ArticleBMC bioinformatics2020
Multistability in the epithelial-mesenchymal transition network.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 42 citations in OpenAlex.
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- Assessing biological network dynamics: comparing numerical simulations with analytical decomposition of parameter space.NPJ systems biology and applications · 2023Article
- Robustness and reproducibility of simple and complex synthetic logic circuit designs using a DBTL loop.Synthetic biology (Oxford, England) · 2023Article
- Network motifs and hypermotifs in TGFβ-induced epithelial to mesenchymal transition and metastasis.Frontiers in systems biology · 2023Article
- Joint Realizability of Monotone Boolean Functions.Theoretical computer science · 2022Article
- Population Dynamics of Epithelial-Mesenchymal Heterogeneity in Cancer Cells.Biomolecules · 2022Article
- SLC6A14 Depletion Contributes to Amino Acid Starvation to Suppress EMT-Induced Metastasis in Gastric Cancer by Perturbing the PI3K/AKT/mTORC1 Pathway.BioMed research international · 2022Article
- Review
- Trichostatin A promotes esophageal squamous cell carcinoma cell migration and EMT through BRD4/ERK1/2-dependent pathway.Cancer medicine · 2021Article
- Rational design of complex phenotype via network models.PLoS computational biology · 2021Article
- Coupled Feedback Loops Involving PAGE4, EMT and Notch Signaling Can Give Rise to Non-genetic Heterogeneity in Prostate Cancer Cells.Entropy (Basel, Switzerland) · 2021Article
- Mapping parameter spaces of biological switches.PLoS computational biology · 2021Article
- Multi-Stability and Consequent Phenotypic Plasticity in AMPK-Akt Double Negative Feedback Loop in Cancer Cells.Journal of clinical medicine · 2021Article
- Comprehensive analysis of partial epithelial mesenchymal transition-related genes in hepatocellular carcinoma.Journal of cellular and molecular medicine · 2021Article
- Hybrid E/M Phenotype(s) and Stemness: A Mechanistic Connection Embedded in Network Topology.Journal of clinical medicine · 2020Article
- Multi-parameter exploration of dynamics of regulatory networks.Bio Systems · 2020Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThe transitions between epithelial (E) and mesenchymal (M) cell phenotypes are essential in many biological processes like tissue development and cancer metastasis. Previous studies, both modeling and experimental, suggested that in addition to E and M states, the network responsible for these phenotypes exhibits intermediate phenotypes between E and M states. The number and importance of such states is subject to intense discussion in the epithelial-mesenchymal transition (EMT) community.
resultsPrevious modeling efforts used traditional bifurcation analysis to explore the number of the steady states that correspond to E, M and intermediate states by varying one or two parameters at a time. Since the system has dozens of parameters that are largely unknown, it remains a challenging problem to fully describe the potential set of states and their relationship across all parameters. We use the computational tool DSGRN (Dynamic Signatures Generated by Regulatory Networks) to explore the intermediate states of an EMT model network by computing summaries of the dynamics across all of parameter space. We find that the only attractors in the system are equilibria, that E and M states dominate across parameter space, but that bistability and multistability are common. Even at extreme levels of some of the known inducers of the transition, there is a certain proportion of the parameter space at which an E or an M state co-exists with other stable steady states.
conclusionsOur results suggest that the multistability is broadly present in the EMT network across parameters and thus response of cells to signals may strongly depend on the particular cell line and genetic background.
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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.