An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location

Norton, Kerri-Ann; Popel, Aleksander S.

doi:10.1098/rsif.2014.0640

Cited by 43 publications

(49 citation statements)

References 89 publications

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“…This complements other recent studies on the use of computational modeling to elucidate cellular behavior such as genetic expression in individual stem cells, 21,22 the role of stem cells in tumor development and metastasis, 23,24 and embryogenesis in the pancreas. 25 …”

Section: Discussionsupporting

confidence: 74%

A Computational Model of Cellular Engraftment on Lung Scaffolds

Pothen

Rajendran

Wagner

et al. 2016

BioResearch Open Access

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The possibility that stem cells might be used to regenerate tissue is now being investigated for a variety of organs, but these investigations are still essentially exploratory and have few predictive tools available to guide experimentation. We propose, in this study, that the field of lung tissue regeneration might be better served by predictive tools that treat stem cells as agents that obey certain rules of behavior governed by both their phenotype and their environment. Sufficient knowledge of these rules of behavior would then, in principle, allow lung tissue development to be simulated computationally. Toward this end, we developed a simple agent-based computational model to simulate geographic patterns of cells seeded onto a lung scaffold. Comparison of the simulated patterns to those observed experimentally supports the hypothesis that mesenchymal stem cells proliferate preferentially toward the scaffold boundary, whereas alveolar epithelial cells do not. This demonstrates that a computational model of this type has the potential to assist in the discovery of rules of cellular behavior.

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Section: Discussionsupporting

confidence: 74%

A Computational Model of Cellular Engraftment on Lung Scaffolds

Pothen

Rajendran

Wagner

et al. 2016

BioResearch Open Access

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“…Breast cancer is the most common malignancy in women worldwide, and tumor invasion and metastasis are the major detrimental events that threaten patients' life. Regarding tumor invasion, tumor cells themselves can obtain invasive capacities through epithelial‐mesenchymal transition (EMT) and acquisition of stem‐like properties and so on . In addition, interactions between tumor cells and their adjacent microenvironment also play pivotal roles in tumor invasion and metastasis .…”

mentioning

confidence: 99%

“…Regarding tumor invasion, tumor cells themselves can obtain invasive capacities through epithelial-mesenchymal transition (EMT) (1,2) and acquisition of stem-like properties and so on. (3,4) In addition, interactions between tumor cells and their adjacent microenvironment also play pivotal roles in tumor invasion and metastasis. (5,6) Our laboratory has been focusing on an important tumor microenvironment molecule, adenosine 5 0 -triphosphate (ATP).…”

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confidence: 99%

ATP‐P2Y2‐β‐catenin axis promotes cell invasion in breast cancer cells

et al. 2017

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Extracellular adenosine 5′‐triphosphate (ATP), secreted by living cancer cells or released by necrotic tumor cells, plays an important role in tumor invasion and metastasis. Our previous study demonstrated that ATP treatment in vitro could promote invasion in human prostate cancer cells via P2Y2, a preferred receptor for ATP, by enhancing EMT process. However, the pro‐invasion mechanisms of ATP and P2Y2 are still poorly studied in breast cancer. In this study, we found that P2Y2 was highly expressed in breast cancer cells and associated with human breast cancer metastasis. ATP could promote the in vitro invasion of breast cancer cells and enhance the expression of β‐catenin as well as its downstream target genes CD44, c‐Myc and cyclin D1, while P2Y2 knockdown attenuated above ATP‐driven events in vitro and in vivo. Furthermore, iCRT14, a β‐catenin/TCF complex inhibitor, could also suppress ATP‐driven migration and invasion in vitro. These results suggest that ATP promoted breast cancer cell invasion via P2Y2‐β‐catenin axis. Thus blockade of the ATP‐P2Y2‐β‐catenin axis could suppress the invasive and metastatic potential of breast cancer cells and may serve as potential targets for therapeutic interventions of breast cancer.

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“…Our model takes into account limited availability of space for cells to occupy in the following manner. As the amount of free space decreases, cells are more likely to enter quiescence (Norton and Popel, 2014). However, for simplicity we do not include a separate compartment representing these cells; instead the rate at which cells re-enter G2/M from G1/S is assumed to be dependent on the available free space, and goes down as space becomes limited.…”

Section: Methodsmentioning

confidence: 99%

A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study

Eisenberg

Jain

2017

Journal of Theoretical Biology

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Mathematical modeling has a long history in the field of cancer therapeutics, and there is increasing recognition that it can help uncover the mechanisms that underlie tumor response to treatment. However, making quantitative predictions with such models often requires parameter estimation from data, raising questions of parameter identifiability and estimability. Even in the case of structural (theoretical) identifiability, imperfect data and the resulting practical unidentifiability of model parameters can make it difficult to infer the desired information, and in some cases, to yield biologically correct inferences and predictions. Here, we examine parameter identifiability and estimability using a case study of two compartmental, ordinary differential equation models of cancer treatment with drugs that are cell cycle-specific (taxol) as well as non-specific (oxaliplatin). We proceed through model building, structural identifiability analysis, parameter estimation, practical identifiability analysis and its biological implications, as well as alternative data collection protocols and experimental designs that render the model identifiable. We use the differential algebra/input-output relationship approach for structural identifiability, and primarily the profile likelihood approach for practical identifiability. Despite the models being structurally identifiable, we show that without consideration of practical identifiability, incorrect cell cycle distributions can be inferred, that would result in suboptimal therapeutic choices. We illustrate the usefulness of estimating practically identifiable combinations (in addition to the more typically considered structurally identifiable combinations) in generating biologically meaningful insights. We also use simulated data to evaluate how the practical identifiability of the model would change under alternative experimental designs. These results highlight the importance of understanding the underlying mechanisms rather than purely using parsimony or information criteria/goodness-of-fit to decide model selection questions. The overall roadmap for identifiability testing laid out here can be used to help provide mechanistic insight into complex biological phenomena, reduce experimental costs, and optimize model-driven experimentation.

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An agent-based model of cancer stem cell initiated avascular tumour growth and metastasis: the effect of seeding frequency and location

Cited by 43 publications

References 89 publications

A Computational Model of Cellular Engraftment on Lung Scaffolds

A Computational Model of Cellular Engraftment on Lung Scaffolds

ATP‐P2Y2‐β‐catenin axis promotes cell invasion in breast cancer cells

A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study

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