Spatial structure impacts adaptive therapy by shaping intra-tumoral competition

Area of Science:

• Mathematical oncology
• Computational biology
• Cancer research

Background:

• Adaptive therapy aims to overcome cancer drug resistance by utilizing resource competition.
• Intra-tumoral competition between drug-sensitive and resistant cells is a key mechanism.
• Understanding when adaptive therapy surpasses aggressive treatment is crucial.

Purpose of the Study:

• To theoretically investigate intra-tumoral competition during adaptive therapy.
• To determine conditions under which adaptive therapy is superior to aggressive treatment.
• To analyze the role of spatial architecture and cell competition in adaptive therapy efficacy.

Main Methods:

• Development and analysis of a 2-D, on-lattice, agent-based tumor model.
• Classification of cells into drug-sensitive and drug-resistant phenotypes.
• Comparison with a non-spatial ordinary differential equation model.
• Fitting the model to longitudinal prostate-specific antigen data from prostate cancer patients.

Main Results:

• Explicit demonstration of competitive suppression of resistant cells during adaptive therapy.
• Identification of factors influencing competition, including initial resistance fraction and resistance costs.
• Revealed the significant role of competition among resistant cells in solid tumors.
• Corroboration of theoretical understanding of adaptive therapy mechanisms.

Conclusions:

• Tumor spatial architecture is a critical factor in adaptive therapy effectiveness.
• Adaptive therapy leverages inter- and intra-specific competition to manage drug resistance.
• Insights provided for mathematical modeling of adaptive therapy and intra-tumoral dynamics in prostate cancer.