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Identification of a Gene Signature Closely Related to Immunosuppressive Tumour Microenvironment Predicting Prognosis of Patients in EGFR Mutant Lung Adenocarcinoma
Lung adenocarcinomas (LUADs) harbouring epidermal growth factor receptor (EGFR) mutations are generally unable to benefit from immune checkpoint inhibitors (ICIs) due to an immunosuppressive tumour microenvironment (TME) and a lower tumour mutation burden. Currently, no gene signature can comprehens...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8498106/ https://www.ncbi.nlm.nih.gov/pubmed/34631565 http://dx.doi.org/10.3389/fonc.2021.732841 |
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author | Li, Jia Li, Huahua Zhang, Chenyue Zhang, Chenxing Jiang, Lifeng Wang, Haiyong Liu, Huaimin |
author_facet | Li, Jia Li, Huahua Zhang, Chenyue Zhang, Chenxing Jiang, Lifeng Wang, Haiyong Liu, Huaimin |
author_sort | Li, Jia |
collection | PubMed |
description | Lung adenocarcinomas (LUADs) harbouring epidermal growth factor receptor (EGFR) mutations are generally unable to benefit from immune checkpoint inhibitors (ICIs) due to an immunosuppressive tumour microenvironment (TME) and a lower tumour mutation burden. Currently, no gene signature can comprehensively evaluate the TME and predict the prognosis of patients with EGFR-mutant LUAD. Using the Cancer Genome Atlas database of EGFR-mutant LUAD based on the immune score derived from the ESTIMATE algorithm, we divided 80 patients with EGFR-mutant LUAD samples into high and low immune score groups with different immune microenvironments. Subsequently, we screened 396 differentially expressed immune-related genes with prognostic value. The top Gene Ontology terms were significantly enriched in biological functions related to T cell differentiation, immune response, cell cycle, and cell proliferation, which are closely related to the immune microenvironment of tumours. In addition, the KEGG pathway enrichment analysis mainly focused on cell cycle, cell adhesion molecules, and cytokine-cytokine receptor interaction, which also had a relationship with the immune response. Subsequently, we identified a three-gene signature including BTLA, BUB1B, and CENPE using the LASSO Cox regression model. The three-gene signature could accurately identify patients at risk of EGFR-mutant LUAD in the training and validation sets and high-risk patients from both the sets exhibited significantly shorter overall survival (p=0.0053 and p=0.035, respectively). CIBERSORT was used to evaluate the abundance of immune cell infiltration in the EGFR-mutant LUAD microenvironment. The immune activity of B cells and macrophages was higher in the low-risk group, while the immune activity of natural killer cells and T cells was higher in the high-risk group. Thus, the three-gene signature closely related to immunosuppressive TME could predict the risk and prognosis in patients with EGFR-mutant LUAD. |
format | Online Article Text |
id | pubmed-8498106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-84981062021-10-09 Identification of a Gene Signature Closely Related to Immunosuppressive Tumour Microenvironment Predicting Prognosis of Patients in EGFR Mutant Lung Adenocarcinoma Li, Jia Li, Huahua Zhang, Chenyue Zhang, Chenxing Jiang, Lifeng Wang, Haiyong Liu, Huaimin Front Oncol Oncology Lung adenocarcinomas (LUADs) harbouring epidermal growth factor receptor (EGFR) mutations are generally unable to benefit from immune checkpoint inhibitors (ICIs) due to an immunosuppressive tumour microenvironment (TME) and a lower tumour mutation burden. Currently, no gene signature can comprehensively evaluate the TME and predict the prognosis of patients with EGFR-mutant LUAD. Using the Cancer Genome Atlas database of EGFR-mutant LUAD based on the immune score derived from the ESTIMATE algorithm, we divided 80 patients with EGFR-mutant LUAD samples into high and low immune score groups with different immune microenvironments. Subsequently, we screened 396 differentially expressed immune-related genes with prognostic value. The top Gene Ontology terms were significantly enriched in biological functions related to T cell differentiation, immune response, cell cycle, and cell proliferation, which are closely related to the immune microenvironment of tumours. In addition, the KEGG pathway enrichment analysis mainly focused on cell cycle, cell adhesion molecules, and cytokine-cytokine receptor interaction, which also had a relationship with the immune response. Subsequently, we identified a three-gene signature including BTLA, BUB1B, and CENPE using the LASSO Cox regression model. The three-gene signature could accurately identify patients at risk of EGFR-mutant LUAD in the training and validation sets and high-risk patients from both the sets exhibited significantly shorter overall survival (p=0.0053 and p=0.035, respectively). CIBERSORT was used to evaluate the abundance of immune cell infiltration in the EGFR-mutant LUAD microenvironment. The immune activity of B cells and macrophages was higher in the low-risk group, while the immune activity of natural killer cells and T cells was higher in the high-risk group. Thus, the three-gene signature closely related to immunosuppressive TME could predict the risk and prognosis in patients with EGFR-mutant LUAD. Frontiers Media S.A. 2021-09-24 /pmc/articles/PMC8498106/ /pubmed/34631565 http://dx.doi.org/10.3389/fonc.2021.732841 Text en Copyright © 2021 Li, Li, Zhang, Zhang, Jiang, Wang and Liu 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 | Oncology Li, Jia Li, Huahua Zhang, Chenyue Zhang, Chenxing Jiang, Lifeng Wang, Haiyong Liu, Huaimin Identification of a Gene Signature Closely Related to Immunosuppressive Tumour Microenvironment Predicting Prognosis of Patients in EGFR Mutant Lung Adenocarcinoma |
title | Identification of a Gene Signature Closely Related to Immunosuppressive Tumour Microenvironment Predicting Prognosis of Patients in EGFR Mutant Lung Adenocarcinoma |
title_full | Identification of a Gene Signature Closely Related to Immunosuppressive Tumour Microenvironment Predicting Prognosis of Patients in EGFR Mutant Lung Adenocarcinoma |
title_fullStr | Identification of a Gene Signature Closely Related to Immunosuppressive Tumour Microenvironment Predicting Prognosis of Patients in EGFR Mutant Lung Adenocarcinoma |
title_full_unstemmed | Identification of a Gene Signature Closely Related to Immunosuppressive Tumour Microenvironment Predicting Prognosis of Patients in EGFR Mutant Lung Adenocarcinoma |
title_short | Identification of a Gene Signature Closely Related to Immunosuppressive Tumour Microenvironment Predicting Prognosis of Patients in EGFR Mutant Lung Adenocarcinoma |
title_sort | identification of a gene signature closely related to immunosuppressive tumour microenvironment predicting prognosis of patients in egfr mutant lung adenocarcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8498106/ https://www.ncbi.nlm.nih.gov/pubmed/34631565 http://dx.doi.org/10.3389/fonc.2021.732841 |
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