Modeling spatial population dynamics of stem cell lineage in tissue growth

Cao, Youfang; Liang, Claire; Naveed, Hammad; Li, Yingzi; Chen, Meng; Nie, Qing

doi:10.1109/embc.2012.6347240

Cited by 8 publications

(8 citation statements)

References 15 publications

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“…We explore the effects of inhibition range of secreted factor to stem cell growth, as well as the effects of symmetric vs asymmetric cell divisions of stem cells. Additional detailed study of other aspects of tissue size control can be found in [ 101 ].…”

Section: Resultsmentioning

confidence: 99%

Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

et al. 2015

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Geometric and mechanical properties of individual cells and interactions among neighboring cells are the basis of formation of tissue patterns. Understanding the complex interplay of cells is essential for gaining insight into embryogenesis, tissue development, and other emerging behavior. Here we describe a cell model and an efficient geometric algorithm for studying the dynamic process of tissue formation in 2D (e.g. epithelial tissues). Our approach improves upon previous methods by incorporating properties of individual cells as well as detailed description of the dynamic growth process, with all topological changes accounted for. Cell size, shape, and division plane orientation are modeled realistically. In addition, cell birth, cell growth, cell shrinkage, cell death, cell division, cell collision, and cell rearrangements are now fully accounted for. Different models of cell-cell interactions, such as lateral inhibition during the process of growth, can be studied in detail. Cellular pattern formation for monolayered tissues from arbitrary initial conditions, including that of a single cell, can also be studied in detail. Computational efficiency is achieved through the employment of a special data structure that ensures access to neighboring cells in constant time, without additional space requirement. We have successfully generated tissues consisting of more than 20,000 cells starting from 2 cells within 1 hour. We show that our model can be used to study embryogenesis, tissue fusion, and cell apoptosis. We give detailed study of the classical developmental process of bristle formation on the epidermis of D. melanogaster and the fundamental problem of homeostatic size control in epithelial tissues. Simulation results reveal significant roles of solubility of secreted factors in both the bristle formation and the homeostatic control of tissue size. Our method can be used to study broad problems in monolayered tissue formation. Our software is publicly available.

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Section: Resultsmentioning

confidence: 99%

Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

et al. 2015

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“…A novel temporal-spatial cell population dynamics model has been developed to realistically model wound healing by combining a realistic cell growth model [13] with the population dynamics of stem cell niche and lineages [14]. The geometries and forces for cell growth and divisions are incorporated in the cell growth model, and the growth rates and division types after receiving inhibitions from surrounding differentiated cells are modeled individually in negative feedback controls.…”

Section: Discussionmentioning

confidence: 99%

Modeling spatial population dynamics of stem cell lineage in wound healing and cancerogenesis

Cao

Naveed

Liang

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Modeling the dynamics of cell population in tissues involving stem cell niches allows insight into the control mechanisms of the important wound healing process. It is well known that growth and divisions of stem cells are mainly repressed by niche cells, but can also be activated by signals released from wound. In addition, the proliferation and differentiation among three different types of cell: stem cells (SCs), intermediate progenitor cells (IPCs), and fully differentiated cells (FDCs) in stem cell lineage are under different activation and inhibition controls. We have developed a novel stochastic spatial dynamic model of cells. We can characterize not only overall cell population dynamics, but also details of temporalspatial relationship of individual cells within a tissue. In our model, the shape, growth, and division of each cell are modeled using a realistic geometric model. Furthermore, the inhibited growth rate, proliferation and differentiation probabilities of individual cells are modeled through feedback loops controlled by secreted factors and wound signals from neighboring cells. With specific proliferation and differentiation probabilities, the actual division type that each cell will take is chosen by a Monte Carlo sampling process. With simulations, we study the effects of different strengths of wound signals to wound healing behaviors. We also study the correlations between chronic wound and cancerogenesis.

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“…Zhang et al (2012) presented a partial differential equation (PDE)model of Wnt, BMP and their feedback regulation on a colon crypt cell lineage, which included separate compartments for stem/transit amplifying cells and terminally differentiated cells, and studied mechanisms for intestinal crypt formation. Cao et al (2012) modeled stem, progenitor and differentiated cells as geometric objects and showed that negative feedback on cell division and self-renewal contributes to homeostatic size control in tissue development. Smallbone and Corfe (2014) developed data-driven models that capture feedback control between stem and differentiated cells.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Spatiotemporal Modeling of Colon Cancer Organoids Reveals that Multimodal Control of Stem Cell Self-Renewal is a Critical Determinant of Size and Shape in Early Stages of Tumor Growth

2017

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We develop a three-dimensional multispecies mathematical model to simulate the growth of colon cancer organoids containing stem, progenitor and terminally differentiated cells, as a model of early (prevascular) tumor growth. Stem cells (SCs) secrete short-range self-renewal promoters (e.g., Wnt) and their long-range inhibitors (e.g., Dkk) and proliferate slowly. Committed progenitor (CP) cells proliferate more rapidly and differentiate to produce post-mitotic terminally differentiated cells that release differentiation promoters, forming negative feedback loops on SC and CP self-renewal. We demonstrate that SCs play a central role in normal and cancer colon organoids. Spatial patterning of the SC self-renewal promoter gives rise to SC clusters, which mimic stem cell niches, around the organoid surface, and drive the development of invasive fingers. We also study the effects of externally applied signaling factors. Applying bone morphogenic proteins, which inhibit SC and CP self-renewal, reduces invasiveness and organoid size. Applying hepatocyte growth factor, which enhances SC self-renewal, produces larger sizes and enhances finger development at low concentrations but suppresses fingers at high concentrations. These results are consistent with recent experiments on colon organoids. Because many cancers are hierarchically organized and are subject to feedback regulation similar to that in normal tissues, our results suggest that in cancer, control of cancer stem cell self-renewal should influence the size and shape in similar ways, thereby opening the door to novel therapies.

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Modeling spatial population dynamics of stem cell lineage in tissue growth

Cited by 8 publications

References 15 publications

Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

Mechanical Model of Geometric Cell and Topological Algorithm for Cell Dynamics from Single-Cell to Formation of Monolayered Tissues with Pattern

Modeling spatial population dynamics of stem cell lineage in wound healing and cancerogenesis

Three-Dimensional Spatiotemporal Modeling of Colon Cancer Organoids Reveals that Multimodal Control of Stem Cell Self-Renewal is a Critical Determinant of Size and Shape in Early Stages of Tumor Growth

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