Objective To explore a new method based on cellular secreted protein combined with surface enhanced Raman spectroscopy (SERS) to effectively distinguish well-differentiated and poorly-differentiated nasopharyngeal carcinoma cells. Methods Human well-differentiated nasopharyngeal carcinoma cell CNE1, poorly-differentiated nasopharyngeal carcinoma cell CNE2 and normal nasopharyngeal epithelial cell NP69 were taken as the research objects. After 24 hours of natural culture, the secreted proteins were collected and measured by SERS spectrum. By comparing the spectral characteristics of the three groups of cells, the differences in composition and structure of protein secreted by cells were analyzed. Furthermore, principal component analysis (PCA) and linear discriminant analysis (LDA) are combined to reduce and classify the spectral data, and the performance of this method in distinguishing cancer cells with different degrees of differentiation from normal cells is evaluated. Results SERS spectra of secreted proteins of CNE1, CNE2 and NP69 cells were successfully obtained. There were obvious differences in Raman peak position, peak intensity and peak shape among the three groups of cells, suggesting that there were significant changes in the composition of secreted proteins. PCA-LDA model shows excellent classification ability, which can clearly distinguish cancer from non-cancer cells, and effectively separate well-differentiated and poorly-differentiated nasopharyngeal carcinoma cells. The recognition sensitivity and specificity of the model for highly differentiated nasopharyngeal carcinoma cell CNE1 are over 96%, and the classification accuracy is over 98%. The recognition sensitivity and specificity of poorly differentiated nasopharyngeal carcinoma cell CNE2 are over 95%, and the classification accuracy is over 95%, showing good diagnostic performance. Conclusion Cell secretory protein combined with SERS technology can not only effectively distinguish nasopharyngeal carcinoma cells from normal cells, but also further identify the differentiation degree of cancer cells, with high sensitivity and specificity. This method is expected to provide a non-labeled and rapid detection method for pathological classification of nasopharyngeal carcinoma.