This week in MathOnco 342

Lineage tracing, directed evolution, generative AI, clonal hematopoiesis and more..

“This week in Mathematical Oncology” — Sept 4, 2025

> mathematical-oncology.org

From the editor:

Welcome to

Veronika Hofmann

, who joined the math onco team to help with the artwork!

Of note, the MathOnco25 abstract deadline has been extended to tomorrow, Sept 5 (final deadline): https://mathematical-oncology.org/mathonco25.

Jeffrey West
jeffrey.west@moffitt.org

1. Mechanistic modeling of cell viability assays with in silico lineage tracing
   Arnab Mutsuddy, Jonah R. Huggins, Aurore K. Amrit, Atalanta Manuela Harley-Gasaway, Cemal Erdem, Evan T. Jones, Olivia G. Laurine, Jon C. Calhoun, Marc R. Birtwistle

2. Directed Evolution Restored Castrate Sensitivity in a Patient With Castrate Resistant Metastatic Prostate Cancer
   Robert A. Gatenby, Alexander R. A. Anderson, Joel S. Brown, Jill Gallaher, Jeffrey Krolick, Dawn Lemanne

3. Ordinary differential equation model of cancer-associated fibroblast heterogeneity predicts treatment outcomes
   Junho Lee & Eunjung Kim

4. Intermittent afatinib treatment suppresses the growth of resistant T790M-H1975 cells in non-small cell lung cancer (NSCLC) co-culture
   Amir Imran Faisal Hamdi , Wen Tsin Poh , Jonathan Chee Woei Lim , Ummi Nadira Daut , Soon Hin How , Yong Kek Pang, Johnson Stanslas

5. The role of environmentally mediated drug resistance in facilitating the spatial distribution of residual disease
   Amy Milne, Andriy Marusyk, Philip K. Maini, Alexander R. A. Anderson, Noemi Picco

6. A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints
   Kiril Kuzmin, Henri Schmidt, Maryam Kafi Kang, Sagi Snir, Benjamin J. Raphael & Pavel Skums

7. Generative Artificial Intelligence as a Catalyst for Effective Cancer Treatments
   Youcef Derbal

1. Clonal Hematopoiesis Dynamics and Evolutionary Fitness During Cancer Treatment Impact Clinical Outcomes
   Mona Arabzadeh, Yi-Han Tang, Christelle Colin-Leitzinger, Sadegh Marzban, …, Jeffrey West, Shridar Ganesan, Hossein Khiabanian, Nancy Gillis

2. A stochastic agent-based model for simulating tumor-immune dynamics and evaluating therapeutic strategies
   Yuhong Zhang, Chenghang Li, Boya Wang, Jinzhi Lei

3. Multiscale modeling predicts dependence of mesenchymally transitioned tumor niche fitness on cell-cell and cell-matrix adhesions
   C. Venkata Sai Prasanna, Mohit Kumar Jolly, Ramray Bhat

4. Heritability of human lifespan is about 50% when confounding factors are addressed
   Ben Shenhar, Glen Pridham, Thaís Lopes De Oliveira, Yifan Yang, Naveh Raz, Joris Deelen, Sara Hägg, Uri Alon

1. Generative AI & Mathematical Oncology

   The Mathematical Oncology Blog
   Ari Barnett, Zhifan Jiang, Daria Laslo - “As generative artificial intelligence (genAI) continues progressing into mainstream research pipelines, the opportunities available for its application to supporting clinical decision research do as well. Here we aim to provide a brief perspective on how genAI methods and mechanistic models may be integrated into a mechanistic learning framework. While recently most attention has been directed towards genAI approaches applied to natural language, in particular large language models, in this post we focus on the generative application to medical images.”

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: Logistic models inspired by non-Gaussian statistics: an application to tumor growth published in The European Physical Journal Plus

Artist: Maxsuel Lima (@limammf), Lázaro Lima Sales (@drlazarolima)

Caption: In the background, we represent what would be cancer cells competing for nutrients and influencing each other's growth dynamics. In the center, we show multiple possibilities for evolution, where each organism can follow a distinct path and evolve differently. The highlighted rays demonstrate and highlight the ability of the proposed models to explain a wide range of behaviors, whether fast or slow growing, respecting the particularities of each organism studied. This art was generated with help from ChatGPT.

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.

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