This week in MathOnco 228
IMO X, tumor glycolysis, fixation & fitness, metastasis, phenotypic heterogeneity, and antifragility
“This week in Mathematical Oncology” — Sept. 29, 2022
> mathematical-oncology.org
From the editor:
Today we feature articles on tumor glycolysis, fixation & fitness, metastasis, phenotypic heterogeneity, and antifragility.
In other exciting news, the IMO Workshop is happening again this year. Please consider joining us for the 10th annual workshop. This year’s theme is “Cancer Communities.” Learn more & register at imoworkshop.org.
Enjoy,
Jeffrey West
jeffrey.west@moffitt.org
“Doing what has never been done before is intellectually seductive, whether or not we deem it practical.”
— N. D. Tyson
A simulation of parental and glycolytic tumor phenotype competition predicts observed responses to pH changes and increased glycolysis after anti-VEGF therapy
Frederika Rentzeperis, Naomi Miller, Arig Ibrahim-Hashim, Robert J. Gillies, Robert A. Gatenby, Dorothy WallaceSuppressors of fixation can increase average fitness beyond amplifiers of selection
Nikhil Sharma, Arne TraulsenInferring the initiation and development of myeloproliferative neoplasms
Gurvan Hermange, Alicia Rakotonirainy, Mahmoud Bentriou, Amandine Tisserand, …, Christophe Marzac, William Vainchenker, Isabelle Plo, Paul-Henry CournèdeInterdisciplinary approaches to metastasis
Stephen W. Smye, Robert A. GatenbySpatial interplay of tissue hypoxia and T-cell regulation in ductal carcinoma in situ
Faranak Sobhani, Sathya Muralidhar, Azam Hamidinekoo, Allison H. Hall, Lorraine M. King, Jeffrey R. Marks, Carlo Maley, Hugo M. Horlings, E. Shelley Hwang, Yinyin YuanSpatio-temporal modelling of phenotypic heterogeneity in tumour tissues and its impact on radiotherapy treatment
Giulia L. Celora, Helen M. Byrne, P. G. Kevrekidis
Decomposing spatial heterogeneity of cell trajectories with Paella
Wenpin Hou, Zhicheng JiA mathematical framework for evo-devo dynamics
Mauricio González-ForeroConfronting population models with experimental microcosm data: from trajectory matching to state-space models
Benjamin Rosenbaum, Emanuel A. FronhoferAntifragile Control Systems: The Case of An Anti-Symmetric Network Model of the Tumor–Immune–Drug Interactions
Cristian Axenie, Daria Kurz, Matteo SaverianoMathematical modelling of the dynamics of image-informed tumor habitats in a murine model of glioma
Kalina P. Slavkova, Sahil H. Patel, Zachary Cacini, Anum S. Kazerouni, Andrea Gardner, Thomas E. Yankeelov, David A. Hormuth, IIDesigning experimental conditions to use the Lotka-Volterra model to infer tumor cell line interaction types
Heyrim Cho, Allison L. Lewis, Kathleen M. Storey, Helen M. ByrneBayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma Growth
Baoshan Liang, Jingye Tan, Luke Lozenski, David A. Hormuth II, Thomas E. Yankeelov, Umberto Villa, Danial Faghihi
Tricks for maintaining your CV/resume with Google Docs: easy to edit, immediately published
Jeanelle Ackerman
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: “Circulating tumor DNA to guide rechallenge with panitumumab in metastatic colorectal cancer: the phase 2 CHRONOS trial” in Nature Medicine
Artist: Francesca Borgia
Caption: “In the CHRONOS clinical trial we integrated liquid biopsy for circulating tumor DNA (ctDNA) detection into real-time therapeutic decision-making for metastatic colorectal cancer. In this artwork it is metaphorically expressed how, with the passage of time, the mutational state of the tumor can change through a process of Darwinian evolution taking place under the pharmacological pressure of the therapies previously received by the patient. It is therefore essential to understand this clock of tumor evolution and liquid biopsy, by evaluating shedding of tumor DNA molecules in the blood. This allows to timely assess the genetic make-up of the tumor at the actual moment of starting a targeted treatment and allows to achieve best outcomes.”
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