Liver cancer is the sixth most common cancer, with 782,000 new cases diagnosed in 2012 worldwide1. It is the fifth most common cancer in
men (554,000 cases, 7.5% of the total) and the ninth in women (228,000 cases, 3.4%). In Europe liver cancer is the 14th most common cancer,
with around 63,500 new cases diagnosed in 2012 (2% of the total). Hepatocellular carcinoma (HCC) is the most common primary
malignancy of the liver. Among all cancers, HCC is one of the fastest growing causes of death (second leading cause of cancer mortality worldwide, Fig.1) and poses a significant economic burden on healthcare.

Liver transplantation for hepatocellular carcinoma (HCC) isthe best treatment option for patients with early-stage tumours. However, there is no robust tools to accurately select  HCC patients for liver transplantation – eligibility decisions are based solely on clinical parameters. Optimum candidate selection is crucial to both save lives of more patients and limit unsuccessfully attempts, leading to mortality. Limited available livers for transplantation are being misused, with increased patient mortality and money is wasted in each failed intervention. There is an urgent need to better decide the eligibility of patients and the best use of the resources (existing livers and budget).

We are developing HepatoPredict, a powerful predictive tool that integrates a molecular signature with clinical parameters in a predictive algorithm with high predictive power. HepatoPredict is currently under multi centric validation, and we plan to commercialise it as an IVD diagnostic test towards 2020-2021, aimed at the Hepatology Clinic of the Gastro-Enterology Departments.

This project is a collaboration with the  Centro Hepato-Bilio-Pancreático e Transplantação do Hospital Curry Cabral.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 827173.