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pmid:36466903

M2 macrophage-related gene signature in chronic rhinosinusitis with nasal polyps.

Ying Zhu · Xiwen Sun · Shaolin Tan · Chunyu Luo · Jiayao Zhou · Shiyao Zhang · Zhipeng Li · Hai Lin · Weitian Zhang

Frontiers in immunology · 2022 doi:10.3389/fimmu.2022.1047930

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:36466903
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science-record
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2026-11-01T19:00:56Z
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2026-11-01T22:08:14Z
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paper object · 10 fields
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title
M2 macrophage-related gene signature in chronic rhinosinusitis with nasal polyps.
doi
10.3389/fimmu.2022.1047930
pmid
36466903
authors array · 9 items
[0]
Ying Zhu
[1]
Xiwen Sun
[2]
Shaolin Tan
[3]
Chunyu Luo
[4]
Jiayao Zhou
[5]
Shiyao Zhang
[6]
Zhipeng Li
[7]
Hai Lin
[8]
Weitian Zhang
journal
Frontiers in immunology
year
2022
abstract
Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a common sinonasal inflammatory disorder with high heterogeneity. Increasing evidence have indicated that the infiltration of macrophages especially M2 macrophages play pivotal roles in the pathogenesis of CRSwNP, but the underlying mechanisms remain undetermined. This study sought to identify potential biomarkers related to M2 macrophages in CRSwNP. Methods: The expression datasets of GSE136825 and GSE179265 were download from Gene Expression Omnibus (GEO) database and merged. Then, CIBERSORT and weighted gene co-expression network analysis (WGCNA) algorithms were applied to identify M2 macrophage-related gene modules. Thereafter, differentially expressed genes (DEGs) related to M2 macrophages were selected to perform functional enrichment analyses. A protein-protein interaction (PPI) network was built to identify hub genes and quantitative real-time reverse transcriptions PCR was used to verify the bioinformatics results. Results: A total of 92 DEGs associated with M2 macrophages were identified for further analysis. The results of Gene ontology (GO) and Kyoto Encyclopedia of genes and genomes (KEGG) analyses illustrated that M2 macrophage-associated DEGs primarily enriched in immune responses and extracellular matrix structure. PPI network analysis identified 18 hub genes related to M2 macrophages that might be pivotal in the pathogenesis of CRSwNP. After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP. Conclusion: These findings yield new insights into the hub genes and mechanisms related to M2 macrophages in the pathogenesis of CRSwNP. Further studies of these hub genes would help better understand the disease progression and identify potential treatment targets.
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The comparison of 22 types of immune cells infiltration in merged datasets, the expression levels of hub DEGs in GSE23552, GSE36830 and the relative mRNA levels of hub DEGs in clinical samples from enrolled subjects between CRSwNP and control groups were carried out with Mann–Whitney U test as the data did not conform to normal distribution. Correlation analysis was performed by Spearman’s correlation.
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sections[13] "Statistical analysis" paragraph 2
quote
The comparison of 22 types of immune cells infiltration in merged datasets, the expression levels of hub DEGs in GSE23552, GSE36830 and the relative mRNA levels of hub DEGs in clinical samples from enrolled subjects between CRSwNP and control groups were carried out with Mann–Whitney U test as the data did not conform to normal distribution. Correlation analysis was performed by Spearman’s correlation.
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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 below: https://www.ncbi.nlm.nih.gov/geo/, GSE136825, GSE179265, GSE23552, GSE36830.
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sections[26] "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 below: https://www.ncbi.nlm.nih.gov/geo/, GSE136825, GSE179265, GSE23552, GSE36830.
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After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP.
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sections[0] "Abstract" paragraph 3
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After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP.
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After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP.
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Whole-transcriptome sequencing reveals heightened inflammation and defective host-defense responses in inflammation and defective host-defense responses in chronic rhinosinusitis with nasal polyps
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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 below: https://www.ncbi.nlm.nih.gov/geo/, GSE136825, GSE179265, GSE23552, GSE36830.
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title
Exon Array Analysis of Asthmatic Chronic Rhinosinusitis with Nasal Polyps
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Gene expression analysis of Chronic rhinosinusitis
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The comparison of 22 types of immune cells infiltration in merged datasets, the expression levels of hub DEGs in GSE23552, GSE36830 and the relative mRNA levels of hub DEGs in clinical samples from enrolled subjects between CRSwNP and control groups were carried out with Mann–Whitney U test as the data did not conform to normal distribution. Correlation analysis was performed by Spearman’s correlation.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36466903", "kind": "science-record", "revision": 3, "content_hash": "sha256:1c295656b0d0d28f9f6e9941c0f24692e8ec7b53984d477ac8ed4a1c8ec33fc9", "created_at": "2026-11-01T19:00:56Z", "updated_at": "2026-11-01T22:08:14Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "M2 macrophage-related gene signature in chronic rhinosinusitis with nasal polyps.", "doi": "10.3389/fimmu.2022.1047930", "pmid": "36466903", "authors": ["Ying Zhu", "Xiwen Sun", "Shaolin Tan", "Chunyu Luo", "Jiayao Zhou", "Shiyao Zhang", "Zhipeng Li", "Hai Lin", "Weitian Zhang"], "journal": "Frontiers in immunology", "year": 2022, "abstract": "Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a common sinonasal inflammatory disorder with high heterogeneity. Increasing evidence have indicated that the infiltration of macrophages especially M2 macrophages play pivotal roles in the pathogenesis of CRSwNP, but the underlying mechanisms remain undetermined. This study sought to identify potential biomarkers related to M2 macrophages in CRSwNP.\nMethods: The expression datasets of GSE136825 and GSE179265 were download from Gene Expression Omnibus (GEO) database and merged. Then, CIBERSORT and weighted gene co-expression network analysis (WGCNA) algorithms were applied to identify M2 macrophage-related gene modules. Thereafter, differentially expressed genes (DEGs) related to M2 macrophages were selected to perform functional enrichment analyses. A protein-protein interaction (PPI) network was built to identify hub genes and quantitative real-time reverse transcriptions PCR was used to verify the bioinformatics results.\nResults: A total of 92 DEGs associated with M2 macrophages were identified for further analysis. The results of Gene ontology (GO) and Kyoto Encyclopedia of genes and genomes (KEGG) analyses illustrated that M2 macrophage-associated DEGs primarily enriched in immune responses and extracellular matrix structure. PPI network analysis identified 18 hub genes related to M2 macrophages that might be pivotal in the pathogenesis of CRSwNP. After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP.\nConclusion: These findings yield new insights into the hub genes and mechanisms related to M2 macrophages in the pathogenesis of CRSwNP. Further studies of these hub genes would help better understand the disease progression and identify potential treatment targets.", "claims": [{"id": "claim-method", "statement": "The comparison of 22 types of immune cells infiltration in merged datasets, the expression levels of hub DEGs in GSE23552, GSE36830 and the relative mRNA levels of hub DEGs in clinical samples from enrolled subjects between CRSwNP and control groups were carried out with Mann–Whitney U test as the data did not conform to normal distribution. Correlation analysis was performed by Spearman’s correlation.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36466903", "locator": "sections[13] \"Statistical analysis\" paragraph 2", "quote": "The comparison of 22 types of immune cells infiltration in merged datasets, the expression levels of hub DEGs in GSE23552, GSE36830 and the relative mRNA levels of hub DEGs in clinical samples from enrolled subjects between CRSwNP and control groups were carried out with Mann–Whitney U test as the data did not conform to normal distribution. Correlation analysis was performed by Spearman’s correlation."}], "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 below: https://www.ncbi.nlm.nih.gov/geo/, GSE136825, GSE179265, GSE23552, GSE36830.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36466903", "locator": "sections[26] \"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 below: https://www.ncbi.nlm.nih.gov/geo/, GSE136825, GSE179265, GSE23552, GSE36830."}], "state": "complete"}, {"id": "claim-target-result", "statement": "After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36466903", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "After verification, AIF1, C1QA, C1QB, C3AR1, CCR1, CD163, CD4, CD53, CD86, CSF1R, CYBB, FCER1G, FCGR3A, IL10RA, ITGB2, LAPTM5, PLEK, TYROBP were identified as potential M2 macrophage-related biomarkers for CRSwNP.", "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:36466903"], "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:36466903", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2022.1047930", "sha256": "sha256:b374ab434fe49ae80f1ff7754ee945adde292e4bd02288aa3318802f09699b29", "bytes": 45781, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2022.1047930", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9712459", "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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Correlation analysis was performed by Spearman’s correlation."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["pca_fit"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pca."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE136825", "GSE179265", "GSE36830", "GSE23552"], "resolved_accessions": ["GSE136825", "GSE179265", "GSE36830", "GSE23552"], "statements": ["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 below: https://www.ncbi.nlm.nih.gov/geo/, GSE136825, GSE179265, GSE23552, GSE36830."], "basis": "The paper names GSE136825, GSE179265, GSE36830, GSE23552 in Gene Expression Omnibus (GEO) database and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["pca_fit"], "assets": ["source:pmid:36466903", "data:geo:GSE136825"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE136825"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:18:14Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12245, "completion_tokens": 1801, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:36466903", "type": "paper", "label": "pmid:36466903"}, {"id": "source:pmid:36466903", "type": "manuscript", "label": "PMID 36466903 full text"}, {"id": "data:geo:GSE136825", "type": "dataset", "label": "GEO GSE136825"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36466903", "type": "paper", "label": "pmid:36466903"}, {"id": "source:pmid:36466903", "type": "manuscript", "label": "PMID 36466903 full text"}, {"id": "data:geo:GSE136825", "type": "dataset", "label": "GEO GSE136825"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36466903", "type": "extraction", "used": ["source:pmid:36466903"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE136825", "type": "accession_resolution", "used": ["data:geo:GSE136825"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:36466903", "parent_hash": "sha256:e4c0004609d7aaae304aa9056922ed131e61f1ebf2fa5e487c9229aa31b00eac", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE136825 licence not read", "asset:data:geo:GSE136825 not downloaded", "asset:data:geo:GSE179265 licence not read", "asset:data:geo:GSE179265 not downloaded", "asset:data:geo:GSE23552 licence not read", "asset:data:geo:GSE23552 not downloaded", "asset:data:geo:GSE36830 licence not read", "asset:data:geo:GSE36830 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["d Genomes; PPI, protein-protein interaction; RT-qPCR, real-time quantitative PCR. To reduce the r", "enomes; PPI, protein-protein interaction; RT-qPCR, real-time quantitative PCR. To reduce the r", "; PPI, protein-protein interaction; RT-qPCR, real-time quantitative PCR. To reduce the ratio of false positives in a"], "order_basis": "paper_text_order:4260", "id": "assay:1"}, {"role": "analysis", "definition_id": "principal_component_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["pca_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Principal component analysis"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}