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Immune landscapes associated with different glioblastoma molecular subtypes
by
Greene, Casey S.
, Kandpal, Manoj
, Yan, Rachel E.
, Cocito, Carolina
, Way, Gregory P.
, Lynch, Timothy M.
, Bi, Yingtao
, Dahmane, Nadia
, Martinez-Lage, Maria
, Haller, Josephine
, Ziober, Amy
, Davuluri, Ramana V.
, Pal, Sharmistha
, Greenfield, Jeffrey P.
, Nguyen, Aivi
, O’Rourke, Donald M.
in
Antibodies
/ Automation
/ B cells
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain cancer
/ Brain tumors
/ Cancer
/ Cancer therapies
/ Cytokines
/ Datasets
/ Development and progression
/ Gene expression
/ Glioblastomas
/ Gliomas
/ Histology
/ Immune system
/ Immunohistochemistry
/ Immunotherapy
/ Kinases
/ Lymphocytes
/ Macrophages
/ Mutation
/ Neurology
/ Neurosciences
/ Pathology
/ RNA
/ Software
/ Statistical analysis
/ Stem cells
/ Survival analysis
/ T cells
/ Tumors
/ Variance analysis
2019
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Immune landscapes associated with different glioblastoma molecular subtypes
by
Greene, Casey S.
, Kandpal, Manoj
, Yan, Rachel E.
, Cocito, Carolina
, Way, Gregory P.
, Lynch, Timothy M.
, Bi, Yingtao
, Dahmane, Nadia
, Martinez-Lage, Maria
, Haller, Josephine
, Ziober, Amy
, Davuluri, Ramana V.
, Pal, Sharmistha
, Greenfield, Jeffrey P.
, Nguyen, Aivi
, O’Rourke, Donald M.
in
Antibodies
/ Automation
/ B cells
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain cancer
/ Brain tumors
/ Cancer
/ Cancer therapies
/ Cytokines
/ Datasets
/ Development and progression
/ Gene expression
/ Glioblastomas
/ Gliomas
/ Histology
/ Immune system
/ Immunohistochemistry
/ Immunotherapy
/ Kinases
/ Lymphocytes
/ Macrophages
/ Mutation
/ Neurology
/ Neurosciences
/ Pathology
/ RNA
/ Software
/ Statistical analysis
/ Stem cells
/ Survival analysis
/ T cells
/ Tumors
/ Variance analysis
2019
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Do you wish to request the book?
Immune landscapes associated with different glioblastoma molecular subtypes
by
Greene, Casey S.
, Kandpal, Manoj
, Yan, Rachel E.
, Cocito, Carolina
, Way, Gregory P.
, Lynch, Timothy M.
, Bi, Yingtao
, Dahmane, Nadia
, Martinez-Lage, Maria
, Haller, Josephine
, Ziober, Amy
, Davuluri, Ramana V.
, Pal, Sharmistha
, Greenfield, Jeffrey P.
, Nguyen, Aivi
, O’Rourke, Donald M.
in
Antibodies
/ Automation
/ B cells
/ Biomedical and Life Sciences
/ Biomedicine
/ Brain cancer
/ Brain tumors
/ Cancer
/ Cancer therapies
/ Cytokines
/ Datasets
/ Development and progression
/ Gene expression
/ Glioblastomas
/ Gliomas
/ Histology
/ Immune system
/ Immunohistochemistry
/ Immunotherapy
/ Kinases
/ Lymphocytes
/ Macrophages
/ Mutation
/ Neurology
/ Neurosciences
/ Pathology
/ RNA
/ Software
/ Statistical analysis
/ Stem cells
/ Survival analysis
/ T cells
/ Tumors
/ Variance analysis
2019
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Immune landscapes associated with different glioblastoma molecular subtypes
Journal Article
Immune landscapes associated with different glioblastoma molecular subtypes
2019
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Overview
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.
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