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A Race between Tumor Immunoescape and Genome Maintenance Selects for Optimum Levels of (epi)genetic Instability

Overview of attention for article published in PLoS Computational Biology, February 2012
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Title
A Race between Tumor Immunoescape and Genome Maintenance Selects for Optimum Levels of (epi)genetic Instability
Published in
PLoS Computational Biology, February 2012
DOI 10.1371/journal.pcbi.1002370
Pubmed ID
Authors

Shingo Iwami, Hiroshi Haeno, Franziska Michor

Abstract

The human immune system functions to provide continuous body-wide surveillance to detect and eliminate foreign agents such as bacteria and viruses as well as the body's own cells that undergo malignant transformation. To counteract this surveillance, tumor cells evolve mechanisms to evade elimination by the immune system; this tumor immunoescape leads to continuous tumor expansion, albeit potentially with a different composition of the tumor cell population ("immunoediting"). Tumor immunoescape and immunoediting are products of an evolutionary process and are hence driven by mutation and selection. Higher mutation rates allow cells to more rapidly acquire new phenotypes that help evade the immune system, but also harbor the risk of an inability to maintain essential genome structure and functions, thereby leading to an error catastrophe. In this paper, we designed a novel mathematical framework, based upon the quasispecies model, to study the effects of tumor immunoediting and the evolution of (epi)genetic instability on the abundance of tumor and immune system cells. We found that there exists an optimum number of tumor variants and an optimum magnitude of mutation rates that maximize tumor progression despite an active immune response. Our findings provide insights into the dynamics of tumorigenesis during immune system attacks and help guide the choice of treatment strategies that best inhibit diverse tumor cell populations.

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Mendeley readers

The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Sweden 1 2%
France 1 2%
Mexico 1 2%
United Kingdom 1 2%
Unknown 46 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 31%
Student > Ph. D. Student 12 23%
Student > Master 6 12%
Other 4 8%
Professor > Associate Professor 3 6%
Other 6 12%
Unknown 5 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 44%
Medicine and Dentistry 8 15%
Biochemistry, Genetics and Molecular Biology 4 8%
Computer Science 4 8%
Engineering 2 4%
Other 4 8%
Unknown 7 13%