This week in MathOnco 290

Integro-differential equations, chemo optimization, immunotherapy biomarkers, second-order effects, and more...

“This week in Mathematical Oncology” — April 4, 2024

> mathematical-oncology.org

From the editor:

Hello!

Today’s newsletter features articles on integro-differential equations, chemo optimization, immunotherapy biomarkers, and one of my own papers on second-order effects (antifragility)!

If you missed it last week, the newsletter now has an associated LaTeX bibliography file (>1500 papers), here!

PS, if you’d like to apply for a postdoc position in my group, please take a look at the advertisement, here. Let me know if you plan to apply by replying to this email!

Enjoy,

Jeffrey West
jeffrey.west@moffitt.org

1. Second-Order Effects of Chemotherapy Pharmacodynamics and Pharmacokinetics on Tumor Regression and Cachexia
   Luke Pierik, Patricia McDonald, Alexander R. A. Anderson & Jeffrey West

2. Analysis and simulation of an integro-differential Lotka–Volterra model with variable reproduction rates and optimal control
   Anderson L.A. de Araujo, Artur C. Fassoni, Kamila F.L. Madalena, Luís F. Salvino

3. Optimization of chemotherapy regimens using mathematical programming
   Konstantin Bräutigam

4. Digital twins for health: a scoping review
   Evangelia Katsoulakis, Qi Wang, Huanmei Wu, Leili Shahriyari, Richard Fletcher, Jinwei Liu, Luke Achenie, Hongfang Liu, Pamela Jackson, Ying Xiao, Tanveer Syeda-Mahmood, Richard Tuli & Jun Deng

5. Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy
   Yurong Qin, Miaozhe Huo, Xingwu Liu, Shuai Cheng Li

6. Localized radiotherapy of solid tumors using radiopharmaceutical loaded implantable system: insights from a mathematical model
   Anahita Piranfar, Mohammad Souri, Arman Rahmim, Madjid Soltan

1. Evolution of phenotypic plasticity leads to tumor heterogeneity with implications for therapy
   Simon Syga, Harish P Jain, Marcus Krellner, Haralampos Hatzikirou, Andreas Deutsch

2. Hybridizing mechanistic mathematical modeling with deep learning methods to predict individual cancer patient survival after immune checkpoint inhibitor therapy
   Joseph Butner, Prashant Dogra, Caroline Chung, Eugene Koay, James Welsh, David Hong, Vittorio Cristini, Zhihui Wang

1. ADAPT

   ADvanced Analysis for Precision cancer Therapy: The ADvanced Analysis for Precision cancer Therapy (ADAPT) program aims to harness advanced technologies and a deep understanding of tumor biology to build cancer biomarkers. By tracking tumor changes before, during, and after treatment, clinicians can pinpoint alterations in tumor traits, enabling a more proactive response to cancer care. A key feature of ADAPT will be to establish a central hub for clinicians and researchers to access data and resources. This repository will house algorithms, protocols, and evolving data on biomarkers and anti-cancer agents. These tools will allow clinicians to deliver truly adaptive and personalized cancer care.

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: A mathematical model for predicting the spatiotemporal response of breast cancer cells treated with doxorubicin published in Cancer Biology & Therapy

Artist: Hugo Miniere, Thomas Yankeelov

Caption: Tumor diversity is a major roadblock in fighting cancer, often making treatments less effective. To tackle this challenge, we need tools that can spot and predict these differences within and between tumors. Enter our solution: a cool blend of experimentation, biology and math that merged together into a straightforward pipeline for personalized therapies. Our new approach looks at breast cancer cells in the lab, tracking how they respond to treatment over time and space. We've divided the cells into two groups: the surviving population (in red) that resists treatment and the sensitive population (in blue) that is ultimately destroyed. By analyzing images and longitudinal cell counts from experiments with doxorubicin, we're building a map of how these cells behave under pressure, and then predicting the growth and development of cell clusters. Those predictions can then be leveraged to inform future treatment decisions!

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

• Postdoc position on the biophysical determinants of cell fate decisions in skin inflammatory diseases (Adrien Hallou, University of Oxford)

• Postdoc position on evolutionary game theory models of cancer progression and treatment (Jeffrey West, Moffitt Cancer Center)

2. Conferences / Meetings

3. Special issues

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