Immune Cell Infiltration Characteristics of Pigmented Villous Nodular Synovitis and Prediction of Potential Diagnostic Markers Based on Bioinformatics.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35711523", "kind": "science-record", "revision": 4, "content_hash": "sha256:adc9bb9d6ea16b2a2bbb431cb5a3820ceddb98ba19adf47d77070acf54c822c9", "created_at": "2026-11-01T18:14:41Z", "updated_at": "2026-11-01T22:06:47Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Immune Cell Infiltration Characteristics of Pigmented Villous Nodular Synovitis and Prediction of Potential Diagnostic Markers Based on Bioinformatics.", "doi": "10.1155/2022/8708692", "pmid": "35711523", "authors": ["Jun Zhang", "Bin Li", "Boming Zhao", "Yongjian Qi", "Liaobin Chen", "Jun Chen", "Biao Chen"], "journal": "BioMed research international", "year": 2022, "abstract": "Background: Pigmented villous nodular synovitis (PVNS) is a tumor-like proliferative disease characterized by impairment of daily activities, decreased quality of life, and a high recurrence rate. However, the specific pathological mechanisms are still ill-defined and controversial. The purpose of this study was to define potential diagnostic markers and evaluate immune cell infiltration in the pathogenesis of PVNS.\nMethod: The expression profile of GSE3698 was reanalyzed in the Gene Expression Omnibus (GEO) database. First, differentially expressed genes (DEGs) were identified using the R package \"limma\" and analyzed by Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Next, the DEGs were imported into the STRING database and Cytoscape to construct a protein-protein interaction (PPI) network. Then, cytoHubba and ROC curve analyses were used to determine potential diagnostic biomarkers of PVNS. Finally, we used CIBERSORT to estimate the proportions of 22 immune cell subtypes in PVNS and analyzed the correlation between diagnostic markers and infiltrating immune cells.\nResult: We found 139 DEGs (including 93 upregulated genes and 46 downregulated genes). TYROBP, FCER1G, LAPTM5, and HLA-DPB1 were identified as potential diagnostic biomarkers of PVNS. Immune cell infiltration analysis indicated that neutrophils and M2 macrophages might be associated with the genesis and progression of PVNS. Furthermore, our correlation analysis of diagnostic markers and infiltrating immune cells found that TYROBP, FCER1G, LAPTM5, and HLA-DPB1 were positively correlated with M2 macrophage infiltration and that neutrophils, TYROBP, FCER1G, and LAPTM5 were negatively correlated with plasma cell infiltration.\nConclusions: We identified TYROBP, FCER1G, LAPTM5, and HLA-DPB1 as potential diagnostic markers for PVNS and concluded that immune cell infiltration plays an important role in the genesis and progression of PVNS.", "claims": [{"id": "claim-method", "statement": "We performed Spearman correlation analysis between the expression matrix data of diagnostic markers and infiltrating immune cells.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35711523", "locator": "sections[9] \"2.7. Correlation Analysis between Diagnostic Markers and Infiltrating Immune Cells\" paragraph 2", "quote": "We performed Spearman correlation analysis between the expression matrix data of diagnostic markers and infiltrating immune cells."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are available from the GEO database (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35711523", "locator": "sections[21] \"Data Availability\" paragraph 2", "quote": "The data used to support the findings of this study are available from the GEO database (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The diagnostic markers LAPTM5, FCER1G, TYROBP, and HLA-DPB1 were significantly correlated with M2 macrophage and neutrophil infiltration, while LAPTM5, FCER1G, and TYROBP were negatively associated with plasma cell infiltration.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35711523", "locator": "sections[16] \"3.6. Correlation Analysis between Diagnostic Markers and Infiltrating Immune Cells\" paragraph 2", "quote": "The results showed that LAPTM5 was positively correlated with M2 macrophages (r = 0.53, P = 0.0058) and neutrophils (r = 0.43, P = 0.0027) and negatively correlated with plasma cells (r = −0.5, P = 0.0097); FCER1G was positively correlated with M2 macrophages (r = 0.54, P = 0.0049) and neutrophils (r = 0.4, P = 0.04) and negatively correlated with plasma cells (r = −0.58, P = 0.0021); TYROBP was positively correlated with M2 macrophages (r = 0.49, P = 0.011) and neutrophils and negatively correlated with plasma cells (r = −0.47, P = 0.015); HLA-DPB1 was positively correlated with M2 macrophages (r = 0.43, P = 0.029) and neutrophils (r = 0.4, P = 0.042) (Figure 7)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The diagnostic markers LAPTM5, FCER1G, TYROBP, and HLA-DPB1 were significantly correlated with M2 macrophage and neutrophil infiltration, while LAPTM5, FCER1G, and TYROBP were negatively associated with plasma cell infiltration.", "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:35711523"], "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. 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