A Novel Partial EMT-Associated Transcriptomic Signature for Prognostic Stratification in Ovarian Cancer.
Partial epithelial-mesenchymal transition (p-EMT) is a dynamic cellular state associated with metastasis and adverse outcomes in multiple cancers, but its prognostic significance in ovarian cancer remains unclear. This study aimed to develop and validate an ovarian cancer-specific transcriptomic signature based on p-EMT-related genes, and to determine whether this signature can improve prognostic stratification and overall survival prediction across independent cohorts.
A pan-cancer p-EMT gene set was curated from ten published studies. Using transcriptomic and clinical data from TCGA-OV (n = 488), a six-gene p-EMT signature was developed via LASSO regression to generate a patient-specific risk score. The score was integrated with clinical variables to construct a prognostic nomogram and validated in the external GEO cohort GSE140082 (n = 380) and GSE165808 (n = 51).
A six-gene p-EMT transcriptomic signature (ADAM9, ANXA8L1, FSTL3, RABAC1, TPM4, and TWIST1) was significantly associated with overall survival (OS) and stratified patients into high- and low-risk groups (adjusted HR = 1.74, p < 0.001). Incorporation with age and FIGO stage in a nomogram improved predictive performance, with AUCs of 0.727, 0.700, and 0.656 at 1-, 3-, and 5-year OS, respectively. External validation in GSE140082 and GSE165808 confirmed model robustness, yielding 3-year AUCs of 0.630 and 0.826, respectively, demonstrating preserved prognostic value across independent cohorts and disease stages.
This six-gene p-EMT transcriptomic signature demonstrates prognostic value in ovarian cancer and offers potential for individualized risk stratification and clinical decisionsupport.
A pan-cancer p-EMT gene set was curated from ten published studies. Using transcriptomic and clinical data from TCGA-OV (n = 488), a six-gene p-EMT signature was developed via LASSO regression to generate a patient-specific risk score. The score was integrated with clinical variables to construct a prognostic nomogram and validated in the external GEO cohort GSE140082 (n = 380) and GSE165808 (n = 51).
A six-gene p-EMT transcriptomic signature (ADAM9, ANXA8L1, FSTL3, RABAC1, TPM4, and TWIST1) was significantly associated with overall survival (OS) and stratified patients into high- and low-risk groups (adjusted HR = 1.74, p < 0.001). Incorporation with age and FIGO stage in a nomogram improved predictive performance, with AUCs of 0.727, 0.700, and 0.656 at 1-, 3-, and 5-year OS, respectively. External validation in GSE140082 and GSE165808 confirmed model robustness, yielding 3-year AUCs of 0.630 and 0.826, respectively, demonstrating preserved prognostic value across independent cohorts and disease stages.
This six-gene p-EMT transcriptomic signature demonstrates prognostic value in ovarian cancer and offers potential for individualized risk stratification and clinical decisionsupport.