A novel 3D atomistic-continuum cancer invasion model: In silico simulations of an in vitro organotypic invasion assay

2022

Preprint

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Invasion of the surrounding tissue is a key aspect of cancer growth and spread involving a coordinated effort between cell migration and matrix degradation, and has been the subject of mathematical modelling for almost 30 years. In this current paper we address a long-standing question in the field of cancer cell migration modelling: identify the migratory pattern and spread of individual cancer cells, or small clusters of cancer cells, when the macroscopic evolution of the cancer cell colony is dictated by a specific partial differential equation (PDE). We show that the usual heuristic understanding of the diffusion and advection terms of the PDE being responsible for the random and biased motion of the solitary cancer cells, respectively, is not precise. On the contrary, we show that the drift term of the correct stochastic differential equation (SDE) that dictates the individual cancer cell migration, should account also for the divergence of the diffusion of the PDE. Furthermore, we support our claims with a number of numerical experiments and computational simulations.

“…A promising avenue of development in this regard, given the difficulty in obtaining in vivo data, is to use in vitro data from organotypic invasion assays cf. [18], [19], [20].…”

Section: Discussionmentioning

confidence: 99%

Stochastic differential equation modelling of cancer cell migration and tissue invasion

Sfakianakis

Katsaounis

2022

Preprint

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Mathematical Modelling of Cancer Invasion: A Review

Sfakianakis

Springer Proceedings in Mathematics &Amp; Statistics

2021

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A defining feature of cancer is the capability to spread locally into the surrounding tissue, with cancer cells spreading beyond any normal boundaries. Cancer invasion is a complex phenomenon involving many inter-connected processes at different spatial and temporal scales. A key component of invasion is the ability of cancer cells to alter and degrade the extracellular matrix through the secretion of matrix-degrading enzymes. Combined with excessive cell proliferation and cell migration (individual and collective), this facilitates the spread of cancer cells into the local tissue. Along with tumour-induced angiogenesis, invasion is a critical component of metastatic spread, ultimately leading to the formation of secondary tumours in other parts of the host body. In this paper we present an overview of the various mathematical models and different modelling techniques and approaches that have been developed over the past 25 years or so and which focus on various aspects of the invasive process.

A mathematical multi-organ model for bidirectional epithelial–mesenchymal transitions in the metastatic spread of cancer

Franssen

IMA Journal of Applied Mathematics

2020

Cancer invasion and metastatic spread to secondary sites in the body are facilitated by a complex interplay between cancer cells of different phenotypes and their microenvironment. A trade-off between the cancer cells’ ability to invade the tissue and to metastasize, and their ability to proliferate has been observed. This gives rise to the classification of cancer cells into those of mesenchymal and epithelial phenotype, respectively. Additionally, mixed phenotypic states between these two extremes exist. Cancer cells can transit between these states via epithelial–mesenchymal transition (EMT) and the reverse process, mesenchymal–epithelial transition (MET). These processes are crucial for both the local tissue invasion and the metastatic spread of cancer cells. To shed light on the role of these phenotypic states and the transitions between them in the invasive and metastatic process, we extend our recently published multi-grid, hybrid, individual-based mathematical metastasis framework (Franssen et al. 2019, A mathematical framework for modelling the metastatic spread of cancer. Bull. Math. Biol., 81, 1965). In addition to cancer cells of epithelial and of mesenchymal phenotype, we now also include those of an intermediate partial-EMT phenotype. Furthermore, we allow for the switching between these phenotypic states via EMT and MET at the biologically appropriate steps of the invasion-metastasis cascade. We also account for the likelihood of spread of cancer cells to the various secondary sites and differentiate between the tissues of the organs involved in our simulations. Finally, we consider the maladaptation of metastasized cancer cells to the new tumour microenvironment at secondary sites as well as the immune response at these sites by accounting for cancer cell dormancy and death. This way, we create a first mathematical multi-organ model that explicitly accounts for EMT-processes occurring at the level of individual cancer cells in the context of the invasion-metastasis cascade.