A novel ferroptosis-related long noncoding RNA signature for relapse free survival prediction in patients with breast cancer

Ferroptosis is the process of cell death dependent on iron. Growing evidence suggests that ferroptosis plays vital roles in the biological process of many cancers. However, just a small number of ferroptosis-related lncRNAs have been explored in depth. Ferroptosis-related lncRNAs in breast cancer (BC) were identified by co-expression analysis based on The Cancer Genome Atlas database (TCGA). The whole set was divided into a training set and a test set with a 1:1 ratio. Univariate Cox regression and LASSO analyses were performed to establish a signature in the 3 sets. Kaplan-Meier analysis and receiver operating characteristic (ROC) for the 3 sets validated the effectiveness and robustness of the signature. Besides, we also explore the relationship between this and clinical characteristics, immune cell infiltration and tumor microenvironment. Meanwhile, the nomogram was drawn by screening indicators of independent recurrent prediction. Finally, we evaluated the relationships between the signature and tumor microenvironment. We identified 391 ferroptosis-related lncRNAs and constructed a 5 lncRNAs-based signature in the training, test, and whole sets, stratifying patients into high-risk and low-risk groups. According to survival analysis, patients in the high-risk groups had worse relapse free survival (RFS) compared to the low risk-groups. The ROC curves indicated that the recurrent signature had a promising predictive capability for BC patients. Moreover, an independent factors-based nomogram model could offer the quantitative prediction and net benefit for the recurrence of BC patients. Finally, the microenvironment, including tumor mutational burden (TMB), immune cell functions and immune checkpoints, showed big differences between the 2 groups. The 5 ferroptosis-related lncRNAs and their signature might be novel promising biomarkers and immunotherapy targets for patients with BC.