BioGate SERS Chip enables robust metabolite-oriented nanobiotechnological detection of breast cancer margins

Accurate identification of malignant surgical margins remains a major challenge in breast cancer surgery due to the lack of rapid and molecularly specific diagnostic tools capable of operating in complex biological environments. Surface-enhanced Raman spectroscopy (SERS) holds promise for molecular detection; however, its application in tissues is limited by nonspecific macromolecular adsorption, signal instability, and biological screening effects. Here, we present the BioGate SERS Chip, a nanobiotechnological platform designed to enable robust, metabolite-oriented SERS detection by regulating molecular access to plasmonic hotspots. The chip features a hierarchical gold nanoparticle architecture that forms bioselective nanochannels, allowing low-molecular-weight metabolites to access electromagnetic hotspot regions while excluding macromolecules responsible for biofouling and signal suppression. This bioselective hotspot-gating strategy couples plasmonic field confinement with size-selective molecular transport, enabling reliable metabolite sensing directly in complex tissue environments. The BioGate platform exhibited a detection limit of 10⁻¹³ M for molecular probes and enabled reliable identification of malignant signatures in mixed cell populations containing as little as 1% tumor cells. Across spontaneous tumor models, xenograft surgeries, and intraoperative specimens from 50 breast cancer patients representing three major molecular subtypes (HER2+, TNBC, and HR+), the platform rapidly distinguished malignant from benign tissues within minutes using subtype-independent metabolic fingerprints. Integrated metabolomic and transcriptomic analyses further revealed that the characteristic Raman peaks originate from amino acid-related metabolic pathways, providing biochemical interpretability at the nano-bio interface. Together, these results establish the BioGate SERS Chip as a practical nanobiotechnology strategy for rapid metabolite-based intraoperative margin detection and demonstrate how bioengineered plasmonic architectures can enable robust SERS sensing in complex biological tissues.