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Exploration of the Tumor Immune Landscape and Identification of Two Novel Immunotherapy-Related Genes for Epstein-Barr virus-associated Gastric Carcinoma via Integrated Bioinformatics Analysis

Epstein–Barr virus (EBV)-associated gastric carcinoma (EBVaGC) is a specific molecular subtype of gastric carcinoma with a high proportion of tumor-infiltrating lymphocytes. It is a highly immunogenic tumor that may benefit from immunotherapy. Hence, it is imperative to analyze the immune landscape...

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Autores principales: Deng, Shi-Zhou, Wang, Xiang-Xu, Zhao, Xing-Yu, Bai, Yin-Miao, Zhang, Hong-Mei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9450882/
https://www.ncbi.nlm.nih.gov/pubmed/36090326
http://dx.doi.org/10.3389/fsurg.2022.898733
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author Deng, Shi-Zhou
Wang, Xiang-Xu
Zhao, Xing-Yu
Bai, Yin-Miao
Zhang, Hong-Mei
author_facet Deng, Shi-Zhou
Wang, Xiang-Xu
Zhao, Xing-Yu
Bai, Yin-Miao
Zhang, Hong-Mei
author_sort Deng, Shi-Zhou
collection PubMed
description Epstein–Barr virus (EBV)-associated gastric carcinoma (EBVaGC) is a specific molecular subtype of gastric carcinoma with a high proportion of tumor-infiltrating lymphocytes. It is a highly immunogenic tumor that may benefit from immunotherapy. Hence, it is imperative to analyze the immune landscape and identify immunotherapy biomarkers for EBVaGC. In our study, we investigated the immune landscape and identified 10 hub genes for EBVaGC via integrated bioinformatics analysis. We found that EBVaGC expressed more immune-related genes, including common immune checkpoints and human leukocyte antigen (HLA) genes than EBV-negative gastric carcinoma (EBVnGC). The immune score in EBVaGC was higher, which means EBVaGC has greater immune cell infiltration. Ten hub genes (CD4, STAT1, FCGR3A, IL10, C1QA, CXCL9, CXCL10, CXCR6, PD-L1, and CCL18) were detected as candidate biomarkers for EBVaGC. Two hub genes, CXCL9 and CXCR6, were identified as novel immunotherapy-related genes. Taken together, the results of our comprehensive analysis of the immune microenvironment of EBVaGC revealed its unique immune landscape, demonstrating that it is a highly immunogenic tumor. Moreover, we identified hub genes that may serve as potential immunotherapy biomarkers for EBVaGC.
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spelling pubmed-94508822022-09-08 Exploration of the Tumor Immune Landscape and Identification of Two Novel Immunotherapy-Related Genes for Epstein-Barr virus-associated Gastric Carcinoma via Integrated Bioinformatics Analysis Deng, Shi-Zhou Wang, Xiang-Xu Zhao, Xing-Yu Bai, Yin-Miao Zhang, Hong-Mei Front Surg Surgery Epstein–Barr virus (EBV)-associated gastric carcinoma (EBVaGC) is a specific molecular subtype of gastric carcinoma with a high proportion of tumor-infiltrating lymphocytes. It is a highly immunogenic tumor that may benefit from immunotherapy. Hence, it is imperative to analyze the immune landscape and identify immunotherapy biomarkers for EBVaGC. In our study, we investigated the immune landscape and identified 10 hub genes for EBVaGC via integrated bioinformatics analysis. We found that EBVaGC expressed more immune-related genes, including common immune checkpoints and human leukocyte antigen (HLA) genes than EBV-negative gastric carcinoma (EBVnGC). The immune score in EBVaGC was higher, which means EBVaGC has greater immune cell infiltration. Ten hub genes (CD4, STAT1, FCGR3A, IL10, C1QA, CXCL9, CXCL10, CXCR6, PD-L1, and CCL18) were detected as candidate biomarkers for EBVaGC. Two hub genes, CXCL9 and CXCR6, were identified as novel immunotherapy-related genes. Taken together, the results of our comprehensive analysis of the immune microenvironment of EBVaGC revealed its unique immune landscape, demonstrating that it is a highly immunogenic tumor. Moreover, we identified hub genes that may serve as potential immunotherapy biomarkers for EBVaGC. Frontiers Media S.A. 2022-05-23 /pmc/articles/PMC9450882/ /pubmed/36090326 http://dx.doi.org/10.3389/fsurg.2022.898733 Text en Copyright © 2022 Deng, Wang, Zhao, Bai and Zhang. 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) (https://creativecommons.org/licenses/by/4.0/) . 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 Surgery
Deng, Shi-Zhou
Wang, Xiang-Xu
Zhao, Xing-Yu
Bai, Yin-Miao
Zhang, Hong-Mei
Exploration of the Tumor Immune Landscape and Identification of Two Novel Immunotherapy-Related Genes for Epstein-Barr virus-associated Gastric Carcinoma via Integrated Bioinformatics Analysis
title Exploration of the Tumor Immune Landscape and Identification of Two Novel Immunotherapy-Related Genes for Epstein-Barr virus-associated Gastric Carcinoma via Integrated Bioinformatics Analysis
title_full Exploration of the Tumor Immune Landscape and Identification of Two Novel Immunotherapy-Related Genes for Epstein-Barr virus-associated Gastric Carcinoma via Integrated Bioinformatics Analysis
title_fullStr Exploration of the Tumor Immune Landscape and Identification of Two Novel Immunotherapy-Related Genes for Epstein-Barr virus-associated Gastric Carcinoma via Integrated Bioinformatics Analysis
title_full_unstemmed Exploration of the Tumor Immune Landscape and Identification of Two Novel Immunotherapy-Related Genes for Epstein-Barr virus-associated Gastric Carcinoma via Integrated Bioinformatics Analysis
title_short Exploration of the Tumor Immune Landscape and Identification of Two Novel Immunotherapy-Related Genes for Epstein-Barr virus-associated Gastric Carcinoma via Integrated Bioinformatics Analysis
title_sort exploration of the tumor immune landscape and identification of two novel immunotherapy-related genes for epstein-barr virus-associated gastric carcinoma via integrated bioinformatics analysis
topic Surgery
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9450882/
https://www.ncbi.nlm.nih.gov/pubmed/36090326
http://dx.doi.org/10.3389/fsurg.2022.898733
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