Obesity, metabolic dysfunction, and hepatic steatosis are dominant drivers of increasing hepatobiliary cancer (HBC) incidence. Preclinical studies have demonstrated that the High-density lipoprotein (HDL) proteome mirrors the liver proteome in health and disease transition. Here, we propose that early metabolic liver disease and cancer can be distinguished by a novel, targeted proteomic assay ‘MetHealth’ developed at UCD that enables blood measurements of >80 HDL-derived proteins known to be associated with liver and metabolic dysfunction. We will assess associations between these HDL protein signatures with liver diseases and HBC using existing data and biospecimens from well-phenotyped French and Irish clinical studies including patients with metabolic dysfunction-associated steatotic liver disease [MASLD], metabolic dysfunction-associated steatohepatitis [MASH], liver cancers (230 cases/230 controls) and an HBC case-control study nested within the European Prospective Investigation into Cancer (EPIC) cohort (515 HBC cases, 515 controls with pre-diagnostic data and biospecimen collections). These will also be correlated with proteomic assays from a matched subset of 70 MASH/MASLD (n=70) disease and HBC (n=50) tumour tissue samples. The HDL proteome will be isolated from plasma or tissue by a novel solid-phase extraction method and assayed by mass spectrometry (MS) using targeted and discovery MS respectively in UCD. Multivariable adjusted logistic regression models will be used to assess associations (odds ratios (OR), 95% confidence intervals (CI), and tests for linear trends) between metabolic liver disease and HBC (plus anatomical subsites) risk and individual plus combined peptide concentrations, including mediation by obesity and dietary/lifestyle data. Hepato-ProMet will be a large, unique study combining powerful prospective and patient cohort resources with an innovative Irish-developed diagnostic technology. The findings will provide robust information on how novel proteomic biomarkers of metabolic dysfunction may identify and potentially differentiate metabolic liver disease and HBC risk, thereby enhancing public cancer prevention policy, cancer diagnosis, and patient risk stratification.
