Abstract
Computational methods that predict tissue assembly aid in the production of biological substitutes that mimic native tissue. In particular prostate cancer cells self-assemble on an attachment-limiting substrate into spheroids that resemble micrometastases and have application to in vitro drug testing. Two mathematical models of spheroid formation have been developed using the population-balance and Monte Carlo method. The models accommodate a variety of size populations: single cells and spheroids of different sizes. The population-balance model predicts spheroid size distributions over a 5-fold range of cell concentrations in the inoculum. Monte Carlo simulations predict long-range interactions between aggregating cells on the order of several cell diameters. This study provides evidence of intercellular bridges between the cancer cells that contain alpha-tubulin and can extend at least 100 microns in length. The computational methods presented here are robust in predicting spheroid assembly and underlying biological phenomena. Since spheroid composition is size-dependent, the models may be able to predict both spheroid size and composition from properties of the inoculum.
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O’Connor, K., Vidulescu, C., Clejan, S., Song, H., Venczel, M. (2007). Predicting Tissue Assembly of Prostate Cancer Spheroids. In: Smith, R. (eds) Cell Technology for Cell Products., vol 3. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-5476-1_47
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DOI: https://doi.org/10.1007/978-1-4020-5476-1_47
Publisher Name: Springer, Dordrecht
Print ISBN: 978-1-4020-5475-4
Online ISBN: 978-1-4020-5476-1
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