Abstract It becomes more clear that many deleterious cancer mutations could exhibit a 'gain-of-function' (GOF) behavior. Systematic investigation of such mutations has been lacking and largely overlooked. Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in breast cancer. Alterations in immune-related pathways are common hallmarks of cancer. A comprehensive understanding of how cancer mutations rewire immune signaling networks and functional output in breast cancer is instrumental to realize the full potential of immunotherapy. Here, we systematically interrogated somatic mutations involved in immune signaling that alter immune responses in cancer patients. To do so, we developed a network-based integrative model to prioritize potential immune responder genes. Identified mutations were enriched in essential protein domains and genes identified were associated with responsiveness to multiple immunotherapy modalities. These genes were used to devise an interactome network propagation framework integrated with drug-associated gene signatures to identify potential immunomodulatory drug candidates in breast cancer. Together, our systems-level analysis results help interpret the heterogeneous immune responses among patients and serve as a resource for future functional studies and targeted breast cancer therapeutics. This study is significant and innovative, as it demonstrates that integration of multi-omics data can help identify critical molecular determinants for effective targeted therapeutics. Citation Format: Stephen Yi. Systems-scale characterization of the human immunome in breast cancer for precision medicine [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-09-17.