Predicting tissue assembly of prostate cancer spheroids

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.