MicroRNA-based regulation of epithelial-hybrid-mesenchymal fate determination. Proc Natl Acad Sci U S A. 2013;110:18144-18149. [PMID: 24154725 DOI: 10.1073/pnas.1318192110]

Energy Landscape Analysis of the Epithelial-Mesenchymal Transition Network

The epithelial-mesenchymal transition (EMT) is a key developmental program that is often activated during the cancer invasion, metastasis, and drug resistance. However, it remains a critical question to elucidate the mechanisms of EMT. For example, how to quantify the global stability and stochastic transition dynamics of EMT under fluctuations is yet to be clarified. Here, we describe a framework and detailed steps for stochastic dynamics analysis of EMT. Starting from the underlying EMT gene regulatory network, we quantify the energy landscape of the EMT computationally. Multiple steady-state attractors are identified on the landscape surface, characterizing different cell phenotypes. The kinetic transition paths based on large deviation theory delineate the transition processes between different attractors quantitatively. The EMT or the reverse process, the mesenchymal-epithelial transition (MET), can be achieved by either a direct transition or a step-wise transition that goes through an intermediate state, depending on different extracellular environments. The landscape and transition paths presented in this chapter provide a new physical and quantitative picture to understand the underlying mechanisms of the EMT process. The approach for landscape and path analysis can be extended to other biological networks.

Effects of immunosuppressants on T-cell dynamics: Understanding from a generic coarse-grained immune network model

Long-term immunosuppressive therapy is a drug regimen often used to lower aggressive immune responses in various chronic inflammatory diseases. However, such long-term therapy leading to immune suppression may trigger other adverse reactions in the immune system. The rising concern regarding the optimal dose and duration of such treatment has motivated us to understand non-classical immunomodulatory responses induced by various immunosuppressive steroid and secosteroid drugs such as glucocorticoid and vitamin D supplements. The immunomodulatory actions of such immunosuppressants (that govern the adaptive immune response) are often mediated through their characteristic control over CD4+ T-cells involving pro- and antiinflammatory T-cells. Several early studies attempted to decode temporal and dose-dependent behaviors of such pro- and anti-inflammatory T-cells using the chemical dynamics approach. We first summarize these early works. Then, we develop a minimal coarse-grained kinetic network model to capture the commonality in their immunomodulatory functions. This generic model successfully reproduces the characteristic dynamical features, including the clinical latency period in long-term T-cell dynamics. The temporal behavior of T-cells is found to be sensitive to specific rate parameters and doses of immunosuppressants. The steady-state analysis reflects the transition from an early classified weakly regulated (autoimmune-prone) immune state to a strongly regulated state (immunocompromised state), separated by an intervening state of moderate/balanced regulation. An optimal dose and duration are essential in rescuing balanced immune regulation. This review elucidates how developing a simple generic coarse-grained immune network model may provide immense information that helps diagnose inefficacy in adaptive immune function before and after administering immunosuppressants such as glucocorticoid or vitamin D.

The Hexosamine Biosynthetic Pathway Links Innate Inflammation With Epithelial-Mesenchymal Plasticity in Airway Remodeling

Disruption of the lower airway epithelial barrier plays a major role in the initiation and progression of chronic lung disease. Here, repetitive environmental insults produced by viral and allergens triggers metabolic adaptations, epithelial-mesenchymal plasticity (EMP) and airway remodeling. Epithelial plasticity disrupts epithelial barrier function, stimulates release of fibroblastic growth factors, and remodels the extracellular matrix (ECM). This review will focus on recent work demonstrating how the hexosamine biosynthetic pathway (HBP) links innate inflammation to airway remodeling. The HBP is a core metabolic pathway of the unfolded protein response (UPR) responsible for protein N-glycosylation, relief of proteotoxic stress and secretion of ECM modifiers. We will overview findings that the IκB kinase (IKK)-NFκB pathway directly activates expression of the SNAI-ZEB1 mesenchymal transcription factor module through regulation of the Bromodomain Containing Protein 4 (BRD4) chromatin modifier. BRD4 mediates transcriptional elongation of SNAI1-ZEB as well as enhancing chromatin accessibility and transcription of fibroblast growth factors, ECM and matrix metalloproteinases (MMPs). In addition, recent exciting findings that IKK cross-talks with the UPR by controlling phosphorylation and nuclear translocation of the autoregulatory XBP1s transcription factor are presented. HBP is required for N glycosylation and secretion of ECM components that play an important signaling role in airway remodeling. This interplay between innate inflammation, metabolic reprogramming and lower airway plasticity expands a population of subepithelial myofibroblasts by secreting fibroblastic growth factors, producing changes in ECM tensile strength, and fibroblast stimulation by MMP binding. Through these actions on myofibroblasts, EMP in lower airway cells produces expansion of the lamina reticularis and promotes airway remodeling. In this manner, metabolic reprogramming by the HBP mediates environmental insult-induced inflammation with remodeling in chronic airway diseases.

Volumetric compression develops noise-driven single-cell heterogeneity

Recent studies have revealed that extensive heterogeneity of biological systems arises through various routes ranging from intracellular chromosome segregation to spatiotemporally varying biochemical stimulations. However, the contribution of physical microenvironments to single-cell heterogeneity remains largely unexplored. Here, we show that a homogeneous population of non-small-cell lung carcinoma develops into heterogeneous subpopulations upon application of a homogeneous physical compression, as shown by single-cell transcriptome profiling. The generated subpopulations stochastically gain the signature genes associated with epithelial-mesenchymal transition (EMT; VIM, CDH1, EPCAM, ZEB1, and ZEB2) and cancer stem cells (MKI67, BIRC5, and KLF4), respectively. Trajectory analysis revealed two bifurcated paths as cells evolving upon the physical compression, along each path the corresponding signature genes (epithelial or mesenchymal) gradually increase. Furthermore, we show that compression increases gene expression noise, which interplays with regulatory network architecture and thus generates differential cell-fate outcomes. The experimental observations of both single-cell sequencing and single-molecule fluorescent in situ hybridization agrees well with our computational modeling of regulatory network in the EMT process. These results demonstrate a paradigm of how mechanical stimulations impact cell-fate determination by altering transcription dynamics; moreover, we show a distinct path that the ecology and evolution of cancer interplay with their physical microenvironments from the view of mechanobiology and systems biology, with insight into the origin of single-cell heterogeneity.

Monostability and bistability of biological switches

Cell-fate transition can be modeled by ordinary differential equations (ODEs) which describe the behavior of several molecules in interaction, and for which each stable equilibrium corresponds to a possible phenotype (or 'biological trait'). In this paper, we focus on simple ODE systems modeling two molecules which each negatively (or positively) regulate the other. It is well-known that such models may lead to monostability or multistability, depending on the selected parameters. However, extensive numerical simulations have led systems biologists to conjecture that in the vast majority of cases, there cannot be more than two stable points. Our main result is a proof of this conjecture. More specifically, we provide a criterion ensuring at most bistability, which is indeed satisfied by most commonly used functions. This includes Hill functions, but also a wide family of convex and sigmoid functions. We also determine which parameters lead to monostability, and which lead to bistability, by developing a more general framework encompassing all our results.

Control of tissue homeostasis, tumorigenesis, and degeneration by coupled bidirectional bistable switches

The Hippo-YAP/TAZ signaling pathway plays a critical role in tissue homeostasis, tumorigenesis, and degeneration disorders. The regulation of YAP/TAZ levels is controlled by a complex regulatory network, where several feedback loops have been identified. However, it remains elusive how these feedback loops contain the YAP/TAZ levels and maintain the system in a healthy physiological state or trap the system in pathological conditions. Here, a mathematical model was developed to represent the YAP/TAZ regulatory network. Through theoretical analyses, three distinct states that designate the one physiological and two pathological outcomes were found. The transition from the physiological state to the two pathological states is mechanistically controlled by coupled bidirectional bistable switches, which are robust to parametric variation and stochastic fluctuations at the molecular level. This work provides a mechanistic understanding of the regulation and dysregulation of YAP/TAZ levels in tissue state transitions.

Tissue development and homeostasis require well-controlled cell proliferation. Lack of this control could lead to degenerative or tumorigenic diseases. Signaling pathways have been explored in promoting or inhibiting these diseases. The Hippo signaling pathway is one of these, which has been found to control tissue homeostasis and organ size through cell proliferation and apoptosis, as evidenced by extensive experimental data. However, the question remains of how tissue can transition from a homeostatic state to either a degenerative or tumorigenic state. By theoretically analyzing a mathematical model of its regulatory network, we present a mechanism that underlies Hippo signaling to control tissue transition from a homeostatic state to a disease state. This provides us with a mechanistic understanding of how the parts of the regulatory network are coordinated for the transitions between the homeostasis state and the disease states. In addition, we looked at the role of system noise and found that it could promote the transition to one of the disease states. Our model allows for experimental hypotheses to be generated and could lead to the development of therapeutic strategies by targeting the Hippo signaling pathway.

Cluster size distribution of cells disseminating from a primary tumor

The first stage of the metastatic cascade often involves motile cells emerging from a primary tumor either as single cells or as clusters. These cells enter the circulation, transit to other parts of the body and finally are responsible for growth of secondary tumors in distant organs. The mode of dissemination is believed to depend on the EMT nature (epithelial, hybrid or mesenchymal) of the cells. Here, we calculate the cluster size distribution of these migrating cells, using a mechanistic computational model, in presence of different degree of EMT-ness of the cells; EMT is treated as given rise to changes in their active motile forces (μ) and cell-medium surface tension (Γ). We find that, for (μ > μ_min, Γ > 1), when the cells are hybrid in nature, the mean cluster size, N¯∼Γ2.0/μ2.8, where μ_min increases with increase in Γ. For Γ ≤ 0, N¯=1, the cells behave as completely mesenchymal. In presence of spectrum of hybrid states with different degree of EMT-ness (motility) in primary tumor, the cells which are relatively more mesenchymal (higher μ) in nature, form larger clusters, whereas the smaller clusters are relatively more epithelial (lower μ). Moreover, the heterogeneity in μ is comparatively higher for smaller clusters with respect to that for larger clusters. We also observe that more extended cell shapes promote the formation of smaller clusters. Overall, this study establishes a framework which connects the nature and size of migrating clusters disseminating from a primary tumor with the phenotypic composition of the tumor, and can lead to the better understanding of metastasis.

In the process of metastasis, tumor cells disseminate from the primary tumor either as single cells or multicellular clusters. These clusters are potential contributor to the initiation of secondary tumor in distant organs. Our computational model captures the size distribution of migrating clusters depending on the adhesion and motility of the cells (which determine the degree of their EMT nature). Furthermore, we investigate the effect of heterogeneity of cell types in the primary tumor on the resultant heterogeneity of cell types in clusters of different sizes. We believe that the understanding the formation and nature of these clusters, dangerous actors in the deadly aspect of cancer progression, will be useful for improving prognostic methods and eventually better treatments.

A reciprocal feedback loop between HIF-1α and HPIP controls phenotypic plasticity in breast cancer cells

While phenotypic plasticity is a critical factor contributing to tumor heterogeneity, molecular mechanisms underlying this process are largely unknown. Here we report that breast cancer cells display phenotypic diversity in response to hypoxia or normoxia microenvironments by operating a reciprocal positive feedback regulation of HPIP and HIF-1α. We show that under hypoxia, HIF-1α induces HPIP expression that establishes cell survival, and also promotes cell migration/invasion, EMT and metastatic phenotypes in breast cancer cells. Mechanistic studies revealed that HPIP interacts with SRP14, a component of signal recognition particle, and stimulates MMP9 synthesis under hypoxic stress. Whereas, in normoxia, HPIP stabilizes HIF-1α, causing the Warburg effect to support cell growth. Concurrently, mathematical modelling corroborates this reciprocal feedback loop in enabling cell-state transitions in cancer cells. Clinical data indicate that elevated levels of HPIP and HIF-1α correlate with unfavorable prognosis and shorter survival rates in breast cancer subjects. Together, this data shows a reciprocal positive feedback loop between HPIP and HIF-1α that was unknown hitherto. It unveils how the tumor microenvironment influences phenotypic plasticity that has an impact on tumor growth and metastasis and, further signifies considering this pathway as a potential therapeutic target in breast cancer.

Deciphering the molecular mechanism of the cancer formation by chromosome structural dynamics

Cancer reflects the dysregulation of the underlying gene network, which is strongly related to the 3D genome organization. Numerous efforts have been spent on experimental characterizations of the structural alterations in cancer genomes. However, there is still a lack of genomic structural-level understanding of the temporal dynamics for cancer initiation and progression. Here, we use a landscape-switching model to investigate the chromosome structural transition during the cancerization and reversion processes. We find that the chromosome undergoes a non-monotonic structural shape-changing pathway with initial expansion followed by compaction during both of these processes. Furthermore, our analysis reveals that the chromosome with a more expanding structure than those at both the normal and cancer cell during cancerization exhibits a sparse contact pattern, which shows significant structural similarity to the one at the embryonic stem cell in many aspects, including the trend of contact probability declining with the genomic distance, the global structural shape geometry and the spatial distribution of loci on the chromosome. In light of the intimate structure-function relationship at the chromosomal level, we further describe the cell state transition processes by the chromosome structural changes, suggesting an elevated cell stemness during the formation of the cancer cells. We show that cell cancerization and reversion are highly irreversible processes in terms of the chromosome structural transition pathways, spatial repositioning of chromosomal loci and hysteresis loop of contact evolution analysis. Our model draws a molecular-scale picture of cell cancerization from the chromosome structural perspective. The process contains initial reprogramming towards the stem cell followed by the differentiation towards the cancer cell, accompanied by an initial increase and subsequent decrease of the cell stemness.

Quantifying the Landscape of Decision Making From Spiking Neural Networks

The decision making function is governed by the complex coupled neural circuit in the brain. The underlying energy landscape provides a global picture for the dynamics of the neural decision making system and has been described extensively in the literature, but often as illustrations. In this work, we explicitly quantified the landscape for perceptual decision making based on biophysically-realistic cortical network with spiking neurons to mimic a two-alternative visual motion discrimination task. Under certain parameter regions, the underlying landscape displays bistable or tristable attractor states, which quantify the transition dynamics between different decision states. We identified two intermediate states: the spontaneous state which increases the plasticity and robustness of changes of minds and the "double-up" state which facilitates the state transitions. The irreversibility of the bistable and tristable switches due to the probabilistic curl flux demonstrates the inherent non-equilibrium characteristics of the neural decision system. The results of global stability of decision-making quantified by barrier height inferred from landscape topography and mean first passage time are in line with experimental observations. These results advance our understanding of the stochastic and dynamical transition mechanism of decision-making function, and the landscape and kinetic path approach can be applied to other cognitive function related problems (such as working memory) in brain networks.

Landscape and kinetic path quantify critical transitions in epithelial-mesenchymal transition

Epithelial-mesenchymal transition (EMT), a basic developmental process that might promote cancer metastasis, has been studied from various perspectives. Recently, the early warning theory has been used to anticipate critical transitions in EMT from mathematical modeling. However, the underlying mechanisms of EMT involving complex molecular networks remain to be clarified. Especially, how to quantify the global stability and stochastic transition dynamics of EMT and what the underlying mechanism for early warning theory in EMT is remain to be fully clarified. To address these issues, we constructed a comprehensive gene regulatory network model for EMT and quantified the corresponding potential landscape. The landscape for EMT displays multiple stable attractors, which correspond to E, M, and some other intermediate states. Based on the path-integral approach, we identified the most probable transition paths of EMT, which are supported by experimental data. Correspondingly, the results of transition actions demonstrated that intermediate states can accelerate EMT, consistent with recent studies. By integrating the landscape and path with early warning concept, we identified the potential barrier height from the landscape as a global and more accurate measure for early warning signals to predict critical transitions in EMT. The landscape results also provide an intuitive and quantitative explanation for the early warning theory. Overall, the landscape and path results advance our mechanistic understanding of dynamical transitions and roles of intermediate states in EMT, and the potential barrier height provides a new, to our knowledge, measure for critical transitions and quantitative explanations for the early warning theory.

Identification, visualization, statistical analysis and mathematical modeling of high-feedback loops in gene regulatory networks

Background

Feedback loops in gene regulatory networks play pivotal roles in governing functional dynamics of cells. Systems approaches demonstrated characteristic dynamical features, including multistability and oscillation, of positive and negative feedback loops. Recent experiments and theories have implicated highly interconnected feedback loops (high-feedback loops) in additional nonintuitive functions, such as controlling cell differentiation rate and multistep cell lineage progression. However, it remains challenging to identify and visualize high-feedback loops in complex gene regulatory networks due to the myriad of ways in which the loops can be combined. Furthermore, it is unclear whether the high-feedback loop structures with these potential functions are widespread in biological systems. Finally, it remains challenging to understand diverse dynamical features, such as high-order multistability and oscillation, generated by individual networks containing high-feedback loops. To address these problems, we developed HiLoop, a toolkit that enables discovery, visualization, and analysis of several types of high-feedback loops in large biological networks.

Results

HiLoop not only extracts high-feedback structures and visualize them in intuitive ways, but also quantifies the enrichment of overrepresented structures. Through random parameterization of mathematical models derived from target networks, HiLoop presents characteristic features of the underlying systems, including complex multistability and oscillations, in a unifying framework. Using HiLoop, we were able to analyze realistic gene regulatory networks containing dozens to hundreds of genes, and to identify many small high-feedback systems. We found more than a 100 human transcription factors involved in high-feedback loops that were not studied previously. In addition, HiLoop enabled the discovery of an enrichment of high feedback in pathways related to epithelial-mesenchymal transition.

Conclusions

HiLoop makes the study of complex networks accessible without significant computational demands. It can serve as a hypothesis generator through identification and modeling of high-feedback subnetworks, or as a quantification method for motif enrichment analysis. As an example of discovery, we found that multistep cell lineage progression may be driven by either specific instances of high-feedback loops with sparse appearances, or generally enriched topologies in gene regulatory networks. We expect HiLoop’s usefulness to increase as experimental data of regulatory networks accumulate. Code is freely available for use or extension at https://github.com/BenNordick/HiLoop.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04405-z.

Epithelial-to-Mesenchymal Transition in Fibrosis: Concepts and Targeting Strategies

The epithelial-to-mesenchymal transition (EMT), an embryonic program relaunched during wound healing and in pathological conditions such as fibrosis and cancer, continues to gain the attention of the research community, as testified by the exponential trend of publications since its discovery in the seventies. From the first description as a mesenchymal transformation, the concept of EMT has been substantially refined as an in-depth comprehension of its functional role has recently emerged thanks to the implementation of novel mouse models as well as the use of sophisticated mathematical modeling and bioinformatic analysis. Nevertheless, attempts to targeting EMT in fibrotic diseases are at their infancy and continue to pose several challenges. The aim of this mini review is to recapitulate the most recent concepts in the EMT field and to summarize the different strategies which have been exploited to target EMT in fibrotic disorders.

An intermediate state in trans-differentiation with proliferation, metabolic, and epigenetic switching

Although TGF-β signaling can effectively activate fibroblasts to transform to myofibroblasts, the underlying mechanisms involved in the cell fate switching for trans-differentiation have not been fully elucidated. In this study, we found the evidence of an intermediate state in the process of trans-differentiation. In the early stage of trans-differentiation, cells enter the intermediate state first with multiple characteristics such as accelerating cell cycle, metabolic switching, enhanced anti-apoptotic ability, and pluripotency, which is very similar to the early stage of reprogramming. As the trans-differentiation continues, these characteristics get switched. Therefore, trans-differentiation appears to require the switching of cell proliferation ability, metabolic pathway, and “stemness” to complete the process. In this study, we can conclude that an intermediate state may be necessary with high pluripotency in trans-differentiation from fibroblasts to myofibroblasts. Only after passing the intermediate state, the trans-differentiation is finally completed and will not easily return to the original state.

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Smads and Akt/p38MAPK pathways play the key role in fibroblast transition

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There is a cell proliferation capability switching induced by TGF-β1

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Metabolic reprogramming is required during trans-differentiation

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An intermediate state appeared with high pluripotency in trans-differentiation

The Underappreciated Role of Epithelial Mesenchymal Transition in Chronic Obstructive Pulmonary Disease and Its Strong Link to Lung Cancer

The World Health Organisation reported COPD to be the third leading cause of death globally in 2019, and in 2020, the most common cause of cancer death was lung cancer; when these linked conditions are added together they come near the top of the leading causes of mortality. The cell-biological program termed epithelial-to-mesenchymal transition (EMT) plays an important role in organ development, fibrosis and cancer progression. Over the past decade there has emerged a substantial literature that also links EMT specifically to the pathophysiology of chronic obstructive pulmonary disease (COPD) as primarily an airway fibrosis disease; COPD is a recognised strong independent risk factor for the development of lung cancer, over and above the risks associated with smoking. In this review, our primary focus is to highlight these linkages and alert both the COPD and lung cancer fields to these complex interactions. We emphasise the need for inter-disciplinary attention and research focused on the likely crucial roles of EMT (and potential for its inhibition) with recognition of its strategic place mechanistically in both COPD and lung cancer. As part of this we discuss the future potential directions for novel therapeutic opportunities, including evidence-based strategic repurposing of currently used familiar/approved medications.

Prediction and Boolean logical modelling of synergistic microRNA regulatory networks during reprogramming of male germline pluripotent stem cells

Unipotent male germline stem (GS) cells can undergo spontaneous reprogramming to germline pluripotent stem (GPS) cells during in vitro culture. In our previous study, we proposed a Boolean logical model of gene regulatory network (GRN) during reprogramming of GS cells to GPS cells. This study was designed to predict and model synergistic microRNA (miRNA) regulatory network during reprogramming of GS cells into GPS cells. The miRNAs targeting differentially expressed genes (DEGs) among GS and GPS cells were predicted by a novel Gene Ontology (GO) enrichment analysis to construct miRNA synergistic networks (MSN) and identify regulatory miRNA modules. Qualitative Boolean logical model of synergistic miRNAs and its regulated genes was then constructed by considering discrete, asynchronous, multivalued logical formalism using the GINsim modeling and simulation tools. Topology, functional and community overlap studies revealed that mmu-miR-200b-3p, mmu-miR-429-3p and mmu-miR-141-3p, mmu-miR-200a-3p and mmu-miR-200c-3p in MSN belongs to the family of miR-200/429/141 and conjectured to control the pluripotency and reprogramming by promoting Mesenchymal to Epithelial Transition (MET). Synergistic network involving mmu-miR-20b-5p, mmu-miR-20a-5p, mmu-miR-106a-5p, mmu-miR-106b-5p, and mmu-miR-17-5p were found to be essential for the maintenance of GS cells. Logical miRNA regulatory network modelling showed that synergistic miRNAs regulates the gene dynamics of MET during GS-GPS reprogramming, as confirmed by perturbation analysis. Taken together, our study predicted novel synergistic miRNAs involved in the regulation of reprogramming and pluripotency in GPS cells. The Boolean logical model of synergistic miRNAs regulatory network further confirms our previous study that gene dynamics of MET regulates GS-GPS reprogramming.

Decoding leader cells in collective cancer invasion

Collective cancer invasion with leader-follower organization is increasingly recognized as a predominant mechanism in the metastatic cascade. Leader cells support cancer invasion by creating invasion tracks, sensing environmental cues and coordinating with follower cells biochemically and biomechanically. With the latest developments in experimental and computational models and analysis techniques, the range of specific traits and features of leader cells reported in the literature is rapidly expanding. Yet, despite their importance, there is no consensus on how leader cells arise or their essential characteristics. In this Perspective, we propose a framework for defining the essential aspects of leader cells and provide a unifying perspective on the varying cellular and molecular programmes that are adopted by each leader cell subtype to accomplish their functions. This Perspective can lead to more effective strategies to interdict a major contributor to metastatic capability.

Single-cell lineage tracing of metastatic cancer reveals selection of hybrid EMT states

The underpinnings of cancer metastasis remain poorly understood, in part due to a lack of tools for probing their emergence at high resolution. Here we present macsGESTALT, an inducible CRISPR-Cas9-based lineage recorder with highly efficient single-cell capture of both transcriptional and phylogenetic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we recover ∼380,000 CRISPR target sites and reconstruct dissemination of ∼28,000 single cells across multiple metastatic sites. We find that cells occupy a continuum of epithelial-to-mesenchymal transition (EMT) states. Metastatic potential peaks in rare, late-hybrid EMT states, which are aggressively selected from a predominately epithelial ancestral pool. The gene signatures of these late-hybrid EMT states are predictive of reduced survival in both human pancreatic and lung cancer patients, highlighting their relevance to clinical disease progression. Finally, we observe evidence for in vivo propagation of S100 family gene expression across clonally distinct metastatic subpopulations.

Lineage Plasticity in Cancer: The Tale of a Skin-Walker

Lineage plasticity, the switching of cells from one lineage to another, has been recognized as a cardinal property essential for embryonic development, tissue repair and homeostasis. However, such a highly regulated process goes awry when cancer cells exploit this inherent ability to their advantage, resulting in tumorigenesis, relapse, metastasis and therapy resistance. In this review, we summarize our current understanding on the role of lineage plasticity in tumor progression and therapeutic resistance in multiple cancers. Lineage plasticity can be triggered by treatment itself and is reported across various solid as well as liquid tumors. Here, we focus on the importance of lineage switching in tumor progression and therapeutic resistance of solid tumors such as the prostate, lung, hepatocellular and colorectal carcinoma and the myeloid and lymphoid lineage switch observed in leukemias. Besides this, we also discuss the role of epithelial-mesenchymal transition (EMT) in facilitating the lineage switch in biphasic cancers such as aggressive carcinosarcomas. We also discuss the mechanisms involved, current therapeutic approaches and challenges that lie ahead in taming the scourge of lineage plasticity in cancer.

Partial EMT in Squamous Cell Carcinoma: A Snapshot

In the process of cancer EMT, some subgroups of cancer cells simultaneously exhibit both mesenchymal and epithelial characteristics, a phenomenon termed partial EMT (pEMT). pEMT is a plastic state in which cells coexpress epithelial and mesenchymal markers. In squamous cell carcinoma (SCC), pEMT is regulated, and the phenotype is maintained via the HIPPO pathway, NOTCH pathway and TGF-β pathways and by microRNAs, lncRNAs and the cancer microenvironment (CME); thus, SCC exhibits aggressive tumorigenic properties and high stemness, which leads collective migration and therapy resistance. Few studies have reported therapeutic interventions to address cells that have undergone pEMT, and this approach may be an effective way to inhibit the plasticity, drug resistance and metastatic potential of SCC.

A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells

Resistance to anti-estrogen therapy is an unsolved clinical challenge in successfully treating ER+ breast cancer patients. Recent studies have demonstrated the role of non-genetic (i.e. phenotypic) adaptations in tolerating drug treatments; however, the mechanisms and dynamics of such non-genetic adaptation remain elusive. Here, we investigate coupled dynamics of epithelial–mesenchymal transition (EMT) in breast cancer cells and emergence of reversible drug resistance. Our mechanism-based model for underlying regulatory network reveals that these two axes can drive one another, thus enabling non-genetic heterogeneity in a cell population by allowing for six co-existing phenotypes: epithelial-sensitive, mesenchymal-resistant, hybrid E/M-sensitive, hybrid E/M-resistant, mesenchymal-sensitive and epithelial-resistant, with the first two ones being most dominant. Next, in a population dynamics framework, we exemplify the implications of phenotypic plasticity (both drug-induced and intrinsic stochastic switching) and/or non-genetic heterogeneity in promoting population survival in a mixture of sensitive and resistant cells, even in the absence of any cell–cell cooperation. Finally, we propose the potential therapeutic use of mesenchymal–epithelial transition inducers besides canonical anti-estrogen therapy to limit the emergence of reversible drug resistance. Our results offer mechanistic insights into empirical observations on EMT and drug resistance and illustrate how such dynamical insights can be exploited for better therapeutic designs.

Nickel in terrestrial biota: Comprehensive review on contamination, toxicity, tolerance and its remediation approaches

Nickel (Ni) has been a subject of interest for environmental, physiological, biological scientists due to its dual effect (toxicity and essentiality) in terrestrial biota. In general, the safer limit of Ni is 1.5 μg g^-1 in plants and 75-150 μg g^-1 in soil. Litreature review indicates that Ni concentrations have been estimated up to 26 g kg^-1 in terrestrial, and 0.2 mg L^-1 in aquatic resources. In case of vegetables and fruits, mean Ni content has been reported in the range of 0.08-0.26 and 0.03-0.16 mg kg^-1. Considering, Ni toxicity and its potential health hazards, there is an urgent need to find out the suitable remedial approaches. Plant vascular (>80%) and cortical (<20%) tissues are the major sequestration site (cation exchange) of absorbed Ni. Deciphering molecular mechanisms in transgenic plants have immense potential for enhancing Ni phytoremediation and microbial remediation efficiency. Further, it has been suggested that integrated bioremediation approaches have a potential futuristic path for Ni decontamination in natural resources. This systematic review provides insight on Ni effects on terrestrial biota including human and further explores its transportation, bioaccumulation through food chain contamination, human health hazards, and possible Ni remediation approaches.

Towards decoding the coupled decision-making of metabolism and epithelial-to-mesenchymal transition in cancer

Cancer cells have the plasticity to adjust their metabolic phenotypes for survival and metastasis. A developmental programme known as epithelial-to-mesenchymal transition (EMT) plays a critical role during metastasis, promoting the loss of polarity and cell-cell adhesion and the acquisition of motile, stem-cell characteristics. Cells undergoing EMT or the reverse mesenchymal-to-epithelial transition (MET) are often associated with metabolic changes, as the change in phenotype often correlates with a different balance of proliferation versus energy-intensive migration. Extensive crosstalk occurs between metabolism and EMT, but how this crosstalk leads to coordinated physiological changes is still uncertain. The elusive connection between metabolism and EMT compromises the efficacy of metabolic therapies targeting metastasis. In this review, we aim to clarify the causation between metabolism and EMT on the basis of experimental studies, and propose integrated theoretical-experimental efforts to better understand the coupled decision-making of metabolism and EMT.

Computational systems-biology approaches for modeling gene networks driving epithelial-mesenchymal transitions

Epithelial-mesenchymal transition (EMT) is an important biological process through which epithelial cells undergo phenotypic transitions to mesenchymal cells by losing cell-cell adhesion and gaining migratory properties that cells use in embryogenesis, wound healing, and cancer metastasis. An important research topic is to identify the underlying gene regulatory networks (GRNs) governing the decision making of EMT and develop predictive models based on the GRNs. The advent of recent genomic technology, such as single-cell RNA sequencing, has opened new opportunities to improve our understanding about the dynamical controls of EMT. In this article, we review three major types of computational and mathematical approaches and methods for inferring and modeling GRNs driving EMT. We emphasize (1) the bottom-up approaches, where GRNs are constructed through literature search; (2) the top-down approaches, where GRNs are derived from genome-wide sequencing data; (3) the combined top-down and bottom-up approaches, where EMT GRNs are constructed and simulated by integrating bioinformatics and mathematical modeling. We discuss the methodologies and applications of each approach and the available resources for these studies.

What we can learn from embryos to understand the mesenchymal-to-epithelial transition in tumor progression

Epithelial plasticity involved the terminal and transitional stages that occur during epithelial-to-mesenchymal transition (EMT) and mesenchymal-to-epithelial transition (MET), both are essential at different stages of early embryonic development that have been co-opted by cancer cells to undergo tumor metastasis. These processes are regulated at multiple instances, whereas the post-transcriptional regulation of key genes mediated by microRNAs is gaining major attention as a common and conserved pathway. In this review, we focus on discussing the latest findings of the cellular and molecular basis of the less characterized process of MET during embryonic development, with special attention to the role of microRNAs. Although we take in consideration the necessity of being cautious when extrapolating the obtained evidence, we propose some commonalities between early embryonic development and cancer progression that can shed light into our current understanding of this complex event and might aid in the design of specific therapeutic approaches.

The role of mechanical interactions in EMT

The detachment of cells from the boundary of an epithelial tissue and the subsequent invasion of these cells into surrounding tissues is important for cancer development and wound healing, and is strongly associated with the epithelial-mesenchymal transition (EMT). Chemical signals, such as TGF-β, produced by surrounding tissue can be uptaken by cells and induce EMT. In this work, we present a novel cell-based discrete mathematical model of mechanical cellular relaxation, cell proliferation, and cell detachment driven by chemically-dependent EMT in an epithelial tissue. A continuum description of the model is then derived in the form of a novel nonlinear free boundary problem. Using the discrete and continuum models we explore how the coupling of chemical transport and mechanical interactions influences EMT, and postulate how this could be used to help control EMT in pathological situations.

Phenotypic Heterogeneity and Metastasis of Breast Cancer Cells

Although intratumoral genomic heterogeneity can impede cancer research and treatment, less is known about the effects of phenotypic heterogeneities. To investigate the role of cell migration heterogeneities in metastasis, we phenotypically sorted metastatic breast cancer cells into two subpopulations based on migration ability. Although migration is typically considered to be associated with metastasis, when injected orthotopically in vivo, the weakly migratory subpopulation metastasized significantly more than the highly migratory subpopulation. To investigate the mechanism behind this observation, both subpopulations were assessed at each stage of the metastatic cascade, including dissemination from the primary tumor, survival in the circulation, extravasation, and colonization. Although both subpopulations performed each step successfully, weakly migratory cells presented as circulating tumor cell (CTC) clusters in the circulation, suggesting clustering as one potential mechanism behind the increased metastasis of weakly migratory cells. RNA sequencing revealed weakly migratory subpopulations to be more epithelial and highly migratory subpopulations to be more mesenchymal. Depletion of E-cadherin expression from weakly migratory cells abrogated metastasis. Conversely, induction of E-cadherin expression in highly migratory cells increased metastasis. Clinical patient data and blood samples showed that CTC clustering and E-cadherin expression are both associated with worsened patient outcome. This study demonstrates that deconvolving phenotypic heterogeneities can reveal fundamental insights into metastatic progression. More specifically, these results indicate that migratory ability does not necessarily correlate with metastatic potential and that E-cadherin promotes metastasis in phenotypically sorted breast cancer cell subpopulations by enabling CTC clustering. SIGNIFICANCE: This study employs phenotypic cell sorting for migration to reveal a weakly migratory, highly metastatic breast cancer cell subpopulation regulated by E-cadherin, highlighting the dichotomy between cancer cell migration and metastasis.

A Dimension Reduction Approach for Energy Landscape: Identifying Intermediate States in Metabolism-EMT Network

Dimension reduction is a challenging problem in complex dynamical systems. Here, a dimension reduction approach of landscape (DRL) for complex dynamical systems is proposed, by mapping a high-dimensional system on a low-dimensional energy landscape. The DRL approach is applied to three biological networks, which validates that new reduced dimensions preserve the major information of stability and transition of original high-dimensional systems. The consistency of barrier heights calculated from the low-dimensional landscape and transition actions calculated from the high-dimensional system further shows that the landscape after dimension reduction can quantify the global stability of the system. The epithelial-mesenchymal transition (EMT) and abnormal metabolism are two hallmarks of cancer. With the DRL approach, a quadrastable landscape for metabolism-EMT network is identified, including epithelial (E), abnormal metabolic (A), hybrid E/M (H), and mesenchymal (M) cell states. The quantified energy landscape and kinetic transition paths suggest that for the EMT process, the cells at E state need to first change their metabolism, then enter the M state. The work proposes a general framework for the dimension reduction of a stochastic dynamical system, and advances the mechanistic understanding of the underlying relationship between EMT and cellular metabolism.

Linking EMT programmes to normal and neoplastic epithelial stem cells

Epithelial stem cells serve critical physiological functions in the generation, maintenance and repair of diverse tissues through their ability to self-renew and spawn more specialized, differentiated cell types. In an analogous fashion, cancer stem cells have been proposed to fuel the growth, progression and recurrence of many carcinomas. Activation of an epithelial-mesenchymal transition (EMT), a latent cell-biological programme involved in development and wound healing, has been linked to the formation of both normal and neoplastic stem cells, but the mechanistic basis underlying this connection remains unclear. In this Perspective, we outline the instances where aspects of an EMT have been implicated in normal and neoplastic epithelial stem cells and consider the involvement of this programme during tissue regeneration and repair. We also discuss emerging concepts and evidence related to the heterogeneous and plastic cell states generated by EMT programmes and how these bear on our understanding of cancer stem cell biology and cancer metastasis. A more comprehensive accounting of the still-elusive links between EMT programmes and the stem cell state will surely advance our understanding of both normal stem cell biology and cancer pathogenesis.

Measuring and Modelling the Epithelial- Mesenchymal Hybrid State in Cancer: Clinical Implications

The epithelial-mesenchymal (E/M) hybrid state has emerged as an important mediator of elements of cancer progression, facilitated by epithelial mesenchymal plasticity (EMP). We review here evidence for the presence, prognostic significance, and therapeutic potential of the E/M hybrid state in carcinoma. We further assess modelling predictions and validation studies to demonstrate stabilised E/M hybrid states along the spectrum of EMP, as well as computational approaches for characterising and quantifying EMP phenotypes, with particular attention to the emerging realm of single-cell approaches through RNA sequencing and protein-based techniques.

Roles of microRNAs in Regulating Cancer Stemness in Head and Neck Cancers

Head and neck squamous cell carcinomas (HNSCCs) are epithelial malignancies with 5-year overall survival rates of approximately 40-50%. Emerging evidence indicates that a small population of cells in HNSCC patients, named cancer stem cells (CSCs), play vital roles in the processes of tumor initiation, progression, metastasis, immune evasion, chemo-/radioresistance, and recurrence. The acquisition of stem-like properties of cancer cells further provides cellular plasticity for stress adaptation and contributes to therapeutic resistance, resulting in a worse clinical outcome. Thus, targeting cancer stemness is fundamental for cancer treatment. MicroRNAs (miRNAs) are known to regulate stem cell features in the development and tissue regeneration through a miRNA-target interactive network. In HNSCCs, miRNAs act as tumor suppressors and/or oncogenes to modulate cancer stemness and therapeutic efficacy by regulating the CSC-specific tumor microenvironment (TME) and signaling pathways, such as epithelial-to-mesenchymal transition (EMT), Wnt/β-catenin signaling, and epidermal growth factor receptor (EGFR) or insulin-like growth factor 1 receptor (IGF1R) signaling pathways. Owing to a deeper understanding of disease-relevant miRNAs and advances in in vivo delivery systems, the administration of miRNA-based therapeutics is feasible and safe in humans, with encouraging efficacy results in early-phase clinical trials. In this review, we summarize the present findings to better understand the mechanical actions of miRNAs in maintaining CSCs and acquiring the stem-like features of cancer cells during HNSCC pathogenesis.

Loss of the Metastasis Suppressor NME1, But Not of Its Highly Related Isoform NME2, Induces a Hybrid Epithelial-Mesenchymal State in Cancer Cells

Epithelial-mesenchymal transition (EMT) is important for the initial steps of metastasis. Although it is well accepted that the nucleoside diphosphate kinase NME1 is a metastasis suppressor, its effect on EMT remains poorly documented, as does that of its closely related isoform, NME2. Here, by using gene silencing, inactivation and overexpression strategies in a variety of cellular models of cancer, we show that NME1 is a powerful inhibitor of EMT. Genetic manipulation of NME2, by contrast, had no effect on the EMT phenotype of cancer cells, indicating a specific function of NME1 in EMT regulation. Loss of NME1 in epithelial cancer cells resulted in a hybrid phenotype intermediate between epithelial and mesenchymal cells, which is known to be associated with cells with a highly metastatic character. Conversely, overexpression of NME1 in mesenchymal cancer cells resulted in a more epithelial phenotype. We found that NME1 expression was negatively associated with EMT markers in many human cancers and was reduced in human breast tumor cell lines with the aggressive 'triple-negative' phenotype when compared to human breast tumor cell lines positive for estrogen receptor. We show that NME1, but not NME2, is an inhibitor of essential concerted intracellular signaling pathways involved in inducing EMT, including the AKT and MAPK (ERK, p38, and JNK) pathways. Additionally, NME1 depletion considerably altered the distribution of E-cadherin, a gatekeeper of the epithelial phenotype, shifting it from the plasma membrane to the cytosol and resulting in less E-cadherin on the cell surface than in control cells. Functional aggregation and dispersion assays demonstrated that inactivation of NME1 decreases E-cadherin-mediated cell-cell adhesion. We conclude that NME1, but not NME2, acts specifically to inhibit EMT and prevent the earliest stages of metastasis.

A Theoretical Approach to Coupling the Epithelial-Mesenchymal Transition (EMT) to Extracellular Matrix (ECM) Stiffness via LOXL2

Simple Summary

Epithelial-mesenchymal transition (EMT) is a key process in cancer progression through which cells weaken their cell-cell adhesion and gain mobility and invasive traits. Besides chemical signaling, recent studies have established the connection of EMT to mechanical microenvironment, such as the stiffness of extracellular matrix (ECM). LOXL2 is representative of a family of enzymes that promotes fiber cross-linking in ECM. With increased cross-linking comes increased stiffness, which induces EMT that can, in turn, elevate LOXL2 levels. As such, a positive feedback loop among EMT, LOXL2, and ECM stiffness can be formed. We built a mathematical model on a core biochemical reaction network featuring this feedback loop, and showed how strongly it drives EMT. We also illustrated mechanistically how cross-linking connects with stiffness, using a mechanical model of collagen (a major component of ECM). Using this theoretical framework, we demonstrated the heterogeneity of LOXL2/stiffness and its implications on migrating cancer cells that could seed metastasis, the growth of secondary malignant tumors. This framework can inspire experimental studies of more fine-grained mechanotransduction and biomechanical heterogeneity in cancers.

Abstract

The epithelial-mesenchymal transition (EMT) plays a critical role in cancer progression, being responsible in many cases for the onset of the metastatic cascade and being integral in the ability of cells to resist drug treatment. Most studies of EMT focus on its induction via chemical signals such as TGF-β or Notch ligands, but it has become increasingly clear that biomechanical features of the microenvironment such as extracellular matrix (ECM) stiffness can be equally important. Here, we introduce a coupled feedback loop connecting stiffness to the EMT transcription factor ZEB1, which acts via increasing the secretion of LOXL2 that leads to increased cross-linking of collagen fibers in the ECM. This increased cross-linking can effectively increase ECM stiffness and increase ZEB1 levels, thus setting a positive feedback loop between ZEB1 and ECM stiffness. To investigate the impact of this non-cell-autonomous effect, we introduce a computational approach capable of connecting LOXL2 concentration to increased stiffness and thereby to higher ZEB1 levels. Our results indicate that this positive feedback loop, once activated, can effectively lock the cells in a mesenchymal state. The spatial-temporal heterogeneity of the LOXL2 concentration and thus the mechanical stiffness also has direct implications for migrating cells that attempt to escape the primary tumor.

The Impact of Non-coding RNAs in the Epithelial to Mesenchymal Transition

Epithelial to mesenchymal transition (EMT) is a course of action that enables a polarized epithelial cell to undertake numerous biochemical alterations that allow it to adopt features of mesenchymal cells such as high migratory ability, invasive properties, resistance to apoptosis, and importantly higher-order formation of extracellular matrix elements. EMT has important roles in implantation and gastrulation of the embryo, inflammatory reactions and fibrosis, and transformation of cancer cells, their invasiveness and metastatic ability. Regarding the importance of EMT in the invasive progression of cancer, this process has been well studies in in this context. Non-coding RNAs (ncRNAs) have been shown to exert critical function in the regulation of cellular processes that are involved in the EMT. These processes include regulation of some transcription factors namely SNAI1 and SNAI2, ZEB1 and ZEB2, Twist, and E12/E47, modulation of chromatin configuration, alternative splicing, and protein stability and subcellular location of proteins. In the present paper, we describe the influence of ncRNAs including microRNAs and long non-coding RNAs in the EMT process and their application as biomarkers for this process and cancer progression and their potential as therapeutic targets.

Genetic and Non-Genetic Mechanisms Underlying Cancer Evolution

Simple Summary

Our manuscript summarizes the up-to-date data on the complex and dynamic nature of adaptation mechanisms and evolutionary processes taking place during cancer initiation, development and progression. Although for decades cancer has been viewed as a process governed by genetic mechanisms, it is becoming more and more clear that non-genetic mechanisms may play an equally important role in cancer evolution. In this review, we bring together these fundamental concepts and discuss how those tightly interconnected mechanisms lead to the establishment of highly adaptive quickly evolving cancers. Furthermore, we argue that in depth understanding of cancer progression from the evolutionary perspective may allow the prediction and direction of the evolutionary path of cancer populations towards drug sensitive phenotypes and thus facilitate the development of more effective anti-cancer approaches.

Abstract

Cancer development can be defined as a process of cellular and tissular microevolution ultimately leading to malignancy. Strikingly, though this concept has prevailed in the field for more than a century, the precise mechanisms underlying evolutionary processes occurring within tumours remain largely uncharacterized and rather cryptic. Nevertheless, although our current knowledge is fragmentary, data collected to date suggest that most tumours display features compatible with a diverse array of evolutionary paths, suggesting that most of the existing macro-evolutionary models find their avatar in cancer biology. Herein, we discuss an up-to-date view of the fundamental genetic and non-genetic mechanisms underlying tumour evolution with the aim of concurring into an integrated view of the evolutionary forces at play throughout the emergence and progression of the disease and into the acquisition of resistance to diverse therapeutic paradigms. Our ultimate goal is to delve into the intricacies of genetic and non-genetic networks underlying tumour evolution to build a framework where both core concepts are considered non-negligible and equally fundamental.

Coupled Feedback Loops Involving PAGE4, EMT and Notch Signaling Can Give Rise to Non-genetic Heterogeneity in Prostate Cancer Cells

Non-genetic heterogeneity is emerging as a crucial factor underlying therapy resistance in multiple cancers. However, the design principles of regulatory networks underlying non-genetic heterogeneity in cancer remain poorly understood. Here, we investigate the coupled dynamics of feedback loops involving (a) oscillations in androgen receptor (AR) signaling mediated through an intrinsically disordered protein PAGE4, (b) multistability in epithelial-mesenchymal transition (EMT), and c) Notch-Delta-Jagged signaling mediated cell-cell communication, each of which can generate non-genetic heterogeneity through multistability and/or oscillations. Our results show how different coupling strengths between AR and EMT signaling can lead to monostability, bistability, or oscillations in the levels of AR, as well as propagation of oscillations to EMT dynamics. These results reveal the emergent dynamics of coupled oscillatory and multi-stable systems and unravel mechanisms by which non-genetic heterogeneity in AR levels can be generated, which can act as a barrier to most existing therapies for prostate cancer patients.

Potential Landscapes, Bifurcations, and Robustness of Tristable Networks

Bistable switches that produce all-or-none responses have been found to regulate a number of natural cellular decision making processes, and subsequently synthetic switches were designed to exploit their potential. However, an increasing number of studies, particularly in the context of cellular differentiation, highlight the existence of a mixed state that can be explained by tristable switches. The criterion for designing robust tristable switches still remains to be understood from the perspective of network topology. To address such a question, we calculated the robustness of several 2- and 3-component network motifs, connected via only two positive feedback loops, in generating tristable signal response curves. By calculating the effective potential landscape and following its modifications with the bifurcation parameter, we constructed one-parameter bifurcation diagrams of these models in a high-throughput manner for a large combinations of parameters. We report here that introduction of a self-activatory positive feedback loop, directly or indirectly, into a mutual inhibition loop leads to generating the most robust tristable response. The high-throughput approach of our method further allowed us to determine the robustness of four types of tristable responses that originate from the relative locations of four bifurcation points. Using the method, we also analyzed the role of additional mutual inhibition loops in stabilizing the mixed state.

A Computational Systems Biology Approach Identifies SLUG as a Mediator of Partial Epithelial-Mesenchymal Transition (EMT)

Epithelial-mesenchymal plasticity comprises reversible transitions among epithelial, hybrid epithelial/mesenchymal (E/M) and mesenchymal phenotypes, and underlies various aspects of aggressive tumor progression such as metastasis, therapy resistance, and immune evasion. The process of cells attaining one or more hybrid E/M phenotypes is termed as partial epithelial mesenchymal transition (EMT). Cells in hybrid E/M phenotype(s) can be more aggressive than those in either fully epithelial or mesenchymal state. Thus, identifying regulators of hybrid E/M phenotypes is essential to decipher the rheostats of phenotypic plasticity and consequent accelerators of metastasis. Here, using a computational systems biology approach, we demonstrate that SLUG (SNAIL2) - an EMT-inducing transcription factor - can inhibit cells from undergoing a complete EMT and thus stabilize them in hybrid E/M phenotype(s). It expands the parametric range enabling the existence of a hybrid E/M phenotype, thereby behaving as a phenotypic stability factor. Our simulations suggest that this specific property of SLUG emerges from the topology of the regulatory network it forms with other key regulators of epithelial-mesenchymal plasticity. Clinical data suggest that SLUG associates with worse patient prognosis across multiple carcinomas. Together, our results indicate that SLUG can stabilize hybrid E/M phenotype(s).

Cell memory of epithelial-mesenchymal plasticity in cancer

Fundamental biological processes of cell identity and cell fate determination are controlled by complex regulatory networks. These processes require molecular mechanisms that confer cellular phenotypic memory and state persistence. In this minireview, we will summarize mechanisms of cell memory based on regulatory hysteretic feedback loops and explore epigenetic mechanisms widely represented in nature, with special focus on epithelial-to-mesenchymal plasticity. We will also discuss the functional consequences of cell memory and epithelial-to-mesenchymal plasticity dynamics during development and cancer metastasis.

Winner-takes-all resource competition redirects cascading cell fate transitions

Failure of modularity remains a significant challenge for assembling synthetic gene circuits with tested modules as they often do not function as expected. Competition over shared limited gene expression resources is a crucial underlying reason. It was reported that resource competition makes two seemingly separate genes connect in a graded linear manner. Here we unveil nonlinear resource competition within synthetic gene circuits. We first build a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain with two coupled self-activation modules to achieve two successive cell fate transitions. Interestingly, we find that the in vivo transition path was redirected as the activation of one switch always prevails against the other, contrary to the theoretically expected coactivation. This qualitatively different type of resource competition between the two modules follows a ‘winner-takes-all’ rule, where the winner is determined by the relative connection strength between the modules. To decouple the resource competition, we construct a two-strain circuit, which achieves successive activation and stable coactivation of the two switches. These results illustrate that a highly nonlinear hidden interaction between the circuit modules due to resource competition may cause counterintuitive consequences on circuit functions, which can be controlled with a division of labor strategy.

Synthetic gene circuits may not function as expected due to the resource competition between modules. Here the authors build cascading bistable switches to achieve two successive cell fate transitions but found a ‘winner-takes-all’ behaviour, which is overcome by a division of labour strategy.

Multi-Stability and Consequent Phenotypic Plasticity in AMPK-Akt Double Negative Feedback Loop in Cancer Cells

Adaptation and survival of cancer cells to various stress and growth factor conditions is crucial for successful metastasis. A double-negative feedback loop between two serine/threonine kinases AMPK (AMP-activated protein kinase) and Akt can regulate the adaptation of breast cancer cells to matrix-deprivation stress. This feedback loop can significantly generate two phenotypes or cell states: matrix detachment-triggered pAMPK^high/ pAkt^low state, and matrix (re)attachment-triggered pAkt^high/ pAMPK^low state. However, whether these two cell states can exhibit phenotypic plasticity and heterogeneity in a given cell population, i.e., whether they can co-exist and undergo spontaneous switching to generate the other subpopulation, remains unclear. Here, we develop a mechanism-based mathematical model that captures the set of experimentally reported interactions among AMPK and Akt. Our simulations suggest that the AMPK-Akt feedback loop can give rise to two co-existing phenotypes (pAkt^high/ pAMPK^low and pAMPK^high/pAkt^low) in specific parameter regimes. Next, to test the model predictions, we segregated these two subpopulations in MDA-MB-231 cells and observed that each of them was capable of switching to another in adherent conditions. Finally, the predicted trends are supported by clinical data analysis of The Cancer Genome Atlas (TCGA) breast cancer and pan-cancer cohorts that revealed negatively correlated pAMPK and pAkt protein levels. Overall, our integrated computational-experimental approach unravels that AMPK-Akt feedback loop can generate multi-stability and drive phenotypic switching and heterogeneity in a cancer cell population.

A multiscale model of complex endothelial cell dynamics in early angiogenesis

We introduce a hybrid two-dimensional multiscale model of angiogenesis, the process by which endothelial cells (ECs) migrate from a pre-existing vascular bed in response to local environmental cues and cell-cell interactions, to create a new vascular network. Recent experimental studies have highlighted a central role of cell rearrangements in the formation of angiogenic networks. Our model accounts for this phenomenon via the heterogeneous response of ECs to their microenvironment. These cell rearrangements, in turn, dynamically remodel the local environment. The model reproduces characteristic features of angiogenic sprouting that include branching, chemotactic sensitivity, the brush border effect, and cell mixing. These properties, rather than being hardwired into the model, emerge naturally from the gene expression patterns of individual cells. After calibrating and validating our model against experimental data, we use it to predict how the structure of the vascular network changes as the baseline gene expression levels of the VEGF-Delta-Notch pathway, and the composition of the extracellular environment, vary. In order to investigate the impact of cell rearrangements on the vascular network structure, we introduce the mixing measure, a scalar metric that quantifies cell mixing as the vascular network grows. We calculate the mixing measure for the simulated vascular networks generated by ECs of different lineages (wild type cells and mutant cells with impaired expression of a specific receptor). Our results show that the time evolution of the mixing measure is directly correlated to the generic features of the vascular branching pattern, thus, supporting the hypothesis that cell rearrangements play an essential role in sprouting angiogenesis. Furthermore, we predict that lower cell rearrangement leads to an imbalance between branching and sprout elongation. Since the computation of this statistic requires only individual cell trajectories, it can be computed for networks generated in biological experiments, making it a potential biomarker for pathological angiogenesis.

Angiogenesis, the process by which new blood vessels are formed by sprouting from the pre-existing vascular bed, plays a key role in both physiological and pathological processes, including tumour growth. The structure of a growing vascular network is determined by the coordinated behaviour of endothelial cells in response to various signalling cues. Recent experimental studies have highlighted the importance of cell rearrangements as a driver for sprout elongation. However, the functional role of this phenomenon remains unclear. We formulate a new multiscale model of angiogenesis which, by accounting explicitly for the complex dynamics of endothelial cells within growing angiogenic sprouts, is able to reproduce generic features of angiogenic structures (branching, chemotactic sensitivity, cell mixing, etc.) as emergent properties of its dynamics. We validate our model against experimental data and then use it to quantify the phenomenon of cell mixing in vascular networks generated by endothelial cells of different lineages. Our results show that there is a direct correlation between the time evolution of cell mixing in a growing vascular network and its branching structure, thus paving the way for understanding the functional role of cell rearrangements in angiogenesis.

Mathematical Modeling of Plasticity and Heterogeneity in EMT

The epithelial-mesenchymal transition (EMT) and the corresponding reverse process, mesenchymal-epithelial transition (MET), are dynamic and reversible cellular programs orchestrated by many changes at both biochemical and morphological levels. A recent surge in identifying the molecular mechanisms underlying EMT/MET has led to the development of various mathematical models that have contributed to our improved understanding of dynamics at single-cell and population levels: (a) multi-stability-how many phenotypes can cells attain during an EMT/MET?, (b) reversibility/irreversibility-what time and/or concentration of an EMT inducer marks the "tipping point" when cells induced to undergo EMT cannot revert?, (c) symmetry in EMT/MET-do cells take the same path when reverting as they took during the induction of EMT?, and (d) non-cell autonomous mechanisms-how does a cell undergoing EMT alter the tendency of its neighbors to undergo EMT? These dynamical traits may facilitate a heterogenous response within a cell population undergoing EMT/MET. Here, we present a few examples of designing different mathematical models that can contribute to decoding EMT/MET dynamics.

TRAIL receptor-induced features of epithelial-to-mesenchymal transition increase tumour phenotypic heterogeneity: potential cell survival mechanisms

The continuing efforts to exploit the death receptor agonists, such as the tumour necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL), for cancer therapy, have largely been impaired by the anti-apoptotic and pro-survival signalling pathways leading to drug resistance. Cell migration, invasion, differentiation, immune evasion and anoikis resistance are plastic processes sharing features of the epithelial-to-mesenchymal transition (EMT) that have been shown to give cancer cells the ability to escape cell death upon cytotoxic treatments. EMT has recently been suggested to drive a heterogeneous cellular environment that appears favourable for tumour progression. Recent studies have highlighted a link between EMT and cell sensitivity to TRAIL, whereas others have highlighted their effects on the induction of EMT. This review aims to explore the molecular mechanisms by which death signals can elicit an increase in response heterogeneity in the metastasis context, and to evaluate the impact of these processes on cell responses to cancer therapeutics.

Hybrid E/M Phenotype(s) and Stemness: A Mechanistic Connection Embedded in Network Topology

Metastasis remains an unsolved clinical challenge. Two crucial features of metastasizing cancer cells are (a) their ability to dynamically move along the epithelial-hybrid-mesenchymal spectrum and (b) their tumor initiation potential or stemness. With increasing functional characterization of hybrid epithelial/mesenchymal (E/M) phenotypes along the spectrum, recent in vitro and in vivo studies have suggested an increasing association of hybrid E/M phenotypes with stemness. However, the mechanistic underpinnings enabling this association remain unclear. Here, we develop a mechanism-based mathematical modeling framework that interrogates the emergent nonlinear dynamics of the coupled network modules regulating E/M plasticity (miR-200/ZEB) and stemness (LIN28/let-7). Simulating the dynamics of this coupled network across a large ensemble of parameter sets, we observe that hybrid E/M phenotype(s) are more likely to acquire stemness relative to "pure" epithelial or mesenchymal states. We also integrate multiple "phenotypic stability factors" (PSFs) that have been shown to stabilize hybrid E/M phenotypes both in silico and in vitro-such as OVOL1/2, GRHL2, and NRF2-with this network, and demonstrate that the enrichment of hybrid E/M phenotype(s) with stemness is largely conserved in the presence of these PSFs. Thus, our results offer mechanistic insights into recent experimental observations of hybrid E/M phenotype(s) that are essential for tumor initiation and highlight how this feature is embedded in the underlying topology of interconnected EMT (Epithelial-Mesenchymal Transition) and stemness networks.

Persistence as an Optimal Hedging Strategy

Bacteria invest in a slow-growing subpopulation, called persisters, to ensure survival in the face of uncertainty. This hedging strategy is remarkably similar to financial hedging, where diversifying an investment portfolio protects against economic uncertainty. We provide a new, to our knowledge, theoretical foundation for understanding cellular hedging by unifying the study of biological population dynamics and the mathematics of financial risk management through optimal control theory. Motivated by the widely accepted role of volatility in the emergence of persistence, we consider several models of environmental volatility described by continuous-time stochastic processes. This allows us to study an emergent cellular hedging strategy that maximizes the expected per capita growth rate of the population. Analytical and simulation results probe the optimal persister strategy, revealing results that are consistent with experimental observations and suggest new opportunities for experimental investigation and design. Overall, we provide a new, to our knowledge, way of conceptualizing and modeling cellular decision making in volatile environments by explicitly unifying theory from mathematical biology and finance.

Tackle Epithelial-Mesenchymal Transition With Epigenetic Drugs in Cancer

Epithelial-mesenchymal Transition (EMT) is a de-differentiation process in which epithelial cells lose their epithelial properties to acquire mesenchymal features. EMT is essential for embryogenesis and wound healing but is aberrantly activated in pathological conditions like fibrosis and cancer. Tumor-associated EMT contributes to cancer cell initiation, invasion, metastasis, drug resistance and recurrence. This dynamic and reversible event is governed by EMT-transcription factors (EMT-TFs) with epigenetic complexes. In this review, we discuss recent advances regarding the mechanisms that modulate EMT in the context of epigenetic regulation, with emphasis on epigenetic drugs, such as DNA demethylating reagents, inhibitors of histone modifiers and non-coding RNA medication. Therapeutic contributions that improve epigenetic regulation of EMT will translate the clinical manifestation as treating cancer progression more efficiently.