Understanding tissue morphology: model repurposing using the CoSMoS process
We present CoSMoS as a way of structuring thinking on how to reuse parts of an existing model and simulation in a new model and its implementation. CoSMoS provides a lens through which to consider, post-implementation, the assumptions made during the design and implementation of a software simulation of physical interactions in the formation of vascular structures from endothelial cells. We show how the abstract physical model and its software implementation can be adapted for a different problem: the growth of cancer cells under varying environmental perturbations. We identify the changes that must be made to adapt the model to its new context, along with the gaps in our knowledge of the domain that must be filled by wet-lab experimentation when recalibrating the model. Through parameter exploration, we identify the parameters that are critical to the dynamic physical structure of the modelled tissue, and we calibrate these parameters using a series of in vitro experiments. Drawing inspiration from the CoSMoS project structure, we maintain confidence in the repurposed model, and achieve a satisfactory degree of model reuse within our in silico experimental system.
KeywordsCalibration CoSMoS Model reuse Simulation
The authors would like to thank their colleagues who kindly provided resources for this paper. David Harrison and Peter Mullen (University of St. Andrews) provided the HCT-116 cells used for the experiments in Sect. 4. Figure 10 appears courtesy of Simon Langdon (University of Edinburgh). Figure 15 appears courtesy of Peter Caie (University of Edinburgh). James Bown acknowledges support from the Northwood Trust.
- Andrews PS, Polack FAC, Sampson AT, Stepney S, Timmis J (2010) The CoSMoS process version 0.1: A process for the modelling and simulation of complex systems. Technical Report YCS-2010-453, Department of Computer Science, University of York, YorkGoogle Scholar
- Céspedes MV, Espina C, García-Cabezas MA, Trias M, Boluda A, del Pulgar MTG, Sancho FJ, Nistal M, Lacal JC, Mangues R (2007) Orthotopic microinjection of human colon cancer cells in nude mice induces tumor foci in all clinically relevant metastatic sites. Am J Pathol 170(3):1077–1085CrossRefGoogle Scholar
- Étienne M (2006) Companion modelling: a tool for dialogue and concertation. In: Biodiversity and stakeholders: concertation itineraries, Editions Quae, Versailles, pp 44–52Google Scholar
- Gamba A, Ambrosi D, Coniglio A, de Candia A, Di Talia S, Giraudo E, Serini G, Preziosi L, Bussolino F (2003) Percolation, morphogenesis, and burgers dynamics in blood vessels formation. Phys Rev Lett 90(118):101Google Scholar
- Goldstein H, Poole CP, Safko JL (2001) Classical mechanics, 3rd edn. Addison-Wesley, BostonGoogle Scholar
- Morgan DO (2007) The cell cycle: principles of control. New Science Press, New YorkGoogle Scholar
- Niles L (2012) Human cultured neural stem cells. https://www.youtube.com/watch?v=x_e3PEJgrFY
- Reinders J (2007) Intel Threading Building Blocks: outfitting C++ for multi-core processor parallelism. O’Reilly & Associates Inc., SebastopolGoogle Scholar
- Stepney S (2012) A pattern language for scientific simulations. In: Proceedings of the 2012 workshop on complex systems modelling and simulation, Orleans, France, September 2012. Luniver Press, Bristol, pp 77–103Google Scholar
- Stepney S et al. (2015) Engineering simulations as scientific instruments. Springer, New YorkGoogle Scholar
- Yoshikawa R, Kusunoki M, Yanagi H, Noda M, Yamamura T, Hashimoto-Tamaoki T (2001) Dual antitumor effects of 5-fluorouracil on the cell cycle in colorectal carcinoma cells: a novel target mechanism concept for pharmacokinetic modulating chemotherapy. Cancer Res 61(3):1029–1037Google Scholar
- Zhu J, Coakley S, Holcombe M, MacNeil S, Smallwood R (2006) Individual cell-based simulation of 3D multicellular spheroid self-assembly. Eur Cells Mater 11(Suppl 3):31Google Scholar