Spectral analysis of human saliva for detection of lung cancer using surface-enhanced Raman spectroscopy

Abstract

Surface-enhanced Raman spectroscopy (SERS) has been shown to be able to detect low-concentration biofluids. Saliva SERS readings of 21 lung cancer patients and 20 normal people were measured and differentiated. Most of the Raman peak intensities decrease for lung cancer patients compared with that of normal people. Those peaks were assigned to proteins and nucleic acids, which indicate a corresponding decrease of those substances in saliva. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to reduce and discriminate between the two groups of data, and the study resulted in accuracy, sensitivity, and specificity being 80%, 78%, and 83%, respectively. In conclusion, SERS of saliva showed the ability to predict lung cancer in our experiment.