Objective
In physiological situations, the extracellular matrix (ECM) sequesters cytokines, localizes them, and modulates their signaling. Thus, physiological signaling from cytokines occurs primarily when the cytokines are interacting with the ECM. In therapeutic use of cytokines, however, this interaction and balance have not been respected; rather the growth factors are merely injected or applied as soluble molecules, perhaps in controlled release forms. This has led to modest efficacy and substantial concerns on safety. Here, we will develop a protein engineering design for second-generation cytokines to lead to their super-affinity binding to ECM molecules in the targeted tissues; this would allow application to a tissue site to yield a tight association with ECM molecules there, turning the tissue itself into a reservoir for cytokine sequestration and presentation. To accomplish this, we have undertaken preliminary work screening a library of cytokines for extraordinarily high affinity binding to a library of ECM molecules. We have thereby identified a small peptide domain within placental growth factor-2 (PlGF-2), namely PlGF-2123-144, that displays super-affinity for a number of ECM proteins. Also in preliminary work, we have demonstrated that recombinant fusion of this domain to low-affinity binding cytokines, namely VEGF-A, PDGF-BB and BMP-2, confers super-affinity binding to ECM molecules and accentuates their functionality in vivo in regenerative medicine models. In the proposed project, based on this preliminary data, we will push forward this protein engineering design, pursuing super-affinity variants of VEGF-A and PDGF-BB in chronic wounds, TGF-beta3 and CXCL11 in skin scar reduction, FGF-18 in osteoarthritic cartilage repair and CXCL12 in stem cell recruitment to ischemic cardiac muscle. Thus, we seek to demonstrate a fundamentally new concept and platform for second-generation growth factor protein engineering.
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.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteins
- medical and health sciencesmedical biotechnologycells technologiesstem cells
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Call for proposal
ERC-2013-ADG
See other projects for this call
Funding Scheme
ERC-AG - ERC Advanced GrantHost institution
1015 Lausanne
Switzerland