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Epithelial-to-mesenchymal transition (EMT) is a developmental program that consists of the loss of epithelial features concomitant with the acquisition of mesenchymal features. Activation of EMT in cancer facilitates the acquisition of aggressive traits and cancer invasion. EMT plasticity (EMP), the dynamic transition between multiple hybrid states in which cancer cells display both epithelial and mesenchymal markers, confers survival advantages for cancer cells in constantly changing environments during metastasis.
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Cluster size distribution of cells disseminating from a primary tumor
The first stage of the metastatic cascade often involves motile cells emerging from a primary tumor either as single cells or as clusters. These cells enter the circulation, transit to other parts of the body and finally are responsible for growth of secondary tumors in distant organs. The mode of dissemination is believed to depend on the EMT nature (epithelial, hybrid or mesenchymal) of the cells. Here, we calculate the cluster size distribution of these migrating cells, using a mechanistic computational model, in presence of different degree of EMT-ness of the cells; EMT is treated as given rise to changes in their active motile forces ( μ ) and cell-medium surface tension (Γ). We find that, for ( μ > μ min , Γ > 1), when the cells are hybrid in nature, the mean cluster size, N ¯ ∼ Γ 2 . 0 / μ 2 . 8 , where μ min increases with increase in Γ. For Γ ≤ 0, N ¯ = 1 , the cells behave as completely mesenchymal. In presence of spectrum of hybrid states with different degree of EMT-ness (motility) in primary tumor, the cells which are relatively more mesenchymal (higher μ ) in nature, form larger clusters, whereas the smaller clusters are relatively more epithelial (lower μ ). Moreover, the heterogeneity in μ is comparatively higher for smaller clusters with respect to that for larger clusters. We also observe that more extended cell shapes promote the formation of smaller clusters. Overall, this study establishes a framework which connects the nature and size of migrating clusters disseminating from a primary tumor with the phenotypic composition of the tumor, and can lead to the better understanding of metastasis.
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- Award ID(s):
- 2019745
- PAR ID:
- 10320626
- Editor(s):
- Merks, Roeland M.H.
- Date Published:
- Journal Name:
- PLOS Computational Biology
- Volume:
- 17
- Issue:
- 11
- ISSN:
- 1553-7358
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pcbi.1009011
