Objective
The strategic development of accurate biomarkers to predict response to therapy in cancer medicine will enhance clinical outcome and reduce the health economic impact of drug resistant disease. The PREDICT consortium will identify and validate predictive biomarkers for two drugs which have direct anti-tumour cell and anti-angiogenic activity and for which no established predictive biomarkers of tumour response exist: sunitinib, a multi-targeted tyrosine kinase inhibitor, and everolimus, an mTOR pathway inhibitor. Renal cell carcinoma (RCC), a disease sensitive to these agents, will serve as the model tumour type to identify predictive response biomarkers suitable for widespread application across diverse tumour types. PREDICT’s biomarker discovery approach is based on the integration of genomics data from pre-operative RCC therapeutic clinical trials with novel personalised functional genomic screen datasets. We will systematically collect tumour tissue from monotherapy pre-operative window RCC clinical trials of 240 patients treated with everolimus or sunitinib and determine expression profiles, copy number aberrations, and genome-wide exon sequences of tumours before and after drug treatment. We will perform two types of RNA interference drug- and hypoxia-resistance screens: one using reverse transfection of commercial siRNA libraries into previously established RCC cell lines, and one using a novel approach through personalised tumour cDNA derived-shRNA library transduction of ex-vivo cultured autologous tumour cell lines. Bioinformatics integration of these complementary individualised clinical and experimental datasets will enable the rapid and cost efficient identification of predictive biomarkers and simultaneously define molecular mechanisms contributing to intrinsic and acquired drug resistant disease in vivo, yielding additional targets for therapeutic intervention.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- medical and health sciences clinical medicine oncology
- natural sciences biological sciences genetics RNA
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
FP7-HEALTH-2010-two-stage
See other projects for this call
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
2800 KONGENS LYNGBY
Denmark
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.