Coupled reversible and irreversible bistable switches underlying TGFβ-induced epithelial to mesenchymal transition

Synthetic gene circuit evolution: Insights and opportunities at the mid-scale

Directed evolution focuses on optimizing single genetic components for predefined engineering goals by artificial mutagenesis and selection. In contrast, experimental evolution studies the adaptation of entire genomes in serially propagated cell populations, to provide an experimental basis for evolutionary theory. There is a relatively unexplored gap at the middle ground between these two techniques, to evolve in vivo entire synthetic gene circuits with nontrivial dynamic function instead of single parts or whole genomes. We discuss the requirements for such mid-scale evolution, with hypothetical examples for evolving synthetic gene circuits by appropriate selection and targeted shuffling of a seed set of genetic components in vivo. Implementing similar methods should aid the rapid generation, functionalization, and optimization of synthetic gene circuits in various organisms and environments, accelerating both the development of biomedical and technological applications and the understanding of principles guiding regulatory network evolution.

Spatial transition tensor of single cells

Spatial transcriptomics and messenger RNA splicing encode extensive spatiotemporal information for cell states and transitions. The current lineage-inference methods either lack spatial dynamics for state transition or cannot capture different dynamics associated with multiple cell states and transition paths. Here we present spatial transition tensor (STT), a method that uses messenger RNA splicing and spatial transcriptomes through a multiscale dynamical model to characterize multistability in space. By learning a four-dimensional transition tensor and spatial-constrained random walk, STT reconstructs cell-state-specific dynamics and spatial state transitions via both short-time local tensor streamlines between cells and long-time transition paths among attractors. Benchmarking and applications of STT on several transcriptome datasets via multiple technologies on epithelial-mesenchymal transitions, blood development, spatially resolved mouse brain and chicken heart development, indicate STT's capability in recovering cell-state-specific dynamics and their associated genes not seen using existing methods. Overall, STT provides a consistent multiscale description of single-cell transcriptome data across multiple spatiotemporal scales.

Mesenchymal stem cells derived from CHIR99021 and TGF‑β induction remained on the colicomentum and improved cardiac function of a rat model of acute myocardium infarction

Human induced pluripotent stem cells (hiPSCs) have been regarded as a potential stem cell source for cell therapy. However, the production of cells with mesenchymal potential from hiPSCs through spontaneous differentiation is time consuming and laborious. In the present study, the combined use of the GSK-3 inhibitor CHIR99021 and TGF-β was used to obtain mesenchymal stem cell (MSC)-like cells from hiPSCs. During the induction process, the transcription of epithelial-mesenchymal transition (EMT)-related genes N-cadherin and Vimentin in the transformed cells was upregulated, whereas the transcription of E-cadherin and pluripotency-related transcription factors SOX2, OCT4 and NANOG did not change significantly. This indicated that whilst cells were pluripotent, EMT was initiated by the upregulation of transcription of EMT promoting genes. Both SMAD-dependent and independent signalling pathways were significantly activated by the combined induction treatment compared with the single factor induction. The hiPSC-derived MSC-like cells (hiPSC-MSCs) expressed MSC-related markers and acquired osteogenic, chondrogenic and adipogenic differentiation potentials. After being injected into the peritoneal cavity of rats, the hiPSC-MSCs secreted angiogenic and immune-regulatory factors and remained on the colicomentum for 3 weeks. Within an 11-week period, four intraperitoneal hiPSC-MSC injections (1x107 cells/injection) into acute myocardial infarction (AMI) model rats significantly increased the left ventricular ejection fraction, left ventricular fractional shortening and angiogenesis and significantly reduced scar size and the extent of apoptosis in the infarcted area compared with that of the control PBS injection. Symptoms of hiPSC-MSC-induced immune reaction or tumour formation were not observed over the course of the experiment in the hiSPC-MSC treated rats. In conclusion, the CHIR99021 and TGF-β combined induction was a rapid and effective method to obtain MSC-like cells from hiPSCs and multiple high dose intraperitoneal injections of hiPSC-derived MSCs were safe and effective at restoring cardiac function in an AMI rat model.

Data- and theory-driven approaches for understanding paths of epithelial-mesenchymal transition

Reversible transitions between epithelial and mesenchymal cell states are a crucial form of epithelial plasticity for development and disease progression. Recent experimental data and mechanistic models showed multiple intermediate epithelial-mesenchymal transition (EMT) states as well as trajectories of EMT underpinned by complex gene regulatory networks. In this review, we summarize recent progress in quantifying EMT and characterizing EMT paths with computational methods and quantitative experiments including omics-level measurements. We provide perspectives on how these studies can help relating fundamental cell biology to physiological and pathological outcomes of EMT.

Resveratrol is an inhibitory polyphenol of epithelial-mesenchymal transition induced by Fusobacterium nucleatum

OBJECTIVE

Resveratrol is a natural phytoalexin that has anti-inflammatory properties, reverses doxorubicin resistance, and inhibits epithelial-mesenchymal transition (EMT) in many types of cancer cells. Fusobacterium nucleatum is reportedly enriched in oral squamous cell carcinoma (OSCC) tissues compared to adjacent normal tissues, sparking interest in the relationship between F. nucleatum and OSCC. Recently, F. nucleatum was shown to be associated with EMT in OSCC. In the present study, we aimed to investigate the effects of the natural plant compound resveratrol on F. nucleatum-induced EMT in OSCC.

DESIGN

F. nucleatum was co-cultured with OSCC cells, with a multiplicity of infection (MOI) of 300:1. Resveratrol was used at a concentration of 10 μM. Cell Counting Kit-8 and wound healing assays were performed to examine the viability and migratory ability of OSCC cells. Subsequently, real-time RT-PCR was performed to investigate the gene expression of EMT-related markers. Western blotting and immunofluorescence analyses were used to further analyze the expression of the epithelial marker E-cadherin and the EMT transcription factor SNAI1.

RESULTS

Co-cultivation with F. nucleatum did not significantly enhance cell viability. The co-cultured cells displayed similarities to the positive control of EMT, exhibiting enhanced migration and expression changes in EMT-related markers. SNAI1 was significantly upregulated, whereas E-cadherin, was significantly downregulated. Notably, resveratrol inhibited F. nucleatum-induced cell migration, decreasing the expression of SNAI1.

CONCLUSIONS

Resveratrol inhibited F. nucleatum-induced EMT by downregulating SNAI1, which may provide a target for OSCC treatment.

Combinatorial Cooperativity in miR200-Zeb Feedback Network can Control Epithelial-Mesenchymal Transition

Carcinomas often utilize epithelial-mesenchymal transition (EMT) programs for cancer progression and metastasis. Numerous studies report SNAIL-induced miR200/Zeb feedback circuit as crucial in regulating EMT by placing cancer cells in at least three phenotypic states, viz. epithelial (E), hybrid (h-E/M), mesenchymal (M), along the E-M phenotypic spectrum. However, a coherent molecular-level understanding of how such a tiny circuit controls carcinoma cell entrance into and residence in various states is lacking. Here, we use molecular binding data and mathematical modeling to report that the miR200/Zeb circuit can essentially utilize combinatorial cooperativity to control E-M phenotypic plasticity. We identify minimal combinatorial cooperativities that give rise to E, h-E/M, and M phenotypes. We show that disrupting a specific number of miR200 binding sites on Zeb as well as Zeb binding sites on miR200 can have phenotypic consequences-the circuit can dynamically switch between two (E, M) and three (E, h-E/M, M) phenotypes. Further, we report that in both SNAIL-induced and SNAIL knock-out miR200/Zeb circuits, cooperative transcriptional feedback on Zeb as well as Zeb translation inhibition due to miR200 are essential for the occurrence of intermediate h-E/M phenotype. Finally, we demonstrate that SNAIL can be dispensable for EMT, and in the absence of SNAIL, the transcriptional feedback can control cell state transition from E to h-E/M, to M state. Our results thus highlight molecular-level regulation of EMT in miR200/Zeb circuit and we expect these findings to be crucial to future efforts aiming to prevent EMT-facilitated dissemination of carcinomas.

Tipping points in epithelial-mesenchymal lineages from single-cell transcriptomics data

Understanding cell fate decision-making during complex biological processes is an open challenge that is now aided by high-resolution single-cell sequencing technologies. Specifically, it remains challenging to identify and characterize transition states corresponding to "tipping points" whereby cells commit to new cell states. Here, we present a computational method that takes advantage of single-cell transcriptomics data to infer the stability and gene regulatory networks (GRNs) along cell lineages. Our method uses the unspliced and spliced counts from single-cell RNA sequencing data and cell ordering along lineage trajectories to train an RNA splicing multivariate model, from which cell-state stability along the lineage is inferred based on spectral analysis of the model's Jacobian matrix. Moreover, the model infers the RNA cross-species interactions resulting in GRNs and their variation along the cell lineage. When applied to epithelial-mesenchymal transition in ovarian and lung cancer-derived cell lines, our model predicts a saddle-node transition between the epithelial and mesenchymal states passing through an unstable, intermediate cell state. Furthermore, we show that the underlying GRN controlling epithelial-mesenchymal transition rearranges during the transition, resulting in denser and less modular networks in the intermediate state. Overall, our method represents a flexible tool to study cell lineages with a combination of theory-driven modeling and single-cell transcriptomics data.

Increased heterogeneity in expression of genes associated with cancer progression and drug resistance

Fluctuations in the number of regulatory molecules and differences in timings of molecular events can generate variation in gene expression among genetically identical cells in the same environmental condition. This variation, termed as expression noise, can create differences in metabolic state and cellular functions, leading to phenotypic heterogeneity. Expression noise and phenotypic heterogeneity have been recognized as important contributors to intra-tumor heterogeneity, and have been associated with cancer growth, progression, and therapy resistance. However, how expression noise changes with cancer progression in actual cancer patients has remained poorly explored. Such an analysis, through identification of genes with increasing expression noise, can provide valuable insights into generation of intra-tumor heterogeneity, and could have important implications for understanding immune-suppression, drug tolerance and therapy resistance. In this work, we performed a genome-wide identification of changes in gene expression noise with cancer progression using single-cell RNA-seq data of lung adenocarcinoma patients at different stages of cancer. We identified 37 genes in epithelial cells that showed an increasing noise trend with cancer progression, many of which were also associated with cancer growth, EMT and therapy resistance. We found that expression of several of these genes was positively associated with expression of mitochondrial genes, suggesting an important role of mitochondria in generation of heterogeneity. In addition, we uncovered substantial differences in sample-specific noise profiles which could have implications for personalized prognosis and treatment.

Identifying critical regulatory interactions in cell fate decision and transition by systematic perturbation analysis

One of the most significant challenges in biology is to elucidate the roles of various regulatory interactions in cell fate decision and transition. However, it remains to be fully clarified how they cooperate and determine fate transition. Here, a general framework based on statistical analysis and bifurcation theory is proposed to identify crucial regulatory interactions and how they play decisive roles in fate transition. More exactly, specific feedback loops determine occurrence of bifurcations by which cell fate transition can be realized. While regulatory interactions in the feedback loops determine the direction of transition. In addition, two-parameter bifurcation analysis further provides detailed understanding of how the fate transition based on statistical analysis occurs. Statistical analysis can also be used to reveal synergistic combinatorial perturbations by which fate transition can be more efficiently realized. The integrative analysis approach can be used to identify critical regulatory interactions in cell fate transition and reveal how specific cell fate transition occurs. To verify feasibility of the approach, the epithelial to mesenchymal transition (EMT) network is chosen as an illustrative example. In agreement with experimental observations, the approach reveals some critical regulatory interactions and underlying mechanisms in cell fate determination and transitions between three states. The approach can also be applied to analyze other regulatory networks related to cell fate decision and transition.

MicroRNA-200b-mediated reversion of a spectrum of epithelial-to-mesenchymal transition states in recessive dystrophic epidermolysis bullosa squamous cell carcinomas

BACKGROUND

Cutaneous squamous cell carcinoma (SCC) is the leading cause of death in patients with recessive dystrophic epidermolysis bullosa (RDEB). However, the survival time from first diagnosis differs between patients; some tumours spread particularly fast, while others may remain localized for years. As treatment options are limited, there is an urgent need for further insights into the pathomechanisms of RDEB tumours, to foster therapy development and support clinical decision-making.

OBJECTIVES

To investigate differences in RDEB tumours of diverging aggressiveness at the molecular and phenotypic level, with a particular focus on epithelial-to-mesenchymal (EMT) transition states and thus microRNA-200b (miR-200b) as a regulator.

METHODS

Primary RDEB-SCC keratinocyte lines were characterized with respect to their EMT state. For this purpose, cell morphology was classified and the expression of EMT markers analysed using immunofluorescence, flow cytometry, semi-quantitative reverse transcriptase polymerase chain reaction and Western blotting. The motility of RDEB-SCC cells was determined and conditioned medium of RDEB-SCC cells was used to treat endothelial cells in an angiogenesis assay. In addition, we mined previously generated microRNA (miRNA) profiling data to identify a candidate with potential therapeutic relevance and performed transient miRNA transfection studies to investigate the candidate's ability to reverse EMT characteristics.

RESULTS

We observed high variability in EMT state in the RDEB-SCC cell lines, which correlated with in situ analysis of two available patient biopsies and respective clinical disease course. Furthermore, we identified miR-200b-3p to be downregulated in RDEB-SCCs, and the extent of deregulation significantly correlated with the EMT features of the various tumour lines. miR-200b-3p was reintroduced into RDEB-SCC cell lines with pronounced EMT features, which resulted in a significant increase in epithelial characteristics, including cell morphology, EMT marker expression, migration and angiogenic potential.

CONCLUSIONS

RDEB-SCCs exist in different EMT states and the level of miR-200b is indicative of how far an RDEB-SCC has gone down the EMT path. Moreover, the reintroduction of miR-200b significantly reduced mesenchymal features.

A dynamical model of growth and maturation in Drosophila

The decision to stop growing and mature into an adult is a critical point in development that determines adult body size, impacting multiple aspects of an adult's biology. In many animals, growth cessation is a consequence of hormone release that appears to be tied to the attainment of a particular body size or condition. Nevertheless, the size-sensing mechanism animals use to initiate hormone synthesis is poorly understood. Here, we develop a simple mathematical model of growth cessation in Drosophila melanogaster, which is ostensibly triggered by the attainment of a critical weight (CW) early in the last instar. Attainment of CW is correlated with the synthesis of the steroid hormone ecdysone, which causes a larva to stop growing, pupate, and metamorphose into the adult form. Our model suggests that, contrary to expectation, the size-sensing mechanism that initiates metamorphosis occurs before the larva reaches CW; that is, the critical-weight phenomenon is a downstream consequence of an earlier size-dependent developmental decision, not a decision point itself. Further, this size-sensing mechanism does not require a direct assessment of body size but emerges from the interactions between body size, ecdysone, and nutritional signaling. Because many aspects of our model are evolutionarily conserved among all animals, the model may provide a general framework for understanding how animals commit to maturing from their juvenile to adult form.

Dynamical hallmarks of cancer: Phenotypic switching in melanoma and epithelial-mesenchymal plasticity

Phenotypic plasticity was recently incorporated as a hallmark of cancer. This plasticity can manifest along many interconnected axes, such as stemness and differentiation, drug-sensitive and drug-resistant states, and between epithelial and mesenchymal cell-states. Despite growing acceptance for phenotypic plasticity as a hallmark of cancer, the dynamics of this process remains poorly understood. In particular, the knowledge necessary for a predictive understanding of how individual cancer cells and populations of cells dynamically switch their phenotypes in response to the intensity and/or duration of their current and past environmental stimuli remains far from complete. Here, we present recent investigations of phenotypic plasticity from a systems-level perspective using two exemplars: epithelial-mesenchymal plasticity in carcinomas and phenotypic switching in melanoma. We highlight how an integrated computational-experimental approach has helped unravel insights into specific dynamical hallmarks of phenotypic plasticity in different cancers to address the following questions: a) how many distinct cell-states or phenotypes exist?; b) how reversible are transitions among these cell-states, and what factors control the extent of reversibility?; and c) how might cell-cell communication be able to alter rates of cell-state switching and enable diverse patterns of phenotypic heterogeneity? Understanding these dynamic features of phenotypic plasticity may be a key component in shifting the paradigm of cancer treatment from reactionary to a more predictive, proactive approach.

Constructing maps between distinct cell fates and parametric conditions by systematic perturbations

MOTIVATION

Cell fate transitions are common in many developmental processes. Therefore, identifying the mechanisms behind them is crucial. Traditionally, due to complexity of networks and existence of plenty of kinetic parameters, dynamical analysis of biomolecular networks can only be performed by simultaneously perturbing a small number of parameters. Although many efforts have focused on how cell states change under specific perturbations, conversely, how to infer parametric conditions underlying distinct cell fates by systematic perturbations is less clear and needs to be further investigated.

RESULTS

In this article, we present a general computational method by integrating systematic perturbations, unsupervised clustering, principal component analysis, and fitting analysis. The method can be used to to construct maps between distinct cell fates and parametric conditions by systematic perturbations. In particular, there are no needs of accurate parameter measurements and occurrence of bifurcations to establish the maps. To validate feasibility and inference performance of the method, we use toggle switch, inner cell mass, and epithelial mesenchymal transition as model systems to show how the maps are constructed and how system parameters encode essential information on cell fates. The maps tell us how systematic perturbations drive cell fate decisions and transitions, and allow us to purposefully predict, manipulate, and even control cell states. The approach is especially helpful in understanding crucial roles of certain parameter combinations during fate transitions. We hope that the approach can provide us valuable information on parametric or perturbation conditions so some specific targets, e.g. directional differentiation, can be realized.

AVAILABILITY AND IMPLEMENTATION

No public data are used. The data we used are generated by randomly chosen values of model parameters in certain ranges, and the corresponding parameters are already attached in supplementary materials.

The epithelial-mesenchymal plasticity landscape: principles of design and mechanisms of regulation

Epithelial-mesenchymal plasticity (EMP) enables cells to interconvert between several states across the epithelial-mesenchymal landscape, thereby acquiring hybrid epithelial/mesenchymal phenotypic features. This plasticity is crucial for embryonic development and wound healing, but also underlies the acquisition of several malignant traits during cancer progression. Recent research using systems biology and single-cell profiling methods has provided novel insights into the main forces that shape EMP, which include the microenvironment, lineage specification and cell identity, and the genome. Additionally, key roles have emerged for hysteresis (cell memory) and cellular noise, which can drive stochastic transitions between cell states. Here, we review these forces and the distinct but interwoven layers of regulatory control that stabilize EMP states or facilitate epithelial-mesenchymal transitions (EMTs) and discuss the therapeutic potential of manipulating the EMP landscape.

Tumor-mediated immunosuppression and cytokine spreading affects the relation between EMT and PD-L1 status

Epithelial-mesenchymal transition (EMT) and immune resistance mediated by Programmed Death-Ligand 1 (PD-L1) upregulation are established drivers of tumor progression. Their bi-directional crosstalk has been proposed to facilitate tumor immunoevasion, yet the impact of immunosuppression and spatial heterogeneity on the interplay between these processes remains to be characterized. Here we study the role of these factors using mathematical and spatial models. We first designed models incorporating immunosuppressive effects on T cells mediated via PD-L1 and the EMT-inducing cytokine Transforming Growth Factor beta (TGFβ). Our models predict that PD-L1-mediated immunosuppression merely reduces the difference in PD-L1 levels between EMT states, while TGFβ-mediated suppression also causes PD-L1 expression to correlate negatively with TGFβ within each EMT phenotype. We subsequently embedded the models in multi-scale spatial simulations to explicitly describe heterogeneity in cytokine levels and intratumoral heterogeneity. Our multi-scale models show that Interferon gamma (IFNγ)-induced partial EMT of a tumor cell subpopulation can provide some, albeit limited protection to bystander tumor cells. Moreover, our simulations show that the true relationship between EMT status and PD-L1 expression may be hidden at the population level, highlighting the importance of studying EMT and PD-L1 status at the single-cell level. Our findings deepen the understanding of the interactions between EMT and the immune response, which is crucial for developing novel diagnostics and therapeutics for cancer patients.

A Cell-Fate Reprogramming Strategy Reverses Epithelial-to-Mesenchymal Transition of Lung Cancer Cells While Avoiding Hybrid States

The epithelial-to-mesenchymal transition (EMT) of primary cancer contributes to the acquisition of lethal properties, including metastasis and drug resistance. Blocking or reversing EMT could be an effective strategy to improve cancer treatment. However, it is still unclear how to achieve complete EMT reversal (rEMT), as cancer cells often transition to hybrid EMT states with high metastatic potential. To tackle this problem, we employed a systems biology approach and identified a core-regulatory circuit that plays the primary role in driving rEMT without hybrid properties. Perturbation of any single node was not sufficient to completely revert EMT. Inhibition of both SMAD4 and ERK signaling along with p53 activation could induce rEMT in cancer cells even with TGFβ stimulation, a primary inducer of EMT. Induction of rEMT in lung cancer cells with the triple combination approach restored chemosensitivity. This cell-fate reprogramming strategy based on attractor landscapes revealed potential therapeutic targets that can eradicate metastatic potential by subverting EMT while avoiding hybrid states.

SIGNIFICANCE

Network modeling unravels the highly complex and plastic process regulating epithelial and mesenchymal states in cancer cells and discovers therapeutic interventions for reversing epithelial-to-mesenchymal transition and enhancing chemosensitivity.

Involvement of Epithelial-Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity

Small cell lung cancer (SCLC) is an aggressive cancer recalcitrant to treatment, arising predominantly from epithelial pulmonary neuroendocrine (NE) cells. Intratumor heterogeneity plays critical roles in SCLC disease progression, metastasis, and treatment resistance. At least five transcriptional SCLC NE and non-NE cell subtypes were recently defined by gene expression signatures. Transition from NE to non-NE cell states and cooperation between subtypes within a tumor likely contribute to SCLC progression by mechanisms of adaptation to perturbations. Therefore, gene regulatory programs distinguishing SCLC subtypes or promoting transitions are of great interest. Here, we systematically analyze the relationship between SCLC NE/non-NE transition and epithelial to mesenchymal transition (EMT)-a well-studied cellular process contributing to cancer invasiveness and resistance-using multiple transcriptome datasets from SCLC mouse tumor models, human cancer cell lines, and tumor samples. The NE SCLC-A2 subtype maps to the epithelial state. In contrast, SCLC-A and SCLC-N (NE) map to a partial mesenchymal state (M1) that is distinct from the non-NE, partial mesenchymal state (M2). The correspondence between SCLC subtypes and the EMT program paves the way for further work to understand gene regulatory mechanisms of SCLC tumor plasticity with applicability to other cancer types.

Harnessing epithelial-mesenchymal plasticity to boost cancer immunotherapy

Immune checkpoint blockade (ICB) therapy is a powerful option for cancer treatment. Despite demonstrable progress, most patients fail to respond or achieve durable responses due to primary or acquired ICB resistance. Recently, tumor epithelial-to-mesenchymal plasticity (EMP) was identified as a critical determinant in regulating immune escape and immunotherapy resistance in cancer. In this review, we summarize the emerging role of tumor EMP in ICB resistance and the tumor-intrinsic or extrinsic mechanisms by which tumors exploit EMP to achieve immunosuppression and immune escape. We discuss strategies to modulate tumor EMP to alleviate immune resistance and to enhance the efficiency of ICB therapy. Our discussion provides new prospects to enhance the ICB response for therapeutic gain in cancer patients.

Heterogeneity and plasticity of epithelial-mesenchymal transition (EMT) in cancer metastasis: Focusing on partial EMT and regulatory mechanisms

Epithelial-mesenchymal transition (EMT) or mesenchymal-epithelial transition (MET) plays critical roles in cancer metastasis. Recent studies, especially those based on single-cell sequencing, have revealed that EMT is not a binary process, but a heterogeneous and dynamic disposition with intermediary or partial EMT states. Multiple double-negative feedback loops involved by EMT-related transcription factors (EMT-TFs) have been identified. These feedback loops between EMT drivers and MET drivers finely regulate the EMT transition state of the cell. In this review, the general characteristics, biomarkers and molecular mechanisms of different EMT transition states were summarized. We additionally discussed the direct and indirect roles of EMT transition state in tumour metastasis. More importantly, this article provides direct evidence that the heterogeneity of EMT is closely related to the poor prognosis in gastric cancer. Notably, a seesaw model was proposed to explain how tumour cells regulate themselves to remain in specific EMT transition states, including epithelial state, hybrid/intermediate state and mesenchymal state. Additionally, this article also provides a review of the current status, limitations and future perspectives of EMT signalling in clinical applications.

Single-copy Snail upregulation causes partial epithelial-mesenchymal transition in colon cancer cells

BACKGROUND

Epithelial-mesenchymal transition (EMT) is an embryonic programme implicated in cancer stem cells, metastasis and therapeutic resistance. Its role in cancer progression remains controversial because the transition can be partial or complete in different models and contexts.

METHODS

Using human colon cancer DLD-1 cells, we engineered a cell line with a single-copy of Snail that was doxycycline-inducible and compared it to existing EMT models in DLD-1. The effect of Snail upregulation was characterised functionally, morphologically, and by transcriptional profiling and protein expression.

RESULTS

Induction with doxycycline increased Snail expression to a level similar to that observed in cancer cell lines spontaneously expressing Snail and results in partial EMT. In comparison, higher levels of overexpression arising from introduction of episomal-Snail, results in complete EMT. DLD-1 cells with partial EMT show chemoresistance in vitro, increased tumour growth in vivo and decreased apoptosis.

CONCLUSIONS

These findings highlight that the amount of bioavailable Snail can dictate phenotypic outcome and that partial EMT may be a preferred outcome of models operating within a natural range of Snail overexpression.

Encoding and Decoding of p53 Dynamics in Cellular Response to Stresses

In the cellular response to stresses, the tumor suppressor p53 is activated to maintain genomic integrity and fidelity. As a transcription factor, p53 exhibits rich dynamics to allow for discrimination of the type and intensity of stresses and to direct the selective activation of target genes involved in different processes including cell cycle arrest and apoptosis. In this review, we focused on how stresses are encoded into p53 dynamics and how the dynamics are decoded into cellular outcomes. Theoretical modeling may provide a global view of signaling in the p53 network by coupling the encoding and decoding processes. We discussed the significance of modeling in revealing the mechanisms of the transition between p53 dynamic modes. Moreover, we shed light on the crosstalk between the p53 network and other signaling networks. This review may advance the understanding of operating principles of the p53 signaling network comprehensively and provide insights into p53 dynamics-based cancer therapy.

A data-driven optimization method for coarse-graining gene regulatory networks

One major challenge in systems biology is to understand how various genes in a gene regulatory network (GRN) collectively perform their functions and control network dynamics. This task becomes extremely hard to tackle in the case of large networks with hundreds of genes and edges, many of which have redundant regulatory roles and functions. The existing methods for model reduction usually require the detailed mathematical description of dynamical systems and their corresponding kinetic parameters, which are often not available. Here, we present a data-driven method for coarse-graining large GRNs, named SacoGraci, using ensemble-based mathematical modeling, dimensionality reduction, and gene circuit optimization by Markov Chain Monte Carlo methods. SacoGraci requires network topology as the only input and is robust against errors in GRNs. We benchmark and demonstrate its usage with synthetic, literature-based, and bioinformatics-derived GRNs. We hope SacoGraci will enhance our ability to model the gene regulation of complex biological systems.

Minimal frustration underlies the usefulness of incomplete regulatory network models in biology

Regulatory networks as large and complex as those implicated in cell-fate choice are expected to exhibit intricate, very high-dimensional dynamics. Cell-fate choice, however, is a macroscopically simple process. Additionally, regulatory network models are almost always incomplete and/or inexact, and do not incorporate all the regulators and interactions that may be involved in cell-fate regulation. In spite of these issues, regulatory network models have proven to be incredibly effective tools for understanding cell-fate choice across contexts and for making useful predictions. Here, we show that minimal frustration-a feature of biological networks across contexts but not of random networks-can compel simple, low-dimensional steady-state behavior even in large and complex networks. Moreover, the steady-state behavior of minimally frustrated networks can be recapitulated by simpler networks such as those lacking many of the nodes and edges and those that treat multiple regulators as one. The present study provides a theoretical explanation for the success of network models in biology and for the challenges in network inference.

Epigenetic memory acquired during long-term EMT induction governs the recovery to the epithelial state

Epithelial-mesenchymal transition (EMT) and its reverse mesenchymal-epithelial transition (MET) are critical during embryonic development, wound healing and cancer metastasis. While phenotypic changes during short-term EMT induction are reversible, long-term EMT induction has been often associated with irreversibility. Here, we show that phenotypic changes seen in MCF10A cells upon long-term EMT induction by TGFβ need not be irreversible, but have relatively longer time scales of reversibility than those seen in short-term induction. Next, using a phenomenological mathematical model to account for the chromatin-mediated epigenetic silencing of the miR-200 family by ZEB family, we highlight how the epigenetic memory gained during long-term EMT induction can slow the recovery to the epithelial state post-TGFβ withdrawal. Our results suggest that epigenetic modifiers can govern the extent and time scale of EMT reversibility and advise caution against labelling phenotypic changes seen in long-term EMT induction as 'irreversible'.

Coordination of the AMPK, Akt, mTOR, and p53 Pathways under Glucose Starvation

Glucose is a direct energy source for eukaryotic cells, and its deficiency elicits complex stress responses and diverse cellular outcomes. Although several signaling pathways involved have been identified, how they coordinately dictate the cell fate remains obscure. We propose a minimal network model for the cellular response to glucose restriction, characterizing the glucose uptake and signaling of the AMPK, Akt, mTOR, and p53 pathways. We demonstrate that in the presence of sufficient growth factors and amino acids, cells may undergo proliferation, senescence, or apoptosis, depending on the extracellular glucose level. AMPK is first activated upon glucose limitation, activating p53 to induce cell-cycle arrest; possibly, cells resume proliferation after timely glucose restoration. For long-term energy stress, cell senescence is maintained by low/intermediate levels of p53 and persistent activation of mTOR and Akt, or cells commit apoptosis when the proteins undergo biphasic dynamics, e.g., p53 switches from intermediate levels to high levels while mTOR and Akt become inactivated in the later phase. The biphasic dynamics of p53 are associated with flipping of two bistable switches. Appropriate mTOR levels are required for optimal cell-fate decision. This work suggests that senescence and apoptosis occur sequentially in glucose-depleted cells, and a theoretical framework is provided for exploring the cellular response to energy stress.

Network topology metrics explaining enrichment of hybrid epithelial mesenchymal phenotypes in metastasis

Epithelial to Mesenchymal Transition (EMT) and its reverse—Mesenchymal to Epithelial Transition (MET) are hallmarks of metastasis. Cancer cells use this reversible cellular programming to switch among Epithelial (E), Mesenchymal (M), and hybrid Epithelial/Mesenchymal (hybrid E/M) state(s) and seed tumors at distant sites. Hybrid E/M cells are often more aggressive and metastatic than the “pure” E and M cells. Thus, identifying mechanisms to inhibit hybrid E/M cells can be promising in curtailing metastasis. While multiple gene regulatory networks (GRNs) based mathematical models for EMT/MET have been developed recently, identifying topological signatures enriching hybrid E/M phenotypes remains to be done. Here, we investigate the dynamics of 13 different GRNs and report an interesting association between “hybridness” and the number of negative/positive feedback loops across the networks. While networks having more negative feedback loops favor hybrid phenotype(s), networks having more positive feedback loops (PFLs) or many HiLoops–specific combinations of PFLs, support terminal (E and M) phenotypes. We also establish a connection between “hybridness” and network-frustration by showing that hybrid phenotypes likely result from non-reinforcing interactions among network nodes (genes) and therefore tend to be more frustrated (less stable). Our analysis, thus, identifies network topology-based signatures that can give rise to, as well as prevent, the emergence of hybrid E/M phenotype in GRNs underlying EMP. Our results can have implications in terms of targeting specific interactions in GRNs as a potent way to restrict switching to the hybrid E/M phenotype(s) to curtail metastasis.

spliceJAC: transition genes and state-specific gene regulation from single-cell transcriptome data

Extracting dynamical information from single-cell transcriptomics is a novel task with the promise to advance our understanding of cell state transition and interactions between genes. Yet, theory-oriented, bottom-up approaches that consider differences among cell states are largely lacking. Here, we present spliceJAC, a method to quantify the multivariate mRNA splicing from single-cell RNA sequencing (scRNA-seq). spliceJAC utilizes the unspliced and spliced mRNA count matrices to constructs cell state-specific gene-gene regulatory interactions and applies stability analysis to predict putative driver genes critical to the transitions between cell states. By applying spliceJAC to biological systems including pancreas endothelium development and epithelial-mesenchymal transition (EMT) in A549 lung cancer cells, we predict genes that serve specific signaling roles in different cell states, recover important differentially expressed genes in agreement with pre-existing analysis, and predict new transition genes that are either exclusive or shared between different cell state transitions.

Bidirectional crosstalk between epithelial-mesenchymal plasticity and IFNγ-induced PD-L1 expression promotes tumour progression

Epithelial-mesenchymal transition (EMT) and immunoevasion through upregulation of programmed death-ligand 1 (PD-L1) are important drivers of cancer progression. While EMT has been proposed to facilitate PD-L1-mediated immunosuppression, molecular mechanisms of their interaction remain obscure. Here, we provide insight into these mechanisms by proposing a mathematical model that describes the crosstalk between EMT and interferon gamma (IFNγ)-induced PD-L1 expression. Our model shows that via interaction with microRNA-200 (miR-200), the multi-stability of the EMT regulatory circuit is mirrored in PD-L1 levels, which are further amplified by IFNγ stimulation. This IFNγ-mediated effect is most prominent for cells in a fully mesenchymal state and less strong for those in an epithelial or partially mesenchymal state. In addition, bidirectional crosstalk between miR-200 and PD-L1 implies that IFNγ stimulation allows cells to undergo EMT for lower amounts of inducing signal, and the presence of IFNγ accelerates EMT and decelerates mesenchymal-epithelial transition (MET). Overall, our model agrees with published findings and provides insight into possible mechanisms behind EMT-mediated immune evasion, and primary, adaptive, or acquired resistance to immunotherapy. Our model can be used as a starting point to explore additional crosstalk mechanisms, as an improved understanding of these mechanisms is indispensable for developing better diagnostic and therapeutic options for cancer patients.

Cooperative RNA degradation stabilizes intermediate epithelial-mesenchymal states and supports a phenotypic continuum

Multiple intermediate epithelial-mesenchymal transition (EMT) states reflecting hybrid epithelial and mesenchymal phenotypes were observed in physiological and pathological conditions. Previous theoretical models explaining multiple EMT states rely on regulatory loops involving transcriptional feedback, which produce three or four attractors. This is incompatible with the observed continuum-like EMT spectrum. Here, we used mass-action-based models to describe post-transcriptional regulations, finding that cooperative RNA degradation via multiple microRNA binding sites can generate four-attractor systems without transcriptional feedback. Furthermore, the newly identified intermediates-enabling circuits are common in the EMT regulatory network, and they can synergize with transcriptional feedback to support phenotypic continuum. Finally, our model predicted a role of miR-101 in multistate EMT, and we identified evidence from single-cell RNA-sequencing data that support the prediction. Our work reveals a previously unknown role of cooperative RNA degradation and microRNAs in EMT, providing a framework that can bridge the gap between mechanistic models and single-cell experiments.

P4HA2: A link between tumor-intrinsic hypoxia, partial EMT and collective migration

Epithelial-to-mesenchymal transition (EMT), a well-established phenomenon studied across pan-cancer types, has long been known to be a major player in driving tumor invasion and metastasis. Recent studies have highlighted the importance of partial EMT phenotypes in metastasis. Initially thought as a transitional state between epithelial and mesenchymal phenotypic states, partial EMT state is now widely recognized as a key driver of intra-tumoral heterogeneity and phenotypic plasticity, further accelerating tumor metastasis and therapeutic resistance. However, how tumor microenvironment regulates partial EMT phenotypes remains unclear. We have developed unique size-controlled three-dimensional microtumor models that recapitulate tumor-intrinsic hypoxia and the emergence of collectively migrating cells. In this study, we further interrogate these microtumor models to understand how tumor-intrinsic hypoxia regulates partial EMT and collective migration in hypoxic large microtumors fabricated from T47D breast cancer cells. We compared global gene expression profiles of hypoxic, migratory microtumors to that of non-hypoxic, non-migratory microtumors at early and late time-points. Using our microtumor models, we identified unique gene signatures for tumor-intrinsic hypoxia (early versus late), partial EMT and migration (pre-migratory versus migratory phenotype). Through differential gene expression analysis between the microtumor models with an overlap of hypoxia, partial EMT and migration signatures, we identified prolyl 4-hydroxylase subunit 2 (P4HA2), a hypoxia responsive gene, as a central regulator common to hypoxia, partial EMT and collective migration. Further, the inhibition of P4HA2 significantly blocked collective migration in hypoxic microtumors. Thus, using the integrated computational-experimental analysis, we identify the key role of P4HA2 in tumor-intrinsic hypoxia-driven partial EMT and collective migration.

Non-coding RNAs and epithelial mesenchymal transition in cancer: molecular mechanisms and clinical implications

Epithelial-mesenchymal transition (EMT) is a fundamental process for embryonic development during which epithelial cells acquire mesenchymal characteristics, and the underlying mechanisms confer malignant features to carcinoma cells such as dissemination throughout the organism and resistance to anticancer treatments. During the past decades, an entire class of molecules, called non-coding RNA (ncRNA), has been characterized as a key regulator of almost every cellular process, including EMT. Like protein-coding genes, ncRNAs can be deregulated in cancer, acting as oncogenes or tumor suppressors. The various forms of ncRNAs, including microRNAs, PIWI-interacting RNAs, small nucleolar RNAs, transfer RNA-derived RNA fragments, long non-coding RNAs, and circular RNAs can orchestrate the complex regulatory networks of EMT at multiple levels. Understanding the molecular mechanism underlying ncRNAs in EMT can provide fundamental insights into cancer metastasis and may lead to novel therapeutic approaches. In this review, we describe recent advances in the understanding of ncRNAs in EMT and provide an overview of recent ncRNA applications in the clinic.

Stochastic population dynamics of cancer stemness and adaptive response to therapies

Intratumoral heterogeneity can exist along multiple axes: Cancer stem cells (CSCs)/non-CSCs, drug-sensitive/drug-tolerant states, and a spectrum of epithelial-hybrid-mesenchymal phenotypes. Further, these diverse cell-states can switch reversibly among one another, thereby posing a major challenge to therapeutic efficacy. Therefore, understanding the origins of phenotypic plasticity and heterogeneity remains an active area of investigation. While genomic components (mutations, chromosomal instability) driving heterogeneity have been well-studied, recent reports highlight the role of non-genetic mechanisms in enabling both phenotypic plasticity and heterogeneity. Here, we discuss various processes underlying phenotypic plasticity such as stochastic gene expression, chromatin reprogramming, asymmetric cell division and the presence of multiple stable gene expression patterns ('attractors'). These processes can facilitate a dynamically evolving cell population such that a subpopulation of (drug-tolerant) cells can survive lethal drug exposure and recapitulate population heterogeneity on drug withdrawal, leading to relapse. These drug-tolerant cells can be both pre-existing and also induced by the drug itself through cell-state reprogramming. The dynamics of cell-state transitions both in absence and presence of the drug can be quantified through mathematical models. Such a dynamical systems approach to elucidating patterns of intratumoral heterogeneity by integrating longitudinal experimental data with mathematical models can help design effective combinatorial and/or sequential therapies for better clinical outcomes.

The molecular mechanisms and therapeutic strategies of EMT in tumor progression and metastasis

Epithelial–mesenchymal transition (EMT) is an essential process in normal embryonic development and tissue regeneration. However, aberrant reactivation of EMT is associated with malignant properties of tumor cells during cancer progression and metastasis, including promoted migration and invasiveness, increased tumor stemness, and enhanced resistance to chemotherapy and immunotherapy. EMT is tightly regulated by a complex network which is orchestrated with several intrinsic and extrinsic factors, including multiple transcription factors, post-translational control, epigenetic modifications, and noncoding RNA-mediated regulation. In this review, we described the molecular mechanisms, signaling pathways, and the stages of tumorigenesis involved in the EMT process and discussed the dynamic non-binary process of EMT and its role in tumor metastasis. Finally, we summarized the challenges of chemotherapy and immunotherapy in EMT and proposed strategies for tumor therapy targeting EMT.

A data-assimilation approach to predict population dynamics during epithelial-mesenchymal transition

Epithelial-mesenchymal transition (EMT) is a biological process that plays a central role in embryonic development, tissue regeneration, and cancer metastasis. Transforming growth factor-β (TGFβ) is a potent inducer of this cellular transition, comprising transitions from an epithelial state to partial or hybrid EMT state(s), to a mesenchymal state. Recent experimental studies have shown that, within a population of epithelial cells, heterogeneous phenotypical profiles arise in response to different time- and TGFβ dose-dependent stimuli. This offers a challenge for computational models, as most model parameters are generally obtained to represent typical cell responses, not necessarily specific responses nor to capture population variability. In this study, we applied a data-assimilation approach that combines limited noisy observations with predictions from a computational model, paired with parameter estimation. Synthetic experiments mimic the biological heterogeneity in cell states that is observed in epithelial cell populations by generating a large population of model parameter sets. Analysis of the parameters for virtual epithelial cells with biologically significant characteristics (e.g., EMT prone or resistant) illustrates that these sub-populations have identifiable critical model parameters. We perform a series of in silico experiments in which a forecasting system reconstructs the EMT dynamics of each virtual cell within a heterogeneous population exposed to time-dependent exogenous TGFβ dose and either an EMT-suppressing or EMT-promoting perturbation. We find that estimating population-specific critical parameters significantly improved the prediction accuracy of cell responses. Thus, with appropriate protocol design, we demonstrate that a data-assimilation approach successfully reconstructs and predicts the dynamics of a heterogeneous virtual epithelial cell population in the presence of physiological model error and parameter uncertainty.

Engaging plasticity: Differentiation therapy in solid tumors

Cancer is a systemic heterogeneous disease that can undergo several rounds of latency and activation. Tumor progression evolves by increasing diversity, adaptation to signals from the microenvironment and escape mechanisms from therapy. These dynamic processes indicate necessity for cell plasticity. Epithelial-mesenchymal transition (EMT) plays a major role in facilitating cell plasticity in solid tumors by inducing dedifferentiation and cell type transitions. These two practices, plasticity and dedifferentiation enhance tumor heterogeneity creating a key challenge in cancer treatment. In this review we will explore cancer cell plasticity and elaborate treatment modalities that aspire to overcome such dynamic processes in solid tumors. We will further discuss the therapeutic potential of utilizing enhanced cell plasticity for differentiation therapy.

Macrophage induced ERK-TGF-β1 signaling in MCF7 breast cancer cells result in reversible cancer stem cell plasticity and epithelial mesenchymal transition

BACKGROUND

Breast cancer is a heterogenous disease composed of multiple clonal populations and the mechanism by which the tumor microenvironment induces cancer stem cell plasticity is not fully understood.

METHODS

MCF7 breast cancer cells were treated with macrophage conditioned medium (MɸCM). PD98059 and SB431542 were used for ERK and TGF-βR inhibition respectively. Epithelial-mesenchymal transition (EMT) and cancer stem cell markers (CSC) were studied using qRT-PCR and flowcytometry. SCID mice were used for animal experiments.

RESULTS

MɸCM- induced ERK/TGF-β1 signaling led to enrichment of CSC and EMT in MCF7 cells and mammospheres. These effects were abrogated by both MEK inhibitor PD98059 (TGF-β1 synthesis) and SB431542 (TGF-β1 signaling). The increase in CSC was both hybrid (ALDH1⁺) and mesenchymal (CD44⁺ CD24^- cells). Increase in hybrid E/M state was at a single cell level as confirmed by the increase in both claudin-1 (E) and vimentin (M). This did not have any growth advantage in SCID mice and monitoring of CSC and EMT markers before and after growth in SCID mice indicated reversal of these markers in tumor cells recovered from mice. Removal of MɸCM and neutralization of TNF-α, IL-6 and IL-1β in MɸCM abrogated ERK phosphorylation, TGF-β and CSC enrichment indicating the requirement of continuous signaling for maintenance.

CONCLUSIONS

ERK signaling plays an important role in MɸCM- induced EMT and CSC plasticity which is completely reversible upon withdrawal of signals.

GENERAL SIGNIFICANCE

Our experimental observations support the semi-independent nature of EMT-stemness connection which is very dynamic and reversible depending on the microenvironment.

Lack of Correlation between Landscape Geometry and Transition Rates

Biological cells can exist in a variety of distinct phenotypes, determined by the steady-state solutions of genetic networks governing their cell fate. A popular way of representing these states relies on the creation of landscape related to the relative occupation of these states. It is often assumed that this landscape offers direct information regarding the state-to-state transition rates, suggesting that these are related to barrier heights separating landscape minima. Here, we study a toggle triad network exhibiting multistability and directly demonstrate the lack of any direct correlation between properties of the landscape and corresponding transition rates.

Comparative single-cell transcriptomes of dose and time dependent epithelial–mesenchymal spectrums

Epithelial–mesenchymal transition (EMT) is a cellular process involved in development and disease progression. Intermediate EMT states were observed in tumors and fibrotic tissues, but previous in vitro studies focused on time-dependent responses with single doses of signals; it was unclear whether single-cell transcriptomes support stable intermediates observed in diseases. Here, we performed single-cell RNA-sequencing with human mammary epithelial cells treated with multiple doses of TGF-β. We found that dose-dependent EMT harbors multiple intermediate states at nearly steady state. Comparisons of dose- and time-dependent EMT transcriptomes revealed that the dose-dependent data enable higher sensitivity to detect genes associated with EMT. We identified cell clusters unique to time-dependent EMT, reflecting cells en route to stable states. Combining dose- and time-dependent cell clusters gave rise to accurate prognosis for cancer patients. Our transcriptomic data and analyses uncover a stable EMT continuum at the single-cell resolution, and complementary information of two types of single-cell experiments.

SNAIL driven by a feed forward loop motif promotes TGFβinduced epithelial to mesenchymal transition

Epithelial to Mesenchymal Transition (EMT) plays an important role in tissue regeneration, embryonic development, and cancer metastasis. Several signaling pathways are known to regulate EMT, among which the modulation of TGFβ(Transforming Growth Factor-β) induced EMT is crucial in several cancer types. Several mathematical models were built to explore the role of core regulatory circuit of ZEB/miR-200, SNAIL/miR-34 double negative feedback loops in modulating TGFβinduced EMT. Different emergent behavior including tristability, irreversible switching, existence of hybrid EMT states were inferred though these models. Some studies have explored the role of TGFβreceptor activation, SMADs nucleocytoplasmic shuttling and complex formation. Recent experiments have revealed that MDM2 along with SMAD complex regulates SNAIL expression driven EMT. Encouraged by this, in the present study we developed a mathematical model for p53/MDM2 dependent TGFβinduced EMT regulation. Inclusion of p53 brings in an additional mechanistic perspective in exploring the EM transition. The network formulated comprises a C1FFL moderating SNAIL expression involving MDM2 and SMAD complex, which functions as a noise filter and persistent detector. The C1FFL was also observed to operate as a coincidence detector driving the SNAIL dependent downstream signaling into phenotypic switching decision. Systems modelling and analysis of the devised network, displayed interesting dynamic behavior, systems response to various inputs stimulus, providing a better understanding of p53/MDM2 dependent TGF-βinduced Epithelial to Mesenchymal Transition.

Emergence of Resistance to MTI-101 Selects for a MET Genotype and Phenotype in EGFR Driven PC-9 and PTEN Deleted H446 Lung Cancer Cell Lines

MTI-101 is a first-in-class cyclic peptide that kills cells via calcium overload in a caspase-independent manner. Understanding biomarkers of response is critical for positioning a novel therapeutic toward clinical development. Isogenic MTI-101-acquired drug-resistant lung cancer cell line systems (PC-9 and H446) coupled with differential RNA-SEQ analysis indicated that downregulated genes were enriched in the hallmark gene set for epithelial-to-mesenchymal transition (EMT) in both MTI-101-acquired resistant cell lines. The RNA-SEQ results were consistent with changes in the phenotype, including a decreased invasion in Matrigel and expression changes in EMT markers (E-cadherin, vimentin and Twist) at the protein level. Furthermore, in the EGFR-driven PC-9 cell line, selection for resistance towards MTI-101 resulted in collateral sensitivity toward EGFR inhibitors. MTI-101 treatment showed synergistic activity with the standard of care agents erlotinib, osimertinib and cisplatin when used in combination in PC-9 and H446 cells, respectively. Finally, in vivo data indicate that MTI-101 treatment selects for increased E-cadherin and decreased vimentin in H446, along with a decreased incident of bone metastasis in the PC-9 in vivo model. Together, these data indicate that chronic MTI-101 treatment can lead to a change in cell state that could potentially be leveraged therapeutically to reduce metastatic disease.

The Wnt pathway can stabilize hybrid phenotypes in the epithelial-mesenchymal transition: A logical modeling approach

The Wnt pathway is important to regulate a variety of biochemical functions and can contribute to cancer development through its influence on the epithelial-mesenchymal transition (EMT). Multiple circuits have been reported to participate in the regulation of the Wnt signaling, however, the way these circuits coordinately regulate this signaling is still unclear. Moreover, the mechanisms responsible for the appearance of hybrid phenotypes (cells presenting both E and M features) are not well determined. The hybrid phenotype can present much higher metastatic potential than the mesenchymal phenotype. In this study, we propose a Boolean model of the Wnt pathway signaling contemplating recent published biochemical information on hepatocarcinoma. The model presents good coherence with experimental data for perturbed and wild-type cases. With the model, we propose two new molecular circuits involving several molecules that can stabilize hybrid states during the EMT. Moreover, we found that the two well studied circuits, AKT1/β-catenin and SNAIL1/miR-34, can cooperate with the predicted ones to favor the stabilization of the hybrid states. These findings highlight some possible unrecognized mechanisms during Wnt signaling and may provide alternative therapeutic strategies to control cancer metastatization.

Translocating proteins compartment-specifically alter the fate of epithelial-mesenchymal transition in a compartmentalized Boolean network model

Regulation of translocating proteins is crucial in defining cellular behaviour. Epithelial-mesenchymal transition (EMT) is important in cellular processes, such as cancer progression. Several orchestrators of EMT, such as key transcription factors, are known to translocate. We show that translocating proteins become enriched in EMT-signalling. To simulate the compartment-specific functions of translocating proteins we created a compartmentalized Boolean network model. This model successfully reproduced known biological traits of EMT and as a novel feature it also captured organelle-specific functions of proteins. Our results predicted that glycogen synthase kinase-3 beta (GSK3B) compartment-specifically alters the fate of EMT, amongst others the activation of nuclear GSK3B halts transforming growth factor beta-1 (TGFB) induced EMT. Moreover, our results recapitulated that the nuclear activation of glioma associated oncogene transcription factors (GLI) is needed to achieve a complete EMT. Compartmentalized network models will be useful to uncover novel control mechanisms of biological processes. Our algorithmic procedures can be automatically rerun on the https://translocaboole.linkgroup.hu website, which provides a framework for similar future studies.

Modeling the influence of cell-cell contact and TGF-β signaling on the epithelial mesenchymal transition in MCF7 breast carcinoma cells

The epithelial mesenchymal transition (EMT) is a process by which cells lose their adhesive nature and gain the migratory properties associated with mesenchymal cells. This transition allows cells to migrate away from a primary tumor while maintaining their newly acquired invasive behavior, suggesting that there is a bistable switch between the epithelial and mesenchymal phenotypes. In recent experimental work, we found evidence of this bistability in the MCF7 breast carcinoma cell line (Gasior et al., 2019). Underlying the complex processes governing EMT, we identify a feedback loop between E-cadherin, a protein involved in cellular adhesion, and Slug, a transcription factor that is upregulated during EMT. Here, we present a simple mathematical model that examines the relationship between E-cadherin and Slug in response to pro-epithelial and pro-mesenchymal factors, cell-cell contact and TGF-β, respectively. We hypothesize that cell-cell contact is a critical component in the transition from the epithelial to the mesenchymal phenotype and that it is possible to initiate EMT with the loss of cell-cell contact or the activation of the TGF-β signaling pathway. We propose a reversible bistable switch in response to a loss of cell-cell contact but an irreversible bistable switch when the cell is exposed to TGF-β. Taken together, this model shows that acquiring and retaining invasive behavior by cells with high levels of cell-cell contact is not impossible but, instead, depends on the cooperation between the two switches. The predictions of this model for E-cadherin and Slug levels were compared against relative gene expression data from our recent experiments with MCF7 cells (Gasior et al., 2019). Our model works well to predict E-cadherin and Slug mRNA expression in low confluence experiments, while also highlighting issues that arise when comparing in vitro experimental results to theoretical predictions.

Multi-synchronization and other patterns of multi-rhythmicity in oscillatory biological systems

While experimental and theoretical studies have established the prevalence of rhythmic behaviour at all levels of biological organization, less common is the coexistence between multiple oscillatory regimes (multi-rhythmicity), which has been predicted by a variety of models for biological oscillators. The phenomenon of multi-rhythmicity involves, most commonly, the coexistence between two (birhythmicity) or three (trirhythmicity) distinct regimes of self-sustained oscillations. Birhythmicity has been observed experimentally in a few chemical reactions and in biological examples pertaining to cardiac cell physiology, neurobiology, human voice patterns and ecology. The present study consists of two parts. We first review the mechanisms underlying multi-rhythmicity in models for biochemical and cellular oscillations in which the phenomenon was investigated over the years. In the second part, we focus on the coupling of the cell cycle and the circadian clock and show how an additional source of multi-rhythmicity arises from the bidirectional coupling of these two cellular oscillators. Upon bidirectional coupling, the two oscillatory networks generally synchronize in a unique manner characterized by a single, common period. In some conditions, however, the two oscillators may synchronize in two or three different ways characterized by distinct waveforms and periods. We refer to this type of multi-rhythmicity as ‘multi-synchronization’.

Nonmodular oscillator and switch based on RNA decay drive regeneration of multimodal gene expression

Periodic gene expression dynamics are key to cell and organism physiology. Studies of oscillatory expression have focused on networks with intuitive regulatory negative feedback loops, leaving unknown whether other common biochemical reactions can produce oscillations. Oscillation and noise have been proposed to support mammalian progenitor cells’ capacity to restore heterogenous, multimodal expression from extreme subpopulations, but underlying networks and specific roles of noise remained elusive. We use mass-action-based models to show that regulated RNA degradation involving as few as two RNA species—applicable to nearly half of human protein-coding genes—can generate sustained oscillations without explicit feedback. Diverging oscillation periods synergize with noise to robustly restore cell populations’ bimodal expression on timescales of days. The global bifurcation organizing this divergence relies on an oscillator and bistable switch which cannot be decomposed into two structural modules. Our work reveals surprisingly rich dynamics of post-transcriptional reactions and a potentially widespread mechanism underlying development, tissue regeneration, and cancer cell heterogeneity.

TGFβ selects for pro-stemness over pro-invasive phenotypes during cancer cell epithelial-mesenchymal transition

Transforming growth factor β (TGFβ) induces epithelial-mesenchymal transition (EMT), which correlates with stemness and invasiveness. Mesenchymal-epithelial transition (MET) is induced by TGFβ withdrawal and correlates with metastatic colonization. Whether TGFβ promotes stemness and invasiveness simultaneously via EMT remains unclear. We established a breast cancer cell model expressing red fluorescent protein (RFP) under the E-cadherin promoter. In 2D cultures, TGFβ induced EMT, generating RFP^low cells with a mesenchymal transcriptome, and regained RFP, with an epithelial transcriptome, after MET induced by TGFβ withdrawal. RFP^low cells generated robust mammospheres, with epithelio-mesenchymal cell surface features. Mammospheres that were forced to adhere generated migratory cells, devoid of RFP, a phenotype which was inhibited by a TGFβ receptor kinase inhibitor. Further stimulation of RFP^low mammospheres with TGFβ suppressed the generation of motile cells, but enhanced mammosphere growth. Accordingly, mammary fat-pad-transplanted mammospheres, in the absence of exogenous TGFβ treatment, established lung metastases with evident MET (RFP^high cells). In contrast, TGFβ-treated mammospheres revealed high tumor-initiating capacity, but limited metastatic potential. Thus, the biological context of partial EMT and MET allows TGFβ to differentiate between pro-stemness and pro-invasive phenotypes.