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The screening of immune-related biomarkers for prognosis of lung adenocarcinoma
Lung adenocarcinoma (LUAD) accounts for a frequently seen non-small cell lung cancer (NSCLC) histological subtype, and it is associated with dismal prognostic outcome. However, the benefits of traditional treatment are still limited, and the efficacies of immunotherapy are quite different. Therefore...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806236/ https://www.ncbi.nlm.nih.gov/pubmed/33870858 http://dx.doi.org/10.1080/21655979.2021.1911211 |
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author | Liu, Zhonghui Sun, Dan Zhu, Qing Liu, Xinmin |
author_facet | Liu, Zhonghui Sun, Dan Zhu, Qing Liu, Xinmin |
author_sort | Liu, Zhonghui |
collection | PubMed |
description | Lung adenocarcinoma (LUAD) accounts for a frequently seen non-small cell lung cancer (NSCLC) histological subtype, and it is associated with dismal prognostic outcome. However, the benefits of traditional treatment are still limited, and the efficacies of immunotherapy are quite different. Therefore, it is of great significance to identify novel immune-related therapeutic targets in lung adenocarcinoma. In this study, we identified a set of immune-related biomarkers for prognosis of lung adenocarcinoma, which could provide new ideas for immunotherapy of lung adenocarcinoma. Datasets related to LUAD were filtered from the GEO database. The appropriate packages were used to identify differentially expressed genes (DEGs) and to carry out enrichment analysis, followed by the construction of prognostic biomarkers. The Kaplan-Meier (K-M) curves were plotted to analyze patient survival based on hub genes. Associations between the expression of selected biomarkers and six types of tumor-infiltrating immune cells were evaluated based on the online tool TIMER. After analyzing five GEO datasets(GSE32867, GSE46539, GSE63459, GSE75037 and GSE116959), we discovered altogether 67 DEGs, among which, 15 showed up-regulation while 52 showed down-regulation. Enrichments of integrated DEGs were identified in the ontology categories. CAV1, CFD, FMO2 and CLEC3B were eventually selected as independent prognostic biomarkers, they were correlated with clinical outcomes of LUAD patients. Moreover, a positive correlation was observed between biomarker expression and all different types of immune infiltration, and the expression level of the four biomarkers was all positively related to macrophage. |
format | Online Article Text |
id | pubmed-8806236 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-88062362022-02-02 The screening of immune-related biomarkers for prognosis of lung adenocarcinoma Liu, Zhonghui Sun, Dan Zhu, Qing Liu, Xinmin Bioengineered Research Paper Lung adenocarcinoma (LUAD) accounts for a frequently seen non-small cell lung cancer (NSCLC) histological subtype, and it is associated with dismal prognostic outcome. However, the benefits of traditional treatment are still limited, and the efficacies of immunotherapy are quite different. Therefore, it is of great significance to identify novel immune-related therapeutic targets in lung adenocarcinoma. In this study, we identified a set of immune-related biomarkers for prognosis of lung adenocarcinoma, which could provide new ideas for immunotherapy of lung adenocarcinoma. Datasets related to LUAD were filtered from the GEO database. The appropriate packages were used to identify differentially expressed genes (DEGs) and to carry out enrichment analysis, followed by the construction of prognostic biomarkers. The Kaplan-Meier (K-M) curves were plotted to analyze patient survival based on hub genes. Associations between the expression of selected biomarkers and six types of tumor-infiltrating immune cells were evaluated based on the online tool TIMER. After analyzing five GEO datasets(GSE32867, GSE46539, GSE63459, GSE75037 and GSE116959), we discovered altogether 67 DEGs, among which, 15 showed up-regulation while 52 showed down-regulation. Enrichments of integrated DEGs were identified in the ontology categories. CAV1, CFD, FMO2 and CLEC3B were eventually selected as independent prognostic biomarkers, they were correlated with clinical outcomes of LUAD patients. Moreover, a positive correlation was observed between biomarker expression and all different types of immune infiltration, and the expression level of the four biomarkers was all positively related to macrophage. Taylor & Francis 2021-04-17 /pmc/articles/PMC8806236/ /pubmed/33870858 http://dx.doi.org/10.1080/21655979.2021.1911211 Text en © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Paper Liu, Zhonghui Sun, Dan Zhu, Qing Liu, Xinmin The screening of immune-related biomarkers for prognosis of lung adenocarcinoma |
title | The screening of immune-related biomarkers for prognosis of lung adenocarcinoma |
title_full | The screening of immune-related biomarkers for prognosis of lung adenocarcinoma |
title_fullStr | The screening of immune-related biomarkers for prognosis of lung adenocarcinoma |
title_full_unstemmed | The screening of immune-related biomarkers for prognosis of lung adenocarcinoma |
title_short | The screening of immune-related biomarkers for prognosis of lung adenocarcinoma |
title_sort | screening of immune-related biomarkers for prognosis of lung adenocarcinoma |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8806236/ https://www.ncbi.nlm.nih.gov/pubmed/33870858 http://dx.doi.org/10.1080/21655979.2021.1911211 |
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