Objective
Neuroblastoma are pediatric tumors that respond poorly to chemotherapy and have a very poor prognosis. To improve treatment options, a global development towards precision medicine is ongoing. This strongly focusses on molecular genetic target identification in tumors and subsequent assigning patients to the best trials according to their molecular profile. Still it is difficult to predict which patients will benefit from these targeted compounds. In addition, if tumors do respond to single compound targeted therapy, they almost always relapse. These tumor evolution processes could be prevented by simultaneous intervention in different activated tumor pathways.
We now want to study how we can select patients that will most likely respond to a targeted compound and what combinations of targeted compounds are most effective? This can’t be tested in a clinical setting since the number of neuroblastoma patients that can be included in Phase1/2 trials is very small. Recent research shows that tumor organoids mimic human tumors and can effectively be used as xenograft in nude mice as well. These in vitro and in vivo models could be used as an alternative selection system for optimal combination treatment in a personalized approach.
The overall aim is now to test if combinations of targeted compounds can cause complete remission in neuroblastoma organoid model systems to select combination treatment options for personalized clinical trials
For this purpose we will generate neuroblastoma organoids that properly represents the complexity and heterogeneity of individual tumors and build a repository that represents the various subtypes of neuroblastoma tumors. We will identify synergistic compound combinations that are effective in neuroblastoma tumors that are characterized by specific molecular genetic aberrations. Thereby we will build an efficient pipeline to generate personalized models that can be used in precision medicine programs to perform compound validation.
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.
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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.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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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.
ERC-STG - Starting Grant
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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) ERC-2016-STG
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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.
3584CS Utrecht
Netherlands
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.