Identification of different tumor states in nasopharyngeal cancer using surface-enhanced Raman spectroscopy combined with Lasso-PLS-DA algorithm. Issue 10 (19th January 2016)

• Record Type: Journal Article
• Authors: Chen, Guannan; Lin, Xueliang; Lin, Duo; Ge, Xiaosong; Feng, Shangyuan; Pan, Jianji; Lin, Juqiang; Huang, Zufang; Huang, Xi; Chen, Rong
• Is Part Of: RSC advances. Volume 6:Issue 10(2016)
• Page Start: 7760
• Page End: 7764
• Publication Date: 2016-01-19
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/c5ra24438b
• Languages: English
• ISSNs: 2046-2069

Abstract

Abstract : Identification of different states in cancer is of vital importance for cancer treatment and management. Abstract : Identification of different states in cancer is of vital importance for cancer treatment and management. A powerful diagnostic algorithm based on Lasso-partial least squares-discriminant analysis (Lasso-PLS-DA) was developed here for improving blood surface-enhanced Raman spectroscopy (SERS) analysis, with the aim to classify different states in nasopharyngeal cancer (NPC). A total of 160 blood plasma samples were collected for this study, obtained from 60 normal volunteers, 25 T1 stage cancer and 75 T2–T4 stages cancer patients. Results show that a diagnostic sensitivity of 68% and a specificity of 84.0% can be achieved for separating T2–T4 stage from T1 stage cancer, which had a 20% improvement in diagnostic specificity compared with the previous work. This exploratory study demonstrates that the Lasso-PLS-DA can be integrated with blood SERS analysis as a promising clinical complement for different T stages detection in NPC.