Event Title

Role of Cancer Cells on Force Transmission in a Multicomponent, Multicell Model of the Endothelium

Mentor 1

Mahsa Dabaghmeshin

Start Date

1-5-2020 12:00 AM

Description

Cancer cells (CC) alter local hemodynamics in their vicinity which will influence the function of endothelial cells (ECs). Hemodynamic forces applied at the apical surface of vascular ECs provide the mechanical signals at intracellular organelles and through the inter-connected cellular network. ECs transduce the hemodynamic forces resulting from blood flow into intracellular signals that affect gene expression and cellular functions such as proliferation, apoptosis, migration, permeability, cell alignment and mechanical properties. An understanding of how the presence of a CC influences hemodynamic forces on the endothelium is needed before we can identify potential structural components of ECs that are believed to play important roles in force transmission. The objective of this study is to investigate computationally how the cancer cell influences the forces experienced by structural components of ECs. The 3D multiscale, multi-component model of an endothelial cell monolayer was developed using COMSOL Multiphysics CAD software. The model was successfully designed to simulate a layer of endothelial cells, including their glycocalyx layer, cortical apical layer, focal adhesions, adherens junctions, stress fibers, and nuclei. By investigating the effects of arterial wall stiffnesses and high shear conditions, we can better understand how CC impact the local hemodynamics in their vicinity, how the changes in the local hemodynamics may impact the force transmission to subcellular organelles, how the stiffness of arterial wall may impact the force transmission in ECs, and identify the subcellular components (mechanosensors) which may be activated during the adhesion of cancer cells to endothelial cells. We will validate our model by several tests of different parameters to determine that the results are sensible for each test. Our model will establish accurate criteria predisposing the cancer metastasis and identify the role of each individual mechanosensors in metastasis.

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May 1st, 12:00 AM

Role of Cancer Cells on Force Transmission in a Multicomponent, Multicell Model of the Endothelium

Cancer cells (CC) alter local hemodynamics in their vicinity which will influence the function of endothelial cells (ECs). Hemodynamic forces applied at the apical surface of vascular ECs provide the mechanical signals at intracellular organelles and through the inter-connected cellular network. ECs transduce the hemodynamic forces resulting from blood flow into intracellular signals that affect gene expression and cellular functions such as proliferation, apoptosis, migration, permeability, cell alignment and mechanical properties. An understanding of how the presence of a CC influences hemodynamic forces on the endothelium is needed before we can identify potential structural components of ECs that are believed to play important roles in force transmission. The objective of this study is to investigate computationally how the cancer cell influences the forces experienced by structural components of ECs. The 3D multiscale, multi-component model of an endothelial cell monolayer was developed using COMSOL Multiphysics CAD software. The model was successfully designed to simulate a layer of endothelial cells, including their glycocalyx layer, cortical apical layer, focal adhesions, adherens junctions, stress fibers, and nuclei. By investigating the effects of arterial wall stiffnesses and high shear conditions, we can better understand how CC impact the local hemodynamics in their vicinity, how the changes in the local hemodynamics may impact the force transmission to subcellular organelles, how the stiffness of arterial wall may impact the force transmission in ECs, and identify the subcellular components (mechanosensors) which may be activated during the adhesion of cancer cells to endothelial cells. We will validate our model by several tests of different parameters to determine that the results are sensible for each test. Our model will establish accurate criteria predisposing the cancer metastasis and identify the role of each individual mechanosensors in metastasis.