ArticleJournal of inflammation research2024
Characterization of the Immune Microenvironment and Identification of Biomarkers in Chronic Rhinosinusitis with Nasal Polyps Using Single-Cell RNA Sequencing and Transcriptome Analysis.
Article in Journal of inflammation research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 5 citations in OpenAlex.
- Endogenous Hypersensitivity Infection: A Unifying Framework forMicroorganisms · 2026Review
- Uncovering the immune-related PCD genes in chronic rhinosinusitis with nasal polyps inflammatory progression: a machine learning and functional validation study.Frontiers in cell and developmental biology · 2026Article
- [The role ofLin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2025Review
- CLEC4G Reverses Lenvatinib Resistance in Hepatocellular Carcinoma by Suppressing PD-1 Expression via the Wnt/International journal of genomics · 2025Article
- Integrated machine learning and bioinformatic analysis of mitochondrial-related signature in chronic rhinosinusitis with nasal polyps.The World Allergy Organization journal · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: 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 Methods: 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. Results: 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. Conclusion: 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.
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