Objective
The efficacy of standard cancer therapies varies, and while some patients respond to a particular treatment, other patients do not gain any benefit. In response, an era of individualized cancer treatments is emerging which are based on the identification of biomarkers that characterize the state of a tumor. Many solid tumors (e.g. breast cancers and sarcomas) stiffen as they grow within a normal tissue. Tumor stiffening is a known factor leading to compromised efficacy of therapeutics. Repurposing drugs in order to alleviate tumor stiffness before the initiation of therapy has been tested in preclinical studies and has recently made it to the clinic. Despite recent success of these strategies, optimization of their application is understudied. Here, we aim to harness the power of deep learning (DL) methods in order to construct a robust biomarker based on ultrasound shear wave elastography (SWE). The biomarker will aim to: (i) predict the tumors response to treatment with chemo- and immuno-therapy and (ii) monitor treatment outcomes, in the case of strategies that target tumor stiffness. The project will capitalize on the existing strengths of the applicant in medical image processing and DL and the expertise of the host in tumor mechanopathology and in vivo experiments. In past experiments, the host acquired a large number of SWE tumor data, which will enable the development of the DL biomarker. Through the experimental part of the project, additional data on murine cancer models will be acquired enabling the validation of the biomarker. Formulation of the developed DL-derived biomarker in a user-friendly software will allow for potential clinical translation and further exploitation through IPR. The applicant will acquire new knowledge in the fields of cancer therapy, tumor biology and in vivo experimental design. The attained knowledge and skills will be instrumental to the applicants ambition to lead the field of artificial intelligence in biomedicine.
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.
- natural sciences computer and information sciences software
- medical and health sciences clinical medicine oncology
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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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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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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) HORIZON-MSCA-2021-PF-01
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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.
1678 Nicosia
Cyprus
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.