Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/110051
Title: Tumor angiogenesis and vascular patterning: a mathematical model
Authors: Travasso, Rui D. M. 
Corvera Poiré, Eugenia
Castro, Mário 
Rodríguez-Manzaneque, Juan Carlos
Hernández-Machado, A.
Issue Date: 2011
Publisher: Public Library of Science
Project: This work was supported by Fundac¸a˜o para a Cieˆncia e Tecnologia (http://www.fct.mctes.pt), project PTDC/SAU-ENB/110354/2009; Fundac¸a˜o Calouste Gulbenkian (http://www.gulbenkian.pt/), Estı´mulo a` Investigac¸a˜o Prize; CONACyT (http://www.conacyt.mx/), project 83149; Instituto de Salud Carlos III (http:// www.isciii.es/), project EMER07/055; Spanish Ministry of Science and Innovation (http://www.micinn.es/), projects FIS2009-12964-C05-02 and FIS2009-12964-C05- 03. 
Serial title, monograph or event: PLoS ONE
Volume: 6
Issue: 5
Abstract: Understanding tumor induced angiogenesis is a challenging problem with important consequences for diagnosis and treatment of cancer. Recently, strong evidences suggest the dual role of endothelial cells on the migrating tips and on the proliferating body of blood vessels, in consonance with further events behind lumen formation and vascular patterning. In this paper we present a multi-scale phase-field model that combines the benefits of continuum physics description and the capability of tracking individual cells. The model allows us to discuss the role of the endothelial cells' chemotactic response and proliferation rate as key factors that tailor the neovascular network. Importantly, we also test the predictions of our theoretical model against relevant experimental approaches in mice that displayed distinctive vascular patterns. The model reproduces the in vivo patterns of newly formed vascular networks, providing quantitative and qualitative results for branch density and vessel diameter on the order of the ones measured experimentally in mouse retinas. Our results highlight the ability of mathematical models to suggest relevant hypotheses with respect to the role of different parameters in this process, hence underlining the necessary collaboration between mathematical modeling, in vivo imaging and molecular biology techniques to improve current diagnostic and therapeutic tools.
URI: https://hdl.handle.net/10316/110051
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0019989
Rights: openAccess
Appears in Collections:FCTUC Física - Artigos em Revistas Internacionais

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