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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and current imaging techniques and biomarkers that seek to identify HCC, lack sensitivity, specificity and use outdated modalities.


In this programme we aim to overcome the barriers to HCC-EDx by characterising the pre-cancerous liver microenvironment and applying new methodologies to measure this, combining novel quantitative multi-parametric magnetic resonance imaging and state-of-the-art molecular biomarker technologies. To achieve this, we have established an internationally renowned research team in the fields of immunology, imaging, (epi)genomics, biochemistry, oncology and integrative data science.


We will define the pre-cancerous microenvironmental liver landscape through deep-phenotyping of cirrhotic tissue sampled using fine needle aspiration in patients with and without HCC. Recent data support our hypothesis that HCC is driven by inflammatory signals that perturb the microenvironment, establishing epigenetic programmes that contribute to malignant transformation. We will assess epigenetic modifications in cell-free DNA (cfDNA), using novel biochemistry, recently developed at Oxford, that can detect epigenetic modifications, DNA mutations, and copy number variations simultaneously (TAPS assay). Aberrant immune and hypoxia gene signalling that may predispose to malignant transformation will be determined contemporaneously 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. We will exploit our considerable expertise in integrative host and viral genomics to identify genetic determinants that promote malignant transformation. We will leverage a unique, genetically characterised cohort of HCV-infected patients with cirrhosis expanded to include additional disease aetiologies, followed prospectively, and build a cohort of patients with small HCC, so that EDx technologies can be rapidly evaluated before testing prospectively.

How the results of this research will be used:

Understanding the pre-cancer liver landscape and integrating multi-modal technologies through leveraging our expertise in data science will develop, refine and iterate strategies for translatable EDx methods, risk prediction and therapeutics.

A team of internationally renowned scientists from academia and industry have been assembled under the DeLIVER (The Early Detection of Hepatocellular Liver Cancer) consortium in order find new methods for the early detection of HCC using state-of-the-art technologies.

DeLIVER Hypotheses and Goals

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