Cox-LASSO Analysis Reveals a Ten-lncRNA Signature to Predict Outcomes in Patients with High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is one of the most common and lethal gynecological cancers. Long noncoding RNAs (lncRNAs) play important roles and act as prognostic biomarkers of ovarian cancer. However, few studies have focused on the prognostic prediction of lncRNAs solely in HGSOC. In this study, we identified candidate lncRNAs for a prognostic evaluation by examining reannotated lncRNA expression profiles and clinical data of 343 patients with HGSOC from The Cancer Genome Atlas. We built a 10-lncRNA signature using Cox-LASSO regression to predict the prognosis of patients with HGSOC. Trichotomized by the 10-lncRNA signature, high-risk patients experienced significantly shorter disease-free survival and overall survival (OS). Our novel 10-lncRNA signature showed superior predictive capacity compared to the other 2 published lncRNA signature models and clinicopathological parameters. We developed a nomogram for clinical use by integrating the 10-lncRNA signature and two clinicopathological risk factors to predict 1-, 3-, and 5-year OS. In addition, gene set enrichment analysis suggested that the group of high-risk patients was associated with mitotic spindle pathways. This model was also compatible with patients with or without BRCA1/2 mutations and had the potential to predict the response to platinum-based adjuvant chemotherapy. Our findings provide a novel 10-lncRNA prognostic signature for further clinical application in patients with HGSOC and indicate the underlying mechanisms of HGSOC progression.