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 Reveals the Underlying Mechanism of Cancer-Adipose Conversion in Gene Network Models

Cancer is a systemic heterogeneous disease involving complex molecular networks. Tumor formation involves an epithelial-mesenchymal transition (EMT), which promotes both metastasis and plasticity of cancer cells. Recent experiments have proposed that cancer cells can be transformed into adipocytes via a combination of drugs. However, the underlying mechanisms for how these drugs work, from a molecular network perspective, remain elusive. To reveal the mechanism of cancer-adipose conversion (CAC), this study adopts a systems biology approach by combing mathematical modeling and molecular experiments, based on underlying molecular regulatory networks. Four types of attractors are identified, corresponding to epithelial (E), mesenchymal (M), adipose (A) and partial/intermediate EMT (P) cell states on the CAC landscape. Landscape and transition path results illustrate that intermediate states play critical roles in the cancer to adipose transition. Through a landscape control approach, two new therapeutic strategies for drug combinations are identified, that promote CAC. These predictions are verified by molecular experiments in different cell lines. The combined computational and experimental approach provides a powerful tool to explore molecular mechanisms for cell fate transitions in cancer networks. The results reveal underlying mechanisms of intermediate cell states that govern the CAC, and identified new potential drug combinations to induce cancer adipogenesis.

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.

A Boolean model explains phenotypic plasticity changes underlying hepatic cancer stem cells emergence

In several carcinomas, including hepatocellular carcinoma, it has been demonstrated that cancer stem cells (CSCs) have enhanced invasiveness and therapy resistance compared to differentiated cancer cells. Mathematical-computational tools could be valuable for integrating experimental results and understanding the phenotypic plasticity mechanisms for CSCs emergence. Based on the literature review, we constructed a Boolean model that recovers eight stable states (attractors) corresponding to the gene expression profile of hepatocytes and mesenchymal cells in senescent, quiescent, proliferative, and stem-like states. The epigenetic landscape associated with the regulatory network was analyzed. We observed that the loss of p53, p16, RB, or the constitutive activation of β-catenin and YAP1 increases the robustness of the proliferative stem-like phenotypes. Additionally, we found that p53 inactivation facilitates the transition of proliferative hepatocytes into stem-like mesenchymal phenotype. Thus, phenotypic plasticity may be altered, and stem-like phenotypes related to CSCs may be easier to attain following the mutation acquisition.

Reconstruction of single-cell lineage trajectories and identification of diversity in fates during the epithelial-to-mesenchymal transition

Exploring the complexity of the epithelial-to-mesenchymal transition (EMT) unveils a diversity of potential cell fates; however, the exact timing and mechanisms by which early cell states diverge into distinct EMT trajectories remain unclear. Studying these EMT trajectories through single-cell RNA sequencing is challenging due to the necessity of sacrificing cells for each measurement. In this study, we employed optimal-transport analysis to reconstruct the past trajectories of different cell fates during TGF-beta-induced EMT in the MCF10A cell line. Our analysis revealed three distinct trajectories leading to low EMT, partial EMT, and high EMT states. Cells along the partial EMT trajectory showed substantial variations in the EMT signature and exhibited pronounced stemness. Throughout this EMT trajectory, we observed a consistent downregulation of the EED and EZH2 genes. This finding was validated by recent inhibitor screens of EMT regulators and CRISPR screen studies. Moreover, we applied our analysis of early-phase differential gene expression to gene sets associated with stemness and proliferation, pinpointing ITGB4, LAMA3, and LAMB3 as genes differentially expressed in the initial stages of the partial versus high EMT trajectories. We also found that CENPF, CKS1B, and MKI67 showed significant upregulation in the high EMT trajectory. While the first group of genes aligns with findings from previous studies, our work uniquely pinpoints the precise timing of these upregulations. Finally, the identification of the latter group of genes sheds light on potential cell cycle targets for modulating EMT trajectories.

Phenotypic Plasticity and Cancer: A System Biology Perspective

Epithelial-to-mesenchymal transition (EMT) is a major axis of phenotypic plasticity not only in diseased conditions such as cancer metastasis and fibrosis but also during normal development and wound healing. Yet-another important axis of plasticity with metastatic implications includes the cancer stem cell (CSCs) and non-CSC transitions. However, in both processes, epithelial (E) and mesenchymal (M) phenotypes are not merely binary states. Cancer cells acquire a spectrum of phenotypes with traits, properties, and markers of both E and M phenotypes, giving rise to intermediary hybrid (E/M) phenotypes. E/M cells play an important role in tumor initiation, metastasis, and disease progression in multiple cancers. Furthermore, the hybrid phenotypes also play a major role in causing therapeutic resistance in cancer. Here, we discuss how a systems biology perspective on the problem, which is implicit in the 'Team Medicine' approach outlined in the theme of this Special Issue of The Journal of Clinical Medicine and includes an interdisciplinary team of experts, is more likely to shed new light on EMT in cancer and help us to identify novel therapeutics and strategies to target phenotypic plasticity in cancer.

Cell-state transitions and density-dependent interactions together explain the dynamics of spontaneous epithelial-mesenchymal heterogeneity

Cancer cell populations comprise phenotypes distributed among the epithelial-mesenchymal (E-M) spectrum. However, it remains unclear which population-level processes give rise to the observed experimental distribution and dynamical changes in E-M heterogeneity, including (1) differential growth, (2) cell-state switching, and (3) population density-dependent growth or state-transition rates. Here, we analyze the necessity of these three processes in explaining the dynamics of E-M population distributions as observed in PMC42-LA and HCC38 breast cancer cells. We find that, while cell-state transition is necessary to reproduce experimental observations of dynamical changes in E-M fractions, including density-dependent growth interactions (cooperation or suppression) better explains the data. Further, our models predict that treatment of HCC38 cells with transforming growth factor β (TGF-β) signaling and Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/3) inhibitors enhances the rate of mesenchymal-epithelial transition (MET) instead of lowering that of E-M transition (EMT). Overall, our study identifies the population-level processes shaping the dynamics of spontaneous E-M heterogeneity in breast cancer cells.

NF-κB/RelA signaling in secretoglobin progenitors mediates plasticity and MMP-induced barrier disruption in house dust mite-induced allergic asthma

The mechanisms how aeroallergens induce sensitization are incompletely understood. The house dust mite (HDM) Dermatophagoides pteronyssius (Der p) is a ubiquitous aeroallergen that represents a major cause of allergic rhinitis and asthma. Herein, we tested whether HDM-induced aeroallergen exposure sensitivity is caused by the innate-immune response in small airway epithelial cells. HDM exposure is a rapid activator of NF-κB/RelA in the Secretoglobin (Scgb1a1+) lineage associated with upregulation of NF-κB/RelA-dependent markers of epithelial plasticity. To determine the effect of epithelial NF-κB signaling, NF-κB was depleted in a tamoxifen (TMX)-inducible Scgb1a1-CreERTM mouse within a CL57B/L6 background. Corn oil or TMX-treated/RelA-depleted [RelA knockdown (KD)] mice were repetitively exposed to airway HDM challenges to induce airway hyperresponsiveness (AHR). Strikingly, we observed that HDM induces hallmarks of epithelial plasticity through upregulation of the mesenchymal core factors SNAI1 and ZEB1 and production of metalloproteinase (MMP)9 that are RelA-dependent. Downstream, HDM-induced mucous metaplasia, Th2 polarization, allergen sensitivity, and airway hyperreactivity were all reduced in the RelA-depleted mice. Mechanistically, HDM-induced functional and structural barrier disruption was dependent on RelA signaling and associated with active MMP secretion into the bronchoalveolar lavage fluid. To establish the role of MMP2/9 in barrier disruption, we observe that a small-molecule MMP inhibitor (SB-3CT) blocked HDM-induced barrier disruption and activation of plasticity in naïve wild-type (WT) mice. Loss of functional barrier was associated with MMP disruption of zona occludens (ZO)-1 containing adherens junctions. Overall, this data indicates that host innate signaling in the Scgb1a1+ progenitors is directly linked to epithelial plasticity, MMP9 secretion, and enhanced barrier permeability that allows allergen penetration, sensitization producing allergic asthma (AA) in vivo. We propose that maintenance of epithelial integrity may reduce allergic sensitization and AA.NEW & NOTEWORTHY Allergic asthma from house dust mite (HDM) allergy causes substantial morbidity. This study examines the dynamic changes in small airway epithelial cells in a mouse model of HDM exposure. Our findings indicate that NF-κB/RelA signaling mediates matrix metalloproteinase production, disrupting the epithelial barrier resulting in allergic sensitization. Our findings bring new insight into mechanisms for epithelial cell-state change in the allergen response, creating a potential therapeutic pathway for maintaining barrier function in asthma.

RNA regulatory mechanisms controlling TGF-β signaling and EMT in cancer

Epithelial-mesenchymal transition (EMT) is a major contributor to metastatic progression and is prominently regulated by TGF-β signalling. Both EMT and TGF-β pathway components are tightly controlled by non-coding RNAs - including microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) - that collectively have major impacts on gene expression and resulting cellular states. While miRNAs are the best characterised regulators of EMT and TGF-β signaling and the miR-200-ZEB1/2 feedback loop plays a central role, important functions for lncRNAs and circRNAs are also now emerging. This review will summarise our current understanding of the roles of non-coding RNAs in EMT and TGF-β signaling with a focus on their functions in cancer progression.

Comprehensive molecular interaction map of TGFβ induced epithelial to mesenchymal transition in breast cancer

Breast cancer is one of the prevailing cancers globally, with a high mortality rate. Metastatic breast cancer (MBC) is an advanced stage of cancer, characterised by a highly nonlinear, heterogeneous process involving numerous singling pathways and regulatory interactions. Epithelial-mesenchymal transition (EMT) emerges as a key mechanism exploited by cancer cells. Transforming Growth Factor-β (TGFβ)-dependent signalling is attributed to promote EMT in advanced stages of breast cancer. A comprehensive regulatory map of TGFβ induced EMT was developed through an extensive literature survey. The network assembled comprises of 312 distinct species (proteins, genes, RNAs, complexes), and 426 reactions (state transitions, nuclear translocations, complex associations, and dissociations). The map was developed by following Systems Biology Graphical Notation (SBGN) using Cell Designer and made publicly available using MINERVA ( http://35.174.227.105:8080/minerva/?id=Metastatic_Breast_Cancer_1 ). While the complete molecular mechanism of MBC is still not known, the map captures the elaborate signalling interplay of TGFβ induced EMT-promoting MBC. Subsequently, the disease map assembled was translated into a Boolean model utilising CaSQ and analysed using Cell Collective. Simulations of these have captured the known experimental outcomes of TGFβ induced EMT in MBC. Hub regulators of the assembled map were identified, and their transcriptome-based analysis confirmed their role in cancer metastasis. Elaborate analysis of this map may help in gaining additional insights into the development and progression of metastatic breast cancer.

Decoding the principle of cell-fate determination for its reverse control

Understanding and manipulating cell fate determination is pivotal in biology. Cell fate is determined by intricate and nonlinear interactions among molecules, making mathematical model-based quantitative analysis indispensable for its elucidation. Nevertheless, obtaining the essential dynamic experimental data for model development has been a significant obstacle. However, recent advancements in large-scale omics data technology are providing the necessary foundation for developing such models. Based on accumulated experimental evidence, we can postulate that cell fate is governed by a limited number of core regulatory circuits. Following this concept, we present a conceptual control framework that leverages single-cell RNA-seq data for dynamic molecular regulatory network modeling, aiming to identify and manipulate core regulatory circuits and their master regulators to drive desired cellular state transitions. We illustrate the proposed framework by applying it to the reversion of lung cancer cell states, although it is more broadly applicable to understanding and controlling a wide range of cell-fate determination processes.

The role of alternative polyadenylation in epithelial-mesenchymal transition of non-small cell lung cancer

The metastatic non-small cell lung cancer (NSCLC) is one of the cancers with high incidence, poor survival, and limited treatment. Epithelial-mesenchymal transition (EMT) is the first step by which an early tumor converts to an invasive one. Studying the underlying mechanisms of EMT can help the understanding of cancer metastasis and improve the treatment. In this study, 1013 NSCLC patients and 123 NSCLC cell lines are deeply analyzed for the potential roles of alternative polyadenylation (APA) in the EMT process. A trend of shorter 3'-UTRs (three prime untranslated region) is discovered in the mesenchymal samples. The identification of EMT-related APA events highlights the proximal poly(A) selection of CARM1. It is a pathological biomarker of mesenchymal tumor and cancer metastasis through losing miRNA binding to upregulate the EMT inducer of CARM1 and releasing miRNAs to downregulate the EMT inhibitor of RBM47. The crucial role of this APA event in EMT also guides its effect on drug responses. The patients with shorter 3'-UTR of CARM1 are more benefit from chemotherapy drugs, especially cisplatin. A stratification of NSCLC patients based on this APA event is useful for chemotherapy design in future clinics.

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.

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.

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.

How important is EMT for cancer metastasis?

Epithelial-to-mesenchymal transition (EMT), a biological phenomenon of cellular plasticity initially reported in embryonic development, has been increasingly recognized for its importance in cancer progression and metastasis. Despite tremendous progress being made in the past 2 decades in our understanding of the molecular mechanism and functional importance of EMT in cancer, there are several mysteries around EMT that remain unresolved. In this Unsolved Mystery, we focus on the variety of EMT types in metastasis, cooperative and collective EMT behaviors, spatiotemporal characterization of EMT, and strategies of therapeutically targeting EMT. We also highlight new technical advances that will facilitate the efforts to elucidate the unsolved mysteries of EMT in metastasis.

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.

Expression profiles of lncRNAs, miRNAs, and mRNAs and interaction analysis indicate their potential involvement during testicular fusion in Spodoptera litura

Testicular fusion of Spodoptera litura occures during metamorphosis, which benefits sperms development. Previous research identified involvement of ECM-integrin interaction pathways, MMPs in testicular fusion, but the regulatory mechanism remains unclear. RNA-seq was performed to analyze long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) in testes, aiming to uncover potential regulatory mechanisms of testicular fusion. 2150 lncRNAs, 2742 targeted mRNAs, and 347 miRNAs were identified in testes at three different developmental stages. Up-regulated DElncRNAs and DEmRNAs, as well as down-regulated DEmiRNAs, were observed during testicular fusion, while the opposite expression pattern was observed after fusion. Enrichment analysis of DEmRNAs revealed that cAMP signal pathway, ECM remodeling enzymes, ECM-integrin interaction pathways, and cell adhesion molecules were potentially associated with testicular fusion. The identified DElncRNA-DEmiRNA-DEmRNA regulatory network related to cAMP signal pathway, ECM remodeling enzymes suggests their roles during testicular fusion. Our research will provide new targets for studying the mechanism of testicular fusion.

Subconfluent ARPE-19 Cells Display Mesenchymal Cell-State Characteristics and Behave like Fibroblasts, Rather Than Epithelial Cells, in Experimental HCMV Infection Studies

Human cytomegalovirus (HCMV) has a broad cellular tropism and epithelial cells are important physiological targets during infection. The retinal pigment epithelial cell line ARPE-19 has been used to model HCMV infection in epithelial cells for decades and remains a commonly used cell type for studying viral entry, replication, and the cellular response to infection. We previously found that ARPE-19 cells, despite being derived from an epithelial cell explant, express extremely low levels of canonical epithelial proteins, such as E-cadherin and EpCAM. Here, we perform comparative studies of ARPE-19 and additional epithelial cell lines with strong epithelial characteristics. We find that ARPE-19 cells cultured under subconfluent conditions resemble mesenchymal fibroblasts, rather than epithelial cells; this is consistent with previous studies showing that ARPE-19 cultures require extended periods of high confluency culture to maintain epithelial characteristics. By reanalyzing public gene expression data and using machine learning, we find evidence that ARPE-19 cultures maintained across many labs exhibit mesenchymal characteristics and that the majority of studies employing ARPE-19 use them in a mesenchymal state. Lastly, by performing experimental HCMV infections across mesenchymal and epithelial cell lines, we find that ARPE-19 cells behave like mesenchymal fibroblasts, producing logarithmic yields of cell-free infectious progeny, while cell lines with strong epithelial character exhibit an atypical infectious cycle and naturally restrict the production of cell-free progeny. Our work highlights important characteristics of the ARPE-19 cell line and suggests that subconfluent ARPE-19 cells may not be optimal for modeling epithelial infection with HCMV or other human viruses. It also suggests that HCMV biosynthesis and/or spread may occur quite differently in epithelial cells compared to mesenchymal cells. These differences could contribute to viral persistence or pathogenesis in epithelial tissues.

Morphological and cytoskeleton changes in cells after EMT

Epithelial cells undergoing EMT experience significant alterations at transcriptional and morphological levels. However, changes in the cytoskeleton, especially cytoskeleton dynamics are poorly described. Addressing the question we induced EMT in three cell lines (MCF-7, HaCaT and A-549) and analyzed morphological and cytoskeletal changes there using immunostaining and life cell imaging of cells transfected with microtubule and focal adhesion markers. In all studied cell lines, cell area after EMT increased, MCF-7 and A-549 cells became elongated, while HaCaT cells kept the aspect ratio the same. We next analyzed three components of the cytoskeleton: microtubules, stress fibers and focal adhesions. The following changes were observed after EMT in cultured cells: (i) Organization of microtubules becomes more radial; and the growth rate of microtubule plus ends was accelerated; (ii) Actin stress fibers become co-aligned forming the longitudinal cell axis; and (iii) Focal adhesions had decreased area in all cancer cell lines studied and became more numerous in HaCaT cells. We conclude that among dynamic components of the cytoskeleton, the most significant changes during EMT happen in the regulation of microtubules.

Altered Phenotypes of Breast Epithelial × Breast Cancer Hybrids after ZEB1 Knock-Out

ZEB1 plays a pivotal role in epithelial-to-mesenchymal transition (EMT), (cancer) cell stemness and cancer therapy resistance. The M13HS tumor hybrids, which were derived from spontaneous fusion events between the M13SV1-EGFP-Neo breast epithelial cells and HS578T-Hyg breast cancer cells, express ZEB1 and exhibit prospective cancer stem cell properties. To explore a possible correlation between the ZEB1 and stemness/ EMT-related properties in M13HS tumor hybrids, ZEB1 was knocked-out by CRISPR/Cas9. Colony formation, mammosphere formation, cell migration, invasion assays, flow cytometry and Western blot analyses were performed for the characterization of ZEB1 knock-out cells. The ZEB1 knock-out in M13HS tumor cells was not correlated with the down-regulation of the EMT-related markers N-CADHERIN (CDH2) and VIMENTIN and up-regulation of miR-200c-3p. Nonetheless, both the colony formation and mammosphere formation capacities of the M13HS ZEB1 knock-out cells were markedly reduced. Interestingly, the M13HS-2 ZEB1-KO cells harbored a markedly higher fraction of ALDH1-positive cells. The Transwell/ Boyden chamber migration assay data indicated a reduced migratory activity of the M13HS ZEB1-knock-out tumor hybrids, whereas in scratch/ wound-healing assays only the M13SH-8 ZEB1-knock-out cells possessed a reduced locomotory activity. Similarly, only the M13HS-8 ZEB1-knock-out tumor hybrids showed a reduced invasion capacity. Although the ZEB1 knock-out resulted in only moderate phenotypic changes, our data support the role of ZEB1 in EMT and stemness.

Identifying key factors in cell fate decisions by machine learning interpretable strategies

Cell fate decisions and transitions are common in almost all developmental processes. Therefore, it is important to identify the decision-making mechanisms and important individual molecules behind the fate decision processes. In this paper, we propose an interpretable strategy based on systematic perturbation, unsupervised hierarchical cluster analysis (HCA), machine learning (ML), and Shapley additive explanation (SHAP) analysis for inferring the contribution and importance of individual molecules in cell fate decision and transition processes. In order to verify feasibility of the approach, we apply it to the core epithelial to mesenchymal transition (EMT)-metastasis network. The key factors identified in EMT-metastasis are consistent with relevant experimental observations. The approach presented here can be applied to other biological networks to identify important factors related to cell fate decisions and transitions.

Effects of microRNA-mediated negative feedback on gene expression noise

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression post-transcriptionally in eukaryotes by binding with target mRNAs and preventing translation. miRNA-mediated feedback motifs are ubiquitous in various genetic networks that control cellular decision making. A key question is how such a feedback mechanism may affect gene expression noise. To answer this, we have developed a mathematical model to study the effects of a miRNA-dependent negative-feedback loop on mean expression and noise in target mRNAs. Combining analytics and simulations, we show the existence of an expression threshold demarcating repressed and expressed regimes in agreement with earlier studies. The steady-state mRNA distributions are bimodal near the threshold, where copy numbers of mRNAs and miRNAs exhibit enhanced anticorrelated fluctuations. Moreover, variation of negative-feedback strength shifts the threshold locations and modulates the noise profiles. Notably, the miRNA-mRNA binding affinity and feedback strength collectively shape the bimodality. We also compare our model with a direct auto-repression motif, where a gene produces its own repressor. Auto-repression fails to produce bimodal mRNA distributions as found in miRNA-based indirect repression, suggesting the crucial role of miRNAs in creating phenotypic diversity. Together, we demonstrate how miRNA-dependent negative feedback modifies the expression threshold and leads to a broader parameter regime of bimodality compared to the no-feedback case.

Cusp bifurcation in a metastatic regulatory network

Understanding the potential for cancers to metastasize is still relatively unknown. While many predictive methods may use deep learning or stochastic processes, we highlight a long standing mathematical concept that may be useful for modeling metastatic breast cancer systems. Ordinary differential equations (ODEs) can model cell state transitions by considering the pertinent environmental variables as well as the paths systems take over time. Bifurcation theory is a branch of dynamical systems which studies changes in the behavior of an ODE system while one or more parameters are varied. Many studies have applied concepts in one-parameter bifurcation theory to model biological network dynamics, and cell division. However, studies of two-parameter bifurcations are much more rare. Two-parameter bifurcations have not been studied in metastatic systems. Here we show how a specific two-parameter bifurcation phenomenon called a cusp bifurcation separates two qualitatively different metastatic cell state transitions modalities and propose a new perspective on defining such transitions based on mathematical theory. We hope the observations and verification methods detailed here may help in the understanding of metastatic potential from a basic biological perspective and in clinical settings.

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.

Dynamics, statistics, and task allocation of foraging ants

Ant foraging is one of the most fascinating examples of cooperative behavior observed in nature. It is well studied from an entomology viewpoint, but there is currently a lack of mathematical synthesis of this phenomenon. We address this by constructing an ant foraging model that incorporates simple behavioral rules within three task groups of the ant colony during foraging (foragers, transporters, and followers), pheromone trails, and memory effects. The motion of an ant is modeled as a discrete correlated random walk, with a characteristic zigzag path that is congruent with experimental data. We simulate the foraging cycle, which consists of ants searching for food, transporting food, and depositing chemical trails to recruit and orient more ants (en masse) to the food source. This allows us to gain insights into the basic mechanism of the cooperative interactions between ants and the dynamical division of labor within an ant colony during foraging to achieve optimal efficiency. We observe a disorder-order phase transition from the start to the end of a foraging process, signaling collective motion at the population level. Finally, we present a set of time delay ODEs that corroborates with numerical simulations.

Understanding and leveraging phenotypic plasticity during metastasis formation

Cancer metastasis is the process of detrimental systemic spread and the primary cause of cancer-related fatalities. Successful metastasis formation requires tumor cells to be proliferative and invasive; however, cells cannot be effective at both tasks simultaneously. Tumor cells compensate for this trade-off by changing their phenotype during metastasis formation through phenotypic plasticity. Given the changing selection pressures and competitive interactions that tumor cells face, it is poorly understood how plasticity shapes the process of metastasis formation. Here, we develop an ecology-inspired mathematical model with phenotypic plasticity and resource competition between phenotypes to address this knowledge gap. We find that phenotypically plastic tumor cell populations attain a stable phenotype equilibrium that maintains tumor cell heterogeneity. Considering treatment types inspired by chemo- and immunotherapy, we highlight that plasticity can protect tumors against interventions. Turning this strength into a weakness, we corroborate current clinical practices to use plasticity as a target for adjuvant therapy. We present a parsimonious view of tumor plasticity-driven metastasis that is quantitative and experimentally testable, and thus potentially improving the mechanistic understanding of metastasis at the cell population level, and its treatment consequences.

A unique cell population expressing the Epithelial-Mesenchymal Transition-transcription factor Snail moderates microglial and astrocyte injury responses

Insults to the central nervous system (CNS) elicit common glial responses including microglial activation evidenced by functional, morphological, and phenotypic changes, as well as astrocyte reactions including hypertrophy, altered process orientation, and changes in gene expression and function. However, the cellular and molecular mechanisms that initiate and modulate such glial response are less well-defined. Here we show that an adult cortical lesion generates a population of ultrastructurally unique microglial-like cells that express Epithelial-Mesenchymal Transcription factors including Snail. Knockdown of Snail with antisense oligonucleotides results in a postinjury increase in activated microglial cells, elevation in astrocyte reactivity with increased expression of C3 and phagocytosis, disruption of astrocyte junctions and neurovascular structure, increases in neuronal cell death, and reduction in cortical synapses. These changes were associated with alterations in pro-inflammatory cytokine expression. By contrast, overexpression of Snail through microglia-targeted an adeno-associated virus (AAV) improved many of the injury characteristics. Together, our results suggest that the coordination of glial responses to CNS injury is partly mediated by epithelial-mesenchymal transition-factors (EMT-Fsl).

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.

Theoretical and computational tools to model multistable gene regulatory networks

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.

Population dynamics of EMT elucidates the timing and distribution of phenotypic intra-tumoral heterogeneity

The Epithelial-to-Mesenchymal Transition (EMT) is a hallmark of cancer metastasis and morbidity. EMT is a non-binary process, and cells can be stably arrested en route to EMT in an intermediate hybrid state associated with enhanced tumor aggressiveness and worse patient outcomes. Understanding EMT progression in detail will provide fundamental insights into the mechanisms underlying metastasis. Despite increasingly available single-cell RNA sequencing (scRNA-seq) data that enable in-depth analyses of EMT at the single-cell resolution, current inferential approaches are limited to bulk microarray data. There is thus a great need for computational frameworks to systematically infer and predict the timing and distribution of EMT-related states at single-cell resolution. Here, we develop a computational framework for reliable inference and prediction of EMT-related trajectories from scRNA-seq data. Our model can be utilized across a variety of applications to predict the timing and distribution of EMT from single-cell sequencing data.

ZHX2 deficiency enriches hybrid MET cells through regulating E-cadherin expression

Growing evidence indicates that the epithelial to mesenchymal (E/M) hybrid state plays a key role in tumorigenesis. Importantly, a hybrid mesenchymal to epithelial transition (MET) state in which individual cells express both epithelial and mesenchymal markers was recently identified in vivo, further strengthening the bonds between the hybrid EMT state and cancer progression. However, the role and the molecular mechanisms by which the hybrid MET state is maintained in triple-negative breast cancer cells (TNBC) remain elusive. Here, we find that loss of ZHX2 expression results in the hybrid MET phenotype in mesenchymal TNBC cells. Mechanistically, through directly binding to the CDH1 promoter, depletion of ZHX2 specifically reactivates expression of CDH1 encoding E-cadherin, an epithelial marker that is crucial for maintaining epithelial phenotype. Functionally, loss of ZHX2 expression enriches the hybrid MET cells and inhibits the migration and dissemination of TNBC cells or organoids, which could be reversed by restoration of E-cadherin. Moreover, depletion of ZHX2 suppresses lung metastasis in preclinical models of TNBC. In patients with TNBC, ZHX2 expression was amplified and negatively correlated with the expression of E-cadherin. These findings suggest that loss of ZHX2 promotes the hybrid MET state to impair TNBC progression.

Genomic targets of the IRE1-XBP1s pathway in mediating metabolic adaptation in epithelial plasticity

Epithelial mesenchymal plasticity (EMP) is a complex cellular reprogramming event that plays a major role in tissue homeostasis. Recently we observed the unfolded protein response (UPR) triggers EMP through the inositol-requiring protein 1 (IRE1α)-X-box-binding protein 1 spliced (XBP1s) axis, enhancing glucose shunting to protein N glycosylation. To better understand the genomic targets of XBP1s, we identified its genomic targets using Cleavage Under Targets and Release Using Nuclease (CUT&RUN) of a FLAG-epitope tagged XBP1s in RSV infection. CUT&RUN identified 7086 binding sites in chromatin that were enriched in AP-1 motifs and GC-sequences. Of these binding sites, XBP1s peaks mapped to 4827 genes controlling Rho-GTPase signaling, N-linked glycosylation and ER-Golgi transport. Strikingly, XBP1s peaks were within 1 kb of transcription start sites of 2119 promoters. In addition to binding core mesenchymal transcription factors SNAI1 and ZEB1, we observed that hexosamine biosynthetic pathway (HBP) enzymes were induced and contained proximal XBP1s peaks. We demonstrate that IRE1α -XBP1s signaling is necessary and sufficient to activate core enzymes by recruiting elongation-competent phospho-Ser2 CTD modified RNA Pol II. We conclude that the IRE1α-XBP1s pathway coordinately regulates mesenchymal transcription factors and hexosamine biosynthesis in EMP by a mechanism involving recruitment of activated pSer2-Pol II to GC-rich promoters.

Dynamics of Epithelial-Mesenchymal Plasticity: What Have Single-Cell Investigations Elucidated So Far?

Epithelial-mesenchymal plasticity (EMP) is a key driver of cancer metastasis and therapeutic resistance, through which cancer cells can reversibly and dynamically alter their molecular and functional traits along the epithelial-mesenchymal spectrum. While cells in the epithelial phenotype are usually tightly adherent, less metastatic, and drug-sensitive, those in the hybrid epithelial/mesenchymal and/or mesenchymal state are more invasive, migratory, drug-resistant, and immune-evasive. Single-cell studies have emerged as a powerful tool in gaining new insights into the dynamics of EMP across various cancer types. Here, we review many recent studies that employ single-cell analysis techniques to better understand the dynamics of EMP in cancer both in vitro and in vivo. These single-cell studies have underlined the plurality of trajectories cells can traverse during EMP and the consequent heterogeneity of hybrid epithelial/mesenchymal phenotypes seen at both preclinical and clinical levels. They also demonstrate how diverse EMP trajectories may exhibit hysteretic behavior and how the rate of such cell-state transitions depends on the genetic/epigenetic background of recipient cells, as well as the dose and/or duration of EMP-inducing growth factors. Finally, we discuss the relationship between EMP and patient survival across many cancer types. We also present a next set of questions related to EMP that could benefit much from single-cell observations and pave the way to better tackle phenotypic switching and heterogeneity in clinic.

Unraveling non-genetic heterogeneity in cancer with dynamical models and computational tools

Individual cells within an otherwise genetically homogenous population constantly undergo fluctuations in their molecular state, giving rise to non-genetic heterogeneity. Such diversity is being increasingly implicated in cancer therapy resistance and metastasis. Identifying the origins of non-genetic heterogeneity is therefore crucial for making clinical breakthroughs. We discuss with examples how dynamical models and computational tools have provided critical multiscale insights into the nature and consequences of non-genetic heterogeneity in cancer. We demonstrate how mechanistic modeling has been pivotal in establishing key concepts underlying non-genetic diversity at various biological scales, from population dynamics to gene regulatory networks. We discuss advances in single-cell longitudinal profiling techniques to reveal patterns of non-genetic heterogeneity, highlighting the ongoing efforts and challenges in statistical frameworks to robustly interpret such multimodal datasets. Moving forward, we stress the need for data-driven statistical and mechanistically motivated dynamical frameworks to come together to develop predictive cancer models and inform therapeutic strategies.

The molecular mechanism of Y473 phosphorylation of UGDH relieves the inhibition effect of UDP-glucose on HuR

Uridine diphosphate glucose (UDP-Glc) is able to accelerate the decay of snail family transcriptional repressor 1 (SNAI1) mRNA by inhibiting Hu antigen R (HuR, an RNA-binding protein), thereby preventing cancer invasiveness and drug resistance. Nevertheless, the phosphorylation of tyrosine 473 (Y473) of UDP-glucose dehydrogenase (UGDH is capable of converting UDP-Glc to uridine diphosphate glucuronic acid (UDP-GlcUA)) weakens the inhibition of UDP-Glc to HuR, thus initiating the epithelial-mesenchymal transformation of tumor cells and promoting tumor cell migration and metastasis. To address the mechanism, we performed molecular dynamics simulations combined with molecular mechanics generalized Born surface area (MM/GBSA) analysis on wild-type and Y473 phosphorylated UGDH and HuR, UDP-Glc, UDP-GlcUA complexes. We demonstrated that Y473 phosphorylation was able to enhance the binding between UGDH and the HuR/UDP-Glc complex. Compared with HuR, UGDH has a stronger binding ability with UDP-Glc; therefore, UDP-Glc was inclined to bind to UGDH and then was catalyzed to UDP-GlcUA by UGDH, which relieved the inhibition of UDP-Glc to HuR. In addition, the binding ability of HuR for UDP-GlcUA was lower than its affinity for UDP-Glc, significantly reducing the inhibition of HuR. Hence, HuR bound to SNAI1 mRNA more easily to increase the stability of mRNA. Our results revealed the micromolecular mechanism of Y473 phosphorylation of UGDH regulating the interaction between UGDH and HuR as well as relieving the inhibition of UDP-Glc on HuR, which contributed to understanding the role of UGDH and HuR in tumor metastasis and developing small molecule drugs targeting the interaction between UGDH and HuR.

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.

Inhibition of WNT signaling by conjugated microRNA nano-carriers: A new therapeutic approach for treating triple-negative breast cancer a perspective review

Triple-Negative Breast Cancer is the most aggressive form and accounts the 15%-25% of all breast cancer. Receptors are absent in triple-negative breast cancer, which makes them unresponsive to the current hormonal therapies. The patients with TNBC are left with the option of cytotoxic chemotherapy. The Wnt pathways are connected to cancer, and when activated, they result in mammary hyperplasia and tumors. The tumor suppressor microRNAs can block tumor cell proliferation, invasion, and migration, lead to cancer cell death, and are also known to down-regulate the WNT signaling. Nanoparticles with microRNA have been seen to be more effective when compared with their single release. In this review, we have tried to understand how Wnt signaling plays a crucial role in TNBC, EMT, metastasis, anti-drug resistance, and regulation of Wnt by microRNA. The role of nano-carriers in delivering micro-RNA. The clinical biomarkers, including the present state-of-the-art, involve novel pathways of Wnt.

Spatiotemporal Patterning Enabled by Gene Regulatory Networks

Spatiotemporal pattern formation plays a key role in various biological phenomena including embryogenesis and neural network formation. Though the reaction-diffusion systems enabling pattern formation have been studied phenomenologically, the biomolecular mechanisms behind these processes have not been modeled in detail. Here, we study the emergence of spatiotemporal patterns due to simple, synthetic and commonly observed two- and three-node gene regulatory network motifs coupled with their molecular diffusion in one- and two-dimensional space. We investigate the patterns formed due to the coupling of inherent multistable and oscillatory behavior of the toggle switch, toggle switch with double self-activation, toggle triad, and repressilator with the effect of spatial diffusion of these molecules. We probe multiple parameter regimes corresponding to different regions of stability (monostable, multistable, oscillatory) and assess the impact of varying diffusion coefficients. This analysis offers valuable insights into the design principles of pattern formation facilitated by these network motifs, and it suggests the mechanistic underpinnings of biological pattern formation.

A quantitative evaluation of topological motifs and their coupling in gene circuit state distributions

One of the major challenges in biology is to understand how gene interactions collaborate to determine overall functions of biological systems. Here, we present a new computational framework that enables systematic, high-throughput, and quantitative evaluation of how small transcriptional regulatory circuit motifs, and their coupling, contribute to functions of a dynamical biological system. We illustrate how this approach can be applied to identify four-node gene circuits, circuit motifs, and motif coupling responsible for various gene expression state distributions, including those derived from single-cell RNA sequencing data. We also identify seven major classes of four-node circuits from clustering analysis of state distributions. The method is applied to establish phenomenological models of gene circuits driving human neuron differentiation, revealing important biologically relevant regulatory interactions. Our study will shed light on a better understanding of gene regulatory mechanisms in creating and maintaining cellular states.

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.

Mechanisms involved in cancer stem cell resistance in head and neck squamous cell carcinoma

Despite scientific advances in the Oncology field, cancer remains a leading cause of death worldwide. Molecular and cellular heterogeneity of head and neck squamous cell carcinoma (HNSCC) is a significant contributor to the unpredictability of the clinical response and failure in cancer treatment. Cancer stem cells (CSCs) are recognized as a subpopulation of tumor cells that can drive and maintain tumorigenesis and metastasis, leading to poor prognosis in different types of cancer. CSCs exhibit a high level of plasticity, quickly adapting to the tumor microenvironment changes, and are intrinsically resistant to current chemo and radiotherapies. The mechanisms of CSC-mediated therapy resistance are not fully understood. However, they include different strategies used by CSCs to overcome challenges imposed by treatment, such as activation of DNA repair system, anti-apoptotic mechanisms, acquisition of quiescent state and Epithelial-mesenchymal transition, increased drug efflux capacity, hypoxic environment, protection by the CSC niche, overexpression of stemness related genes, and immune surveillance. Complete elimination of CSCs seems to be the main target for achieving tumor control and improving overall survival for cancer patients. This review will focus on the multi-factorial mechanisms by which CSCs are resistant to radiotherapy and chemotherapy in HNSCC, supporting the use of possible strategies to overcome therapy failure.

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'.

Innate Immunity, Epithelial Plasticity, and Remodeling in Asthma

Innate immune responses (IIR) of the epithelium play a critical role in the initiation and progression of asthma. The core of the IIR is an intracellular signaling pathway activated by pattern recognition receptors (PRRs) to limit the spread of infectious organisms. This chapter will focus on the epithelium as the major innate sentinel cell and its role in acute exacerbations (AEs). Although the pathways of how the IIR activates the NFκB transcription factor, triggering cytokine secretion, dendritic cell activation, and Th2 polarization are well-described, recent exciting work has developed mechanistic insights into how chronic activation of the IIR is linked to mucosal adaptive responses. These adaptations include changes in cell state, now called epithelial-mesenchymal plasticity (EMP). EMP is a coordinated, genomic response to airway injury disrupting epithelial barrier function, expanding the basal lamina, and producing airway remodeling. EMP is driven by activation of the unfolded protein response (UPR), a transcriptional response producing metabolic shunting of glucose through the hexosamine biosynthetic pathway (HBP) to protein N-glycosylation. NFκB signaling and UPR activation pathways potentiate each other in remodeling the basement membrane. Understanding of injury-repair process of epithelium provides new therapeutic targets for precision approaches to the treatment of asthma exacerbations and their sequelae.

NetAct: a computational platform to construct core transcription factor regulatory networks using gene activity

A major question in systems biology is how to identify the core gene regulatory circuit that governs the decision-making of a biological process. Here, we develop a computational platform, named NetAct, for constructing core transcription factor regulatory networks using both transcriptomics data and literature-based transcription factor-target databases. NetAct robustly infers regulators' activity using target expression, constructs networks based on transcriptional activity, and integrates mathematical modeling for validation. Our in silico benchmark test shows that NetAct outperforms existing algorithms in inferring transcriptional activity and gene networks. We illustrate the application of NetAct to model networks driving TGF-β-induced epithelial-mesenchymal transition and macrophage polarization.

Engineering antiviral immune-like systems for autonomous virus detection and inhibition in mice

The ongoing COVID-19 pandemic has demonstrated that viral diseases represent an enormous public health and economic threat to mankind and that individuals with compromised immune systems are at greater risk of complications and death from viral diseases. The development of broad-spectrum antivirals is an important part of pandemic preparedness. Here, we have engineer a series of designer cells which we term autonomous, intelligent, virus-inducible immune-like (ALICE) cells as sense-and-destroy antiviral system. After developing a destabilized STING-based sensor to detect viruses from seven different genera, we have used a synthetic signal transduction system to link viral detection to the expression of multiple antiviral effector molecules, including antiviral cytokines, a CRISPR-Cas9 module for viral degradation and the secretion of a neutralizing antibody. We perform a proof-of-concept study using multiple iterations of our ALICE system in vitro, followed by in vivo functionality testing in mice. We show that dual output ALICE_SaCas9+Ab system delivered by an AAV-vector inhibited viral infection in herpetic simplex keratitis (HSK) mouse model. Our work demonstrates that viral detection and antiviral countermeasures can be paired for intelligent sense-and-destroy applications as a flexible and innovative method against virus infection.

Decoding the coupled decision-making of the epithelial-mesenchymal transition and metabolic reprogramming in cancer

Cancer metastasis relies on an orchestration of traits driven by different interacting functional modules, including metabolism and epithelial-mesenchymal transition (EMT). During metastasis, cancer cells can acquire a hybrid metabolic phenotype (W/O) by increasing oxidative phosphorylation without compromising glycolysis and they can acquire a hybrid epithelial/mesenchymal (E/M) phenotype by engaging EMT. Both the W/O and E/M states are associated with high metastatic potentials, and many regulatory links coupling metabolism and EMT have been identified. Here, we investigate the coupled decision-making networks of metabolism and EMT. Their crosstalk can exhibit synergistic or antagonistic effects on the acquisition and stability of different coupled metabolism-EMT states. Strikingly, the aggressive E/M-W/O state can be enabled and stabilized by the crosstalk irrespective of these hybrid states' availability in individual metabolism or EMT modules. Our work emphasizes the mutual activation between metabolism and EMT, providing an important step toward understanding the multifaceted nature of cancer metastasis.

"In medio stat virtus": Insights into hybrid E/M phenotype attitudes

Epithelial-mesenchymal plasticity (EMP) refers to the ability of cells to dynamically interconvert between epithelial (E) and mesenchymal (M) phenotypes, thus generating an array of hybrid E/M intermediates with mixed E and M features. Recent findings have demonstrated how these hybrid E/M rather than fully M cells play key roles in most of physiological and pathological processes involving EMT. To this regard, the onset of hybrid E/M state coincides with the highest stemness gene expression and is involved in differentiation of either normal and cancer stem cells. Moreover, hybrid E/M cells are responsible for wound healing and create a favorable immunosuppressive environment for tissue regeneration. Nevertheless, hybrid state is responsible of metastatic process and of the increasing of survival, apoptosis and therapy resistance in cancer cells. The present review aims to describe the main features and the emerging concepts regulating EMP and the formation of E/M hybrid intermediates by describing differences and similarities between cancer and normal hybrid stem cells. In particular, the comprehension of hybrid E/M cells biology will surely advance our understanding of their features and how they could be exploited to improve tissue regeneration and repair.