Competitive clonal hematopoiesis in mouse chimeras explained by a stochastic model of stem cell organization

Preclinical lentiviral hematopoietic stem cell gene therapy corrects Pompe disease-related muscle and neurological manifestations

Pompe disease, a rare genetic neuromuscular disorder, is caused by a deficiency of acid alpha-glucosidase (GAA), leading to an accumulation of glycogen in lysosomes, and resulting in the progressive development of muscle weakness. The current standard treatment, enzyme replacement therapy (ERT), is not curative and has limitations such as poor penetration into skeletal muscle and both the central and peripheral nervous systems, a risk of immune responses against the recombinant enzyme, and the requirement for high doses and frequent infusions. To overcome these limitations, lentiviral vector-mediated hematopoietic stem and progenitor cell (HSPC) gene therapy has been proposed as a next-generation approach for treating Pompe disease. This study demonstrates the potential of lentiviral HSPC gene therapy to reverse the pathological effects of Pompe disease in a preclinical mouse model. It includes a comprehensive safety assessment via integration site analysis, along with single-cell RNA sequencing analysis of central nervous tissue samples to gain insights into the underlying mechanisms of phenotype correction.

Emerging insights into epigenetics and hematopoietic stem cell trafficking in age-related hematological malignancies

BACKGROUND

Hematopoiesis within the bone marrow (BM) is a complex and tightly regulated process predominantly influenced by immune factors. Aging, diabetes, and obesity are significant contributors to BM niche damage, which can alter hematopoiesis and lead to the development of clonal hematopoiesis of intermediate potential (CHIP). Genetic/epigenetic alterations during aging could influence BM niche reorganization for hematopoiesis or clonal hematopoiesis. CHIP is driven by mutations in genes such as Tet2, Dnmt3a, Asxl1, and Jak2, which are associated with age-related hematological malignancies.

OBJECTIVE

This literature review aims to provide an updated exploration of the functional aspects of BM niche cells within the hematopoietic microenvironment in the context of age-related hematological malignancies. The review specifically focuses on how immunological stressors modulate different signaling pathways that impact hematopoiesis.

METHODS

An extensive review of recent studies was conducted, examining the roles of various BM niche cells in hematopoietic stem cell (HSC) trafficking and the development of age-related hematological malignancies. Emphasis was placed on understanding the influence of immunological stressors on these processes.

RESULTS

Recent findings reveal a significant microheterogeneity and temporal stochasticity of niche cells across the BM during hematopoiesis. These studies demonstrate that niche cells, including mesenchymal stem cells, osteoblasts, and endothelial cells, exhibit dynamic interactions with HSCs, significantly influenced by the BM microenvironment as the age increases. Immunosurveillance plays a crucial role in maintaining hematopoietic homeostasis, with alterations in immune signaling pathways contributing to the onset of hematological malignancies. Novel insights into the interaction between niche cells and HSCs under stress/aging conditions highlight the importance of niche plasticity and adaptability.

CONCLUSION

The involvement of age-induced genetic/epigenetic alterations in BM niche cells and immunological stressors in hematopoiesis is crucial for understanding the development of age-related hematological malignancies. This comprehensive review provides new insights into the complex interplay between niche cells and HSCs, emphasizing the potential for novel therapeutic approaches that target niche cell functionality and resilience to improve hematopoietic outcomes in the context of aging and metabolic disorders.

NOVELTY STATEMENT

This review introduces novel concepts regarding the plasticity and adaptability of BM niche cells in response to immunological stressors and epigenetics. It proposes that targeted therapeutic strategies aimed at enhancing niche cell resilience could mitigate the adverse effects of aging, diabetes, and obesity on hematopoiesis and clonal hematopoiesis. Additionally, the review suggests that understanding the precise temporal and spatial dynamics of niche-HSC interactions and epigenetics influence may lead to innovative treatments for age-related hematological malignancies.

Scalable inference of cell differentiation networks in gene therapy clonal tracking studies of haematopoiesis

MOTIVATION

Investigating cell differentiation under a genetic disorder offers the potential for improving current gene therapy strategies. Clonal tracking provides a basis for mathematical modelling of population stem cell dynamics that sustain the blood cell formation, a process known as haematopoiesis. However, many clonal tracking protocols rely on a subset of cell types for the characterization of the stem cell output, and the data generated are subject to measurement errors and noise.

RESULTS

We propose a stochastic framework to infer dynamic models of cell differentiation from clonal tracking data. A state-space formulation combines a stochastic quasi-reaction network, describing cell differentiation, with a Gaussian measurement model accounting for data errors and noise. We developed an inference algorithm based on an extended Kalman filter, a nonlinear optimization, and a Rauch-Tung-Striebel smoother. Simulations show that our proposed method outperforms the state-of-the-art and scales to complex structures of cell differentiations in terms of nodes size and network depth. The application of our method to five in vivo gene therapy studies reveals different dynamics of cell differentiation. Our tool can provide statistical support to biologists and clinicians to better understand cell differentiation and haematopoietic reconstitution after a gene therapy treatment. The equations of the state-space model can be modified to infer other dynamics besides cell differentiation.

AVAILABILITY AND IMPLEMENTATION

The stochastic framework is implemented in the R package Karen which is available for download at https://cran.r-project.org/package=Karen. The code that supports the findings of this study is openly available at https://github.com/delcore-luca/CellDifferentiationNetworks.

A mixed-effects stochastic model reveals clonal dominance in gene therapy safety studies

BACKGROUND

Mathematical models of haematopoiesis can provide insights on abnormal cell expansions (clonal dominance), and in turn can guide safety monitoring in gene therapy clinical applications. Clonal tracking is a recent high-throughput technology that can be used to quantify cells arising from a single haematopoietic stem cell ancestor after a gene therapy treatment. Thus, clonal tracking data can be used to calibrate the stochastic differential equations describing clonal population dynamics and hierarchical relationships in vivo.

RESULTS

In this work we propose a random-effects stochastic framework that allows to investigate the presence of events of clonal dominance from high-dimensional clonal tracking data. Our framework is based on the combination between stochastic reaction networks and mixed-effects generalized linear models. Starting from the Kramers-Moyal approximated Master equation, the dynamics of cells duplication, death and differentiation at clonal level, can be described by a local linear approximation. The parameters of this formulation, which are inferred using a maximum likelihood approach, are assumed to be shared across the clones and are not sufficient to describe situation in which clones exhibit heterogeneity in their fitness that can lead to clonal dominance. In order to overcome this limitation, we extend the base model by introducing random-effects for the clonal parameters. This extended formulation is calibrated to the clonal data using a tailor-made expectation-maximization algorithm. We also provide the companion  package RestoreNet, publicly available for download at https://cran.r-project.org/package=RestoreNet .

CONCLUSIONS

Simulation studies show that our proposed method outperforms the state-of-the-art. The application of our method in two in-vivo studies unveils the dynamics of clonal dominance. Our tool can provide statistical support to biologists in gene therapy safety analyses.

Understanding Hematopoietic Stem Cell Dynamics—Insights from Mathematical Modelling

Purpose of review

Hematopoietic stem cells (HSCs) drive blood-cell production (hematopoiesis). Out-competition of HSCs by malignant cells occurs in many hematologic malignancies like acute myeloid leukemia (AML). Through mathematical modelling, HSC dynamics and their impact on healthy blood cell formation can be studied, using mathematical analysis and computer simulations. We review important work within this field and discuss mathematical modelling as a tool for attaining biological insight.

Recent findings

Various mechanism-based models of HSC dynamics have been proposed in recent years. Key properties of such models agree with observations and medical knowledge and suggest relations between stem cell properties, e.g., rates of division and the temporal evolution of the HSC population. This has made it possible to study how HSC properties shape clinically relevant processes, including engraftment following an HSC transplantation and the response to different treatment.

Summary

Understanding how properties of HSCs affect hematopoiesis is important for efficient treatment of diseases. Mathematical modelling can contribute significantly to these efforts.

Calibration, Selection and Identifiability Analysis of a Mathematical Model of the in vitro Erythropoiesis in Normal and Perturbed Contexts

The in vivo erythropoiesis, which is the generation of mature red blood cells in the bone marrow of whole organisms, has been described by a variety of mathematical models in the past decades. However, the in vitro erythropoiesis, which produces red blood cells in cultures, has received much less attention from the modelling community. In this paper, we propose the first mathematical model of in vitro erythropoiesis. We start by formulating different models and select the best one at fitting experimental data of in vitro erythropoietic differentiation obtained from chicken erythroid progenitor cells. It is based on a set of linear ODE, describing 3 hypothetical populations of cells at different stages of differentiation. We then compute confidence intervals for all of its parameters estimates, and conclude that our model is fully identifiable. Finally, we use this model to compute the effect of a chemical drug called Rapamycin, which affects all states of differentiation in the culture, and relate these effects to specific parameter variations. We provide the first model for the kinetics of in vitro cellular differentiation which is proven to be identifiable. It will serve as a basis for a model which will better account for the variability which is inherent to the experimental protocol used for the model calibration.

Quantitative prediction of long-term molecular response in TKI-treated CML - Lessons from an imatinib versus dasatinib comparison

Longitudinal monitoring of BCR-ABL transcript levels in peripheral blood of CML patients treated with tyrosine kinase inhibitors (TKI) revealed a typical biphasic response. Although second generation TKIs like dasatinib proved more efficient in achieving molecular remission compared to first generation TKI imatinib, it is unclear how individual responses differ between the drugs and whether mechanisms of drug action can be deduced from the dynamic data. We use time courses from the DASISION trial to address statistical differences in the dynamic response between first line imatinib vs. dasatinib treatment cohorts and we analyze differences between the cohorts by fitting an established mathematical model of functional CML treatment to individual time courses. On average, dasatinib-treated patients show a steeper initial response, while the long-term response only marginally differed between the treatments. Supplementing each patient time course with a corresponding confidence region, we illustrate the consequences of the uncertainty estimate for the underlying mechanisms of CML remission. Our model suggests that the observed BCR-ABL dynamics may result from different, underlying stem cell dynamics. These results illustrate that the perception and description of CML treatment response as a dynamic process on the level of individual patients is a prerequisite for reliable patient-specific response predictions and treatment optimizations.

Aging of hematopoietic stem cells

Hematopoietic stem cells (HSCs) ensure a balanced production of all blood cells throughout life. As they age, HSCs gradually lose their self-renewal and regenerative potential, whereas the occurrence of cellular derailment strongly increases. Here we review our current understanding of the molecular mechanisms that contribute to HSC aging. We argue that most of the causes that underlie HSC aging result from cell-intrinsic pathways, and reflect on which aspects of the aging process may be reversible. Because many hematological pathologies are strongly age-associated, strategies to intervene in aspects of the stem cell aging process may have significant clinical relevance.

Clonal competition in BcrAbl-driven leukemia: how transplantations can accelerate clonal conversion

Background

Clonal competition in cancer describes the process in which the progeny of a cell clone supersedes or succumbs to other competing clones due to differences in their functional characteristics, mostly based on subsequently acquired mutations. Even though the patterns of those mutations are well explored in many tumors, the dynamical process of clonal selection is underexposed.

Methods

We studied the dynamics of clonal competition in a BcrAbl-induced leukemia using a γ-retroviral vector library encoding the oncogene in conjunction with genetic barcodes. To this end, we studied the growth dynamics of transduced cells on the clonal level both in vitro and in vivo in transplanted mice.

Results

While we detected moderate changes in clonal abundancies in vitro, we observed monoclonal leukemias in 6/30 mice after transplantation, which intriguingly were caused by only two different BcrAbl clones. To analyze the success of these clones, we applied a mathematical model of hematopoietic tissue maintenance, which indicated that a differential engraftment capacity of these two dominant clones provides a possible explanation of our observations. These findings were further supported by additional transplantation experiments and increased BcrAbl transcript levels in both clones.

Conclusion

Our findings show that clonal competition is not an absolute process based on mutations, but highly dependent on selection mechanisms in a given environmental context.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-017-0668-x) contains supplementary material, which is available to authorized users.

Model Based Analysis of Clonal Developments Allows for Early Detection of Monoclonal Conversion and Leukemia

The availability of several methods to unambiguously mark individual cells has strongly fostered the understanding of clonal developments in hematopoiesis and other stem cell driven regenerative tissues. While cellular barcoding is the method of choice for experimental studies, patients that underwent gene therapy carry a unique insertional mark within the transplanted cells originating from the integration of the retroviral vector. Close monitoring of such patients allows accessing their clonal dynamics, however, the early detection of events that predict monoclonal conversion and potentially the onset of leukemia are beneficial for treatment. We developed a simple mathematical model of a self-stabilizing hematopoietic stem cell population to generate a wide range of possible clonal developments, reproducing typical, experimentally and clinically observed scenarios. We use the resulting model scenarios to suggest and test a set of statistical measures that should allow for an interpretation and classification of relevant clonal dynamics. Apart from the assessment of several established diversity indices we suggest a measure that quantifies the extension to which the increase in the size of one clone is attributed to the total loss in the size of all other clones. By evaluating the change in relative clone sizes between consecutive measurements, the suggested measure, referred to as maximum relative clonal expansion (mRCE), proves to be highly sensitive in the detection of rapidly expanding cell clones prior to their dominant manifestation. This predictive potential places the mRCE as a suitable means for the early recognition of leukemogenesis especially in gene therapy patients that are closely monitored. Our model based approach illustrates how simulation studies can actively support the design and evaluation of preclinical strategies for the analysis and risk evaluation of clonal developments.

Transplantation Dose Alters the Differentiation Program of Hematopoietic Stem Cells

Hematopoietic stem cell (HSC) transplantation is the most prevalent stem cell therapy, but it remains a risky procedure. To improve this treatment, it is important to understand how transplanted stem cells rebuild the blood and immune systems and how this process is impacted by transplantation variables such as the HSC dose. Here, we find that, in the long term following transplantation, 70%-80% of donor-HSC-derived clones do not produce all measured blood cell types. High HSC doses lead to more clones that exhibit balanced lymphocyte production, whereas low doses produce more T-cell-specialized clones. High HSC doses also produce significantly higher proportions of early-differentiating clones compared to low doses. These complex differentiation behaviors uncover the clonal-level regeneration dynamics of hematopoietic regeneration and suggest that transplantation dose can be exploited to improve stem cell therapy.

Cellular population dynamics control the robustness of the stem cell niche

Within populations of cells, fate decisions are controlled by an indeterminate combination of cell-intrinsic and cell-extrinsic factors. In the case of stem cells, the stem cell niche is believed to maintain ‘stemness’ through communication and interactions between the stem cells and one or more other cell-types that contribute to the niche conditions. To investigate the robustness of cell fate decisions in the stem cell hierarchy and the role that the niche plays, we introduce simple mathematical models of stem and progenitor cells, their progeny and their interplay in the niche. These models capture the fundamental processes of proliferation and differentiation and allow us to consider alternative possibilities regarding how niche-mediated signalling feedback regulates the niche dynamics. Generalised stability analysis of these stem cell niche systems enables us to describe the stability properties of each model. We find that although the number of feasible states depends on the model, their probabilities of stability in general do not: stem cell–niche models are stable across a wide range of parameters. We demonstrate that niche-mediated feedback increases the number of stable steady states, and show how distinct cell states have distinct branching characteristics. The ecological feedback and interactions mediated by the stem cell niche thus lend (surprisingly) high levels of robustness to the stem and progenitor cell population dynamics. Furthermore, cell–cell interactions are sufficient for populations of stem cells and their progeny to achieve stability and maintain homeostasis. We show that the robustness of the niche – and hence of the stem cell pool in the niche – depends only weakly, if at all, on the complexity of the niche make-up: simple as well as complicated niche systems are capable of supporting robust and stable stem cell dynamics.

Summary: Stem cell niche dynamics are very robust to external and physiological perturbations because proliferation and differentiation are naturally balanced and controlled by the reliance on a shared niche environment.

Single-cell RNA-seq reveals changes in cell cycle and differentiation programs upon aging of hematopoietic stem cells

Both intrinsic cell state changes and variations in the composition of stem cell populations have been implicated as contributors to aging. We used single-cell RNA-seq to dissect variability in hematopoietic stem cell (HSC) and hematopoietic progenitor cell populations from young and old mice from two strains. We found that cell cycle dominates the variability within each population and that there is a lower frequency of cells in the G1 phase among old compared with young long-term HSCs, suggesting that they traverse through G1 faster. Moreover, transcriptional changes in HSCs during aging are inversely related to those upon HSC differentiation, such that old short-term (ST) HSCs resemble young long-term (LT-HSCs), suggesting that they exist in a less differentiated state. Our results indicate both compositional changes and intrinsic, population-wide changes with age and are consistent with a model where a relationship between cell cycle progression and self-renewal versus differentiation of HSCs is affected by aging and may contribute to the functional decline of old HSCs.

Mathematical Modelling as a Tool to Understand Cell Self-renewal and Differentiation

Mathematical modeling is a powerful technique to address key questions and paradigms in a variety of complex biological systems and can provide quantitative insights into cell kinetics, fate determination and development of cell populations. The chapter is devoted to a review of modeling of the dynamics of stem cell-initiated systems using mathematical methods of ordinary differential equations. Some basic concepts and tools for cell population dynamics are summarized and presented as a gentle introduction to non-mathematicians. The models take into account different plausible mechanisms regulating homeostasis. Two mathematical frameworks are proposed reflecting, respectively, a discrete (punctuated by division events) and a continuous character of transitions between differentiation stages. Advantages and constraints of the mathematical approaches are presented on examples of models of blood systems and compared to patients data on healthy hematopoiesis.

Clonal heterogeneity as a driver of disease variability in the evolution of myeloproliferative neoplasms

Myeloproliferative neoplasms (MPNs) are clonal hematological diseases in which cells of the myelo-erythroid lineage are overproduced and patients are predisposed to leukemic transformation. Hematopoietic stem cells are the suspected disease-initiating cells, and these cells must acquire a clonal advantage relative to nonmutant hematopoietic stem cells to perpetuate disease. In 2005, several groups identified a single gain-of-function point mutation in JAK2 that associated with the majority of MPNs, and subsequent studies have led to a comprehensive understanding of the mutational landscape in MPNs. However, confusion still exists as to how a single genetic aberration can be associated with multiple distinct disease entities. Many explanations have been proposed, including JAK2V617F homozygosity, individual patient heterogeneity, and the differential regulation of downstream JAK2 signaling pathways. Several groups have made knock-in mouse models expressing JAK2V617F and have observed divergent phenotypes, each recapitulating some aspects of disease. Intriguingly, most of these models do not observe a strong hematopoietic stem cell self-renewal advantage compared with wild-type littermate controls, raising the question of how a clonal advantage is established in patients with MPNs. This review summarizes the current molecular understanding of MPNs and the diversity of disease phenotypes and proposes that the increased proliferation induced by JAK2V617F applies a selection pressure on the mutant clone that results in highly diverse clonal evolution in individuals.

Quantification and modeling of stem cell-niche interaction

Adult stem cells persist lifelong in the organism, where they are responsible for tissue homeostasis and repair. It is commonly assumed that their maintenance and function are facilitated in local environments called "stem cell niches." Although there is convincing evidence that a variety of niche components determine stem cell fate, the regulatory details of stem cell-niche interactions are widely unknown. To pave the way for a substantiated discussion of these interactions, we first focus on the stem cells themselves and describe the stem cell defining criteria and their implications. The fate of the cells that fulfill these criteria is regulated by a broad spectrum of factors and regulatory mechanisms. A summary of established components and their action is given exemplary for the hematopoietic system. The complexity resulting from the interplay of various cell types, signaling molecules, and extracellular structures can be boiled down to important key features as exemplified by the presented model of hematopoietic stem cell organization. Although neglecting many details, we show that this and similar models have the power to yield intriguing results as proven by the agreement of the presented model with experimental data and the predictions derived from model simulations. Finally, we will discuss the paradigm of systems biology and give a summary of the techniques that promise to unveil further details of the organization principles of stem cell niches at different levels. The synergistic effect of the described techniques together with the integration of their results into a unified model that allows quantitative evaluation and predictions may lead to a better and more systematic understanding of the most relevant niche elements and their interactions.

Assessing hematopoietic (stem-) cell behavior during regenerative pressure

Hematopoiesis is a complex and strongly regulated process. In case of regenerative pressure, efficient recovery of blood cell counts is crucial for survival of an individual. We propose a quantitative mathematical model of white blood cell formation based on the following cell parameters: (1) proliferation rate, (2) self-renewal, and (3) cell death. Simulating this model we assess the change of these parameters under regenerative pressure. The proposed model allows to quantitatively describe the impact of these cell parameters on engraftment time after stem cell transplantation. Results indicate that enhanced self-renewal during the posttransplant period is crucial for efficient regeneration of blood cell counts while constant or reduced self-renewal leads to delayed recovery or graft failure. Increased cell death in the posttransplant period has a similar impact. In contrast, reduced proliferation or pre-homing cell death causes only mild delays in blood cell recovery which can be compensated sufficiently by increasing the dose of transplanted cells.

Stem cell clonality -- theoretical concepts, experimental techniques, and clinical challenges

Here we report highlights of discussions and results presented at an International Workshop on Concepts and Models of Stem Cell Organization held on July 16th and 17th, 2012 in Dresden, Germany. The goal of the workshop was to undertake a systematic survey of state-of-the-art methods and results of clonality studies of tissue regeneration and maintenance with a particular emphasis on the hematopoietic system. The meeting was the 6th in a series of similar conceptual workshops, termed StemCellMathLab,(2) all of which have had the general objective of using an interdisciplinary approach to discuss specific aspects of stem cell biology. The StemCellMathLab 2012, which was jointly organized by the Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology and the Institute for Medical Informatics, Statistics and Epidemiology, Medical Faculty, University of Leipzig, brought together 32 scientists from 8 countries, with scientific backgrounds in medicine, cell biology, virology, physics, computer sciences, bioinformatics and mathematics. The workshop focused on the following questions: (1) How heterogeneous are stem cells and their progeny? and (2) What are the characteristic differences in the clonal dynamics between physiological and pathophysiological situations? In discussing these questions, particular emphasis was placed on (a) the methods for quantifying clones and their dynamics in experimental and clinical settings and (b) general concepts and models for their description. In this workshop summary we start with an introduction to the current state of clonality research and a proposal for clearly defined terminology. Major topics of discussion include clonal heterogeneity in unperturbed tissues, clonal dynamics due to physiological and pathophysiological pressures and conceptual and technical issues of clone quantification. We conclude that an interactive cross-disciplinary approach to research in this field will continue to promote a conceptual understanding of tissue organization.

Therapy of chronic myeloid leukaemia can benefit from the activation of stem cells: simulation studies of different treatment combinations

Background:

Newly diagnosed patients with chronic myeloid leukaemia (CML) are currently treated with tyrosine kinase inhibitors (TKIs) such as imatinib, nilotinib or dasatinib. However, incomplete eradication of residual disease is a general problem of long-term TKI therapy. Activation of mouse haematopoietic stem cells by interferon-α (IFNα) stimulated the discussion of whether a combination treatment leads to accelerated eradication of the CML clone.

Methods:

We base our simulation approach on a mathematical model describing human CML as a competition phenomenon between normal and malignant cells. We amend this model to incorporate the description of IFNα activity and simulate different scenarios for potential treatment combinations.

Results:

We demonstrate that the overall sensitivity of CML stem cells to IFNα activation is a crucial determinant for the benefit of a potential combination therapy. We furthermore show that pulsed IFNα together with continuous TKI administration is the most promising strategy for a combination treatment in which the therapeutic benefit prevails adverse side effects.

Conclusion:

Our modelling approach is a highly beneficial tool to quantitatively address the competition between normal and leukaemic haematopoiesis in treated CML patients. We derive testable predictions for different experimental settings that are suggested before the clinical implementation of the combination treatment.

Stem cell heterogeneity: implications for aging and regenerative medicine

For decades, hematopoietic stem cells (HSCs) were thought to be a homogeneous population of cells with flexible behavior. Now a new picture has emerged: The HSC compartment consists of several subpopulations of HSCs each with distinct, preprogrammed differentiation and proliferation behaviors. These programs are epigenetically fixed and are stably bequeathed to all daughter HSCs on self-renewal. HSCs within each subset are remarkably similar in their self- renewal and differentiation behaviors, to the point where their life span can be predicted with mathematical certainty. Three subsets can be distinguished when HSCs are classified by their differentiation capacity: myeloid-biased, balanced, and lymphoid-biased HSCs. The relative number of the HSC subsets is developmentally regulated. Lymphoid-biased HSCs are found predominantly early in the life of an organism, whereas myeloid-biased HSCs accumulate in aged mice and humans. Thus, the discovery of distinct subpopulations of HSCs has led to a new understanding of HCS aging. This finding has implications for other aspects of HSC biology and applications in re-generative medicine. The possibility that other adult tissue stem cells show similar heterogeneity and mechanisms of aging is discussed.

Stochastic modeling of adipogenesis in 3T3-L1 cultures to determine probabilities of events in the cell's life cycle

3T3-L1 preadipocytes are often being used in research of adipose-related diseases such as obesity, insulin resistance, and hyperlipidemia. We developed a stochastic model that simulated differentiation of four 3T3-L1 culture conditions distinct by the insulin concentration in the differentiation medium (2.5, 5, 7.5, or 10 μg/mL). The model simulated culture behavior and the accumulation of lipid droplets in the maturing cells from the day of induction of differentiation through 28 days after that. The cellular processes including cell adhesion, mitosis, growing after undergoing mitosis, commitment to the adipocyte lineage, and apoptosis were referred to as stochastic events in the modeling. By minimizing the error between our model and experimental results, we found that the probability for becoming committed to the adipocyte lineage in a single division and the probability for growing after undergoing mitosis were 0.02 and 0.8, respectively, regardless of the insulin concentration. The probability for undergoing mitosis was equal to 0.2 and 0.4 in cultures that had insulin concentrations of 2.5 and 5-10 μg/mL in the differentiation medium, respectively; hence the insulin concentration affected the probability for mitosis in the 3T3-L1 cells. The model and resulted probabilities now allow quantitative and visual predictions of adipogenesis in 3T3-L1 cultures, toward computational design of cell culturing protocols.

Cellular aging leads to functional heterogeneity of hematopoietic stem cells: a modeling perspective

Hematopoietic stem cells (HSCs) are the source for the life-long supply of functional cells in peripheral blood while they simultaneously maintain their own reserve pool. However, there is accumulating evidence that HSCs are themselves subject to quantitative and qualitative exhaustion. Although several processes linked to mitotic activity can potentially account for the observed aging phenomena (e.g., DNA damage, telomere shortening, epigenetic modification), a precise understanding of HSC exhaustion is still missing. It is particularly unclear how individual aging processes on the single-cell level translate on the phenotypic level of the overall tissue and whether there is a functional implication of an age-structured HSC population. We address these issues by applying a novel mathematical model of HSC organization in which division-specific, cumulative alterations of stem cell quality determine the phenotypic and functional appearance of the overall cell population. Adapting the model to a number of basic experimental findings, we quantify the level of additional heterogeneity that is introduced by a population of individually aging cells. Based on this model, we are able to conclude that division-dependent processes of cellular aging explain a wide range of phenomena on HSC exhaustion and that HSC aging needs to be considered as a highly heterogeneous process. We furthermore report that functional heterogeneity between young and old HSCs appears closely similar to the phenomena described for long- and short-term repopulating cells. We speculate whether differential, division-coupled stem cell aging introduces an intra-animal variability that also accounts for heterogeneity with respect to the repopulation ability of HSCs.

Polyclonal fluctuation of lentiviral vector–transduced and expanded murine hematopoietic stem cells

Gene therapy has proven its potential to cure diseases of the hematopoietic system. However, severe adverse events observed in clinical trials have demanded improved gene-transfer conditions. Whereas progress has been made to reduce the genotoxicity of integrating gene vectors, the role of pretransplantation cultivation is less well investigated. We observed that the STIF (stem cell factor [SCF], thrombopoietin [TPO], insulin-like growth factor-2 [IGF-2], and fibroblast growth factor-1 [FGF-1]) cytokine cocktail developed to effectively expand murine hematopoietic stem cells (HSCs) also supports the expansion of leukemia-initiating insertional mutants caused by gammaretroviral gene transfer. We compared 4 protocols to examine the impact of prestimulation and posttransduction culture in STIF in the context of lentiviral gene transfer. Observing 56 transplanted mice for up to 9.5 months, we found consistent engraftment and gene-marking rates after prolonged ex vivo expansion. Although a lentiviral vector with a validated insertional-mutagenic potential was used, longitudinal analysis identifying > 7000 integration sites revealed polyclonal fluctuations, especially in “expanded” groups, with de novo detection of clones even at late time points. Posttransduction expansion in STIF did not enrich clones with insertions in proto-oncogenes but rather increased clonal diversity. Our data indicate that lentiviral transduction in optimized media mediates intact polyclonal hematopoiesis without selection for growth-promoting hits by posttransduction expansion.

Modeling the clonal heterogeneity of stem cells

Recent experimental studies suggest that tissue stem cell pools are composed of functionally diverse clones. Metapopulation models in ecology concentrate on collections of populations and their role in stabilizing coexistence and maintaining selected genetic or epigenetic variation. Such models are characterized by expansion and extinction of spatially distributed populations. We develop a mathematical framework derived from the multispecies metapopulation model of Tilman et al (1994) to study the dynamics of heterogeneous stem cell metapopulations. In addition to normal stem cells, the model can be applied to cancer cell populations and their response to treatment. In our model disturbances may lead to expansion or contraction of cells with distinct properties, reflecting proliferation, apoptosis, and clonal competition. We first present closed-form expressions for the basic model which defines clonal dynamics in the presence of exogenous global disturbances. We then extend the model to include disturbances which are periodic and which may affect clones differently. Within the model framework, we propose a method to devise an optimal strategy of treatments to regulate expansion, contraction, or mutual maintenance of cells with specific properties.

Single-cell and coupled GRN models of cell patterning in the Arabidopsis thaliana root stem cell niche

BACKGROUND

Recent experimental work has uncovered some of the genetic components required to maintain the Arabidopsis thaliana root stem cell niche (SCN) and its structure. Two main pathways are involved. One pathway depends on the genes SHORTROOT and SCARECROW and the other depends on the PLETHORA genes, which have been proposed to constitute the auxin readouts. Recent evidence suggests that a regulatory circuit, composed of WOX5 and CLE40, also contributes to the SCN maintenance. Yet, we still do not understand how the niche is dynamically maintained and patterned or if the uncovered molecular components are sufficient to recover the observed gene expression configurations that characterize the cell types within the root SCN. Mathematical and computational tools have proven useful in understanding the dynamics of cell differentiation. Hence, to further explore root SCN patterning, we integrated available experimental data into dynamic Gene Regulatory Network (GRN) models and addressed if these are sufficient to attain observed gene expression configurations in the root SCN in a robust and autonomous manner.

RESULTS

We found that an SCN GRN model based only on experimental data did not reproduce the configurations observed within the root SCN. We developed several alternative GRN models that recover these expected stable gene configurations. Such models incorporate a few additional components and interactions in addition to those that have been uncovered. The recovered configurations are stable to perturbations, and the models are able to recover the observed gene expression profiles of almost all the mutants described so far. However, the robustness of the postulated GRNs is not as high as that of other previously studied networks.

CONCLUSIONS

These models are the first published approximations for a dynamic mechanism of the A. thaliana root SCN cellular pattering. Our model is useful to formally show that the data now available are not sufficient to fully reproduce root SCN organization and genetic profiles. We then highlight some experimental holes that remain to be studied and postulate some novel gene interactions. Finally, we suggest the existence of a generic dynamical motif that can be involved in both plant and animal SCN maintenance.

Heterogeneity of non-cycling and cycling synchronized murine hematopoietic stem/progenitor cells

Purified long-term multilineage repopulating marrow stem cells have been considered to be homogenous, but functionally these cells are heterogeneous. Many investigators urge clonal studies to define stem cells but, if stem cells are truly heterogeneous, clonal studies can only define heterogeneity. We have determined the colony growth and differentiation of individual lineage negative, rhodamine low, Hoechst low (LRH) stem cells at various times in cytokine culture, corresponding to specific cell cycle stages. These highly purified and cycle synchronized (98% in S phase at 40 h of culture) stem cells were exposed to two cytokine cocktails for 0, 18, 32, or 40 h and clonal differentiation assessed 14 days later. Total heterogeneity as to gross colony morphology and differentiation stage was demonstrated. This heterogeneity showed patterns of differentiation at different cycle times. These data hearken to previous suggestions that stem cells might be similar to radioactive isotopes; decay rate of a population of radioisotopes being highly predictable, while the decay of individual nuclei is heterogeneous and unpredictable (Till et al., 1964). Marrow stem cells may be most adequately defined on a population basis; stem cells existing in a continuum of reversible change rather than a hierarchy.

Stem cell transplant into preimplantation embryo yields myocardial infarction-resistant adult phenotype

Stem cells are an emerging strategy for treatment of myocardial infarction, limited however to postinjury intervention. Preventive stem cell-based therapy to augment stress tolerance has yet to be considered for lifelong protection. Here, pluripotent stem cells were microsurgically introduced at the blastocyst stage of murine embryo development to ensure stochastic integration and sustained organ contribution. Engineered chimera displayed excess in body weight due to increased fat deposits, but were otherwise devoid of obesity-related morbidity. Remarkably, and in sharp contrast to susceptible nonchimeric offspring, chimera was resistant to myocardial infarction induced by permanent coronary occlusion. Infarcted nonchimeric adult hearts demonstrated progressive deterioration in ejection fraction, while age-matched 12-14-months-old chimera recovered from equivalent ischemic insult to regain within one-month preocclusion contractile performance. Electrical remodeling and ventricular enlargement with fibrosis, prominent in failing nonchimera, were averted in the chimeric cohort characterized by an increased stem cell load in adipose tissue and upregulated markers of biogenesis Ki67, c-Kit, and stem cell antigen-1 in the myocardium. Favorable outcome in infarcted chimera translated into an overall benefit in workload capacity and survival. Thus, prenatal stem cell transplant yields a cardioprotective phenotype in adulthood, expanding cell-based indications beyond traditional postinjury applications to include pre-emptive therapy.

Stem cell proliferation and quiescence--two sides of the same coin

The kinetics of label uptake and dilution in dividing stem cells, e.g., using Bromodeoxyuridine (BrdU) as a labeling substance, are a common way to assess the cellular turnover of all hematopoietic stem cells (HSCs) in vivo. The assumption that HSCs form a homogeneous population of cells which regularly undergo cell division has recently been challenged by new experimental results. For a consistent functional explanation of heterogeneity among HSCs, we propose a concept in which stem cells flexibly and reversibly adapt their cycling state according to systemic needs. Applying a mathematical model analysis, we demonstrate that different experimentally observed label dilution kinetics are consistently explained by the proposed model. The dynamically stabilized equilibrium between quiescent and activated cells leads to a biphasic label dilution kinetic in which an initial and pronounced decline of label retaining cells is attributed to faster turnover of activated cells, whereas a secondary, decelerated decline results from the slow turnover of quiescent cells. These results, which support our previous model prediction of a reversible activation/deactivation of HSCs, are also consistent with recent findings that use GFP-conjugated histones as a label instead of BrdU. Based on our findings we interpret HSC organization as an adaptive and regulated process in which the slow activation of quiescent cells and their possible return into quiescence after division are sufficient to explain the simultaneous occurrence of self-renewal and differentiation. Furthermore, we suggest an experimental strategy which is suited to demonstrate that the repopulation ability among the population of label retaining cells changes during the course of dilution.

Hematopoietic stem cells (HSCs) are among the best-studied populations of adult stem cells. Commonly HSCs are considered to be in a so called quiescent state of reduced cellular turnover. However, it appears that even quiescent HSCs are activated into the cell cycle from time to time to support the continuous production of peripheral blood. Previous reports on cell kinetic studies using specific chromosomal labeling techniques suggest that all HSCs regularly undergo cell divisions on average once in two weeks. However, these results are challenged by recent experimental findings supporting the idea that HSC populations are heterogeneous with respect to their cell cycle activity. Applying an established model of HSC organization, we demonstrate that different data sets can be consistently explained by the assumption that HSCs are reversibly switching between a quiescent and an activated state. Based on this assumption, we provide a functional explanation for the experimentally observed biphasic label dilution kinetics of HSCs. We conclude that the ability of these cells to reversibly change between proliferation and quiescence is a critical and inherent property of the HSC system necessary for the sustained balance between stem cell self-renewal and the maintenance of functional blood cells.

From genes to cells to tissues--modelling the haematopoietic system

Haematopoiesis (or blood formation) in general and haematopoietic stem cells more specifically represent some of the best studied mammalian developmental systems. Sophisticated purification protocols coupled with powerful biological assays permit functional analysis of highly purified cell populations both in vitro and in vivo. However, despite several decades of intensive research, the sheer complexity of the haematopoietic system means that many important questions remain unanswered or even unanswerable with current experimental tools. Scientists have therefore increasingly turned to modelling to tackle complexity at multiple levels ranging from networks of genes to the behaviour of cells and tissues. Early modelling attempts of gene regulatory networks have focused on core regulatory circuits but have more recently been extended to genome-wide datasets such as expression profiling and ChIP-sequencing data. Modelling of haematopoietic cells and tissues has provided insight into the importance of phenotypic heterogeneity for the differentiation of normal progenitor cells as well as a greater understanding of treatment response for particular pathologies such as chronic myeloid leukaemia. Here we will review recent progress in attempts to reconstruct segments of the haematopoietic system. A variety of modelling strategies will be covered from small-scale, protein-DNA or protein-protein interactions to large scale reconstructions. Also discussed will be examples of how stochastic modelling may be applied to multi cell systems such as those seen in normal and malignant haematopoiesis.

A novel view on stem cell development: analysing the shape of cellular genealogies

OBJECTIVES

The analysis of individual cell fates within a population of stem and progenitor cells is still a major experimental challenge in stem cell biology. However, new monitoring techniques, such as high-resolution time-lapse video microscopy, facilitate tracking and quantitative analysis of single cells and their progeny. Information on cellular development, divisional history and differentiation are naturally comprised into a pedigree-like structure, denoted as cellular genealogy. To extract reliable information concerning effecting variables and control mechanisms underlying cell fate decisions, it is necessary to analyse a large number of cellular genealogies.

MATERIALS AND METHODS

Here, we propose a set of statistical measures that are specifically tailored for the analysis of cellular genealogies. These measures address the degree and symmetry of cellular expansion, as well as occurrence and correlation of characteristic events such as cell death. Furthermore, we discuss two different methods for reconstruction of lineage fate decisions and show their impact on the interpretation of asymmetric developments. In order to illustrate these techniques, and to circumvent the present shortage of available experimental data, we obtain cellular genealogies from a single-cell-based mathematical model of haematopoietic stem cell organization.

RESULTS AND CONCLUSIONS

Based on statistical analysis of cellular genealogies, we conclude that effects of external variables, such as growth conditions, are imprinted in their topology. Moreover, we demonstrate that it is essential to analyse timing of cell fate-specific changes and of occurrence of cell death events in the divisional context in order to understand the mechanisms of lineage commitment.

Characterization and quantification of clonal heterogeneity among hematopoietic stem cells: a model-based approach

Hematopoietic stem cells (HSCs) show pronounced heterogeneity in self-renewal and differentiation behavior, which is reflected in their repopulation kinetics. Here, a single-cell-based mathematical model of HSC organization is used to examine the basis of HSC heterogeneity. Our modeling results, which are based on the analysis of limiting dilution competitive repopulation experiments in mice, demonstrate that small quantitative but clonally fixed differences of cellular properties are necessary and sufficient to account for the observed functional heterogeneity. The model predicts, and experimental data validate, that competitive pressures will amplify small clonal differences into large changes in the number of differentiated progeny. We further predict that the repertoire of HSC clones will evolve over time. Last, our results suggest that larger differences in cellular properties have to be assumed to account for genetically determined differences in HSC behavior as observed in different inbred mice strains. The model provides comprehensive systemic and quantitative insights into the clonal heterogeneity among HSCs with potential applications in predicting the behavior of malignant and/or genetically modified cells.

Long-term propagation of distinct hematopoietic differentiation programs in vivo

Heterogeneity in the differentiation behavior of hematopoietic stem cells is well documented but poorly understood. To investigate this question at a clonal level, we isolated a subpopulation of adult mouse bone marrow that is highly enriched for multilineage in vivo repopulating cells and transplanted these as single cells, or their short-term clonal progeny generated in vitro, into 352 recipients. Of the mice, 93 showed a donor-derived contribution to the circulating white blood cells for at least 4 months in one of four distinct patterns. Serial transplantation experiments indicated that two of the patterns were associated with extensive self-renewal of the original cell transplanted. However, within 4 days in vitro, the repopulation patterns subsequently obtained in vivo shifted in a clone-specific fashion to those with less myeloid contribution. Thus, primitive hematopoietic cells can maintain distinct repopulation properties upon serial transplantation in vivo, although these properties can also alter rapidly in vitro.

Gene network dynamics controlling keratinocyte migration

Translation of large-scale data into a coherent model that allows one to simulate, predict and control cellular behavior is far from being resolved. Assuming that long-term cellular behavior is reflected in the gene expression kinetics, we infer a dynamic gene regulatory network from time-series measurements of DNA microarray data of hepatocyte growth factor-induced migration of primary human keratinocytes. Transferring the obtained interactions to the level of signaling pathways, we predict in silico and verify in vitro the necessary and sufficient time-ordered events that control migration. We show that pulse-like activation of the proto-oncogene receptor Met triggers a responsive state, whereas time sequential activation of EGF-R is required to initiate and maintain migration. Context information for enhancing, delaying or stopping migration is provided by the activity of the protein kinase A signaling pathway. Our study reveals the complex orchestration of multiple pathways controlling cell migration.

Insertional mutagenesis and clonal dominance: biological and statistical considerations

Improvements of (retroviral) gene transfer vectors, stem cell isolation and culture techniques as well as transduction protocols eventually resulted not only in the successful genetic modification of cells capable of reconstituting the haematopoietic system in various animal models, but also human beings. This was a conditio sine qua non for the successful application of gene therapy for inherited diseases as meanwhile achieved for severe combined immune deficiencies (SCID-X1, ADA-SCID) and chronic granulomatous disease (CGD). Unexpectedly, in long-term animal experiments as well as in the follow up of patients from the CGD trial, haematopoietic clones bearing insertions in certain gene loci became dominant, which was most apparent in the myeloid blood compartment. Accumulating data strongly suggest that this clonal dominance was due to some growth and/or survival advantage conferred by gene-activating or -suppressing effects of the integrated retroviral vector (insertional mutagenesis). Importantly, such induced clonal dominance seems not to lead to malignant transformation of affected cell clones inadvertently. The latter finding has become the basis for the concept of 'induced haematopoietic stem cells', a potentially powerful tool to investigate genes involved in the regulation of mechanisms underlying competitive advantages of stem cells, but also in the multi-step nature of malignant transformation. Here we discuss promises and open issues of this concept as well as the important question of common insertion sites statistics and its pitfalls.

Asymmetry of stem cell fate and the potential impact of the niche: observations, simulations, and interpretations

Asymmetric cell division is a common concept to explain the capability of stem cells to simultaneously produce a continuous output of differentiated cells and to maintain their own population of undifferentiated cells. Whereas for some stem cell systems, an asymmetry in the division process has explicitly been demonstrated, no evidence for such a functional asymmetry has been shown for hematopoietic stem cells (HSC) so far. This raises the question regarding whether asymmetry of cell division is a prerequisite to explain obvious heterogeneity in the cellular fate of HSC. Through the application of a mathematical model based on self-organizing principles, we demonstrate that the assumption of asymmetric stem cell division is not necessary to provide a consistent account for experimentally observed asymmetries in the development of HSC. Our simulation results show that asymmetric cell fate can alternatively be explained by a reversible expression of functional stem cell potentials, controlled by changing cell-cell and cell-microenvironment interactions. The proposed view on stem cell organization is pointing to the potential role of stem cell niches as specific signaling environments, which induce developmental asymmetries and therefore, generate cell fate heterogeneity. The self-organizing concept is fully consistent with the functional definition of tissue stem cells. It naturally includes plasticity phenomena without contradicting a hierarchical appearance of the stem cell population. The concept implies that stem cell fate is only predictable in a probabilistic sense and that retrospective categorization of stem cell potential, based on individual cellular fates, provides an incomplete picture.

No Evidence of Clonal Dominance in Primates up to 4 Years Following Transplantation of Multidrug Resistance 1 Retrovirally Transduced Long-Term Repopulating Cells

Previous murine studies have suggested that retroviral multidrug resistance 1 (MDR1) gene transfer may be associated with a myeloproliferative disorder. Analyses at a clonal level and prolonged long-term follow-up in a model with more direct relevance to human biology were lacking. In this study, we analyzed the contribution of individual CD34-selected peripheral blood progenitor cells to long-term rhesus macaque hematopoiesis after transduction with a retroviral vector either expressing the multidrug resistance 1 gene (HaMDR1 vector) or expressing the neomycin resistance (NeoR) gene (G1Na vector). We found a total of 122 contributing clones from 8 weeks up to 4 years after transplantation. One hundred two clones contained the G1Na vector, whereas only 20 clones contained the HaMDR1 vector. Here, we show for the first time real-time polymerase chain reaction based quantification of individual transduced cell clones constituting 0.0008% +/- 0.0003% to 0.0041% +/- 0.00032% of primate peripheral blood cells. No clonal dominance was observed. Disclosure of potential conflicts of interest is found at the end of this article.

Global expression profiles from C57BL/6J and DBA/2J mouse lungs to determine aging-related genes

This study identified gene expression profiles that provided evidence for genomic mechanisms underlying the pathophysiology of aging lung. Aging lungs from C57BL/6 (B6) and DBA/2 (D2) mouse strains differ in physiology and morphometry. Lungs were harvested from B6 mice at 2, 18, and 26 mo and from D2 mice at 2 and 18 mo of age. Purified RNA was subjected to oligonucleotide microarray analyses, and differential expression analyses were performed for comparison of various data sets. A significant majority of differentially expressed genes were upregulated with aging in both strains. Aging D2 lungs uniquely exhibited upregulation in stress-response genes including xenobiotic detoxification cascades. In contrast, aging B6 lungs showed downregulation of heat shock-response genes. Age-dependent downregulation of genes common to both B6 and D2 strains included several collagen genes (e.g., Col1a1 and Col3a1). There was a greater elastin gene (Eln) expression in D2 mice at 2 mo, and Eln was uniquely downregulated with age in this strain. The matrix metalloproteinase 14 gene (Mmp14), critical to alveolar structural integrity, was also downregulated with aging in D2 mice only. Several polymorphisms in the regulatory and untranslated regions of Mmp14 were identified between strains, suggesting that variation in Mmp14 gene regulation contributes to accelerated aging of lungs in D2 mice. In summary, lungs of B6 and D2 mice age with variable rates at the gene expression level, and these quantifiable genomic differences provide a template for understanding the variability in age-dependent changes in lung structure and function.

Stem cell fate analysis revisited: interpretation of individual clone dynamics in the light of a new paradigm of stem cell organization

Many experimental findings on heterogeneity, flexibility, and plasticity of tissue stem cells are currently challenging stem cell concepts that assume a cell intrinsically predefined, unidirectional differentiation program. In contrast to these classical concepts, nonhierarchical self-organizing systems provide an elegant and comprehensive alternative to explain the experimental data. Here we present the application of such a self-organizing concept to quantitatively describe the hematopoietic stem cell system. Focusing on the analysis of individual-stem-cell fates and clonal dynamics, we particularly discuss implications of the theoretical results on the interpretation of experimental findings. We demonstrate that it is possible to understand hematopoietic stem cell organization without assumptions on unidirectional developmental hierarchies, preprogrammed asymmetric division events or other assumptions implying the existence of a predetermined stem cell entity. The proposed perspective, therefore, changes the general paradigm of thinking about stem cells.

Lineage specification of hematopoietic stem cells: mathematical modeling and biological implications

Lineage specification of hematopoietic stem cells is considered a progressive restriction in lineage potential. This view is consistent with observations that differentiation and lineage specification is preceded by a low-level coexpression of lineage specific, potentially antagonistic genes in early progenitor cells. This coexistence, commonly referred to as priming, disappears in the course of differentiation when certain lineage-restricted genes are upregulated while others are downregulated. Based on this phenomenological description, we propose a quantitative model that describes lineage specification as a competition process between different interacting lineage propensities. The competition is governed by environmental stimuli promoting a drift from a multipotent coexpression to the dominance of one lineage. The assumption of a context-dependent intracellular differentiation control is consistently embedded into our previously proposed model of hematopoietic stem cell organization. The extended model, which comprises self-renewal and lineage specification, is verified using available data on the lineage specification potential of primary hematopoietic stem cells and on the differentiation kinetics of the FDCP-mix cell line. The model provides a number of experimentally testable predictions. From our results, we conclude that lineage specification is best described as a flexible and temporally extended process in which lineage commitment emerges as the result of a sequence of small decision steps. The proposed model provides a novel systems biological view on the functioning of lineage specification in adult tissue stem cells and its connections to the self-renewal properties of these cells. Disclosure of potential conflicts of interest is found at the end of this article.

Dynamic modeling of imatinib-treated chronic myeloid leukemia: functional insights and clinical implications

Treatment of chronic myeloid leukemia (CML) with the tyrosine kinase inhibitor imatinib represents a successful application of molecularly targeted cancer therapy. A rapid hematologic and cytogenetic response can be induced in the majority of people, even in advanced disease. However, complete eradication of malignant cells, which are characterized by the expression of the BCR-ABL1 fusion protein, is rare. Reasons for the persistence of the malignant clone are currently not known and provide a substantial challenge for clinicians and biologists. Based on a mathematical modeling approach that quantitatively explains a broad range of phenomena, we show for two independent datasets that clinically observed BCR-ABL1 transcript dynamics during imatinib treatment of CML can consistently be explained by a selective functional effect of imatinib on proliferative leukemia stem cells. Our results suggest the general potential of imatinib to induce a complete elimination of the malignant clone. Moreover, we predict that the therapeutic benefit of imatinib can, under certain circumstances, be accelerated by combination with proliferation-stimulating treatment strategies.

Individual cell-based models of the spatial-temporal organization of multicellular systems--achievements and limitations

Computational approaches of multicellular assemblies have reached a stage where they may contribute to unveil the processes that underlie the organization of tissues and multicellular aggregates. In this article, we briefly review and present some new results on a number of 3D lattice free individual cell-based mathematical models of epithelial cell populations. The models we consider here are parameterized by bio-physical and cell-biological quantities on the level of an individual cell. Eventually, they aim at predicting the dynamics of the biological processes on the tissue level. We focus on a number of systems, the growth of cell populations in vitro, and the spatial-temporal organization of regenerative tissues. For selected examples we compare different model approaches and show that the qualitative results are robust with respect to many model details. Hence, for the qualitative features and largely for the quantitative features many model details do not matter as long as characteristic biological features and mechanisms are correctly represented. For a quantitative prediction, the control of the bio-physical and cell-biological parameters on the molecular scale has to be known. At this point, slide-based cytometry may contribute. It permits to track the fate of cells and other tissue subunits in time and validated the organization processes predicted by the mathematical models.

Quantitative stem cell biology: computational studies in the hematopoietic system

PURPOSE OF REVIEW

This review is intended to provide an overview of recently published computational methods, including bioinformatic algorithms, mathematical models and simulation studies, applied to stem cell biology, with particular reference to the hematopoietic system.

RECENT FINDINGS

The analysis of molecular data is making an increased contribution to identify dynamic system responses. Specifically, there are promising computational approaches to characterizing the functional interrelation of network components regulating the process of differentiation and lineage specification of hematopoietic stem cells. Furthermore, evidence is accumulating that stem cell organization should be regarded as a flexible, self-organizing process rather than as a predetermined sequence of events. A number of mathematical models relevant to the hematopoietic (stem cell) system are applied successfully to clinical situations, demonstrating the predictive power of theoretical methods.

SUMMARY

Based on the advances in measurement technology, an increasing amount of cellular and molecular data is being generated within the field of stem cell biology. The complexity of the underlying systems, however, most often limits a direct interpretation of the data and makes computational methods indispensable. Mathematical models and simulation techniques are contributing considerably to the discovery of general regulatory principles of stem cell organization and are providing clinically relevant predictions.