Descripción del proyecto
Inteligencia artificial para identificar patrones de metástasis del cáncer
La propagación del cáncer a lugares distantes del organismo, también conocida como «metástasis», es en gran medida responsable de la mortalidad relacionada con el cáncer. Aunque los mecanismos subyacentes a la formación de metástasis no se han dilucidado por completo, las células tumorales circulantes (CTC) parecen estar implicadas en este proceso. El equipo del proyecto 3DSecret, financiado por el Consejo Europeo de Innovación, pretende identificar patrones estocásticos en la formación de metástasis. Los investigadores aislarán CTC de pacientes con cáncer de mama, las cultivarán en esferoides y realizarán análisis transcriptómicos, metabolómicos y genómicos. La labor contribuirá a comprender la heterogeneidad tumoral y, junto con la información clínica, conducirá al desarrollo de una herramienta de inteligencia artificial capaz de identificar patrones de metástasis.
Objetivo
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.
Ámbito científico
- natural sciencescomputer and information sciencesartificial intelligence
- natural sciencesphysical sciencesclassical mechanicsfluid mechanicsmicrofluidics
- natural sciencesbiological sciencescell biologycell metabolism
- medical and health sciencesclinical medicineoncologybreast cancer
- natural sciencesbiological sciencesgeneticsgenomes
Palabras clave
Programa(s)
- HORIZON.3.1 - The European Innovation Council (EIC) Main Programme
Convocatoria de propuestas
HORIZON-EIC-2022-PATHFINDEROPEN-01
Consulte otros proyectos de esta convocatoriaRégimen de financiación
HORIZON-EIC - HORIZON EIC GrantsCoordinador
4715-330 Braga
Portugal