Descripción del proyecto
Motivos de tejidos funcionales en el cáncer de mama metastásico
El cáncer es una enfermedad heterogénea favorecida por la interacción dinámica de los compartimentos de células tumorales, inmunitarias y estromales. Por lo tanto, es importante caracterizar la complejidad de la enfermedad para cada individuo a fin de desarrollar soluciones de medicina de precisión. El proyecto Precision Motifs, financiado con fondos europeos, trabajará para obtener un método de procesamiento de imágenes 3D altamente multiplexado que identifique motivos funcionales de tejidos en el cáncer de mama metastásico. Estos motivos, identificados mediante modelización de redes probabilísticas, se utilizarán para desarrollar un novedoso sistema de clasificación de enfermedades que se aplicará a la toma de decisiones de terapias personales en pacientes con cáncer. En combinación con datos clínicos, servirán como forma de clasificación de enfermedades y se espera que faciliten las decisiones relativas a los tratamientos para pacientes con cáncer.
Objetivo
Cancer precision medicine aims to bring the right drug (or right drug combination) to the right person. To achieve this, the molecular cause of an individual’s disease must be identified and a treatment chosen that targets that cause to remedy the dysfunction. Tumors are dynamic ecosystems with high heterogeneity in tumor, immune, and stromal cell compartments. This complexity is the main obstacle to implementation of precision medicine. Consequently, approaches that rationalize and use tumor ecosystems for precision medicine are needed. To enable this, I propose to establish the concept of functional tissue motif, a multiscale network representation of multi-cellular assemblies that executes a definable set of anti-tumor or pro-tumor functional outputs. The utility of functional tissue motifs for precision medicine will be demonstrated in the context of metastatic breast cancer, which causes nearly 450,000 cancer-associated deaths each year. We will develop a highly multiplexed 3D tissue imaging approach with unprecedented throughput that provides subcellular resolution to analyze a large cohort of primary and matched metastatic tumors. We will then use viable tumor samples ex vivo to systematically perturb intra-cellular and inter-cellular network wiring using approved drugs, and the drug effects will be measured by highly multiplexed imaging. Functional tissue motifs will be identified using community and geostatistical methods and probabilistic network modeling. Analysis of functional tissue motifs in the light of the clinical data will be used to derive a novel classification system and to identify vulnerabilities in metastatic breast tumors. These vulnerabilities will be validated in follow-up experiments and in a clinical study. Given their focus on functional output, information content and versatility, functional tissue motifs promise to be a powerful concept and should enable to point to appropriate treatments, and inform development of new therapies.
Ámbito científico
Palabras clave
Programa(s)
Régimen de financiación
ERC-COG - Consolidator GrantInstitución de acogida
8006 Zurich
Suiza