signaling states within a tumoral mass, subpopulations exhibiting
different phenotypic profiles can exist in different parts of the
tumor. The EMT regulatory circuit in cancer cells is further coupled with other regulatory modules including the Notch signaling
module. Such additional couplings can further increase the number
of phenotypes that can be exhibited by cells in a population in a
manner similar to the EMT-stemness coupling described above.
Additionally, since Notch signaling leads to the emergence of spatial patterns in the distribution of different phenotypes, EMTNotch-stemness coupling can lead to the localization of different
stemness associated phenotypes in different parts of the tumor
microenvironment [76].
8 Conclusion
Here, we have presented EMT from the lens of computational
systems biology where the focus is on the emergent properties of
the underlying regulatory network, instead of those of individual
nodes in the network. We have highlighted various examples of
how physics/engineering/mathematics driven approaches can
reveal unprecedented insights into various aspects of EMT dynamics, such as multi-stability, reversibility/irreversibility, symmetry
(or not) in EMT/MET, the effects of non-cell autonomous
mechanisms in EMT/MET, and finally the connection of EMT/
MET with other cellular traits such as stemness. The in silico
models presented here have their own strengths, limitations, and
assumptions, just as is the case with any in vitro, in vivo, or ex vivo
model. The examples presented here emphasize how an iterative
cross talk between mathematical modeling and experimental biology can help decode plasticity and heterogeneity in EMT/MET.
Acknowledgements
This work was supported by the National Science Foundation grant
PHY- 1427654 and by the Ramanujan Fellowship awarded to
M.K.J. by SERB, DST, Government of India (SB/S2/RJN-049/
2018).
References
1. Jolly MK, Ware KE, Gilja S et al (2017) EMT
and MET: necessary or permissive for metastasis? Mol Oncol 11:755–769. https://doi.org/
10.1002/1878-0261.12083
2. Aiello NM, Kang Y (2019) Context-dependent
EMT programs in cancer metastasis. J Exp Med
216:1016–1026. https://doi.org/10.1084/
jem.20181827
3. Kumar S, Das A, Sen S (2014) Extracellular
matrix density promotes EMT by weakening
cell–cell adhesions. Mol BioSyst 10:838–850.
https://doi.org/10.1039/C3MB70431A
Mathematical Modelling of EMT
409
different phenotypic profiles can exist in different parts of the
tumor. The EMT regulatory circuit in cancer cells is further coupled with other regulatory modules including the Notch signaling
module. Such additional couplings can further increase the number
of phenotypes that can be exhibited by cells in a population in a
manner similar to the EMT-stemness coupling described above.
Additionally, since Notch signaling leads to the emergence of spatial patterns in the distribution of different phenotypes, EMTNotch-stemness coupling can lead to the localization of different
stemness associated phenotypes in different parts of the tumor
microenvironment [76].
8 Conclusion
Here, we have presented EMT from the lens of computational
systems biology where the focus is on the emergent properties of
the underlying regulatory network, instead of those of individual
nodes in the network. We have highlighted various examples of
how physics/engineering/mathematics driven approaches can
reveal unprecedented insights into various aspects of EMT dynamics, such as multi-stability, reversibility/irreversibility, symmetry
(or not) in EMT/MET, the effects of non-cell autonomous
mechanisms in EMT/MET, and finally the connection of EMT/
MET with other cellular traits such as stemness. The in silico
models presented here have their own strengths, limitations, and
assumptions, just as is the case with any in vitro, in vivo, or ex vivo
model. The examples presented here emphasize how an iterative
cross talk between mathematical modeling and experimental biology can help decode plasticity and heterogeneity in EMT/MET.
Acknowledgements
This work was supported by the National Science Foundation grant
PHY- 1427654 and by the Ramanujan Fellowship awarded to
M.K.J. by SERB, DST, Government of India (SB/S2/RJN-049/
2018).
References
1. Jolly MK, Ware KE, Gilja S et al (2017) EMT
and MET: necessary or permissive for metastasis? Mol Oncol 11:755–769. https://doi.org/
10.1002/1878-0261.12083
2. Aiello NM, Kang Y (2019) Context-dependent
EMT programs in cancer metastasis. J Exp Med
216:1016–1026. https://doi.org/10.1084/
jem.20181827
3. Kumar S, Das A, Sen S (2014) Extracellular
matrix density promotes EMT by weakening
cell–cell adhesions. Mol BioSyst 10:838–850.
https://doi.org/10.1039/C3MB70431A
Mathematical Modelling of EMT
409