ArticleBritish journal of cancer2013
Evolutionary game theory of growth factor production: implications for tumour heterogeneity and resistance to therapies.
Article in British journal of cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed, 70 citations in OpenAlex.
- A guide to understanding tumour evolution through the lens of population genetics.Nature reviews. Cancer · 2026Review
- Artificial Intelligence (AI) and Liquid Biopsy Transforming Early Detection of Liver Metastases in Gastrointestinal Cancers.Current cancer drug targets · 2026Review
- The balance between intrinsic and ecological fitness reveals hidden regimes in eco-evolutionary population dynamics.Research square · 2025Article
- The balance between intrinsic and ecological fitness reveals hidden regimes in eco-evolutionary population dynamics.bioRxiv : the preprint server for biology · 2025Article
- The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer.Dynamic games and applications · 2022Review
- Statistical tests for intra-tumour clonal co-occurrence and exclusivity.PLoS computational biology · 2021Article
- Article
- Cancer immunoediting: A game theoretical approach.In silico biology · 2021Article
- Senescence-Induced Chemoresistance in Triple Negative Breast Cancer and Evolution-Based Treatment Strategies.Frontiers in oncology · 2021Review
- Integrating evolutionary dynamics into cancer therapy.Nature reviews. Clinical oncology · 2020Review
- Cancer systems immunology.eLife · 2020Review
- Modeling and Analyzing Stem-Cell Therapy toward Cancer: Evolutionary Game Theory Perspective.Iranian journal of public health · 2020Article
- Optimal control to reach eco-evolutionary stability in metastatic castrate-resistant prostate cancer.PloS one · 2020Article
- Multidrug Cancer Therapy in Metastatic Castrate-Resistant Prostate Cancer: An Evolution-Based Strategy.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019Article
- Evolution of cooperation in an epithelium.Journal of the Royal Society, Interface · 2019Article
- Cooperation among cancer cells: applying game theory to cancer.Nature reviews. Cancer · 2019Review
- Optimizing Cancer Treatment Using Game Theory: A Review.JAMA oncology · 2019Review
- Article
- Non-cell-autonomous effects yield lower clonal diversity in expanding tumors.Scientific reports · 2017Article
- Homeostasis Back and Forth: An Ecoevolutionary Perspective of Cancer.Cold Spring Harbor perspectives in medicine · 2017Review
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTumour heterogeneity is documented for many characters, including the production of growth factors, one of the hallmarks of cancer. What maintains heterogeneity remains an open question that has implications for diagnosis and treatment, as drugs that target growth factors are susceptible to the evolution of resistance.
methodsI use evolutionary game theory to model collective interactions between cancer cells, to analyse the dynamics of the production of growth factors and the effect of therapies that reduce their amount.
resultsFive types of dynamics are possible, including the coexistence of producer and non-producer cells, depending on the production cost of the growth factor, on its diffusion range and on the degree of synergy of the benefit it confers to the cells. Perturbations of the equilibrium mimicking therapies that target growth factors are effective in reducing the amount of growth factor in the long term only if the reduction is extremely efficient and immediate.
conclusionCollective interactions within the tumour can maintain heterogeneity for the production of growth factors and explain why therapies like anti-angiogenic drugs and RNA interference that reduce the amount of available growth factors are effective in the short term but often lead to relapse. Alternative strategies for evolutionarily stable treatments are discussed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.