TAS-103 is a DNA intercalating indeno-quinoline derivative that stimulates DNA cleavage by topoisomerases. This synthetic drug has a broad spectrum of antitumor activity against many human solid tumor xenografts and is currently undergoing clinical trials. We investigated the induction of apoptosis in human promyelocytic leukemia cells treated with TAS-103. The treatment of proliferating human leukemia cells for 24 h with various concentrations of the drug induces significant variations in the mitochondrial transmembrane potential (delta(psi)mt) measured by flow cytometry using the fluorochromes 3,3-dihexyloxacarbocyanine iodide, Mitotracker Red, and tetrachloro-tetraethylbenzimidazolcarbocyanine iodide. The collapse of delta(psi)mt is accompanied by a marked decrease of the intracellular pH. Cleavage experiments with the substrates N-acetyl-Asp-Glu-Val-Asp-pNA, poly(ADP-ribose) polymerase, and pro-caspase-3 reveal unambiguously that caspase-3 is a key mediator of the apoptotic pathway induced by TAS-103. Caspase-8 is also cleaved, and the bcl-2 oncoprotein is underexpressed. Drug-induced internucleosomal DNA fragmentation and the externalization of phosphatidylserine residues in the outer leaflet of the plasma membrane were also characterized. The cell cycle perturbations produced by TAS-103 can be connected with the changes in deltapsi(mt). At low concentrations (2-25 nM), the drug induces a marked G2 arrest and concomitantly provokes an increase in the potential of mitochondrial membranes. In contrast, treatment of the HL-60 cells with higher drug concentrations (50 nM to 1 microM) triggers massive apoptosis and a collapse of deltaP(mt) that is a signature for the opening of the mitochondrial permeability transition pores. The discovery of a correlation between the G2 arrest and changes in mitochondrial membrane potential provides an important mechanistic insight into the action of TAS-103.
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PLoS One
January 2025
School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
The incidence of acute myeloid leukemia (AML) is increasing annually, and timely diagnostic and treatments can substantially improve patient survival rates. AML typing traditionally relies on manual microscopy for classifying and counting myeloid cells, which is time-consuming, laborious, and subjective. Therefore, developing a reliable automated model for myeloid cell classification is imperative.
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