ArticleJournal of clinical medicine2023
Identification of S100A9 as a Potential Inflammation-Related Biomarker for Radiation-Induced Lung Injury.
Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Integrative network pharmacology and molecular modeling approaches reveal the therapeutic potential ofFrontiers in bioinformatics · 2026Article
- Unveiling pharmacological targets of Rihimaside C for radiation-induced lung injury: An in silico and experimental integrated approach.Journal of traditional and complementary medicine · 2025Article
- Anti-cancer Effect and Active Phytochemicals of Houttuynia cordata Thunb. against Human Breast Cancer Cells.Asian Pacific journal of cancer prevention : APJCP · 2023Article
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8 authors.
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Abstract
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.
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