Identification of Key Genes Associated with Polycystic Ovarian Syndrome and Endometrial and Ovarian Cancer through Bioinformatics.

ABSTRACT:

Background

Polycystic ovary syndrome (PCOS), a common endocrine disorder, is linked to increased risks of endometrial cancer (EC) and ovarian cancer (OC). Our study utilises bioinformatics analysis to identify shared gene signatures and elucidate biological processes between EC and OC and PCOS.

Aim

The objective of this research is to unveil the common molecular landscape shared by PCOS and EC and OC.

Settings and design

An observational computational bioinformatics analysis.

Materials and methods

Gene expression profiles for PCOS (GSE199225), EC (GSE215413) and OC (GSE174670) were obtained from the Gene Expression Omnibus database. Hub genes were identified through functional enrichment analysis and protein-protein interaction. Drug identification analyses wer

SUBMITTER: Raulo K 

PROVIDER: S-EPMC11290717 | biostudies-literature | 2024 Apr-Jun

REPOSITORIES: biostudies-literature