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Mathematical Models of Stem Cell Differentiation and Dedifferentiation

  • Alexandra JilkineEmail author
Mathematical Models of Stem Cell Behavior (M Kohandel, Section Editor)
  • 35 Downloads
Part of the following topical collections:
  1. Topical Collection on Mathematical Models of Stem Cell Behavior

Abstract

Purpose of Review

To maintain and repair adult tissues, a balance must be maintained between stem cell proliferation and generation of differentiated offspring. This review explores recent mathematical and computational models that address stem cell fate decisions in adult tissues in the context of normal tissue regulation and cancer development.

Recent Findings

Quantitative models suggest that upregulation of stem cell self-renewal has a crucial impact on the dynamics of differentiated cells and plays an important role in cancer progression. Assuming cancer stem cells are the primary cause of drug resistance, models have estimated how different treatments may influence the prognosis of the disease. Recent evidence of phenotype switching and plasticity in cancer cell populations complicates the cancer stem cell hypothesis of unidirectional differentiation.

Summary

Mathematical models of stem cell dynamics can make counterintuitive predictions about cancer initiation, metastasis, and treatment response. By challenging current paradigms, they can shape future research in stem cell biology.

Keywords

Stem cells Cell fate determination Tissue homeostasis Cancer stem cells Phenotypic plasticity Mathematical modeling 

Notes

Compliance with Ethical Standards

Conflict of Interest

Alexandra Jilkine declares that she has no conflict of interest.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

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Authors and Affiliations

  1. 1.Department of Applied and Computational Mathematics and StatisticsUniversity of Notre DameNotre DameUSA

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