During the development of tumors, some protein molecules, secreted proteins, are secreted, which are closely related to the proliferation, invasion and metastasis of malignant tumor cells. Therefore, the study of tumor cell secreted proteins not only helps to understand the molecular mechanism of tumorigenesis and development, but also helps to find new tumor markers for early screening of cancer and monitoring of high-risk populations. Surface-enhanced Raman spectroscopy (SERS) and partial least squares-support vector machine (PLS-SVM) data processing methods were used to characterize secreted proteins from human liver cancer cells HepG2 and normal human liver cells LO2 cells in this paper. The discriminative sensitivity and specificity of secreted proteins reach 100%, respectively. These results show that SERS technology combined with PLS-SVM data processing method can effectively distinguish normal cells from cancer cells and provide new ideas for finding biomarkers of cancer cells.
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