Noninvasive detection of nasopharyngeal carcinoma based on saliva proteins using surface-enhanced Raman spectroscopy

• Published in: Journal of biomedical optics Vol. 22; no. 10; p. 105004
• Main Authors: Lin, Xueliang, Lin, Duo, Ge, Xiaosong, Qiu, Sufang, Feng, Shangyuan, Chen, Rong
• Format: Journal Article
• Language: English
• Published: United States Society of Photo-Optical Instrumentation Engineers 01.10.2017
• Subjects: Adult; Algorithms; Carcinoma - diagnostic imaging; Cellulose - analogs & derivatives; Cellulose - chemistry; Colloids - chemistry; Discriminant Analysis; Female; Healthy Volunteers; Humans; Linear Models; Male; Membranes, Artificial; Middle Aged; Multivariate Analysis; Nasopharyngeal Carcinoma; Nasopharyngeal Neoplasms - diagnostic imaging; Nose Neoplasms - diagnostic imaging; Principal Component Analysis; Reproducibility of Results; Saliva - chemistry; Salivary Proteins and Peptides - chemistry; Sensitivity and Specificity; Silver - chemistry; Spectrum Analysis, Raman; nasopharyngeal carcinoma detection; saliva protein; surface-enhanced Raman spectroscopy; principal component analysis combined with linear discriminant analysis
• ISSN: 1083-3668; 1560-2281; 1560-2281
• DOI: 10.1117/1.JBO.22.10.105004

The present study evaluated the capability of saliva analysis combining membrane protein purification with surface-enhanced Raman spectroscopy (SERS) for noninvasive detection of nasopharyngeal carcinoma (NPC). A rapid and convenient protein purification method based on cellulose acetate membrane was developed. A total of 659 high-quality SERS spectra were acquired from purified proteins extracted from the saliva samples of 170 patients with pathologically confirmed NPC and 71 healthy volunteers. Spectral analysis of those saliva protein SERS spectra revealed specific changes in some biochemical compositions, which were possibly associated with NPC transformation. Furthermore, principal component analysis combined with linear discriminant analysis (PCA-LDA) was utilized to analyze and classify the saliva protein SERS spectra from NPC and healthy subjects. Diagnostic sensitivity of 70.7%, specificity of 70.3%, and diagnostic accuracy of 70.5% could be achieved by PCA-LDA for NPC identification. These results show that this assay based on saliva protein SERS analysis holds promising potential for developing a rapid, noninvasive, and convenient clinical tool for NPC screening.