Application of surface-enhanced Raman spectroscopy to human serum for diagnosing liver cancer.

[Display omitted] • Surface-enhanced Raman spectroscopy (SERS) for liver cancer diagnosis. • Ag@SiO 2 nanoparticles were selected as the SERS-enhanced substrate. • OPLS-DA combined with standard normal variate analysis of the SERS profiles. • The analysis model exhibited high sensitivity, accuracy, and specificity. This study investigates the application of surface-enhanced Raman spectroscopy (SERS) in the diagnosis of liver cancer using Ag@SiO 2 nanoparticles as SERS substrates. A SERS test was conducted on serum samples obtained from patients with liver cancer and healthy individuals. After repeated several times experiments, it was found that the best SERS spectrum was obtained when the volume ratio of serum to deionized water was 1:2. Moreover, data preprocessing was performed on the tested SERS spectrum, and the preprocessed spectral data were combined with principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) for further analysis to classify the serum samples of patients with liver cancer and healthy individuals. The results showed that the classification effect of standard normal variate spectral data combined with the OPLS-DA was the best for the serum samples, with a classification accuracy of 97.98%, sensitivity of 97.14%, and specificity of 98.44%. Therefore, the SERS technology can be developed as a favorable method for the accurate diagnosis of liver cancer in the future. [ABSTRACT FROM AUTHOR]