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Breast cancer encompasses molecularly distinct subtypes with divergent oncogenic dependencies, each amenable to precision therapeutic intervention. Over the past decade, clinically meaningful advances have reshaped breast cancer management: antibody–drug conjugates (ADCs) have expanded actionable HER2 expression thresholds to include HER2-low and HER2-ultralow populations; cyclin-dependent kinase (CDK) 4/6 inhibitors have become standard-of-care in hormone receptor-positive disease; and immune checkpoint blockade has established durable responses in a defined subset of triple-negative breast cancer (TNBC). Nevertheless, therapeutic resistance remains the central unresolved obstacle to durable benefit. Here, we synthesize current evidence on the signaling architecture underlying targeted therapy across breast cancer subtypes and propose a four-layer network topology model of resistance integrating: (i) canonical pathway reactivation; (ii) receptor tyrosine kinase (RTK) reprogramming; (iii) non-coding RNA (ncRNA) regulatory circuits; and (iv) epigenetic plasticity coupled with tumor microenvironment (TME) co-evolution. We explicitly stratify the discussed mechanisms into three evidence tiers—clinically actionable, plausibly translational, and exploratory—to avoid conflating preclinical observations with validated biomarkers. We critically evaluate FDA-approved and emerging agents within this framework, identify knowledge gaps, and outline future directions—including liquid biopsy-guided adaptive therapy, multi-omic resistance profiling, and biologically rational combination strategies—together with their feasibility constraints related to toxicity, sequencing, cost, and biomarker validation.
Wang et al. (Wed,) studied this question.