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Modelling the Role of Angiogenesis and Vasculogenesis in Solid Tumour Growth

Overview of attention for article published in Bulletin of Mathematical Biology, September 2007
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Title
Modelling the Role of Angiogenesis and Vasculogenesis in Solid Tumour Growth
Published in
Bulletin of Mathematical Biology, September 2007
DOI 10.1007/s11538-007-9253-6
Pubmed ID
Authors

I. J. Stamper, H. M. Byrne, M. R. Owen, P. K. Maini

Abstract

Recent experimental evidence suggests that vasculogenesis may play an important role in tumour vascularisation. While angiogenesis involves the proliferation and migration of endothelial cells (ECs) in pre-existing vessels, vasculogenesis involves the mobilisation of bone-marrow-derived endothelial progenitor cells (EPCs) into the bloodstream. Once blood-borne, EPCs home in on the tumour site, where subsequently they may differentiate into ECs and form vascular structures. In this paper, we develop a mathematical model, formulated as a system of nonlinear ordinary differential equations (ODEs), which describes vascular tumour growth with both angiogenesis and vasculogenesis contributing to vessel formation. Submodels describing exclusively angiogenic and exclusively vasculogenic tumours are shown to exhibit similar growth dynamics. In each case, there are three possible scenarios: the tumour remains in an avascular steady state, the tumour evolves to a vascular equilibrium, or unbounded vascular growth occurs. Analysis of the full model reveals that these three behaviours persist when angiogenesis and vasculogenesis act simultaneously. However, when both vascularisation mechanisms are active, the tumour growth rate may increase, causing the tumour to evolve to a larger equilibrium size or to expand uncontrollably. Alternatively, the growth rate may be left unaffected, which occurs if either vascularisation process alone is able to keep pace with the demands of the growing tumour. To clarify further the effects of vasculogenesis, the full model is also used to compare possible treatment strategies, including chemotherapy and antiangiogenic therapies aimed at suppressing vascularisation. This investigation highlights how, dependent on model parameter values, targeting both ECs and EPCs may be necessary in order to effectively reduce tumour vasculature and inhibit tumour growth.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 4%
Switzerland 1 2%
Germany 1 2%
Australia 1 2%
United States 1 2%
Unknown 51 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 33%
Researcher 8 14%
Student > Master 7 12%
Professor > Associate Professor 6 11%
Professor 5 9%
Other 8 14%
Unknown 4 7%
Readers by discipline Count As %
Engineering 12 21%
Mathematics 12 21%
Agricultural and Biological Sciences 11 19%
Medicine and Dentistry 6 11%
Biochemistry, Genetics and Molecular Biology 3 5%
Other 8 14%
Unknown 5 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 October 2007.
All research outputs
#15,240,835
of 22,660,862 outputs
Outputs from Bulletin of Mathematical Biology
#720
of 1,095 outputs
Outputs of similar age
#59,973
of 69,932 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#5
of 7 outputs
Altmetric has tracked 22,660,862 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,095 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 69,932 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.