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Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma
Lung cancer has the highest tumor incidence in China. Lung squamous cell carcinoma (LUSC) is the most common type, accounting for 40–51% of primary lung cancers. LUSC is slow in growth and late in metastasis. Immune-related genes (IRGs) and immune infiltrating cells play a vital role in the clinical...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024339/ https://www.ncbi.nlm.nih.gov/pubmed/35463955 http://dx.doi.org/10.3389/fmolb.2022.867494 |
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author | Zhang, Xiaoting Xiao, Jing Fu, Xian Qin, Guicheng Yu, Mengli Chen, Guihong Li, Xiaofeng |
author_facet | Zhang, Xiaoting Xiao, Jing Fu, Xian Qin, Guicheng Yu, Mengli Chen, Guihong Li, Xiaofeng |
author_sort | Zhang, Xiaoting |
collection | PubMed |
description | Lung cancer has the highest tumor incidence in China. Lung squamous cell carcinoma (LUSC) is the most common type, accounting for 40–51% of primary lung cancers. LUSC is slow in growth and late in metastasis. Immune-related genes (IRGs) and immune infiltrating cells play a vital role in the clinical outcomes of LUSC. It is important to systematically study its immune gene map to help the prognosis of cancer patients. In this study, we combined the prognostic landscape and expression status of IRGs downloaded from the TCGA and InnatedDB databases and systematically analyzed the prognostic information of LUSC patients to obtain IRGs. After systematically exploring the survival analysis, prognosis-related genes were found, and the PPI network revealed that a total of 11 genes were hub genes. A two-gene prognosis risk model was established by multivariate Cox analysis. Two IRGs were closely correlated with the prognosis of LUSC. Based on these two genes, a new independent prognostic risk model was established, and this model was further verified in the GEO database. Moreover, the risk score of the model was correlated with sex, survival status, and lymphatic metastasis in LUSC patients, and the predictive risk of the prognostic risk model was significantly positively correlated with five kinds of immune cells (CD4 T cells, CD8 T cells, neutrophils, macrophages, and dendritic cells). This study comprehensively analyzed immunogenomics and presented immune-related prognostic biomarkers for LUSC. |
format | Online Article Text |
id | pubmed-9024339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90243392022-04-23 Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma Zhang, Xiaoting Xiao, Jing Fu, Xian Qin, Guicheng Yu, Mengli Chen, Guihong Li, Xiaofeng Front Mol Biosci Molecular Biosciences Lung cancer has the highest tumor incidence in China. Lung squamous cell carcinoma (LUSC) is the most common type, accounting for 40–51% of primary lung cancers. LUSC is slow in growth and late in metastasis. Immune-related genes (IRGs) and immune infiltrating cells play a vital role in the clinical outcomes of LUSC. It is important to systematically study its immune gene map to help the prognosis of cancer patients. In this study, we combined the prognostic landscape and expression status of IRGs downloaded from the TCGA and InnatedDB databases and systematically analyzed the prognostic information of LUSC patients to obtain IRGs. After systematically exploring the survival analysis, prognosis-related genes were found, and the PPI network revealed that a total of 11 genes were hub genes. A two-gene prognosis risk model was established by multivariate Cox analysis. Two IRGs were closely correlated with the prognosis of LUSC. Based on these two genes, a new independent prognostic risk model was established, and this model was further verified in the GEO database. Moreover, the risk score of the model was correlated with sex, survival status, and lymphatic metastasis in LUSC patients, and the predictive risk of the prognostic risk model was significantly positively correlated with five kinds of immune cells (CD4 T cells, CD8 T cells, neutrophils, macrophages, and dendritic cells). This study comprehensively analyzed immunogenomics and presented immune-related prognostic biomarkers for LUSC. Frontiers Media S.A. 2022-04-08 /pmc/articles/PMC9024339/ /pubmed/35463955 http://dx.doi.org/10.3389/fmolb.2022.867494 Text en Copyright © 2022 Zhang, Xiao, Fu, Qin, Yu, Chen and Li. 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 | Molecular Biosciences Zhang, Xiaoting Xiao, Jing Fu, Xian Qin, Guicheng Yu, Mengli Chen, Guihong Li, Xiaofeng Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma |
title | Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma |
title_full | Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma |
title_fullStr | Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma |
title_full_unstemmed | Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma |
title_short | Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma |
title_sort | construction of a two-gene immunogenomic-related prognostic signature in lung squamous cell carcinoma |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9024339/ https://www.ncbi.nlm.nih.gov/pubmed/35463955 http://dx.doi.org/10.3389/fmolb.2022.867494 |
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