Evolutionary dynamics of residual disease in human glioblastoma

Spiteri, Inmaculada; Caravagna, Giulio; Cresswell, George D; Vatsiou, Alexandra; Nichol, Daniel; Acar, Ahmet; Ermini, Luca; Chkhaidze, Kate; Werner, Benjamin; Mair, Richard; Brognaro, Enrico; Verhaak, Roel G.W.; Sanguinetti, Guido; Piccirillo, Sara Grazia Maria; Watts, Colin; Sottoriva, Andrea

doi:10.1093/annonc/mdy506

Cited by 58 publications

(55 citation statements)

References 22 publications

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“…The possibility of exploiting ecology for the treatment of tumors based on studies in conservation biology about extinction and control of invasive species has been proposed (13)(14)(15)(16)(17)(18)(19)(20)(21)(22), but this is the first work to our knowledge that has explicitly tested for the presence of the Allee effect in a regime in which low cancer cell populations can be measured and fit to a number of stochastic model structures representing different biological hypotheses about the Allee effect. Our finding is consistent with pre-clinical(2) and clinical observations (3,56) of threshold-like behavior of tumor growth or slowed tumor growth following resection. Evidence for the Allee effect is also consistent with evidence of cooperation among cancer cell subclones as has been amply demonstrated (5-7,57-59) An understanding of subpopulation interactions and their molecular mediators that drive the observed Allee effect offer new approaches to manipulate cancer cell growth dynamics in favor of extinction.…”

Section: Discussionsupporting

confidence: 91%

“…Most notably we apply the modeling and analysis framework to an in vitro data set for a single breast cancer cell line. The in vitro system may not faithfully represent in vivo growth dynamics, although we expect, and others have shown evidence that (3,56), the Allee effect would only be more pronounced in vivo. An in vitro setting provides cells with all of the growth factors, nutrients, and space to robustly grow at low cell densities, whereas these factors may be less abundant for tumor cells in vivo at a low cell density.…”

Section: Discussionmentioning

confidence: 67%

See 1 more Smart Citation

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Johnson

Howard

et al. 2019

Preprint

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Models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations from exponential growth only at higher densities due to limited resources such as space and nutrients. However, recent pre-clinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models however, tumor growth data is limited by the lower limit of detection (i.e. a measurable lesion) and confounding variables, such as tumor microenvironment and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to consider the small number of cells in this low-density regime and use the moment approach for stochastic parameter estimation to calibrate the stochastic growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells depends on cell number. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging tumors and relapse. Author SummaryThe growth kinetics of cancer cells at very low cell densities are of utmost clinical importance as the ability of a small number of newly transformed or surviving cells to grow exponentially and thus, to "take off" underlies tumor formation and relapse after treatment. Mathematical models of stochastic tumor cell growth typically assume a stochastic birth-death process of cells impacted by limited nutrients and space when cells reach high density, resulting in the widely accepted logistic growth model. Here we present an in-depth investigation of alternate growth models adopted from ecology to describe potential deviations from a simple cell autonomous birth-death model at low cell densities. We show that our stochastic modeling framework is robust and can be used to identify the underlying structure of stochastic growth trajectories from both simulated and experimental data taken from a controlled in vitro setting in which we can capture data from the relevant low cell density regime. This work suggests that the assumption of cell autonomous proliferation via a constant exponential growth rate at low cell densities may not be appropriate for all cancer cell growth dynamics. Consideration of cooperative behavior amongst tumor cells in this regime is critical for elucidating strategies for controll...

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 67%

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Johnson

Howard

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…However, this is the first work to our knowledge that has explicitly tested for the presence of the Allee effect in a regime in which low cancer cell populations can be measured and fit to a number of stochastic model structures representing different biological hypotheses about the Allee effect. Our finding is consistent with preclinical [2] and clinical observations [3,63] of threshold-like behavior of tumor growth or slowed tumor growth following resection. Evidence for the Allee effect is also consistent with evidence of cooperation among cancer cell subclones as has been amply demonstrated [5][6][7][64][65][66]].…”

Section: Discussionsupporting

confidence: 91%

“…Most notably, we apply the modeling and analysis framework to an in vitro data set for a single breast cancer cell line. The in vitro system may not faithfully represent in vivo growth dynamics, although we expect, and others have shown evidence that [3,63], the Allee effect would only be more pronounced in vivo. An in vitro setting provides cells with all of the growth factors, nutrients, and space to robustly grow at low cell densities, whereas these factors may be less abundant for tumor cells in vivo at a low cell density.…”

Section: Discussionmentioning

confidence: 67%

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

et al. 2019

View full text Add to dashboard Cite

Most models of cancer cell population expansion assume exponential growth kinetics at low cell densities, with deviations to account for observed slowing of growth rate only at higher densities due to limited resources such as space and nutrients. However, recent preclinical and clinical observations of tumor initiation or recurrence indicate the presence of tumor growth kinetics in which growth rates scale positively with cell numbers. These observations are analogous to the cooperative behavior of species in an ecosystem described by the ecological principle of the Allee effect. In preclinical and clinical models, however, tumor growth data are limited by the lower limit of detection (i.e., a measurable lesion) and confounding variables, such as tumor microenvironment, and immune responses may cause and mask deviations from exponential growth models. In this work, we present alternative growth models to investigate the presence of an Allee effect in cancer cells seeded at low cell densities in a controlled in vitro setting. We propose a stochastic modeling framework to disentangle expected deviations due to small population size stochastic effects from cooperative growth and use the moment approach for stochastic parameter estimation to calibrate the observed growth trajectories. We validate the framework on simulated data and apply this approach to longitudinal cell proliferation data of BT-474 luminal B breast cancer cells. We find that cell population growth kinetics are best described by a model structure that considers the Allee effect, in that the birth rate of tumor cells increases with cell number in the regime of small population size. This indicates a potentially critical role of cooperative behavior among tumor cells at low cell densities with relevance to early stage growth patterns of emerging and relapsed tumors.

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“…Invasion and infiltration are hallmarks of advanced cancers, including breast cancer, and accumulating evidence suggests that invasive subclones arise early during tumor evolution [1]. MTOR inhibitors (mTOR-I) significantly decrease migration of breast cancer cells in a dose-dependent manner [2].…”

Section: Introductionmentioning

confidence: 99%

Invasion of homogeneous and polyploid populations in nutrient-limiting environments

Kimmel

Dane

Heiser

et al. 2020

Preprint

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Breast cancer progresses in a multistep process from primary tumor growth and stroma invasion to metastasis. Progression is accompanied by a switch to an invasive cell phenotype. Nutrient-limiting environments exhibit chemotaxis with aggressive morphologies characteristic of invasion. The mTOR pathway senses essential nutrients, informing the cell to respond with either increased chemotaxis and nutrient uptake or cell cycle progression. Randomized clinical trials have shown that mTOR inhibitors (mTOR-I) improve the outcome of metastatic breast cancer patients. However, there are considerable differences between and within tumors that impact the effectiveness of mTOR-I, including differences in access to nutrients. It is unknown how co-existing cells differ in their response to nutrient limitations and how this impacts invasion of the metapopulation as a whole. We integrate modeling with microenvironmental perturbations data to investigate invasion in nutrient-limiting environments inhabited by one or two cancer cell subpopulations. Hereby subpopulations are defined by their energy efficiency and chemotactic ability. We calculate the invasion-distance traveled by a homogeneous population. For heterogeneous populations, our results suggest that an imbalance between nutrient efficacy and chemotactic superiority accelerates invasion. Such imbalance will segregate the two populations spatially and only one type will dominate at the invasion front. Only if these two phenotypes are balanced do the two populations compete for the same space, which decelerates invasion. We investigate ploidy as a candidate biomarker of this phenotypic heterogeneity to discern circumstances when inhibiting chemotaxis amplifies innternal competition and decelerates tumor progression, from circumstances that render clinical consequences of chemotactic inhibition unfavorable. Significance: A better understanding of the nature of the double-edged sword of high ploidy is a prerequisite to personalize combinationtherapies with cytotoxic drugs and inhibitors of signal transduction pathways such as MTOR-Is.

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Evolutionary dynamics of residual disease in human glioblastoma

Cited by 58 publications

References 22 publications

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Cancer cell population growth kinetics at low densities deviate from the exponential growth model and suggest an Allee effect

Invasion of homogeneous and polyploid populations in nutrient-limiting environments

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