Characterization of the Immune Microenvironment and Identification of Biomarkers in Chronic Rhinosinusitis with Nasal Polyps Using Single-Cell RNA Sequencing and Transcriptome Analysis

We screened and identified potential DC-associated biomarkers of CRSwNP progression by integrating scRNA-seq with whole transcriptome sequencing. We analyzed the biological pathways in which they were involved, explored their molecular regulatory mechanisms and related drugs, and constructed ceRNA, TF-mRNA, and biomarker-drug networks to identify new CRSwNP treatment targets, laying the groundwork for the clinical management of CRSwNP.

We categorized cells using single-cell RNA (scRNA) sequencing, and combined transcriptome sequencing was used to identify potential candidate genes for CRSwNP. We selected three biomarkers based on two algorithms and performed enrichment and immune correlation analyses. Biomarkers were verified using training and validation sets, receiver operating characteristic curves, immunohistochemistry, and quantitative real-time reverse-transcription PCR (qRT-PCR). Variations in biomarker expression were validated using pseudotime analysis. The networks of competing transcription factor (TF)-mRNA and competing endogenous RNA (ceRNA) were established, and the protein drugs associated with these biomarkers were predicted.

Chronic rhinosinusitis is a prevalent condition in the field of otorhinolaryngology; however, its pathogenesis remains to be elucidated. The immunological defense of the nasal mucosa is significantly influenced by dendritic cells (DCs). We identified specific biological indicators linked to DCs and explored their significance in cases of chronic rhinosinusitis with nasal polyps (CRSwNP). Patients and

Both scRNA-seq and transcriptome data showed that DCs immune infiltration was higher in the CRSwNP group than in the control group. Three DC-related biomarkers (NR4A1, CLEC4G, and CD163) were identified. In CRSwNP, NR4A1 expression decreased, whereas CLEC4G and CD163 expression increased. All biomarkers were shown to be involved in immunological and metabolic pathways by enrichment analysis. These biomarkers were associated with γδ T cells, effector memory CD4 + T cells, regulatory T cells, and immature DCs. According to pseudotime analysis, NR4A1 and CD163 expression decreased from high to low, whereas CLEC4G expression remained low.