A Novel Eight-Gene Signature for Lipid Metabolism Predicts the Progression of Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Recently, studies on the mechanisms underlying lipid metabolic reprogramming in cancer have increased. However, its significance in cervical cancer remains unclear. In the present study, a prognostic signature was constructed for patients with cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) using the expression profiles of lipid metabolism-related genes (LMRGs). Furthermore, using various bioinformatics methods, a prognostic gene signature was developed for progression-free survival (PFS). This signature was externally validated using a cervical cancer dataset (GSE44001). The characteristics of the molecular subgroups of LMRGs were analyzed, and target LMRGs were identified via differential gene analysis of the expression profiles and weighted gene correlation network analysis. Thereafter, the identified target genes were used to develop the prognostic gene signature using univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. The performance of the LMRG signature was evaluated using Kaplan–Meier curves, time-dependent receiver operating characteristic curves, decision curve analysis, mutation landscapes, gene set enrichment analysis, and immune score calculation. As a result, a novel eight-LMRG signature comprising ALDH3B2, CERS3, FA2H, GLTP, NR1H3, PLIN3, SLC44A3, and SQLE was constructed. Using this gene signature, patients with CESC and significantly distinguished PFS were divided. This eight-LMRG signature exhibited independent prognostic potential and superior predictive performance compared with a previously developed 12-gene signature. Our findings suggest that our novel eight-LMRG signature contributes to the implementation of precision medicine strategies for managing patients with cervical cancer by facilitating CESC prognosis.