Abstract
BACKGROUND: Triple-negative breast cancer (TNBC) is characterized by heterogeneity and metabolic reprogramming. Disulfidptosis represents a new category of regulated cell death that is mediated by cystine and cysteine metabolism. However, the underlying mechanism related to the heterogeneity of TNBC disulfidptosis remains unclear. In this study, we aimed to analyze whether disulfidptosis exhibits heterogeneity in TNBC. METHODS: Initial molecular subtyping was performed via K-means clustering. Subsequent subtype characterization included enrichment analysis, differential activity score (DA score) analysis, and in vitro drug sensitivity assays targeting disulfidptosis pathways. The prognostic model was derived through univariate Cox regression followed by least absolute shrinkage and selection operator (LASSO) regression of disulfidptosis-associated genes and metabolites. The prediction model was graphically displayed as a nomogram. RESULTS: Through bioinformatics analysis of a TNBC multiomic dataset (n=465), we divided TNBCs into two disulfidptosis-related subtypes: cluster 1 and cluster 2. Compared with cluster 2, cluster 1 had an activated pentose phosphate pathway, an immunosuppressive microenvironment and a poor prognosis. We further confirmed that TNBC cell lines in cluster 1 were more sensitive to disulfidptosis induced by glucose deprivation or the inhibition of GLUT1. Moreover, the disulfidptosis-associated genes and metabolites-based predictive model demonstrated robust predictive performance. CONCLUSIONS: Taken together, our research demonstrated the heterogeneity of TNBC disulfidptosis and presented a promising treatment strategy for targeting disulfidptosis in TNBC.