This week in MathOnco 181

Drug interactions, MRI tumor forecasting, neutral evolution, collateral sensitivity, game theory, and immune-tumor coevolution

“This week in Mathematical Oncology” — Sept. 30, 2021
> mathematical-oncology.org
From the editor:

This week’s edition includes papers on drug interactions, MRI tumor forecasting, neutral evolution, collateral sensitivity, game theory, and immune-tumor coevolution.

Enjoy!

Jeffrey West
jeffrey.west@moffitt.org

  1. Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance
    Erida Gjini, Kevin B Wood

  2. Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting
    Angela M. Jarrett, Anum S. Kazerouni, Chengyue Wu, John Virostko, …, Debra Patt, Boone Goodgame, Sarah Avery, Thomas E. Yankeelov

  3. Genome and metabolome: chance and necessity
    Emanuel Gonçalves & Christian Frezza

  4. Exact site frequency spectra of neutrally evolving tumors: A transition between power laws reveals a signature of cell viability
    Einar Bjarki Gunnarsson, Kevin Leder, Jasmine Foo

  5. Asymptotic analysis of a biphase tumor fluid flow: the weak coupling case
    Cristina Vaghi, Sebastien Benzekry, Clair Poignard

  6. Quantitative prediction of breast cancer resistant protein mediated drug-drug interactions using physiologically-based pharmacokinetic modeling
    Chester Costales, Jian Lin, Emi Kimoto, Shinji Yamazaki, James R. Gosset, A. David Rodrigues, Sarah Lazzaro, Mark A. West, Michael West, Manthena V. S. Varma

  7. Design principles of collateral sensitivity-based dosing strategies
    Linda B. S. Aulin, Apostolos Liakopoulos, Piet H. van der Graaf, Daniel E. Rozen, J. G. Coen van Hasselt

  8. Systems Biology at the giga-scale: large multi-scale models of complex, heterogeneous multicellular systems
    Arnau Montagud, Miguel Ponce de León, Alfonso Valencia

  9. Evolutionary Game Theory: Darwinian Dynamics and the G Function Approach
    Anuraag Bukkuri, Joel S. Brown

  10. Dynamic changes in epithelial cell packing during tissue morphogenesis
    Sandra B.Lemke, Celeste M. Nelson

  1. Julia for Biologists
    Elisabeth Roesch, Joe G. Greener, Adam L. MacLean, Huda Nassar, Christopher Rackauckas, Timothy E. Holy, Michael P.H. Stumpf

  2. Discrete and continuum models for the coevolutionary dynamics between CD8+ cytotoxic T lymphocytes and tumour cells
    Luís Almeida, Chloe Audebert, Emma Leschiera, Tommaso Lorenzi

  3. Cancer: More Than a Geneticist’s Pandora’s Box
    Kritika Saxena, Ayalur Raghu Subbalakshmi, Prakash Kulkarni, Mohit Kumar Jolly

  4. Tree balance indices: a comprehensive survey
    Mareike Fischer, Lina Herbst, Sophie Kersting, Luise Kühn, Kristina Wicke

  1. JupyterLab Desktop App now available!
    Jupyter Blog
    Mehmet Bektas: “JupyterLab App is the cross-platform standalone application distribution of JupyterLab. It is a self-contained desktop application which bundles a Python environment with several popular Python libraries ready to use in scientific computing and data science workflows.”

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Caption: The combined effects of mutational constraints, collateral effects (cross resistance or collateral sensitivity), and drug interactions shape the dynamics of multi-drug resistance. In our recent paper, we show that these processes can be integrated via a Price Equation whose terms encode statistical properties of resistance mutants, geometric features of the two-drug response surface in ancestral cells, and mutational constraints that limit the available pathways for sequential mutations. In this model, growth adaptation follows a type of weighted gradient dynamics where the underlying landscape is determined by the drug interaction, while the collateral effects and mutational pathways constrain motion on that landscape. To learn more, see our paper here.

Created by: Erida Gjini, Kevin Wood, Alexander Anderson

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