Summary
Metastasis remains accountable for 9 out of 10 fatalities within cancer disease. However, the mechanisms governing the onset of metastasis are far from being fully understood. Notably, metastases are predominantly clonal and arise from a single cell. 3DSecret will investigate metastasis from a radically new perspective, with the overarching goal of unravelling stochastic patterns at the single-cell level with predictive and prognostic capacity. Critically, defining the hallmarks of metastasis from holistic studies of single circulating tumour cells (CTCs), thus dissecting tumour heterogeneity, has the power to revolutionise cancer treatment and diagnosis. This will pave the way for game-changing discoveries in what is one of the holy grails of modern clinical science. To achieve our goal, 3DSecret will use a set of key enabling technologies including microfluidics, nanosensors, genomics, and artificial intelligence (AI). Microfluidics will drive the isolation of single CTCs from whole blood samples of 60+ metastatic breast cancer patients. These will be grown on-chip to form 3D spheroids, thus allowing comprehensive genomic and transcriptomic studies of single-cell origin while bypassing the errors typically introduced by single-cell genome amplification. The genomic and transcriptomic data will be combined with clinical information, single-cell growth profiles and dynamic metabolomic analyses obtained by the use of nanosensors and SERS, to develop a multimodal AI analytical tool capable of identifying unknown patterns driving metastasis. The bold assumption that there could be stochastic patterns driving metastasis, cancer evolution and malignancy, makes the approach of 3DSecret exceptionally high-risk, high-gain. We are confident that such a breakthrough would lead to a major paradigm shift with significant implications in biology, physics, disruptive technologies such as AI, and critically, in the medical arena and patient care.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101099066 |
| Start date: | 01-01-2023 |
| End date: | 31-12-2026 |
| Total budget - Public funding: | 2 591 050,25 Euro - 2 591 050,00 Euro |
Cordis data
Original description
Metastasis remains accountable for 9 out of 10 fatalities within cancer disease. However, the mechanisms governing the onset of metastasis are far from being fully understood. Notably, metastases are predominantly clonal and arise from a single cell. 3DSecret will investigate metastasis from a radically new perspective, with the overarching goal of unravelling stochastic patterns at the single-cell level with predictive and prognostic capacity. Critically, defining the hallmarks of metastasis from holistic studies of single circulating tumour cells (CTCs), thus dissecting tumour heterogeneity, has the power to revolutionise cancer treatment and diagnosis. This will pave the way for game-changing discoveries in what is one of the holy grails of modern clinical science. To achieve our goal, 3DSecret will use a set of key enabling technologies including microfluidics, nanosensors, genomics, and artificial intelligence (AI). Microfluidics will drive the isolation of single CTCs from whole blood samples of 60+ metastatic breast cancer patients. These will be grown on-chip to form 3D spheroids, thus allowing comprehensive genomic and transcriptomic studies of single-cell origin while bypassing the errors typically introduced by single-cell genome amplification. The genomic and transcriptomic data will be combined with clinical information, single-cell growth profiles and dynamic metabolomic analyses obtained by the use of nanosensors and SERS, to develop a multimodal AI analytical tool capable of identifying unknown patterns driving metastasis. The bold assumption that there could be stochastic patterns driving metastasis, cancer evolution and malignancy, makes the approach of 3DSecret exceptionally high-risk, high-gain. We are confident that such a breakthrough would lead to a major paradigm shift with significant implications in biology, physics, disruptive technologies such as AI, and critically, in the medical arena and patient care.Status
SIGNEDCall topic
HORIZON-EIC-2022-PATHFINDEROPEN-01-01Update Date
31-07-2023
Images
No images available.
Geographical location(s)
Search
Organisations
