Objective
Several new therapies have been recently approved for the treatment of castration-resistant prostate cancer (CRPC) but drug resistance invariably develops and eventually causes death. Currently, the knowledge on the molecular mechanisms underlying resistance is limited; this is an area of urgent unmet medical need to allow improved treatments for patients. This study proposes a multidisciplinary effort led by the Marie-Curie fellow that will aim to identify genomic aberrations associated with drug resistance. We hypothesize that disseminated circulating tumor cells (CTCs) and DNA (CTD) from blood and plasma will contain real-time genetic information about the changes occurring in the tumor and can be used as an early biomarker of progression or responsiveness to treatment, with minimal invasiveness and discomfort to the patient. Firstly, next generation sequencing data of fresh-frozen CRPC biopsies collected prior to, and after progression on abiraterone and/or enzalutamide treatment and patient-matched archival hormone therapy-naïve samples collected at The Institute of Cancer Research, will be analyzed together with the computational oncology group at University of Trento (PI: Dr Demichelis). Second, single CTC isolation will be performed using a research protocol that is novel and developed in collaboration with Dr Terstappen (University of Twente) and Dr Tibbe (biotechnology company Aquamarijn) in the setting of the FP7 grant “CTCtrap”. The fellow aims to genetically characterize CTCs and CTD over time by high-throughput targeted deep sequencing to elucidate the processes underlying metastasis and evolution of resistance in prostate cancer. Thirdly, the fellow will perform studies on selected genomic aberrations to functionally confirm their role. The results could identify novel therapeutic targets and inform on the development of assays to select patients for a specific treatment.
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 medicineoncologyprostate cancer
- natural sciencesbiological sciencesgeneticsDNA
- medical and health sciencesbasic medicinepharmacology and pharmacydrug resistance
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Topic(s)
Call for proposal
FP7-PEOPLE-2013-IEF
See other projects for this call
Funding Scheme
MC-IEF - Intra-European Fellowships (IEF)Coordinator
SW7 3RP London
United Kingdom