Molecular characteristics of early- and late-onset ovarian cancer: insights from multidimensional evidence.

ABSTRACT:

Background

Ovarian cancer (OC) is among the most lethal gynecologic malignancies, characterized by poor prognosis. While aging is a well-established risk factor, the underlying mechanisms distinguishing early- and late-onset ovarian cancer remain poorly understood.

Methods

This study analyzed the global burden and age-related trends of ovarian cancer using the GBD database. A cut-off age of 55 years was used to differentiate between early and late onset ovarian cancer, and a Mendelian randomization method was also used to investigate the causal relationship between aging and ovarian cancer. Machine learning was applied to identify tumor-specific age-associated genes, followed by bioinformatics analyses and single-cell sequencing to explore the roles of these genes and immune

SUBMITTER: Shen Y 

PROVIDER: S-EPMC12016143 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature