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          Institute: MPI für Evolutionsbiologie     Collection: Research Group Evolutionary Theory     Display Documents

ID: 576466.0, MPI für Evolutionsbiologie / Research Group Evolutionary Theory
Dynamics of resistance development to imatinib under increasing selection pressure: a combination of mathematical models and in vitro data
Authors:Werner, Benjamin; Lutz, David; Brümmendorf, Tim H.; Traulsen, Arne; Balabanov, Stefan
Date of Publication (YYYY-MM-DD):2011-12-22
Title of Journal:PLoS ONE
Issue / Number:12
Sequence Number of Article:e28955
Review Status:not specified
Audience:Not Specified
Abstract / Description:In the last decade, cancer research has been a highly active and rapidly evolving scientific area. The ultimate goal of all efforts is a better understanding of the mechanisms that discriminate malignant from normal cell biology in order to allow the design of molecular targeted treatment strategies. In individual cases of malignant model diseases addicted to a specific, ideally single oncogene, e.g. Chronic myeloid leukemia (CML), specific tyrosine kinase inhibitors (TKI) have indeed been able to convert the disease from a ultimately life-threatening into a chronic disease with individual patients staying in remission even without treatment suggestive of operational cure. These developments have been raising hopes to transfer this concept to other cancer types. Unfortunately, cancer cells tend to develop both primary and secondary resistance to targeted drugs in a substantially higher frequency often leading to a failure of treatment clinically. Therefore, a detailed understanding of how cells can bypass targeted inhibition of signaling cascades crucial for malignant growths is necessary. Here, we have performed an in vitro experiment that investigates kinetics and mechanisms underlying resistance development in former drug sensitive cancer cells over time in vitro. We show that the dynamics observed in these experiments can be described by a simple mathematical model. By comparing these experimental data with the mathematical model, important parameters such as mutation rates, cellular fitness and the impact of individual drugs on these processes can be assessed. Excitingly, the experiment and the model suggest two fundamentally different ways of resistance evolution, i.e. acquisition of mutations and phenotype switching, each subject to different parameters. Most importantly, this complementary approach allows to assess the risk of resistance development in the different phases of treatment and thus helps to identify the critical periods where resistance development is most likely to occur.
External Publication Status:published
Document Type:Article
Communicated by:Brigitte Lechner
Affiliations:MPI für Evolutionsbiologie/AG Evolutionstheorie
External Affiliations:Department of Oncology, Hematology, Bone Marrow Transplantation and Pneumology, Hubertus Wald Tumor Zentrum, University Hospital Eppendorf, Hamburg, Germany; Department Hematology and Oncology, RWTH Medical School, Aachen, Germany
Identifiers:ISSN:1932-6203 (online) [ID-No:1]
DOI:10.1371/journal.pone.0028955 [ID-No:2]
LOCALID:2887/S 39231 [Listen-Nummer/S-Nummer]
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