Examining Go-or-Grow Using Fluorescent Cell-Cycle Indicators and Cell-Cycle-Inhibiting Drugs

Abstract

The go-or-grow hypothesis states that adherent cells undergo reversible phenotype switching between migratory and proliferative states, with cells in the migratory state being more motile than cells in the proliferative state. Here, we examine go-or-grow in two-dimensional in vitro assays using melanoma cells with fluorescent cell-cycle indicators and cell-cycle-inhibiting drugs. We analyze the experimental data using single-cell tracking to calculate mean diffusivities and compare motility between cells in different cell-cycle phases and in cell-cycle arrest. Unequivocally, our analysis does not support the go-or-grow hypothesis. We present clear evidence that cell motility is independent of the cell-cycle phase and that nonproliferative arrested cells have the same motility as cycling cells.

Figure 1

Experimental data and mean diffusivities. (a) The cell cycle, indicating the color of FUCCI in each phase. (b and c) Experimental images of cycling C8161 cells; cell counts at 0 and 48 h are 331 and 1878, respectively. (d) The cell cycle, indicating the color of FUCCI in each phase together with arrest in G1. (e and f) Experimental images of C8161 cells in G1 arrest (30 nM trametinib); cell counts at 0 and 48 h are 261 and 469, respectively. (g–i) 50 cell trajectories of G1 cycling, S/G2/M cycling, and G1-arrested (30 nM trametinib) C8161 cells, respectively. (j–l) There is no difference in mean diffusivity, $\langle D\rangle$, for C8161, WM983C, and 1205Lu cells, respectively. For each 2-h time interval, $\langle D\rangle$ is the mean of all individual diffusivities D corresponding to cells with trajectories within the time interval. In each case, we show $\langle D\rangle$ and report the variability using $\langle D\rangle$ plus or minus the sample standard deviation. Data for each experimental condition are offset with respect to the time-interval axis for clarity. Scale bars, 200 μm. To see this figure in color, go online.