PRECURSOR-HCC
L’Ente Capofila del progetto è la Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico. Il Responsabile Scientifico del progetto è il Professor Luca Vittorio Carlo Valenti.
| Patologia: | La steatoepatite associata a disfunzione metabolica |
| Area Tematica: | Fisiopatologia endocrino-metabolica |
| Data di Inizio Progetto: | 30.01.2026 |
| Data di Fine Progetto: | 29.01.2029 |
| Finanziamento: | € 1.910.368,00 |
| Partenariato | Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico IRCCS Istituto Clinico Humanitas ASST Grande Ospedale metropolitano Niguarda |
Metabolic dysfunction associated steatotic liver disease (MASLD) is now the leading cause of liver disease leading to cirrhosis, hepatocellular carcinoma (HCC) and increased mortality, representing a looming public health threat. Development on non-invasive biomarkers and effective treatments are main unmet clinical needs for progressive MASLD. Aim of this project will be to pinpoint the mechanisms leading the transition from liver fat accumulation to steatohepatitis, fibrosis and HCC. We hypothesize that alterations in lipid droplets (LDs) biology in liver cells are the precursor to progressive MASLD. To test this, we propose to combine human genetics in well characterized clinical cohorts with disease modelling in human liver organoids (HLOs) and artificial intelligence. Specifically, we will: a) integrate common and rare genetic determinants of MASLD into partitioned polygenic risk scores (pPRS) linking genetic predisposition to specific LDs features with liver-related outcomes; b) create a novel experimental platform for high-throughput LDs screening (morphology, kinetics, composition, transcriptome) through multi-omics, disentangling MASLD genetic diversity; c) integrate results by artificial intelligence to improve risk stratification, yielding novel diagnostic/prognostic tools for cirrhosis and HCC and therapeutic targets. By isolating high-risk MASLD subtypes through distinct LDs pathways, we will enable a precision medicine improving clinical management efficacy.

