Development and validation of stable ferroptosis‐ and pyroptosis‐related signatures in predicting prognosis and immune status in breast cancer

Abstract

AbstractTo develop and validate the predictive effects of stable ferroptosis‐ and pyroptosis‐related features on the prognosis and immune status of breast cancer (BC). We retrieved as well as downloaded ferroptosis‐ and pyroptosis‐related genes from the FerrDb and GeneCards databases. The minimum absolute contraction and selection operator (LASSO) algorithm in The Cancer Genome Atlas (TCGA) was used to construct a prognostic classifier combining the above two types of prognostic genes with differential expression, and the Integrated Gene Expression (GEO) dataset was used for validation. Seventeen genes presented a close association with BC prognosis. Thirteen key prognostic genes with prognostic value were considered to construct a new expression signature for classifying patients with BC into high‐ and low‐risk groups. Kaplan–Meier analysis revealed a worse prognosis in the high‐risk group. The receiver operating characteristic (ROC) curve and multivariate Cox regression analysis identified its predictive and independent features. Immune profile analysis showed that immunosuppressive cells were upregulated in the high‐risk group, and this risk model was related to immunosuppressive molecules. We successfully constructed combined features of ferroptosis and pyroptosis in BC that are closely related to prognosis, clinicopathological and immune features, chemotherapy efficacy and immunosuppressive molecules. However, further experimental studies are required to verify these findings.