Butein

Although kinesin family member 2C (KIF2C) is implicated in various cancers, its role in osteosarcoma (OS) and the associated inflammatory microenvironment remains unclear.

Publicly available datasets were analyzed to determine KIF2C expression, diagnostic value, and prognostic relevance in OS. In vitro (proliferation, colony formation, apoptosis, migration, invasion) and in vivo assays assessed its biological functions. KEGG enrichment and GSVA explored underlying pathways. ssGSEA, ESTIMATE algorithms, and single‐cell sequencing evaluated the immune context, and molecular docking and molecular dynamics identified potential inhibitory compounds.

KIF2C was significantly overexpressed in OS, effectively distinguishing OS from normal tissues. Elevated KIF2C levels correlated with poor survival outcomes. Silencing KIF2C suppressed OS cell proliferation, migration, invasion, and in vivo tumor growth, while promoting apoptosis; conversely, overexpression of KIF2C had the opposite effect. Mechanistically, co‐immunoprecipitation results indicated that KIF2C can bind to β‐catenin to regulate the Wnt/β‐catenin pathway. Furthermore, high KIF2C expression was associated with an immunosuppressive tumor microenvironment characterized by immune exhaustion. Molecular docking and molecular dynamics suggested butein as a candidate small‐molecule inhibitor targeting KIF2C‐related oncogenic mechanisms.

KIF2C drives OS progression by enhancing Wnt/β‐catenin signaling and fostering an immunosuppressive microenvironment. Targeting KIF2C may offer new therapeutic approaches in managing OS.

Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic disorder affecting women of reproductive age. Oxidative stress (OS) is suggested to play a significant role in the development of PCOS. Using antioxidants to reduce OS and maintain a healthy balance in the body could be a novel treatment approach for PCOS. This study analyzed transcriptome data from the Gene Expression Omnibus database, focusing on genes associated with OS. By implementing two machine learning algorithms, three OS-related biomarkers-HMOX1, MMP9, and KLF2-were successfully identified. To evaluate the diagnostic potential of these biomarkers, a Logistic regression model was employed. Additionally, granulosa cells were collected from healthy individuals and infertile women with PCOS, and the reliability of HMOX1, MMP9, and KLF2 was verified by quantitative real-time PCR experiments. Furthermore, small molecule drugs targeting proteins encoded by genes HMOX1 and MMP9 were predicted through the Drug Signature Database. Molecular docking of drugs to proteins identified two antioxidants, butein and demethoxycurcumin, as potential candidates for PCOS therapy.