Rxivist logo

Anticipating critical transitions in epithelial-hybrid-mesenchymal cell-fate determination

By Sukanta Sarkar, Sudipta Kumar Sinha, Herbert Levine, Mohit Kumar Jolly, Partha S. Dutta

Posted 13 Aug 2019
bioRxiv DOI: 10.1101/733006 (published DOI: 10.1073/pnas.1913773116)

In the vicinity of a tipping point, critical transitions occur when small changes in an input condition causes 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 diseased 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, hybrid epithelial/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 mRNA 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 elude the transition to a hybrid E/M phenotype. Overall, our results unravel the early warning signals that can be used to anticipate upcoming epithelial-hybrid-mesenchymal 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 evade these transitions, reducing the fitness of cancer cells and restricting tumor aggressiveness.

Download data

  • Downloaded 436 times
  • Download rankings, all-time:
    • Site-wide: 88,233
    • In systems biology: 1,922
  • Year to date:
    • Site-wide: 110,848
  • Since beginning of last month:
    • Site-wide: 153,842

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide