Density-Dependent Migration Characteristics of Cancer Cells Driven by Pseudopod Interaction

Abstract

The ability of cancer cells to invade neighboring tissue from primary tumors is an important determinant of metastatic behavior. Quantification of cell migration characteristics such as migration speed and persistence helps to understand the requirements for such invasiveness. One factor that may influence invasion is how local tumor cell density shapes cell migration characteristics, which we here investigate with a combined experimental and computational modeling approach. First, we generated and analyzed time-lapse imaging data on two aggressive Triple-Negative Breast Cancer (TNBC) cell lines, HCC38 and Hs578T, during 2D migration assays at various cell densities. HCC38 cells exhibited a counter-intuitive increase in speed and persistence with increasing density, whereas Hs578T did not exhibit such an increase. Moreover, HCC38 cells exhibited strong cluster formation with active pseudopod-driven migration, especially at low densities, whereas Hs578T cells maintained a dispersed positioning. In order to obtain a mechanistic understanding of the density-dependent cell migration characteristics and cluster formation, we developed realistic spatial simulations using a Cellular Potts Model (CPM) with an explicit description of pseudopod dynamics. Model analysis demonstrated that pseudopods exerting a pulling force on the cell and interacting via increased adhesion at pseudopod tips could explain the experimentally observed increase in speed and persistence with increasing density in HCC38 cells. Thus, the density-dependent migratory behavior could be an emergent property of single-cell characteristics without the need for additional mechanisms. This implies that pseudopod dynamics and interaction may play a role in the aggressive nature of cancers through mediating dispersal.

Efficacy and selectivity of tumor-treating field therapy for triple-negative breast cancer cells via in-house delivery device

“…When taking viable cell counts using flow cytometry, data for each cell line were gated based on the measured mean diameter of the cell ± three standard deviations of the mean based on a sample size of n = 5 from experimentation during device validation. Diameters for MDA-MB-231 and HCC38 cells were further validated by comparison to previous studies [ 22 , 23 ], but reliable previous data for MCF-12 cells could not be found.…”

How cells align to structured collagen fibrils: A hybrid cellular Potts and molecular dynamics model with dynamic mechanosensitive focal adhesions

“…This hybrid model can be utilized to investigate various aspects of the interplay between cells and the extracellular matrix in both singlecell and multicellular contexts. Possible extensions include the study of cell migration along fibers by using one of the many active cell migration models implemented for the CPM such as a polarity vector (Burger et al, 2022), or the Act model (Niculescu et al, 2015); the difficulty lies in the detachment of FAs at the rear of the migrating cell, this could be done, for example, by applying a model for asymmetric traction forces that would rupture the rear FAs or by introducing a chemical symmetry breaking component (Yamaguchi and Knaut, 2022). Another example of possible further study is that of multicellular mechanical interaction.…”

Constraints and trade-offs shape the evolution of T cell search strategies

“…Would they adopt a different pattern in the same environment when fighting a more prevalent pathogen, or would they maintain the same migration mode even when it is no longer beneficial? We therefore suggest using models like the CPM [31, 13, 39, 40], where migration patterns arise naturally from an interaction between the cell and its environment rather than being imposed, to define the baseline expectations for T-cell search. By investigating which migratory characteristics emerge without being optimal or even beneficial, we can zoom in on the motility aspects that have truly been evolved to assist immune system function—without being misled by features that are merely inevitable side effects of an intracellular machinery acting in a complex environment.…”