Multivariate Statistical Analysis of Serum from Breast Cancer Patients Using Surface Enhanced Raman Spectrum

The present paper studied surface-enhanced Raman spectra (SERS) of serum from breast cancer using chemometrics methods of principal component analysis (PCA) and linear discriminant analysis (LDA) respectively. Firstly, the structure of peptidyl backbone and side chain of protein, which is destroyed in the serum from breast cancer, is explained. Meanwhile the structure of lipid and also the environment of glucid are changed. Then, we studied the SERS of 18 serum samples from breast cancer patients who were clinically diagnosed and 20 serum samples from healthy volunteers control using the method above mentioned. It was showed that the method of PCA cannot discriminate the two groups completely, but after using the method of LDA the analysis result is satisfactory.