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Biomarkers or biotargets? Using competition to lure cancer cells into evolutionary traps
Anuraag Bukkuri1,2, Frederick R Adler3,4,5
1Tissue Development and Evolution Research Group, Department of Laboratory Medicine, Lund University, Lund, Sweden.
Evolution, Medicine, and Public Health
|August 21, 2023
Summary
Cancer biomarkers can evolve, impacting treatment effectiveness. An evolutionary game theory model shows that targeting biomarker evolution can create an "evolutionary trap" for cancer extinction, improving therapeutic strategies.
Area of Science:
- Evolutionary biology
- Cancer research
- Mathematical modeling
Background:
- Cancer biomarkers offer insights into tumor characteristics and progression.
- Biomarkers can functionally contribute to oncogenesis, metastasis, angiogenesis, and chemoresistance.
- Biomarker evolution can distort cancer progression estimates and treatment decisions.
Purpose of the Study:
- To model cell-cell competition in cancer based on biomarker production.
- To simulate therapeutic interventions within an evolutionary game theory framework.
- To analyze population and biomarker dynamics under different treatment scenarios.
Main Methods:
- Developed an evolutionary game theoretic model of cancer cell competition.
- Incorporated varying levels of biomarker production among cancer cells.
- Simulated chemotherapy and targeted therapy strategies on the model.
Main Results:
- Using total biomarker levels can inaccurately predict therapy efficacy.
- Biomarker production can confer resistance, enabling targeted therapy-based evolutionary traps.
- An 'evolutionary trap' strategy, combining therapies, can be more effective for cancer extinction.
- Increased cell-cell competition, influenced by biomarker levels, aids in setting these traps.
Conclusions:
- Functional biomarker evolution complicates using total biomarker levels for treatment planning.
- Evolutionarily informed strategies, especially with targeted therapies, show promise for cancer extinction.
- Targeted therapies against biomarkers can be leveraged to create effective evolutionary traps.
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