Purpose of Review
Adult stem cells play a key role in tissue regeneration and cancer. To translate findings from stem cell biology into clinics, we require a quantitative characterization of stem cell dynamics in vivo. This review explores how mathematical models can help to characterize stem cell behavior in health and disease.
Mathematical models significantly contribute to quantification of stem cell traits such as proliferation, self-renewal, and quiescence. They provide insights into the role of systemic and micro-environmental feedback loops during regeneration and cancer. Computer simulations allow linking stem cell properties to tumor composition, clinical course, and drug response. Therefore, models are helpful in personalizing treatments and predicting patient survival.
Mathematical models coupled with tools of parameter estimation and model selection provide quantitative insights into stem cell properties and their regulation. They help to understand experimentally inaccessible processes occurring in regeneration, aging, and cancer.
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This work was funded by research funding from the German Research Foundation DFG (Collaborative Research Center SFB 873, Maintenance and Differentiation of Stem Cells in Development and Disease).
Conflict of Interest
Thomas Stiehl and Anna Marciniak-Czochra declare that they have no conflict of interest.
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This article is part of the Topical Collection on Mathematical Models of Stem Cell Behavior
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Stiehl, T., Marciniak-Czochra, A. How to Characterize Stem Cells? Contributions from Mathematical Modeling. Curr Stem Cell Rep 5, 57–65 (2019). https://doi.org/10.1007/s40778-019-00155-0
- Cancer stem cell
- Mathematical model
- Tumor heterogeneity
- Clonal evolution
- Bone marrow transplantation
- Patient prognosis
- Differential equations