Identification of metabolic reprogramming-associated biomarkers in endometriosis through integrated bioinformatics analysis.

BACKGROUND: Endometriosis (EMs), a common gynecological disorder, involves complex molecular mechanisms. Metabolic reprogramming (MR) has been recognized as a hallmark of EMs, contributing to lesion survival and immune microenvironment remodeling. This study aimed to identify MR-associated hub genes and pathways associated with EMs through integrated multi-omics analyses. METHODS: EMs-related datasets were downloaded from the Gene Expression Omnibus database, including training sets (GSE51981 and GSE7305) and validation sets (GSE25628 and GSE141549). MR related genes were retrieved from the Genecards database. EMs-related differentially expressed genes (DEGs) were identified, and WGCNA was performed to identify module genes. Protein-protein interaction (PPI) networks were constructed. The expression of key genes was validated in an external dataset and clinical samples (immunohi0stochemistry). The CIBERSORT and ssGSEA tools were utilized to explore immune cell infiltration. In vitro experiments involving overexpression and RT-qPCR in Z12 cells were conducted to explore gene function on MR. RESULTS: A total 107 MR-associated candidate genes were identified. PPI network analysis identified top 10 hub genes. External validation confirmed significant downregulation of key genes in ectopic endometrium, with HNRNPR, SYNCRIP, HSP90B1, HSPA4, HSPA8, CCT2 and CCT5 demonstrating high diagnostic value (AUC > 0.8). Immune infiltration analysis revealed associations between key genes and CD8 + T cells, regulatory T cells, and mast cells. Immunohistochemistry confirmed reduced expression of CCT2, HSP90B1, and SYNCRIP in EMs lesions. In vitro validation confirmed that HSP90B1 overexpression upregulated GLUT1, LDH, and COX-2 expression in Z12 cells. CONCLUSION: This study identified several MR-related genes, as potential diagnostic biomarkers and mechanistic contributors to EMs.