Title |
Senescent Cells in Growing Tumors: Population Dynamics and Cancer Stem Cells
|
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Published in |
PLoS Computational Biology, January 2012
|
DOI | 10.1371/journal.pcbi.1002316 |
Pubmed ID | |
Authors |
Caterina A. M. La Porta, Stefano Zapperi, James P. Sethna |
Abstract |
Tumors are defined by their intense proliferation, but sometimes cancer cells turn senescent and stop replicating. In the stochastic cancer model in which all cells are tumorigenic, senescence is seen as the result of random mutations, suggesting that it could represent a barrier to tumor growth. In the hierarchical cancer model a subset of the cells, the cancer stem cells, divide indefinitely while other cells eventually turn senescent. Here we formulate cancer growth in mathematical terms and obtain predictions for the evolution of senescence. We perform experiments in human melanoma cells which are compatible with the hierarchical model and show that senescence is a reversible process controlled by survivin. We conclude that enhancing senescence is unlikely to provide a useful therapeutic strategy to fight cancer, unless the cancer stem cells are specifically targeted. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Germany | 1 | 25% |
Spain | 1 | 25% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 75% |
Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 4% |
United Kingdom | 2 | 2% |
Portugal | 1 | <1% |
Italy | 1 | <1% |
South Africa | 1 | <1% |
Japan | 1 | <1% |
Spain | 1 | <1% |
Unknown | 100 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 34 | 30% |
Student > Ph. D. Student | 24 | 21% |
Student > Master | 12 | 11% |
Student > Bachelor | 10 | 9% |
Professor | 9 | 8% |
Other | 17 | 15% |
Unknown | 6 | 5% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 50 | 45% |
Medicine and Dentistry | 14 | 13% |
Biochemistry, Genetics and Molecular Biology | 12 | 11% |
Physics and Astronomy | 9 | 8% |
Mathematics | 5 | 4% |
Other | 12 | 11% |
Unknown | 10 | 9% |