Analysis and prediction model of ferroptosis related genes in breast cancer

Background: The prognosis of patients with breast cancer (BRCA) is difficult to predict because of the high degree of heterogeneity and complex etiological factors. Ferroptosis, an iron-dependent, new form of cell death, plays an important role in regulation of tumor growth and progression. The aim of this study was to clarify the predictive value of ferroptosis-related genes in the overall survival of patients with BRCA. Methods: The messenger RNA expression profile and clinical information of patients with BRCA were collected from The Cancer Genome Atlas (TCGA) database. The differences between BRCA and adjacent normal tissues were analyzed, and candidates with differentially expressed ferroptosis-related genes were identified. Through Cox and LASSO analyses, the prognostic genetic characteristics of ferroptosis- related genes were established. Lastly, according to the median risk score, the patients were divided into high-risk and low-risk groups, a nomogram was constructed, and the prediction accuracy was tested. Results: It was determined that the four ferroptosis related genes had a significant difference in survival in BRCA (P<0.05); a prognostic model was constructed based on the four ferroptosis related genes, and the overall survival of patients in the high-risk group was significantly worse (P<0.05). The four-gene nomogram can quantify the contribution of each index to survival, and the calibration chart shows high prediction accuracy. Conclusions: This study constructed four ferroptosis related gene characteristics and nomogram, which can effectively predict the prognosis of BRCA patients and provide new insights for future anti-cancer treatments based on ferroptosis targets.