Literature DB >> 30654341

Towards control of cellular decision-making networks in the epithelial-to-mesenchymal transition.

Jorge Gómez Tejeda Zañudo1, M Tyler Guinn, Kevin Farquhar, Mariola Szenk, Steven N Steinway, Gábor Balázsi, Réka Albert.   

Abstract

We present the epithelial-to-mesenchymal transition (EMT) from two perspectives: experimental/technological and theoretical. We review the state of the current understanding of the regulatory networks that underlie EMT in three physiological contexts: embryonic development, wound healing, and metastasis. We describe the existing experimental systems and manipulations used to better understand the molecular participants and factors that influence EMT and metastasis. We review the mathematical models of the regulatory networks involved in EMT, with a particular emphasis on the network motifs (such as coupled feedback loops) that can generate intermediate hybrid states between the epithelial and mesenchymal states. Ultimately, the understanding gained about these networks should be translated into methods to control phenotypic outcomes, especially in the context of cancer therapeutic strategies. We present emerging theories of how to drive the dynamics of a network toward a desired dynamical attractor (e.g. an epithelial cell state) and emerging synthetic biology technologies to monitor and control the state of cells.

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Mesh:

Year:  2019        PMID: 30654341      PMCID: PMC6405305          DOI: 10.1088/1478-3975/aaffa1

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  14 in total

1.  Bidirectional interplay between physical and biological approaches on studying the epithelial-to-mesenchymal transition.

Authors:  Jianhua Xing
Journal:  Phys Biol       Date:  2020-02-28       Impact factor: 2.583

2.  Noise-reducing optogenetic negative-feedback gene circuits in human cells.

Authors:  Michael Tyler Guinn; Gábor Balázsi
Journal:  Nucleic Acids Res       Date:  2019-08-22       Impact factor: 16.971

3.  The identifiability of gene regulatory networks: the role of observation data.

Authors:  Xiao-Na Huang; Wen-Jia Shi; Zuo Zhou; Xue-Jun Zhang
Journal:  J Biol Phys       Date:  2022-01-06       Impact factor: 1.365

Review 4.  Gene-circuit therapy on the horizon: synthetic biology tools for engineered therapeutics.

Authors:  Rafał Krzysztoń; Yiming Wan; Julia Petreczky; Gábor Balázsi
Journal:  Acta Biochim Pol       Date:  2021-08-30       Impact factor: 2.149

5.  NETISCE: a network-based tool for cell fate reprogramming.

Authors:  Lauren Marazzi; Milan Shah; Shreedula Balakrishnan; Ananya Patil; Paola Vera-Licona
Journal:  NPJ Syst Biol Appl       Date:  2022-06-20

Review 6.  How Do Cells Adapt? Stories Told in Landscapes.

Authors:  Luca Agozzino; Gábor Balázsi; Jin Wang; Ken A Dill
Journal:  Annu Rev Chem Biomol Eng       Date:  2020-06-07       Impact factor: 11.059

7.  Immunofluorescence Image Feature Analysis and Phenotype Scoring Pipeline for Distinguishing Epithelial-Mesenchymal Transition.

Authors:  Shreyas U Hirway; Nadiah T Hassan; Michael Sofroniou; Christopher A Lemmon; Seth H Weinberg
Journal:  Microsc Microanal       Date:  2021-08       Impact factor: 4.127

Review 8.  Cell plasticity in cancer cell populations.

Authors:  Shensi Shen; Jean Clairambault
Journal:  F1000Res       Date:  2020-06-22

9.  Multiplexed Gene Expression Tuning with Orthogonal Synthetic Gene Circuits.

Authors:  Mariola Szenk; Terrence Yim; Gábor Balázsi
Journal:  ACS Synth Biol       Date:  2020-03-23       Impact factor: 5.110

Review 10.  In Silico Logical Modelling to Uncover Cooperative Interactions in Cancer.

Authors:  Gianluca Selvaggio; Claudine Chaouiya; Florence Janody
Journal:  Int J Mol Sci       Date:  2021-05-05       Impact factor: 5.923

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