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Biological tissues contain micrometer-scale gaps and pores, including those found within extracellular matrix fiber networks, between tightly packed cells, and between blood vessels or nerve bundles and their associated basement membranes. These spaces restrict cell motion to a single-spatial dimension (1D), a feature that is not captured in traditional in vitro cell migration assays performed on flat, unconfined two-dimensional (2D) substrates. Mechanical confinement can variably influence cell migration behaviors, and it is presently unclear whether the mechanisms used for migration in 2D unconfined environments are relevant in 1D confined environments. Here, we assessed whether a cell migration simulator and associated parameters previously measured for cells on 2D unconfined compliant hydrogels could predict 1D confined cell migration in microfluidic channels. We manufactured microfluidic devices with narrow channels (60-μm 2 rectangular cross-sectional area) and tracked human glioma cells that spontaneously migrated within channels. Cell velocities (v exp  = 0.51 ± 0.02 μm min -1 ) were comparable to brain tumor expansion rates measured in the clinic. Using motor-clutch model parameters estimated from cells on unconfined 2D planar hydrogel substrates, simulations predicted similar migration velocities (v sim  = 0.37 ± 0.04 μm min -1 ) and also predicted the effects of drugs targeting the motor-clutch system or cytoskeletal assembly. These results are consistent with glioma cells utilizing a motor-clutch system to migrate in confined environments., (Copyright © 2020 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

The ability of glioblastoma to disperse through the brain contributes to its lethality, and blocking this behavior has been an appealing therapeutic approach. Although a number of proinvasive signaling pathways are active in glioblastoma, many are redundant, so targeting one can be overcome by activating another. However, these pathways converge on nonredundant components of the cytoskeleton, and we have shown that inhibiting one of these-the myosin II family of cytoskeletal motors-blocks glioblastoma invasion even with simultaneous activation of multiple upstream promigratory pathways. Myosin IIA and IIB are the most prevalent isoforms of myosin II in glioblastoma, and we now show that codeleting these myosins markedly impairs tumorigenesis and significantly prolongs survival in a rodent model of this disease. However, while targeting just myosin IIA also impairs tumor invasion, it surprisingly increases tumor proliferation in a manner that depends on environmental mechanics. On soft surfaces myosin IIA deletion enhances ERK1/2 activity, while on stiff surfaces it enhances the activity of NFκB, not only in glioblastoma but in triple-negative breast carcinoma and normal keratinocytes as well. We conclude myosin IIA suppresses tumorigenesis in at least two ways that are modulated by the mechanics of the tumor and its stroma. Our results also suggest that inhibiting tumor invasion can enhance tumor proliferation and that effective therapy requires targeting cellular components that drive both proliferation and invasion simultaneously., Competing Interests: The authors declare no conflict of interest.

Cell migration is the physical movement of cells and is responsible for the extensive cellular invasion and metastasis that occur in high-grade tumors. Motivated by decades of direct observation of cell migration via light microscopy, theoretical models have emerged to capture various aspects of the fundamental physical phenomena underlying cell migration. Yet, the motility mechanisms actually used by tumor cells during invasion are still poorly understood, as is the role of cellular interactions with the extracellular environment. In this chapter, we review key physical principles of cytoskeletal self-assembly and force generation, membrane tension, biological adhesion, hydrostatic and osmotic pressures, and their integration in mathematical models of cell migration. With the goal of modeling-driven cancer therapy, we provide examples to guide oncologists and physical scientists in developing next-generation models to predict disease progression and treatment.

Microtubules are dynamic polymers required for a number of processes, including chromosome movement in mitosis. While regulators of microtubule dynamics have been well characterized, we lack a convenient way to predict how the measured dynamic parameters shape the entire microtubule system within a cell, or how the system responds when specific parameters change in response to internal or external signals. Here we describe a Monte Carlo model to simulate an array of dynamic microtubules from parameters including the cell radius, total tubulin concentration, microtubule nucleation rate from the centrosome, and plus end dynamic instability. The algorithm also allows dynamic instability or position of the cell edge to vary during the simulation. Outputs from simulations include free tubulin concentration, average microtubule lengths, length distributions, and individual length changes over time. Using this platform and reported parameters measured in interphase LLCPK1 epithelial cells, we predict that sequestering ~ 15–20% of total tubulin results in fewer microtubules, but promotes dynamic instability of those remaining. Simulations also predict that lowering nucleation rate will increase the stability and average length of the remaining microtubules. Allowing the position of the cell’s edge to vary over time changed the average length but not the number of microtubules and generated length distributions consistent with experimental measurements. Simulating the switch from interphase to prophase demonstrated that decreased rescue frequency at prophase is the critical factor needed to rapidly clear the cell of interphase microtubules prior to mitotic spindle assembly. Finally, consistent with several previous simulations, our results demonstrate that microtubule nucleation and dynamic instability in a confined space determines the partitioning of tubulin between monomer and polymer pools. The model and simulations will be useful for predicting changes to the entire microtubule array after modification to one or more parameters, including predicting the effects of tubulin-targeted chemotherapies. [ABSTRACT FROM AUTHOR]