Identification of a ferroptosis-related long non-coding RNA signature for prognosis prediction of ovarian cancer

Abstract

Ovarian cancer is one of the deadliest malignant tumors. Ferroptosis is closely related to various cancers, including ovarian cancer, but the genes involved in regulating ferroptosis in ovarian cancer are still unclear. The aim of this study is to construct a long non-coding RNA (lncRNA) signature related to ferroptosis and evaluate its relationship with the prognosis and clinicopathological characteristics of patients with ovarian cancer. In this study, a prognostic risk model comprising 18 lncRNAs related to ferroptosis was obtained. Compared to the low-risk group, the high-risk group based on the FerRLSig score had significantly poorer overall survival (P < 0.001). The receiver operating characteristics curve supported the accuracy of the model, established a prognostic nomogram combining FerRLSig and clinical characteristics, and showed a good prognosis and survival risk stratification predictive power. In addition, Gene Set Enrichment Analysis (GSEA) showed that FerRLSig was involved in many malignant tumor-related immunomodulatory pathways. Based on the risk model, we found that immune status and immunotherapy, chemotherapy, and targeted therapy were significantly different between the high-risk and low-risk groups. This study provided a more in-depth understanding of the molecular and signaling pathways of ferroptosis in ovarian cancer and showed the impact of tumor microenvironment on ovarian cancer, as well as provided a prognostic model for ovarian cancer patients to guide the clinical treatment of ovarian cancer.