Breast cancer (BC) is a prominent cause of cancer incidence and mortality around the world. Disulfidptosis, a type of cell death, can induce tumor cell death. The purpose of this study was to analyze the potential impact of disulfidptosis-related genes (DRGs) on the prognosis and immune infiltration features of BC. Based on DRGs, we conducted an unsupervised clustering analysis on gene expression data of BC in TCGA-BRCA dataset and identified two BC subtypes, cluster1 and cluster2, with cluster1 showing a higher likelihood of favorable survival. Through immune analysis, we found that cluster1 had lower proportions of infiltration in immune-related cells, including aDCs, DCs, NK_cells, Th2_cells, and Treg. Based on the immunophenoscore (IPS) results, we inferred that cluster1 might benefit more from immune checkpoint inhibitors targeting CTLA-4 and PD1. Targeted small molecule prediction results showed that patients with cluster2 BC might respond better to antagonistic small molecule compounds, including clofazimine, lenalidomide, and epigallocatechin. Differentially expressed genes between the two subtypes were found to be enriched in signaling pathways related to steroid hormone biosynthesis, ovarian steroidogenesis, and neutrophil extracellular trap formation, according to enrichment analyses. In conclusion, this study identified BC subtypes based on DRGs so as to help predict patient prognosis and provide valuable tools for guiding clinical management and precise treatment of BC patients.
Keywords: Breast cancer; Disulfidptosis; Immune feature; Immunotherapy; Unsupervised clustering.
© 2023. The Author(s).