Literature DB >> 25033031

Quantifying metastatic inefficiency: rare genotypes versus rare dynamics.

Luis H Cisneros1, Timothy J Newman.   

Abstract

We introduce and solve a 'null model' of stochastic metastatic colonization. The model is described by a single parameter θ: the ratio of the rate of cell division to the rate of cell death for a disseminated tumour cell in a given secondary tissue environment. We are primarily interested in the case in which colonizing cells are poorly adapted for proliferation in the local tissue environment, so that cell death is more likely than cell division, i.e. θ < 1. We quantify the rare event statistics for the successful establishment of a metastatic colony of size N. For N >> 1, we find that the probability of establishment is exponentially rare, as expected, and yet the mean time for such rare events is of the form ~log (N)/(1 - θ) while the standard deviation of colonization times is ~1/(1 - θ). Thus, counter to naive expectation, for θ < 1, the average time for establishment of successful metastatic colonies decreases with decreasing cell fitness, and colonies seeded from lower fitness cells show less stochastic variation in their growth. These results indicate that metastatic growth from poorly adapted cells is rare, exponentially explosive and essentially deterministic. These statements are brought into sharper focus by the finding that the temporal statistics of the early stages of metastatic colonization from low-fitness cells (θ < 1) are statistically indistinguishable from those initiated from high-fitness cells (θ > 1), i.e. the statistics show a duality mapping (1 - θ) --> (θ - 1). We conclude our analysis with a study of heterogeneity in the fitness of colonising cells, and describe a phase diagram delineating parameter regions in which metastatic colonization is dominated either by low or high fitness cells, showing that both are plausible given our current knowledge of physiological conditions in human cancer.

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Year:  2014        PMID: 25033031     DOI: 10.1088/1478-3975/11/4/046003

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  6 in total

1.  Prognostic Implications of Tumor Diameter in Association With Gene Expression Profile for Uveal Melanoma.

Authors:  Scott D Walter; Daniel L Chao; William Feuer; Joyce Schiffman; Devron H Char; J William Harbour
Journal:  JAMA Ophthalmol       Date:  2016-07-01       Impact factor: 7.389

2.  Thymic involution and rising disease incidence with age.

Authors:  Sam Palmer; Luca Albergante; Clare C Blackburn; T J Newman
Journal:  Proc Natl Acad Sci U S A       Date:  2018-02-05       Impact factor: 11.205

3.  A Mathematical Framework for Modelling the Metastatic Spread of Cancer.

Authors:  Linnea C Franssen; Tommaso Lorenzi; Andrew E F Burgess; Mark A J Chaplain
Journal:  Bull Math Biol       Date:  2019-03-22       Impact factor: 1.758

4.  Primary and metastatic tumor dormancy as a result of population heterogeneity.

Authors:  Irina Kareva
Journal:  Biol Direct       Date:  2016-08-23       Impact factor: 4.540

Review 5.  The p38 pathway, a major pleiotropic cascade that transduces stress and metastatic signals in endothelial cells.

Authors:  Isabelle Corre; François Paris; Jacques Huot
Journal:  Oncotarget       Date:  2017-05-29

6.  A mathematical model of the metastatic bottleneck predicts patient outcome and response to cancer treatment.

Authors:  Ewa Szczurek; Tyll Krüger; Barbara Klink; Niko Beerenwinkel
Journal:  PLoS Comput Biol       Date:  2020-10-02       Impact factor: 4.475

  6 in total

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