Normal vs. Malignant hematopoiesis: the complexity of acute leukemia through systems biology

摘要

The early stages of malignant hematopoiesis: A multi-cellular, multi-compartment and multi-factorial challenging study model Development of normal hematopoietic cells is an ordered multi-step process, tightly regulated by a complex network of intrinsic factors and microenvironmental cues that control cell fate decisions within the bone marrow (BM) (Pelayo et al., 2012 ; Purizaca et al., 2012 ; Boulais and Frenette, 2015 ). During malignant hematological disorders, including acute leukemias (AL), the uncontrolled differentiation of precursors of the lymphoid or myeloid series sustains tumor growth at the expense of normal blood cell production. Moreover, selection and dominance among leukemic clones occur while competing for niche resources and creating abnormal BM microenvironments that co-participate in the pathobiology of the disease (Colmone et al., 2008 ; Ayala et al., 2009 ; Purizaca et al., 2012 ; Kim et al., 2015 ; Vilchis-Ordo?ez et al., 2015 ). Thus, due to the complexity and health impact of AL (Gupta et al., 2014 ), new strategies to better predict cell population dynamics according to genetics, microenvironmental and clinical heterogeneous contexts may contribute to understand its pathobiology and to guide strategies for decreasing overall mortality. Mathematical modeling has emerged as a powerful tool in biomedical and health research because it enables the simulation of complex biological systems and the efficient generation of testable hypotheses. In recent years, leukemic cell dynamics has been addressed from the novel view of systems biology, resulting in helpful stochastic and deterministic models and providing clearer understanding of the disease by simplification of malignant clonal evolution processes (Vesely et al., 2011 ; Amir et al., 2013 ; Paguirigan et al., 2015 ). However, models fitted to experimental data must strike a balance between simplicity and reality, so that they can bring insights into clinical scenarios. Here we discuss the importance and challenges of incorporating the BM microenvironment into AL modeling, as a key element that will control the interplay between cell populations and the selective pressure leading to leukemic or normal hematopoiesis progression. By developing integrative tools that better mimic and predict the behavior of heterogeneous and polyclonal cells in the context of abnormal microenvironments within leukemic bone marrow, we may learn about crucial mechanisms co-participating in the etiology and progression of the disease. Normal vs. leukemic clones: Systems biology in the study of acute leukemia complexity Continuous dynamic modeling with differential equations (DEs) has been the most popular systems biology tool for the study of normal and leukemic hematopoiesis. This type of modeling is useful for the time evolving non-linear competition between normal and leukemic cell populations, considering multiple compartments to simulate different maturation stages or multiclonal behavior (Catlin et al., 2005 ; Stiehl and Marciniak-Czochra, 2012 ; MacLean et al., 2013 ; Stiehl et al., 2014 ). Of special interest, theoretical data suggests the existence of an initial “steady state” before the disease development, when co-existence of normal hematopoiesis with a limited number of pre-leukemic cells controls leukemia installation (Rubinow and Lebowitz, 1976 ; Stiehl and Marciniak-Czochra, 2012 ; Swaminathan et al., 2015 ). A sudden change in the homeostatic parameters may induce leukemic cell expansion leading to a progressive decrease of normal hematopoiesis, while perturbation of initial homeostatic state endows malignant cells with self-renewal and proliferation. Accordingly, the model by Rubinow and Lebowitz's on competition advantage of leukemia cells proposed a higher value of their equilibrium number that refers to the maximum population size that can be supported within the niche. If the stop-expansion signal for malignant progenitors is not delivered before the equilibrium number is reached, a signal activating the slow-down of normal cells promotes the expansion of the leukemic population. High equilibrium numbers in leukemic compartments could be biologically interpreted as independence from the microenvironment, unbalanced proliferation/apoptosis rates, and further accumulation of blasts. Using a stochastic model to simulate stem cell decisions, Abkowitz and colleagues have analyzed the behavior of individual components (HSC) acting collectively within a dynamical complex context (clonal diversity plus heterogeneous surrounding microenvironment). By tracking HSC replication, the expansion of the hematopoietic system was apparent from birth to adolescence, when steady-state levels are reached. Stochastic modeling of replication kinetics has shown to be useful to predict cell rebounding upon hematopoietic transplantation or under emerging conditions (Catlin et al., 2005 , 2011 ). In contrast, agent-based deterministic modeling of HSC organizati