SYSBIODREZ
SYSTEMS BIOLOGY APPROACH TO PREDICTING OUTCOMES OF LUNG CANCER THERAPIES AND STRATEGIES TO OVERCOME DRUG RESISTANCE IN VITRO
| Coordinatore | CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: Rue Michel -Ange 3 contact info |
| Nazionalità Coordinatore | France [FR] |
| Totale costo | 269˙743 € |
| EC contributo | 269˙743 € |
| 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-2013-IIF |
| Funding Scheme | MC-IIF |
| Anno di inizio | 2014 |
| Periodo (anno-mese-giorno) | 2014-05-01 - 2016-04-30 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE
Organization address
address: Rue Michel -Ange 3 contact info |
FR (PARIS) | coordinator | 269˙743.80 |
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Obiettivo del progetto (Objective)
'There has been extensive research dedicated to identifying predictive biomarkers of tumor sensitivity to ligand-based therapies. Although some biomarkers have emerged, there is still no comprehensive understanding that unifies the observed tumor cell type-specific behaviors, in particular the differential responses to anti-cancer drugs. The collective realization is that no single protein measurement is predictive of therapeutic outcome. Large-scale studies focusing on multiple genetic biomarkers may be partially inadequate given the observed fractional killing of genetically-identical clonal cell populations. The objective of this proposal is to address this deficiency by coupling high-content analyses (dynamic live cell imaging, high-throughput assays) with theoretical and computational methods to provide a global understanding of the origins of tumor cell heterogeneity in response to anti-cancer drugs that target the apoptotic signaling pathway at the receptor level. Ultimately this approach will serve to identify, on a tumor cell type basis, the most predictive set of biomarkers and design optimal therapeutic combinations.'