Abstract
Breast cancer is a malignant tumor of breast epithelial tissue. Early diagnosis and postoperative evaluation of breast cancer are critical to improve the survival rate. The current main screening methods are mammography and computerized tomography (CT), however, these methods suffer from false positives, over-diagnosis and radiation risk. Herein, unlabeled surface-enhanced Raman spectroscopy (SERS) technology combined with silver nanoparticles that was used to measure and analyze peripheral serum protein samples from patients of breast cancer for preoperation, postoperation and normal subjects. Results showed that there were significant differences in the serum protein SERS spectra among three groups due to changes in certain biochemical compositions related to breast cancer transformation. Moreover, diagnostic sensitivity, based on principal component analysis combined with linear discriminant analysis (PCA-LDA) for pre-surgery versus post-surgery, post-surgery versus normal and pre-surgery versus normal were 96.7%, 53.3%, and 100%, respectively, and the diagnostic specificities were 96.7%, 46.7%, and 96.7%, respectively. Therefore, serum protein SERS combined with PCA-LDA analysis holds promising potential as a novel strategy for early screening and postoperative evaluation of breast cancer.
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