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Tumor morphological evolution: directed migration and gain and loss of the self-metastatic phenotype

Overview of attention for article published in Biology Direct, April 2010
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Title
Tumor morphological evolution: directed migration and gain and loss of the self-metastatic phenotype
Published in
Biology Direct, April 2010
DOI 10.1186/1745-6150-5-23
Pubmed ID
Authors

Heiko Enderling, Lynn Hlatky, Philip Hahnfeldt

Abstract

Aside from the stepwise genetic alterations known to underlie cancer cell creation, the microenvironment is known to profoundly influence subsequent tumor development, morphology and metastasis. Invasive cluster formation has been assumed to be dependent on directed migration and a heterogeneous environment--a conclusion derived from complex models of tumor-environment interaction. At the same time, these models have not included the prospect, now supported by a preponderance of evidence, that only a minority of cancer cells may have stem cell capacity. This proves to weigh heavily on the microenvironmental requirements for the display of characteristic tumor growth phenotypes. We show using agent-based modeling that some defining features of tumor growth ascribed to directed migration might also be realized under random migration, and discuss broader implications for cause-and-effect determination in general.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Haiti 1 3%
Germany 1 3%
Unknown 33 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 28%
Student > Ph. D. Student 9 25%
Student > Master 4 11%
Student > Bachelor 2 6%
Professor 2 6%
Other 5 14%
Unknown 4 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 33%
Medicine and Dentistry 5 14%
Engineering 3 8%
Biochemistry, Genetics and Molecular Biology 2 6%
Physics and Astronomy 2 6%
Other 5 14%
Unknown 7 19%