KAZN methylation as a potential diagnostic and prognostic marker in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is characterized by aggressive malignancy and poor prognosis often attributed to challenges in early diagnosis. Using machine learning on extensive public methylation databases (including TCGA and GEO), we developed a model that accurately distinguishes NSCLC from normal tissues (>94%), comparable to typical diagnostic methods. KAZN methylation patterns also proved informative for predicting patient survival. Mendelian randomization (MR) analyses provided support for a potential causal relationship between KAZN methylation and NSCLC development. In vitro experiments validated that KAZN expression is significantly lower in NSCLC tumor tissues and cell lines compared to normal controls. Demethylation treatment significantly elevated KAZN expression in lung adenocarcinoma cell lines. KAZN expression significantly affects the apoptosis and proliferation in NSCLC cell lines by potentially targeting USP2. Overall, aberrant methylation of KAZN plays an important role in NSCLC pathogenesis and KAZN methylation may serves as a useful biomarker for molecular characterization, diagnosis, and prognosis.