Omics · study · 2026
Whole-transcriptome sequencing reveals the inflammatory endotypes and potential biomarkers of antrochoanal polyps
Listed in NCBI GEO
Objective: To determine the transcriptome of antrochoanal polyps (ACP) in children and find the patterns of gene expression.
Description
In the meantime, by analyzing the gene expression profiles and performing functional network analysis, to investigate inflammatory patterns (endotypes), diagnostic biomarkers, and therapeutic targets of ACP.
Methods
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Whole-transcriptome analysis with next-generation sequencing (RNA-seq) was used to identify differentially expressed genes (DEGs) between 6 pairs of ACP and ipsilateral uncinate process (UP) samples from the same patients. The hub genes were identified based on the protein-protein interaction (PPI) network constructed by DEGs. For the enrichment analysis of DEGs, the Gene Ontology (GO) database was employed.
Results: ACP samples were independent of UP samples as determined by PCA analysis. A total of 1419 DEGs were screened, with 604 up-regulated genes and 815 down-regulated genes. 10 hub genes were identified that may play a crucial role in the pathogenesis of ACP: IL6, ITGAM, CXCL8, FN1, EGF, ITGAX, TLR8, FCGR3B, IFNG, LEP, from the PPI network of 1419 significantly DEGs with 942 nodes and 5085 edges. Neutrophil activation, neutrophil-mediated immunity, neutrophil activation involved in immune response, neutrophil degranulation, neutrophil chemotaxis, neutrophil migration, and other neutrophil-related biological processes were significantly enriched by GO analysis.
Links
Get the data
- GEO FTP directory ftp.ncbi.nlm.nih.gov/geo/series/GSE210nnn/GSE210515 ↗
download · from NCBI GEO
Where it is published
- GEO accession page ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE210515 ↗
landing page · from NCBI GEO
Documentation and papers
- PRJNA865938 ncbi.nlm.nih.gov/bioproject/PRJNA865938 ↗
project · from NCBI GEO
Topics
- Stated by source
- Expression profiling by high throughput sequencing · Homo sapiens
- From keywords
- Life Sciences
- Inferred from text
- Bioinformatics and computational biology 68% · RNA sequencing 65% · Sequencing 75%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NCBI GEO | GSE210515 | 15 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[field].anzsrc:group:3102 | enrichment · NCBI GEO | taxonomy-embedding@1.1.0 | title+keywords+description (68%) |
| concepts[field].local:field:life-sciences | mapping · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| concepts[method].geo_series_type:expression-profiling-by-high-throughput-sequencing | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /gdstype |
| concepts[modality].local:modality:rna-seq | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[modality].local:modality:sequencing | enrichment · NCBI GEO | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[organism].NCBITaxon:9606 | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /taxon |
| description | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /summary |
| publication_date | source · NCBI GEO | connector:ncbi_geo@1.0.0 | |
| title | source · NCBI GEO | connector:ncbi_geo@1.0.0 | /title |