4.6 Review

Phenotypic Plasticity and Cell Fate Decisions in Cancer: Insights from Dynamical Systems Theory

Journal

CANCERS
Volume 9, Issue 7, Pages -

Publisher

MDPI
DOI: 10.3390/cancers9070070

Keywords

cell fate decision; cancer attractors; gene network dynamics; EMT; therapy resistance; intrinsically disordered proteins

Categories

Funding

  1. Physics Frontiers Center National Science Foundation (NSF) [PHY-1427654]
  2. NSF [DMS-1361411, PHY-1605817]
  3. Cancer Prevention and Research Institute of Texas (CPRIT) [R1111]
  4. Keck Center for Interdisciplinary Bioscience Training of the Gulf Coast Consortia (CPRIT) [RP170593]
  5. Direct For Mathematical & Physical Scien
  6. Division Of Mathematical Sciences [1361411] Funding Source: National Science Foundation
  7. Division Of Physics
  8. Direct For Mathematical & Physical Scien [1427654] Funding Source: National Science Foundation
  9. Division Of Physics
  10. Direct For Mathematical & Physical Scien [1605817] Funding Source: National Science Foundation

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Waddington's epigenetic landscape, a famous metaphor in developmental biology, depicts how a stem cell progresses from an undifferentiated phenotype to a differentiated one. The concept of landscape in the context of dynamical systems theory represents a high-dimensional space, in which each cell phenotype is considered as an attractor that is determined by interactions between multiple molecular players, and is buffered against environmental fluctuations. In addition, biological noise is thought to play an important role during these cell-fate decisions and in fact controls transitions between different phenotypes. Here, we discuss the phenotypic transitions in cancer from a dynamical systems perspective and invoke the concept of cancer attractors-hidden stable states of the underlying regulatory network that are not occupied by normal cells. Phenotypic transitions in cancer occur at varying levels depending on the context. Using epithelial-to-mesenchymal transition (EMT), cancer stem-like properties, metabolic reprogramming and the emergence of therapy resistance as examples, we illustrate how phenotypic plasticity in cancer cells enables them to acquire hybrid phenotypes (such as hybrid epithelial/mesenchymal and hybrid metabolic phenotypes) that tend to be more aggressive and notoriously resilient to therapies such as chemotherapy and androgen-deprivation therapy. Furthermore, we highlight multiple factors that may give rise to phenotypic plasticity in cancer cells, such as (a) multi-stability or oscillatory behaviors governed by underlying regulatory networks involved in cell-fate decisions in cancer cells, and (b) network rewiring due to conformational dynamics of intrinsically disordered proteins (IDPs) that are highly enriched in cancer cells. We conclude by discussing why a therapeutic approach that promotes recanalization, i.e., the exit from cancer attractors and re-entry into normal attractors, is more likely to succeed rather than a conventional approach that targets individual molecules/pathways.

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