Breast cancer classification has been in the focus of numerous large worldwide efforts, analyzing the molecular basis of breast cancer subtypes, aiming to associate them with clinical outcome and improve the current diagnostic routine. Genomic and transcriptomic profiles of breast cancer have been well established, however the proteomic contribution to these profiles is yet to be elucidated. In this work, we examined inter-tumor heterogeneity by performing a mass-spectrometry (MS)-based proteomic analysis of more than 130 clinical breast samples originating from three breast cancer subtypes and healthy tissue. Unsupervised analysis identified four proteomic clusters, among them one that represents a novel luminal subtype characterized by increased cancer signaling. This subtype was further validated using an independent protein-based dataset, but not in two independent transcriptome cohorts. Altogether, our results demonstrate the importance of deep proteomic analysis, which may affect cancer treatment decision making.