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A theoretical quantitative model for evolution of cancer chemotherapy resistance

Overview of attention for article published in Biology Direct, April 2010
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Title
A theoretical quantitative model for evolution of cancer chemotherapy resistance
Published in
Biology Direct, April 2010
DOI 10.1186/1745-6150-5-25
Pubmed ID
Authors

Ariosto S Silva, Robert A Gatenby

Abstract

Disseminated cancer remains a nearly uniformly fatal disease. While a number of effective chemotherapies are available, tumors inevitably evolve resistance to these drugs ultimately resulting in treatment failure and cancer progression. Causes for chemotherapy failure in cancer treatment reside in multiple levels: poor vascularization, hypoxia, intratumoral high interstitial fluid pressure, and phenotypic resistance to drug-induced toxicity through upregulated xenobiotic metabolism or DNA repair mechanisms and silencing of apoptotic pathways. We propose that in order to understand the evolutionary dynamics that allow tumors to develop chemoresistance, a comprehensive quantitative model must be used to describe the interactions of cell resistance mechanisms and tumor microenvironment during chemotherapy.Ultimately, the purpose of this model is to identify the best strategies to treat different types of tumor (tumor microenvironment, genetic/phenotypic tumor heterogeneity, tumor growth rate, etc.). We predict that the most promising strategies are those that are both cytotoxic and apply a selective pressure for a phenotype that is less fit than that of the original cancer population. This strategy, known as double bind, is different from the selection process imposed by standard chemotherapy, which tends to produce a resistant population that simply upregulates xenobiotic metabolism. In order to achieve this goal we propose to simulate different tumor progression and therapy strategies (chemotherapy and glucose restriction) targeting stabilization of tumor size and minimization of chemoresistance.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 114 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 4%
France 2 2%
Germany 1 <1%
Brazil 1 <1%
Portugal 1 <1%
United Kingdom 1 <1%
Sweden 1 <1%
Denmark 1 <1%
Canada 1 <1%
Other 0 0%
Unknown 101 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 25%
Researcher 28 25%
Student > Master 13 11%
Professor > Associate Professor 9 8%
Professor 7 6%
Other 18 16%
Unknown 11 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 41 36%
Medicine and Dentistry 13 11%
Biochemistry, Genetics and Molecular Biology 11 10%
Mathematics 11 10%
Physics and Astronomy 7 6%
Other 15 13%
Unknown 16 14%