Background <p>Breast cancer (BC) represents one of the most prevalent malignancies among women worldwide. Despite substantial advances in diagnostic and therapeutic modalities and pharmacological interventions in recent years, the accurate assessment of prognosis continues to pose formidable challenges. Exosomes exert pivotal roles in tumorigenesis, tumor progression, and immune modulation, with exosome-related mRNAs emerging as promising novel prognostic biomarkers. Nevertheless, the role of exosome-related mRNA in BC oncogenesis, progression, and prognostic prediction warrants further extensive investigation.</p> Methods <p>The study constructed the exosome-related signature and validated the results in the Gene Expression Omnibus database (GSE9893). Candidate genes were selected based on differential expression, univariate Cox, and LASSO regression to build a prognostic risk model. Its predictive accuracy was evaluated using Kaplan–Meier (K-M) survival curves and time-dependent ROC analysis. Furthermore, the ESTIMATE and CIBERSORT algorithms were employed to elucidate the association between the prognostic risk signature and tumor immune microenvironment (TIME), alongside comparative analyses of HLA gene and immune checkpoint expression differences. GSEA was subsequently conducted to explore the potential biological pathways associated with the prognostic risk signature and individual signature genes. In addition, qRT-PCR was performed in breast cancer cell lines to experimentally validate the expression of signature genes. Finally, a nomogram was developed by combining risk scores with clinical features.</p> Results <p>Ultimately, four exosome-related mRNAs were identified to construct a prognostic risk signature. In the TCGA cohort, this signature effectively stratified patients into high- and low-risk groups with respect to overall survival (OS), as evidenced by robust predictive performance in ROC analysis. In the GEO validation cohort (GSE9893), results aligned with the training cohor. Immunological analyses showed the risk score’s association with the tumor microenvironment (TME), encompassing stromal scores, immune cell abundance, and HLA gene and immune checkpoint levels. In vitro qRT-PCR validation demonstrated expression trends consistent with the computational predictions. The nomogram integrating clinical characteristics demonstrated calibration and substantial clinical utility.</p> Conclusion <p>This study innovatively developed a BC prognostic risk signature based on exosome-related mRNAs, which not only effectively predicts patient survival but also elucidates its intimate association with the TIME. This signature offers novel insights and substantial clinical utility for personalized prognostic evaluation and treatment decision-making in BC patients.</p>