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Cell lines and immune classification of glioblastoma define patient’s prognosis

BACKGROUND: Prognostic markers for glioblastoma are lacking. Both intrinsic tumour characteristics and microenvironment could influence cancer prognostic. The aim of our study was to generate a pure glioblastoma cell lines and immune classification in order to decipher the respective role of gliobla...

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Autores principales: Klopfenstein, Quentin, Truntzer, Caroline, Vincent, Julie, Ghiringhelli, Francois
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474266/
https://www.ncbi.nlm.nih.gov/pubmed/30899088
http://dx.doi.org/10.1038/s41416-019-0404-y
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author Klopfenstein, Quentin
Truntzer, Caroline
Vincent, Julie
Ghiringhelli, Francois
author_facet Klopfenstein, Quentin
Truntzer, Caroline
Vincent, Julie
Ghiringhelli, Francois
author_sort Klopfenstein, Quentin
collection PubMed
description BACKGROUND: Prognostic markers for glioblastoma are lacking. Both intrinsic tumour characteristics and microenvironment could influence cancer prognostic. The aim of our study was to generate a pure glioblastoma cell lines and immune classification in order to decipher the respective role of glioblastoma cell and microenvironment on prognosis. METHODS: We worked on two large cohorts of patients suffering from glioblastoma (TCGA, n = 481 and Rembrandt, n = 180) for which clinical data, transcriptomic profiles and outcome were recorded. Transcriptomic profiles of 129 pure glioblastoma cell lines were clustered to generate a glioblastoma cell lines classification. Presence of subtypes of glioblastoma cell lines and immune cells was determined using deconvolution. RESULTS: Glioblastoma cell lines classification defined three new molecular groups called oncogenic, metabolic and neuronal communication enriched. Neuronal communication-enriched tumours were associated with poor prognosis in both cohorts. Immune cell infiltrate was more frequent in mesenchymal classical classification subgroup and metabolic-enriched tumours. A combination of age, glioblastoma cell lines classification and immune classification could be used to determine patient’s outcome in both cohorts. CONCLUSIONS: Our study shows that glioblastoma-bearing patients can be classified based on their age, glioblastoma cell lines classification and immune classification. The combination of these information improves the capacity to address prognosis.
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spelling pubmed-64742662019-09-11 Cell lines and immune classification of glioblastoma define patient’s prognosis Klopfenstein, Quentin Truntzer, Caroline Vincent, Julie Ghiringhelli, Francois Br J Cancer Article BACKGROUND: Prognostic markers for glioblastoma are lacking. Both intrinsic tumour characteristics and microenvironment could influence cancer prognostic. The aim of our study was to generate a pure glioblastoma cell lines and immune classification in order to decipher the respective role of glioblastoma cell and microenvironment on prognosis. METHODS: We worked on two large cohorts of patients suffering from glioblastoma (TCGA, n = 481 and Rembrandt, n = 180) for which clinical data, transcriptomic profiles and outcome were recorded. Transcriptomic profiles of 129 pure glioblastoma cell lines were clustered to generate a glioblastoma cell lines classification. Presence of subtypes of glioblastoma cell lines and immune cells was determined using deconvolution. RESULTS: Glioblastoma cell lines classification defined three new molecular groups called oncogenic, metabolic and neuronal communication enriched. Neuronal communication-enriched tumours were associated with poor prognosis in both cohorts. Immune cell infiltrate was more frequent in mesenchymal classical classification subgroup and metabolic-enriched tumours. A combination of age, glioblastoma cell lines classification and immune classification could be used to determine patient’s outcome in both cohorts. CONCLUSIONS: Our study shows that glioblastoma-bearing patients can be classified based on their age, glioblastoma cell lines classification and immune classification. The combination of these information improves the capacity to address prognosis. Nature Publishing Group UK 2019-03-22 2019-04-16 /pmc/articles/PMC6474266/ /pubmed/30899088 http://dx.doi.org/10.1038/s41416-019-0404-y Text en © The Author(s) 2019 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Klopfenstein, Quentin
Truntzer, Caroline
Vincent, Julie
Ghiringhelli, Francois
Cell lines and immune classification of glioblastoma define patient’s prognosis
title Cell lines and immune classification of glioblastoma define patient’s prognosis
title_full Cell lines and immune classification of glioblastoma define patient’s prognosis
title_fullStr Cell lines and immune classification of glioblastoma define patient’s prognosis
title_full_unstemmed Cell lines and immune classification of glioblastoma define patient’s prognosis
title_short Cell lines and immune classification of glioblastoma define patient’s prognosis
title_sort cell lines and immune classification of glioblastoma define patient’s prognosis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474266/
https://www.ncbi.nlm.nih.gov/pubmed/30899088
http://dx.doi.org/10.1038/s41416-019-0404-y
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