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Label-Free Quantitative Proteomics Analysis of Nasal Lavage Fluid in Chronic Rhinosinusitis with Nasal Polyposis
Label-Free Quantitative Proteomics Analysis of Nasal Lavage Fluid in Chronic Rhinosinusitis with Nasal Polyposis
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Label-Free Quantitative Proteomics Analysis of Nasal Lavage Fluid in Chronic Rhinosinusitis with Nasal Polyposis
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Label-Free Quantitative Proteomics Analysis of Nasal Lavage Fluid in Chronic Rhinosinusitis with Nasal Polyposis
Label-Free Quantitative Proteomics Analysis of Nasal Lavage Fluid in Chronic Rhinosinusitis with Nasal Polyposis

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Label-Free Quantitative Proteomics Analysis of Nasal Lavage Fluid in Chronic Rhinosinusitis with Nasal Polyposis
Label-Free Quantitative Proteomics Analysis of Nasal Lavage Fluid in Chronic Rhinosinusitis with Nasal Polyposis
Journal Article

Label-Free Quantitative Proteomics Analysis of Nasal Lavage Fluid in Chronic Rhinosinusitis with Nasal Polyposis

2024
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Overview
(1) Background: Chronic rhinosinusitis (CRS) is a common chronic inflammation of the nasal mucosa and the paranasal sinuses. The pathogenesis of chronic rhinosinusitis (CRS) is multifactorial and, as of yet, not well understood. (2) Methods: Nasal lavage fluid samples were collected from patients diagnosed with chronic sinusitis with nasal polyposis (CRSwNP) (n = 10) and individuals without sinusitis (control group) (n = 10) who had no nasal complaints. In the present study, we used an untargeted label-free LC-MS/MS mass spectrometric approach combined with bioinformatics and network pathway analysis to compare the changes in the proteomic profiles of the CRSwNP group and the control group. Data from LC-MS/MS underwent univariate and multivariate analyses. (3) Results: The proteomic analyses revealed distinct differences in the abundances of nasal lavage fluid proteins between the CRSwNP and control groups: a total of 234 proteins, 151 up- and 83 down-regulated in CRSwNP. Functional Gene Ontology (GO) analysis showed that dysregulated proteins were involved in airway inflammatory reaction, immune response, and oxidative stress. The biomarkers were evaluated using the Receiver Operating Characteristic (ROC) curve; an Area Under the Curve (AUC) of 0.999 (95% CI) identified potential biomarkers between the CRSwNP and control group. EMILIN-3 and RAB11-binding protein RELCH were down-regulated, and Macrophage migration inhibitory factor and deoxyribonuclease-1 were up-regulated, in CRSwNP compared to the control group. (4) Conclusions: These differentially expressed proteins identified in CRSwNP are involved in airway inflammatory reaction, immune response, and oxidative stress. In particular, the identification of increased interleukin-36 gamma (IL-36γ), which contributes to inflammatory response, and a decrease in SOD, in this group are notable findings. In the future, several of these proteins may prove useful for exploring the pathogenesis of nasal polyps and chronic sinusitis or as objective biomarkers for quantitatively monitoring disease progression or response to therapy.