Summary
The growing number of classes of RNA therapeutics, including siRNA, mRNA and RNA components of the CRISPR/Cas9 machinery, hold the promise of providing new treatment possibilities for almost any disease. However, these interventions require delivery of therapeutic RNA to their final intracellular targets in diseased cells, and delivery efficiency by current RNA nanocarriers is unsatisfactory.
Endogenous nanoparticles called extracellular vesicles (EVs) have emerged as promising novel RNA delivery systems, due to their intrinsic ability to transfer biological cargo between cells in a selective manner. In fact, with my ERC StG, I have shown that EVs outperform synthetic carriers in terms of RNA delivery efficiency. However, EVs are a heterogeneous population of vesicles that differ in their targeting and cargo delivery properties, which forms a hurdle for the design of EV-based delivery systems. As methods to separate EV subpopulations and study their characteristics individually are lacking, a fundamentally different approach to address this hurdle is necessary.
The aim of UNRAVEL is to reveal how variations in EV composition lead to specialized subpopulations with unique delivery features. Using this knowledge, I will develop the first biomimetic class of EV-inspired synthetic RNA delivery systems. I will pursue three objectives:
1) Identify EV subpopulations with unique targeting and RNA delivery properties using a novel EV barcoding strategy
2) Define these EV subpopulations in terms of unique surface properties, intracellular trafficking and cargo release
3) Apply this knowledge to improve synthetic RNA delivery systems by incorporating molecular features from EV subpopulations
This work will significantly advance our understanding of the natural targeting and RNA delivery mechanisms of EV subpopulations and may result in a new generation RNA delivery system based on EV mimetics. In turn, this will allow more widespread application of RNA therapeutics.
Endogenous nanoparticles called extracellular vesicles (EVs) have emerged as promising novel RNA delivery systems, due to their intrinsic ability to transfer biological cargo between cells in a selective manner. In fact, with my ERC StG, I have shown that EVs outperform synthetic carriers in terms of RNA delivery efficiency. However, EVs are a heterogeneous population of vesicles that differ in their targeting and cargo delivery properties, which forms a hurdle for the design of EV-based delivery systems. As methods to separate EV subpopulations and study their characteristics individually are lacking, a fundamentally different approach to address this hurdle is necessary.
The aim of UNRAVEL is to reveal how variations in EV composition lead to specialized subpopulations with unique delivery features. Using this knowledge, I will develop the first biomimetic class of EV-inspired synthetic RNA delivery systems. I will pursue three objectives:
1) Identify EV subpopulations with unique targeting and RNA delivery properties using a novel EV barcoding strategy
2) Define these EV subpopulations in terms of unique surface properties, intracellular trafficking and cargo release
3) Apply this knowledge to improve synthetic RNA delivery systems by incorporating molecular features from EV subpopulations
This work will significantly advance our understanding of the natural targeting and RNA delivery mechanisms of EV subpopulations and may result in a new generation RNA delivery system based on EV mimetics. In turn, this will allow more widespread application of RNA therapeutics.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101125348 |
| Start date: | 01-02-2025 |
| End date: | 31-01-2030 |
| Total budget - Public funding: | 2 000 000,00 Euro - 2 000 000,00 Euro |
Cordis data
Original description
The growing number of classes of RNA therapeutics, including siRNA, mRNA and RNA components of the CRISPR/Cas9 machinery, hold the promise of providing new treatment possibilities for almost any disease. However, these interventions require delivery of therapeutic RNA to their final intracellular targets in diseased cells, and delivery efficiency by current RNA nanocarriers is unsatisfactory.Endogenous nanoparticles called extracellular vesicles (EVs) have emerged as promising novel RNA delivery systems, due to their intrinsic ability to transfer biological cargo between cells in a selective manner. In fact, with my ERC StG, I have shown that EVs outperform synthetic carriers in terms of RNA delivery efficiency. However, EVs are a heterogeneous population of vesicles that differ in their targeting and cargo delivery properties, which forms a hurdle for the design of EV-based delivery systems. As methods to separate EV subpopulations and study their characteristics individually are lacking, a fundamentally different approach to address this hurdle is necessary.
The aim of UNRAVEL is to reveal how variations in EV composition lead to specialized subpopulations with unique delivery features. Using this knowledge, I will develop the first biomimetic class of EV-inspired synthetic RNA delivery systems. I will pursue three objectives:
1) Identify EV subpopulations with unique targeting and RNA delivery properties using a novel EV barcoding strategy
2) Define these EV subpopulations in terms of unique surface properties, intracellular trafficking and cargo release
3) Apply this knowledge to improve synthetic RNA delivery systems by incorporating molecular features from EV subpopulations
This work will significantly advance our understanding of the natural targeting and RNA delivery mechanisms of EV subpopulations and may result in a new generation RNA delivery system based on EV mimetics. In turn, this will allow more widespread application of RNA therapeutics.
Status
SIGNEDCall topic
ERC-2023-COGUpdate Date
22-11-2024
Images
No images available.
Geographical location(s)
