Abstract / Summary
Abstract Dysregulated phospholipid metabolism is implicated in endometrial cancer (EC) progression, but the prognostic relevance of phospholipid metabolism-related genes (PMRGs) remains unclear. This study identified prognostic PMRGs and constructed a risk-stratification model for EC. EC transcriptome datasets and PMRGs were obtained from public databases. Prognostic genes were screened through differential expression analysis and LASSO-Cox regression, and a risk score classified patients into high- (HRG) and low-risk (LRG) groups. Gene set enrichment analysis (GSEA), immune infiltration, and drug sensitivity analyses were performed to explore underlying mechanisms, and RT-qPCR validated candidate genes. A three-gene signature (SPATA18, XBP1, LPCAT1) showed favorable prognostic performance. Pathways including Fatty Acid Metabolism, cell adhesion molecules, and cardiac muscle contraction were differentially enriched between groups (p < 0.05). SPATA18 correlated positively with eosinophils (cor = 0.35) and negatively with effector memory CD4⁺ T cells (cor = − 0.41). IC50 values of 170 drugs, including Dactolisib, Afuresertib, and Uprosertib, differed significantly between groups (p < 0.05). RT-qPCR confirmed XBP1 up-regulation and SPATA18 down-regulation in EC (p < 0.05). This phospholipid metabolism-based signature, integrating metabolic and immune features, provides a framework for risk stratification and personalized treatment in EC.