Analysis of diagnostic apoptosis-related biomarkers and immune cell infiltration characteristics in endometriosis by integrating bioinformatics and machine learning.

ABSTRACT: Endometriosis (EMs) is a chronic disease affecting millions of women worldwide, yet its pathogenesis remains unclear, and current diagnostic methods are limited. This study based on the EMs dataset from Gene Expression Omnibus (GEO), key genes related to cell apoptosis in EMs were identified through methods such as differential expression analysis and machine learning. Furthermore, analyses including nomogram construction, immune infiltration analysis, and drug prediction were performed based on these key genes. Three apoptosis-related genes-FAS, PRKAR2B and CSF2RB were identified as key genes. The nomogram constructed based on these key genes has good predictive performance. Immune infiltration analysis revealed associations between CSF2RB and activated B cells and immature dendritic cell

SUBMITTER: Weng X 

PROVIDER: S-EPMC12480475 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature