Retrospective analysis of metabolism-related genes in endometrial carcinoma: links to prognosis and immunity
Endometrial carcinoma is a clinically complex gynaecologic malignancy exhibiting significant molecular heterogeneity. This heterogeneity manifests as marked variability in clinical outcomes and heterogeneous therapeutic responses to emerging treatment modalities, particularly to immune checkpoint inhibitors. Metabolic reprogramming has been implicated in tumour progression and immune evasion in endometrial carcinoma. However, the prognostic implications of metabolism-related genes and their interaction with the tumour immune microenvironment remain insufficiently characterised. RNA-seq and clinical data of endometrial carcinoma were downloaded from The Cancer Genome Atlas (TCGA) database, along with a metabolism-related gene set (MRGs) curated from the Msigdb database. Differential expression analysis was conducted to identify differentially expressed metabolism-related genes (DE-MRGs), which were subsequently analysed to evaluate their expression patterns and prognostic significance in uterine corpus endometrial carcinoma. Functional enrichment was performed via GO and KEGG analysis. The CIBEROSRT computational algorithm was employed to quantify immune infiltration characteristics and their correlation with MRGs. Furthermore, an external GEO dataset (GSE17025) was employed to validate hub gene expression. A total of 49 differentially expressed MRGs were identified in endometrial carcinoma. Functional analyses showed enrichment in retinol and tyrosine metabolism pathways. Two hub genes, LIPG and DDC, were significantly associated with overall survival ( Our study analysed the expression and prognostic relevance of MRGs of endometrial carcinoma. We validated the prognostic value of MRGs and their potential to offer novel insights into prognostication and personalised treatment strategies for endometrial carcinoma.