Development of a five-gene signature as a novel prognostic marker in ovarian cancer

 Rui Wang, Xiang-Hua Ye, Xiao-Lei Zhao, Jun-Li Liu, Chun-Yan Zhang

Abstract:

The prognosis of ovarian cancer (OC) remains poor. Thus, the present study aims to identify independently prognostic factor in patients with OC. OC gene expression study GSE26712 and TCGA-OV were included in the study. Prognosis associated differentially expressed genes (DEGs) between normal ovarian tissue and OC were identified. LASSO Cox proportional hazards regression model was conducted and a prognostic signature was constructed based on these DEGs. The predictive ability of the signature was analyzed in the training set and test set. The prognosis performance of the signature was compared with CA-125 and HE4. Gene set enrichment analysis (GSEA) was conducted to identify relevant mechanism. 332 DEGs were identified, of which 64 DEGs were significantly correlated with the overall survival (OS) of OC patients, and 5 DEGs (IGF2, PEG3, DCN, LYPD1 and RARRES1) were applied to build a 5-gene signature. Patients in the 5-gene signature low risk group had significantly better OS compared with those in the 5-gene high risk group (P=0.0004) in the training set. Similar results were found in the test set, and the signature was also an independent prognostic factor. The prognosis performance of the 5-gene signature was significantly better than that of CA-125 and HE4. GSEA suggested that OC samples in the 5-gene high risk group were significantly enriched in WNT/β-catenin signaling and epithelial-mesenchymal transition. We developed and validated a 5-gene signature that might be used as an independent prognostic factor in patients with OS.