The analysis of leukocytes of peripheral blood is a crucial step in hematologic exams commonly used for disease diagnosis and, typically, requires molecular labelling. In addition, only a detailed, laborious phenotypic analysis allows identifying the presence and stage of specific pathologies such as leukemia. Most of the biochemical information is lost in the routine blood tests. In the present study, we tackle 2 important issues of label-free biochemical identification and classification of leukocytes using Raman spectroscopy (RS). First, we demonstrate that leukocyte subpopulations of lymphocytes (B, T and NK cells), monocytes and granulocytes can be identified by the unsupervised statistical approach of principal component analysis and classified by linear discriminant analysis with approximately 99% of accuracy. Second, we apply the same procedure to identify and discriminate normal B cells and transformed MN60 lymphocyte leukemic cell lines. In addition, we demonstrate that RS can be efficiently used for monitoring the cell response to low-dose chemotherapy treatment, experimentally eliciting the sensitivity to a dose-dependent cell response, which is of fundamental importance to determine the efficacy of any treatment. These results largely expand established Raman-based research protocols for label-free analysis of white blood cells, leukemic cells and chemotherapy treatment follow-up.
Keywords: Raman spectroscopy; chemotherapy treatment; leukemia cells; white blood cells.
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