Speaker
Description
\emph{This is the keynote presentation for the 2024 Reinhart Heinrich Doctoral Thesis Award.}
Cancer is a complex ecosystem where genetic and phenotypic diversity drive tumor evolution, progression, and treatment resistance. Understanding how microscopic cellular processes, such as mutation, proliferation, and migration, shape macroscopic tumor dynamics remains a challenge. In this talk, I present a mathematical framework to study tumor heterogeneity \cite{syga2026}. By linking discrete stochastic models to population genetics and evolutionary game theory, I explore the role of the distribution of fitness effects (DFE) and the evolution of phenotypic plasticity in tumor growth. The findings highlight how spatial dynamics influence cancer evolution and how tumor heterogeneity can predict treatment outcomes \cite{syga2024}. This work provides new insights into cancer progression and potential strategies for therapeutic intervention.
Bibliography
@article{syga2026,
title = {A novel cellular automaton approach for modeling genotypic and phenotypic heterogeneity in cell systems},
issn = {1951-6401},
url = {https://doi.org/10.1140/epjs/s11734-026-02186-1},
doi = {10.1140/epjs/s11734-026-02186-1},
journal = {The European Physical Journal Special Topics},
author = {Syga, Simon and Nava-Sedeño, Josué Manik and Deutsch, Andreas},
year = {2026},
}
@article{syga2024,
title = {Evolution of phenotypic plasticity leads to tumor heterogeneity with implications for therapy},
author = {Syga, Simon and Jain, Harish P. and Krellner, Marcus and Hatzikirou, Haralampos and Deutsch, Andreas},
year = 2024,
month = mar,
journal = {PLOS Computational Biology},
pages = {2024.03.18.585460},
doi = {10.1101/2024.03.18.585460}}
