#MathOnco Issue 124: tumor-immune interactions, immuno-oncology models, evolution of resistance, AI, and personalized therapy.
This week in
Math Oncology
July 23, 2020 ~ Issue 124
From the editor
Dear newsletter readers,
Today's issue includes publications on tumor-immune interactions, immuno-oncology models, evolution of resistance, AI, and personalized therapy.
Enjoy,
-Jeffrey West
#MathOnco Publications
Modeling Osteocyte Network Formation: Healthy and Cancerous Environments
Authors: Jake P. Taylor-King, Pascal R. Buenzli, S. Jon Chapman, Conor C. Lynch, David Basanta
Parameterization of mechanistic models from qualitative data using an efficient optimal scaling approach
Authors: Leonard Schmiester, Daniel Weindl, Jan Hasenauer
A Tumor-Immune Interaction Model for Hepatocellular Carcinoma based on measured Lymphocyte Counts in Patients undergoing Radiotherapy
Authors: Wonmo Sung, Clemens Grassberger, Aimee Louise McNamara, Lucas Basler, Stefanie Ehrbar, Stephanie Tanadini-Lang, Theodore S. Hong, Harald Paganetti
Quantitative Translation in Immuno‐Oncology Research and Development
Authors: Dean Bottino, Rachael Liu, Hojjat Bazzazi, Karthik Venkatakrishnan
The Detection of Dynamical Organization in Cancer Evolution Models
Authors: Laura Sani, Gianluca D’Addese, Alex Graudenzi, Marco Villani
Exploiting evolutionary trade-offs for posttreatment management of drug-resistant populations
Authors: Sergey V. Melnikov, David L. Stevens, Xian Fu, Hui Si Kwok, Jin-Tao Zhang, Yue Shen, Jeffery Sabina, Kevin Lee, Harry Lee, Dieter Söll
Modelling Artificial Immune – Tumor Ecosystem Interaction During Radiation Therapy Using a Perceptron – Based Antigen Pattern Recognition
Authors: Stephan Scheidegger, Alexander Mikos, Harold Fellermann
The National Lung Matrix Trial of personalized therapy in lung cancer
Authors: Gary Middleton, Peter Fletcher, Sanjay Popat, Joshua Savage, ..., Thomas B. K. Watkins, Emilia Lim, Charles Swanton, Lucinda Billingham
Quantitative Systems Pharmacology approaches for Immuno‐oncology: adding virtual patients to the development paradigm
Authors: Vijayalakshmi Chelliah, Georgia Lazarou, Sumit Bhatnagar, John P. Gibbs, ..., Tomoki Yoneyama, Andy Z.X. Zhu, Piet H. van der Graaf, Andrzej M. Kierzek
Modeling collaterally sensitive drug cycles
Shaping heterogeneity to allow adaptive therapy
Nara Yoon, The Mathematical Oncology Blog
"Despite major strides in the treatment of cancer, the development of drug resistance remains a major hurdle. One strategy which has been proposed to address this is the sequential application of drug therapies where resistance to one drug induces sensitivity to another drug, a concept called collateral sensitivity. Particularly, there is utility in a drug sequence which completes a cycle of such relationships."
Virtual Seminars
1. Moffitt's Integrated Mathematical Oncology Dept. Series
Mathematical Oncology Series
Next talk: Dr. Elsa Hansen (Pennsylvania State University)
"Ecological considerations of trial design to test competitive suppression of resistance"
Aug. 6, 2020 at 12:00pm EST
2. Computational modelling to study cancer biology and treatments
"This virtual workshop focuses on the techniques and applications of computational modelling approaches in cancer biology."
Speakers:
- Morgan Craig (Université de Montréal)
- Adrianne Jenner, (Université de Montréal)
- Paul Macklin (Indiana University)
- Randy Heiland (Indiana University)
Pantea Poolavand (University of Sydney)
Thu, August 13, 2020 12:30pm – 4:30pm
3. Mathematical and Computational Biology Seminar Series:
Bioinformatics, Computational Biology, General Mathematics
Next talk: Santiago Schnell (University of Michigan)
"Developing models for the accurate measurement of enzyme kinetic parameters"
July 27, 2020 at 11:00am EST
#MathOnco - Book of the month
The Cheating Cell
Athena Aktipis: "When we think of the forces driving cancer, we don’t necessarily think of evolution. But evolution and cancer are closely linked, for the historical processes that created life also created cancer. The Cheating Cell delves into this extraordinary relationship, and shows that by understanding cancer’s evolutionary origins, researchers can come up with more effective, revolutionary treatments."
Jobs
Postdoctoral Research Position in Computational Immunology (Sylvain Cussat-Blanc)
Postdoc Position - TKI treatments in lung cancer (David Basanta)
Research Associate, Postdoc, and Research Faculty positions – Mathematical Oncology (Russ Rockne)
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)
Do you see something we missed? Reply to this email to send us an idea for next week's issue.
The #MathOnco newsletter is maintained by Jeffrey West.
If you were forwarded this email, subscribe for free here to get it delivered every week.