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Esophageal carcinoma is a common cancer worldwide with a high mortality. Early diagnosis and treatment is critical to reduce the mortality of esophageal cancer patients. In this work, we developed a novel method for detection of esophageal cancer by Raman spectroscopy measurements of extracellular fluid taken from esophageal tissue. The extracellular fluid samples were prepared by sliding the esophageal tissue over an aluminum plate substrate, and then the Raman spectra of the air-drying extracellular fluid samples from 10 esophageal cancer patients and 10 healthy volunteers were successfully recorded. Difference spectrum analysis combined with the assignment of Raman bands indicated that there were subtle but distinct changes between esophageal cancer and normal tissues, which could be associated with the special changes of nucleic acid, protein, lipid and other biological molecules during the process of canceration. To further investigate the diagnostic ability of extracellular fluid taken from human esophageal tissue, the spectral data was combined with multivariate analysis processes. Principal component analysis (PCA), as a spectral dimensionality reduction approach, and in conjunction with the linear discriminant analysis (LDA) algorithm, was employed to identify the esophageal cancer samples, and the diagnostic sensitivity and specificity of 90% and 80%, respectively, could be achieved for classification between normal and cancer groups. Moreover, receiver operating characteristic (ROC) curves further confirmed the effectiveness of the diagnostic algorithm based on PCA-LDA diagnostic algorithm. The results of this exploratory study demonstrated the great potential of esophageal cancer screening based on the analysis of extracellular fluid of tissue, and provided a rapid and label-free tool for clinical cancer detection.
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