Cancer invasion and the ability of malignant tumor cells for directed migration and metastasis have remained a focus of research for many years. Numerous studies have confirmed the existence of two ...main patterns of cancer cell invasion: collective cell migration and individual cell migration, by which tumor cells overcome barriers of the extracellular matrix and spread into surrounding tissues. Each pattern of cell migration displays specific morphological features and the biochemical/molecular genetic mechanisms underlying cell migration. Two types of migrating tumor cells, mesenchymal (fibroblast-like) and amoeboid, are observed in each pattern of cancer cell invasion. This review describes the key differences between the variants of cancer cell migration, the role of epithelial-mesenchymal, collective-amoeboid, mesenchymal-amoeboid, and amoeboid- mesenchymal transitions, as well as the significance of different tumor factors and stromal molecules in tumor invasion. The data and facts collected are essential to the understanding of how the patterns of cancer cell invasion are related to cancer progression and therapy efficacy. Convincing evidence is provided that morphological manifestations of the invasion patterns are characterized by a variety of tissue (tumor) structures. The results of our own studies are presented to show the association of breast cancer progression with intratumoral morphological heterogeneity, which most likely reflects the types of cancer cell migration and results from different activities of cell adhesion molecules in tumor cells of distinct morphological structures.
The dynamics of single-cell migration on flat surfaces are usually modeled by a Langevin-like problem for particle velocity, consisting of a ballistic motion for short time intervals and a diffusive ...regime for long time intervals. However, experiments and simulations have revealed an additional diffusive motion at very short time intervals, which rules out the definition of cells’ instantaneous velocities. The experimental consequence is that one cannot estimate velocity by decreasing time intervals in a sequence of measurements. While for ballistic motion, the ratio of displacement over time intervals converges to a constant value (the limit value is taken as the velocity estimate), for diffusive motion this ratio diverges. Here, instead of cell velocity, we consider cell polarization as the dynamical variable and assume evolution equations for polarization modulus (a biased Langevin equation) and direction (a Wiener process). This circumvents the measurement problems for cell velocity when the system presents short-time diffusion. That means we take cell speed and displacement as consequences of cell polarization. For displacements, we also considered an additional noise term to account for membrane fluctuations that, in fact, cause the short-time-interval diffusive behavior. As novel results, we obtain memory preservation in polarization modulus for short time intervals and a displacement distribution function that may present a maximum at finite values of polarization modulus, for adequate time intervals. We also obtain a bi-exponential displacement autocorrelation function, improving the agreement between theoretical fits and experiments or simulations. Overall, this model contributes to the robustness of experimental measurements in cell migration experiments, besides providing a sound basis for theoretical models. For wet laboratory procedures, our findings provide a warning in what regards velocity and speed estimates and we propose experimental protocols to obtain these estimates at different levels of precision.
Cancer cell migration and invasion are integral components of metastatic disease, which is the major cause of death in cancer patients. Cancer cells can disseminate and migrate via several ...alternative mechanisms including amoeboid cell migration, mesenchymal cell migration, and collective cell migration. These diverse movement strategies display certain specific and distinct hallmarks in cell-cell junctions, actin cytoskeleton, matrix adhesion, and protease activity. During tumor progression, cells pass through complex microenvironments and adapt their migration strategies by reversible mesenchymal-amoeboid and individual-collective transitions. This plasticity in motility patterns enables cancer cells disseminate further and thus limit the efficiency of anti-metastasis therapies. In this review, we discuss the modes and mechanisms of cancer cell migration and focus on the plasticity of tumor cell movement as well as potential emerging therapeutic options for reducing cancer cell invasion.
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•Cancer cells can disseminate via amoeboid cell migration, mesenchymal cell migration or collective cell migration.•Tumor microenvironment and certain therapeutic challenge can trigger the transitions of migration patterns.•Plasticity of cancer cells migration limit efficiency of anti-metastasis therapies.•Combination therapy targeting different migration is a promising anti-metastasis therapy.
The spatial presentation of mechanical information is a key parameter for cell behavior. We have developed a method of polymerization control in which the differential diffusion distance of unreacted ...cross-linker and monomer into a prepolymerized hydrogel sink results in a tunable stiffness gradient at the cell–matrix interface. This simple, low-cost, robust method was used to produce polyacrylamide hydrogels with stiffness gradients of 0.5, 1.7, 2.9, 4.5, 6.8, and 8.2 kPa/mm, spanning the in vivo physiological and pathological mechanical landscape. Importantly, three of these gradients were found to be nondurotactic for human adipose-derived stem cells (hASCs), allowing the presentation of a continuous range of stiffnesses in a single well without the confounding effect of differential cell migration. Using these nondurotactic gradient gels, stiffness-dependent hASC morphology, migration, and differentiation were studied. Finally, the mechanosensitive proteins YAP, Lamin A/C, Lamin B, MRTF-A, and MRTF-B were analyzed on these gradients, providing higher-resolution data on stiffness-dependent expression and localization.
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