Nasopharyngeal cancer (NPC), which arises from the nasopharyngeal epithelial lining, is one of the common malignant otorhinolaryngological tumors in China. Due to its insidious anatomical location and highly invasive and metastatic features, it is challenging to detect NPC at early stages. In this work, a rapid laser tweezer Raman spectroscopic (LTRS) system was built and used to trap and characterize single NPC cells. Using LTRS, high-quality Raman signals of the normal nasopharyngeal cell line (NP69) and NPC cells could be successfully obtained. By analysing the Raman peaks, some unique changes were found in components, such as DNA, amide I and amide III, in NPC cells compared with normal cells. In addition, we also used a multivariate statistical algorithm to establish a diagnostic model for identifying NPC cells with an accuracy of 90.0%. These results demonstrate that LTRS in combination with the multivariate statistical analysis is a convenient and high-efficiency cell identification technology, providing a novel and rapid methodology for NPC detection at the single cell level.