Dynamic Computational Model Suggests That Cellular Citizenship Is Fundamental for Selective Tumor Apoptosis

Computational models in the field of cancer research have focused primarily on estimates of biological events based on laboratory generated data. We introduce a novel in-silico technology that takes us to the next level of prediction models and facilitates innovative solutions through the mathematical system. The model's building blocks are cells defined phenotypically as normal or tumor, with biological processes translated into equations describing the life protocols of the cells in a quantitative and stochastic manner. The essentials of communication in a society composed of normal and tumor cells are explored to reveal “protocols” for selective tumor eradication. Results consistently identify “citizenship properties” among cells that are essential for the induction of healing processes in a healthy system invaded by cancer. These properties act via inter-cellular communication protocols that can be optimized to induce tumor eradication along with system recovery. Within the computational systems, the protocols universally succeed in removing a wide variety of tumors defined by proliferation rates, initial volumes, and apoptosis resistant phenotypes; they show high adaptability for biological details and allow incorporation of population heterogeneity. These protocols work as long as at least 32% of cells obey extra-cellular commands and at least 28% of cancer cells report their deaths. This low percentage implies that the protocols are resilient to the suboptimal situations often seen in biological systems. We conclude that our in-silico model is a powerful tool to investigate, to propose, and to exercise logical anti-cancer solutions. Functional results should be confirmed in a biological system and molecular findings should be loaded into the computational model for the next level of directed experiments

Lotka-Volterra equations with chemotaxis: walls, barriers and travelling waves.

In this paper we consider a simple two species model for the growth of new blood vessels. The model is based upon the Lotka-Volterra system of predator and prey interaction, where we identify newly developed capillary tips as the predator species and a chemoattractant which directs their motion as the prey. We extend the Lotka-Volterra system to include a one-dimensional spatial dependence, by allowing the predators to migrate in a manner modelled on the phenomenon of chemotaxis. A feature of this model is its potential to support travelling wave solutions. We emphasize that in order to determine the existence of such travelling waves it is essential that the global relationships of a number of phase plane features other than the equilibria be investigated

SpheroidSim-Preliminary evaluation of a new computational tool to predict the influence of cell cycle time and phase fraction on spheroid growth.

BACKGROUND: There is a relative paucity of research that integrates materials science and bioengineering with computational simulations to decipher the intricate processes promoting cancer progression. Therefore, a first-generation computational model, SpheroidSim, was developed that includes a biological data set derived from a bioengineered spheroid model to obtain a quantitative description of cell kinetics. RESULTS: SpheroidSim is a 3D agent-based model simulating the growth of multicellular cancer spheroids. Cell cycle time and phases mathematically motivated the population growth. SpheroidSim simulated the growth dynamics of multiple spheroids by individually defining a collection of specific phenotypic traits and characteristics for each cell. Experimental data derived from a hydrogel-based spheroid model were fit to the predictions providing insight into the influence of cell cycle time (CCT) and cell phase fraction (CPF) on the cell population. A comparison of the number of active cells predicted for each analysis showed that the value and method used to define CCT had a greater effect on the predicted cell population than CPF. The model predictions were similar to the experimental results for the number of cells, with the predicted total number of cells varying by 8% and 12%, respectively, compared to the experimental data. CONCLUSIONS: SpheroidSim is a first step in developing a biologically based predictive tool capable of revealing fundamental elements in cancer cell physiology. This computational model may be applied to study the effect of the microenvironment on spheroid growth and other cancer cell types that demonstrate a similar multicellular clustering behavior as the population develops. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1335-1343, 2018.Cancer Council Queensland. Grant Number: project grant; Australian Research Council. Grant Number: fellowship project gran

A model of wound-healing angiogenesis in soft tissue.

Angiogenesis, or blood vessel growth, is a critical step in the wound-healing process, involving the chemotactic response of blood vessel endothelial cells to macrophage-derived factors produced in the wound space. In this article, we formulate a system of partial differential equations that model the evolution of the capillary-tip endothelial cells, macrophage-derived chemoattractants, and the new blood vessels during the tissue repair process. Chemotaxis is incorporated as a dominant feature of the model, driving the wave-like ingrowth of the wound-healing unit. The resulting model admits traveling wave solutions that exhibit many of the features characteristic of wound healing in soft tissue. The steady propagation of the healing unit through the wound space, the development of a dense band of fine, tipped capillaries near the leading edge of the wound-healing unit (the brush-border effect), and an elevated vessel density associated with newly healed wounds, prior to vascular remodeling, are all discernible from numerical simulations of the full model. Numerical simulations mimic not only the normal progression of wound healing but also the potential for some wounds to fail to heal. Through the development and analysis of a simplified model, insight is gained into how the balance between chemotaxis, tip proliferation, and tip death affects the structure and speed of propagation of the healing unit. Further, expressions defining the healed vessel density and the wavespeed in terms of known parameters lead naturally to the identification of a maximum wavespeed for the wound-healing process and to bounds on the healed vessel density. The implications of these results for wound-healing management are also discussed

Fibroblast α11β1 Integrin Regulates Tensional Homeostasis in Fibroblast/A549 Carcinoma Heterospheroids

We have previously shown that fibroblast expression of α11β1 integrin stimulates A549 carcinoma cell growth in a xenograft tumor model. To understand the molecular mechanisms whereby a collagen receptor on fibroblast can regulate tumor growth we have used a 3D heterospheroid system composed of A549 tumor cells and fibroblasts without (α11+/+) or with a deletion (α11-/-) in integrin α11 gene. Our data show that α11-/-/A549 spheroids are larger than α11+/+/A549 spheroids, and that A549 cell number, cell migration and cell invasion in a collagen I gel are decreased in α11-/-/A549 spheroids. Gene expression profiling of differentially expressed genes in fibroblast/A549 spheroids identified CXCL5 as one molecule down-regulated in A549 cells in the absence of α11 on the fibroblasts. Blocking CXCL5 function with the CXCR2 inhibitor SB225002 reduced cell proliferation and cell migration of A549 cells within spheroids, demonstrating that the fibroblast integrin α11β1 in a 3D heterospheroid context affects carcinoma cell growth and invasion by stimulating autocrine secretion of CXCL5. We furthermore suggest that fibroblast α11β1 in fibroblast/A549 spheroids regulates interstitial fluid pressure by compacting the collagen matrix, in turn implying a role for stromal collagen receptors in regulating tensional hemostasis in tumors. In summary, blocking stromal α11β1 integrin function might thus be a stroma-targeted therapeutic strategy to increase the efficacy of chemotherapy

A finite-element model for healing of cutaneous wounds combining contraction, angiogenesis and closure

A simplified finite-element model for wound healing is proposed. The model takes into account the sequential steps of dermal regeneration, wound contraction, angiogenesis and wound closure. An innovation in the present study is the combination of the aforementioned partially overlapping processes, which can be used to deliver novel insights into the process of wound healing, such as geometry related influences, as well as the influence of coupling between the various existing subprocesses on the actual healing behavior. The model confirms the clinical observation that epidermal closure proceeds by a crawling and climbing mechanism at the early stages, and by a stratification process in layers parallel to the skin surface at the later stages. The local epidermal oxygen content may play an important role here. The model can also be used to investigate the influence of local injection of hormones that stimulate partial processes occurring during wound healing. These insights can be used to improve wound healing treatments.Delft Institute of Applied MathematicsElectrical Engineering, Mathematics and Computer Scienc