{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T05:43:08Z","timestamp":1776058988347,"version":"3.50.1"},"reference-count":58,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T00:00:00Z","timestamp":1776038400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Osteoarthritis (OA) is widely recognized as the most prevalent degenerative disorder affecting the joints, representing a major contributor to chronic pain and disability. Despite its high burden, the molecular mechanisms underlying OA pathogenesis remain poorly understood, particularly in the context of immune microenvironment modulation. This study explores the immune-related OA progression mechanisms and investigates potential biomarkers to aid diagnosis and therapeutic intervention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Gene expression data from the GEO database were analyzed, differentially expressed genes (DEGs) and OA-associated gene modules were identified using the LIMMA package in combination with weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted on intersecting genes, which were analyzed using the protein-protein interaction network, XGBoost, and Random Forest, identifying core genes. Subsequently, immune cell infiltration was determined through immune cell infiltration analysis and single-cell sequencing analysis. Next, core genes were validated using Mendelian randomization (MR) and Western blotting (WB). Finally,\n                      <jats:italic>in vitro<\/jats:italic>\n                      validation confirmed key findings.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 1,171 upregulated DEGs were identified. WGCNA analysis delineated 25 co-expression modules, and the turquoise module emerged as the most strongly related to OA. The PPI network, XGBoost, and Random Forest analysis pinpointed three hub genes: protein tyrosine phosphatase receptor type C (PTPRC), C-X3-C Motif Chemokine Receptor 1 (CX3CR1) and Integrin Subunit Beta 2 (ITGB2). Immune cell infiltration analysis indicates that these key genes exhibit significant associations with immune cells, while single-cell sequencing and GSEA enrichment analysis further suggested their involvement in inflammatory pathways and immune activation.\n                      <jats:italic>In vitro<\/jats:italic>\n                      experiments demonstrate that one of the hub genes\u2014PTPRC\u2014alleviates the deterioration of OA through three levels. Virtual knockout in Natural Killer (NK) cells further confirms that PTPRC influences OA by regulating the immune microenvironment.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study identified three promising biomarkers in OA and certificated that PTPRC plays a pivotal role in alleviating OA progression through immunomodulation, offering a novel intervention pathway for tissue engineering combined with immunomodulatory therapy in OA.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1795075","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T04:47:19Z","timestamp":1776055639000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploring immune modulation in osteoarthritis: identifying key biomarkers and the role of PTPRC 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University of Technology","place":["Panjin, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohui","family":"Yu","sequence":"additional","affiliation":[{"name":"Women and Children\u2019s Hospital of Dalian University of Technology","place":["Dalian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Liu","sequence":"additional","affiliation":[{"name":"Women and Children\u2019s Hospital of Dalian University of Technology","place":["Dalian, China"]},{"name":"Liaoning Key Laboratory of Integrated Circuit and Biomedical Electronic System, Faculty of Medicine, Dalian University of Technology","place":["Dalian, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2026,4,13]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.autrev.2018.06.002","article-title":"Osteoarthritis and its management - epidemiology, nutritional aspects and environmental 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