Skip to main content
Log in

Combinatorial Cooperativity in miR200-Zeb Feedback Network can Control Epithelial–Mesenchymal Transition

  • Original Article
  • Published:
Bulletin of Mathematical Biology Aims and scope Submit manuscript

Abstract

Carcinomas often utilize epithelial-mesenchymal transition (EMT) programs for cancer progression and metastasis. Numerous studies report SNAIL-induced miR200/Zeb feedback circuit as crucial in regulating EMT by placing cancer cells in at least three phenotypic states, viz. epithelial (E), hybrid (h-E/M), mesenchymal (M), along the E-M phenotypic spectrum. However, a coherent molecular-level understanding of how such a tiny circuit controls carcinoma cell entrance into and residence in various states is lacking. Here, we use molecular binding data and mathematical modeling to report that the miR200/Zeb circuit can essentially utilize combinatorial cooperativity to control E-M phenotypic plasticity. We identify minimal combinatorial cooperativities that give rise to E, h-E/M, and M phenotypes. We show that disrupting a specific number of miR200 binding sites on Zeb as well as Zeb binding sites on miR200 can have phenotypic consequences—the circuit can dynamically switch between two (E, M) and three (E, h-E/M, M) phenotypes. Further, we report that in both SNAIL-induced and SNAIL knock-out miR200/Zeb circuits, cooperative transcriptional feedback on Zeb as well as Zeb translation inhibition due to miR200 are essential for the occurrence of intermediate h-E/M phenotype. Finally, we demonstrate that SNAIL can be dispensable for EMT, and in the absence of SNAIL, the transcriptional feedback can control cell state transition from E to h-E/M, to M state. Our results thus highlight molecular-level regulation of EMT in miR200/Zeb circuit and we expect these findings to be crucial to future efforts aiming to prevent EMT-facilitated dissemination of carcinomas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data availability

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

References

Download references

Acknowledgements

We benefited from useful discussions with Prof. Mohit Kumar Jolly, Department of Bioengineering, Indian Institute of Science, Bangalore, India. We gratefully acknowledge funding by the Department of Science and Technology (DST), Govt. of India, to MR (grant number: DST/INSPIRE/04/2020/001492).

Funding

The Funding was provided by DST, Govt of India, DST/INSPIRE/04/2020/001492, Mubasher Rashid

Author information

Authors and Affiliations

Authors

Contributions

MR: Conceptualization, methodology, simulations, data analysis, supervision, funding acquisition, writing—original draft as well as revision. BMD: Data analysis and simulations. MB: discussions and simulations.

Corresponding author

Correspondence to Mubasher Rashid.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 588 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rashid, M., Devi, B.M. & Banerjee, M. Combinatorial Cooperativity in miR200-Zeb Feedback Network can Control Epithelial–Mesenchymal Transition. Bull Math Biol 86, 48 (2024). https://doi.org/10.1007/s11538-024-01277-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11538-024-01277-1

Keywords

Navigation