This week in MathOnco: 142
Mutability landscapes, CAR T Cell therapy, polyploidization, cancer screening, eco-evo stability, game theory, and more
“This week in Mathematical Oncology” — Newsletter
Dec. 10, 2020
From the editor:
Dear readers,
This week’s edition includes articles on mutability landscapes, CAR T Cell therapy, polyploidization, cancer screening, eco-evo stability, game theory, and more.
Thank you to those who commented on the new format & appearance of the newsletter! A special thank you to Maximilian Strobl (Moffitt/Oxford) who helped with the re-design of the banner images.
-Jeffrey West
Integrating transcriptomics and bulk time course data into a mathematical framework to describe and predict therapeutic resistance in cancer
Kaitlyn E Johnson, Grant R Howard, Daylin Morgan, Eric A Brenner, Andrea L Gardner, Russell E Durrett, William Mo, Aziz Al'Khafaji, Eduardo D Sontag, Angela M Jarrett, Thomas E Yankeelov, Amy BrockInference of mutability landscapes of tumors from single cell sequencing data
Viachaslau Tsyvina, Alex Zelikovsky, Sagi Snir, Pavel SkumsThe Most Logical Approach to Improve CAR T Cell Therapy
Seunghee Lee, Wilson W. WongComparing the Efficacy of Cancer Therapies between Subgroups in Basket Trials
Adam C. Palmer, Deborah Plana, Peter K. SorgerModeling the effect of immunotherapies on human castration-resistant prostate cancer
Roberta Coletti, Andrea Pugliese, Luca MarchettiCancer cells employ an evolutionarily conserved polyploidization program to resist therapy
KJ Pienta, EU Hammarlund, RH Austin, R Axelrod, JS Brown, SR AmendCancer Cell Foraging to Explain Bone-Specific Metastatic Progression
Mikaela M. Mallin, Kenneth J.Pienta, Sarah R. AmendComparative study between discrete and continuum models for the evolution of competing phenotype-structured cell populations in dynamical environments
Aleksandra Ardaševa, Alexander R. A. Anderson, Robert A. Gatenby, Helen M. Byrne, Philip K. Maini, Tommaso LorenziOptimal timing for cancer screening and adaptive surveillance using mathematical modeling
Kit Curtius, Anup Dewanji, William D. Hazelton, Joel H. Rubenstein and Georg E LuebeckOptimal control to reach eco-evolutionary stability in metastatic castrate-resistant prostate cancer
Jessica Cunningham, Frank Thuijsman, Ralf Peeters, Yannick Viossat, Joel Brown, Robert Gatenby, Kateřina Staňková
The contribution of evolutionary game theory to understanding and treating cancer
Benjamin Woelfl, Hedy te Rietmole, Monica Salvioli, Frank Thuijsman, Joel S Brown, Boudewijn Burgering, Katerina StankovaTowards decoding the coupled decision-making of metabolism and epithelial-mesenchymal transition in cancer
Dongya Jia, Jun Hyoung Park, Harsimran Kaur, Kwang Hwa Jung, Sukjin Yang, Shubham Tripathi, Madeline Galbraith, Youyuan Deng, Mohit Kumar Jolly, Benny Abraham Kaipparettu, Jose N. Onuchic, Herbert Levine
Evolutionary Therapy - Request for Application (RFA)
Anticancer Fund: Independent research fund focusing on cancer treatments
Knowledge about tumour evolutionary dynamics has been growing rapidly. However, there has been a limited translation of that knowledge into therapeutic trials. The most clinically advanced strategy is adaptive therapy. Adaptive therapy is a treatment strategy attempting to prolong response to treatment by delaying the emergence of resistance. The goal of adaptive therapy is to maintain a controllable stable tumour burden by allowing a significant population of treatment-sensitive cells to survive. The main principle of the intervention is to control the tumour and prolong survival by allowing on/off treatment periods based on a valid marker.
This RFA will accept clinical trials on adaptive therapy and any other evolutionarily informed strategy, as long as they meet all criteria (see eligibility criteria here).
Modeling Emergent Cellular Behavior in Cancer (Due TOMORROW, Dec. 11)
Virtual Innovation Lab
Hanna Dueck: "Recent large-scale single-cell atlasing efforts have led to rich catalogues of cell types within tumors, but use of these data to predict emergent aggregate behavior in cancer has lagged behind. This five-day innovation lab will bring together diverse research and clinical communities to generate creative strategies and new research collaborations aimed at improving understanding, prediction, and validation of dynamic cell-cell communication and emergent behavior of cell ensembles in cancerous tissues. This Innovation Lab is intended to bring together experts to develop a roadmap for the direction of this research area. It is anticipated that this Innovation Lab will lead to interdisciplinary teams poised to advance scientific questions related to dynamic cell-cell communication and emergent cellular behavior. In addition to research projects, participants will have the opportunity to contribute to a white paper aimed at shaping the direction of this developing research area. The event will be held online, and will take place on February 25-26 & March 1-2, 5."
The Cancer Code: A Revolutionary New Understanding of a Medical Mystery
Jason Fung: "In The Cancer Code, Dr. Jason Fung offers a revolutionary new understanding of this invasive, often fatal disease—what it is, how it manifests, and why it is so challenging to treat. In this rousing narrative, Dr. Fung identifies the medical community’s many missteps in cancer research—in particular, its focus on genetics, or what he terms the “seed” of cancer, at the expense of examining the “soil,” or the conditions under which cancer flourishes. Dr. Fung—whose groundbreaking work in the treatment of obesity and diabetes has won him international acclaim—suggests that the primary disease pathway of cancer is caused by the dysregulation of insulin. In fact, obesity and type 2 diabetes significantly increase an individual’s risk of cancer."
NEW: Understanding the Evolutionary Dynamics and Ecology of Cancer in Treatment Resistance
Guest Editor: David BasantaMathematical Models of Cellular Immunotherapies in Cancer
Guest Editors: V. Pérez-García, L. de Pillis, P. Altrock, R. RockneFrom Ecology to Cancer Biology and Back Again
Guest Editors: Fred Adler, Sarah Amend, Chris WhelanFrontiers in quantitative cancer modeling
Guest Editors: Mohit Kumar Jolly, Heiko Enderling
NEW: CDC Steven M. Teutsch Prevention Effectiveness Fellowship
NEW: Postdoc in Statistics & Mathematics for Personalized Breast Cancer Therapy (Alvaro Köhn-Luque)
PhD on Modelling Cell Life and Death (Dan Tennant/Fabian Spill)
Mathematical Modeling Expert in Oncology Translational Science (Boehringer Ingelheim)
Research Associate - Biostatistician (University of Manchester)
Research Fellow in Computational Systems Biology Cancer Research (Simon Mitchell)
Research Fellow in Laboratory and Computational Systems Biology Cancer Research (Simon Mitchell)
Postdoctoral Fellow in Cancer Resistance Modeling, Pfizer (Blerta Shtylla)
Principal Scientist – Oncology PK/PD Modelling (Boehringer Ingelheim)
Postdoctoral Research Position in Computational Immunology (Sylvain Cussat-Blanc)
Postdoc Position - TKI treatments in lung cancer (David Basanta)
Systems Biology Modeler Positions in Biopharma Consulting Company (Helen Moore)
Computational Approaches to Breast Cancer Evolution - Postdoc (Marc Ryser)
Math/statistical models of stem cell lineage dynamics and cancer genomics - Postdoc (Adam MacLean)
Postdoctoral Research Position in Computational Oncology (Tom Yankeelov)
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