Identification of novel immune ferroptosis-related genes associated with clinical and prognostic features in breast cancer.

Breast cancer is the most common form of cancer among women, it is critical to identify potential targets and prognostic biomarkers. Ferroptosis combined with immunity shows a pivotal role in a variety of tumors, which provides new opportunities to detect and treat breast cancer. Our first step was to combine multiple datasets to search for immune ferroptosis-related mRNAs. In the next step, risk signatures were created using Least Absolute Shrinkage and Selection Operator (LASSO). After that, based on the results of the multivariate Cox analysis, we created a prognostic nomogram and validated the model's accuracy. Finally, functional enrichment analysis, single sample gene set enrichment analysis (ssGSEA), immunity and drug sensitivity correlation analysis were performed to explore the possible mechanisms by which these immune ferroptosis associated mRNAs affect BRCA survival. An immune ferroptosis signature (IFRSig) consisting of 5 mRNAs was constructed and showed excellent predictability in the training and validation cohorts. A correlation analysis revealed that clinical characteristics were closely related to risk characteristics. Our nomogram model, which we created by combining risk characteristics and clinical parameters, was proven to be accurate at predicting BRCA prognosis. Further, we divided patients into lowrisk and high-risk groups based on the expression of the model-related genes. Compared with low-risk group, high-risk group showed lower levels of immune cell infiltration, immune-related functions, and immune checkpoints molecules, which may associate with the poor prognosis. The IFRSig could be used to predict overall survival (OS) and treatment response in BRCA patients and could be viewed as an independent prognostic factor. The findings in this study shed light on the role of immune ferroptosis in the progression of BRCA.