ArticleNPJ systems biology and applications2020
Identifying inhibitors of epithelial-mesenchymal plasticity using a network topology-based approach.
Article in NPJ systems biology and applications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed, 90 citations in OpenAlex.
- Modulation of Network Plasticity Opens Novel Therapeutic Possibilities in Cancer, Diabetes, and Neurodegeneration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- A computational approach for perturbation-induced EMT transitions.NPJ systems biology and applications · 2025Article
- Quantitative measurement of phenotype dynamics during cancer drug resistance evolution using genetic barcoding.Nature communications · 2025Article
- An integrative phenotype-structured partial differential equation model for the population dynamics of epithelial-mesenchymal transition.NPJ systems biology and applications · 2025Article
- Multistability and predominant hybrid phenotypes in a four node mutually repressive network of Th1/Th2/Th17/Treg differentiation.NPJ systems biology and applications · 2024Article
- Gene regulatory network topology governs resistance and treatment escape in glioma stem-like cells.Science advances · 2024Article
- Cancer spreading patterns based on epithelial-mesenchymal plasticity.Frontiers in cell and developmental biology · 2024Article
- Theoretical and computational tools to model multistable gene regulatory networks.Reports on progress in physics. Physical Society (Great Britain) · 2023Review
- Assessing biological network dynamics: comparing numerical simulations with analytical decomposition of parameter space.NPJ systems biology and applications · 2023Article
- Dynamics of Epithelial-Mesenchymal Plasticity: What Have Single-Cell Investigations Elucidated So Far?ACS omega · 2023Review
- Spatiotemporal Patterning Enabled by Gene Regulatory Networks.ACS omega · 2023Article
- Network motifs and hypermotifs in TGFβ-induced epithelial to mesenchymal transition and metastasis.Frontiers in systems biology · 2023Article
- Network topology metrics explaining enrichment of hybrid epithelial/mesenchymal phenotypes in metastasis.PLoS computational biology · 2022Article
- Article
- Robustness in phenotypic plasticity and heterogeneity patterns enabled by EMT networks.Biophysical journal · 2022Article
- Classical epithelial-mesenchymal transition (EMT) and alternative cell death process-driven blebbishield metastatic-witch (BMW) pathways to cancer metastasis.Signal transduction and targeted therapy · 2022Review
- Emergent dynamics of a three-node regulatory network explain phenotypic switching and heterogeneity: a case study of Th1/Th2/Th17 cell differentiation.Molecular biology of the cell · 2022Article
- Roadmap on plasticity and epigenetics in cancer.Physical biology · 2022Review
- Intrinsically disordered proteins: Ensembles at the limits of Anfinsen's dogma.Biophysics reviews · 2022Review
- Emerging roles of epithelial-mesenchymal plasticity in invasion-metastasis cascade and therapy resistance.Cancer metastasis reviews · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metastasis is the cause of over 90% of cancer-related deaths. Cancer cells undergoing metastasis can 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 modelling frameworks: a discrete, parameter-independent framework (Boolean) and a continuous, parameter-agnostic modelling 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 to exhibit phenotypic plasticity correlates positively with the number of positive feedback loops in a given network. These results pave a way toward 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.