A phenomenological model for cell and nucleus deformation during cancer metastasis

A bulk-surface mechanobiochemical modelling approach for single cell migration in two-space dimensions

In this work, we present a mechanobiochemical model for two-dimensional cell migration which couples mechanical properties of the cell cytosol with biochemical processes taking place near or on the cell plasma membrane. The modelling approach is based on a recently developed mathematical formalism of evolving bulk-surface partial differential equations of reaction-diffusion type. We solve these equations using finite element methods within a moving-mesh framework derived from the weak formulation of the evolving bulk-surface PDEs. In the present work, the cell cytosol interior (bulk) dynamics are coupled to the cell membrane (surface) dynamics through non-homogeneous Dirichlet boundary conditions. The modelling approach exhibits both directed cell migration in response to chemical cues as well as spontaneous migration in the absence of such cues. As a by-product, the approach shows fundamental characteristics associated with single cell migration such as: (i) cytosolic and membrane polarisation, (ii) actin dependent protrusions, and (iii) continuous shape deformation of the cell during migration. Cell migration is an ubiquitous process in life that is mainly triggered by the dynamics of the actin cytoskeleton and therefore is driven by both mechanical and biochemical processes. It is a multistep process essential for mammalian organisms and is closely linked to a vast diversity of processes; from embryonic development to cancer invasion. Experimental, theoretical and computational studies have been key to elucidate the mechanisms underlying cell migration. On one hand, rapid advances in experimental techniques allow for detailed experimental measurements of cell migration pathways, while, on the other, computational approaches allow for the modelling, analysis and understanding of such observations. The bulk-surface mechanobiochemical modelling approach presented in this work, set premises to study single cell migration through complex non-isotropic environments in two- and three-space dimensions.

Mechanical deformation and death of circulating tumor cells in the bloodstream

The circulation of tumor cells through the bloodstream is a significant step in tumor metastasis. To better understand the metastatic process, circulating tumor cell (CTC) survival in the circulation must be explored. While immune interactions with CTCs in recent decades have been examined, research has yet to sufficiently explain some CTC behaviors in blood flow. Studies related to CTC mechanical responses in the bloodstream have recently been conducted to further study conditions under which CTCs might die. While experimental methods can assess the mechanical properties and death of CTCs, increasingly sophisticated computational models are being built to simulate the blood flow and CTC mechanical deformation under fluid shear stresses (FSS) in the bloodstream.Several factors contribute to the mechanical deformation and death of CTCs as they circulate. While FSS can damage CTC structure, diverse interactions between CTCs and blood components may either promote or hinder the next metastatic step-extravasation at a remote site. Overall understanding of how these factors influence the deformation and death of CTCs could serve as a basis for future experiments and simulations, enabling researchers to predict CTC death more accurately. Ultimately, these efforts can lead to improved metastasis-specific therapeutics and diagnostics specific in the future.

Mechanobiological cell adaptations to changing microenvironments determine cancer invasiveness: Experimentally validated finite element modeling

Metastases are the leading cause of cancer-associated deaths. A key process in metastasis is cell invasiveness, which is driven and controlled by cancer cell interactions with their microenvironment. We have previously shown that invasive cancer cells forcefully push into and indent physiological stiffness gels to cell-scale depths, where the percentage of indenting cells and their attained depths provide clinically relevant predictions of tumor invasiveness and the potential metastatic risk. The cell-attained, invasive indentation depths are directly affected by gel-microenvironment mechanics, which can concurrently modulate the cells' mechanics and force application capacity, in a complex, coordinated mechanobiological response. As it is impossible to experimentally isolate the different contributions of cell and gel mechanics to cancer cell invasiveness, we perform finite element modeling with literature-based parameters. Under average-scale, cell cytoplasm and nucleus mechanics and cell-applied force levels, increasing gel stiffness 1-50 kPa significantly reduced the attained indentation depth by >200%, while the gel's Poisson ratio reduced depths only by up to 20% and only when the ratio was >0.4; this reveals microenvironment mechanics that can promote invasiveness. Experiments with varying-invasiveness cancer cells exhibited qualitative variations in their responses to gel stiffness increase, for example large/small reduction in indentation depth or increase and then reduction. We quantitatively and qualitatively reproduced the different experimental responses via coordinated changes in cell mechanics and applied force levels. Thus, the different cancer cell capacities to adapt their mechanobiology in response to mechanically changing microenvironments likely determine the varying cancer invasiveness and metastatic risk levels in patients.

A mathematical model of cell movement and clustering due to chemotaxis

This paper presents a numerical method for modelling cell migration and aggregation due to chemotaxis where the cell is attracted towards the direction in which the concentration of a chemical signal is increasing. In the model presented here, each cell is represented by a system of springs connected together at node points on the cell's membrane and on the boundary of the cell's nucleus. The nodes located on a cell's membrane are subject to a force which is proportional to the gradient of the concentration of the chemical signal which mimics the behaviour of the chemical receptors in the cell's membrane. In particular, the model developed here will consider what happens when two (or more) cells collide and how their membranes connect to each other to form clusters of cells. The methods described in this paper will be illustrated with a number of typical examples simulating cells moving in response to a chemical signal and how they combine to form clusters.

The Influence of Nucleus Mechanics in Modelling Adhesion-independent Cell Migration in Structured and Confined Environments

Recent biological experiments (Lämmermann et al. in Nature 453(7191):51-55, 2008; Reversat et al. in Nature 7813:582-585, 2020; Balzer et al. in ASEB J Off Publ Fed Am Soc Exp Biol 26(10):4045-4056, 2012) have shown that certain types of cells are able to move in structured and confined environments even without the activation of focal adhesion. Focusing on this particular phenomenon and based on previous works (Jankowiak et al. in Math Models Methods Appl Sci 30(03):513-537, 2020), we derive a novel two-dimensional mechanical model, which relies on the following physical ingredients: the asymmetrical renewal of the actin cortex supporting the membrane, resulting in a backward flow of material; the mechanical description of the nuclear membrane and the inner nuclear material; the microtubule network guiding nucleus location; the contact interactions between the cell and the external environment. The resulting fourth order system of partial differential equations is then solved numerically to conduct a study of the qualitative effects of the model parameters, mainly those governing the mechanical properties of the nucleus and the geometry of the confining structure. Coherently with biological observations, we find that cells characterized by a stiff nucleus are unable to migrate in channels that can be crossed by cells with a softer nucleus. Regarding the geometry, cell velocity and ability to migrate are influenced by the width of the channel and the wavelength of the external structure. Even though still preliminary, these results may be potentially useful in determining the physical limit of cell migration in confined environments and in designing scaffolds for tissue engineering.

Physical confinement and cell proximity increase cell migration rates and invasiveness: A mathematical model of cancer cell invasion through flexible channels

Cancer cell migration between different body parts is the driving force behind cancer metastasis, which is the main cause of mortality of patients. Migration of cancer cells often proceeds by penetration through narrow cavities in locally stiff, yet flexible tissues. In our previous work, we developed a model for cell geometry evolution during invasion, which we extend here to investigate whether leader and follower (cancer) cells that only interact mechanically can benefit from sequential transmigration through narrow micro-channels and cavities. We consider two cases of cells sequentially migrating through a flexible channel: leader and follower cells being closely adjacent or distant. Using Wilcoxon's signed-rank test on the data collected from Monte Carlo simulations, we conclude that the modelled transmigration speed for the follower cell is significantly larger than for the leader cell when cells are distant, i.e. follower cells transmigrate after the leader has completed the crossing. Furthermore, it appears that there exists an optimum with respect to the width of the channel such that cell moves fastest. On the other hand, in the case of closely adjacent cells, effectively performing collective migration, the leader cell moves 12% faster since the follower cell pushes it. This work shows that mechanical interactions between cells can increase the net transmigration speed of cancer cells, resulting in increased invasiveness. In other words, interaction between cancer cells can accelerate metastatic invasion.

Computational modeling reveals a vital role for proximity-driven additive and synergistic cell-cell interactions in increasing cancer invasiveness

Solid-tumor cell invasion typically occurs by collective migration of attached cell-cohorts, yet we show here that indirect cell-interactions through the substrate can also drive invasiveness. We have previously shown that well-spaced, invasive cancer cells push-into and indent gels to depths of 10 µm, while closely adjacent, non-contacting cancer cells may reach up to 18 µm, potentially relying on cell-cell interactions through the gel-substrate. To test that, we developed finite element models of indenting cells, using experimental gel mechanics, cell mechanostructure, and force magnitudes. We show that under 50-350 nN of combined traction and normal forces, a stiff nucleus-region is essential in facilitating 5-10 µm single-cell indentations, while uniformly soft cells attain 1.6-fold smaller indentations. We observe that indentation depths of cells in close proximity (0.5-50 µm distance) increase relative to well-spaced cells, due to additive, continuum mechanics-driven contributions. Specifically, 2-3 cells applying 220 nN normal forces gained up to 3% in depth, which interestingly increased to 7.8% when two cells, 10 µm apart, applied unequal force-magnitudes (i.e., 220 and 350 nN). Such additive, energy-free contributions can reduce cell mechanical energy -output required for invasiveness, yet the experimentally observed 10-18 µm depths likely necessitate synergistic, mechanobiological changes, which may be mechanically triggered. We note that nucleus stiffening or cytoplasm softening by 25-50% increased indentation depths by only 1-7%, while depths increase nearly linearly with force-magnitude even to two-fold levels. Hence, cell-proximity triggered, synergistic and additive cell-interactions through the substrate can drive collective cancer-cell invasiveness, even without direct cell-cell interactions. STATEMENT OF SIGNIFICANCE: Metastatic cancer invasion typically occurs collectively in attached cell-cohorts. We have previously shown increased invasiveness in closely adjacent cancer cells that are able to push-into and indent soft-gels more deeply than single, well-spaced cells. Using finite element models, we reveal mechanisms of cell-proximity driven invasiveness, demonstrating an important role for the stiff nucleus. Cell-proximity can additively induce small increase in indentation depth via continuum mechanics contributions, especially when adjacent cells apply unequal forces, and without requiring increased cell-mechanical-energy-output. Concurrently, proximity-triggered synergistic interactions that produce changes in cell mechanics or capacity for increased force-levels can facilitate deep invasive-indentations. Thus, we reveal concurrent additive and synergistic mechanisms to drive collective cancer-cell invasiveness even without direct cell-cell interactions.

Quantitative modeling identifies critical cell mechanics driving bile duct lumen formation

Biliary ducts collect bile from liver lobules, the smallest functional and anatomical units of liver, and carry it to the gallbladder. Disruptions in this process caused by defective embryonic development, or through ductal reaction in liver disease have a major impact on life quality and survival of patients. A deep understanding of the processes underlying bile duct lumen formation is crucial to identify intervention points to avoid or treat the appearance of defective bile ducts. Several hypotheses have been proposed to characterize the biophysical mechanisms driving initial bile duct lumen formation during embryogenesis. Here, guided by the quantification of morphological features and expression of genes in bile ducts from embryonic mouse liver, we sharpened these hypotheses and collected data to develop a high resolution individual cell-based computational model that enables to test alternative hypotheses in silico. This model permits realistic simulations of tissue and cell mechanics at sub-cellular scale. Our simulations suggest that successful bile duct lumen formation requires a simultaneous contribution of directed cell division of cholangiocytes, local osmotic effects generated by salt excretion in the lumen, and temporally-controlled differentiation of hepatoblasts to cholangiocytes, with apical constriction of cholangiocytes only moderately affecting luminal size.

The initial step in bile duct development is the formation of a biliary lumen, a process which involves several cellular mechanisms, such as cell division and polarization, and secretion of fluid. However, how these mechanisms are orchestrated in time and space is difficult to understand. Here, we built a computational model of biliary lumen formation which represents every cell and its function in detail. With the model we can simulate the effect of biophysical aspects that affect duct formation. We have tested the individual and combined effects of directed cell division, apical constriction, and osmotic effects on lumen expansion by varying the parameters that control their relative strength. Our simulations suggest that successful bile duct lumen formation requires the simultaneous contribution of directed cell division of cholangiocytes, local osmotic effects generated by salt excretion in the lumen, and temporally-controlled differentiation of hepatoblasts to cholangiocytes, with apical constriction of cholangiocytes only moderately affecting luminal size.

3D Tumor Models for Breast Cancer: Whither We Are and What We Need

Three-dimensional (3D) models have led to a paradigm shift in disease modeling in vitro, particularly for cancer. The past decade has seen a phenomenal increase in the development of 3D models for various types of cancers with a focus on studying stemness, invasive behavior, angiogenesis, and chemoresistance of cancer cells, as well as contributions of its stroma, which has expanded our understanding of these processes. Cancer biology is moving into exploring the emerging hallmarks of cancer, such as inflammation, immune evasion, and reprogramming of energy metabolism. Studies into these emerging concepts have provided novel targets and treatment options such as antitumor immunotherapy. However, 3D models that can investigate the emerging hallmarks are few and underexplored. As commonly used immunocompromised mice and syngenic mice cannot accurately mimic human immunology, stromal interactions, and metabolism and require the use of prohibitively expensive humanized mice, there is tremendous scope to develop authentic 3D tumor models in these areas. Taking the specific case of breast cancer, we discuss the currently available 3D models, their applications to mimic signaling in cancer, tumor-stroma interactions, drug responses, and assessment of drug delivery systems and therapies. We discuss the lacunae in the development of 3D tumor models for the emerging hallmarks of cancer, for lesser-explored forms of breast cancer, and provide insights to develop such models. We discuss how the next generation of 3D models can provide a better mimic of human cancer modeling compared to xenograft models and the scope toward preclinical models and precision medicine.

A formalism for modelling traction forces and cell shape evolution during cell migration in various biomedical processes

The phenomenological model for cell shape deformation and cell migration Chen (BMM 17:1429–1450, 2018), Vermolen and Gefen (BMM 12:301–323, 2012), is extended with the incorporation of cell traction forces and the evolution of cell equilibrium shapes as a result of cell differentiation. Plastic deformations of the extracellular matrix are modelled using morphoelasticity theory. The resulting partial differential differential equations are solved by the use of the finite element method. The paper treats various biological scenarios that entail cell migration and cell shape evolution. The experimental observations in Mak et al. (LC 13:340–348, 2013), where transmigration of cancer cells through narrow apertures is studied, are reproduced using a Monte Carlo framework.

Modeling force application configurations and morphologies required for cancer cell invasion

We show that cell-applied, normal mechanical stresses are required for cells to penetrate into soft substrates, matching experimental observations in invasive cancer cells, while in-plane traction forces alone reproduce observations in non-cancer/noninvasive cells. Mechanobiological interactions of cells with their microenvironment drive migration and cancer invasion. We have previously shown that invasive cancer cells forcefully and rapidly push into impenetrable, physiological stiffness gels and indent them to cell-scale depths (up to 10 μm); normal, noninvasive cells indent at most to 0.7 μm. Significantly indenting cells signpost increased cancer invasiveness and higher metastatic risk in vitro and in vivo, as verified experimentally in different cancer types, yet the underlying cell-applied, force magnitudes and configurations required to produce the cell-scale gel indentations have yet to be evaluated. Hence, we have developed finite element models of forces applied onto soft, impenetrable gels using experimental cell/gel morphologies, gel mechanics, and force magnitudes. We show that in-plane traction forces can only induce small-scale indentations in soft gels (< 0.7 μm), matching experiments with various single, normal cells. Addition of a normal force (on the scale of experimental traction forces) produced cell-scale indentations that matched observations in invasive cancer cells. We note that normal stresses (force and area) determine the indentation depth, while contact area size and morphology have a minor effect, explaining the origin of experimentally observed cell morphologies. We have thus revealed controlling features facilitating invasive indentations by single cancer cells, which will allow application of our model to complex problems, such as multicellular systems.

Micropatterned Surfaces Expose the Coupling between Actin Cytoskeleton-Lamin/Nesprin and Nuclear Deformability of Breast Cancer Cells with Different Malignancies

Mechanotransduction proteins transfer mechanical stimuli through nucleo-cytoskeletal coupling and affect the nuclear morphology of cancer cells. However, the contribution of actin filament integrity has never been studied directly. It is hypothesized that differences in nuclear deformability of cancer cells are influenced by the integrity of actin filaments. In this study, transparent micropatterned surfaces as simple tools to screen cytoskeletal and nuclear distortions are presented. Surfaces decorated with micropillars are used to culture and image breast cancer cells and quantify their deformation using shape descriptors (circularity, area, perimeter). Using two drugs (cytochalasin D and jasplakinolide), actin filaments are disrupted. Deformation of cells on micropillars is decreased upon drug treatment as shown by increased circularity. However, the effect is much smaller on benign MCF10A than on malignant MCF7 and MDAMB231 cells. On micropatterned surfaces, molecular analysis shows that Lamin A/C and Nesprin-2 expressions decreased but, after drug treatment, increased in malignant cells but not in benign cells. These findings suggest that Lamin A/C, Nesprin-2 and actin filaments are critical in mechanotransduction of cancer cells. Consequently, transparent micropatterned surfaces can be used as image analysis platforms to provide robust, high throughput measurements of nuclear deformability of cancer cells, including the effect of cytoskeletal elements.

Computational models of migration modes improve our understanding of metastasis

Tumor cells migrate through changing microenvironments of diseased and healthy tissue, making their migration particularly challenging to describe. To better understand this process, computational models have been developed for both the ameboid and mesenchymal modes of cell migration. Here, we review various approaches that have been used to account for the physical environment's effect on cell migration in computational models, with a focus on their application to understanding cancer metastasis and the related phenomenon of durotaxis. We then discuss how mesenchymal migration models typically simulate complex cell–extracellular matrix (ECM) interactions, while ameboid migration models use a cell-focused approach that largely ignores ECM when not acting as a physical barrier. This approach greatly simplifies or ignores the mechanosensing ability of ameboid migrating cells and should be reevaluated in future models. We conclude by describing future model elements that have not been included to date but would enhance model accuracy.

A Cellular Automata Model of Oncolytic Virotherapy in Pancreatic Cancer

Oncolytic virotherapy is known as a new treatment to employ less virulent viruses to specifically target and damage cancer cells. This work presents a cellular automata model of oncolytic virotherapy with an application to pancreatic cancer. The fundamental biomedical processes (like cell proliferation, mutation, apoptosis) are modeled by the use of probabilistic principles. The migration of injected viruses (as therapy) is modeled by diffusion through the tissue. The resulting diffusion–reaction equation with smoothed point viral sources is discretized by the finite difference method and integrated by the IMEX approach. Furthermore, Monte Carlo simulations are done to quantitatively evaluate the correlations between various input parameters and numerical results. As we expected, our model is able to simulate the pancreatic cancer growth at early stages, which is calibrated with experimental results. In addition, the model can be used to predict and evaluate the therapeutic effect of oncolytic virotherapy.

A quantitative high-resolution computational mechanics cell model for growing and regenerating tissues

Mathematical models are increasingly designed to guide experiments in biology, biotechnology, as well as to assist in medical decision making. They are in particular important to understand emergent collective cell behavior. For this purpose, the models, despite still abstractions of reality, need to be quantitative in all aspects relevant for the question of interest. This paper considers as showcase example the regeneration of liver after drug-induced depletion of hepatocytes, in which the surviving and dividing hepatocytes must squeeze in between the blood vessels of a network to refill the emerged lesions. Here, the cells' response to mechanical stress might significantly impact the regeneration process. We present a 3D high-resolution cell-based model integrating information from measurements in order to obtain a refined and quantitative understanding of the impact of cell-biomechanical effects on the closure of drug-induced lesions in liver. Our model represents each cell individually and is constructed by a discrete, physically scalable network of viscoelastic elements, capable of mimicking realistic cell deformation and supplying information at subcellular scales. The cells have the capability to migrate, grow, and divide, and the nature and parameters of their mechanical elements can be inferred from comparisons with optical stretcher experiments. Due to triangulation of the cell surface, interactions of cells with arbitrarily shaped (triangulated) structures such as blood vessels can be captured naturally. Comparing our simulations with those of so-called center-based models, in which cells have a largely rigid shape and forces are exerted between cell centers, we find that the migration forces a cell needs to exert on its environment to close a tissue lesion, is much smaller than predicted by center-based models. To stress generality of the approach, the liver simulations were complemented by monolayer and multicellular spheroid growth simulations. In summary, our model can give quantitative insight in many tissue organization processes, permits hypothesis testing in silico, and guide experiments in situations in which cell mechanics is considered important.

Computational modeling of therapy on pancreatic cancer in its early stages

More than eighty percent of pancreatic cancer involves ductal adenocarcinoma with an abundant desmoplastic extracellular matrix surrounding the solid tumor entity. This aberrant tumor microenvironment facilitates a strong resistance of pancreatic cancer to medication. Although various therapeutic strategies have been reported to be effective in mice with pancreatic cancer, they still need to be tested quantitatively in wider animal-based experiments before being applied as therapies. To aid the design of experiments, we develop a cell-based mathematical model to describe cancer progression under therapy with a specific application to pancreatic cancer. The displacement of cells is simulated by solving a large system of stochastic differential equations with the Euler-Maruyama method. We consider treatment with the PEGylated drug PEGPH20 that breaks down hyaluronan in desmoplastic stroma followed by administration of the chemotherapy drug gemcitabine to inhibit the proliferation of cancer cells. Modeling the effects of PEGPH20 + gemcitabine concentrations is based on Green's fundamental solutions of the reaction-diffusion equation. Moreover, Monte Carlo simulations are performed to quantitatively investigate uncertainties in the input parameters as well as predictions for the likelihood of success of cancer therapy. Our simplified model is able to simulate cancer progression and evaluate treatments to inhibit the progression of cancer.

Quantitative cell-based model predicts mechanical stress response of growing tumor spheroids over various growth conditions and cell lines

Model simulations indicate that the response of growing cell populations on mechanical stress follows the same functional relationship and is predictable over different cell lines and growth conditions despite experimental response curves look largely different. We develop a hybrid model strategy in which cells are represented by coarse-grained individual units calibrated with a high resolution cell model and parameterized by measurable biophysical and cell-biological parameters. Cell cycle progression in our model is controlled by volumetric strain, the latter being derived from a bio-mechanical relation between applied pressure and cell compressibility. After parameter calibration from experiments with mouse colon carcinoma cells growing against the resistance of an elastic alginate capsule, the model adequately predicts the growth curve in i) soft and rigid capsules, ii) in different experimental conditions where the mechanical stress is generated by osmosis via a high molecular weight dextran solution, and iii) for other cell types with different growth kinetics from the growth kinetics in absence of external stress. Our model simulation results suggest a generic, even quantitatively same, growth response of cell populations upon externally applied mechanical stress, as it can be quantitatively predicted using the same growth progression function.

Modelling actin polymerization: the effect on confined cell migration

The aim of this work is to model cell motility under conditions of mechanical confinement. This cell migration mode may occur in extravasation of tumour and neutrophil-like cells. Cell migration is the result of the complex action of different forces exerted by the interplay between myosin contractility forces and actin processes. Here, we propose and implement a finite element model of the confined migration of a single cell. In this model, we consider the effects of actin and myosin in cell motility. Both filament and globular actin are modelled. We model the cell considering cytoplasm and nucleus with different mechanical properties. The migration speed in the simulation is around 0.1 μm/min, which is in agreement with existing literature. From our simulation, we observe that the nucleus size has an important role in cell migration inside the channel. In the simulation the cell moves further when the nucleus is smaller. However, this speed is less sensitive to nucleus stiffness. The results show that the cell displacement is lower when the nucleus is stiffer. The degree of adhesion between the channel walls and the cell is also very important in confined migration. We observe an increment of cell velocity when the friction coefficient is higher.