ArticleJournal of theoretical biology2009
Evolution of cell motility in an individual-based model of tumour growth.
Article in Journal of theoretical biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 71 citations in OpenAlex.
- An agent-based learning model integrating sex differences in renal cell carcinoma.Frontiers in immunology · 2026Article
- Physics-based tissue simulator to model multicellular systems: A study of liver regeneration and hepatocellular carcinoma recurrence.PLoS computational biology · 2023Article
- Metastasis and the evolution of dispersal.Proceedings. Biological sciences · 2019Article
- Simulation of glioblastoma growth using a 3D multispecies tumor model with mass effect.Journal of mathematical biology · 2019Article
- PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling.Bioinformatics (Oxford, England) · 2019Article
- The impact of proliferation-migration tradeoffs on phenotypic evolution in cancer.Scientific reports · 2019Article
- Dynamic Load Balancing Strategy for Parallel Tumor Growth Simulations.Journal of integrative bioinformatics · 2019Article
- A Review of Cell-Based Computational Modeling in Cancer Biology.JCO clinical cancer informatics · 2019Review
- A computational multiscale agent-based model for simulating spatio-temporal tumour immune response to PD1 and PDL1 inhibition.Journal of the Royal Society, Interface · 2017Article
- Blood vessel tortuosity selects against evolution of aggressive tumor cells in confined tissue environments: A modeling approach.PLoS computational biology · 2017Article
- Integrated PK-PD and agent-based modeling in oncology.Journal of pharmacokinetics and pharmacodynamics · 2015Review
- Bridging scales in cancer progression: mapping genotype to phenotype using neural networks.Seminars in cancer biology · 2015Review
- Simulating cancer growth with multiscale agent-based modeling.Seminars in cancer biology · 2015Review
- Multiple types of data are required to identify the mechanisms influencing the spatial expansion of melanoma cell colonies.BMC systems biology · 2013Article
- Dealing with diversity in computational cancer modeling.Cancer informatics · 2013Article
- Tumor evolution in space: the effects of competition colonization tradeoffs on tumor invasion dynamics.Frontiers in oncology · 2013Article
- Multiscale models of breast cancer progression.Annals of biomedical engineering · 2012Review
- Modeling drug- and chemical-induced hepatotoxicity with systems biology approaches.Frontiers in physiology · 2012Article
- In silico modelling of tumour margin diffusion and infiltration: review of current status.Computational and mathematical methods in medicine · 2012Review
- Multiscale cancer modeling.Annual review of biomedical engineering · 2011Review
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
Abstract
Tumour invasion is driven by proliferation and importantly migration into the surrounding tissue. Cancer cell motility is also critical in the formation of metastases and is therefore a fundamental issue in cancer research. In this paper we investigate the emergence of cancer cell motility in an evolving tumour population using an individual-based modelling approach. In this model of tumour growth each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells divide. With this model we have investigated the impact of the micro-environment on the emergence of a motile invasive phenotype. The results show that when a motile phenotype emerges the dynamics of the model are radically changed and we observe faster growing tumours exhibiting diffuse morphologies. Further we observe that the emergence of a motile subclone can occur in a wide range of micro-environmental growth conditions. Iterated simulations showed that in identical growth conditions the evolutionary dynamics either converge to a proliferating or migratory phenotype, which suggests that the introduction of cell motility into the model changes the shape of fitness landscape on which the cancer cell population evolves and that it now contains several local maxima. This could have important implications for cancer treatments which focus on the gene level, as our results show that several distinct genotypes and critically distinct phenotypes can emerge and become dominant in the same micro-environment.
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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.