Unveiling and validating biomarkers related to the IL-10 family in chronic sinusitis with nasal polyps: insights from transcriptomics and single-cell RNA sequencing analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39830981", "kind": "science-record", "revision": 4, "content_hash": "sha256:e3257ea3028956d656f62eeb75a6a7d531a9ca2a23b9b7d5558923fc7f1fa310", "created_at": "2026-11-01T20:30:07Z", "updated_at": "2026-11-01T22:56:01Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Unveiling and validating biomarkers related to the IL-10 family in chronic sinusitis with nasal polyps: insights from transcriptomics and single-cell RNA sequencing analysis.", "doi": "10.3389/fmolb.2024.1513951", "pmid": "39830981", "authors": ["Xinghong Liu", "Yi Peng", "Ling Guo", "Weilan Xiong", "Weijiang Liao", "Jiangang Fan"], "journal": "Frontiers in molecular biosciences", "year": 2024, "abstract": "Introduction: Extensive efforts have been made to explore members of the IL-10 family as potential therapeutic strategies for various diseases; however, their biological role in chronic rhinosinusitis with nasal polyps (CRSwNP) remains underexplored.\nMethods: Gene expression datasets GSE136825, GSE179265, and GSE196169 were retrieved from the Gene Expression Omnibus (GEO) for analysis. Candidate genes were identified by intersecting differentially expressed genes (DEGs) between the CRSwNP and control groups (DEGsall) with those between the high- and low-score groups within the CRSwNP cohort (DEGsNP). Biomarker selection was performed using the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine Recursive Feature Elimination (SVM-RFE), and the Boruta algorithm. Further refinement of biomarkers was carried out using receiver operating characteristic (ROC) analysis, with genes demonstrating an area under the curve (AUC) greater than 0.7 being considered significant. Genes exhibiting consistent expression trends and significant differences across both GSE136825 and GSE179265 were selected as potential biomarkers. Cell-type annotation was performed on GSE196169, and the expression profiles of the biomarkers across various cell types were analyzed. A competing endogenous RNA (ceRNA) network and a biomarker-drug interaction network were also established. Additionally, the mRNALocater database was utilized to determine the cellular localization of the identified biomarkers.\nResults: The intersection of 1817 DEGsall and 24 DEGsNP yielded 15 candidate genes. Further filtering through LASSO, SVM-RFE, and Boruta led to the identification of seven candidate biomarkers: PRB3, KRT16, MUC6, SPAG4, FGFBP1, NR4A1, and GSTA2. Six of these genes demonstrated strong diagnostic performance in GSE179265, while four biomarkers, showing both significant differences and consistent expression trends, were validated in both GSE179265 and GSE136825. Single-cell sequencing analysis of GSE196169 revealed seven distinct cell types, including endothelial cells, with the biomarkers predominantly expressed in epithelial cells. The ceRNA network comprised nine nodes and eleven edges, with only FGFBP1 exhibiting a complete lncRNA-miRNA-mRNA interaction.\nDiscussion: This study identifies several novel biomarkers and their associated drugs for CRSwNP therapy, as well as potential therapeutic targets, such as spiperone and arnenous acid, identified through molecular docking. Ultimately, this work underscores the identification of four IL-10 family-related biomarkers, providing a theoretical foundation for future clinical research in CRSwNP.", "claims": [{"id": "claim-method", "statement": "For GSE136825, differential gene expression between CRSwNP and control samples (DEG_all) was analyzed using the DESeq2 package in R (McDermaid et al., 2019).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39830981", "locator": "sections[4] \"2.2 Differential expression analysis\" paragraph 2", "quote": "For GSE136825, differential gene expression between CRSwNP and control samples (DEG_all) was analyzed using the DESeq2 package in R (McDermaid et al., 2019)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39830981", "locator": "sections[33] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The intersection of 1817 DEGsall and 24 DEGsNP yielded 15 candidate genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39830981", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The intersection of 1817 DEGsall and 24 DEGsNP yielded 15 candidate genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The intersection of 1817 DEGsall and 24 DEGsNP yielded 15 candidate genes.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:39830981"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE136825"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE136825"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39830981", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fmolb.2024.1513951", "sha256": "sha256:fd797ee344d8840fd1a8a19c47a33a797671d3facc8851e51dab5fec63d6288f", "bytes": 49488, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fmolb.2024.1513951", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11738911", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE136825", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE136825", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE136825", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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