Paterson, C. | Search bioRxiv

bioRxiv2018

Modulation of corneal tissue mechanics influences epithelial cell phenotype

Whilst the control of stem cell differentiation using substrates of differing compliance has been extensively explored in vitro, the significance of this mechanism at a physiological level is not known. Here we set to explore the role of corneal surface biomechanics in controlling epithelial cell proliferation and differentiation. Using non-contact high-resolution Brillouin spectro-microscopy we showed that the corneal outer edge (limbus) has significantly lower bulk modulus compared to the central cornea, and that this difference is precisely delimited in the organ. Furthermore, the areas of the limbus with distinctly softer properties were shown to be associated with limbal epithelial stem cell (LESC) residence. Based on these findings, we then provided the first demonstration of the capacity to modulate LESC phenotype, both in vivo and ex vivo, solely through the recreation/restoration of suitable biomechanical niches. These results thus confirm the fundamental role of corneal biomechanics in directing epithelial stem cell behavior.

cell biology↗

bioRxiv2016

An exactly solvable, spatial model of mutation accumulation in cancer

One of the hallmarks of cancer is the accumulation of driver mutations which increase the net reproductive rate of cancer cells and allow them to spread. This process has been studied in mathematical models of well mixed populations, and in computer simulations of three-dimensional spatial models. But the computational complexity of these more realistic, spatial models makes it difficult to simulate realistically large and clinically detectable solid tumours. Here we describe an exactly solvable mathematical model of a tumour featuring replication, mutation and local migration of cancer cells. The model predicts a quasi-exponential growth of large tumours even if different fragments of the tumour grow sub-exponentially due to nutrient and space limitations. The model reproduces clinically observed tumour growth times using biologically plausible rates for cell birth, death, and migration rates. We also show that the expected number of accumulated driver mutations increases exponentially in time if the average fitness gain per driver is constant, and that it reaches a plateau if the gains decrease over time. We discuss the realism of the underlying assumptions and possible extensions of the model.

cancer biology↗