Evolutionary game theory in an agent-based brain tumor model: exploring the 'Genotype-Phenotype' link

Area of Science:

• Computational Biology
• Cancer Research
• Evolutionary Dynamics

Background:

• Understanding the genotype-phenotype link in polyclonal cancer cell populations is crucial for effective treatment strategies.
• Previous agent-based models have simulated tumor growth, but incorporating evolutionary game theory offers new insights into cellular interactions.

Purpose of the Study:

• To investigate the genotype-phenotype link in a polyclonal brain tumor cell population using evolutionary game theory.
• To model the spatial expansion dynamics of a heterogeneous tumor composed of proliferative (Type A) and migratory (Type B) cells.

Main Methods:

• Development of an agent-based brain tumor model incorporating evolutionary game theory.
• Simulation of a heterogeneous cell population comprising two distinct genotypes: Type A (proliferative) and Type B (migratory).
• Analysis of tumor velocity, genotypic composition, and spatial aggression under varying payoff conditions.

Main Results:

• A phase transition in tumor spatial expansion velocity was observed, directly linked to genotypic composition and tumor fitness.
• Tumor velocity initially decreased with increased payoffs for stationary Type A cells but unexpectedly accelerated at higher payoff levels.
• A competitive advantage for fewer migratory Type B cells was identified at later stages, leading to accelerated tumor dynamics and reduced surface roughness.

Conclusions:

• Genotypic composition and cell-cell interactions significantly influence brain tumor expansion dynamics.
• The study highlights a non-linear relationship between cellular payoffs, genotypic ratios, and tumor aggression.
• Findings suggest potential therapeutic strategies targeting specific genotype interactions to control tumor progression.