Objective
"In non-small cell lung cancer (NSCLC), approximately 80% of patients have a poor response or develop resistance to current immunotherapies (IT), highlighting a critical need for more effective treatments. To date, most ITs focus on targeting cancer or immune cells, often overlooking endothelial cells (ECs), the body's largest organ. In the running ERC Adv Grant project MystIMEC (#101055155), we demonstrated the immunosuppressive nature of tumor ECs and their pathobiological role in tumor progression. With up to 90% of new drug candidates failing in clinical trials, often due to suboptimal target selection, the host lab has taken a fundamentally different approach to discovering novel therapeutic targets. Leveraging cutting-edge in-house developed AI and gene prioritization tools together with EC-selective lipid nanoparticle-based genetic silencing in a mouse lung tumor model, we discovered and validated 26 previously unexplored immunosuppressive genes (with poor functional annotation, ca 1/3 of human coding genome) as candidate therapeutic targets specific to ECs: silencing these genes promotes anti-tumor immune responses and reduces tumor growth. This ERC-PoC proposal builds further on these findings, aiming to develop nanobody (Nb) therapeutics for three promising targets with the greatest therapeutic efficacy. These targets are either secreted or membrane-exposed and therefore amenable to Nb-based inhibition, a treatment modality successfully used in the clinic. The results will provide the first Proof-of-Concept that our visionary approach to discover and validate unexplored immunosuppressive genes is an efficient, innovative, game-changing strategy. After generating Nbs, we will screen for the top two candidates with the strongest neutralizing effects in vitro (amongst other criteria). Finally, as Proof-of-Concept, the two selected Nbs will be validated in an in vivo lung tumor model for their efficacy to enhance anti-tumor immunity and to reduce tumor growth."
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 medicineoncologylung cancer
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesbasic medicineimmunologyimmunotherapy
- natural sciencesbiological sciencesgeneticsgenomes
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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
9052 ZWIJNAARDE - GENT
Belgium