## 1 Introduction  
Cancer is one of the main causes of human death in recent years [1]. Early diagnosis of cancer is a prerequisite for patient recovery [2], however the human body has many organs which may produce cancer cells, so there are many types of cancer cells. Therefore, the classification of cancer cells is also critical for the location of cancer incidence site. Not only that, another major feature of cancer is that it is prone to metastasis [3]. For example, the patient will bleed heavily undergoing tumor resection in the early stage of cancer, so cancerous cells may enter the peripheral blood circulation system, moving in the blood vessels in the form of a single cell or cell clusters, called circulating tumor cells. So, it is easy for cancer cells to migrate through the blood system. Therefore, the accurate identification of cancer cells is of great significance for diagnosing the metastasis, diffusion, and recurrence of cancer cells.  
At present, the fluorescent labelling method is mainly used in the identification of the type of cancer cells due to its specificity. Fluorescent labelling is based on the specific binding of antigen and antibody [4]. The method has a substantial impact on, and even damage to, the original physiological activity of cells, which is not conducive to further analysis and research. It is prone to false positives for antigen and antibody specific binding [5]. In addition, the treatment of samples is complex, costly, and inefficient, so there are many drawbacks in clinical applications. If there is a non-contact technique which can specifically identify cancer cells at the physical level, it will not only keep the cell activity intact, but can also effectively solve the problem of efficiency in the complexity of biological sample pre-treatment. Raman spectroscopy is such a technique, which is a kind of inelastic scattering fingerprint spectra of molecules [6]. There is a strong specificity to reflect the changes in biochemical components of living cells in aqueous solutions without any labelling and fixation [7], as such Raman spectroscopy has been employed in clinical diagnostics, toxicology tests, and tissue engineering [8; 9].  
Raman spectroscopy is a fast, accurate, label-free, and non-destructive analytical tool for the detection of the human cells at the single cell level [10; 11]. It can be used to obtain the difference of the intranuclear genetic material between the cancer cells and the normal cells, and the differences of the proteins in the cell membrane and cytoplasm [6; 12]. It is known that cellular biochemical components vary depending upon the cancer cells coming from different organs, and different malignancy degrees. The difference is critical for the development of Raman spectroscopy as a new clinical diagnostic approach [10; 11; 13; 14; 15]. The main objective of the present experimental study was to investigate the biochemical difference in these different cancer cells (SH-SYSY, HeLa, HO-8910, MDA-MB-231, U87, A549), the cells of distinct malignancy degree (MDA-MB-231 and MCF-7) and the normal cell line and cancer cells (HEB and U87) utilizing Raman spectroscopy.  
In recent years, Raman spectroscopy combined with discriminant analysis techniques has drawn considerable attention for distinguishing similar biological materials such as tissues, cells, and biological molecules [16; 17; 18; 19; 20; 21; 22]. In this work, a rapid approach for distinguishing eight kinds of different human cells by Raman spectroscopy was studied. To develop an accurate Raman spectroscopic discrimination model, principal component analysis (PCA) was employed to extract useful spectral information, and then two discriminant analysis algorithms, linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) were employed to and contrasted to discriminate the eight different human cells.