Abstract:Epithelial–mesenchymal transition (EMT) and its reverse process, mesenchymal–epithelial transition MET, are crucial in several stages of cancer metastasis. Epithelial–mesenchymal transition allows cancer cells to move to proximal blood vessels for intravasation. However, because EMT and MET processes are dynamic, mesenchymal cancer cells are likely to undergo MET transiently and subsequently re‐undergo EMT to restart the metastatic process. Therefore, spatiotemporally coordinated mutual regulation between EMT … Show more
“…CD44 low non-CSC populations, isolated from five different basal breast cancer cell lines, also reported a return to CD44 high state in vivo [66]. The dynamic EMT and MET was also observed in parental and HCC38 cells delineated by EpCAM profiling [26], in Zeb1 driving CD44 Low to CD44 High cellular plasticity [58] and in mammary carcinoma mouse MyPT models delineated by E-cadherin profiling [30]. Autocrine signaling is also speculated to play a significant role in EMP dynamics [67].…”
Section: Discussionmentioning
confidence: 99%
“…EMP-specific cellular phenotypes can be isolated using EpCAM, Integrin-β4 or CD44/CD24 expression in basal-like cell lines representing TNBC [26,27,28,29], or by using E-cadherin in mammary carcinoma in mouse PyMT models [30]. Similar work has also shown that basal, luminal and stem-like cancer cell subpopulations, isolated from different breast cancer cell lines, can stably retain intra-tumoral heterogeneity, and that all three populations of cells are able to initiate tumor formation in vivo [29].…”
Dynamic interconversions between transitional epithelial and mesenchymal states underpin the epithelial mesenchymal plasticity (EMP) seen in some carcinoma cell systems. We have delineated epithelial and mesenchymal subpopulations existing within the PMC42-LA breast cancer cell line by their EpCAM expression. These purified but phenotypically plastic states, EpCAMHigh (epithelial) and EpCAMLow (mesenchymal), have the ability to regain the phenotypic equilibrium of the parental population (i.e., 80% epithelial and 20% mesenchymal) over time, although the rate of reversion in the mesenchymal direction (epithelial-mesenchymal transition; EMT) is higher than that in the epithelial direction (mesenchymal-epithelial transition; MET). Single-cell clonal propagation was implemented to delineate the molecular and cellular features of this intrinsic heterogeneity with respect to EMP flux. The dynamics of the phenotypic proportions of epithelial and mesenchymal states in single-cell generated clones revealed clonal diversity and intrinsic plasticity. Single cell-derived clonal progenies displayed differences in their functional attributes of proliferation, stemness marker (CD44/CD24), migration, invasion and chemo-sensitivity. Interrogation of genomic copy number variations (CNV) with whole exome sequencing (WES) in the context of chromosome count from metaphase spread indicated that chromosomal instability was not influential in driving intrinsic phenotypic plasticity. Overall, these findings reveal the stochastic nature of both the epithelial and mesenchymal subpopulations, and the single cell-derived clones for differential functional attributes.
“…CD44 low non-CSC populations, isolated from five different basal breast cancer cell lines, also reported a return to CD44 high state in vivo [66]. The dynamic EMT and MET was also observed in parental and HCC38 cells delineated by EpCAM profiling [26], in Zeb1 driving CD44 Low to CD44 High cellular plasticity [58] and in mammary carcinoma mouse MyPT models delineated by E-cadherin profiling [30]. Autocrine signaling is also speculated to play a significant role in EMP dynamics [67].…”
Section: Discussionmentioning
confidence: 99%
“…EMP-specific cellular phenotypes can be isolated using EpCAM, Integrin-β4 or CD44/CD24 expression in basal-like cell lines representing TNBC [26,27,28,29], or by using E-cadherin in mammary carcinoma in mouse PyMT models [30]. Similar work has also shown that basal, luminal and stem-like cancer cell subpopulations, isolated from different breast cancer cell lines, can stably retain intra-tumoral heterogeneity, and that all three populations of cells are able to initiate tumor formation in vivo [29].…”
Dynamic interconversions between transitional epithelial and mesenchymal states underpin the epithelial mesenchymal plasticity (EMP) seen in some carcinoma cell systems. We have delineated epithelial and mesenchymal subpopulations existing within the PMC42-LA breast cancer cell line by their EpCAM expression. These purified but phenotypically plastic states, EpCAMHigh (epithelial) and EpCAMLow (mesenchymal), have the ability to regain the phenotypic equilibrium of the parental population (i.e., 80% epithelial and 20% mesenchymal) over time, although the rate of reversion in the mesenchymal direction (epithelial-mesenchymal transition; EMT) is higher than that in the epithelial direction (mesenchymal-epithelial transition; MET). Single-cell clonal propagation was implemented to delineate the molecular and cellular features of this intrinsic heterogeneity with respect to EMP flux. The dynamics of the phenotypic proportions of epithelial and mesenchymal states in single-cell generated clones revealed clonal diversity and intrinsic plasticity. Single cell-derived clonal progenies displayed differences in their functional attributes of proliferation, stemness marker (CD44/CD24), migration, invasion and chemo-sensitivity. Interrogation of genomic copy number variations (CNV) with whole exome sequencing (WES) in the context of chromosome count from metaphase spread indicated that chromosomal instability was not influential in driving intrinsic phenotypic plasticity. Overall, these findings reveal the stochastic nature of both the epithelial and mesenchymal subpopulations, and the single cell-derived clones for differential functional attributes.
“…It is believed that EMT contributes to cancer metastasis by facilitating local invasion, intravasation, transport, extravasation (by allowing cells to move to nearby blood vessels), and finally colonization [ 161 ]. During cancer, EMT and MET show a dynamic relationship in which cells transiently undergo MET and in the next step undergo EMT to restart the metastatic process [ 162 ]. A study by Yamamoto et al showed that spatiotemporally coordinated mutual regulation between EMT and MET could occur during metastasis [ 162 , 163 ].…”
Section: Role Of Emt and Met In Csc Establishment And Progressionmentioning
confidence: 99%
“…During cancer, EMT and MET show a dynamic relationship in which cells transiently undergo MET and in the next step undergo EMT to restart the metastatic process [ 162 ]. A study by Yamamoto et al showed that spatiotemporally coordinated mutual regulation between EMT and MET could occur during metastasis [ 162 , 163 ]. Fig.…”
Section: Role Of Emt and Met In Csc Establishment And Progressionmentioning
Over the last decades, the cancer survival rate has increased due to personalized therapies, the discovery of targeted therapeutics and novel biological agents, and the application of palliative treatments. Despite these advances, tumor resistance to chemotherapy and radiation and rapid progression to metastatic disease are still seen in many patients. Evidence has shown that cancer stem cells (CSCs), a sub-population of cells that share many common characteristics with somatic stem cells (SSCs), contribute to this therapeutic failure. The most critical properties of CSCs are their self-renewal ability and their capacity for differentiation into heterogeneous populations of cancer cells. Although CSCs only constitute a low percentage of the total tumor mass, these cells can regrow the tumor mass on their own. Initially identified in leukemia, CSCs have subsequently been found in cancers of the breast, the colon, the pancreas, and the brain. Common genetic and phenotypic features found in both SSCs and CSCs, including upregulated signaling pathways such as Notch, Wnt, Hedgehog, and TGF-β. These pathways play fundamental roles in the development as well as in the control of cell survival and cell fate and are relevant to therapeutic targeting of CSCs. The differences in the expression of membrane proteins and exosome-delivered microRNAs between SSCs and CSCs are also important to specifically target the stem cells of the cancer. Further research efforts should be directed toward elucidation of the fundamental differences between SSCs and CSCs to improve existing therapies and generate new clinically relevant cancer treatments.
“…When cultured, the isolated epithelial and mesenchymal cells remained in their initial cell state, while the E/M hybrid tumour cells exhibited plasticity, transitioning into either epithelial or mesenchymal states within 24 hrs of plating. It has been shown that EMP state subpopulations isolated from systems with inherent EMP tend to revert to a stable equilibrium, as seen with EpCAM-low subpopulations of MMTV-PyMT [Beerling et al, 2016] and PMC42-LA [Bhatia et al, 2019] cells, and either epithelial (EpCAM high ) or mesenchymal (EpCAM low ) subpopulations of the HCC-38 human breast cancer cell line [Yamamoto et al, 2017], all of which revert to a tightly controlled epithelial: mesenchymal ratio [Beerling et al, 2016]. In SCC9 cells, pEMT high and pEMT low subpopulations remained distinct at 4 hours and 24 hours of culture after cell sorting, but resembled parental SCC9 cells after 4 days [Puram et al, 2017].…”
Section: The E/m Hybrid Phenotype In Experimental Systemsmentioning
The epithelial-mesenchymal (E/M) hybrid state has emerged as an important mediator of the elements of cancer progression facilitated by epithelial mesenchymal plasticity (EMP). We review here the evidence for the presence and prognostic potential of E/M hybrid state in carcinoma, modelling predictions and validations studies to demonstrate stabilised E/M hybrid intermediates along the spectrum of EMP, and computational approaches for characterising and quantifying EMP phenotypes, with particular attention to the emerging realm of single-cell approaches through RNA sequencing and protein-based approaches.
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