Academic Journal
Network quantification of EGFR signaling unveils potential for targeted combination therapy
| Title: | Network quantification of EGFR signaling unveils potential for targeted combination therapy |
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| Authors: | Bertram Klinger, Anja Sieber, Raphaela Fritsche‐Guenther, Franziska Witzel, Leanne Berry, Dirk Schumacher, Yibing Yan, Pawel Durek, Mark Merchant, Reinhold Schäfer, Christine Sers, Nils Blüthgen |
| Source: | Molecular Systems Biology, Vol 9, Iss 1, Pp 1-14 (2013) |
| Publisher Information: | Springer Nature, 2013. |
| Publication Year: | 2013 |
| Collection: | LCC:Biology (General) LCC:Medicine (General) |
| Subject Terms: | cancer, EGFR signaling, mathematical modeling, modular response analysis, signal transduction, Biology (General), QH301-705.5, Medicine (General), R5-920 |
| More Details: | Abstract The epidermal growth factor receptor (EGFR) signaling network is activated in most solid tumors, and small‐molecule drugs targeting this network are increasingly available. However, often only specific combinations of inhibitors are effective. Therefore, the prediction of potent combinatorial treatments is a major challenge in targeted cancer therapy. In this study, we demonstrate how a model‐based evaluation of signaling data can assist in finding the most suitable treatment combination. We generated a perturbation data set by monitoring the response of RAS/PI3K signaling to combined stimulations and inhibitions in a panel of colorectal cancer cell lines, which we analyzed using mathematical models. We detected that a negative feedback involving EGFR mediates strong cross talk from ERK to AKT. Consequently, when inhibiting MAPK, AKT activity is increased in an EGFR‐dependent manner. Using the model, we predict that in contrast to single inhibition, combined inactivation of MEK and EGFR could inactivate both endpoints of RAS, ERK and AKT. We further could demonstrate that this combination blocked cell growth in BRAF‐ as well as KRAS‐mutated tumor cells, which we confirmed using a xenograft model. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1744-4292 |
| Relation: | https://doaj.org/toc/1744-4292 |
| DOI: | 10.1038/msb.2013.29 |
| Access URL: | https://doaj.org/article/a4ed5dbe243d4ea28f53fa9649700665 |
| Accession Number: | edsdoj.4ed5dbe243d4ea28f53fa9649700665 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 17444292 |
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| DOI: | 10.1038/msb.2013.29 |
| Published in: | Molecular Systems Biology |
| Language: | English |