Construction of a prognostic model based on cuproptosis-related patterns for predicting survival, immune infiltration, and immunotherapy efficacy in breast cancer

Background: Breast cancer is now the most common and lethal malignancy among women worldwide. Cuproptosis is a newly identified copper-dependent programmed cell death and has been found to be closely associated with the development of cancer. However, reports describing cuproptosis regulatory mechanism on breast cancer are still lacking. In this study, we aimed to establish a prognostic model for patients with breast cancer to improve risk stratification. Methods The mRNA expression data was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering was utilized to identify patterns based on cuproptosis-related genes (CRGs). Significant modules and key genes were screened by WGCNA analysis and differentially expressed genes (DEGs) analysis. Cox regression was used to construct prognostic model, and time-dependent receiver-operating characteristic and Kaplan-Meier analyses were used to evaluate its prediction ability. Functional pathways, immune cell infiltration, tumor purity, tumor mutation, tumor heterogeneity and drug sensitivity prediction between the two risk groups were also analyzed. Results Two cuproptosis patterns with distinct prognosis were identified, and the top 21 DEGs that were most significantly and survival associated between the two patterns were screened for constructing our prognostic model. The risk score based on the prognostic model exhibited negative correlation with survival. Enrichment analysis showed that multiple immune related pathways were mainly enriched in the low-risk group. In addition, patients in the low-risk group presented more abundant immune cell infiltration, higher stromal component, lower tumor purity, cancer stemness, tumor mutational burden, and tumor heterogeneity, perhaps associated with their better prognosis. Finally, significant differences of IC50 were also observed between patients in high- and low-risk groups who received chemotherapy and targeted therapy drugs. Conclusions These findings in our study may provide evidence for further research and individualized management of breast cancer.