Robust Synthesis of Targeting Glyco-nanoparticles for Surface Enhanced Resonance Raman Based Image-Guided Tumor Surgery.

Abstract

Surface Enhanced Resonance Raman (SERS) is a powerful optical technique, which can help enhance the sensitivity of Raman spectroscopy aided by noble metal nanoparticles (NPs). However, current SERS-NPs are often suboptimal, which can aggregate under physiological conditions with much reduced SERS enhancement. Herein, a robust one-pot method has been developed to synthesize SERS-NPs with more uniform core diameters of 50 nm, which is applicable to both non-resonant and resonant Raman dyes. The resulting SERS-NPs are colloidally stable and bright, enabling NP detection with low-femtomolar sensitivity. An algorithm has been established, which can accurately unmix multiple types of SERS-NPs enabling potential multiplex detection. Furthermore, a new liposome-based approach has been developed to install a targeting carbohydrate ligand, i.e., hyaluronan, onto the SERS-NPs bestowing significantly enhanced binding affinity to its biological receptor CD44 overexpressed on tumor cell surface. The liposomal HA-SERS-NPs enabled visualization of spontaneously developed breast cancer in mice in real time guiding complete surgical removal of the tumor, highlighting the translational potential of these new glyco-SERS-NPs.