Computational and Mathematical Methods in Medicine
Volume 8 (2007), Issue 1, Pages 1-9
Book Review

Targeting Tumour Vasculature as a Cancer Treatment

1School of Medicine, University of Leeds, Worsley Building, Clarendon Way, Leeds LS2 9NL, UK
2Leeds Institute of Molecular Medicine, St James's University Hospital, Wellcome Trust Brenner Building, Leeds LS9 7TF, UK

Received 21 February 2007; Accepted 22 February 2007

Copyright © 2007 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Modelling blood flow and capillary growth in tumours has been the focus of several research groups with the aim of generating theoretical models that can be used to predict biological behaviour within these systems. Since dysfunctional angiogenesis is seen in a wide range of pathological conditions ranging from cardiovascular, to arthritis, to diabetes, it is easy to see how these models may have a far-reaching influence on future therapeutic strategies.

One major area of anti-cancer treatment is the targeting of the tumour blood vessels. Paradoxically, different approaches taken in angiogenic therapy have different aims. Prevention of new vessel growth, or disruption of existing vessels, are both aimed at preventing sufficient oxygen and nutrients to reach the tumour. However, since drug delivery to tumours is often very poor, due to the disorganised architecture of the tumour vessels, one suggested strategy is to improve circulation within a tumour through “normalisation” of the vasculature which results in more effective anti-tumour drug delivery.

There are currently no theoretical models of vessel regression or vascular disruption even though both are actively targeted by tumour therapies. This article will give an overview of the different mechanisms targeted by different anti-angiogenic strategies and highlight areas that may benefit from the development of predictive theoretical models.