A Novel Six-Gene Signature for Prognosis Prediction in Ovarian Cancer - Pan, Xin; Ma, Xiaoxin (Frontiers in Genetics, 2020)
Ovarian cancer (OC) is the most malignant tumor in the female reproductive tract. Although abundant molecular biomarkers have been identified, a robust and accurate gene expression signature is still essential to assist oncologists in evaluating the prognosis of OC patients. In this study, samples from 367 patients in The Cancer Genome Atlas (TCGA) database were subjected to mRNA expression profiling. Then, we used gene set enrichment analysis (GSEA) to screen genes correlated with epithelial-mesenchymal transition (EMT) and assess their prognostic power with a Cox proportional regression model. Six genes (TGFBI, SFRP1, COL16A1, THY1, PPIB, BGN) associated with overall survival (OS) were used to construct a risk assessment model, after which the patients were divided into high-risk and low-risk groups. The six-gene signature was an independent prognostic biomarker of OS for OC patients based on multivariate Cox regression analysis. In addition, the six-gene model was validated with samples from the Gene Expression Omnibus (GEO) database. In summary, we established a six-gene signature relevant to the prognosis of OC, which might become a therapeutic tool with clinical applications in the future.