Development and validation of subtype and risk models for kinase-related genes as novel prognostic features in breast cancer

BACKGROUND: Protein kinases are essential regulators of cellular signaling pathways and are deeply involved in breast cancer (BC) progression. This study aimed to identify BC molecular subtypes and construct a prognostic model based on kinase-related genes (KRGs). METHODS: pRRophetic) were performed between risk groups. RESULTS: Two distinct molecular subtypes were identified based on KRG expression. A 7-gene prognostic model reliably estimated survival in both the training cohort and external validation datasets. Patients were stratified into high- and low-risk groups, with the low-risk group showing significantly improved survival, elevated immune cell infiltration, and higher immune scores. These patients also exhibited more robust responses to a range of anticancer drugs, and signature genes were correlated with therapeutic response, indicating their potential as targets. CONCLUSION: We established a KRG-based BC molecular subtyping and prognostic model that effectively stratifies patients by survival risk. This model may improve diagnostic accuracy and support the identification of novel therapeutic targets in future clinical practice.