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Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups

BACKGROUND: Molecular data of histologically classified oligodendrogliomas are available offering the possibility to stratify these human brain tumors into clinically relevant molecular subtypes. METHODS: Gene copy number, mutation, and expression data of 193 histologically classified oligodendrogli...

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Autores principales: Lauber, Chris, Klink, Barbara, Seifert, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5892046/
https://www.ncbi.nlm.nih.gov/pubmed/29631562
http://dx.doi.org/10.1186/s12885-018-4251-7
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author Lauber, Chris
Klink, Barbara
Seifert, Michael
author_facet Lauber, Chris
Klink, Barbara
Seifert, Michael
author_sort Lauber, Chris
collection PubMed
description BACKGROUND: Molecular data of histologically classified oligodendrogliomas are available offering the possibility to stratify these human brain tumors into clinically relevant molecular subtypes. METHODS: Gene copy number, mutation, and expression data of 193 histologically classified oligodendrogliomas from The Cancer Genome Atlas (TCGA) were analyzed by well-established computational approaches (unsupervised clustering, statistical testing, network inference). RESULTS: We applied hierarchical clustering to tumor gene copy number profiles and revealed three molecular subgroups within histologically classified oligodendrogliomas. We further screened these subgroups for molecular glioma markers (1p/19q co-deletion, IDH mutation, gain of chromosome 7 and loss of chromosome 10) and found that our subgroups largely resemble known molecular glioma subtypes. We excluded glioblastoma-like tumors (7a10d subgroup) and derived a gene expression signature distinguishing histologically classified oligodendrogliomas with concurrent 1p/19q co-deletion and IDH mutation (1p/19q subgroup) from those with predominant IDH mutation alone (IDHme subgroup). Interestingly, many signature genes were part of signaling pathways involved in the regulation of cell proliferation, differentiation, migration, and cell-cell contacts. We further learned a gene regulatory network associated with the gene expression signature revealing novel putative major regulators with functions in cytoskeleton remodeling (e.g. APBB1IP, VAV1, ARPC1B), apoptosis (CCNL2, CREB3L1), and neural development (e.g. MYTIL, SCRT1, MEF2C) potentially contributing to the manifestation of differences between both subgroups. Moreover, we revealed characteristic expression differences of several HOX and SOX transcription factors suggesting the activity of different glioma stemness programs in both subgroups. CONCLUSIONS: We show that gene copy number profiles alone are sufficient to derive molecular subgroups of histologically classified oligodendrogliomas that are well-embedded into general glioma classification schemes. Moreover, our revealed novel putative major regulators and characteristic stemness signatures indicate that different developmental programs might be active in these subgroups, providing a basis for future studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4251-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-58920462018-04-11 Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups Lauber, Chris Klink, Barbara Seifert, Michael BMC Cancer Research Article BACKGROUND: Molecular data of histologically classified oligodendrogliomas are available offering the possibility to stratify these human brain tumors into clinically relevant molecular subtypes. METHODS: Gene copy number, mutation, and expression data of 193 histologically classified oligodendrogliomas from The Cancer Genome Atlas (TCGA) were analyzed by well-established computational approaches (unsupervised clustering, statistical testing, network inference). RESULTS: We applied hierarchical clustering to tumor gene copy number profiles and revealed three molecular subgroups within histologically classified oligodendrogliomas. We further screened these subgroups for molecular glioma markers (1p/19q co-deletion, IDH mutation, gain of chromosome 7 and loss of chromosome 10) and found that our subgroups largely resemble known molecular glioma subtypes. We excluded glioblastoma-like tumors (7a10d subgroup) and derived a gene expression signature distinguishing histologically classified oligodendrogliomas with concurrent 1p/19q co-deletion and IDH mutation (1p/19q subgroup) from those with predominant IDH mutation alone (IDHme subgroup). Interestingly, many signature genes were part of signaling pathways involved in the regulation of cell proliferation, differentiation, migration, and cell-cell contacts. We further learned a gene regulatory network associated with the gene expression signature revealing novel putative major regulators with functions in cytoskeleton remodeling (e.g. APBB1IP, VAV1, ARPC1B), apoptosis (CCNL2, CREB3L1), and neural development (e.g. MYTIL, SCRT1, MEF2C) potentially contributing to the manifestation of differences between both subgroups. Moreover, we revealed characteristic expression differences of several HOX and SOX transcription factors suggesting the activity of different glioma stemness programs in both subgroups. CONCLUSIONS: We show that gene copy number profiles alone are sufficient to derive molecular subgroups of histologically classified oligodendrogliomas that are well-embedded into general glioma classification schemes. Moreover, our revealed novel putative major regulators and characteristic stemness signatures indicate that different developmental programs might be active in these subgroups, providing a basis for future studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-018-4251-7) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-10 /pmc/articles/PMC5892046/ /pubmed/29631562 http://dx.doi.org/10.1186/s12885-018-4251-7 Text en © 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.
spellingShingle Research Article
Lauber, Chris
Klink, Barbara
Seifert, Michael
Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups
title Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups
title_full Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups
title_fullStr Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups
title_full_unstemmed Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups
title_short Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups
title_sort comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5892046/
https://www.ncbi.nlm.nih.gov/pubmed/29631562
http://dx.doi.org/10.1186/s12885-018-4251-7
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