A novel mitochondrial autophagy and aging-related gene signature for predicting ovarian cancer.

ABSTRACT: Ovarian cancer (OC) is a highly malignant gynecologic tumor with a poor prognosis. In recent years, mitochondrial autophagy and aging (MiAg) have been recognized as crucial pathophysiological mechanisms leading to tumorigenesis. However, the expression of MiAg-related genes in OC and their correlation with prognosis remain unclear. In this study, we used multiple machine learning methods to identify 52 MiAg genes that were differentially expressed between OC and normal ovarian tissues. Based on these 52 differentially expressed genes (DEGs), 375 OC patients were classified into two subtypes by consensus clustering analysis. Subsequently, we evaluated the prognostic value of MiAg-related genes in relation to survival in 375 OC patients with complete survival information, and developed a MiA

SUBMITTER: Zhang H 

PROVIDER: S-EPMC12177532 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature