

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