ArticleScientific reports2019
The impact of proliferation-migration tradeoffs on phenotypic evolution in cancer.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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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.
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Who cites it
57 citing papers in PubMed.
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- Uncovering the signaling networks of disseminated glioblastoma cells in vivo with INSIGHT.Nature communications · 2026Article
- Fibroblast activation protein (FAP)-mediated promotion of metastasis via the FN1-TGFβ axis and immune suppression in aggressive thyroid cancer.Journal of translational medicine · 2025Article
- Characterization of glioma spheroid viability and metastatic potential following monophasic and biphasic pulsed electric fields.Bioelectrochemistry (Amsterdam, Netherlands) · 2025Article
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- Multi-omics profiling reveals key factors involved in Ewing sarcoma metastasis.Molecular oncology · 2025Article
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- Glioblastoma progression is hindered by melatonin-primed mesenchymal stromal cells through dynamic intracellular and extracellular reorganizations.Theranostics · 2025Article
- Cell-Level Modelling of Homeostasis in Confined Epithelial Monolayers.Journal Of Elasticity · 2025Article
- Agent-based modeling in cancer biomedicine: applications and tools for calibration and validation.Cancer biology & therapy · 2024Review
- Insights from a multiscale framework on metabolic rate variation driving glioblastoma multiforme growth and invasion.Communications engineering · 2024Article
- Life history dynamics of evolving tumors: insights into task specialization, trade-offs, and tumor heterogeneity.Cancer cell international · 2024Review
- Mitochondrial Bioenergetics of Functional Wound Closure is Dependent on Macrophage-Keratinocyte Exosomal Crosstalk.ACS nano · 2024Article
- AMBER: A Modular Model for Tumor Growth, Vasculature and Radiation Response.Bulletin of mathematical biology · 2024Article
- Evolution of phenotypic plasticity leads to tumor heterogeneity with implications for therapy.PLoS computational biology · 2024Article
- Non-coding RNA transcripts, incredible modulators of cisplatin chemo-resistance in bladder cancer through operating a broad spectrum of cellular processes and signaling mechanism.Non-coding RNA research · 2024Review
- Cancer cells forgo translating mRNA transcribed from genes of nonspecialized tasks.FEBS open bio · 2024Article
- Article
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Authors and funding
3 authors.
Funding
Abstract
Tumors are not static masses of cells but dynamic ecosystems where cancer cells experience constant turnover and evolve fitness-enhancing phenotypes. Selection for different phenotypes may vary with (1) the tumor niche (edge or core), (2) cell turnover rates, (3) the nature of the tradeoff between traits, and (4) whether deaths occur in response to demographic or environmental stochasticity. Using a spatially-explicit agent-based model, we observe how two traits (proliferation rate and migration speed) evolve under different tradeoff conditions with different turnover rates. Migration rate is favored over proliferation at the tumor's edge and vice-versa for the interior. Increasing cell turnover rates slightly slows tumor growth but accelerates the rate of evolution for both proliferation and migration. The absence of a tradeoff favors ever higher values for proliferation and migration, while a convex tradeoff tends to favor proliferation, often promoting the coexistence of a generalist and specialist phenotype. A concave tradeoff favors migration at low death rates, but switches to proliferation at higher death rates. Mortality via demographic stochasticity favors proliferation, and environmental stochasticity favors migration. While all of these diverse factors contribute to the ecology, heterogeneity, and evolution of a tumor, their effects may be predictable and empirically accessible.
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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.