Discrete stem cells: subsets or a continuum?
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Animals↗
Biomedical subjects
Ingo Roeder
Publications and source records attributed to Ingo Roeder.
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.
Algorithms↗
Towards an understanding of lineage specification in hematopoietic stem cells: a mathematical model for the interaction of transcription factors GATA-1 and PU.1.
In addition to their self-renewal capabilities, hematopoietic stem cells guarantee the continuous supply of fully differentiated, functional cells of various types in the peripheral blood. The process which controls differentiation into the different lineages of the hematopoietic system (erythroid, myeloid, lymphoid) is referred to as lineage specification. It requires a potentially multi-step decision sequence which determines the fate of the cells and their successors. It is generally accepted that lineage specification is regulated by a complex system of interacting transcription factors. However, the underlying principles controlling this regulation are currently unknown. Here, we propose a simple quantitative model describing the interaction of two transcription factors. This model is motivated by experimental observations on the transcription factors GATA-1 and PU.1, both known to act as key regulators and potential antagonists in the erythroid vs. myeloid differentiation processes of hematopoietic progenitor cells. We demonstrate the ability of the model to account for the observed switching behavior of a transition from a state of low expression of both factors (undifferentiated state) to the dominance of one factor (differentiated state). Depending on the parameter choice, the model predicts two different possibilities to explain the experimentally suggested, stem cell characterizing priming state of low level co-expression. Whereas increasing transcription rates are sufficient to induce differentiation in one scenario, an additional system perturbation (by stochastic fluctuations or directed impulses) of transcription factor levels is required in the other case.
Cell Differentiation↗
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.
Algorithms↗
In vitro, clinical, and microbiological evaluation of a linear oscillating device for scaling and root planing.
BACKGROUND: The purpose of this study was to conduct an in vitro and short-term clinical and microbiological evaluation of a linear oscillating device for scaling and root planing (SRP). A comparison was made between conventional ultrasonic scaling (US) and hand scaling (HS) with and without chlorhexidine. METHODS: In vitro, SRP was carried out on human teeth with calculus. Roots and cross-sections thereof were microscopically examined for the efficacy of calculus removal, hard tissue loss, and surface smoothness. In vivo, 11 patients with chronic periodontitis and single-rooted teeth in all quadrants with probing depths of > or =5 mm were selected. One quadrant was treated with linear oscillation and compared to US with chlorhexidine irrigation in the contralateral site. The other arch was treated with HS and compared to HS followed by laser disinfection. One hundred twenty teeth were assessed for clinical attachment level, probing depth, bleeding on probing, and suppuration at baseline and 7, 28, 90, and 180 days. Microbiologically, total numbers of bacteria and six specific periodontal pathogens were determined by quantitative polymerase chain reaction prior to and 1 and 28 days after SRP. Clinical and microbiological data were analyzed statistically with respect to the SRP method, patient specificity, and time effect. RESULTS: In vitro, linear oscillation preserved more root tissues but left more calculus (P <0.05). Significant improvements of all clinical and microbiological parameters were observed for all groups. However, 21 out of 24 tests demonstrated that the clinical microbiological correlations between linear oscillation and control groups did not differ (P <0.05). CONCLUSION: Linear oscillation scaling was clinically acceptable and microbiologically comparable to the control groups despite microscopic remnants of calculus observed in vitro.
Adult↗
Competitive clonal hematopoiesis in mouse chimeras explained by a stochastic model of stem cell organization.
Many current experimental results show the necessity of new conceptual approaches to understand hematopoietic stem cell organization. Recently, we proposed a novel theoretical concept and a corresponding quantitative model based on microenvironment-dependent stem cell plasticity. The objective of our present work is to subject this model to an experimental test for the situation of chimeric hematopoiesis. Investigating clonal competition processes in DBA/2-C57BL/6 mouse chimeras, we observed biphasic chimerism development with initially increasing but long-term declining DBA/2 contribution. These experimental results were used to select the parameters of the mathematical model. To validate the model beyond this specific situation, we fixed the obtained parameter configuration to simulate further experimental settings comprising variations of transplanted DBA/2-C57BL/6 proportions, secondary transplantations, and perturbation of stabilized chimeras by cytokine and cytotoxic treatment. We show that the proposed model is able to consistently describe the situation of chimeric hematopoiesis. Our results strongly support the view that the relative growth advantage of strain-specific stem cells is not a fixed cellular property but is sensitively dependent on the actual state of the entire system. We conclude that hematopoietic stem cell organization should be understood as a flexible, self-organized rather than a fixed, preprogrammed process.
Animals↗
Conceptual models to understand tissue stem cell organization.
PURPOSE OF REVIEW: Theoretic and, in particular, mathematic models can help biologists to select and design experiments, to highlight general principles, to discriminate similar and to link different phenomena, and to predict novel features. Specifically, they contribute to an understanding of latent mechanisms and crucial parameters of biologic processes. The following review gives an overview of recent developments in the field of hematopoietic tissue stem cell modeling. RECENT FINDINGS: A number of experimental findings on heterogeneity, flexibility, and plasticity of hematopoietic and other tissue stem cells are challenging the classic stem cell concept of a predefined intrinsic stem cell program. Self-organizing systems provide a more elegant and comprehensive alternative to explain experimental data. SUMMARY: Within the last few decades, modeling approaches in stem cell biology have evolved and now encompass a broad spectrum of phenomena, ranging from the cellular level to the tissue level. The application of theoretic models is currently suggesting that we abandon the classic assumption of a strict developmental hierarchy and understand stem cell organization as a dynamic, functional process. Such a perspective has implications for a prospective characterization of tissue stem cells (eg, regarding gene expression profiles and genetic regulation patterns).
Animals↗
Quantitative tissue stem cell modeling.
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Cell Cycle↗
A novel dynamic model of hematopoietic stem cell organization based on the concept of within-tissue plasticity.
OBJECTIVE: At present, no dynamic quantitative models of stem cell organization are available that fulfill all criteria of the prevalent functional definition of hematopoietic stem cells and, at the same time, provide a consistent explanation of cell kinetic and functional stem cell heterogeneity, reversibility of cellular properties, self-organized regeneration after damage, fluctuating activity and competition of stem cell clones, and microenvironment dependency of stem cell quality. To solve this problem, we propose a new, comprehensive model concept. MATERIALS AND METHODS: A single cell-based stochastic model is described. It makes the novel concept of within-tissue plasticity operational. Within a range of potential options, individual cells may reversibly change their actual set of properties depending on the influence of the local growth environment. Stochastic switching between the growth environments introduces fluctuations that eventually generate heterogeneity. Extensive model simulations are compared with experimental data. RESULTS: Although stemness is not an explicit cellular model property, the system behavior is consistent with the functional definition of stem cells and explains a large set of experimental observations on stem cell function in vivo and in vitro on the level of cell populations and individual cells. Classic results such as the colony-forming unit spleen assay, as well as recent experimental observations on stem cell kinetics, individual clone tracking, and fluctuating clonal contribution, are discussed. CONCLUSIONS: This concept introduces a fundamentally new perspective on stem cell organization treating stemness not as an explicit cellular property but as the result of a dynamic process of self-organization. The model needs to be extended to incorporate lineage specification and tissue plasticity.
Animals↗
Tissue stem cells: definition, plasticity, heterogeneity, self-organization and models--a conceptual approach.
The classical definition of adult tissue stem cells (TSC) is fundamentally based on a functional perspective. A TSC is an undifferentiated cell, capable of proliferation, self-renewal, production of a large number of differentiated functional progeny, regenerating tissue after injury and a flexibility in the use of these options. Here, we discuss the necessity for amending this definition in the light of recent insight into stem cell biology regarding stem cell heterogeneity, lineage plasticity, clonal fluctuation and cell-environment interactions. We conclude that the definition needs amendments. A decade ago the flexibility criterion has attracted little attention but recent findings have indicated its importance. Flexibility and reversibility of tissue and lineage specification (tissue plasticity) and of properties within a tissue (within-tissue plasticity) have major implications with regard to concepts of stem cell function. We advocate to give up the view of TSC as being entities with a preprogrammed development and to replace it by a concept that makes the capabilities for flexible and regulated tissue self-organization based on cell-cell and cell-environment interactions the new paradigm. This concept would permit to incorporate the context-dependent lineage plasticity, within-lineage plasticity and generation of stem cell heterogeneity as a result of a dynamically regulated process. Such concepts need a rigorous examination by formal modeling including simulation studies. We provide some general ideas on how to proceed with such theories and illustrate this with worked models for tissue stem cells of the hematopoietic system and the intestinal epithelium.
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