RESUMO
Background: Ferroptosis is a kind of programmed cell death that is characterized by iron dependence. It differs from apoptosis, necrosis, autophagy, pyroptosis, and other types of cell death. Some studies have found that most of the genes involved in the regulation of ferroptosis or act as markers of ferroptosis are related to the poor prognosis of cancer patients. Methods: This study evaluated the expression, mutation, and copy number variation (CNV) of 60 previously reported ferroptosis genes in breast cancer samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Unsupervised clustering of breast cancer samples with ferroptosis genes was performed, followed by enrichment analysis with Gene Set Variation Analysis (GSVA), mutation display, and correlation analysis of clinical characteristics. Based on the analysis of differences among groups, the ferroptosis-related genes were identified, and the consistent clustering of breast cancer samples was performed. The characteristic genes were screened by stochastic forest algorithm and COX analysis, and a ferroptosis score (ferr.score) model was constructed to evaluate the prognosis of breast cancer patients. Results: Copy number amplification and deletion of ferroptosis genes are common in breast cancer. Breast cancer patients grouped by ferroptosis gene clusters showed significant differences in survival, immune cell infiltration, and enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. The ferroptosis-related differential genes were identified by comparison among clustering groups of ferroptosis gene. Characteristic genes were screened from these ferroptosis-related differential genes to construct the ferr.score model. The scoring model could accurately distinguish and predict the survival prognosis and immunotherapy efficacy in breast cancer patients. Conclusions: Ferroptosis plays an important role in the occurrence and development of tumors. According to the ferr.score model, the breast cancer samples can be divided into two groups with significantly different prognoses. These results provide novel insights and ideas for immunotherapy in breast cancer patients.
