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

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 temporal-spatial 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.

[1]  Anne L. Calof,et al.  Autoregulation of Neurogenesis by GDF11 , 2003, Neuron.

[2]  E. Fuchs,et al.  Socializing with the Neighbors Stem Cells and Their Niche , 2004, Cell.

[3]  A. Lander Pattern, Growth, and Control , 2011, Cell.

[4]  Fiona M. Watt,et al.  Epithelial stem cells, wound healing and cancer , 2012, Nature Reviews Cancer.

[5]  Q. Nie,et al.  Cell Lineages and the Logic of Proliferative Control , 2009, PLoS biology.

[6]  A. Singer,et al.  Cutaneous wound healing. , 1999, The New England journal of medicine.

[7]  Avner Friedman,et al.  A mathematical model of ischemic cutaneous wounds , 2009, Proceedings of the National Academy of Sciences.

[8]  Scott W. McCue,et al.  Modelling the interaction of keratinocytes and fibroblasts during normal and abnormal wound healing processes , 2012, Proceedings of the Royal Society B: Biological Sciences.

[9]  Meng Chen,et al.  Modeling spatial population dynamics of stem cell lineage in tissue growth , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[10]  P. Boukamp,et al.  Stem cells of the human epidermis and their niche: composition and function in epidermal regeneration and carcinogenesis. , 2012, Carcinogenesis.

[11]  Qing Nie,et al.  Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms , 2010, BMC Systems Biology.

[12]  Jie Liang,et al.  Geometric order in proliferating epithelia: Impact of rearrangements and cleavage plane orientation , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[13]  M. Götz,et al.  The cell biology of neurogenesis , 2006, International Journal of Developmental Neuroscience.

[14]  Ingo Roeder,et al.  Asymmetry of stem cell fate and the potential impact of the niche , 2006, Stem Cell Reviews.

[15]  Qing Nie,et al.  Feedback regulation in multistage cell lineages. , 2008, Mathematical biosciences and engineering : MBE.

[16]  D. McElwain,et al.  A mathematical model of wound healing and subsequent scarring , 2010, Journal of The Royal Society Interface.