Project description
Predictive biomarkers in the treatment of metastatic prostate cancer
Prostate cancer (PC) is among the top five deadliest cancers worldwide. In recent years, several new options for the treatment of metastatic PC have been approved, providing additional therapeutic choices. However, not all patients respond to the treatments, and most of them eventually develop resistance. There is an urgent need for predictive biomarkers to assist in optimal treatment selection, allowing timely changes in the treatment of non-responding patients. The EU-funded PDX-PC project aims to elucidate the molecular mechanisms responsible for tumour cell plasticity associated with treatment response in cases of metastatic PC. Researchers will employ patient-derived xenografts as in vivo models and genomics analysis to understand the molecular evolution of the disease, which will allow them to design more specific and individualised treatments in the future.
Objective
Prostate cancer (PC) is among the top five leading malignancies causing cancer mortality worldwide. Increased prevalence and declined mortality rate have led to an increment in follow-ups with a significant rise in the economic burden. In the last few years, several new options for metastatic disease have been approved leading to clinicians to have multiple choices of therapy sequences. However, not all patients initially respond and most of them eventually develop resistance. The ability of tumour cells to reprogram themselves and survive despite the blocked targets (tumour cell plasticity) may accounts for the absence of durable responses. In addition, the fact that initial treatments may affect the potential benefit of subsequent treatments highlights the need to discover predictive biomarkers for optimal treatment selection, allowing early changes in treatment for non-responding patients.
This multidisciplinary project aims to elucidate the molecular mechanisms responsible for tumour cell plasticity associated to treatment response in metastatic PC. Patient-derived xenografts (PDX) in vivo models will be used, since they preserve molecular heterogeneity and therapeutic response observed in the clinic. They will be treated under different regimens. Tumour tissues will be analysed by RNA sequencing before and after treatment. Bioinformatics analysis will be used to establish molecular signatures of treatment response that will be validated in liquid biopsy (circulating tumour cells and cell free DNA) from metastatic PC patients undergoing different treatments.
PDX-PC will provide a better understanding of the molecular evolution of the disease that will contribute to design more specific and individualized treatments. In the setting of non-curative therapy, the implementation of such molecular findings at clinical practice may help to guide treatment decisions, improve outcomes, and prevent unnecessary side effects and costly therapies in men with metastatic PC.
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 prostate cancer
- social sciences sociology demography mortality
- natural sciences biological sciences genetics DNA
- natural sciences biological sciences genetics RNA transcriptomes
- natural sciences biological sciences molecular biology molecular evolution
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
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.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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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.
(opens in new window) H2020-MSCA-IF-2018
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
08036 BARCELONA
Spain
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.