Identification of different tumor states in nasopharyngeal cancer using surface-enhanced Raman spectroscopy combined with Lasso-PLS-DA algorithm

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) analysi...

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Bibliographic Details
Published in:RSC advances 2016-01, Vol.6 (1), p.776-7764
Main Authors: Chen, Guannan, Lin, Xueliang, Lin, Duo, Ge, Xiaosong, Feng, Shangyuan, Pan, Jianji, Lin, Juqiang, Huang, Zufang, Huang, Xi, Chen, Rong
Format: Article
Language:English
Subjects:
Algorithms
Blood
Cancer
Classification
Complement
Diagnostic systems
Least squares method
Raman spectroscopy
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Summary: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. Identification of different states in cancer is of vital importance for cancer treatment and management.
ISSN:2046-2069
2046-2069
DOI:10.1039/c5ra24438b