Unraveling the Vascular Fate of Deformable Circulating Tumor Cells Via a Hierarchical Computational Model

Lenarda, Pietro; Coclite, Alessandro; Decuzzi, Paolo

doi:10.1007/s12195-019-00587-y

Cited by 14 publications

(13 citation statements)

References 57 publications

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“…Spring-networks have been increasingly employed for modeling the motion and deformation of red blood cells 24 , 27 , 37 , leukocytes 38 , platelets 39 and cancer cells 40 . Spring-network models were already used for designing microfluidic chips 41 and for such designs having a validated model with accurate parameters, as our method provides, is crucial.…”

Section: Discussionmentioning

confidence: 99%

A systematic approach for developing mechanistic models for realistic simulation of cancer cell motion and deformation

Motamed

Maftoon

2021

Sci Rep

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Understanding and predicting metastatic progression and developing novel diagnostic methods can highly benefit from accurate models of the deformability of cancer cells. Spring-based network models of cells can provide a versatile way of integrating deforming cancer cells with other physical and biochemical phenomena, but these models have parameters that need to be accurately identified. In this study we established a systematic method for identifying parameters of spring-network models of cancer cells. We developed a genetic algorithm and coupled it to the fluid–solid interaction model of the cell, immersed in blood plasma or other fluids, to minimize the difference between numerical and experimental data of cell motion and deformation. We used the method to create a validated model for the human lung cancer cell line (H1975), employing existing experimental data of its deformation in a narrow microchannel constriction considering cell-wall friction. Furthermore, using this validated model with accurately identified parameters, we studied the details of motion and deformation of the cancer cell in the microchannel constriction and the effects of flow rates on them. We found that ignoring the viscosity of the cell membrane and the friction between the cell and wall can introduce remarkable errors.

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Section: Discussionmentioning

confidence: 99%

A systematic approach for developing mechanistic models for realistic simulation of cancer cell motion and deformation

Motamed

Maftoon

2021

Sci Rep

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“…Thus, to add a measure of robustness with regard to validation and our findings in recreating the experiments of Byun et al 11 , in the “ Recreating a separate experiment to verify cell properties and interrogate model accuracy under different conditions ” we describe an additional, separate experiment we have recreated to further interrogate our model. We also note here that while there are other modeling paradigms which exist, what we have employed in the present work is common in the literature among simulation-based works 32 – 36 , 38 , 39 , 44 as noted in the Introduction. As such, the findings and novel contributions of this work presented and discussed in the subsequent sections enable other researchers to model cancer cells undergoing large deformation during microcirulatory flow transport, and importantly with characteristics to distinguish between different types of cancer.…”

Section: Methodsmentioning

confidence: 96%

“…While this law was originally designed for red blood cells (RBCs), works have also used it to represent generic cancer cells by simply considering them to be spherical when undeformed, larger, and more stiff 44 – 47 . This idea has also been used with other membrane models and in silico approaches as well 32 , 34 , 39 . Use of the Skalak model is not only convenient within an IBM-based framework, but there is some physical basis for modeling cancer cells in that it is a strain-hardening model 48 , and filamentous actin which is a main contributor to deformation resistance 5 is known to exhibit strain-hardening behavior 49 , 50 .…”

Section: Introductionmentioning

confidence: 99%

A data-driven approach to modeling cancer cell mechanics during microcirculatory transport

Balogh

Gounley

Roychowdhury

et al. 2021

Sci Rep

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In order to understand the effect of cellular level features on the transport of circulating cancer cells in the microcirculation, there has been an increasing reliance on high-resolution in silico models. Accurate simulation of cancer cells flowing with blood cells requires resolving cellular-scale interactions in 3D, which is a significant computational undertaking warranting a cancer cell model that is both computationally efficient yet sufficiently complex to capture relevant behavior. Given that the characteristics of metastatic spread are known to depend on cancer type, it is crucial to account for mechanistic behavior representative of a specific cancer’s cells. To address this gap, in the present work we develop and validate a means by which an efficient and popular membrane model-based approach can be used to simulate deformable cancer cells and reproduce experimental data from specific cell lines. Here, cells are modeled using the immersed boundary method (IBM) within a lattice Boltzmann method (LBM) fluid solver, and the finite element method (FEM) is used to model cell membrane resistance to deformation. Through detailed comparisons with experiments, we (i) validate this model to represent cancer cells undergoing large deformation, (ii) outline a systematic approach to parameterize different cell lines to optimally fit experimental data over a range of deformations, and (iii) provide new insight into nucleated vs. non-nucleated cell models and their ability to match experiments. While many works have used the membrane-model based method employed here to model generic cancer cells, no quantitative comparisons with experiments exist in the literature for specific cell lines undergoing large deformation. Here, we describe a phenomenological, data-driven approach that can not only yield good agreement for large deformations, but explicitly detail how it can be used to represent different cancer cell lines. This model is readily incorporated into cell-resolved hemodynamic transport simulations, and thus offers significant potential to complement experiments towards providing new insights into various aspects of cancer progression.

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“…RBC, WBC, and platelet [4] are the main components of human blood. Therefore, understanding their dynamics could lead to new innovations in many engineering areas such as biomedical devices [5,6], cancer biology [7,8], or drug delivery [9]. From a mechanical standpoint, these special cells (or capsules) are deformable bodies, which are immersed in a flowing fluid.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Continuum-Particle Approach for Fluid-Structure Interaction Simulation of Red Blood Cells in Fluid Flows

Akerkouch

2021

Fluids

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Transport of cells in fluid flow plays a critical role in many physiological processes of the human body. Recent developments of in vitro techniques have enabled the understanding of cellular dynamics in laboratory conditions. However, it is challenging to obtain precise characteristics of cellular dynamics using experimental method alone, especially under in vivo conditions. This challenge motivates new developments of computational methods to provide complementary data that experimental techniques are not able to provide. Since there exists a large disparity in spatial and temporal scales in this problem, which requires a large number of cells to be simulated, it is highly desirable to develop an efficient numerical method for the interaction of cells and fluid flows. In this work, a new Fluid-Structure Interaction formulation is proposed based on the use of hybrid continuum-particle approach, which can resolve local dynamics of cells while providing large-scale flow patterns in the vascular vessel. Here, the Dissipative Particle Dynamics (DPD) model for the cellular membrane is used in conjunction with the Immersed Boundary Method (IBM) for the fluid plasma. Our results show that the new formulation is highly efficient in computing the deformation of cells within fluid flow while satisfying the incompressibility constraints of the fluid. We demonstrate that it is possible to couple the DPD with the IBM to simulate the complex dynamics of Red Blood Cells (RBC) such as parachuting. Our key observation is that the proposed coupling enables the simulation of RBC dynamics in realistic arterioles while ensuring the incompressibility constraint for fluid plasma. Therefore, the proposed method allows an accurate estimation of fluid shear stresses on the surface of simulated RBC. Our results suggest that this hybrid methodology can be extended for a variety of cells in physiological conditions.

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Unraveling the Vascular Fate of Deformable Circulating Tumor Cells Via a Hierarchical Computational Model

Cited by 14 publications

References 57 publications

A systematic approach for developing mechanistic models for realistic simulation of cancer cell motion and deformation

A systematic approach for developing mechanistic models for realistic simulation of cancer cell motion and deformation

A data-driven approach to modeling cancer cell mechanics during microcirculatory transport

A Hybrid Continuum-Particle Approach for Fluid-Structure Interaction Simulation of Red Blood Cells in Fluid Flows

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