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The Crosstalk between the EGFR and IFN-γ Pathways and Synergistic Roles in Survival Prediction and Immune Escape in Gliomas

Glioma is the most common primary malignant brain tumor. The poor prognosis of gliomas, especially glioblastoma (GBM), is associated with their unique molecular landscape and tumor microenvironment (TME) features. The epidermal growth factor receptor (EGFR) gene is one of the frequently altered loci...

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Autores principales: Zhou, Xingang, Liang, Tingyu, Ge, Yulu, Wang, Yu, Ma, Wenbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10526459/
https://www.ncbi.nlm.nih.gov/pubmed/37759950
http://dx.doi.org/10.3390/brainsci13091349
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author Zhou, Xingang
Liang, Tingyu
Ge, Yulu
Wang, Yu
Ma, Wenbin
author_facet Zhou, Xingang
Liang, Tingyu
Ge, Yulu
Wang, Yu
Ma, Wenbin
author_sort Zhou, Xingang
collection PubMed
description Glioma is the most common primary malignant brain tumor. The poor prognosis of gliomas, especially glioblastoma (GBM), is associated with their unique molecular landscape and tumor microenvironment (TME) features. The epidermal growth factor receptor (EGFR) gene is one of the frequently altered loci in gliomas, leading to the activation of the EGFR signaling pathway and thus, promoting the genesis of gliomas. Whether there exist factors within the TME that can lead to EGFR activation in the context of gliomas is currently unexplored. In total, 702 samples from The Cancer Genome Atlas (TCGA) and 325 samples from The Chinese Glioma Genome Atlas (CGGA) were enrolled in this study. Gene signatures related to EGFR signaling and interferon-γ (IFN-γ) response were established via the LASSO-COX algorithm. Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) analysis were applied for function exploration. Kaplan–Meier (KM) curves and single sample GSEA (ssGSEA) of immune cell subpopulations were performed to analyze the prognosis and TME characteristics of different subgroups. Moreover, Western blotting (WB) and flow cytometry (FCM) demonstrated the correlation between IFN-γ and EGFR signaling activation and the subsequent induction of programmed death ligand 1 (PD-L1) expression. An EGFR signaling-related risk score was established, and a higher score was correlated with poorer prognosis and a more malignant phenotype in gliomas. Biological function analysis revealed that a higher EGFR-related score was significantly associated with various cytokine response pathways, especially IFN-γ. Long-term (7 days) exposure to IFN-γ (400 ng/mL) induced the activation of EGFR signaling in the u87 cell line. Next, an IFN-γ response-related risk score was established; the combination of these two scores could be used to further reclassify gliomas into subtypes with different clinical features and TME features. Double high-risk samples tended to have a poorer prognosis and more immunosuppressive TME. Additionally, FCM discovered that the activation of EGFR signaling via EGF (100 ng/mL) could trigger PD-L1 protein expression. This research indicates that IFN-γ, an inflammatory cytokine, can activate the EGFR pathway. The combination of EGFR signaling and IFN-γ response pathway can establish a more precise classification of gliomas.
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spelling pubmed-105264592023-09-28 The Crosstalk between the EGFR and IFN-γ Pathways and Synergistic Roles in Survival Prediction and Immune Escape in Gliomas Zhou, Xingang Liang, Tingyu Ge, Yulu Wang, Yu Ma, Wenbin Brain Sci Article Glioma is the most common primary malignant brain tumor. The poor prognosis of gliomas, especially glioblastoma (GBM), is associated with their unique molecular landscape and tumor microenvironment (TME) features. The epidermal growth factor receptor (EGFR) gene is one of the frequently altered loci in gliomas, leading to the activation of the EGFR signaling pathway and thus, promoting the genesis of gliomas. Whether there exist factors within the TME that can lead to EGFR activation in the context of gliomas is currently unexplored. In total, 702 samples from The Cancer Genome Atlas (TCGA) and 325 samples from The Chinese Glioma Genome Atlas (CGGA) were enrolled in this study. Gene signatures related to EGFR signaling and interferon-γ (IFN-γ) response were established via the LASSO-COX algorithm. Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) analysis were applied for function exploration. Kaplan–Meier (KM) curves and single sample GSEA (ssGSEA) of immune cell subpopulations were performed to analyze the prognosis and TME characteristics of different subgroups. Moreover, Western blotting (WB) and flow cytometry (FCM) demonstrated the correlation between IFN-γ and EGFR signaling activation and the subsequent induction of programmed death ligand 1 (PD-L1) expression. An EGFR signaling-related risk score was established, and a higher score was correlated with poorer prognosis and a more malignant phenotype in gliomas. Biological function analysis revealed that a higher EGFR-related score was significantly associated with various cytokine response pathways, especially IFN-γ. Long-term (7 days) exposure to IFN-γ (400 ng/mL) induced the activation of EGFR signaling in the u87 cell line. Next, an IFN-γ response-related risk score was established; the combination of these two scores could be used to further reclassify gliomas into subtypes with different clinical features and TME features. Double high-risk samples tended to have a poorer prognosis and more immunosuppressive TME. Additionally, FCM discovered that the activation of EGFR signaling via EGF (100 ng/mL) could trigger PD-L1 protein expression. This research indicates that IFN-γ, an inflammatory cytokine, can activate the EGFR pathway. The combination of EGFR signaling and IFN-γ response pathway can establish a more precise classification of gliomas. MDPI 2023-09-20 /pmc/articles/PMC10526459/ /pubmed/37759950 http://dx.doi.org/10.3390/brainsci13091349 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhou, Xingang
Liang, Tingyu
Ge, Yulu
Wang, Yu
Ma, Wenbin
The Crosstalk between the EGFR and IFN-γ Pathways and Synergistic Roles in Survival Prediction and Immune Escape in Gliomas
title The Crosstalk between the EGFR and IFN-γ Pathways and Synergistic Roles in Survival Prediction and Immune Escape in Gliomas
title_full The Crosstalk between the EGFR and IFN-γ Pathways and Synergistic Roles in Survival Prediction and Immune Escape in Gliomas
title_fullStr The Crosstalk between the EGFR and IFN-γ Pathways and Synergistic Roles in Survival Prediction and Immune Escape in Gliomas
title_full_unstemmed The Crosstalk between the EGFR and IFN-γ Pathways and Synergistic Roles in Survival Prediction and Immune Escape in Gliomas
title_short The Crosstalk between the EGFR and IFN-γ Pathways and Synergistic Roles in Survival Prediction and Immune Escape in Gliomas
title_sort crosstalk between the egfr and ifn-γ pathways and synergistic roles in survival prediction and immune escape in gliomas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10526459/
https://www.ncbi.nlm.nih.gov/pubmed/37759950
http://dx.doi.org/10.3390/brainsci13091349
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