Shared genes of polycystic ovary syndrome and sedentary behavior as a novel immune landscape biomarker for endometrial cancer.

ABSTRACT: Endometrial cancer (EC) is associated with significant risk factors such as polycystic ovarian syndrome (PCOS) and sedentary behavior. In our study, we aim to employ machine learning algorithms to investigate the potential molecular processes that underlie their interaction and explore their respective roles in the diagnosis and immunotherapy of EC. The GEO database provides access to microarray data, which was utilized in this study to identify gene expression modules associated with PCOS and sedentary behavior, using weighted gene expression network analysis (WGCNA). Cluego software was then employed to investigate the energy enrichment of shared pathways in both PCOS and sedentary individuals, and differential gene analysis was used to confirm another two databases. The miRNAs-mRNAs con

SUBMITTER: Ge Y 

PROVIDER: S-EPMC11330454 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature