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Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury
Radiation-induced lung injury (RILI), a potentially fatal and dose-limiting complication of radiotherapy for thoracic tumors, is divided into early reversible pneumonitis and irreversible advanced-stage fibrosis. Early detection and intervention contribute to improving clinical outcomes of patients....
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9917937/ https://www.ncbi.nlm.nih.gov/pubmed/36769382 http://dx.doi.org/10.3390/jcm12030733 |
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author | Liu, Youyi Wu, Mengdi Guo, Jingrou Tang, Yifei Jiang, Hongliang Yang, Bo Wu, Minchen Huang, Jianfeng |
author_facet | Liu, Youyi Wu, Mengdi Guo, Jingrou Tang, Yifei Jiang, Hongliang Yang, Bo Wu, Minchen Huang, Jianfeng |
author_sort | Liu, Youyi |
collection | PubMed |
description | Radiation-induced lung injury (RILI), a potentially fatal and dose-limiting complication of radiotherapy for thoracic tumors, is divided into early reversible pneumonitis and irreversible advanced-stage fibrosis. Early detection and intervention contribute to improving clinical outcomes of patients. However, there is still a lack of reliable biomarkers for early prediction and clinical diagnosis of RILI. Given the central role of inflammation in the initiation and progression of RILI, we explored specific inflammation-related biomarkers during the development of RILI in this study. Two expression profiles from the Gene Expression Omnibus (GEO) database were downloaded, in which 75 differentially expressed genes (DEGs) were screened out. Combining Gene Oncology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein–protein interaction (PPI) network analysis, we identified four inflammation-related hub genes in the progression of RILI—MMP9, IL-1β, CCR1 and S100A9. The expression levels of the hub genes were verified in RILI mouse models, with S100A9 showing the highest level of overexpression. The level of S100A9 in bronchoalveolar lavage fluid (BALF) and the expression of S100A9 in lung tissues were positively correlated with the degree of inflammation in RILI. The results above indicate that S100A9 is a potential biomarker for the early prediction and diagnosis of the development of RILI. |
format | Online Article Text |
id | pubmed-9917937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99179372023-02-11 Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury Liu, Youyi Wu, Mengdi Guo, Jingrou Tang, Yifei Jiang, Hongliang Yang, Bo Wu, Minchen Huang, Jianfeng J Clin Med Article Radiation-induced lung injury (RILI), a potentially fatal and dose-limiting complication of radiotherapy for thoracic tumors, is divided into early reversible pneumonitis and irreversible advanced-stage fibrosis. Early detection and intervention contribute to improving clinical outcomes of patients. However, there is still a lack of reliable biomarkers for early prediction and clinical diagnosis of RILI. Given the central role of inflammation in the initiation and progression of RILI, we explored specific inflammation-related biomarkers during the development of RILI in this study. Two expression profiles from the Gene Expression Omnibus (GEO) database were downloaded, in which 75 differentially expressed genes (DEGs) were screened out. Combining Gene Oncology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein–protein interaction (PPI) network analysis, we identified four inflammation-related hub genes in the progression of RILI—MMP9, IL-1β, CCR1 and S100A9. The expression levels of the hub genes were verified in RILI mouse models, with S100A9 showing the highest level of overexpression. The level of S100A9 in bronchoalveolar lavage fluid (BALF) and the expression of S100A9 in lung tissues were positively correlated with the degree of inflammation in RILI. The results above indicate that S100A9 is a potential biomarker for the early prediction and diagnosis of the development of RILI. MDPI 2023-01-17 /pmc/articles/PMC9917937/ /pubmed/36769382 http://dx.doi.org/10.3390/jcm12030733 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Youyi Wu, Mengdi Guo, Jingrou Tang, Yifei Jiang, Hongliang Yang, Bo Wu, Minchen Huang, Jianfeng Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury |
title | Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury |
title_full | Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury |
title_fullStr | Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury |
title_full_unstemmed | Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury |
title_short | Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury |
title_sort | identification of s100a9 as a potential inflammation-related biomarker for radiation-induced lung injury |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9917937/ https://www.ncbi.nlm.nih.gov/pubmed/36769382 http://dx.doi.org/10.3390/jcm12030733 |
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