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Background Breast cancer (BC) is a molecularly and clinically heterogeneous disease, representing the leading cause of cancer-related mortality in women worldwide. While conventional chemo- and radiotherapies remain standard treatments, immunotherapy shows promise for a subset of patients; however, recurrence and metastasis remain significant challenges. This heterogeneity complicates accurate survival prediction, as patients with similar diagnoses often exhibit varied therapeutic responses. In this study, we applied multiplexed spatial proteomics to paired breast cancer and adjacent normal tissues to characterize immune cell populations and biomarkers within the tumor microenvironment (TME).Methods Using the Cell DIVE Multiplex Imaging Solution, which enables iterative staining and dye inactivation for probing dozens of biomarkers on whole tissue sections, we systematically mapped the TME to identify features potentially predictive of immunotherapy response. FFPE (Formalin-Fixed Paraffin-Embedded) tissue slide was obtained from QUICKARRAYS, Inc; BRC483 and imaged on the Cell DIVE imager using four channels plus DAPI, with automatic AF removal, corrections, and stitching. Fully stitched images were analyzed using Aivia 15.Results The flexibility of Cell DIVE, combined with a portfolio of rigorously validated Cell Signaling Technology® (CST®) antibody conjugates allowed precise immune cell phenotyping and biomarker detection within the TME. Integration of AI-powered image analysis using Aivia facilitated spatially resolved tissue characterization. Specifically, we identified differences in the morphology, abundance, co-expression patterns, and spatial positioning of various cell types and components of the TME in invasive ductal carcinoma and its adjacent uninvolved breast tissue across different grades and stages of tumors. We found unique expression patterns for tumor growth, metabolic, stromal, and stem-cell associated markers, as well as immune cell subtypes. We also observed diverse spatial distributions of cell types in relation to the tumor, indicating a heterogeneous tumor-immune landscape across different tumor grades and stages.Conclusions Our findings demonstrate that multiplexed spatial proteomics offers a powerful approach to decipher TME complexity and supports the advancement of precision immuno-oncology strategies in breast cancer.