Network-based identification of feedback modules that control RhoA activity and cell migration

Abstract

Cancer cell migration enables metastatic spread causing most cancer deaths. Rho-family GTPases control cell migration, but being embedded in a highly interconnected feedback network, the control of their dynamical behavior during cell migration remains elusive. To address this question, we reconstructed the Rho-family GTPases signaling network involved in cell migration, and developed a Boolean network model to analyze the different states and emergent rewiring of the Rho-family GTPases signaling network at protrusions and during extracellular matrix-dependent cell migration. Extensive simulations and experimental validations revealed that the bursts of RhoA activity induced at protrusions by EGF are regulated by a negative-feedback module composed of Src, FAK, and CSK. Interestingly, perturbing this module interfered with cyclic Rho activation and extracellular matrix-dependent migration, suggesting that CSK inhibition can be a novel and effective intervention strategy for blocking extracellular matrix-dependent cancer cell migration, while Src inhibition might fail, depending on the genetic background of cells. Thus, this study provides new insights into the mechanisms that regulate the intricate activation states of Rho-family GTPases during extracellular matrix-dependent migration, revealing potential new targets for interfering with extracellular matrix-dependent cancer cell migration.

Mechanisms of cell polarization

“…The mutual inhibition between Rac and Rho embedded in the larger EGF-EGF receptor signaling pathway for example has been modeled using a Boolean approach [138]. See also [139] for a similar approach. A second important area is deciphering the role of mechanical forces such as membrane tension, and incorporating these into models for cell polarization.…”

Periodic propagating waves coordinate RhoGTPase network dynamics at the leading and trailing edges during cell migration

“…To test the model predictions, we used cells stably expressing the mTFP-YFP RhoA-GTP FRETprobe (Kim et al, 2015) allowing us to determine the RhoA-GTP dynamics using ratiometric, livecell spinning disk microscopy. We imaged the cells with a frequency of one image every five seconds and constrained the measurement time to 10 minutes to limit phototoxic effects.…”

“…MDA-MB-231 stably expressing the mTFP-YFP RhoA-GTP FRET biosensor (Kim et al, 2015) were seeded in Fluorodish™ glass-bottomed plate (cat.FD35-100) coated with collagen. Cells were treated as indicated for siRNA or ROCK inhibition experiments (Y-27632 2.5µM).…”

Modelling GTPase dynamics to understand RhoA-driven cancer cell invasion

“…More recent advances in microscopy techniques and studying cells in 3D environments, however, have revealed that Rho GTPase signalling is far more complicated than persistent leading edge Rac1 and rear RhoA activity divided and kept apart by antagonism. While the role of RhoA in cell trailing edge contraction seems well conserved in 3D [20], there has been a suggestion that the efficient formation of protrusions at the leading edge of motile cell requires both Rac1 and RhoA activity in a pseudo-oscillatory manner [21,22]; alternatively, a very tightly regulated band of RhoA activity is required immediately in front of Rac1 activity in a lamellipodium [23]. Moreover, in certain fibronectin-rich ECM conditions, it has been shown that dominant RhoA activity at the leading edge of cells leads to more rapid and random migration in 2D and significantly increased invasion in physiologically relevant 3D microenvironments [24–28].…”

“…proteins) contained within the network are binarised into on or off; relations between the nodes are built using the logical operators AND, OR and NOT, and all such relations are assumed to take the same length of time. Others have used a similar approach previously in the context of predicting GTPase activity to highlight the importance of Src and Csk on pro-migratory oscillatory RhoA and Rac1 dynamics [22]. We built a model to determine which perturbations are important for the pro-invasive Rac1 to RhoA switch at the leading edge of cells as recently described [32].…”