Abstract
BACKGROUND: Osteoarthritis (OA) is a prevalent chronic degenerative joint disorder characterized by progressive cartilage degradation and extracellular matrix breakdown, yet its precise pathogenesis remains elusive. This study aimed to identify a novel diagnostic biomarker for OA associated with chromatin regulators (CRs) and to explore potential correlations between signature genes and immune cell infiltration. METHODS: OA datasets were retrieved from the Gene Expression Omnibus (GEO) database and integrated with a chromatin regulator (CR) dataset. Differential expression analysis was conducted to identify CR-related differentially expressed genes (DEGs), which were subsequently subjected to functional enrichment analysis. Hub genes associated with CRs were identified through protein-protein interaction (PPI) network analysis. Single-sample gene set enrichment analysis (ssGSEA) was then employed to evaluate immune cell infiltration in OA and to assess correlations between hub gene expression and immune infiltration. Potential therapeutic compounds targeting these hub genes were predicted using the Drug Signatures Database (DSigDB). A diagnostic risk model for OA was constructed based on the identified hub genes, and its predictive performance was assessed using receiver operating characteristic (ROC) and calibration curves. Finally, the expression of the signature genes was validated both in vitro and in vivo through quantitative real-time PCR (qRT-PCR), western blotting (WB), and mouse destabilization of the medial meniscus (DMM) models. RESULTS: A total of 86 CR-related DEGs were identified, primarily enriched in histone binding and modification, the cell cycle, and the FoxO signaling pathway. PPI network analysis revealed 10 hub genes, among which Aurora kinase B (AURKB) was identified as a potential diagnostic biomarker for OA based on the constructed risk model. In mouse DMM models and IL-1β-stimulated chondrocytes, qRT-PCR and western blotting demonstrated significantly elevated AURKB expression in diseased tissues and cells. ssGSEA analysis indicated significant differences in the infiltration levels of 11 immune cell types and 12 immune-related functions between OA and control samples. Furthermore, AURKB expression was positively correlated with tumor-infiltrating lymphocytes (TILs), Th1 cells, T-cell co-inhibition, and immune checkpoint activity. Based on the 10 identified hub genes, dasatinib, enterolactone, and genistein were predicted as potential therapeutic compounds for OA. CONCLUSION: Our findings suggest that AURKB serves as a crucial biomarker in the development and progression of OA and is significantly associated with immune infiltration, offering a novel perspective for elucidating the pathogenesis of OA.