Alcohol-related hepatocellular carcinoma (ALD-HCC) is, in Europe, the leading cause of liver cancer (2nd most common cause of cancer-related death worldwide, affecting both men and women). ALD-HCC has a median 5-year survival rate of 15%. Yet, the prognosis is driven by the tumour stage, with curative options providing a 5-year survival exceeding 70% for early-stage HCC (<20% of cases). Therefore, interventions aiming to improve prevention and early detection are key. ALD-HCC results from the interplay between environmental determinants and genetic variations. A comprehensive characterisation of environmental factors (e.g. diet, lifestyle) linked to ALD-HCC is still lacking. We recently performed the 1st genome-wide association study of ALD-HCC and identified predisposing genetic variations. However, their role on alcohol-related liver carcinogenesis needs clarification and the genetic architecture of ALD-HCC remains mostly unknown. GENIAL brings together partners with unique expertise in clinical hepatology, single-cell and spatial multi-omics, artificial intelligence (AI) and communication and dissemination capacities. Our aim is to 1) portray genetic and environmental determinants promoting ALD-HCC; 2) evaluate how they interact at cellular level in human samples and preclinical models to get novel insights into liver carcinogenesis, and identify chemopreventive targets; and 3) assess how these determinants modulate the ALD-HCC risk in prospective cohorts of patients included in HCC surveillance programs. Environmental factors will be comprehensively characterised in an ongoing clinical trial designed to evaluate alternative methods for early-stage HCC detection. Finally, AI models, reaching the minimal viable product stage by the end of GENIAL, will be used to integrate genetic and non-genetic information (including digital imaging) to develop novel cost-effective strategies towards prevention and early-stage detection of ALD-HCC in at-risk individuals. This action is part of the Cancer Mission cluster of projects on ‘‘Understanding’.

Liver transplantation (LT) is a life-saving procedure for decompensated cirrhosis (DC) and hepato-cellular carcinoma (HCC). Its efficacy is hampered by the risk of death/drop-out on the Wait List (WL). This risk is driven by organ shortage and is mitigated by organ offering schemes. According to a sickest first policy, offering schemes prioritize LT candidates with the highest risk of dying, as assessed by predictive models. To drive allocation, Organ Sharing Organizations (OSOs) use a 20-year-old model, the MELD, predicting mortality in DC but not in HCC. Because of a dramatic increase in % of HCC candidates (40% against 10% in early 20ties), MELD schemes are increasingly inaccurate, with persisting 15 to 30% mortality in countries with low/medium donation rate. This scenario, together with advances in prognosis in DC and HCC candidates and statistics, prompts LT community to look for up-dated algorithms to refine offering schemes. To address this issue, key European LT stakeholders including OSOs, experts in LT, Statisticians, Research Labs and SME joined LEOPARD. Building on an innovative, harmonized OSOs pre-LT dataset and advances in modeling, LEOPARD propose to design and validate 1) an AI-based LEOPARD predictive algorithm outperforming current allocation models by better stratifying patients on the risk of mortality, to be proposed OSOs to drive allocation; 2) DC & HCC LEOPARD calculators available for professional for assistance in complex decision-making processes; 3) OMICs/radiomics predictive signatures integrated in a prototype 3rd-generation exploratory model. We expect to generate computational tools improving candidates’ outcomes, with more patients transplanted on time. Adoption of these tools should result in harmonization of European heterogeneous prioritization schemes, and in a signification reduction in disparities of access to LT, a major objective pointed out by EC. LEOPARD should place Europe in leading position for organ offering schemes.

Genetic skeletal diseases (GSDs) are an extremely diverse and complex group of rare genetic diseases that affect the development the skeleton. There are more than 450 unique and well-characterised phenotypes that range in severity from relatively mild to severe and lethal forms. Although individually rare, as a group of related genetic skeletal diseases, GSDs have an overall prevalence of at least 1 per 4,000 children, which extrapolates to a minimum of 225,000 people in the 27 member states and candidate countries of the EU. This burden in pain and disability leads to poor quality of life and high healthcare costs. Metaphyseal chondrodysplasia, type Schmid (MCDS) results from mutations in collagen X and affects <1/100,000 of the population. Mutant collagen X molecules miss-fold during synthesis and are retained within the endoplasmic reticulum (ER) of hypertrophic chondrocytes, thereby causing ER stress. Our extensive pre-clinical studies have shown that carbamazepine (CBZ) can alleviate ER stress caused by the expression of mutant collagen X and restore bone growth in a validated mouse model of MCDS. CBZ is an FDA approved drug used for the treatment of epilepsy and bipolar disorder and received orphan drug designation by the European Commission for the treatment of MCDS in September 2016. MCDS-Therapy was originally proposed as a 5-year collaborative project comprising world-renown clinical centres and SMEs to advance the repurposing of CBZ for MCDS (up to the Marketing Authorization Application dossier) through a multicentre and multinational (EU & AUS) clinical trial (Phase1, Phase2/3). MCDS-Therapy also encompasses biomarker development and health economics assessment studies to deliver, evidence to inform potential further studies of an innovative and affordable (CBZ already exists in a generic form) repurposed therapy for MCDS along with the diagnosis/prognosis tools to personalise the treatment strategy. The original proposal was for completion of this by 2022 however delays associated with the COVID pandemic have resulted in a need to extend the project with completion now forecast by May 2024.