“This week in Mathematical Oncology” — October 19, 2023
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From the editor:
This week the newsletter contains articles on topics like digital twins, radiation therapy, evolvability, and more.
Enjoy,
Jeffrey West
jeffrey.west@moffitt.org
Is there something we missed?
Submit your recent paper or preprint here:
https://mathematical-oncology.org/newsletter
Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas
Anirban Chaudhuri, Graham Pash, David A. Hormuth II, Guillermo Lorenzo, Michael Kapteyn, Chengyue Wu, Ernesto A. B. F. Lima, Thomas E. Yankeelov, Karen WillcoxMathematical modeling of radiotherapy: impact of model selection on estimating minimum radiation dose for tumor control
Achyudhan R. Kutuva, Jimmy J. Caudell, Kosj Yamoah, Heiko Enderling, Mohammad U. ZahidThe contribution of evolvability to the eco-evolutionary dynamics of competing species
Anuraag Bukkuri, Kenneth J. Pienta, Sarah R. Amend, Robert H. Austin, Emma U. Hammarlund, Joel S. BrownDynamical hallmarks of cancer: Phenotypic switching in melanoma and epithelial-mesenchymal plasticity
Paras Jain, Maalavika Pillai, Atchuta Srinivas Duddu, Jason A. Somarelli, Yogesh Goyal, Mohit Kumar JollyMathematical Modeling Support for Lung Cancer Therapy—A Short Review
Jaroslaw SmiejaQian Yu, Susumu S. Kobayashi, Hiroshi Haeno
State-transition Modeling of Blood Transcriptome Predicts Disease Evolution and Treatment Response in Chronic Myeloid Leukemia (CML)
David E. Frankhouser, Russell C. Rockne, Lisa Uechi, Dandan Zhao, Sergio Branciamore, Denis O’Meally, Jihyun Izarriy, Lucy Ghoda, Haris Ali, Jeffery M. Trent, Stephen Forman, Yu-Hsuan Fu, Ya-Huei Kuo, Bin Zhang, Guido Marcucci
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: Agent-Based Modelling Reveals the Role of the Tumor Microenvironment on the Short-Term Success of Combination Temozolomide/Immune Checkpoint Blockade to Treat Glioblastoma published in The Journal of Pharmacology and Experimental Therapeutics
Artist: Jesse Morris Art (jessemorrisart.com; @jessemorrisart)
Caption: In our latest paper, we developed an agent-based model of glioblastoma treatment by immune checkpoint blockade to better understand the mechanisms of recent clinical trial failures of this immunotherapy. We integrated pharmacokinetic models of temozolomide and nivolumab to our glioblastoma growth model that accounts for the immune reaction to glioblastoma through adaptive cell signalling, including CD4+ and CD8+ T cells. Using imaging mass cytometry data of patient resections, we elucidated how factors such as localization of glioblastoma cells and CD8+ T cell infiltration impact treatment outcomes.
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