This week in MathOnco 208

Adaptive therapy, reciprocal interactions, extrinsic drug resistance, barcoding, and more..

“This week in Mathematical Oncology” — May 5, 2022

> mathematical-oncology.org

From the editor:

Another exciting week for Math Onco! This week includes topics like adaptive therapy, reciprocal interactions, extrinsic drug resistance, barcoding, and more.

Jeffrey West
jeffrey.west@moffitt.org

1. Spatial structure impacts adaptive therapy by shaping intra-tumoral competition
   Maximilian A. R. Strobl, Jill Gallaher, Jeffrey West, Mark Robertson-Tessi, Philip K. Maini & Alexander R. A. Anderson

2. Algorithmic reconstruction of glioblastoma network complexity
   Abicumaran Uthamacumaran, Morgan Craig

3. Tumor cell malignancy: A complex trait built through reciprocal interactions between tumors and tissue-body system
   Jean Feunteun, Pauline Ostyn, Suzette Delaloge

4. Materials-driven approaches to understand extrinsic drug resistance in cancer
   Justin R. Pritchard, Michael J. Leeb, Shelly R. Peyton

5. From Fitting the Average to Fitting the Individual: A Cautionary Tale for Mathematical Modelers
   Michael C. Luo, Elpiniki Nikolopoulou, Jana L. Gevertz

6. Mathematical Modeling of Tumor and Cancer Stem Cells Treated with CAR-T Therapy and Inhibition of TGF-𝛽
   Ellen R. Swanson, Emek Köse, Elizabeth A. Zollinger & Samantha L. Elliott

7. Inferring ongoing cancer evolution from single tumour biopsies using synthetic supervised learning
   Tom W. Ouellette, Philip Awadalla

8. Assessing the impact of organ-specific lesion dynamics on survival in patients with recurrent urothelial carcinoma treated with atezolizumab or chemotherapy
   M. Kerioui, S. Desmée, F. Mercier, A. Lin, B. Wu, J. Y. Jin, X. Shen, C. Le Tourneau, R. Bruno, J. Guedj

9. Challenges of proving a causal role of somatic mutations in the aging process
   Irene Franco, Gwladys Revêchon, Maria Eriksson

1. Growth and adaptation mechanisms of tumour spheroids with time-dependent oxygen availability
   Ryan J Murphy, Gency Gunasingh, Nikolas K Haass, Matthew J Simpson

2. Building model prototypes from time-course data
   Alan Veliz-Cuba, Stephen Randal Voss, David Murrugarra

3. CellDrift: Inferring Perturbation Responses in Temporally-Sampled Single Cell Data
   Kang Jin, Daniel Schnell, Guangyuan Li, Nathan Salomonis, V. B. Surya Prasath, Rhonda Szczesniak, Bruce J. Aronow

4. An exploratory study on the role of the stiffness of breast cancer cells in their detachment from spheroids and migration in 3D collagen matrices

   Ghodeejah Higgins, Jessica E. Kim, Jacopo Ferruzzi, Tamer Abdalrahman, Thomas Franz, Muhammad H. Zaman

5. Barcoding and its application for visualizing ecological dynamics
   Vitul Agarwal, Colleen B. Mouw

1. Life With Longer Genetic Codes Seems Possible — but Less Likely

   Quanta Magazine
   "Life’s genetic code is based on sequences of nucleotide bases read as three-letter ‘words.’ A new study suggests that a code based on four-letter words is biophysically possible but poses challenges.”

2. 2022 PhysiCell workshop & hackathon
   ”PhysiCell is an open source agent-based framework for simulating cells as they live and interact in dynamical environments. It has been used extensively to study cancer biology, immunology, and other complex multicellular systems. Paul Macklin is running a virtual workshop and hackathon to teach PhysiCell July 24-30. Participants will learn to build agent-based models, integrate intracellular models in each cell agent, and visualize results. Sessions will also introduce a new modeling language to accelerate work. Morning tutorial sessions are available without participation limit, while up to 30 applicants will be accepted for a mentored hackathon. Targeted funding is available to increase diversity, equity, and inclusion. For best consideration, apply by May 31st at https://www.github.com/PhysiCell-Training/ws2022.”

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.

Caption: Adaptive therapy aims to leverage competition between drug-sensitive and resistant cells by adjusting treatment to maintain the tumor at a tolerable size, whilst preserving sensitive cells. This approach is being tested in trials but is not yet widely used as deeper understanding of cell-cell competition is required. In our recent paper, we used an agent-based model (written in HAL) to investigate how strongly, and with whom, resistant cells compete during continuous and adaptive therapy. This artwork combines snapshots from simulations of adaptive therapy under different parameterisations (varying rates of resistance costs and turnover) with a Muller plot (created using EvoFreq) illustrating the average neighbourhood composition around a resistant cells. Our work shows that the tumour’s spatial architecture is an important factor in adaptive therapy and provides insights into how adaptive therapy leverages both inter- and intra-specific competition to control resistance.

Created by: Maximilian Strobl, Jill Gallaher, Sandy Anderson & Jeffrey West

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