Development and validation of ferroptosis-related lncRNA features to improve prognosis prediction in ovarian cancer

Abstract Background: Long non-coding RNAs (lncRNAs) are thought to be associated with several processes during cancer development and have been shown to be involved in the regulation of ferroptosis. Ovarian cancer is highly malignant tumour with a poor prognosis. The identification biomarkers with prognostic value in ovarian cancer may improve patient outcomes and can help to elucidate potential future therapeutic targets. Methods: We report differential expression of 187 ferroptosis-related lncRNAs in normal and ovarian cancer tissue. Using univariate and multivariable Cox regression analysis, we identified four lncRNAs that were strongly associated with prognosis. We constructed a prognostic risk score based on these four lncRNAs which was effectively able to distinguish between low- and high-risk OC patients based on survival time. Univariate and multivariable Cox regression analyses and time-related receiver operating characteristic curve analyses revealed that this risk score represented an independent prognostic factor in patients with ovarian cancer. And qRT-PCR was performed to further validate the reliability of the prognostic model. For clinical implementation, we developed a nomogram based on the prognostic feature and patient age. Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the four ferroptosis-related lncRNAs were related to tumour immunity. Further immune infiltration analysis was performed to identify multiple immune cells associated with ferroptosis. Conclusions: we identify four novel ferroptosis-related lncRNAs as predictors of ovarian cancer prognosis and they could be applicable in clinical ferroptosis-related targeted therapies for ovarian cancer.