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      Network-based analysis of oligodendrogliomas predicts novel cancer gene candidates within the region of the 1p/19q co-deletion

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          Abstract

          Oligodendrogliomas are primary human brain tumors with a characteristic 1p/19q co-deletion of important prognostic relevance, but little is known about the pathology of this chromosomal mutation. We developed a network-based approach to identify novel cancer gene candidates in the region of the 1p/19q co-deletion. Gene regulatory networks were learned from gene expression and copy number data of 178 oligodendrogliomas and further used to quantify putative impacts of differentially expressed genes of the 1p/19q region on cancer-relevant pathways. We predicted 8 genes with strong impact on signaling pathways and 14 genes with strong impact on metabolic pathways widespread across the region of the 1p/19 co-deletion. Many of these candidates (e.g. ELTD1, SDHB, SEPW1, SLC17A7, SZRD1, THAP3, ZBTB17) are likely to push, whereas others (e.g. CAP1, HBXIP, KLK6, PARK7, PTAFR) might counteract oligodendroglioma development. For example, ELTD1, a functionally validated glioblastoma oncogene located on 1p, was overexpressed. Further, the known glioblastoma tumor suppressor SLC17A7 located on 19q was underexpressed. Moreover, known epigenetic alterations triggered by mutated SDHB in paragangliomas suggest that underexpressed SDHB in oligodendrogliomas may support and possibly enhance the epigenetic reprogramming induced by the IDH-mutation. We further analyzed rarely observed deletions and duplications of chromosomal arms within oligodendroglioma subcohorts identifying putative oncogenes and tumor suppressors that possibly influence the development of oligodendroglioma subgroups. Our in-depth computational study contributes to a better understanding of the pathology of the 1p/19q co-deletion and other chromosomal arm mutations. This might open opportunities for functional validations and new therapeutic strategies.

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          The online version of this article (10.1186/s40478-018-0544-y) contains supplementary material, which is available to authorized users.

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          Most cited references53

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          Pan-Cancer Network Analysis Identifies Combinations of Rare Somatic Mutations across Pathways and Protein Complexes

          Cancers exhibit extensive mutational heterogeneity and the resulting long tail phenomenon complicates the discovery of the genes and pathways that are significantly mutated in cancer. We perform a Pan-Cancer analysis of mutated networks in 3281 samples from 12 cancer types from The Cancer Genome Atlas (TCGA) using HotNet2, a novel algorithm to find mutated subnetworks that overcomes limitations of existing single gene and pathway/network approaches.. We identify 14 significantly mutated subnetworks that include well-known cancer signaling pathways as well as subnetworks with less characterized roles in cancer including cohesin, condensin, and others. Many of these subnetworks exhibit co-occurring mutations across samples. These subnetworks contain dozens of genes with rare somatic mutations across multiple cancers; many of these genes have additional evidence supporting a role in cancer. By illuminating these rare combinations of mutations, Pan-Cancer network analyses provide a roadmap to investigate new diagnostic and therapeutic opportunities across cancer types.
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            IDH1 and IDH2 mutations in gliomas.

            Mutations in isocitrate dehydrogenase (IDH) 1 and 2, originally discovered in 2008, occur in the vast majority of low-grade gliomas and secondary high-grade gliomas. These mutations, which occur early in gliomagenesis, change the function of the enzymes, causing them to produce 2-hydroxyglutarate, a possible oncometabolite, and to not produce NADPH. IDH mutations are oncogenic, although whether the mechanism is through alterations in hydroxylases, redox potential, cellular metabolism, or gene expression is not clear. The mutations also drive increased methylation in gliomas. Gliomas with mutated IDH1 and IDH2 have improved prognosis compared with gliomas with wild-type IDH. Mutated IDH can now be detected by immunohistochemistry and magnetic resonance spectroscopy. No drugs currently target mutated IDH, although this remains an area of active research.
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              Two genetic hits (more or less) to cancer.

              A Knudson (2001)
              Most cancers have many chromosomal abnormalities, both in number and in structure, whereas some show only a single aberration. In the era before molecular biology, cancer researchers, studying both human and animal cancers, proposed that a small number of events was needed for carcinogenesis. Evidence from the recent molecular era also indicates that cancers can arise from small numbers of events that affect common cell birth and death processes.
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                Author and article information

                Contributors
                josef.gladitz@mailbox.tu-dresden.de
                barbara.klink@uniklinikum-dresden.de
                michael.seifert@tu-dresden.de
                Journal
                Acta Neuropathol Commun
                Acta Neuropathol Commun
                Acta Neuropathologica Communications
                BioMed Central (London )
                2051-5960
                11 June 2018
                11 June 2018
                2018
                : 6
                : 49
                Affiliations
                [1 ]ISNI 0000 0001 2111 7257, GRID grid.4488.0, Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, ; Dresden, Germany
                [2 ]ISNI 0000 0001 2111 7257, GRID grid.4488.0, Institute for Clinical Genetics, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, ; Dresden, Germany
                [3 ]ISNI 0000 0001 0328 4908, GRID grid.5253.1, National Center for Tumor Diseases, ; Dresden, Germany
                Article
                544
                10.1186/s40478-018-0544-y
                5996550
                29890994
                58cc5696-c9bf-4b94-9232-d91b6e0e0cb8
                © The Author(s) 2018

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 19 April 2018
                : 8 May 2018
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                oligodendrogliomas,1p/19q co-deletion,network biology,network inference,network propagation,cancer genomics,bioinformatics,computational systems biology

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