This week in MathOnco 229

Antifragility, extrachromosomal DNA, Kuznetsov growth dynamics, team medicine, and more.

“This week in Mathematical Oncology” — Oct. 6, 2022

> mathematical-oncology.org

From the editor:

Today we feature articles on antifragility, extrachromosomal DNA, Kuznetsov growth dynamics, team medicine, and more.

Enjoy,

Jeffrey West
jeffrey.west@moffitt.org

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“Think of the body as a self-maintaining factory; it is constantly regenerating itself down to every cell.”
— David B. Agus, The End of Illness

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1. The evolutionary dynamics of extrachromosomal DNA in human cancers
   Joshua T. Lange, John C. Rose, Celine Y. Chen, Yuriy Pichugin, …, Vineet Bafna, Anton G. Henssen, Benjamin Werner, Paul S. Mischel

2. Immune-checkpoint inhibitor therapy response evaluation using oncophysics-based mathematical models
   Mustafa Syed, Matthew Cagely, Prashant Dogra, Lauren Hollmer, Joseph D. Butner, Vittorio Cristini, Eugene J. Koay

3. Antifragile Control Systems: The Case of an Anti-Symmetric Network Model of the Tumor-Immune-Drug Interactions
   Cristian Axenie, Daria Kurz, Matteo Saveriano

4. Can the Kuznetsov Model Replicate and Predict Cancer Growth in Humans?
   Mohammad El Wajeh, Falco Jung, Dominik Bongartz, Chrysoula Dimitra Kappatou, Narmin Ghaffari Laleh, Alexander Mitsos & Jakob Nikolas Kather

5. Addressing Drug Resistance in Cancer: A Team Medicine Approach
   Prakash Kulkarni, Atish Mohanty, Supriyo Bhattacharya, Sharad Singhal, …,Danny Nguyen, Amartej Merla, Sudarsan V. Kollimuttathuillam, Tanyanika Phillips

6. Multiscale modeling of collective cell migration elucidates the mechanism underlying tumor–stromal interactions in different spatiotemporal scales
   Zarifeh Heidary, Shaghayegh Haghjooy Javanmard, Iman Izadi, Nasrin Zare & Jafar Ghaisari

1. Working With Convex Responses: Antifragility From Finance to Oncology
   Nassim Nicholas Taleb, Jeffrey West

2. Calibration of a Voronoi cell-based model for tumour growth using approximate Bayesian computation
   Xiaoyu Wang, Adrianne L. Jenner, Robert Salomone, Christopher Drovandi

3. Modeling Breast Cancer Proliferation, Drug Synergies, and Alternating Therapies
   Wei He, Diane M. Demas, Ayesha N. Shajahan-Haq, William T. Baumann

4. Cancer cells communicate with macrophages to prevent T cell activation during development of cell cycle therapy resistance
   Jason I. Griffiths, Patrick A. Cosgrove, Eric Medina Castaneda, Aritro Nath, …, Frederick R. Adler, Jeffrey T. Chang, Qamar J. Khan, Andrea H. Bild

5. Statistical inference of the rates of cell proliferation and phenotypic switching in cancer
   Einar Bjarki Gunnarsson, Jasmine Foo, Kevin Leder

6. Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables
   Alexander B. Brummer, Agata Xella, Ryan Woodall, Vikram Adhikarla, Heyrim Cho, Margarita B. Gutova, Christine E. Brown, Russell C. Rockne

7. Designing experimental conditions to use the Lotka-Volterra model to infer tumor cell line interaction types
   Heyrim Cho, Allison L. Lewis, Kathleen M. Storey and Helen M. Byrne

1. The Society of Mathematical Biology Annual Meeting 2022:
   A Participant’s Summary
   The Mathematical Oncology Blog
   Gosia Weh: “I strongly believe that a scientist should recognize the results of their research not as fully original, but as the evolution of many intellectual contributions that originate from exchanging ideas with others. This can only happen if one researcher can connect with others, and explains why a great amount of time was dedicated to mentoring lunches and poster sessions.“

The newsletter now has a dedicated homepage where we post the cover artwork for each issue. We encourage submissions that coincide with the release of a recent paper from your group. This week’s artwork:

Based on the paper: “IsoMaTrix: a framework to visualize the isoclines of matrix games and quantify uncertainty in structured populations ” in Bioinformatics

Artist: Jeffrey West

Caption: “IsoMaTrix is a software package that aids in the construction, analysis and visualization of three-strategy matrix games (MATLAB). IsoMaTrix.js is a light-weight version of the software built in javascript that requires no knowledge of programming to use.”

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