Diagnosis of Esophageal Tissue Based on Surface-Enhanced Raman Spectroscopy

Abstract

Gold nanoparticle based surface-enhanced Raman spectroscopy (SERS) was first applied to analyze esophageal cancer tissue and normal tissue in this paper. SERS measurements were performed on 62 tissue samples (31 esophageal carcinoma tissues and 31 normal tissues) obtained from 31 patients. Principal components analysis (PCA) combined with linear discriminant analysis (LDA) were employed to analyze and classify the tissue SERS spectra acquired from esophageal cancer and normal tissues. The diagnostic algorithms based on PCA-LDA yielded high diagnostic sensitivity (90.3%) and specificity (90.3%). Receiver operating characteristic (ROC) curve was employed to confirm the effectiveness of PCA-LDA multivariate analysis. Tentative assignments of the tissue SERS spectra suggested some changes in protein structure, a decrease in the relative amounts of phospholipids, an increase in the percentage of tryptophan, histone, tyrosine and phenylalanine contents in tumor tissue as compared to that of normal subject. The results from our exploratory study demonstrated that gold nanoparticle based tissue SERS spectroscopy in conjunction with PCA-LDA analysis can differentiate esophageal cancer from normal esophageal tissue samples with high accuracy. Tissue SERS spectroscopy may be a potentially clinically useful tool for the early diagnosis of esophageal cancer.