1. Regulation of dual specificity phosphatases in breast cancer during initial treatment with Herceptin: a Boolean model analysis
- Author
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Jean-Marc Schwartz, Lydia Tabernero, Ari Elson, and Petronela Buiga
- Subjects
0301 basic medicine ,Cell signaling ,Systems biology ,DUSPs ,Antineoplastic Agents ,Breast Neoplasms ,Models, Biological ,03 medical and health sciences ,Breast cancer ,Herceptin ,Structural Biology ,Cell Line, Tumor ,Dual-specificity phosphatase ,medicine ,Cluster Analysis ,Humans ,Initial treatment ,Kinase activity ,skin and connective tissue diseases ,lcsh:QH301-705.5 ,Molecular Biology ,biology ,Research ,Applied Mathematics ,Boolean model ,Trastuzumab ,medicine.disease ,Computer Science Applications ,Gene Expression Regulation, Neoplastic ,030104 developmental biology ,lcsh:Biology (General) ,Modeling and Simulation ,Cancer cell ,Cancer research ,biology.protein ,Dual-Specificity Phosphatases ,Function (biology) - Abstract
Background 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. Results 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. Conclusions 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. Electronic supplementary material The online version of this article (10.1186/s12918-018-0534-5) contains supplementary material, which is available to authorized users. more...
- Published
- 2018
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