THOC1 binds to U2AF2 and regulates ovarian cancer progression through the beta-catenin / c-myc / cyclinD1 signaling pathway

Abstract Background: Ovarian cancer (OV) poses a significant challenge in oncology due to its complex molecular mechanisms and poor prognosis. This study aims to identify key genes associated with OV progression and explore their potential as therapeutic targets. Methods: Using multiple machine learning models to identify a key gene in OV. Pan-cancer analysis was conducted to evaluate the expression, mutation, diagnosis, prognosis and pathway of THOC1 across various tumors. Cell proliferation, migration, and invasion experiments were performed to assess the