This week in MathOnco 307

IMO Workshop 12, evolutionary theory, radiation therapy, tumor-immune, adaptive therapy, evolutionary double-bind

“This week in Mathematical Oncology” — Sep 19, 2024

> mathematical-oncology.org

From the editor:

This week’s edition of the math onco newsletter features papers in topics such as evolutionary theory, radiation therapy, tumor-immune, adaptive therapy, and one of my own on evolutionary double-binds.

Would you like to join us for IMO Workshop 12 at Moffitt from November 3-8, 2024? Scroll down to read Sandy’s announcement, or click this link to register.

Thanks,

Jeffrey West
jeffrey.west@moffitt.org

1. The evolutionary theory of cancer: challenges and potential solutions

   Lucie Laplane & Carlo C. Maley

2. Fractionated photoimmunotherapy stimulates an anti-tumour immune response: an integrated mathematical and in vitro study

   Mohammad U. Zahid, Matthew Waguespack, Rebecca C. Harman, Eric M. Kercher, Shubhanker Nath, Tayyaba Hasan, Imran Rizvi, Bryan Q. Spring, Heiko Enderling

3. Spatially fractionated GRID radiation potentiates immune-mediated tumor control

   Rebecca A. Bekker, Nina Obertopp, Gage Redler, José Penagaricano, Jimmy J. Caudell, Kosj Yamoah, Shari Pilon-Thomas, Eduardo G. Moros & Heiko Enderling

4. Predicting resistance and pseudoprogression: are minimalistic immunoediting mathematical models capable of forecasting checkpoint inhibitor treatment outcomes in lung cancer?
   Kevin Robert Scibilia, Pirmin Schlicke, Folker Schneller, Christina Kuttler

5. Mapping cellular interactions from spatially resolved transcriptomics data
   James Zhu, Yunguan Wang, Woo Yong Chang, Alicia Malewska, …, Neil Desai, Xinlei Wang, Yang Xie & Tao Wang

1. A novel combination therapy for ER+ breast cancer suppresses drug resistance via an evolutionary double-bind
   Rena Emond, Jeffrey West, Vince Grolmusz, Patrick Cosgrove, Aritro Nath, Alexander R. A. Anderson, Andrea H. Bild

2. Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A review
   Lingchao Mao, Hairong Wang, Leland S. Hu, Nhan L Tran, Peter D Canoll, Kristin R Swanson, Jing Li

3. On the design and stability of cancer adaptive therapy cycles: deterministic and stochastic models
   Yuri G. Vilela, Artur C. Fassoni, Armando G. M. Neves

1. IMO Workshop 12
   Registration deadline: September 30, 2024
   Sandy Anderson: “Just 2 weeks remaining for deluxe travel awards to attend the 12th Integrated Mathematical Oncology (IMO) workshop on Toxicity! Get your applications in ASAP - and more info on what these workshops are here: imoworkshop.org“

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: Systems modeling of oncogenic G-protein and GPCR signaling reveals unexpected differences in downstream pathway activation published in npj systems biology and applications.

Concept: Michael Trogdon and Ed Stites

Artist: Amy Cao, Salk Institute for Biological Studies

Caption: Uveal melanoma is a rare form of cancer.  This form of melanoma develops within the eye.  The molecular drivers of uveal melanoma are completely different than cutaneous melanoma; approximately 90% of uveal melanoma cases are driven by an oncogenic mutation in GNAQ or GNA11, whereas cutaneous melanoma is driven predominantly by oncogenic BRAF or NRAS mutations. In general, much less is known about uveal melanoma than about cutaneous melanoma.   In this study, we developed a mathematical model of the local GNAQ/GNA11 signaling network.  The model found multiple non-obvious but logical consequences of the available, limited, data.  A limited number of new experiments were able to confirm model predictions and thereby illuminate multiple new aspects of uveal melanoma biology.  This highlights the value of modeling for less-well characterized forms of cancer and less-well characterized biochemical networks.  The illustration portrays this general concept of inferring the unknown with a visual analogy; the image shows a poorly characterized landscape where only a few areas have been well defined (the colored, solid areas) and where the missing areas of the landscape (the black and white, wire mesh-like areas) have been inferred.  The bird is a MAGPIE (for Model-Assisted Generation of Predictions and Integration of Experimental data).

Visit the mathematical oncology page to view jobs, meetings, and special issues. We will post new additions here, but the full list can found at mathematical-oncology.org.

1. Jobs

• Assistant professor in Applied Mathematics, Department of Mathematics and Statistics, Université de Montréal

2. Conferences / Meetings

3. Special issues

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