Abstract
Adipose tissue, also known as fat tissue, surrounds the sites where many solid tumors develop. As a result, invasive tumor cells often migrate through adipose tissue in order to metastasize, which is the leading cause of cancer-related deaths worldwide. Compared to other tissue types, adipose tissue is physically distinct as it is composed of packings of large, spherical adipocytes (i.e. fat cells) encased by a network of collagen-rich extracellular matrix (ECM) proteins. While the biochemical influence of adipose tissue on tumor cell behavior is well established, how tissue mechanics guide tumor cell migration is less clear. Here, we characterize the physical properties of adipose tissue via quantitative histology, atomic force microscopy, and Brillouin microscopy to design bioengineered model systems and discrete element method (DEM) simulations of tumor invasion. For bioengineered model systems, we embed polyacrylamide beads with tunable size and stiffness into collagen hydrogels to create physical mimetics of adipose tissue. For DEM simulations, we model adipocytes as discrete, deformable polyhedra with shape-based energy functions that include cytoplasm incompressibility, perimeter contractility, membrane surface tension, substrate adhesion, and volume exclusion. Using both approaches, we find that the physical properties of adipose tissue (such as adipocyte size, stiffness, and packing fraction, as well as ECM density and alignment) regulate the extent and pattern of tumor cell invasion. In addition, we apply these strategies to investigate how obesity, a known risk factor for many types of cancer, impacts tumor growth by altering adipose tissue mechanics.
*We acknowledge support from the National Institutes of Health under Grant No. R01CA276392 (Y.Z., D.W., and C.S.O.), the National Science Foundation under Grant No. DGE1650441 (G.B.), the National Cancer Institute under Grant No. F31CA278410 (G.B.), the National Cancer Institute under Grant No. R01CA259195 (C.F.), and the Center on the Physics of Cancer Metabolism under Grant No. 1U54CA210184 (C.F.). This work was also supported by the High Performance Computing facilities operated by Yale's Center for Research Computing.
