4.6 Article

Characterization of Drug Resistance in Chronic Myeloid Leukemia Cells Based on Laser Tweezers Raman Spectroscopy

期刊

APPLIED SPECTROSCOPY
卷 75, 期 10, 页码 1296-1304

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/00037028211024581

关键词

Chronic myeloid leukemia; CML; multidrug resistance; K562; principal component analysis; PCA; classification and regression trees; CRT; laser tweezers Raman spectroscopy; LTRS

资金

  1. National Natural Science Foundation of China [61975031]
  2. Natural Science Foundation of Fujian Province [2020J01651]
  3. Distinguished Young Scientific Research Talents Plan in Universities of Fujian Province [2018B036]
  4. Scientific Research Talent Training Project of Fujian Provincial Health and Family Planning Commission [20181-70]
  5. Open Fund of Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance (Xiamen University) [20191203]
  6. Youth Foundation from College Project of Fujian Medical University [2019XY001]

向作者/读者索取更多资源

This study explores the use of laser tweezers Raman spectroscopy for analyzing chemoresistance in chronic myeloid leukemia cells, demonstrating its high specificity and sensitivity as a novel analytical strategy. The research identifies important spectral features and metabolic pathways that can help distinguish different chemoresistance statuses.
Multidrug resistance is highly associated with poor prognosis of chronic myeloid leukemia. This work aims to explore whether the laser tweezers Raman spectroscopy (LTRS) could be practical in separating adriamycin-resistant chronic myeloid leukemia cells K562/adriamycin from its parental cells K562, and to explore the potential mechanisms. Detection of LTRS initially reflected the spectral differences caused by chemoresistance including bands assigned to carbohydrates, amino acid, protein, lipids, and nucleic acid. In addition, principal components analysis as well as the classification and regression trees algorithms showed that the specificity and sensitivity were above 90%. Moreover, the band data-based classification and regression tree model and receiver operating characteristic curve further determined some important bands and band intensity ratios to be reliable indexes in discriminating K562 chemoresistance status. Finally, we highlighted three metabolism pathways correlated with chemoresistance. This work demonstrates that the label-free LTRS analysis combined with multivariate statistical analyses have great potential to be a novel analytical strategy at the single-cell level for rapid evaluation of the chemoresistance status of K562 cells.

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