Lifetime Metabolomics for Paediatric Liver Cancer Detection and Therapy Assessment Using Organ-on-Chip Platforms

Descripción del proyecto

Plataforma para la metabolómica personalizada de enfermedades, desde el diagnóstico hasta el tratamiento

El cuerpo produce continuamente una gran variedad de pequeñas moléculas, o metabolitos, durante el catabolismo y anabolismo moleculares. Los metabolitos funcionan como marcadores relevantes de la salud y la enfermedad. Los métodos actuales para estudiar la metabolómica —el estudio a gran escala de los metabolitos— a nivel intracelular e intercelular en el cáncer para promover la medicina personalizada son limitados. En el proyecto LIFETIME, financiado por el Consejo Europeo de Investigación, se pretende desarrollar una plataforma de órgano en un chip para rastrear la firma metabolómica de una enfermedad, desde su aparición en el paciente «in vivo» hasta su tratamiento. Utilizando el hepatoblastoma como modelo de desarrollo, la plataforma posibilitará hacer mediciones temporales paralelas y repetibles, revelando detalles sobre los fenotipos tumorales y el microentorno tumoral a lo largo del tiempo y posibilitando la identificación de nuevos biomarcadores.

Objetivo

"Understanding cancer metabolism at the individual patient level is central to making accurate early-stage diagnoses and providing effective patient-specific treatments. While some methods do exist to study intra-cell metabolomics and inter-cell metabolic flux alterations (e.g. PET, MRI), their scalability and sensitivity is limited, hindering reliable investigations long-term.
LIFETIME aims to develop a single platform for ""lifetime metabolomics"", where the metabolic fingerprint of a disease is traced throughout patient onset in vivo, analysis ex vivo, and through to treatment. Technologically this involves rapid metabolomic profiling of the cancer model, using microfluidic 3D-cell-cultures in organ-on-chip (OoC) structures and magnetic resonance spectroscopic imaging (MRSI). Scientifically, the disease-specific case study chosen is hepatoblastoma (HB), the most common liver cancer in children, where the platform could improve patient survival rate and quality of life. Metabolic contrast in three phenotypes of HB mouse models (intrahepatic, intravenous, subcutaneous) and their OoC counterparts will be assessed.
A unique benefit of the platform will be its capability for parallel, repeatable measurements on samples to track therapeutic-induced metabolic alterations over time. This will unveil tumours' detailed molecular phenotypes and shed light on their correlation with tumour heterogeneity and interactions within tumour microenvironment.
Overall, LIFETIME will enable the definition of new reliable biomarkers of HB that propel the development of targeted therapies. If successful, the scalability of the platform will hold the important ability to bridge in vivo and in vitro assessment, from biopsy-derived cell cultures (parallelised screening) to patients (correlating with current clinical MRSI). Long term, LIFETIME will empower assessment of the benefits and constraints of OoC technology in cancer and other aggressive disease research."