Detection and identification of leukemic and normal cells using Raman spectroscopy and multivariate statistical analysis

Abstract

Raman spectroscopy technique was successfully employed to study the difference between leukemic cells (Jurkat cell line) and normal human bone marrow mononuclear cells using near-infrared laser (785 nm) excitation in this study. Significant differences in Raman spectra from two kinds of cell lines showed special changes in the percentage of biochemical constituents in different cells. The obtained spectral data were used to develop diagnostic algorithms by multivariate statistical analysis, including principal component analysis combined with linear discriminate analysis. The multivariate statistical analysis method for classification between cancer and normal cells has achieved good differentiation with high diagnostic sensitivity (100%), specificity (100%), and accuracy (100%), respectively. These results showed that Raman spectroscopy is a novel, nondestructive method, that provided interesting information about the changes in biochemical properties of cells. Raman spectroscopy combined with multivariate statistical analysis can serve as a potential clinical diagnosis method of leukemia.

Keywords:

• Raman spectroscopy
• cell detection
• multivariate statistical analysis

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by the National Natural Science Foundation of China (No. 62241504), the Natural Science Foundation of Fujian Province of China (Nos. 2022J01346, 2022J01844, 2021J01888), the Project of the Educational Office of Fujian Province (No. JAT200223), and the Special Research Project of High-level Talent of Fujian Health College (MWY2023-5-01).