Objective
Overall, kidney cancers are the eighth most common cancer and the incidence of the most common form (renal cell carcinoma, RCC) has been increasing steadily over the past 30 years. If detected early, surgical removal of RCC can be curative but the prognosis for metastatic disease is very poor. RCC is resistant to conventional therapy and recently introduced targeted therapies form the mainstay of treatment for metastatic disease. The rationale for the use of targeted therapies (e.g. antiangiogenic tyrosine kinase inhibitors) in RCC was derived from functional investigations of the mechanism of tumourigenesis in the rare inherited RCC syndrome von Hippel-Lindau disease. Whilst currently available targeted therapies can extend progression free survival in advanced RCC they are not curative and better treatments are urgently required. Large scale genomic studies of RCC are in progress and will greatly enhance current knowledge of the molecular pathology of RCC. However, experience from other cancers suggests that the results of genomic analyses of cancer are complex and identifying the key “gatekeeper genes” is frequently challenging. ONCOTREAT is based on the hypothesis that (a) the identification of the genetic basis of inherited forms of RCC will highlight those genes and pathways that are critical for tumourigenesis and (b) that selective targeting of cells deficient in inherited RCC gene function will enable advances in the treatment of inherited and sporadic RCC.
The objectives of ONCOTREAT are to:
1. Identify novel inherited RCC genes
2. Generate and characterise human cell line models for inherited RCC genes
3. Identify candidate therapeutic agents that, in in vitro studies, selectively target human cell line models of inherited RCC genes dysfunction
4. Evaluate candidate therapeutic agents identified from in vitro studies in in vivo investigations to identify agents that target cancers deficient in inherited RCC gatekeeper genes.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- medical and health sciencesclinical medicineoncology
- medical and health sciencesbasic medicinepathology
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Call for proposal
ERC-2012-ADG_20120314
See other projects for this call
Funding Scheme
ERC-AG - ERC Advanced GrantHost institution
CB2 1TN Cambridge
United Kingdom