| Chapter title |
Modeling of Interactions between Cancer Stem Cells and their Microenvironment: Predicting Clinical Response
|
|---|---|
| Chapter number | 16 |
| Book title |
Cancer Systems Biology
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7493-1_16 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7492-4, 978-1-4939-7493-1
|
| Authors |
Mary E. Sehl, Max S. Wicha, Sehl, Mary E., Wicha, Max S. |
| Abstract |
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. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 6 | 33% |
| Student > Ph. D. Student | 4 | 22% |
| Lecturer | 2 | 11% |
| Professor | 1 | 6% |
| Librarian | 1 | 6% |
| Other | 2 | 11% |
| Unknown | 2 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 4 | 22% |
| Medicine and Dentistry | 4 | 22% |
| Biochemistry, Genetics and Molecular Biology | 3 | 17% |
| Agricultural and Biological Sciences | 3 | 17% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 11% |
| Other | 0 | 0% |
| Unknown | 2 | 11% |