Bispecific Antibodies in Breast Cancer Immunotherapy: Mechanisms, Advances, and Translational Challenges.

Breast cancer remains a leading cause of cancer-related mortality despite advances in targeted therapies and immune checkpoint inhibitors (ICIs). While ICIs have reshaped therapeutic paradigms in multiple solid tumors, their clinical efficacy in breast cancer is predominantly restricted to triple-negative breast cancer (TNBC), underscoring the necessity for innovative immunotherapeutic modalities with broader applicability. Bispecific antibodies (BsAbs) are engineered molecules capable of simultaneously engaging tumor-associated antigens (TAAs) such as EGFR, EpCAM, Trop-2, CEACAM5, MUC1, and PSMA, in addition to B7-H4, HER2, and PD-L1, alongside immune effector cells, primarily CD3+ T lymphocytes. This dual targeting promotes the formation of a cytolytic immunological synapse, leading to T-cell activation, proliferation, and targeted tumor cell lysis via granzyme/perforin pathways. Advances in BsAb design-including optimization of affinity constants, valency, Fc engineering to modulate effector functions, and molecular formats (e.g., BiTEs, DARTs, tandem scFvs)-have improved tumor penetration, pharmacokinetics, and reduced off-target toxicity. Preclinical and early-phase clinical data demonstrate robust antitumor activity of BsAbs, both as monotherapy and in synergistic combinations with chemotherapy, targeted agents, or ICIs, potentially overcoming tumor microenvironment-mediated immunosuppression and immune escape mechanisms. Major challenges include heterogeneity and temporal variability of TAA expression, cytokine release syndrome (CRS) mitigation strategies, pharmacodynamic optimization, and delivery methods to maximize tumor bioavailability while limiting systemic toxicity. This review details the molecular mechanisms, preclinical evidence, clinical trial outcomes, and translational challenges for BsAbs in breast cancer, highlighting their transformative potential in expanding immunotherapeutic efficacy beyond current limitations.