Microtubules have long been implicated to play an integral role in metastatic disease, for which a critical step is the local invasion of tumor cells into the 3-dimensional (3D) collagen-rich stromal matrix. Here we show that cell migration of human cancer cells uses the dynamic formation of highly branched protrusions that are composed of a microtubule core surrounded by cortical actin, a cytoskeletal organization that is absent in cells on 2-dimensional (2D) substrates. Microtubule plus-end tracking protein End-binding 1 and motor protein dynein subunits light intermediate chain 2 and heavy chain 1, which do not regulate 2D migration, critically modulate 3D migration by affecting RhoA and thus regulate protrusion branching through differential assembly dynamics of microtubules. An important consequence of this observation is that the commonly used cancer drug paclitaxel is 100-fold more effective at blocking migration in a 3D matrix than on a 2D matrix. This work reveals the central role that microtubule dynamics plays in powering cell migration in a more pathologically relevant setting and suggests further testing of therapeutics targeting microtubules to mitigate migration.—Jayatilaka, H., Giri, A., Karl, M., Aifuwa, I., Trenton, N. J., Phillip, J. M., Khatau, S., Wirtz, D. EB1 and cytoplasmic dynein mediate protrusion dynamics for efficient 3-dimensional cell migration.

The loss of the intercellular adhesion molecule E-cadherin is a hallmark of the epithelial-mesenchymal transition (EMT), which promotes a transition of cancer cells to a migratory and invasive phenotype. E-cadherin is associated with a decrease in cell proliferation in normal cells. Here, using physiologically relevant 3D in vitro models, we find that E-cadherin induces hyper-proliferation in breast cancer cells through activation of the Raf/MEK/ERK signaling pathway. These results were validated and consistent across multiple in vivo models of primary tumor growth and metastatic outgrowth. E-cadherin expression dramatically increases tumor growth and, without affecting the ability of cells to extravasate and colonize the lung, significantly increases macrometastasis formation via cell proliferation at the distant site. Pharmacological inhibition of MEK1/2, blocking phosphorylation of ERK in E-cadherin-expressing cells, significantly depresses both tumor growth and macrometastasis. This work suggests a novel role of E-cadherin in tumor progression and identifies a potential new target to treat hyper-proliferative breast tumors.

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The study of how mammalian cell division is regulated in a 3D environment remains largely unexplored despite its physiological relevance and therapeutic significance. Possible reasons for the lack of exploration are the experimental limitations and technical challenges that render the study of cell division in 3D culture inefficient. Here, we describe an imaging-based method to efficiently study mammalian cell division and cell-matrix interactions in 3D collagen matrices. Cells labeled with fluorescent H2B are synchronized using the combination of thymidine blocking and nocodazole treatment, followed by a mechanical shake-off technique. Synchronized cells are then embedded into a 3D collagen matrix. Cell division is monitored using live-cell microscopy. The deformation of collagen fibers during and after cell division, which is an indicator of cell-matrix interaction, can be monitored and quantified using quantitative confocal reflection microscopy. The method provides an efficient and general approach to study mammalian cell division and cell-matrix interactions in a physiologically relevant 3D environment. This approach not only provides novel insights into the molecular basis of the development of normal tissue and diseases, but also allows for the design of novel diagnostic and therapeutic approaches.

Cell motility is essential to many biological processes as cells navigate and interact within their local microenvironments. Currently, most methods to quantify cell motility rely on the ability to follow and track individual cells. However, results from these approaches are typically reported as averaged values across cell populations. While these approaches offer biological simplicity, it limits the ability to assess cellular heterogeneity and infer generalizable patterns of single-cell behaviors at baseline or after perturbations. Here, we present CaMI, a computational framework that takes advantage of the single-cell nature of cell motility data to identify and classify distinct spatio-temporal behaviors of single cells. Using CaMI, we demonstrate the ability to robustly classify single-cell motility patterns in a large dataset (n=74,253 cells), quantify spatio-temporal heterogeneities, determine motility patterns in unclassified cells, and provide a visualization scheme for direct interpretation of dynamic cell behaviors. Furthermore, as a biological proof of concept, we investigate the biphasic spatial and temporal responses of T-cell lymphoma cells moving in Collagen-I gels of varying collagen concentrations and predict the dimensionality (2D vs. 3D) of matched cellular conditions based solely on spatio-temporal heterogeneities. Together, we present a multivariate framework to robustly classify emergent patterns of single-cell behaviors, highlighting cellular heterogeneity as a critical feature that establishes the behaviors of cellular populations.