title: A mathematical model of subpopulation kinetics for the deconvolution of leukaemia heterogeneity.
abstract: Acute myeloid leukaemia is characterized by marked inter- and intra-patient heterogeneity, the identification of which is critical for the design of personalized treatments. Heterogeneity of leukaemic cells is determined by mutations which ultimately affect the cell cycle. We have developed and validated a biologically relevant, mathematical model of the cell cycle based on unique cell-cycle signatures, defined by duration of cell-cycle phases and cyclin profiles as determined by flow cytometry, for three leukaemia cell lines. The model was discretized for the different phases in their respective progress variables (cyclins and DNA), resulting in a set of time-dependent ordinary differential equations. Cell-cycle phase distribution and cyclin concentration profiles were validated against population chase experiments. Heterogeneity was simulated in culture by combining the three cell lines in a blinded experimental set-up. Based on individual kinetics, the model was capable of identifying and quantifying cellular heterogeneity. When supplying the initial conditions only, the model predicted future cell population dynamics and estimated the previous heterogeneous composition of cells. Identification of heterogeneous leukaemia clones at diagnosis and post-treatment using such a mathematical platform has the potential to predict multiple future outcomes in response to induction and consolidation chemotherapy as well as relapse kinetics.
authors.affiliation: Biological Systems Engineering Laboratory, Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
authors.forename: María
authors.initials: M
authors.lastname: Fuentes-Garí
authors.affiliation: Department of Computing, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
authors.forename: Ruth
authors.initials: R
authors.lastname: Misener
authors.affiliation: Biological Systems Engineering Laboratory, Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.
authors.forename: David
authors.initials: D
authors.lastname: García-Munzer
authors.affiliation: Department of Chemical and Process Engineering, University of Surrey, Guildford GU2 7XH, UK.
authors.forename: Eirini
authors.initials: E
authors.lastname: Velliou
authors.affiliation: Aristotle University of Thessaloniki, Thessaloniki, Greece.
authors.forename: Michael C
authors.initials: MC
authors.lastname: Georgiadis
authors.affiliation: Aristotle University of Thessaloniki, Thessaloniki, Greece.
authors.forename: Margaritis
authors.initials: M
authors.lastname: Kostoglou
authors.affiliation: Artie McFerrin Department of Chemical Engineering, Texas A&M, College Station, TX, USA.
authors.forename: Efstratios N
authors.initials: EN
authors.lastname: Pistikopoulos
authors.affiliation: Department of Hematology, Imperial College London, Northwick Park and St Mark's Campus, Harrow HA1 3UJ, UK.
authors.forename: Nicki
authors.initials: N
authors.lastname: Panoskaltsis
authors.affiliation: Biological Systems Engineering Laboratory, Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK a.mantalaris@imperial.ac.uk.
authors.forename: Athanasios
authors.initials: A
authors.lastname: Mantalaris
mesh_terms: D000818:Animals; D002453:Cell Cycle; D016213:Cyclins / Q000378:metabolism; D004273:DNA, Neoplasm / Q000378:metabolism; D006801:Humans; D015470:Leukemia, Myeloid, Acute / Q000378:metabolism* / Q000473:pathology; D008954:Models, Biological; D009363:Neoplasm Proteins / Q000378:metabolism
chemical_list: D016213:Cyclins; D004273:DNA, Neoplasm; D009363:Neoplasm Proteins
keywords: acute myeloid leukaemia; cell cycle; leukaemia heterogeneity; mathematical model; population balance model