Our overriding goal is to develop a quantitative model describing tumor cell dynamics and dissemination in the microcirculation. Meaningful output from our model is reliant upon the quality of the input variables: the physical and mechanical properties of cancer. However, surprisingly little quantitative information is known about the size, shape and feel of cancer in the fluid phase. Therefore, the first step toward the development of a model of cancer in the metastatic phase will be to establish the fundamental physical parameters of cancer cells in the circulation. Access to a unique population of tissue samples from colon and non-small lung cancer patients will provide us with the unique opportunity to characterize the physical properties of circulating tumor cells (CTCs).The physical models will be based on formulating the conservation of mass and momentum equations for a fluid-solid system in an incompressible flow regime. The solid (cancer cell) will be based on a deformable nonlinear shell model embedded within the flowfield, in a low Reynolds number regime. A newly developed version of the stochastic immersed boundary method will be used to simulate individual CTCs within the human vascular system in various channel geometries, as well as cell clusters via simple spring-mass systems. Mechanical properties of both the individual cell and cell aggregates will be closely correlated with the lab measured properties of the human samples obtained. We are not aware of any other group which is developing a fundamental model of cancer transit hand-in-hand with human samples. We will exploit this combined approach to establish a statistical model and fluid dynamics model for the behavior, survival, and destination of cancer in the vascular system.
The modeling represents the first human-specimen based fluid-solid model of circulating cancer cells within the human vascular system. It will provide a unique view of the physical mechanisms at work in the metastatic phase of various cancers. In the process, we will develop a first-principle description of the disease, based on a mechanistic point of view.
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