This week in MathOnco 177

Contact inhibition, EMT-immune dynamics, multistep growth models, Allee effect, mutation frequency, anti-angiogenic therapy

“This week in Mathematical Oncology” — Newsletter
> mathematical-oncology.org

September 2, 2021

From the editor:
> jeffrey.west@moffitt.org


Hello,

This week’s edition includes papers on contact inhibition, EMT-immune dynamics, multistep growth models, Allee effect, mutation frequency, anti-angiogenic therapy and more. Enjoy!

- Jeffrey West

1. Modeling the effects of EMT-immune dynamics on carcinoma disease progression
   Daniel R. Bergman, Matthew K. Karikomi, Min Yu, Qing Nie & Adam L. MacLean

2. Rates and patterns of clonal oncogenic mutations in the normal human brain
   Javier Ganz, Eduardo A Maury, Basheer Becerra, Sara Bizzotto, …, Zinan Zhou, Keith L Ligon, Eunjung Alice Lee, Christopher A Walsh

3. Prediction of Metastatic Patterns in Bladder Cancer: Spatiotemporal Progression and Development of a Novel, Web-based Platform for Clinical Utility
   Jeremy Mason, Zaki Hasnain, Gus Miranda, Karanvir Gill, Hooman Djaladat, Mihir Desai, Paul K. Newton, Inderbir S. Gill, Peter Kuhn

4. On multistep tumor growth models of fractional variable-order
   Carlos A. Valentim, José A. Rabi, Sergio A. David, José A. Tenreiro Machado

5. Unpacking the Allee effect: determining individual-level mechanisms that drive global population dynamics
   Nabil T. Fadai, Stuart T. Johnston, Matthew J. Simpson

6. Accurate and efficient discretizations for stochastic models providing near agent-based spatial resolution at low computational cost
   Nabil T. Fadai, Ruth E. Baker, Matthew J. Simpson

7. Optimal control of cytotoxic and antiangiogenic therapies on prostate cancer growth
   Pierluigi Colli, Hector Gomez, Guillermo Lorenzo, Gabriela Marinoschi, Alessandro Reali, Elisabetta Rocca

8. Extreme value theory as a framework for understanding mutation frequency distribution in cancer genomes
   Natsuki Tokutomi, Kenta Nakai, Sumio Sugano

1. Local contact inhibition leads to universal principles of cell population growth
   Gregory J. Kimmel, Jeffrey West, Mehdi Damaghi, Alexander R. A. Anderson, Philipp M. Altrock

2. Multiscale modeling of tumor adaption and invasion following anti-angiogenic therapy
   Colin G. Cess, Stacey D. Finley

1. Modeling the effects of EMT-immune dynamics
   The Mathematical Oncology Blog
   Daniel Bergman: “This paper started with the simple observation that two important processes in tumor biology both involved a single protein. Transforming growth factor beta (TGF-β) regulates the immune system and drives the epithelial-to-mesenchymal transition (EMT)2. Recent work showed that mesenchymal cells interacted differently with the immune system than their epithelial counterparts, adding a layer onto these interactions. When the decreased proliferation potential of mesenchymal cells is also accounted for, a natural tension is created between the benefits to the tumor of more evasive mesenchymal cells and more proliferative epithelial cells. We wanted to understand these tradeoffs and see if we could identify potential ways to exploit them for therapeutic purposes.”

The newsletter now has a dedicated homepage (thisweekmathonco.substack.com), which allows us to post cover artwork for each issue. We encourage submissions that coincide with the release of a recent paper from your group.

Caption: The size of a cell’s local interaction neighborhood leads to emergent patterns via contact inhibition. Based on our recent preprint, this cover artwork plays out two cell types. Two types of gray cells can either divide up/down or left/right (interaction neighborhood of size 2). In contrast, red cells can divide up/down/left/right/diagonal (neighborhood size of 8). Red cells change from red to blue over time.

Created by: Jeffrey West (@mathoncbro)

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