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Immune landscapes associated with different glioblastoma molecular subtypes
Recent work has highlighted the tumor microenvironment as a central player in cancer. In particular, interactions between tumor and immune cells may help drive the development of brain tumors such as glioblastoma multiforme (GBM). Despite significant research into the molecular classification of gli...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6902522/ https://www.ncbi.nlm.nih.gov/pubmed/31815646 http://dx.doi.org/10.1186/s40478-019-0803-6 |
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author | Martinez-Lage, Maria Lynch, Timothy M. Bi, Yingtao Cocito, Carolina Way, Gregory P. Pal, Sharmistha Haller, Josephine Yan, Rachel E. Ziober, Amy Nguyen, Aivi Kandpal, Manoj O’Rourke, Donald M. Greenfield, Jeffrey P. Greene, Casey S. Davuluri, Ramana V. Dahmane, Nadia |
author_facet | Martinez-Lage, Maria Lynch, Timothy M. Bi, Yingtao Cocito, Carolina Way, Gregory P. Pal, Sharmistha Haller, Josephine Yan, Rachel E. Ziober, Amy Nguyen, Aivi Kandpal, Manoj O’Rourke, Donald M. Greenfield, Jeffrey P. Greene, Casey S. Davuluri, Ramana V. Dahmane, Nadia |
author_sort | Martinez-Lage, Maria |
collection | PubMed |
description | Recent work has highlighted the tumor microenvironment as a central player in cancer. In particular, interactions between tumor and immune cells may help drive the development of brain tumors such as glioblastoma multiforme (GBM). Despite significant research into the molecular classification of glioblastoma, few studies have characterized in a comprehensive manner the immune infiltrate in situ and within different GBM subtypes. In this study, we use an unbiased, automated immunohistochemistry-based approach to determine the immune phenotype of the four GBM subtypes (classical, mesenchymal, neural and proneural) in a cohort of 98 patients. Tissue Micro Arrays (TMA) were stained for CD20 (B lymphocytes), CD5, CD3, CD4, CD8 (T lymphocytes), CD68 (microglia), and CD163 (bone marrow derived macrophages) antibodies. Using automated image analysis, the percentage of each immune population was calculated with respect to the total tumor cells. Mesenchymal GBMs displayed the highest percentage of microglia, macrophage, and lymphocyte infiltration. CD68(+) and CD163(+) cells were the most abundant cell populations in all four GBM subtypes, and a higher percentage of CD163(+) cells was associated with a worse prognosis. We also compared our results to the relative composition of immune cell type infiltration (using RNA-seq data) across TCGA GBM tumors and validated our results obtained with immunohistochemistry with an external cohort and a different method. The results of this study offer a comprehensive analysis of the distribution and the infiltration of the immune components across the four commonly described GBM subgroups, setting the basis for a more detailed patient classification and new insights that may be used to better apply or design immunotherapies for GBM. |
format | Online Article Text |
id | pubmed-6902522 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-69025222019-12-11 Immune landscapes associated with different glioblastoma molecular subtypes Martinez-Lage, Maria Lynch, Timothy M. Bi, Yingtao Cocito, Carolina Way, Gregory P. Pal, Sharmistha Haller, Josephine Yan, Rachel E. Ziober, Amy Nguyen, Aivi Kandpal, Manoj O’Rourke, Donald M. Greenfield, Jeffrey P. Greene, Casey S. Davuluri, Ramana V. Dahmane, Nadia Acta Neuropathol Commun Research Recent work has highlighted the tumor microenvironment as a central player in cancer. In particular, interactions between tumor and immune cells may help drive the development of brain tumors such as glioblastoma multiforme (GBM). Despite significant research into the molecular classification of glioblastoma, few studies have characterized in a comprehensive manner the immune infiltrate in situ and within different GBM subtypes. In this study, we use an unbiased, automated immunohistochemistry-based approach to determine the immune phenotype of the four GBM subtypes (classical, mesenchymal, neural and proneural) in a cohort of 98 patients. Tissue Micro Arrays (TMA) were stained for CD20 (B lymphocytes), CD5, CD3, CD4, CD8 (T lymphocytes), CD68 (microglia), and CD163 (bone marrow derived macrophages) antibodies. Using automated image analysis, the percentage of each immune population was calculated with respect to the total tumor cells. Mesenchymal GBMs displayed the highest percentage of microglia, macrophage, and lymphocyte infiltration. CD68(+) and CD163(+) cells were the most abundant cell populations in all four GBM subtypes, and a higher percentage of CD163(+) cells was associated with a worse prognosis. We also compared our results to the relative composition of immune cell type infiltration (using RNA-seq data) across TCGA GBM tumors and validated our results obtained with immunohistochemistry with an external cohort and a different method. The results of this study offer a comprehensive analysis of the distribution and the infiltration of the immune components across the four commonly described GBM subgroups, setting the basis for a more detailed patient classification and new insights that may be used to better apply or design immunotherapies for GBM. BioMed Central 2019-11-29 /pmc/articles/PMC6902522/ /pubmed/31815646 http://dx.doi.org/10.1186/s40478-019-0803-6 Text en © The Author(s). 2019 Open AccessThis 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 Martinez-Lage, Maria Lynch, Timothy M. Bi, Yingtao Cocito, Carolina Way, Gregory P. Pal, Sharmistha Haller, Josephine Yan, Rachel E. Ziober, Amy Nguyen, Aivi Kandpal, Manoj O’Rourke, Donald M. Greenfield, Jeffrey P. Greene, Casey S. Davuluri, Ramana V. Dahmane, Nadia Immune landscapes associated with different glioblastoma molecular subtypes |
title | Immune landscapes associated with different glioblastoma molecular subtypes |
title_full | Immune landscapes associated with different glioblastoma molecular subtypes |
title_fullStr | Immune landscapes associated with different glioblastoma molecular subtypes |
title_full_unstemmed | Immune landscapes associated with different glioblastoma molecular subtypes |
title_short | Immune landscapes associated with different glioblastoma molecular subtypes |
title_sort | immune landscapes associated with different glioblastoma molecular subtypes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6902522/ https://www.ncbi.nlm.nih.gov/pubmed/31815646 http://dx.doi.org/10.1186/s40478-019-0803-6 |
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