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Evolutionary dynamics of chronic myeloid leukemia

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons56973

Traulsen,  Arne
Research Group Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Zitation

Dingli, D., Traulsen, A., Lenaerts, T., & Pacheco, J. M. (2010). Evolutionary dynamics of chronic myeloid leukemia. Genes & Cancer, 1(4), 309-315. doi:10.1177/1947601910371122.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-D4A4-0
Zusammenfassung
Cancer is an evolutionary process that arises due to mutations and expands through the selection of clones with higher reproductive success that will outcompete their peers. Most tumors require many mutations to explain the cancer phenotype, making it difficult to identify the gene(s) that confer the reproductive fitness to the clone. Moreover, the impact of any oncogene is context dependent: it can increase the fitness of particular stages of cell differentiation but not other stages. In addition, the fitness advantage of an oncogene is not irreversible: sometimes it can be reversed with targeted therapy, for example. The understanding of these dynamical processes and their consequences may be greatly simplified when addressed from an evolutionary perspective. Using the dynamics of chronic myeloid leukemia—perhaps the best understood human neoplasm—as an example, we show how three fundamental evolutionary behaviors provide insights into the dynamics of this disease: (1) BCR-ABL does not affect the reproductive success of any cell within the stem cell pool (resulting therefore in neutral drift), (2) BCR-ABL expression gives a fitness (selective) advantage to progenitor cells, and (3) imatinib therapy reduces the fitness of progenitor cells expressing the oncogene (selective disadvantage) and consequently leads to significant reductions in disease burden. These three different evolutionary dynamics scenarios based on the interpretation of mutation and gene expression as potentially leading to a fitness imbalance of cell populations clearly explain the course of the disease, providing as such a better grasp of cancer dynamics and the role of related therapies.