Project description
Cancer biomarkers for predicting treatment outcome
Drug effectiveness is often hampered by systemic cytotoxicity. Anti-cancer drugs exhibit adverse effects by damaging normal tissues and organs. Prodrugs that can be activated by specific stimuli to exert their pharmacological effect have emerged as safer options. CP-506 is such a prodrug that is activated by the low oxygen levels of tumours (hypoxia) known to promote cancer aggressiveness and therapy resistance. CP-506 causes DNA damage so tumours defective in DNA repair pathways are at a disadvantage. The mission of the ERC-funded ReverseTheAdvantage project is to develop a solution that can identify tumours that exhibit both hypoxia and defects in DNA damage repair to predict the efficacy of CP-506 treatment.
Objective
Hypoxia-activated prodrugs (HAPs) are a great concept in particular in association therapies more efficient on well-oxygenated cells, such as immunotherapies. CP-506 is a third generation HAP with optimal PK for which we confirmed in more than 20 tumor models that presence of tumor hypoxia is a requisite for prodrug activation. We already had an AI/radiomics-based proprietary IP on a solution to identify hypoxia from standard imaging. Another important determinant for efficacy was the presence of a defective homologous recombination (HRD), a pathway needed to repair the DNA damage of the alkylating warhead of CP-506. A genome-wide mutational scar-based pan-cancer Classifier of HOmologous Recombination Deficiency (CHORD, available open source) is able to detect HRD better as compared to assessing mutation of key genes. It is therefore essential to have a validated software solution integrating both biomarkers. This solution, further developed in this project, will be able to capture intrapatient heterogeneity and make a outcome prediction per patient and per lesion.
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.
- natural sciencescomputer and information sciencessoftware
- natural sciencesbiological sciencesgeneticsDNA
- natural sciencesbiological sciencesgeneticsmutation
- medical and health sciencesclinical medicineoncology
- medical and health sciencesbasic medicineimmunologyimmunotherapy
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsHost institution
6200 MD Maastricht
Netherlands