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Identification of Immune-Related Genes Contributing to the Development of Glioblastoma Using Weighted Gene Co-expression Network Analysis
Background: The tumor microenvironment (TME) of human glioblastoma (GBM) exhibits considerable immune cell infiltration, and such cell types have been shown to be widely involved in the development of GBM. Here, weighted correlation network analysis (WGCNA) was performed on publicly available datase...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378359/ https://www.ncbi.nlm.nih.gov/pubmed/32765489 http://dx.doi.org/10.3389/fimmu.2020.01281 |
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author | Kong, Yang Feng, Zi-Chao Zhang, Yu-Lin Liu, Xiao-Fei Ma, Yuan Zhao, Zhi-Min Huang, Bin Chen, An-Jing Zhang, Di Thorsen, Frits Wang, Jian Yang, Ning Li, Xin-Gang |
author_facet | Kong, Yang Feng, Zi-Chao Zhang, Yu-Lin Liu, Xiao-Fei Ma, Yuan Zhao, Zhi-Min Huang, Bin Chen, An-Jing Zhang, Di Thorsen, Frits Wang, Jian Yang, Ning Li, Xin-Gang |
author_sort | Kong, Yang |
collection | PubMed |
description | Background: The tumor microenvironment (TME) of human glioblastoma (GBM) exhibits considerable immune cell infiltration, and such cell types have been shown to be widely involved in the development of GBM. Here, weighted correlation network analysis (WGCNA) was performed on publicly available datasets to identify immune-related molecules that may contribute to the progression of GBM and thus be exploited as potential therapeutic targets. Methods: WGCNA was used to identify highly correlated gene clusters in Chinese Glioma Genome Atlas glioma dataset. Immune-related genes in significant modules were subsequently validated in the Cancer Genome Atlas (TCGA) and Rembrandt databases, and impact on GBM development was examined in migration and vascular mimicry assays in vitro and in an orthotopic xenograft model (GL261 luciferase-GFP cells) in mice. Results: WGCNA yielded 14 significant modules, one of which (black) contained genes involved in immune response and extracellular matrix formation. The intersection of these genes with a GO immune-related gene set yielded 47 immune-related genes, five of which exhibited increased expression and association with worse prognosis in GBM. One of these genes, TREM1, was highly expressed in areas of pseudopalisading cells around necrosis and associated with other proteins induced in angiogenesis/hypoxia. In macrophages induced from THP1 cells, TREM1 expression levels were increased under hypoxic conditions and associated with markers of macrophage M2 polarization. TREM1 siRNA knockdown in induced macrophages reduced their ability to promote migration and vascular mimicry in GBM cells in vitro, and treatment of mice with LP-17 peptide, which blocks TREM1, inhibited growth of GL261 orthotopic xenografts. Finally, blocking the cytokine receptor for CSF1 in induced macrophages also impeded their potential to promote tumor migration and vascular mimicry in GBM cells. Conclusions: Our results demonstrated that TREM1 could be used as a novel immunotherapy target for glioma patients. |
format | Online Article Text |
id | pubmed-7378359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73783592020-08-05 Identification of Immune-Related Genes Contributing to the Development of Glioblastoma Using Weighted Gene Co-expression Network Analysis Kong, Yang Feng, Zi-Chao Zhang, Yu-Lin Liu, Xiao-Fei Ma, Yuan Zhao, Zhi-Min Huang, Bin Chen, An-Jing Zhang, Di Thorsen, Frits Wang, Jian Yang, Ning Li, Xin-Gang Front Immunol Immunology Background: The tumor microenvironment (TME) of human glioblastoma (GBM) exhibits considerable immune cell infiltration, and such cell types have been shown to be widely involved in the development of GBM. Here, weighted correlation network analysis (WGCNA) was performed on publicly available datasets to identify immune-related molecules that may contribute to the progression of GBM and thus be exploited as potential therapeutic targets. Methods: WGCNA was used to identify highly correlated gene clusters in Chinese Glioma Genome Atlas glioma dataset. Immune-related genes in significant modules were subsequently validated in the Cancer Genome Atlas (TCGA) and Rembrandt databases, and impact on GBM development was examined in migration and vascular mimicry assays in vitro and in an orthotopic xenograft model (GL261 luciferase-GFP cells) in mice. Results: WGCNA yielded 14 significant modules, one of which (black) contained genes involved in immune response and extracellular matrix formation. The intersection of these genes with a GO immune-related gene set yielded 47 immune-related genes, five of which exhibited increased expression and association with worse prognosis in GBM. One of these genes, TREM1, was highly expressed in areas of pseudopalisading cells around necrosis and associated with other proteins induced in angiogenesis/hypoxia. In macrophages induced from THP1 cells, TREM1 expression levels were increased under hypoxic conditions and associated with markers of macrophage M2 polarization. TREM1 siRNA knockdown in induced macrophages reduced their ability to promote migration and vascular mimicry in GBM cells in vitro, and treatment of mice with LP-17 peptide, which blocks TREM1, inhibited growth of GL261 orthotopic xenografts. Finally, blocking the cytokine receptor for CSF1 in induced macrophages also impeded their potential to promote tumor migration and vascular mimicry in GBM cells. Conclusions: Our results demonstrated that TREM1 could be used as a novel immunotherapy target for glioma patients. Frontiers Media S.A. 2020-07-16 /pmc/articles/PMC7378359/ /pubmed/32765489 http://dx.doi.org/10.3389/fimmu.2020.01281 Text en Copyright © 2020 Kong, Feng, Zhang, Liu, Ma, Zhao, Huang, Chen, Zhang, Thorsen, Wang, Yang and Li. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Kong, Yang Feng, Zi-Chao Zhang, Yu-Lin Liu, Xiao-Fei Ma, Yuan Zhao, Zhi-Min Huang, Bin Chen, An-Jing Zhang, Di Thorsen, Frits Wang, Jian Yang, Ning Li, Xin-Gang Identification of Immune-Related Genes Contributing to the Development of Glioblastoma Using Weighted Gene Co-expression Network Analysis |
title | Identification of Immune-Related Genes Contributing to the Development of Glioblastoma Using Weighted Gene Co-expression Network Analysis |
title_full | Identification of Immune-Related Genes Contributing to the Development of Glioblastoma Using Weighted Gene Co-expression Network Analysis |
title_fullStr | Identification of Immune-Related Genes Contributing to the Development of Glioblastoma Using Weighted Gene Co-expression Network Analysis |
title_full_unstemmed | Identification of Immune-Related Genes Contributing to the Development of Glioblastoma Using Weighted Gene Co-expression Network Analysis |
title_short | Identification of Immune-Related Genes Contributing to the Development of Glioblastoma Using Weighted Gene Co-expression Network Analysis |
title_sort | identification of immune-related genes contributing to the development of glioblastoma using weighted gene co-expression network analysis |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378359/ https://www.ncbi.nlm.nih.gov/pubmed/32765489 http://dx.doi.org/10.3389/fimmu.2020.01281 |
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