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Regulation of dual specificity phosphatases in breast cancer during initial treatment with Herceptin: a Boolean model analysis

Overview of attention for article published in BMC Systems Biology, April 2018
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Title
Regulation of dual specificity phosphatases in breast cancer during initial treatment with Herceptin: a Boolean model analysis
Published in
BMC Systems Biology, April 2018
DOI 10.1186/s12918-018-0534-5
Pubmed ID
Authors

Petronela Buiga, Ari Elson, Lydia Tabernero, Jean-Marc Schwartz

Abstract

25% of breast cancer patients suffer from aggressive HER2-positive tumours that are characterised by overexpression of the HER2 protein or by its increased tyrosine kinase activity. Herceptin is a major drug used to treat HER2 positive breast cancer. Understanding the molecular events that occur when breast cancer cells are exposed to Herceptin is therefore of significant importance. Dual specificity phosphatases (DUSPs) are central regulators of cell signalling that function downstream of HER2, but their role in the cellular response to Herceptin is mostly unknown. This study aims to model the initial effects of Herceptin exposure on DUSPs in HER2-positive breast cancer cells using Boolean modelling. We experimentally measured expression time courses of 21 different DUSPs between 0 and 24 h following Herceptin treatment of human MDA-MB-453 HER2-positive breast cancer cells. We clustered these time courses into patterns of similar dynamics over time. In parallel, we built a series of Boolean models representing the known regulatory mechanisms of DUSPs and then demonstrated that the dynamics predicted by the models is in agreement with the experimental data. Furthermore, we used the models to predict regulatory mechanisms of DUSPs, where these mechanisms were partially known. Boolean modelling is a powerful technique to investigate and understand signalling pathways. We obtained an understanding of different regulatory pathways in breast cancer and new insights on how these signalling pathways are activated. This method can be generalized to other drugs and longer time courses to better understand how resistance to drugs develops in cancer cells over time.

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Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 29%
Student > Master 5 21%
Researcher 5 21%
Student > Postgraduate 2 8%
Student > Doctoral Student 1 4%
Other 1 4%
Unknown 3 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 29%
Agricultural and Biological Sciences 3 13%
Medicine and Dentistry 3 13%
Pharmacology, Toxicology and Pharmaceutical Science 2 8%
Nursing and Health Professions 1 4%
Other 4 17%
Unknown 4 17%