Optical tweezers and Raman spectroscopy for single‐cell classification of drug resistance in acute lymphoblastic leukemia

Abstract

Laser Tweezers Raman Spectroscopy (LTRS) is a combination of laser tweezers and Raman spectroscopy. It is a physical tool based on the mechanical effects of the laser, which can be used to study single living cells in suspension in a fast and non‐destructive way. Our work aims to establish a methodology system based on LTRS to rapidly and non‐destructively detect the resistance of acute lymphoblastic leukemia (ALL) cells and to provide a new idea for the evaluation of the resistance of ALL cells. Two specific adriamycin‐resistant and parental ALL cells BALL‐1 and Nalm6 were included in this study. Adriamycin resistant cells can induce the spectral differences, which can be detected by LTRS initially. To ensure the accuracy of the results, we use the principal components analysis (PCA) as well as the classification and regression trees (CRT) algorithms, which show that the specificity and sensitivity of LTRS are above 90%. In addition, to further clarify the chemoresistance status of ALL cells, we used the CRT models and receiver operating characteristic (ROC) curves which are based on the band data to look for some important bands and band intensity ratios that have strong pointing significance. Our work proves that LTRS analysis combined with multivariate statistical analyses have great potential to be a novel analytical strategy at the single‐cell level for rapidly evaluating the chemoresistance status of ALL cells.

Raman identification of single cell component and FMS‐like tyrosine kinase 3‐internal tandem duplications subtype for clinical acute myeloid leukemia

“…The permutation test (P value <0.001) proved that results achieved were valid (Figure 7) for the T A B L E 1 Raman spectra peak assignments of MCR components obtained from the MCR-ALS analysis in Figure 5A-C Note: Assignments based on refs. 12,30,[32][33][34][35][36][37] classification model built for the FLT3-ITD mutation. Such results indicated that the high accuracy of the classifier was unlikely to have occurred by chance.…”

Identification of multiple myeloma resistant cells using machine learning and laser tweezers Raman spectroscopy

“…They have also been used to test the response of human gastric cancer cells to chemotherapy drugs and assess sensitivity to anticancer drugs [23]. Additionally, Raman spectroscopy has been used at the single-cell level to identify drug resistance in acute leukemia cells to daunorubicin [24]. Furthermore, research has shown that Raman spectroscopy can be used for in vitro studies of interactions between multiple myeloma cells and different anticancer drugs.…”