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Identification and validation of autophagy-related genes and exploration of their relationship with disease severity in chronic rhinosinusitis with nasal polyps. | LitMetric

AI Article Synopsis

  • The study investigates the role of autophagy-related genes in chronic rhinosinusitis with nasal polyps (CRSwNP) to identify new treatment targets.
  • Researchers analyzed gene expression data and found 86 differentially expressed autophagy-related genes (DEGs) that could influence the disease.
  • The study confirmed the involvement of specific hub genes in CRSwNP progression and their correlation with disease severity through various validation methods.

Article Abstract

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) pathogenesis might be impacted by autophagy. Nevertheless, autophagy-related gene utilization as a disease indicator about the course of CRSwNP has yet to be elucidated.

Objective: This investigation aimed at discovering pivotal molecules related to autophagy to identify potential treatment targets for CRSwNP.

Methods: The dataset GSE136825 was obtained via the Gene Expression Omnibus (GEO) database, and afterward, differentially expressed genes (DEGs) analysis linked to autophagy was employed via the R software. A comprehensive examination of autophagy-related DEGs was conducted using functional analytic techniques. The utilization of the protein-protein interaction (PPI) network facilitated hub gene identification. Quantitative real-time polymerase chain reaction (qRT-PCR), western blot, and immunohistochemistry staining techniques were performed to validate the expression levels of the central genes in clinical samples. Correlation analysis was performed to examine the correlation between hub genes and disease severity parameters.

Results: A comprehensive set of 86 autophagy-related DEGs were discovered. The functional enrichment analysis of autophagy-related DEGs revealed the identification of enrichment terms involved with the autophagy process. The results obtained from the PPI analysis suggest that there was interaction among the autophagy-related genes. The qRT-PCR, immunohistochemistry staining, and western blot techniques yielded results, demonstrated that , , and expression levels in CRSwNP agreed with the bioinformatics analysis of the dataset. Furthermore, a favorable association between , , and expression levels with illness severity indicators was found.

Conclusion: Bioinformatics analysis yielded 86 autophagy-related DEGs in CRSwNP. , , and regulation of autophagy has been confirmed in CRSwNP progression and pathogenesis.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11608634PMC
http://dx.doi.org/10.5415/apallergy.0000000000000159DOI Listing

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