Abstract Background: Dephosphorylation regulates key signaling pathways in breast cancer, influencing tumor progression, metastasis, and treatment resistance. However, the role of dephosphorylation-related genes (DRGs) in breast cancer (BRCA) and their impact on patient outcomes has not been fully explored. This research sought to explore the prognostic relevance of NRGs in BRCA through the integration of bulk RNA sequencing (bulk RNA-seq) and single-cell RNA sequencing (scRNA-seq) data. Methods: The bulk RNA-seq and scRNA-seq data for BRCA, along with DRGs, were sourced from public databases. Utilizing differential expression analysis, Cox regression analysis, and a machine learning algorithm, this study identified prognostic genes. Leveraging prognostic genes, a risk model was crafted, further dichotomizing BRCA patients into two distinct risk groups. Moreover, enriched pathways and the immune microenvironment of the different risk groups were explored. Subsequent analyses involved examining the expression of prognostic genes at the single-cell level, identifying key cells, and conducting pseudo-time analysis. Results: NOS1, CTNNA2, ACTN2, and KRT5 were identified as prognostic genes in this study. The constructed risk model demonstrated robust predictive ability, with area under the curve (AUC) values surpassing 0.60 at 1-, 2-, and 3-year survival. Subsequently, the functional pathways were related to cellular functions and immune response (such as "apoptosis" and "chemokine signaling pathway"). Moreover, there were six types of immune infiltrating cells that showed significant differences between two risk groups. Additionally, scRNA-seq analysis identified eight cell types, with smooth muscle cells as the key cells, and the expression of KRT5 showed dynamic changes during the different stages of smooth muscle cells differentiation. Conclusion: NOS1, CTNNA2, ACTN2, and KRT5 were identified as prognostic genes for BRCA, highlighting the crucial prognostic role of NRGs in BRCA, which could be particularly important for identifying targeted therapeutic strategies. Citation Format: C. Wei, L. Mengbo, Z. Hui. Revealing the prognostic significance of dephosphorylation-related genes in breast cancer: comprehensive insightsbased on bulk RNAsequencingand single-cell RNA sequencingdata abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-02-04.
Wei et al. (Tue,) studied this question.