Tumor proliferation and diffusion on percolation clusters

J Biol Phys. 2016 Oct;42(4):637-658. doi: 10.1007/s10867-016-9427-2. Epub 2016 Sep 27.

Abstract

We study in silico the influence of host tissue inhomogeneity on tumor cell proliferation and diffusion by simulating the mobility of a tumor on percolation clusters with different homogeneities of surrounding tissues. The proliferation and diffusion of a tumor in an inhomogeneous tissue could be characterized in the framework of the percolation theory, which displays similar thresholds (0.54, 0.44, and 0.37, respectively) for tumor proliferation and diffusion in three kinds of lattices with 4, 6, and 8 connecting near neighbors. Our study reveals the existence of a critical transition concerning the survival and diffusion of tumor cells with leaping metastatic diffusion movement in the host tissues. Tumor cells usually flow in the direction of greater pressure variation during their diffusing and infiltrating to a further location in the host tissue. Some specific sites suitable for tumor invasion were observed on the percolation cluster and around these specific sites a tumor can develop into scattered tumors linked by some advantage tunnels that facilitate tumor invasion. We also investigate the manner that tissue inhomogeneity surrounding a tumor may influence the velocity of tumor diffusion and invasion. Our simulation suggested that invasion of a tumor is controlled by the homogeneity of the tumor microenvironment, which is basically consistent with the experimental report by Riching et al. as well as our clinical observation of medical imaging. Both simulation and clinical observation proved that tumor diffusion and invasion into the surrounding host tissue is positively correlated with the homogeneity of the tissue.

Keywords: Inhomogeneity; Invasive and metastatic diffusion; Percolation; Reaction–diffusion systems; Tumor.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Proliferation
  • Computer Simulation
  • Diffusion
  • Models, Biological*
  • Monte Carlo Method
  • Neoplasm Invasiveness
  • Neoplasm Metastasis
  • Neoplasms / pathology*