The DeLIVER Programme
The DeLIVER programme is investigating new approaches for earlier liver cancer detection. Led by Professor Ellie Barnes (Nuffield Department of Medicine, University of Oxford) the consortium consists of internationally renowned scientists, academics, clinical and industry partners.
Background:
Hepatocellular cancer (HCC) is one of the fastest rising and 4th commonest cause of cancer death world-wide, associated with viral infection, alcohol and obesity. Currently, 80% of HCCs are diagnosed at late stage with a 5-year survival less than 5%. HCC is usually associated with liver inflammation, advanced fibrosis and field cancerisation, as evidenced by multiple HCC that arise contemporaneously irrespective of aetiology. Strategies for the early detection (EDx) of HCC are urgently required so that curative therapies may be applied. To date, little effort has been made to characterise the pre-cancerous liver landscape, and current imaging techniques and biomarkers that seek to identify HCC, lack sensitivity, specificity and use outdated modalities.
Aims:
The DeLIVER consortium aims to overcome the barriers to HCC-EDx by characterising the pre-cancerous liver microenvironment. The approach involves utilising novel quantitative multi-parametric magnetic resonance imaging and state-of-the-art molecular biomarker technologies. The internationally renowned research team spans fields such as immunology, imaging, (epi)genomics, biochemistry, oncology and integrative data science.
Objectives:
a) Define the pre-cancerous microenvironmental liver landscape that drives malignant transformation through deep-phenotyping of the pre-cancerous liver.
b) Assess non-invasive technologies that may “sample” the pre-cancerous liver environment, including the simultaneous detection of epigenetic/genetic information in blood (TAPS)
c) Perform an integrative analysis of multi-parametric datasets (including quantitative mpMRI, TAPS, metabolomic and protein(omic) biomarkers) Recognizing that a single parameter may not accurately predict or detect early HCC.
d) Develop HCC-EDx cohorts including at-risk patients with cirrhosis and patients with small HCC The aim is to rapidly evaluate early detection technologies before prospective testing.
e) Exploit expertise in integrating host and viral genomic polymorphisms that may predispose individuals to malignant transformation.
Hypotheses:
a) HCC is primarily driven by liver microenvironmental processes including immune, metabolic, and stromal processes. Inflammatory signals are believed to establish epigenetic programmes that contribute to malignant transformation. Understanding this pathway is crucial for developing new strategies for the early detection of HCC (HCC-EDx) and potential therapeutic interventions.
b) Combination of molecular and imaging strategies for HCC-EDx can effectively be used for the early detection of HCC in at-risk patient populations.
Methods:
The consortium plans to define the pre-cancerous microenvironmental liver landscape through deep-phenotyping of cirrhotic tissue obtained using fine needle aspiration in patients with and without HCC. Recent data support the hypothesis that HCC is driven by inflammatory signals that perturb the microenvironment, establishing epigenetic programmes that contribute to malignant transformation.
Epigenetic modifications in cell-free DNA will be assessed using the TAPS assay, novel biochemistry recently developed at Oxford. This assay can detect epigenetic modifications, DNA mutations, and copy number variations simultaneously.
Aberrant immune and hypoxia gene signalling that may predispose to malignant transformation will be determined using (single-cell) RNA-seq technology. TAPS on cfDNA and metabolomic/proteomic/autoantibody signatures will be evaluated in blood and combined with multi-parametric MRI liver imaging that samples liver heterogeneity, quantifying inflammation/fibrosis at each voxel. Genetic determinants promoting malignant transformation will be identified through integrative host and viral genomics.
Three unique research cohorts have been created and will serve as the basis for evaluating early hepatocellular carcinoma (HCC) diagnosis technologies and risk stratification methods.
Click here to find out more about the research studies
How the results of this research will be used:
The research aims to understand the pre-cancer liver landscape and develop translatable early detection methods, risk prediction, and therapeutics. The expertise in data science will play a crucial role in integrating multi-modal technologies and iterating strategies for HCC early detection.
The research questions will be addressed through six work packages within the DeLIVER programme.