ArticleBritish journal of cancer2017
Cancer treatment scheduling and dynamic heterogeneity in social dilemmas of tumour acidity and vasculature.
Article in British journal of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Review
- Optimizing breast cancer treatment strategies through fractional-order dynamics: A computational modeling approach.PloS one · 2026Article
- Article
- Sociobiology meets oncology: unraveling altruistic cooperation in cancer cells and its implications.Experimental & molecular medicine · 2025Review
- Validation of polymorphic Gompertzian model of cancer through in vitro and in vivo data.PloS one · 2025Article
- Stackelberg Evolutionary Games of Cancer Treatment: What Treatment Strategy to Choose if Cancer Can be Stabilized?Dynamic games and applications · 2025Article
- Threshold-awareness in adaptive cancer therapy.PLoS computational biology · 2024Article
- Studying mixed-species biofilms of Candida albicans and Staphylococcus aureus using evolutionary game theory.PloS one · 2024Article
- Digitize your Biology! Modeling multicellular systems through interpretable cell behavior.bioRxiv : the preprint server for biology · 2023Article
- A Systems Biology Approach for Addressing Cisplatin Resistance in Non-Small Cell Lung Cancer.Journal of clinical medicine · 2023Article
- The role of evolutionary game theory in spatial and non-spatial models of the survival of cooperation in cancer: a review.Journal of the Royal Society, Interface · 2022Review
- Cancer's second genome: Microbial cancer diagnostics and redefining clonal evolution as a multispecies process: Humans and their tumors are not aseptic, and the multispecies nature of cancer modulates clinical care and clonal evolution: Humans and their tumors are not aseptic, and the multispecies nature of cancer modulates clinical care and clonal evolution.BioEssays : news and reviews in molecular, cellular and developmental biology · 2022Review
- The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer.Dynamic games and applications · 2022Review
- Theoretical modeling of collaterally sensitive drug cycles: shaping heterogeneity to allow adaptive therapy.Journal of mathematical biology · 2021Article
- Group Behavior and Emergence of Cancer Drug Resistance.Trends in cancer · 2021Review
- Senescence-Induced Chemoresistance in Triple Negative Breast Cancer and Evolution-Based Treatment Strategies.Frontiers in oncology · 2021Review
- Can Environmental Manipulation Help Suppress Cancer? Non-Linear Competition Among Tumor Cells in Periodically Changing Conditions.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020Article
- Optimizing adaptive cancer therapy: dynamic programming and evolutionary game theory.Proceedings. Biological sciences · 2020Article
- Phenotypic Heterogeneity in Tumor Progression, and Its Possible Role in the Onset of Cancer.Frontiers in genetics · 2020Review
- Cooperation among cancer cells: applying game theory to cancer.Nature reviews. Cancer · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundTumours are diverse ecosystems with persistent heterogeneity in various cancer hallmarks like self-sufficiency of growth factor production for angiogenesis and reprogramming of energy metabolism for aerobic glycolysis. This heterogeneity has consequences for diagnosis, treatment and disease progression.
methodsWe introduce the double goods game to study the dynamics of these traits using evolutionary game theory. We model glycolytic acid production as a public good for all tumour cells and oxygen from vascularisation via vascular endothelial growth factor production as a club good benefiting non-glycolytic tumour cells. This results in three viable phenotypic strategies: glycolytic, angiogenic and aerobic non-angiogenic.
resultsWe classify the dynamics into three qualitatively distinct regimes: (1) fully glycolytic; (2) fully angiogenic; or (3) polyclonal in all three cell types. The third regime allows for dynamic heterogeneity even with linear goods, something that was not possible in prior public good models that considered glycolysis or growth factor production in isolation.
conclusionsThe cyclic dynamics of the polyclonal regime stress the importance of timing for anti-glycolysis treatments like lonidamine. The existence of qualitatively different dynamic regimes highlights the order effects of treatments. In particular, we consider the potential of vascular normalisation as a neoadjuvant therapy before follow-up with interventions like buffer therapy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.