Modeling of Interactions between Cancer Stem Cells and their Microenvironment: Predicting Clinical Response

  • Mary E. Sehl
  • Max S. Wicha
Part of the Methods in Molecular Biology book series (MIMB, volume 1711)


Mathematical models of cancer stem cells are useful in translational cancer research for facilitating the understanding of tumor growth dynamics and for predicting treatment response and resistance to combined targeted therapies. In this chapter, we describe appealing aspects of different methods used in mathematical oncology and discuss compelling questions in oncology that can be addressed with these modeling techniques. We describe a simplified version of a model of the breast cancer stem cell niche, illustrate the visualization of the model, and apply stochastic simulation to generate full distributions and average trajectories of cell type populations over time. We further discuss the advent of single-cell data in studying cancer stem cell heterogeneity and how these data can be integrated with modeling to advance understanding of the dynamics of invasive and proliferative populations during cancer progression and response to therapy.

Key words

Breast cancer Cancer stem cell Mathematical model Optimal therapy design 



Thanks are given to Jill Granger for manuscript review and editing. This work was supported by grants RO1 CA101860 and R35 CA129765, NIH/NCATS UCLA CTSI Grant KL2TR000122, and by the Breast Cancer Research Foundation


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Copyright information

© Springer Science+Business Media LLC 2018

Authors and Affiliations

  1. 1.Division of Hematology-Oncology, Department of Medicine, David Geffen School of MedicineUniversity of CaliforniaLos AngelesUSA
  2. 2.Department of Biomathematics, David Geffen School of MedicineUniversity of CaliforniaLos AngelesUSA
  3. 3.Department of Internal MedicineUniversity of MichiganAnn ArborUSA

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