3D Plasmonic Multilayered Gold Nanoarchitecture for Multiple Cancer Diagnosis Using SERS and Machine Learning-Assisted Liquid-Phase Human Urine Sensing

Abstract

To develop onsite applicable cancer diagnosis technologies, a noninvasive human biofluid detection method with high sensitivity and specificity is required, available for classifying cancer from the normal group. Herein, a clinical assay platform of a 96-well plate is developed with three-dimensional plasmonic Au nanolaminate/Au nanoparticle/Au nanosponge (3D AuNL/AuNP/AuS) to generate volumetric hotspots in the space. The nanostructure has been demonstrated for liquid-phase human urine detection, which proves more effective for molecular detection in the presence of Brownian motion. Subsequently, cancer metabolite candidates are investigated to verify the metabolic alternation of multicancer, including pancreatic, prostate, lung, and colorectal cancers, simultaneously classifying them into five different groups, including normal, using machine-learning methods. The integration of nanomaterials with the conventional clinical platform provides rapid and high-throughput multicancer diagnostic system and opens a new era for noninvasive diseases diagnosis using clinical human biofluids.