Summary
Glioblastoma multiforme (GBM) is the most common type of brain tumor found in adults and is fatal in all cases. A very promising therapeutic approach for GBM is the use of oncolytic viruses (OVs) that selectively infect, replicate in, and destroy tumor cells, while sparing the surrounding normal cells. Nevertheless, to achieve successful oncolytic virotherapy, frequent non-invasive monitoring of the process must be performed. This is crucial for gaining a better understanding of the interactions between the virus and its tumor-host and predicting a therapeutic response. Thus, the development of a non-invasive method, capable of accurately quantifying the location and extent of the viral spread in the tumor is highly required and is of great importance. Accordingly, the main research goal of this action is to develop a magnetic resonance imaging (MRI)- based method for accurate, quantitative, and rapid imaging of OVs delivery, and spread in clinically relevant tumor models. The devised interdisciplinary methodology includes: genetically modifying the therapeutic virus to be detectable in MRI; developing machine learning methods to increase the speed, specificity, and sensitivity in image-monitoring the virus; and evaluating the established methods using mice models of brain tumor therapy. The allocated training and research environment is optimal for achieving the proposal goals: an outgoing phase at Harvard Medical School, a secondment at a leading clinical MRI company (Insightec), enhancing translation potential, and a return phase at a leading university (Technion), ensuring the transport of knowledge back to the EU. The envisioned technology could be expanded to various additional clinical conditions, and its dissemination could improve patient care. The unique skill set to be acquired by the experienced researcher, would allow claiming a distinct niche of knowledge, increasing competency to a tenure-track position, and a research career in the EU.
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Web resources: | https://cordis.europa.eu/project/id/836752 |
Start date: | 01-11-2019 |
End date: | 30-06-2023 |
Total budget - Public funding: | 269 998,08 Euro - 269 998,00 Euro |
Cordis data
Original description
Glioblastoma multiforme (GBM) is the most common type of brain tumor found in adults and is fatal in all cases. A very promising therapeutic approach for GBM is the use of oncolytic viruses (OVs) that selectively infect, replicate in, and destroy tumor cells, while sparing the surrounding normal cells. Nevertheless, to achieve successful oncolytic virotherapy, frequent non-invasive monitoring of the process must be performed. This is crucial for gaining a better understanding of the interactions between the virus and its tumor-host and predicting a therapeutic response. Thus, the development of a non-invasive method, capable of accurately quantifying the location and extent of the viral spread in the tumor is highly required and is of great importance. Accordingly, the main research goal of this action is to develop a magnetic resonance imaging (MRI)- based method for accurate, quantitative, and rapid imaging of OVs delivery, and spread in clinically relevant tumor models. The devised interdisciplinary methodology includes: genetically modifying the therapeutic virus to be detectable in MRI; developing machine learning methods to increase the speed, specificity, and sensitivity in image-monitoring the virus; and evaluating the established methods using mice models of brain tumor therapy. The allocated training and research environment is optimal for achieving the proposal goals: an outgoing phase at Harvard Medical School, a secondment at a leading clinical MRI company (Insightec), enhancing translation potential, and a return phase at a leading university (Technion), ensuring the transport of knowledge back to the EU. The envisioned technology could be expanded to various additional clinical conditions, and its dissemination could improve patient care. The unique skill set to be acquired by the experienced researcher, would allow claiming a distinct niche of knowledge, increasing competency to a tenure-track position, and a research career in the EU.Status
CLOSEDCall topic
MSCA-IF-2018Update Date
28-04-2024
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