Subsequently, RF, XGBoost, and GBM machine learning methods were employed to identify the optimal prognostic genes, ultimately confirming MAP7D3 as the top prognostic gene associated with angiogenesis in PRAD. The gene discussed is MAP7D3; the disease is prostate adenocarcinoma.