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Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis

Rigorous molecular analysis of the immune cell environment and immune response of human tumors has led to immune checkpoint inhibitors as one of the most promising strategies for the treatment of human cancer. However, in human glioblastoma multiforme (GBM) which develops in part by attracting immun...

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Autores principales: Kong, Yang, Xue, Zhiwei, Wang, Haiying, Cui, Guangqiang, Chen, Anjing, Liu, Jie, Wang, Jian, Li, Xingang, Huang, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294273/
https://www.ncbi.nlm.nih.gov/pubmed/35865015
http://dx.doi.org/10.3389/fgene.2022.890174
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author Kong, Yang
Xue, Zhiwei
Wang, Haiying
Cui, Guangqiang
Chen, Anjing
Liu, Jie
Wang, Jian
Li, Xingang
Huang, Bin
author_facet Kong, Yang
Xue, Zhiwei
Wang, Haiying
Cui, Guangqiang
Chen, Anjing
Liu, Jie
Wang, Jian
Li, Xingang
Huang, Bin
author_sort Kong, Yang
collection PubMed
description Rigorous molecular analysis of the immune cell environment and immune response of human tumors has led to immune checkpoint inhibitors as one of the most promising strategies for the treatment of human cancer. However, in human glioblastoma multiforme (GBM) which develops in part by attracting immune cell types intrinsic to the human brain (microglia), standard immunotherapy has yielded inconsistent results in experimental models and patients. Here, we analyzed publicly available expression datasets to identify molecules possibly associated with immune response originating from or influencing the tumor microenvironment in primary tumor samples. Using three glioma datasets (GSE16011, Rembrandt-glioma and TCGA-glioma), we first analyzed the data to distinguish between GBMs of high and low tumor cell purity, a reflection of the cellular composition of the tumor microenvironment, and second, to identify differentially expressed genes (DEGs) between these two groups using GSEA and other analyses. Tumor purity was negatively correlated with patient prognosis. The interferon gamma-related gene BST2 emerged as a DEG that was highly expressed in GBM and negatively correlated with tumor purity. BST2 ( high ) tumors also tended to harbor PTEN mutations (31 vs. 9%, BST2 ( high ) versus BST2 ( low )) while BST2 ( low ) tumors more often had sustained TP53 mutations (8 versus 36%, BST2 ( high ) versus BST2 ( low )). Prognosis of patients with BST2 ( high ) tumors was also poor relative to patients with BST2 ( low ) tumors. Further molecular in silico analysis demonstrated that high expression of BST2 was negatively correlated with CD8(+) T cells but positively correlated with macrophages with an M2 phenotype. Further functional analysis demonstrated that BST2 was associated with multiple immune checkpoints and cytokines, and may promote tumorigenesis and progression through interferon gamma, IL6/JAK/STAT3 signaling, IL2/STAT5 signaling and the TNF-α signaling via NF-kB pathway. Finally, a series of experiments confirmed that the expression of BST2 can be significantly increased by IFN induction, and knockdown of BST2 can significantly inhibit the growth and invasion of GBM cells, and may affect the phenotype of tumor-associated macrophages. In conclusion, BST2 may promote the progression of GBM and may be a target for treatment.
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spelling pubmed-92942732022-07-20 Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis Kong, Yang Xue, Zhiwei Wang, Haiying Cui, Guangqiang Chen, Anjing Liu, Jie Wang, Jian Li, Xingang Huang, Bin Front Genet Genetics Rigorous molecular analysis of the immune cell environment and immune response of human tumors has led to immune checkpoint inhibitors as one of the most promising strategies for the treatment of human cancer. However, in human glioblastoma multiforme (GBM) which develops in part by attracting immune cell types intrinsic to the human brain (microglia), standard immunotherapy has yielded inconsistent results in experimental models and patients. Here, we analyzed publicly available expression datasets to identify molecules possibly associated with immune response originating from or influencing the tumor microenvironment in primary tumor samples. Using three glioma datasets (GSE16011, Rembrandt-glioma and TCGA-glioma), we first analyzed the data to distinguish between GBMs of high and low tumor cell purity, a reflection of the cellular composition of the tumor microenvironment, and second, to identify differentially expressed genes (DEGs) between these two groups using GSEA and other analyses. Tumor purity was negatively correlated with patient prognosis. The interferon gamma-related gene BST2 emerged as a DEG that was highly expressed in GBM and negatively correlated with tumor purity. BST2 ( high ) tumors also tended to harbor PTEN mutations (31 vs. 9%, BST2 ( high ) versus BST2 ( low )) while BST2 ( low ) tumors more often had sustained TP53 mutations (8 versus 36%, BST2 ( high ) versus BST2 ( low )). Prognosis of patients with BST2 ( high ) tumors was also poor relative to patients with BST2 ( low ) tumors. Further molecular in silico analysis demonstrated that high expression of BST2 was negatively correlated with CD8(+) T cells but positively correlated with macrophages with an M2 phenotype. Further functional analysis demonstrated that BST2 was associated with multiple immune checkpoints and cytokines, and may promote tumorigenesis and progression through interferon gamma, IL6/JAK/STAT3 signaling, IL2/STAT5 signaling and the TNF-α signaling via NF-kB pathway. Finally, a series of experiments confirmed that the expression of BST2 can be significantly increased by IFN induction, and knockdown of BST2 can significantly inhibit the growth and invasion of GBM cells, and may affect the phenotype of tumor-associated macrophages. In conclusion, BST2 may promote the progression of GBM and may be a target for treatment. Frontiers Media S.A. 2022-07-05 /pmc/articles/PMC9294273/ /pubmed/35865015 http://dx.doi.org/10.3389/fgene.2022.890174 Text en Copyright © 2022 Kong, Xue, Wang, Cui, Chen, Liu, Wang, Li and Huang. https://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 Genetics
Kong, Yang
Xue, Zhiwei
Wang, Haiying
Cui, Guangqiang
Chen, Anjing
Liu, Jie
Wang, Jian
Li, Xingang
Huang, Bin
Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis
title Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis
title_full Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis
title_fullStr Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis
title_full_unstemmed Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis
title_short Identification of BST2 Contributing to the Development of Glioblastoma Based on Bioinformatics Analysis
title_sort identification of bst2 contributing to the development of glioblastoma based on bioinformatics analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9294273/
https://www.ncbi.nlm.nih.gov/pubmed/35865015
http://dx.doi.org/10.3389/fgene.2022.890174
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