This week in MathOnco 309

Inverse problems, game theory, somatic evolution, combination therapy, and lineage tracing.

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

> mathematical-oncology.org

From the editor:

Greetings from Toronto, where I’ve been enjoying a fun week of math oncology & eco-evo!

Today’s issue contains articles on topics like inverse problems, game theory, somatic evolution, combination therapy, and lineage tracing.

Enjoy,

Jeffrey West
jeffrey.west@moffitt.org

1. A New Perspective on Tumor Progression: Evolution via Selection for Function
   Frédéric Thomas, James Degregori, Andriy Marusyk, Antoine M Dujon, Beata Ujvari, Jean-Pascal Capp, Robert Gatenby, Aurora M Nedelcu

2. Mathematical Analysis of a Model-Constrained Inverse Problem For the Reconstruction of Early States of Prostate Cancer Growth
   Elena Beretta, Cecilia Cavaterra, Matteo Fornoni, Guillermo Lorenzo, Elisabetta Rocca

3. Evolutionary Game Dynamics with Environmental Feedback in a Network with Two Communities
   Katherine Betz, Feng Fu & Naoki Masuda

4. Defining heritability, plasticity, and transition dynamics of cellular phenotypes in somatic evolution
   Joshua S. Schiffman, Andrew R. D’Avino, Tamara Prieto, Yakun Pang, Yilin Fan, Srinivas Rajagopalan, Catherine Potenski, Toshiro Hara, Mario L. Suvà, Charles Gawad & Dan A. Landau

5. Forecasting and Predicting Stochastic Agent-Based Model Data with Biologically-Informed Neural Networks
   John T. Nardini

6. The effect of tumor composition on the success of adaptive therapy: The case of metastatic Castrate-Resistant Prostate Cancer
   Monica Salvioli, Len Vandelaer, Esther Baena, Katharina Schneider, Rachel Cavill, Kateřina Staňková

7. Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8+ T cells
   Kevin Wang, Paulina Coutifaris, David Brocks, …, Michael D. Farwell, Ramin S. Herati, Alexander C. Huang

1. Mechanistic modeling of cell viability assays with in silico lineage tracing
   Arnab Mutsuddy, Jonah R. Huggins, Aurore Amrit, Cemal Erdem, Jon C. Calhoun, Marc R. Birtwistle

2. Integrating Kolmogorov-Arnold Networks with Ordinary Differential Equations for Efficient, Interpretable and Robust Deep Learning: A Case Study in the Epidemiology of Infectious Diseases
   Kexin Ma, Xu Lu, Nicola Luigi Bragazzi, Biao Tang

3. Combined Stochastic Models for the Evaluation of Cancer Progression and Patient Trajectories
   Vincent Wieland, Jan Hasenauer

1. What is a cell type, really? The quest to categorize life’s myriad forms

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: Spatial computational modelling illuminates the role of the tumour microenvironment for treating glioblastoma with immunotherapies published in npj Systems Biology and Applications

Artist: Blanche Mongeon

Caption: New imaging technologies like imaging mass cytometry (IMC), a labeling strategy that detects cellular biomarkers through metal-tagged antibodies, can generate detailed information on the spatial configuration of tumours. Combined with agent-based models (ABMs), IMC data from patient biopsies (left) allows for patient-specific predictions that account for spatial heterogeneity and its effect on treatment outcomes. However, the prediction precision of an ABM depends on the number of cells at initialization: with too few cells, the model is unable to accurately capture intratumoral mechanisms such as the effects of the adaptive immune system. Our framework provides a means to generate virtual patients who are representative of IMC data from real patients. Using our platform, we studied the role of different immune cells on glioblastoma treatment outcomes through simulations of various treatment combinations including chemotherapy with temozolomide, immune checkpoint inhibition with nivolumab, and an oncolytic virus (right). Our results suggest the key role macrophages and CD4+ T cells play within the tumour microenvironment in determining therapeutic success.

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