A New Mathematical Formula For Cancer Progression
Our understanding of the progression of cancer has long been based on streamlined models where cancer is driven by mutations in only a few genes. Niko Beerenwinkel et al. show how tumor progression can be driven by hundreds of genes. As many as 20 different mutated genes might be responsible for driving an individual tumor's development.
Beerenwinkel et al. used a case of colon cancer to derive their results. Cancer progression proceeds stochastically from a single genetically altered cell to billions of invasive cells through a series of clonal expansions. According to their model, cancer progression is driven by mutations in many genes, each of which confers only a small selective advantage. It was found that the time it takes for a benign tumor to transform into a malignant tumor is dominated by the selective advantage per mutation and by the number of cancer genes, whereas tumor size and mutation rate have smaller impacts.
This new model could help explain the large amount of variation between individual tumors that has long puzzled researchers and clinicians. The increasing amount of high-throughput molecular data that is being generated has resulted in new challenges for understanding complex biosystems such as cancer. New mathematical models like this one can provide unique insights that simplify interpretation and at the same time answer important biomedical questions.
CITATION: Beerenwinkel N, Antal T, Dingli D, Traulsen A, Kinzler KW, et al. (2007) Genetic progression and the waiting time to cancer. PLoS Comput Biol 3(11): e225. doi:10.1371/journal.pcbi.0030225
Please click here
Disclaimer
This press release refers to an upcoming article in PLoS Computational Biology. The release is provided by the article authors. Any opinions expressed in this release or article are the personal views of the journal staff and/or article contributors, and do not necessarily represent the views or policies of PLoS. PLoS expressly disclaims any and all warranties and liability in connection with the information found in the releases and articles and your use of such information.
About PLoS Computational Biology
PLoS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained by the authors. The Public Library of Science uses the Creative Commons Attribution License.
http://www.ploscompbiol.org
About the Public Library of Science
The Public Library of Science (PLoS) is a non-profit organization of scientists and physicians committed to making the world's scientific and medical literature a freely available public resource.
Public Library of Science
185 Berry Street, Suite 3100
San Francisco, CA 94107
USA
O nouã formulã matematicã pentru cancer progresie - A New Mathematical Formula For Cancer Progression - articole medicale engleza - startsanatate