Identifying inhibitors of epithelial-mesenchymal plasticity using a network topology based approach

Metastasis is the cause of over 90% of cancer-related deaths. Cancer cells undergoing metastasis switch dynamically between different phenotypes, enabling them to adapt to harsh challenges such as overcoming anoikis and evading immune response. This ability, known as phenotypic plasticity, is crucial for the survival of cancer cells during metastasis, as well as acquiring therapy resistance. Various biochemical networks have been identified to contribute to phenotypic plasticity, but how plasticity emerges from the dynamics of these networks remains elusive. Here, we investigated the dynamics of various regulatory networks implicated in Epithelial-Mesenchymal Plasticity (EMP) - an important arm of phenotypic plasticity - through two different mathematical modeling frameworks: a discrete, parameter-independent framework (Boolean) and a continuous, parameter-agnostic modeling framework (RACIPE). Results from either framework in terms of phenotypic distributions obtained from a given EMP network are qualitatively similar and suggest that these networks are multi-stable and can give rise to phenotypic plasticity. Neither method requires specific kinetic parameters, thus our results emphasize that EMP can emerge through these networks over a wide range of parameter sets, elucidating the importance of network topology in enabling phenotypic plasticity. Furthermore, we show that the ability of exhibit phenotypic plasticity positively correlates with the number of positive feedback loops. These results pave a way towards an unorthodox network topology-based approach to identify crucial links in a given EMP network that can reduce phenotypic plasticity and possibly inhibit metastasis - by reducing the number of positive feedback loops .

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Theoretical study of the impact of adaptation on cell-fate heterogeneity and fractional killing

Scientific Reports ◽

10.1038/s41598-020-74238-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Julien Hurbain ◽

Darka Labavić ◽

Quentin Thommen ◽

Benjamin Pfeuty

Keyword(s):

Cell Fate ◽

Stochastic Dynamics ◽

Biochemical Networks ◽

Stochastic Bifurcation ◽

Modeling Framework ◽

Life And Death ◽

Cell Fate Decisions ◽

Wide Range ◽

Adaptation Response ◽

The Impact

Abstract Fractional killing illustrates the cell propensity to display a heterogeneous fate response over a wide range of stimuli. The interplay between the nonlinear and stochastic dynamics of biochemical networks plays a fundamental role in shaping this probabilistic response and in reconciling requirements for heterogeneity and controllability of cell-fate decisions. The stress-induced fate choice between life and death depends on an early adaptation response which may contribute to fractional killing by amplifying small differences between cells. To test this hypothesis, we consider a stochastic modeling framework suited for comprehensive sensitivity analysis of dose response curve through the computation of a fractionality index. Combining bifurcation analysis and Langevin simulation, we show that adaptation dynamics enhances noise-induced cell-fate heterogeneity by shifting from a saddle-node to a saddle-collision transition scenario. The generality of this result is further assessed by a computational analysis of a detailed regulatory network model of apoptosis initiation and by a theoretical analysis of stochastic bifurcation mechanisms. Overall, the present study identifies a cooperative interplay between stochastic, adaptation and decision intracellular processes that could promote cell-fate heterogeneity in many contexts.

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Coupled feedback loops involving PAGE4, EMT and Notch signaling can give rise to non-genetic heterogeneity in prostate cancer cells

10.1101/2020.12.29.423275 ◽

2020 ◽

Author(s):

Divyoj Singh ◽

Federico Bocci ◽

Prakash Kulkarni ◽

Mohit Kumar Jolly

Keyword(s):

Prostate Cancer ◽

Genetic Heterogeneity ◽

Regulatory Networks ◽

Epithelial Mesenchymal Transition ◽

Cell Communication ◽

Intrinsically Disordered Protein ◽

Therapy Resistance ◽

Feedback Loops ◽

Mesenchymal Transition ◽

Intrinsically Disordered

AbstractNon-genetic heterogeneity is emerging to be 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 possible bistability in the levels of AR. 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.

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Mechanistic mathematical model of polarity in yeast

Molecular Biology of the Cell ◽

10.1091/mbc.e11-10-0837 ◽

2012 ◽

Vol 23 (10) ◽

pp. 1998-2013 ◽

Cited By ~ 60

Author(s):

Natasha S. Savage ◽

Anita T. Layton ◽

Daniel J. Lew

Keyword(s):

Cell Polarity ◽

Positive Feedback ◽

Reaction Diffusion ◽

Feedback Loops ◽

The Other ◽

Fluorescence Recovery ◽

Modeling Framework ◽

Combined Model ◽

Feedback Mechanisms ◽

Vesicle Traffic

The establishment of cell polarity involves positive-feedback mechanisms that concentrate polarity regulators, including the conserved GTPase Cdc42p, at the “front” of the polarized cell. Previous studies in yeast suggested the presence of two parallel positive-feedback loops, one operating as a diffusion-based system, and the other involving actin-directed trafficking of Cdc42p on vesicles. F-actin (and hence directed vesicle traffic) speeds fluorescence recovery of Cdc42p after photobleaching, suggesting that vesicle traffic of Cdc42p contributes to polarization. We present a mathematical modeling framework that combines previously developed mechanistic reaction-diffusion and vesicle-trafficking models. Surprisingly, the combined model recapitulated the observed effect of vesicle traffic on Cdc42p dynamics even when the vesicles did not carry significant amounts of Cdc42p. Vesicle traffic reduced the concentration of Cdc42p at the front, so that fluorescence recovery mediated by Cdc42p flux from the cytoplasm took less time to replenish the bleached pool. Simulations in which Cdc42p was concentrated into vesicles or depleted from vesicles yielded almost identical predictions, because Cdc42p flux from the cytoplasm was dominant. These findings indicate that vesicle-mediated delivery of Cdc42p is not required to explain the observed Cdc42p dynamics, and raise the question of whether such Cdc42p traffic actually contributes to polarity establishment.

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Emergent properties of coupled bistable switches

10.1101/2021.06.15.448553 ◽

2021 ◽

Author(s):

Kishore Hari ◽

Pradyumna Harlapur ◽

Aditi Gopalan ◽

Varun Ullanat ◽

Atchuta Srinivas Duddu ◽

...

Keyword(s):

Cell Fate ◽

Positive Feedback ◽

Regulatory Networks ◽

Feedback Loops ◽

Emergent Properties ◽

Toggle Switch ◽

Continuous Simulation ◽

Decision Systems ◽

Double Activation ◽

Fate Decision

Understanding the dynamical hallmarks of network motifs is one of the fundamental aspects of systems biology. Positive feedback loops constituting one or two nodes, self-activation, toggle switch, and double activation loops, are commonly observed motifs in regulatory networks underlying cell-fate decision systems. Their individual dynamics are well-studied; they are capable of exhibiting bistability. However, studies across various biological systems suggest that such positive feedback loops are interconnected with one another, and design principles of coupled bistable motifs remain unclear. We wanted to ask what happens to bistability or multistability traits and the phenotypic space (collection of phenotypes exhibited by a system) due to the couplings. In this study, we explore a set of such interactions using discrete and continuous simulation methods. Our results suggest that couplings that do not connect the bistable switches in a way that contradicts the connections within individual bistable switches lead to a steady state space that is strictly a subset of the set of possible combinations of steady states of bistable switches. Furthermore, adding direct and indirect self-activations to these coupled networks can increase the frequency of multistability. Thus, our observations reveal specific dynamical traits exhibited by various coupled bistable motifs.

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Extracellular Vesicle-Based Communication May Contribute to the Co-Evolution of Cancer Stem Cells and Cancer-Associated Fibroblasts in Anti-Cancer Therapy

Cancers ◽

10.3390/cancers12082324 ◽

2020 ◽

Vol 12 (8) ◽

pp. 2324 ◽

Cited By ~ 2

Author(s):

Gábor Valcz ◽

Edit I. Buzás ◽

Anna Sebestyén ◽

Tibor Krenács ◽

Zoltán Szállási ◽

...

Keyword(s):

Stem Cells ◽

Cancer Cells ◽

Tumor Cells ◽

Malignant Tumors ◽

Residual Tumor ◽

Therapy Resistance ◽

Extracellular Vesicle ◽

Cancer Associated Fibroblasts ◽

Stromal Microenvironment ◽

Wide Range

Analogously to the natural selective forces in ecosystems, therapies impose selective pressure on cancer cells within tumors. Some tumor cells can adapt to this stress and are able to form resistant subpopulations, parallel with enrichment of cancer stem cell properties in the residual tumor masses. However, these therapy-resistant cells are unlikely to be sufficient for the fast tumor repopulation and regrowth by themselves. The dynamic and coordinated plasticity of residual tumor cells is essential both for the conversion of their regulatory network and for the stromal microenvironment to produce cancer supporting signals. In this nursing tissue “niche”, cancer-associated fibroblasts are known to play crucial roles in developing therapy resistance and survival of residual stem-like cells. As paracrine messengers, extracellular vesicles carrying a wide range of signaling molecules with oncogenic potential, can support the escape of some tumor cells from their deadly fate. Here, we briefly overview how extracellular vesicle signaling between fibroblasts and cancer cells including cancer progenitor/stem cells may contribute to the progression, therapy resistance and recurrence of malignant tumors.

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Positive Feedback Loops Between Inflammatory, Bone and Cancer Cells During Metastatic Niche Construction

Advances in Experimental Medicine and Biology - Systems Biology of Tumor Microenvironment ◽

10.1007/978-3-319-42023-3_7 ◽

2016 ◽

pp. 137-148

Author(s):

Ardeshir Kianercy ◽

Kenneth J. Pienta

Keyword(s):

Cancer Cells ◽

Positive Feedback ◽

Niche Construction ◽

Feedback Loops ◽

Metastatic Niche

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Interplay of positive and negative feedback loops governs robustness in multistable biological networks

10.1101/2021.10.08.463488 ◽

2021 ◽

Author(s):

Anish Hebbar ◽

Ankush Moger ◽

Kishore Hari ◽

Mohit Kumar Jolly

Keyword(s):

Negative Feedback ◽

Network Topology ◽

Positive Feedback ◽

Biological Networks ◽

Continuous Model ◽

Feedback Loops ◽

Large Networks ◽

Structural Robustness ◽

Negative Feedback Loops ◽

Positive And Negative Feedback

Biological networks are widely reported to be robust to both external and internal perturbations. However, the exact mechanisms and design principles that enable robustness are not yet fully understood. Here we investigated dynamic and structural robustness in biological networks with regards to phenotypic distribution and plasticity. We use two different approaches to simulate these networks: a computationally inexpensive, parameter-independent continuous model, and an ODE-based parameter-agnostic framework (RACIPE), both of which yield similar phenotypic distributions. Using perturbations to network topology and by varying network parameters, we show that multistable biological networks are structurally and dynamically more robust as compared to their randomized counterparts. These features of robustness are governed by an interplay of positive and negative feedback loops embedded in these networks. Using a combination of the number of negative and positive feedback loops weighted by their lengths and sign, we identified a metric that can explain the structural and dynamical robustness of these networks. This metric enabled us to compare networks across multiple sizes, and the network principles thus obtained can be used to identify fragilities in large networks without simulating their dynamics. Our analysis highlights a network topology based approach to quantify robustness in multistable biological networks.

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NFATc acts as a non-canonical phenotypic stability factor for a hybrid epithelial/mesenchymal phenotype

10.1101/2020.04.18.047803 ◽

2020 ◽

Cited By ~ 1

Author(s):

Ayalur Raghu Subbalakshmi ◽

Deepali Kundnani ◽

Kuheli Biswas ◽

Anandamohan Ghosh ◽

Samir M Hanash ◽

...

Keyword(s):

Phenotypic Plasticity ◽

Regulatory Networks ◽

Epithelial Mesenchymal Transition ◽

Therapy Resistance ◽

Stochastic Simulations ◽

Stability Factor ◽

Dependent Manner ◽

Phenotypic Stability ◽

Mesenchymal Transition ◽

Reversible Transitions

AbstractMetastasis remains the cause of over 90% of cancer-related deaths. Cells undergoing metastasis use phenotypic plasticity to adapt to their changing environmental conditions and avoid therapy and immune response. Reversible transitions between epithelial and mesenchymal phenotypes - Epithelial-Mesenchymal Transition (EMT) and its reverse Mesenchymal-Epithelial Transition (MET) - form a key axis of phenotypic plasticity during metastasis and therapy resistance. Recent studies have shown that the cells undergoing EMT/MET can attain one or more hybrid epithelial/mesenchymal (E/M) phenotypes, the process of which is termed as partial EMT/MET. Cells in hybrid E/M phenotype(s) can be more aggressive than those in either epithelial or mesenchymal state. Thus, it is crucial to identify the factors and regulatory networks enabling such hybrid E/M phenotypes. Here, employing an integrated computational-experimental approach, we show that the transcription factor NFATc can inhibit the process of complete EMT, thus stabilizing the hybrid E/M phenotype. It increases the range of parameters enabling the existence of a hybrid E/M phenotype, thus behaving as a phenotypic stability factor (PSF). However, unlike previously identified PSFs, it does not increase the mean residence time of the cells in hybrid E/M phenotypes, as shown by stochastic simulations; rather it enables the co-existence of epithelial, mesenchymal and hybrid E/M phenotypes and transitions among them. Clinical data suggests the effect of NFATc on patient survival in a tissue-specific or context-dependent manner. Together, our results indicate that NFATc behaves as a non-canonical phenotypic stability factor for a hybrid E/M phenotype.

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