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Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma
BACKGROUND: Early-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets. METHODS:...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8643179/ https://www.ncbi.nlm.nih.gov/pubmed/34876838 http://dx.doi.org/10.2147/IJGM.S341175 |
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author | Li, Liang Yu, Xue Ma, Guanqiang Ji, Zhiqi Bao, Shihao He, Xiaopeng Song, Liang Yu, Yang Shi, Mo Liu, Xiangyan |
author_facet | Li, Liang Yu, Xue Ma, Guanqiang Ji, Zhiqi Bao, Shihao He, Xiaopeng Song, Liang Yu, Yang Shi, Mo Liu, Xiangyan |
author_sort | Li, Liang |
collection | PubMed |
description | BACKGROUND: Early-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets. METHODS: Gene expression profiles and clinical data of early-stage LUSC patients were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases and IRGs from the InnateDB database. Univariate and multivariate Cox regression and LASSO regression analyses were performed to identify an innate IRG signature model prognostic in patients with early-stage LUSC. The predictive ability of this model was assessed by time-dependent receiver operator characteristic curve analysis, with the independence of the model-determined risk score assessed by univariate and multivariate Cox regression analyses. Overall survival (OS) in early-stage LUSC patients was assessed using a nomogram and decision curve analysis (DCA). Functional and biological pathways were determined by gene set enrichment analysis, and differences in biological functions and immune microenvironments between the high- and low-risk groups were assessed by ESTIMATE and the CIBERSORT algorithm. RESULTS: A signature involving six IRGs (SREBF2, GP2, BMX, NR1H4, DDX41, and GOPC) was prognostic of OS. Samples were divided into high- and low-risk groups based on median risk scores. OS was significantly shorter in the high-risk than in the low-risk group in the training (P < 0.001), GEO validation (P = 0.00021) and TCGA validation (P = 0.034) cohorts. Multivariate Cox regression analysis showed that risk score was an independent risk factor for OS, with the combination of risk score and T stage being optimally predictive of clinical benefit. GSEA, ESTIMATE, and the CIBERSORT algorithm showed that immune cell infiltration was higher and immune-related pathways were more strongly expressed in the low-risk group. CONCLUSION: A signature that includes these six innate IRGs may predict prognosis in patients with early-stage LUSC. |
format | Online Article Text |
id | pubmed-8643179 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-86431792021-12-06 Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma Li, Liang Yu, Xue Ma, Guanqiang Ji, Zhiqi Bao, Shihao He, Xiaopeng Song, Liang Yu, Yang Shi, Mo Liu, Xiangyan Int J Gen Med Original Research BACKGROUND: Early-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets. METHODS: Gene expression profiles and clinical data of early-stage LUSC patients were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases and IRGs from the InnateDB database. Univariate and multivariate Cox regression and LASSO regression analyses were performed to identify an innate IRG signature model prognostic in patients with early-stage LUSC. The predictive ability of this model was assessed by time-dependent receiver operator characteristic curve analysis, with the independence of the model-determined risk score assessed by univariate and multivariate Cox regression analyses. Overall survival (OS) in early-stage LUSC patients was assessed using a nomogram and decision curve analysis (DCA). Functional and biological pathways were determined by gene set enrichment analysis, and differences in biological functions and immune microenvironments between the high- and low-risk groups were assessed by ESTIMATE and the CIBERSORT algorithm. RESULTS: A signature involving six IRGs (SREBF2, GP2, BMX, NR1H4, DDX41, and GOPC) was prognostic of OS. Samples were divided into high- and low-risk groups based on median risk scores. OS was significantly shorter in the high-risk than in the low-risk group in the training (P < 0.001), GEO validation (P = 0.00021) and TCGA validation (P = 0.034) cohorts. Multivariate Cox regression analysis showed that risk score was an independent risk factor for OS, with the combination of risk score and T stage being optimally predictive of clinical benefit. GSEA, ESTIMATE, and the CIBERSORT algorithm showed that immune cell infiltration was higher and immune-related pathways were more strongly expressed in the low-risk group. CONCLUSION: A signature that includes these six innate IRGs may predict prognosis in patients with early-stage LUSC. Dove 2021-11-30 /pmc/articles/PMC8643179/ /pubmed/34876838 http://dx.doi.org/10.2147/IJGM.S341175 Text en © 2021 Li et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Li, Liang Yu, Xue Ma, Guanqiang Ji, Zhiqi Bao, Shihao He, Xiaopeng Song, Liang Yu, Yang Shi, Mo Liu, Xiangyan Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma |
title | Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma |
title_full | Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma |
title_fullStr | Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma |
title_full_unstemmed | Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma |
title_short | Identification of an Innate Immune-Related Prognostic Signature in Early-Stage Lung Squamous Cell Carcinoma |
title_sort | identification of an innate immune-related prognostic signature in early-stage lung squamous cell carcinoma |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8643179/ https://www.ncbi.nlm.nih.gov/pubmed/34876838 http://dx.doi.org/10.2147/IJGM.S341175 |
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