Zhang D, Li Y, Yang S, et al. - A nine-glycolysis-related gene (GRG) risk model and nomogram that could aid in better predicting overall survival (OS) in patients with ovarian cancer (OV) has been developed herein. For patients with OV, the risk model appears to be a promising and independent prognostic predictor.

• The Cancer Genome Atlas (TCGA) database was examined to retrieve the expression profiles of GRGs and clinical data of patients with OV.

• Based on nine GRGs (ISG20, CITED2, PYGB, IRS2, ANGPTL4, TGFBI, LHX9, PC, and DDIT4), researchers generated a gene risk signature to predict the survival outcome of patients with OV.

• For OV, particularly high-grade OV, the signature exhibited a good prognostic ability.

• The signature had an independent prognostic value.

• Further, a nomogram was generated by combining the prediction model and clinical factors.