Related Experiment Video
Updated: Apr 5, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
Published on: August 19, 2025
Differential proteomic and tissue expression analyses identify valuable diagnostic biomarkers of hepatocellular
Henning Reis1, Juliet Padden, Maike Ahrens
11Institute of Pathology, University Hospital of Essen, University of Duisburg-Essen, Essen 2Medizinisches Proteom-Center, Ruhr-Universität Bochum, Bochum 3Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University of Duisburg-Essen, Essen 4Institute of Pathology, Klinikum Dortmund gGmbH, Dortmund 5Department of General, Visceral and Transplantation Surgery, University Hospital of Essen, University of Duisburg-Essen, Essen 6West German Cancer Centre Essen, University Hospital of Essen, University of Duisburg-Essen, Essen 7Department of Gastroenterology and Hepatology, University Hospital of Essen, University of Duisburg-Essen, Essen 8Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V., Dortmund, Germany *contributed equally as senior authors.
Abstract:
The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

