A machine learning-based basement membrane gene signature model for predicting ovarian cancer survival

Ovarian cancer is a highly invasive malignancy that lacks early symptoms. The basement membrane, which separates epithelial and stromal tissues, is highly implicated in tumor development and invasion. Aberrant expression of basement membrane genes is associated with tumor cell infiltration, invasion, and poor prognosis. This study developed a machine learning-based basement membrane gene signature (BMGS) model for predicting the prognosis of patients with ovarian cancer.