Abstract:
In the vicinity of a tipping point, critical transitions occur when
small changes in an input condition cause sudden, large, and
often irreversible changes in the state of a system. Many natural systems ranging from ecosystems to molecular biosystems are
known to exhibit critical transitions in their response to stochastic perturbations. In diseases, an early prediction of upcoming
critical transitions from a healthy to a disease state by using
early-warning signals is of prime interest due to potential application in forecasting disease onset. Here, we analyze cell-fate
transitions between different phenotypes (epithelial, hybridepithelial/mesenchymal [E/M], and mesenchymal states) that are
implicated in cancer metastasis and chemoresistance. These transitions are mediated by a mutually inhibitory feedback loop—
microRNA-200/ZEB—driven by the levels of transcription factor
SNAIL. We find that the proximity to tipping points enabling
these transitions among different phenotypes can be captured
by critical slowing down-based early-warning signals, calculated
from the trajectory of ZEB messenger RNA level. Further, the
basin stability analysis reveals the unexpectedly large basin of
attraction for a hybrid-E/M phenotype. Finally, we identified
mechanisms that can potentially elude the transition to a hybridE/M phenotype. Overall, our results unravel the early-warning
signals that can be used to anticipate upcoming epithelial–hybridmesenchymal transitions. With the emerging evidence about the
hybrid-E/M phenotype being a key driver of metastasis, drug
resistance, and tumor relapse, our results suggest ways to potentially evade these transitions, reducing the fitness of cancer cells
and restricting tumor aggressiveness.
