Multiscale Tissue Modeling Reveals Impact of Cancer Treatment to Tumor Heterogeneity

Abstract

In the last decade models of cell interactions have allowed allow more and more insight into the dynamics and properties of single cells and their influence on the properties of tissues. Especially in systems that are hard to experimentally access, computational simulations excel in isolating effects and predicting emerging biological properties. Many of these simulations either concentrate on a high-resolution description of a limited number of cells or large numbers of cells at the cost of resolution. In contrast, we developed a highly scalable model that for the first time incorporates a sub-cellular resolution of each single cell while allowing simulating the interplay of millions of cells. Thus, we can investigate the pivotal role of single cells in the progression of the macroscopic tumor. Technically, our model is based on a cellular Potts model that has been expanded to include such as tumor initiation, malignancy transformation, mutations based on single cell alterations and tumor stem cells (TSCs) driving tumor renewal as well as treatment resistivity. We observe the emergence and evolution of tumor heterogeneity and analyze the local neighborhood and clustering of cell types. Different treatment protocols of pulsed chemo- and or radiotherapy show a large influence on the development of the tumor composition. A small amount of TSCs in the tumor significantly alters its properties and especially boosts post-treatment heterogeneity as well as regrowth. We scan the reproducibility and stochasticity of tumor development and treatment outcome in relation to the cell parameters.