ONCOPROTNET
Dynamic protein interaction networks in cancer
| Coordinatore | UNIVERSITY OF SOUTHAMPTON
Organization address
address: Highfield contact info |
| Nazionalità Coordinatore | United Kingdom [UK] |
| Totale costo | 100˙000 € |
| EC contributo | 100˙000 € |
| Programma | FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013) |
| Code Call | FP7-PEOPLE-2012-CIG |
| Funding Scheme | MC-CIG |
| Anno di inizio | 2013 |
| Periodo (anno-mese-giorno) | 2013-08-01 - 2017-07-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
UNIVERSITY OF SOUTHAMPTON
Organization address
address: Highfield contact info |
UK (SOUTHAMPTON) | coordinator | 100˙000.00 |
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Obiettivo del progetto (Objective)
'The inappropriate activity of signaling pathways and activation of gene-expression programs is a primary driver of transformation in cancer cells. In turn, dis-regulation of signaling pathways in cancer cells is frequently caused by mutations in important oncoproteins, which may alter protein expression, structure or function. In addition, increasing evidence shows that oncoprotein mutations may alter the interactions of oncoproteins with other proteins, causing wide-spread perturbations to the network of proteins in the cell. Although high-throughput sequencing techniques are rapidly identifying large volumes of mutations from tumor samples, our understanding of how these mutations transform cancer cells, and more specifically how they perturb protein-protein interactions is lagging behind. This proposal describes novel proteomics and computational techniques directed at understanding how mutations in important oncoproteins disrupt or alter protein-protein interactions, and how these alterations lead in turn to dis-regulation of signaling pathways and gene-expression programs. The work described here focuses on oncoproteins in the Wnt signaling pathway, but importantly, the techniques described are widely applicable, and have the potential to provide a powerful means of elucidating protein interaction networks in cancer cells. The broader impacts of this work include the potential identification of novel colorectal cancer therapeutic targets as well as mapping protein networks in cancer cells, so that in future the wider effects of therapeutics in the cancer cell can be better understood.'