Microenvironment driven invasion: a multiscale multimodel investigation

Abstract

Cancer is a complex, multiscale process, in which genetic mutations occurring at a subcellular level manifest themselves as functional and morphological changes at the cellular and tissue scale. The importance of interactions between tumour cells and their microenvironment is currently of great interest in experimental as well as computational modelling. Both the immediate microenvironment (e.g. cell–cell signalling or cell–matrix interactions) and the extended microenvironment (e.g. nutrient supply or a host tissue structure) are thought to play crucial roles in both tumour progression and suppression. In this paper we focus on tumour invasion, as defined by the emergence of a fingering morphology, which has previously been shown to be dependent upon harsh microenvironmental conditions. Using three different modelling approaches at two different spatial scales we examine the impact of nutrient availability as a driving force for invasion. Specifically we investigate how cell metabolism (the intrinsic rate of nutrient consumption and cell resistance to starvation) influences the growing tumour. We also discuss how dynamical changes in genetic makeup and morphological characteristics, of the tumour population, are driven by extreme changes in nutrient supply during tumour development. The simulation results indicate that aggressive phenotypes produce tumour fingering in poor nutrient, but not rich, microenvironments. The implication of these results is that an invasive outcome appears to be co-dependent upon the evolutionary dynamics of the tumour population driven by the microenvironment.

Migration rules: tumours are conglomerates of self-metastases

“…In other computer models, tumour invasion was characterised by the transformation of a spherical tumour into fingering morphologies (Anderson, 2005). Invasive morphologies emerge upon harsh microenvironmental conditions, and the dynamical changes are driven by extreme changes in nutrient supply during tumour development (Anderson et al, 2009). They found that in a homogeneous environment without haptotactic and chemotactic gradients to direct cell migration, the tumour morphology is persistently radially symmetric.…”

“…Supporting the theory, small cancer stem cell populations are strongly implicated in leukaemia (Furth and Kahn, 1937;Kavalerchik et al, 2008) and tumour-initiating side populations have also recently been identified in solid tumours of the breast, colon and prostate, for example (Al-Hajj et al, 2003;Boman and Huang, 2008;Kakarala and Wicha, 2008;Maitland and Collins, 2008;Price et al, 2008). Taking these basic population-level features into account, we designed an agent-based computer model of cancer cell dynamics operative throughout tumour development (see Anderson et al (2007) and Deutsch and Dormann, (2005) for similar approaches). Tracking three cell-level kinetics -cell death, proliferation capacity and migration rate -in a simulated cancer cell population composed of cancer stem and non-stem cells, we show how they interact to produce emergent population-level effects.…”

A hybrid cellular automaton model of clonal evolution in cancer: The emergence of the glycolytic phenotype

“…Growth in this region in parameter space is therefore more competitive as cells that do not proliferate will quickly be trapped in the low nutrient regions in the interior of the tumour. For a more in depth study of this phenomena please consider Anderson et al (2007), where three different models were used to investigate the impact of nutrient supply on tumour morphology.…”

“…We therefore estimate c ap to be 15 % of the initial oxygen concentration. For high values this parameter is known to have an effect on the morphology of the tumour (Gerlee and Anderson, 2007b;Anderson et al, 2007), but for the relatively small values we consider this effect is negligible. The threshold for glucose induced necrosis is set to 50% of the normal glucose concentration, below which hypoglycemia occurs (Ganong, 1999).…”

Deformable Cell Model of Tissue Growth

“…On the other hand, it imposes a square lattice geometry which can influence the results. This method is used to study tumor growth [32,33] and cell invasion [34,35], angiogenesis [36,37], tissue engineering [38], and development of avian gut tissue [39]. This approach was further developed in the cellular Potts model [30,40] (see also [41,42] and references therein).…”