Plasmonic Glyco-Nanoparticles for Single-Test Multiplexed Detection and Differentiation of Cancer Cells

Abstract

Precise cancer detection and classification require tools that can readily differentiate normal vs cancerous cells, as well as various types of cancer cells. Herein, we present a plasmonic glyco-nanoparticle (PlasGlyNP) system functionalized with six types of carbohydrates including mannose, galactose, fucose, N-acetyl glucosamine, sialic acid, and hyaluronan, to enable multiplex cancer detection and differentiation via surface-enhanced Raman scattering (SERS). The particles were colloidally stable under the physiological condition and a variety of stressor conditions. The carbohydrates immobilized on the particles retained their biological recognition selectivities and the particles could sensitively detect carbohydrate binding proteins with the limit of detection down to pM range using SERS. Importantly, a 7-plex PlasGlyNP array generates distinct SERS signatures from a single incubation and measurement per cell type, allowing rapid differentiation of a panel of twelve cell lines, including normal cells and cancer cells with varying metastatic potential, without requiring prior knowledge of specific receptor expression. By enabling simultaneous profiling of multiple glycan–receptor interactions in a single assay workflow, the PlasGlyNP platform provides a versatile tool for interrogating glycan binding profiles relevant to cancer differentiation and detection.