ArticlePLoS computational biology2022
Network topology metrics explaining enrichment of hybrid epithelial/mesenchymal phenotypes in metastasis.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 21 citations in OpenAlex.
- Novel approaches to modulate CAR-T cell function by targeting the tumor microenvironment in ovarian cancer.Journal of ovarian research · 2026Review
- Network hypermotifs in biological systems: structure, dynamics, and functional implications.NPJ systems biology and applications · 2026Review
- Article
- HOXA10-TWIST2 antagonism drives partial epithelial-to-mesenchymal transition for embryo implantation.Cell death discovery · 2025Article
- Emergent dynamics of cellular decision making in multi-node mutually repressive regulatory networks.Journal of the Royal Society, Interface · 2025Article
- An integrative phenotype-structured partial differential equation model for the population dynamics of epithelial-mesenchymal transition.NPJ systems biology and applications · 2025Article
- Operating principles of interconnected feedback loops driving cell fate transitions.NPJ systems biology and applications · 2025Article
- Role of Ubiquitin-regulated EMT in Cancer Metastasis and Chemoresistance.International journal of biological sciences · 2025Review
- General relationship of local topologies, global dynamics, and bifurcation in cellular networks.NPJ systems biology and applications · 2024Article
- EpCAM-CD24+ circulating cells associated with poor prognosis in breast cancer patients.Scientific reports · 2024Article
- Robustness in phenotypic plasticity and heterogeneity patterns enabled by EMT networks.Biophysical journal · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epithelial to Mesenchymal Transition (EMT) and its reverse-Mesenchymal to Epithelial Transition (MET) are hallmarks of metastasis. Cancer cells use this reversible cellular programming to switch among Epithelial (E), Mesenchymal (M), and hybrid Epithelial/Mesenchymal (hybrid E/M) state(s) and seed tumors at distant sites. Hybrid E/M cells are often more aggressive and metastatic than the "pure" E and M cells. Thus, identifying mechanisms to inhibit hybrid E/M cells can be promising in curtailing metastasis. While multiple gene regulatory networks (GRNs) based mathematical models for EMT/MET have been developed recently, identifying topological signatures enriching hybrid E/M phenotypes remains to be done. Here, we investigate the dynamics of 13 different GRNs and report an interesting association between "hybridness" and the number of negative/positive feedback loops across the networks. While networks having more negative feedback loops favor hybrid phenotype(s), networks having more positive feedback loops (PFLs) or many HiLoops-specific combinations of PFLs, support terminal (E and M) phenotypes. We also establish a connection between "hybridness" and network-frustration by showing that hybrid phenotypes likely result from non-reinforcing interactions among network nodes (genes) and therefore tend to be more frustrated (less stable). Our analysis, thus, identifies network topology-based signatures that can give rise to, as well as prevent, the emergence of hybrid E/M phenotype in GRNs underlying EMP. Our results can have implications in terms of targeting specific interactions in GRNs as a potent way to restrict switching to the hybrid E/M phenotype(s) to curtail metastasis.
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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.