Multiphysics Framework for the Study of Cancer Cell Transport
| dc.contributor.advisor | Randles, Amanda | |
| dc.contributor.author | Puleri, Daniel Franklin | |
| dc.date.accessioned | 2023-03-28T21:41:00Z | |
| dc.date.issued | 2022 | |
| dc.department | Biomedical Engineering | |
| dc.description.abstract | Metastasis causes most cancer-related mortality; thus, it is of paramount importance that science fully understands the factors influencing the fate of cancerous cells. Therefore, a key area of study is how the transport of tumor cells from the primary tumor via the bloodstream is affected by both the cells’ interactions with the endothelium and local hemodynamics in microvessels. In circulating tumor cells (CTCs) traveling through the cardiovascular system, the mechanism by which the trajectory of CTCs is guided and cells attach to the endothelium is not fully understood. Current studies with in silico, in vitro, and in vivo models have not been able to untangle the unclear interplay between hemodynamics and cell-cell interactions in determining a cancer cell’s trajectory and location of secondary metastases—stressing the importance of capturing multiple sources of interaction. Using state-of-the-art computational models to simulate the local microenvironment of a circulating tumor cell (CTC) provides a promising method of recapitulating the complex in vivo setting while maintaining control over parameters to better understand tumor cell transport. The interplay between forces imparted by fluid dynamics and cell-cell interactions on deformable CTCs contributes to the complexity of disease-specific models. The length scales across which cells travel pose an additional set of problems, with the need to bridge dissimilar length scales ranging from the sub-micron scale for cell interactions, micron scale for individual cell deformation, and larger to resolve the fluid dynamics of cells in vessels ranging from capillaries to venules and larger. Thus, there is an unmet need for studies and computational techniques which can integrate the multiple factors impacting CTC transport in microvessels. Towards unraveling the factors influencing cancer cell transport and preferential metastasis in certain tissues; this dissertation required the development of a next-generation framework for the computational study of cancer cell transport. In service of that goal, we have advanced both the size and efficiency of deformable cancer cell simulations. These novel methods enable high hematocrit distributed simulations which we demonstrated to be up to eighteen times faster than comparable simulations while simulating millions of deformable cells. Simulations of millions of deformable erythrocytes were completed using the state- of-the-art GPU-accelerated fluid structure interaction model we have developed and are, to our knowledge, the largest of such simulations. Given the importance of erythrocytes in impacting CTC trajectory, it is important to capture these interactions in an efficient manner. The framework presented in this dissertation additionally captures the microscale interactions between tumor cells and their microenvironment which we have used to study the impact of endothelial receptor patterns on cell transport. We found that adhesive cells were affected by the pattern of endothelial receptors with larger patches causing changes in cell lateral position in curved microvessels, slowing cells in straight microvessels, and impacting branch path in bifurcations. These advances were coupled together into a novel model, which we term adaptive physics refinement (APR), that captures the target CTC at the sub-micron resolution required for biologically-relevant simulation and increases the simulation domain to cellular-scale resolution at previously intractable volumes. With the APR model, we showed that simulation domain sizes > 100 mL were attainable, whereas traditional methods were limited to approximately 10^{-2} mL simulated volume given similar computing resources. Furthermore, APR now permits more flexibility in research study design by lowering the cost of each simulation to enable larger computational experiments. Collectively, we expect these advances to set the stage for disease-specific models of cancer metastasis which will aid in the development of new diagnostics and therapeutics. | |
| dc.identifier.uri | ||
| dc.subject | Biomedical engineering | |
| dc.title | Multiphysics Framework for the Study of Cancer Cell Transport | |
| dc.type | Dissertation | |
| duke.embargo.months | 22 | |
| duke.embargo.release | 2025-01-27T00:00:00Z |