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Jolly, M. K.

Publications and source records attributed to Jolly, M. K..

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Testing the Gene Expression Classification of the EMT Spectrum

The epithelial-mesenchymal transition (EMT) plays a central role in cancer metastasis and drug resistance - two persistent clinical challenges. Epithelial cells can undergo a partial or full EMT, attaining either a hybrid epithelial/mesenchymal (E/M) or mesenchymal phenotype, respectively. Recent studies have emphasized that hybrid E/M cells may be more aggressive than their mesenchymal counterparts. However, mechanisms driving hybrid E/M phenotypes remain largely elusive. Here, to better characterize the hybrid E/M phenotype(s) and tumor aggressiveness, we integrate two computational methods - (a) RACIPE - to identify the robust gene expression patterns emerging from the dynamics of a given gene regulatory network, and (b) EMT scoring metric - to calculate the probability that a given gene expression profile displays a hybrid E/M phenotype. We apply the EMT scoring metric to RACIPE-generated gene expression data generated from a core EMT regulatory network and classify the gene expression profiles into relevant categories (epithelial, hybrid E/M, mesenchymal). This categorization is broadly consistent with hierarchical clustering readouts of RACIPE-generated gene expression data. We show that the EMT scoring metric can be used to distinguish between samples composed of exclusively hybrid E/M cells and those containing mixtures of epithelial and mesenchymal subpopulations using the RACIPE-generated gene expression data.

systems biology

Computational modeling of the crosstalk between macrophage polarization and tumor cell plasticity in the tumor microenvironment

Tumor microenvironments contain multiple cell types interacting among one another via different signaling pathways. Furthermore, both cancer cells and different immune cells can display phenotypic plasticity in response to these communicating signals, thereby leading to complex spatiotemporal patterns that can impact therapeutic response. Here, we investigate the crosstalk between cancer cells and macrophages in a tumor microenvironment through in silico (computational) co-culture models. In particular, we investigate how macrophages of different polarization (M1 vs. M2) can interact with epithelial-mesenchymal plasticity of cancer cells, and conversely, how cancer cells exhibiting different phenotypes (epithelial vs. mesenchymal) can influence the polarization of macrophages. Based on interactions documented in the literature, an interaction network of cancer cells and macrophages is constructed. The steady states of the network are then analyzed. Various interactions were removed or added into the constructed-network to test the functions of those interactions. Also, parameters in the mathematical models were varied to explore their effects on the steady states of the network. In general, the interactions between cancer cells and macrophages can give rise to multiple stable steady-states for a given set of parameters and each steady state is stable against perturbations. Importantly, we show that the system can often reach one type of stable steady states where cancer cells go extinct. Our results may help inform efficient therapeutic strategies.

systems biology

Towards understanding cancer stem cell heterogeneity in the tumor microenvironment

The Epithelial-Mesenchymal Transition (EMT) and Cancer Stem Cell (CSC) formation are two paramount processes driving tumor progression, therapy resistance and cancer metastasis. Some recent experiments show that cells with varying EMT and CSC phenotypes are spatially segregated in the primary tumor. The underlying mechanisms generating such spatiotemporal dynamics and heterogeneity in the tumor micro-environment, however, remain largely unexplored. Here, we show through a mechanism-based dynamical model that the diffusion of EMT-inducing signals such as TGF-{beta} in a tumor tissue, together with non-cell autonomous control of EMT and CSC decision-making via juxtacrine signaling mediated via the Notch signaling pathway, can explain experimentally observed disparate localization of subsets of CSCs with varying EMT states in the tumor. Our simulations show that the more mesenchymal CSCs lie at the invasive edge, while the hybrid epithelial/mesenchymal (E/M) CSCs reside in the tumor interior. Further, motivated by the role of Notch-Jagged signaling in mediating EMT and stemness, we investigated the microenvironmental factors that promote Notch-Jagged signaling. We show that many inflammatory cytokines that can promote Notch-Jagged signaling such as IL-6 can (a) stabilize a hybrid E/M phenotype, (b) increase the likelihood of spatial proximity of hybrid E/M cells, and (c) expand the fraction of CSCs. To validate the predicted connection between Notch-Jagged signaling and stemness, we knocked down JAG1 in hybrid E/M SUM149 human breast cancer cells in vitro. JAG1 knockdown significantly restricted organoid formation, confirming the key role that Notch-Jagged signaling can play in tumor progression. Together, our integrated computational-experimental framework reveals the underlying principles of spatiotemporal dynamics of EMT and CSCs in the tumor microenvironment.\n\nSignificance statementThe presence of heterogeneous subsets of cancer stem cells (CSCs) remains a clinical challenge. These subsets often occupy different regions in the primary tumor and have varied epithelial-mesenchymal phenotypes. Here, we device a theoretical framework to investigate how the tumor microenvironment (TME) modulates this spatial patterning. We find that a spatial gradient of EMT-inducing signal, coupled with juxtacrine Notch-JAG1 signaling triggered by inflammatory cytokines in TME, explains this spatial heterogeneity. Finally, in vitro JAG1 knockdown experiments in triple negative breast cancer cells severely restricts the growth of tumor organoid, hence validating the association between JAG1 and CSC fraction. Our results offer insights into principles of spatiotemporal patterning in TME, and identifies a relevant target to alleviate multiple CSC subsets - JAG1.

cancer biology

NRF2 activates a partial Epithelial-Mesenchymal Transition and is maximally present in a hybrid Epithelial/Mesenchymal phenotype

The Epithelial-Mesenchymal Transition (EMT) is a key process implicated in cancer metastasis and therapy resistance. Recent studies have emphasized that cells can undergo partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype - a cornerstone of tumour aggressiveness and poor prognosis. These cells can have enhanced tumour-initiation potential as compared to purely epithelial or mesenchymal ones, and can integrate the properties of cell-cell adhesion and motility that facilitates collective cell migration leading to clusters of Circulating Tumour Cells (CTCs) - the prevalent mode of metastasis. Thus, identifying the molecular players that can enable cells to maintain a hybrid E/M phenotype is crucial to curb the metastatic load. Here, using an integrated computational-experimental approach, we show that the transcription factor NRF2 can prevent a complete EMT and instead stabilize a hybrid E/M phenotype. Knockdown of NRF2 in hybrid E/M non-small cell lung cancer cells H1975 drove progression to a completely mesenchymal phenotype at molecular and morphological levels. Notably, overexpression of NRF2 enriched for a hybrid E/M phenotype by simultaneously upregulating both E-cadherin and ZEB in RT4 bladder cancer cells. Further, we predict that NRF2 is maximally expressed in hybrid E/M phenotype(s) and demonstrate that this biphasic dynamic arises from the interconnections among NRF2 and the EMT regulatory circuit. Finally, clinical data from multiple datasets suggests a correlation between a hybrid E/M phenotype, high levels of NRF2 and its targets and poor survival, further strengthening the emerging notion that hybrid E/M phenotype(s) may occupy the metastatic sweet spot.

cancer biology

An integrative systems biology and experimental approach identifies convergence of epithelial plasticity, metabolism, and autophagy to promote chemoresistance

The evolution of therapeutic resistance is a major cause of death for patients with solid tumors. The development of therapy resistance is shaped by the ecological dynamics within the tumor microenvironment and the selective pressure induced by the host immune system. These ecological and selective forces often lead to evolutionary convergence on one or more pathways or hallmarks that drive progression. These hallmarks are, in turn, intimately linked to each other through gene expression networks. Thus, a deeper understanding of the evolutionary convergences that occur at the gene expression level could reveal vulnerabilities that could be targeted to treat therapy-resistant cancer. To this end, we used a combination of phylogenetic clustering, systems biology analyses, and wet-bench molecular experimentation to identify convergences in gene expression data onto common signaling pathways. We applied these methods to derive new insights about the networks at play during TGF-{beta}-mediated epithelial-mesenchymal transition in a lung cancer model system. Phylogenetics analyses of gene expression data from TGF-{beta} treated cells revealed evolutionary convergence of cells toward amine-metabolic pathways and autophagy during TGF-{beta} treatment. Using high-throughput drug screens, we found that knockdown of the autophagy regulatory, ATG16L1, re-sensitized lung cancer cells to cancer therapies following TGF-{beta}-induced resistance, implicating autophagy as a TGF-{beta}-mediated chemoresistance mechanism. Analysis of publicly-available clinical data sets validated the adverse prognostic importance of ATG16L expression in multiple cancer types including kidney, lung, and colon cancer patients. These analyses reveal the usefulness of combining evolutionary and systems biology methods with experimental validation to illuminate new therapeutic vulnerabilities.

cancer biology

E-cadherin represses anoikis resistance in sarcomas through both signaling and mechanical mechanisms

E-cadherin, an epithelial-specific cell-cell adhesion molecule, plays multiple roles in maintaining adherens junctions, regulating migration and invasion, and mediating intracellular signaling. Downregulation of E-cadherin is a hallmark of epithelial-mesenchymal transition (EMT) and correlates with poor prognosis in multiple carcinomas. Conversely, upregulation of E-cadherin is prognostic for improved survival in sarcomas. Yet, despite the prognostic benefit of E-cadherin expression in sarcoma, the mechanistic significance of E-cadherin in sarcomas remains poorly understood. Here, by combining mathematical models with wet-bench experiments, we identify the core regulatory networks mediated by E-cadherin in sarcomas, and decipher their functional consequences. Unlike in carcinomas, E-cadherin overexpression in sarcomas does not induce a mesenchymal-epithelial transition (MET). However, E-cadherin acts to reduce both anchorage-independent growth and spheroid formation of sarcoma cells. Ectopic E-cadherin expression acts to downregulate phosphorylated CREB (p-CREB) and the transcription factor, TBX2, to inhibit anoikis resistance. RNAi-mediated knockdown of TBX2 phenocopies the effect of E-cadherin on p-CREB levels and restores anoikis sensitivity to sarcoma cells. Beyond its signaling role, E-cadherin expression in sarcoma cells can also strengthen cell-cell adhesion and restricts spheroid growth through mechanical action. Together, our results demonstrate that E-cadherin inhibits sarcoma aggressiveness by inducing anoikis and restricting colony growth.

cancer biology

A mechanism-based computational model to capture the interconnections among epithelial-mesenchymal transition, cancer stem cells and Notch-Jagged signaling

Epithelial-mesenchymal transition (EMT) and cancer stem cell formation (CSCs) are two fundamental and well-studied processes contributing to cancer metastasis and tumor relapse. Cells can undergo a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype or a complete EMT to attain a mesenchymal one. Similarly, cells can reversibly gain or lose stemness. This plasticity in cell states is modulated by signaling pathways such as Notch. However, the interconnections among the cell states enabled by EMT, CSCs and Notch signaling remain elusive. Here, we devise a computational model to investigate the coupling among the core decision-making circuits for EMT, CSCs and the Notch pathway. Our model predicts that hybrid E/M cells are most likely to associate with stemness traits and exhibit enhanced Notch-Jagged signaling - a pathway that is implicated in therapeutic resistance. Further, we show that the position of the stemness window on the EMT axis is varied by altering the coupling strength between EMT and CSC circuits, and/or modulating Notch signaling. Finally, we analyze the gene expression profile of CSCs from several cancer types and observe a heterogeneous distribution along the EMT axis, suggesting that different subsets of CSCs may exist with varying phenotypes along the epithelial-mesenchymal plasticity axis. Our computational model offers insights into the complex EMT-stemness interplay and provides a platform to investigate the effects of therapeutic perturbations such as treatment with metformin, a common anti-diabetic drug that has been associated with decreased cancer incidence and increased lifespan of patients. Our mechanism-based model helps explain how metformin can both inhibit EMT and blunt the aggressive potential of CSCs simultaneously, by driving the cells out of a hybrid E/M stem-like state with enhanced Notch-Jagged signaling.

cancer biology

Functional Balance between TCF21-Slug defines phenotypic plasticity and sub-classes in high-grade serous ovarian cancer

Cellular plasticity and transitional phenotypes add to complexities of cancer metastasis initiated by single cell epithelial to mesenchymal transition or cooperative cell migration (CCM). We identified novel regulatory cross-talks between Tcf21 and Slug in mediating phenotypic and migration plasticity in high-grade serous ovarian adenocarcinoma. Live imaging discerned CCM as being achieved either through rapid cell proliferation or sheet migration. Transitional states were enriched over the rigid epithelial or mesenchymal phenotypes under conditions of environmental stresses. The Tcf21-Slug interplay identified in HGSC tumors through effective stratification of subtypes also contributed to class-switching in response to disease progression or therapy. Our study effectively provides a framework for understanding the relevance of cellular plasticity in situ as a function of two transcription factors.

cancer biology

PAGE4 and Conformational Switching: Insights from Molecular Dynamics Simulations and Implications for Prostate Cancer

Prostate-Associated Gene 4 (PAGE4) is a disordered protein implicated in the progression of prostate cancer. PAGE4 can be phosphorylated at two residue sites by Homeodomain-Interacting Protein Kinase 1 (HIPK1) to facilitate its binding to the Activator Protein-1 (AP-1) transcription factor. In contrast, a further hyperphosphorylation of PAGE4 by CDC-Like Kinase 2 (CLK2) reduces its binding affinity to AP-1, thus affecting the androgen receptor (AR) activity. Both SAXS and smFRET experiments have shown a structural expansion of PAGE4 upon hyperphosphorylation and a significant increase in size at its N-terminal half than that at its C-terminus. To understand the molecular mechanism underlying this structural transition, we performed a series of constant temperature molecular dynamics simulations using Atomistic AWSEM -- a multi-scale molecular model combining detailed atomistic and coarse-grained simulation approaches. Our simulations show that electrostatic interaction drives a transient formation of an N-terminal loop, which causes the change in size for different phosphorylated forms of PAGE4. Phosphorylation also changes the preference of secondary structure formation of PAGE4, which signifies a transition between states that display different degree of disorder. Finally, we construct a mechanism-based mathematical model that allows us to capture the interactions of different forms of PAGE4 with AP-1 and AR, a key therapeutic target in prostate cancer. Our model predicts intracellular oscillatory dynamics of HIPK1-PAGE4, CLK2-PAGE4 and AR activity, indicating phenotypic heterogeneity in an isogenic cell population. Thus, conformational switching among different forms of PAGE4 may potentially affect the efficiency of therapeutic targeting of AR.

biophysics

Interconnected feedback loops among ESRP1, HAS2, and CD44 regulate epithelial-mesenchymal plasticity in cancer

Aberrant activation of epithelial-mesenchymal transition (EMT) in carcinoma cells contributes to increased migration and invasion, metastasis, drug resistance, and tumor-initiating capacity. EMT is not always a binary process, rather cells may exhibit a hybrid epithelial/mesenchymal (E/M) phenotype. ZEB1 - a key transcription factor driving EMT - can both induce and maintain a mesenchymal phenotype. Recent studies have identified two novel autocrine feedback loops utilizing ESRP1, HAS2, and CD44 that maintain high levels of ZEB1. However, how the crosstalk between these feedback loops alters the dynamics of epithelial-hybrid-mesenchymal transition remains elusive. Here, using an integrated theoretical-experimental framework, we identify that these feedback loops can enable cells to stably maintain a hybrid E/M phenotype. Moreover, computational analysis identifies the regulation of ESRP1 as a crucial node, a prediction that is validated by two complementary experiments showing that (a) overexpression of ESRP1 reverts EMT in MCF10A cells treated with TGF{beta} for 21 days, and (b) knockdown of ESRP1 in stable hybrid E/M H1975 cells drives EMT. Finally, in multiple breast cancer datasets, high levels of ESRP1, ESRP1/HAS2, and ESRP1/ZEB1 correlates with poor prognosis, supporting the relevance of ZEB1/ESRP1 and ZEB1/HAS2 axes in tumor progression. Together, our results unravel how these interconnected feedback loops act in concert to regulate ZEB1 levels and to drive the dynamics of epithelial-hybrid-mesenchymal transition.

cancer biology

Analysis of hierarchical organization in gene expression networks reveals underlying principles of collective tumor cell dissemination and metastatic aggressiveness of inflammatory breast cancer

BackgroundClusters of circulating tumor cells (CTCs), despite being rare, may account for more than 95% of metastases. Cells in these clusters do not undergo a complete epithelial-to-mesenchymal transition (EMT) but retain some epithelial traits as compared to individually disseminating tumor cells. Determinants of single cell dissemination versus collective dissemination remain elusive. Inflammatory breast cancer (IBC), a highly aggressive breast cancer subtype that chiefly metastasizes via CTC clusters, is a promising model for studying mechanisms of collective tumor cell dissemination. Previous studies on breast cancer and adult acute myeloid leukemia, motivated by a theory that suggests physical systems with hierarchical organization tend to be more adaptable, have found that the expression of metastasis associated genes is more hierarchically organized in cases of successful metastases.\n\nMethodsWe used the cophenetic correlation coefficient (CCC) to quantify the hierarchical organization in the expression networks of two distinct gene sets, collective dissemination associated genes and IBC associated genes, in cancer cell lines and in tumor samples from breast cancer patients. Hypothesizing that a higher CCC for collective dissemination associated genes and for IBC associated genes would be associated with a more evident epithelial phenotype and with worse outcomes in breast cancer patients, we evaluated the correlation of CCC with different phenotypic groups.\n\nResultsThe CCC of both gene networks, the collective dissemination associated gene network and the IBC associated gene network, was higher in (a) epithelial cell lines as compared to mesenchymal cell lines and (b) tumor samples from IBC patients, as compared to samples from non-IBC breast cancer patients. A higher CCC of both networks was also correlated with a higher rate of metastatic relapse in breast cancer patients. Neither the levels of CDH1 gene expression, nor gene set enrichment analysis could provide similar insights.\n\nConclusionsThese results suggest that retention of some epithelial traits in disseminating tumor cells as IBC progresses promotes successful breast cancer metastasis to distant organs. The CCC provides additional information regarding the organizational complexity of gene expression in comparison to differential gene expression analyses. We have shown that the CCC may be a useful metric for investigating the collective dissemination phenotype and a prognostic factor for IBC.

cancer biology

Numb prevents a complete EMT by modulating Notch signalling

Epithelial-Mesenchymal Transition (EMT) plays key roles during embryonic development, wound healing, and cancer metastasis. Cells in a partial EMT or hybrid epithelial/mesenchymal (E/M) phenotype tend to exhibit collective cell migration, forming clusters of circulating tumour cells - the primary drivers of metastasis. Activation of cell-cell signalling pathways such as Notch fosters a partial or complete EMT, yet the mechanisms enabling cluster formation remain poorly understood. Using an integrated computational-experimental approach, we examine the role of Numb - an inhibitor of Notch intercellular signalling - in mediating EMT and clusters formation of hybrid E/M cells. Knockdown of Numb in stable hybrid E/M cells H1975 results in a full EMT, thereby showing that Numb acts as a brake for a full EMT. Consistent with this observation, we show via a mathematical model that Numb inhibits a full EMT by stabilizing a hybrid E/M phenotype. Thus, Numb can behave as a phenotypic stability factor by modulating Notch-driven EMT. By generalizing the mathematical model to a multi-cell level, Numb is predicted to alter the balance of hybrid E/M versus mesenchymal cells in clusters, potentially resulting in a higher tumour-initiation ability. Finally, Numb correlates with a poor survival in multiple independent lung and ovarian cancer datasets, hence confirming its relationship with increased cancer aggressiveness.\n\nMajor Findings: we adopt an integrative computational-experimental approach to identify that Numb, an inhibitor of Notch signalling, can stabilize a hybrid epithelial/mesenchymal (E/M) phenotype. We show that knockdown of Numb in H1975 cells that display a stable hybrid E/M state is sufficient to destabilize a hybrid E/M state and push them to a full EMT phenotype. Next, we develop a mechanism-based mathematical model that recapitulates this ability of Numb in maintaining a hybrid E/M state, and predicts that Numb can alter the relative frequency of hybrid E/M and mesenchymal cells at a tissue level or in clusters of circulating tumor cells (CTCs) - the primary drivers of metastasis. Finally, we show that across cancer types, Numb correlates with worse patient survival, thus reinforcing the emerging notion that a hybrid E/M, but not necessarily a completely mesenchymal, phenotype associates with elevated tumour progression.

cancer biology

Epithelial-mesenchymal plasticity: How have quantitative mathematicalmodels helped improve our understanding?

Phenotypic plasticity, the ability of cells to reversibly alter their phenotypes in response to signals, presents a significant clinical challenge to treating solid tumors. Tumor cells utilize phenotypic plasticity to evade therapies, metastasize, and colonize distant organs. As a result, phenotypic plasticity can accelerate tumor progression. A well-studied example of phenotypic plasticity is the bidirectional conversions among epithelial, mesenchymal, and hybrid epithelial/mesenchymal phenotype(s). These conversions can alter a repertoire of cellular traits associated with multiple hallmarks of cancer, such as metabolism, immune-evasion, and invasion and metastasis. To tackle the complexity and heterogeneity of these transitions, mathematical models have been developed that seek to capture the experimentally-verified molecular mechanisms and act as hypothesis-generating machines. Here, we discuss how these quantitative mathematical models have helped us explain existing experimental data, guided further experiments, and provided an improved conceptual framework for understanding how multiple intracellular and extracellular signals can drive epithelial-mesenchymal plasticity at both the single-cell and population levels. We also discuss the implications of this plasticity in driving multiple aggressive facets of tumor progression.

cancer biology

EMT and MET: necessary or permissive for metastasis?

Epithelial-to-mesenchymal transition (EMT) and its reverse mesenchymal-to-epithelial transition (MET) have been often suggested to play crucial roles in metastatic dissemination of carcinomas. Recent studies have revealed that neither of these processes is binary. Instead, carcinoma cells often exhibit a spectrum of epithelial/mesenchymal phenotype(s). While epithelial-mesenchymal plasticity has been observed pre-clinically and clinically, whether any of these phenotypic transitions are indispensable for metastatic outgrowth remains an unanswered question. Here, we focus on epithelial-mesenchymal plasticity in metastatic dissemination and propose alternative mechanisms for successful dissemination and metastases beyond the traditional EMT-MET view. We highlight multiple hypotheses that can help reconcile conflicting observations, and outline the next set of key questions that can offer valuable insights into mechanisms of metastasis in multiple tumor models.

cancer biology

Inflammatory Breast Cancer: a model for investigating cluster-based dissemination

Metastases claim more than 90% of cancer-related patient deaths and are usually seeded by a subset of circulating tumor cells (CTCs) shed off from the primary tumor. In circulation, CTCs are found both as single cells and as clusters of cells. The clusters of CTCs, although many fewer in number, possess much higher metastatic potential as compared to that of individual CTCs. In this review, we highlight recent insights into molecular mechanisms that can enable the formation of these clusters - (a) hybrid epithelial/mesenchymal (E/M) phenotype of cells that couples their ability to migrate and adhere, and (b) intercellular communication that can spatially coordinate the cluster formation and provide survival signals to cancer cells. Building upon these molecular mechanisms, we also offer a possible mechanistic understanding of why clusters are endowed with a higher metastatic potential. Finally, we discuss the highly aggressive Inflammatory Breast Cancer (IBC) as an example of a carcinoma that can metastasize via clusters and corroborates the proposed molecular mechanisms.

cancer biology

Distinguishing Mechanisms Underlying EMT Tristability

BackgroundThe Epithelial-Mesenchymal Transition (EMT) endows epithelial-looking cells with enhanced migratory ability during embryonic development and tissue repair. EMT can also be co-opted by cancer cells to acquire metastatic potential and drug-resistance. Recent research has argued that epithelial (E) cells can undergo either a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype that typically displays collective migration, or a complete EMT to adopt a mesenchymal (M) phenotype that shows individual migration. The core EMT regulatory network - miR-34/SNAIL/miR-200/ZEB1 - has been identified by various studies, but how this network regulates the transitions among the E, E/M, and M phenotypes remains controversial. Two major mathematical models - ternary chimera switch (TCS) and cascading bistable switches (CBS) - that both focus on the miR-34/SNAIL/miR-200/ZEB1 network, have been proposed to elucidate the EMT dynamics, but a detailed analysis of how well either or both of these two models can capture recent experimental observations about EMT dynamics remains to be done.\n\nResultsHere, via an integrated experimental and theoretical approach, we first show that both these two models can be used to understand the two-step transition of EMT - E[->]E/M[->]M, the different responses of SNAIL and ZEB1 to exogenous TGF-{beta} and the irreversibility of complete EMT. Next, we present new experimental results that tend to discriminate between these two models. We show that ZEB1 is present at intermediate levels in the hybrid E/M H1975 cells, and that in HMLE cells, overexpression of SNAIL is not sufficient to initiate EMT in the absence of ZEB1 and FOXC2.\n\nConclusionsThese experimental results argue in favor of the TCS model proposing that miR-200/ZEB1 behaves as a three-way decision-making switch enabling transitions among the E, hybrid E/M and M phenotypes.

cancer biology