Abstract
The objective of this study was to identify and characterize oxidative stress (OS)-related biomarkers in bronchopulmonary dysplasia (BPD) through a combination of bioinformatics analyses and wet experiments. The study utilized the Gene Expression Omnibus database to obtain the mRNA expression profile dataset GSE32472. Differential expression analysis and functional enrichment analysis were employed to investigate the role of OS-related genes in BPD. Gene Ontology Function Enrichment Analysis and Gene Set Enrichment Analysis were conducted to understand the mechanisms behind the signature. Protein-protein interaction analysis to identify hub genes in BPD, and predictions were made for microRNAs (miRNAs), transcription factors (TFs), and potential medications targeting these genes. CIBERSORT was utilized to investigate the correlation between hub genes and the infiltration of immune cells. Hub genes were ultimately determined and confirmed using expression analysis, correlation analysis, receiver operating characteristic (ROC) analysis, and quantitative real-time PCR (qRT-PCR). A novel OS-related gene signature (ARG1, CSF3R, IL1R1, IL1R2, MMP9, RETN, S100A12, and SOCS3) was constructed for the prediction of BPD. We identified 18 miRNAs, 14 TFs, and 30 potential medications targeting these genes. ROC analysis further validated that these genes could diagnose BPD with high specificity and sensitivity. The qRT-PCR revealed that IL1R1 and ARG1 were highly expressed in the lung tissue of the model group, while the expressions of RETN, SOCS3, IL1R2, and MMP9 were decreased. This study demonstrated that ARG1, CSF3R, IL1R1, IL1R2, MMP9, RETN, S100A12, and SOCS3 may serve as potential diagnostic biomarkers in BPD. Furthermore, a significant association between IL1R1 and the pathogenesis of BPD is observed.
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