The go-or-grow hypothesis proposes that adherent cells reversibly switch between migratory and proliferative phenotypes, where cells in the migratory state are more motile than those in the proliferative state, because they are not using energy for proliferation. Conclusive evidence of go-or-grow would have important and broad implications, notably for anti-cancer treatments with cell-cycle-inhibiting drugs and for mathematical modelling of cell migration. We describe a rigorous methodology for testing the go-or-grow hypothesis and apply our methodology to melanoma cells in two-dimensional (2D) assays. We use fluorescent ubiquitination-based cell cycle indicator (FUCCI) technology, cell-cycle-inhibiting drugs, and single-cell tracking to obtain the migration trajectories of cells in G1 phase, S/G2/M phase, and in G1 arrest. Our analysis does not support the go-or-grow hypothesis, with clear evidence for the independence of cell motility and cell cycle phase, and remarkably non-proliferative arrested cells have the same motility as cycling cells.
The cover image of the March 24 issue of Biophysical Journal visualizes the 2D migration trajectories for 10 C8161 melanoma cells in G1-phase cell cycle arrest. The individual trajectories show the relative positions of a cell, and the colors of each trajectory correspond to the duration from the commencement of tracking. The original trajectories are translated so the initial positions are at the same point to facilitate comparison. This single image illustrates aspects of cell motility that must be considered when analyzing cell migration data: migration of individual cells, net migration of multiple cells, directional persistence of individual cells, and the time scale over which cells undergo a random walk.
The cover image and our research highlight detailed quantitative information about cell motility that can be extracted from microscopy images and interpreted with careful mathematical modelling and data analysis. Employing similar analytical techniques to experimental data obtained from further studies of cell migration will hopefully contribute toward a better understanding of cell migration generally, and an improved outcome for cancer patients in particular.
— Scott McCue, Gency Gunasingh, Nikolas Haass, Matthew Simpson, Sean Vittadello