Surface-enhanced Raman scattering (SERS) is an ultrasensitive molecular screening technique with greatly enhanced Raman scattering signals from trace amounts of analytes near plasmonic nanostructures. However, research on the development of a sensor that balances signal enhancement, reproducibility, and uniformity has not yet been proposed for practical applications. In this study, we demonstrate the potential of the practical application for detecting or predicting asymptomatic breast cancer from human tears using a portable Raman spectrometer with an identification algorithm based on multivariate statistics. This potentiality was realized through the fabrication of a plasmonic SERS substrate equipped with a well-aligned, gold-decorated, hexagonal-close-packed polystyrene (Au/HCP-PS) nanosphere monolayer that provided femtomole-scale detection, giga-scale enhancement, and <5% relative standard deviation for reliability and reproducibility, regardless of the measuring site. Our results can provide a first step toward developing a noninvasive, real-time screening technology for detecting asymptomatic tumors and preventing tumor recurrence.
Keywords: Au/HCP-PS nanosphere monolayer; breast cancer detection; human tears; surface-enhanced Raman spectroscopy; uniformity.