Model for in vivo progression of tumors based on co-evolving cell population and vasculature View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-12

AUTHORS

Sehyo C. Choe, Guannan Zhao, Zhenyuan Zhao, Joseph D. Rosenblatt, Hyun-Mi Cho, Seung-Uon Shin, Neil F. Johnson

ABSTRACT

With countless biological details emerging from cancer experiments, there is a growing need for minimal mathematical models which simultaneously advance our understanding of single tumors and metastasis, provide patient-personalized predictions, whilst avoiding excessive hard-to-measure input parameters which complicate simulation, analysis and interpretation. Here we present a model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in a murine mammary cell line EMT6-HER2 model in BALB/c mice and with clinical metastasis data. Seeding data about the tumor and its vasculature from in vivo images, our model predicts corridors of future tumor growth behavior and intervention response. A scaling relation enables the estimation of a tumor's most likely evolution and pinpoints specific target sites to control growth. Our findings suggest that the clinically separate phenomena of individual tumor growth and metastasis can be viewed as mathematical copies of each other differentiated only by network structure. More... »

PAGES

31

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep00031

DOI

http://dx.doi.org/10.1038/srep00031

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033298410

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/22355550


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