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      Cancer cell heterogeneity and plasticity: A paradigm shift in glioblastoma

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          Abstract

          Phenotypic plasticity has emerged as a major contributor to intra-tumoral heterogeneity and treatment resistance in cancer. Increasing evidence shows that glioblastoma (GBM) cells display prominent intrinsic plasticity and reversibly adapt to dynamic microenvironmental conditions. Limited genetic evolution at recurrence further suggests that resistance mechanisms also largely operate at the phenotypic level. Here we review recent literature underpinning the role of GBM plasticity in creating gradients of heterogeneous cells including those that carry cancer stem cell (CSC) properties. A historical perspective from the hierarchical to the nonhierarchical concept of CSCs towards the recent appreciation of GBM plasticity is provided. Cellular states interact dynamically with each other and with the surrounding brain to shape a flexible tumor ecosystem, which enables swift adaptation to external pressure including treatment. We present the key components regulating intra-tumoral phenotypic heterogeneity and the equilibrium of phenotypic states, including genetic, epigenetic, and microenvironmental factors. We further discuss plasticity in the context of intrinsic tumor resistance, where a variable balance between preexisting resistant cells and adaptive persisters leads to reversible adaptation upon treatment. Innovative efforts targeting regulators of plasticity and mechanisms of state transitions towards treatment-resistant states are needed to restrict the adaptive capacities of GBM.

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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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            SCENIC: Single-cell regulatory network inference and clustering

            Although single-cell RNA-seq is revolutionizing biology, data interpretation remains a challenge. We present SCENIC for the simultaneous reconstruction of gene regulatory networks and identification of cell states. We apply SCENIC to a compendium of single-cell data from tumors and brain, and demonstrate that the genomic regulatory code can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity.
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              Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

              The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefit in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies. Copyright (c) 2010 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Neuro Oncol
                Neuro Oncol
                neuonc
                Neuro-Oncology
                Oxford University Press (US )
                1522-8517
                1523-5866
                May 2022
                21 December 2021
                21 December 2021
                : 24
                : 5
                : 669-682
                Affiliations
                NORLUX Neuro-Oncology Laboratory, Department of Oncology, Luxembourg Institute of Health , Luxembourg, Luxembourg
                Faculty of Science, Technology and Medicine, University of Luxembourg , Esch-sur-Alzette, Luxembourg
                NORLUX Neuro-Oncology Laboratory, Department of Oncology, Luxembourg Institute of Health , Luxembourg, Luxembourg
                Department of Biomedicine, University of Bergen , Bergen, Norway
                Faculty of Science, Technology and Medicine, University of Luxembourg , Esch-sur-Alzette, Luxembourg
                Author notes
                Corresponding Author: Anna Golebiewska, PhD, Department of Oncology, Luxembourg Institute of Health, 84, Val Fleuri, L-1526 Luxembourg, Luxembourg ( anna.golebiewska@ 123456lih.lu ).
                Author information
                https://orcid.org/0000-0002-1128-6038
                https://orcid.org/0000-0002-3417-9534
                https://orcid.org/0000-0002-4160-2521
                Article
                noab269
                10.1093/neuonc/noab269
                9071273
                34932099
                2acb0a15-f5dd-4478-ac53-24e05e2cedf5
                © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 21 December 2021
                Page count
                Pages: 14
                Funding
                Funded by: Marie Skłodowska-Curie grant;
                Award ID: 766069
                Categories
                Reviews
                AcademicSubjects/MED00300
                AcademicSubjects/MED00310
                Editor's Choice

                Oncology & Radiotherapy
                glioblastoma,plasticity,treatment resistance,tumor heterogeneity,tumor microenvironment

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