Buhaiqiemu Kadeer, Shaadaiti Wufuer, Adilai Maimaitimin, Nuramatjan Ablat, Xiaopeng Li, Zhifang Chen
Endometriosis (EMs) is a prevalent gynecological disorder. Ferroptosis, known as a novel type of programmed cell death, contributes to EMs pathogenesis by promoting ectopic endometrial migration. This study was designed to investigate ferroptosis-related genes as diagnostic/predictive biomarkers for EMs using bioinformatics. EMs-related datasets were obtained from the Gene Expression Omnibus (GEO) database, while ferroptosis-related data were retrieved from the FerrDb database. Through differential expression analysis (Limma), weighted gene co-expression network analysis (WGCNA), functional enrichment analysis (GO, KEGG, and Metascape), protein-protein interaction (PPI) network analysis, LASSO regression, Random Forest algorithm, immune infiltration analysis, and matrix correlation analysis, miRNA-target gene regulatory network was constructed. Identification of the potential immune-related hub genes and their regulatory miRNAs was performed to develop early diagnostic strategies, prognostic biomarkers, and therapeutic targets for EMs. Bioinformatics analysis revealed 18 differentially expressed genes (DEGs) and 36 WGCNA module genes associated with ferroptosis in EMs. Eleven core genes were identified, and a multi-gene predictive logistic regression model was established. LASSO regression and Random Forest analyses refined the selection to six genes: BRD7, OSBPL9, AGPS, NRAS, PEX12, and NCOA4, with high diagnostic value. CIBERSORT analysis showed that immune microenvironment alterations in EMs may be closely related to these six hub genes. Additionally, three key miRNAs-hsa-mir-125a-5p, hsa-mir-218-5p, and hsa-mir-124-3p-were predicted. The six immune-related hub genes (BRD7, OSBPL9, AGPS, NRAS, PEX12, and NCOA4) and three regulatory miRNAs (hsa-mir-125a-5p, hsa-mir-218-5p, and hsa-mir-124-3p) may serve as promising targets for the early diagnosis, prognostic evaluation, and therapeutic intervention of EMs.