Abstract
In this study, an electroporation-based surface-enhanced Raman scattering (SERS) technique was employed to differentiate the human myeloid leukemia cells from the normal human bone marrow mononuclear cells with the aim to develop a fast and label-free method for leukemia cell screening. The Ag nanoparticles were delivered into living cells by electroporation, and then high quality SERS spectra were successfully obtained from 60 acute promyelocytic leukemia cells (HL60 cell line), 60 chronic myelogenous leukemia cells (K562 cell line) and 60 normal human bone marrow mononuclear cells (BMC). Principal component analysis (PCA) combined with linear discriminant analysis (LDA) differentiated the leukemia cell SERS spectra (HL60 plus K562) from normal cell SERS spectra (BMC) with high sensitivity (98.3%) and specificity (98.3%). Furthermore, partial least squares (PLS) approach was employed to develop a diagnostic model. The model successfully predicted the unidentified subjects with a diagnostic accuracy of 96.7%. This exploratory work demonstrates that the electroporation-based SERS technique combined with PCA-LDA and PLS diagnostic algorithms possesses great promise for cancer cell screening.
Highlights
IntroductionLeukemia is one of the deadliest diseases
Worldwide, leukemia is one of the deadliest diseases
Materials and methods 2.1 Preparation of Ag NPs Colloidal silver was prepared by the aqueous reduction of silver nitrate with hydroxylamine hydrochloride using the method developed by Leopold and Lendl [19]. 4.5 mL sodium hydroxide (0.1 mol/L) was added to 5 ml hydroxylamine hydrochloride (6 × 10−2 mol/L) and the mixtures were added to 90 mL silver nitrate (1.11 × 10−3 mol/L)
Summary
Leukemia is one of the deadliest diseases. A great deal of research has gone into the development of novel approaches for leukemia early detection and screening. Raman spectroscopy combined with statistical methods has been widely applied in disease diagnostics, including leukemia, oesophagus cancer, breast cancer, colorectal cancer, bladder cancer, lung cancer, and skin cancer [3,4,5]. The typical data collection times for Raman spectroscopy of a living cell using a confocal Raman spectrometer can be up to several minutes per point. The data collection times will be too long for practical applications such as high resolution living cell Raman imaging and high-throughput cancer cell screening
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