Abstract
In this paper, we investigated the feasibility of using surface enhanced Raman spectroscopy (SERS) and multivariate analysis method to discriminate liver cancer and nasopharyngeal cancer from healthy volunteers. SERS measurements were performed on serum protein samples from 104 liver cancer patients, 100 nasopharyngeal cancer patients, and 95 healthy volunteers. Two dimensionality reduction methods, principal component analysis (PCA) and partial least square (PLS) were compared, and the results indicated that the performance of PLS is superior to that of PCA. When the number of components was compressed to 3 by PLS, support vector machine (SVM) with a Gaussian radial basis function (RBF) was employed to classify various cancers simultaneously. Based on the PLS-SVM algorithm, high diagnostic accuracies of 95.09% and 90.67% were achieved from the training set and the unknown testing set, respectively. The results of this exploratory work demonstrate that serum protein SERS technology combined with PLS-SVM diagnostic algorithm has great potential for the noninvasive screening of cancer.
Highlights
IntroductionBiopsy remains the gold standard method for cancer diagnosis, but it is invasive and impractical for patient with multiple suspicious lesions
Cancer has become a major public health problem around the world
The results demonstrated that the membrane electrophoresis based surface-enhanced Raman scattering (SERS) technique in conjunction with partial least square (PLS)-support vector machine (SVM) diagnostic algorithm has great potential for simultaneous screening of different types of cancer, which is more convenient for clinical analysis and applications
Summary
Biopsy remains the gold standard method for cancer diagnosis, but it is invasive and impractical for patient with multiple suspicious lesions. Tumor markers screening is useful for the early diagnosis, but the biomarkers test has some limitations in sensitivity and specificity [1]. Surface-enhanced Raman scattering (SERS) has been demonstrated to be a non-invasive and label-free technique and has great potential for biomedical applications and clinical diagnosis [2,3,4,5]. At the early stage of cancer, the biomolecules such as proteins contained in serum will undergo subtle alterations which can be revealed by SERS spectroscopy [6]. It is significant to explore serum-based SERS methods for cancer screening
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