Acquired resistance limits the durability of precision therapies in breast cancer, necessitating novel modalities that eliminate resistance-driving proteins beyond occupancy-driven inhibition. Proteolysis-targeting chimeras (PROTACs) operate via event-driven catalytic degradation, offering unique advantages against binding-pocket mutations, compensatory network rewiring, and historically “undruggable” transcription factors and scaffolding proteins. The 2026 U.S. Food and Drug Administration approval of vepdegestrant of estrogen receptor 1-mutant advanced breast cancer provides definitive clinical validation of this degradation-based paradigm. In this review, we propose two complementary translational frameworks: a clinical-pharmacological classification (Type I–III) that aligns resistance mechanisms with specific degrader advantages, and a spatially informed decision matrix linking subcellular target localization to appropriate degradation platforms—conventional PROTACs for nuclear/cytosolic proteins, lysosome-targeting chimeras for membrane-associated targets, and engineered exosomes for extracellular resistance transmission. We further outline a four-step clinical decision framework encompassing biomarker-guided patient selection via liquid biopsy, technology matching based on target localization, pharmacodynamic monitoring via serial circulating tumour DNA analysis, and proactive management of degrader-acquired resistance through E3 ligase switching or rational combination strategies. Despite persistent pharmacokinetic challenges and limited E3 ligase diversity, emerging innovations in delivery technologies and dual-ligase recruitment hold promise for translating mechanistic advantages into durable clinical benefit across all breast cancer subtypes. By integrating a clinical-pharmacological classification with a spatially informed decision matrix, the present review provides a systematic, mechanism-driven framework to guide the rational deployment of targeted protein degradation strategies against acquired resistance in breast cancer.
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Tang et al. (2026) studied this question.
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