Journal
MOLECULAR ONCOLOGY
Volume 11, Issue 7, Pages 739-754Publisher
WILEY
DOI: 10.1002/1878-0261.12084
Keywords
circulating tumor cells; collective cell migration; epithelial-mesenchymal transition; hybrid epithelial/mesenchymal; mathematical modeling; stemness
Categories
Funding
- National Science Foundation (NSF) Center for Theoretical Biological Physics [NSF PHY-1427654, NSF PHY-1605817, NSF DMS-1361411]
- CPRIT (Cancer Prevention and Research Institute of Texas) Scholar in Cancer Research of the State of Texas at Rice University
- Rubenstein Family Foundation
- Canary Foundation
- Duke Cancer Institute
- Duke Genitourinary Oncology Laboratory
- Department of Orthopaedics
- Triangle Center for Evolutionary Medicine (TriCEM)
- Gulf Coast Consortia on the Computational Cancer Biology Training Program (CPRIT) [RP170593]
- Direct For Mathematical & Physical Scien
- Division Of Physics [1605817] Funding Source: National Science Foundation
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Phenotypic plasticity, the ability of cells to reversibly alter their phenotypes in response to signals, presents a significant clinical challenge to treating solid tumors. Tumor cells utilize phenotypic plasticity to evade therapies, metastasize, and colonize distant organs. As a result, phenotypic plasticity can accelerate tumor progression. A well-studied example of phenotypic plasticity is the bidirectional conversions among epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M) phenotype(s). These conversions can alter a repertoire of cellular traits associated with multiple hallmarks of cancer, such as metabolism, immune evasion, invasion, and metastasis. To tackle the complexity and heterogeneity of these transitions, mathematical models have been developed that seek to capture the experimentally verified molecular mechanisms and act as 'hypothesis-generating machines'. Here, we discuss how these quantitative mathematical models have helped us explain existing experimental data, guided further experiments, and provided an improved conceptual framework for understanding how multiple intracellular and extracellular signals can drive E/M plasticity at both the single-cell and population levels. We also discuss the implications of this plasticity in driving multiple aggressive facets of tumor progression.
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