Abstract. Patients with ovarian carcinoma are at high risk of tumor recurrence. In the present study, 81 Notch pathway genes were selected to find recurrence-related genes in The Cancer Genome Atlas dataset. A 10-gene signature (FZD4, HES1, PSEN2, JAG2, PPARG, FOS, HEY1, CDC16, MFNG, and EP300) was identified and validated that is associated with recurrence-free survival time, but not with overall survival time, in the TCGA dataset and in other two independent datasets, GSE9891 and GSE30161. This gene signature gave a significant performance in discriminating patients at high risk of recurrence from those at low risk, as measured by the area under the receiver operating characteristic curve. Cox proportional hazards regression analyses demonstrated that the prognostic value of this 10-gene set is independent of other clinical variables in all three datasets. The potential as a biomarker for predicting high-and low-risk subgroups for recurrence in ovarian cancer patients deserves further investigation in prospective patient cohorts in the future.