This week in MathOnco 215

Glioblastoma, heterogeneity inference, competitive release, fitness seascapes, and cancer progression

“This week in Mathematical Oncology” — June 23, 2022

> mathematical-oncology.org

From the editor:

Today we feature models on glioblastoma, heterogeneity inference, competitive release, fitness seascapes, cancer progression, and more. Enjoy,

Jeffrey West
jeffrey.west@moffitt.org

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"The discoveries of science, the works of art are explorations — more, are explosions, of a hidden likeness. The discoverer or the artist presents in them two aspects of nature and fuses them into one. This is the act of creation, in which an original thought is born, and it is the same act in original science and original art."
- J. Bronowski

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1. Agent-based computational modeling of glioblastoma predicts that stromal density is central to oncolytic virus efficacy
   Adrianne L. Jenner, Munisha Smalley, David Goldman, William F. Goins, Charles S. Cobbs, Ralph B. Puchalski, E. Antonio Chiocca, Sean Lawler, Paul Macklin, Aaron Goldman, Morgan Craig

2. T cell therapy against cancer: a predictive diffuse-interface mathematical model informed by pre-clinical studies
   G. Pozzi, B. Grammatica, L. Chaabane, M. Catucci, A. Mondino, P. Zunino, P. Ciarletta

3. Comparing the effects of linear and one-term Ogden elasticity in a model of glioblastoma invasion
   Meghan E. Rhodes, Thomas Hillen, Vakhtang Putkaradze

4. Comparison of cell state models derived from single-cell RNA sequencing data: graph versus multi-dimensional space
   Heyrim Cho, Ya-Huei Kuo, Russell C. Rockne

5. Modelling the effect of vascular status on tumour evolution and outcome after thermal therapy
   Jesús J. Bosque, Gabriel F. Calvo, María Cruz Navarro

6. Quantitative models for the inference of intratumor heterogeneity
   Tom van den Bosch, Louis Vermeulen, Daniël M. Miedema

1. Stochastic competitive release and adaptive chemotherapy
   Jiyeon Park, Paul K Newton

2. The conditional defector strategies can violate the most crucial supporting mechanisms of cooperation
   Ahmed Ibrahim

3. Minimal frustration underlies the usefulness of incomplete and inexact regulatory network models in biology
   Shubham Tripathi, David A. Kessler, Herbert Levine

4. Uncovering potential interventions for pancreatic cancer patients via mathematical modeling
   Daniel Plaugher, Boris Aguilar, David Murrugarra

5. Fitness seascapes facilitate the prediction of therapy resistance under time-varying selection
   Eshan S King, Julia Pelesko, Jeff A Maltas, Steph J Owen, Emily Dolson, Jacob G Scott

6. Cancers adapt to their mutational load by buffering protein misfolding stress
   Susanne Tilk, Judith Frydman, Christina Curtis, Dmitri Petrov

7. Computational Image Analysis Techniques, Programming Languages and Software Platforms Used in Cancer Research: A Scoping Review
   Youssef Arafat, Constantino-Carlos Reyes Aldasoro

8. A Conservative Approach for Describing Cancer Progression
   Nicolò Rossi, Nicola Gigante, Nicola Vitacolonna, Carla Piazza

1. Myeloid-derived suppressor cell dynamics control outcomes in the metastatic niche
   The Mathematical Oncology Blog
   Jesse Kreger: “Myeloid-derived suppressor cells (MDSCs) may be the "Most Important Cell You Have Never Heard Of"1. MDSCs are the ultimate sidekick to cancer cells in the tumor environment. When tumors grow, and importantly when they metastasize and spread to other parts of the body, they recruit their potently immunosuppressive MDSC friends to come hang out and shield the tumor cells from the anti-tumor natural killer (NK) and cytotoxic T (CTL) populations2. This greatly suppresses the anti-tumor populations from doing their job and defeating the tumor.”

2. How to Write Software With Mathematical Perfection
   QuantaMagazine
   Sheon Han: “Leslie Lamport may not be a household name, but he’s behind a few of them for computer scientists: the typesetting program LaTeX and the work that made cloud infrastructure at Google and Amazon possible. He’s also brought more attention to a handful of problems, giving them distinctive names like the bakery algorithm and the Byzantine Generals Problem. This is no accident. The 81-year-old computer scientist is unusually thoughtful about how people use and think about software.”

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: “Glioblastoma is the most common adult brain tumour. Its aggressive nature makes it difficult to treat successfully. In our study, we used an ex vivo tumour model developed from human glioblastoma tissue to evaluate a new treatment modality (oncolytic virus) under clinical investigation. We then used this tumour model to develop a computational model of glioblastoma dynamics that accounts for cellular interactions within the tumour. Our integrated modelling strategy can be applied to suggest mechanisms of therapeutic responses for central nervous system cancers and to facilitate the successful translation of new therapies into the clinic.“

Created by: Jesse Morris (@JesseMorrisArt): www.jessemorrisart.com

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