Publication | Open Access
Hybrid E/M phenotype(s) and stemness: a mechanistic connection embedded in network topology
22
Citations
86
References
2020
Year
Unknown Venue
GeneticsLinkage AnalysisCancer BiologyTumor BiologyPhenomicsTumor HeterogeneityBiological NetworkCancer Cell BiologyAbstract MetastasisCancer ResearchCancer Stem CellsHealth SciencesGenetic PredispositionStatistical GeneticsEpithelial-mesenchymal InteractionsCancer CellsPopulation GeneticsCell BiologyHybrid E/m PhenotypeEvolutionary BiologyComputational BiologyMechanistic ConnectionSystems BiologyMedicineMendelian InheritanceNetwork Topology
Abstract Metastasis remains an unsolved clinical challenge. Two crucial features of metastasizing cancer cells are a) their ability to dynamically move along the epithelial-hybrid-mesenchymal spectrum and b) their tumor-initiation potential or stemness. With increasing functional characterization of hybrid epithelial/mesenchymal (E/M) phenotypes along the spectrum, recent in vitro and in vivo studies have suggested an increasing association of hybrid E/M phenotypes with stemness. However, the mechanistic underpinnings enabling this association remain unclear. Here, we develop a mechanism-based mathematical modeling framework that interrogates the emergent nonlinear dynamics of the coupled network modules regulating E/M plasticity (miR-200/ZEB) and stemness (LIN28/let-7). Simulating the dynamics of this coupled network across a large ensemble of parameter sets, we observe that hybrid E/M phenotype(s) are more likely to acquire stemness relative to ‘pure’ epithelial or mesenchymal states. We also integrate multiple ‘phenotypic stability factors’ (PSFs) that have been shown to stabilize hybrid E/M phenotypes both in silico and in vitro – such as OVOL1/2, GRHL2, and NRF2 – with this network, and demonstrate that the enrichment of hybrid E/M phenotype(s) with stemness is largely conserved in the presence of these PSFs. Thus, our results offer mechanistic insights into recent experimental observations of hybrid E/M phenotype(s) being essential for tumor-initiation and highlight how this feature is embedded in the underlying topology of interconnected EMT and stemness networks.
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