This week in MathOnco 174
Adaptive therapy predictions, somatic evolution, multi-drug synergy, spheroid structure, and modeling the mechanism
“This week in Mathematical Oncology” — Newsletter
August 12, 2021
From the editor:
As summer winds down, the pace of publication seems to ramp up. This week’s issue is filled with exciting topics: Adaptive therapy predictions, somatic evolution, multi-drug synergy, spheroid structure, and modeling the mechanism. Enjoy,
- Jeffrey West
Predicting patient-specific response to adaptive therapy in metastatic castration-resistant prostate cancer using prostate-specific antigen dynamics
Renee Brady-Nicholls, Jingsong Zhang, Tian Zhang, Andrew Z. Wang, Robert Butler, Robert A. Gatenby, Heiko Enderling
Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis
Jacob G Scott, Geoffrey Sedor, Patrick Ellsworth, Jessica A Scarborough, Kamran A Ahmed, Daniel E Oliver, Steven A Eschrich, Michael W Kattan, Javier F Torres-Roca
The somatic molecular evolution of cancer: Mutation, selection, and epistasis
Krishna Dasari, Jason A. Somarelli, Sudhir Kumar, Jeffrey P. Townsend
A Spatial Quantitative Systems Pharmacology Platform spQSP-IO for Simulations of Tumor—Immune Interactions and Effects of Checkpoint Inhibitor Immunotherapy
Chang Gong, Alvaro Ruiz-Martinez, Holly Kimko, Aleksander S. Popel
PK/PD modeling analysis for dosing regimen selection of isatuximab as single agent and in combination therapy in patients with multiple myeloma
Kimiko Koiwai, Raouf El-Cheikh, Hoai-Thu Thai, Claire Brillac, …, Marie-Laure Risse, Helgi van de Velde, Dorothée Semiond, Laurent Nguyen
Evolutionary Dynamics of Treatment-Induced Resistance in Cancer Informs Understanding of Rapid Evolution in Natural Systems
Mariyah Pressley, Monica Salvioli, David B. Lewis, Christina L. Richards, Joel S. Brown, Kateřina Staňková
MuSyC is a consensus framework that unifies multi-drug synergy metrics for combinatorial drug discovery
David J. Wooten, Christian T. Meyer, Alexander L. R. Lubbock, Vito Quaranta, Carlos F. Lopez
Quantitative analysis of tumour spheroid structure
Alexander P Browning, Jesse A Sharp, Ryan J Murphy, Gency Gunasingh, Brodie Lawson, Kevin Burrage, Nikolas K Haass, Matthew J Simpson
Do mechanisms matter?
The Mathematical Oncology Blog
Fred Adler: “Adaptive therapy depends on three key assumptions: resistance is costly, resistant cells can be suppressed by competition with sensitive cells, and therapy reduces the population of sensitive cells (although Viossat & Noble show that the first of these assumptions is not essential). However, what happens when these assumptions are tested against a wider set of ecological backgrounds? We expanded on the original work by Zhang et al […] to investigate four extensions of a basic competition model: 1) competition with healthy cells, 2) inclusion of resource dynamics, 3) an immune response, and 4) an Allee effect. We tested how a comprehensive set of intermittent and adaptive therapies balance two types of treatment failure (the time when resistant cells exceed some threshold and the time when the total cell population exceeds a different threshold) and two costs: average cell population and total treatment burden.”
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: We use clinical data of intermittent, adaptive prostate cancer hormone therapy to simulate tumor growth and treatment response dynamics. With that, we can predict possible patient-specific response trajectories to subsequent treatment cycles and recommend treatment adaptations when necessary. Click here to read more.
NEW: Senior Quantitative Systems Pharmacologist (Pfizer Oncology, La Jolla, CA) - Open until filled (Contact Blerta Shtylla: Blerta.Shtylla@pfizer.com)
Evolutionary Medicine: A Special Issue
eLife is pleased to present a Special Issue to highlight recent advances in the growing and increasingly interdisciplinary field of evolutionary medicine.
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