Abstract

The tumor microenvironment (TME) significantly influences disease progression through immune infiltration, while ferroptosis, a recently discovered cell death mechanism, plays a crucial role in tumor suppression. However, its role in breast cancer is not clear. In this study, we analyzed bulk RNA and single-cell RNA sequencing data from 1217 samples, including 1104 breast cancer patients and 113 controls, to identify ferroptosis-related genes (FRGs) and construct a prognostic model. Using univariate cox regression, LASSO regression, and multivariate cox regression analysis, we discovered 21 FRGs and 3 TME-related immune cell types with prognostic value. Dimensionality reduction clustering and visualization were performed using the UMAP method, while the immune infiltration process was calculated with the TIP online tool. We employed GSEA enrichment analysis, WGCNA clustering analysis, and correlation analysis to examine functional differences, and the mutation analysis of the best and worst prognosis groups was conducted using the maftools package. Our findings revealed that knocking down the expression of the hub gene SLC39A7 significantly impacted cancer cell apoptosis and combining ferroptosis and TME scores yielded high prognostic power. Epithelial cells and B cells exhibited higher ferroptosis scores, which were independently associated with immune checkpoint blockade (ICB) response and ICB gene expression. This study provides a foundation for further exploration of the relationship between ferroptosis and ICB response in breast cancer. In conclusion, we developed a prognostic model based on ferroptosis and infiltrated immune cells that effectively stratified breast cancer patients and demonstrated the role of SLC39A7 in breast cancer pathogenesis through the regulation of apoptosis.

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