This study seeks to identify potential clinical biomarkers for osteoarthritis (OA) using bioinformatics and investigate OA mechanisms through cellular assays. Differentially Expressed Genes (DEGs) from GSE52042 (four OA samples, four control samples) were screened and analyzed with protein-protein interaction (PPI) analysis. Overlapping genes in GSE52042 and GSE206848 (seven OA samples, and seven control samples) were identified and evaluated using Gene Set Enrichment Analysis (GSEA) and clinical diagnostic value analysis to determine the hub gene. Finally, whether and how the hub gene impacts LPS-induced OA progression was explored by in vitro experiments, including Western blotting (WB), co-immunoprecipitation (Co-IP), flow cytometry, etc. Bioinformatics analysis of DEGs (142 up-regulated and 171 down-regulated) in GSE52042 identified two overlapping genes (U2AF2, TPX2) that exhibit significant clinical diagnostic value. These genes are up-regulated in OA samples from both GSE52042 and GSE206848 datasets. Notably, TPX2, which AUC = 0.873 was identified as the hub gene. In vitro experiments have demonstrated that silencing TPX2 can alleviate damage to chondrocytes induced by lipopolysaccharide (LPS). Furthermore, there is a protein interaction between TPX2 and MMP13 in OA. Excessive MMP13 can attenuate the effects of TPX2 knockdown on LPS-induced changes in OA protein expression, cell growth, and apoptosis. In conclusion, our findings shed light on the molecular mechanisms of OA and suggested TPX2 as a potential therapeutic target. TPX2 could promote the progression of LPS-induced OA by up-regulating the expression of MMP13, which provides some implications for clinical research.
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