Proteomic Differences Between Hepatocellular Carcinoma and Nontumorous Liver Tissue Investigated by a Combined Gel-based and Label-free Quantitative Proteomics Study

Abstract

Proteomics-based clinical studies have been shown to be promising strategies for the discovery of novel biomarkers of a particular disease. Here, we present a study of hepatocellular carcinoma (HCC) that combines complementary two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography (LC-MS)-based approaches of quantitative proteomics. In our proteomic experiments, we analyzed a set of 14 samples (7 ؋ HCC versus 7 ؋ nontumorous liver tissue) with both techniques. Thereby we identified 573 proteins that were differentially expressed between the experimental groups. Among these, only 51 differentially expressed proteins were identified irrespective of the applied approach. Using Western blotting and immunohistochemical analysis the regulation patterns of six selected proteins from the study overlap (inorganic pyrophosphatase 1 (PPA1), tumor necrosis factor type 1 receptor-associated protein 1 (TRAP1), betaine-homocysteine S-methyltransferase 1 (BHMT)) were successfully verified within the same sample set. In addition, the up-regulations of selected proteins from the complements of both approaches (major vault protein (MVP), gelsolin (GSN), chloride intracellular channel protein 1 (CLIC1)) were also reproducible. Within a second independent verification set (n ‫؍‬ 33) the altered protein expression levels of major vault protein and betaine-homocysteine S-methyltransferase were further confirmed by Western blots quantitatively analyzed via densitometry. For the other candidates slight but nonsignificant trends were detectable in this independent cohort. Based on these results we assume that major vault protein and betaine-homocysteine S-methyltransferase have the potential to act as diagnostic HCC biomarker candidates that are worth to be followed in further validation studies. Hepatocellular carcinoma (HCC)1 currently is the fifth most common malignancy worldwide with an annual incidence up to 500 per 100,000 individuals depending on the geographic region investigated. Whereas 80% of new cases occur in developing countries, the incidence increases in industrialized nations including Western Europe, Japan, and the United States (1). To manage patients with HCC, tumor markers are very important tools for diagnosis, indicators of disease progression, outcome prediction, and evaluation of treatment efficacy. Several tumor markers have been reported for HCC, including ␣-fetoprotein (AFP) (2), Lens culinaris agglutininreactive fraction of AFP (AFP-L3) (3), and des-␥-carboxyl prothrombin (DCP) (4). However, none of these tumor markers show 100% sensitivity or specificity, which calls for new and better biomarkers.To identify novel biomarkers of HCC, many clinical studies using "omics"-based methods have been reported over the past decade (5-6). In particular, the proteomics-based approach has turned out to be a promising one, offering several quantification techniques to reveal differences in protein expression that are caused by a particular disease. In most studies, the well-established 2D-D...

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“…The supernatants were collected, evaporated to dryness, and dissolved in 50 l of 0.1% trifluoroacetic acid. The peptide concentration of the resulting solution was determined by amino acid analysis as previously described (23). For the subsequent liquid chromatography-tandem mass spectrometry experiment, the sample was diluted to a concentration of 0.33 pmol/l, and 5 pmol was analyzed using an UltiMate 3000 RSLCnano system online coupled to a Velos Pro linear ion trap mass spectrometer (both from Thermo Scientific, Bremen, Germany) as described earlier (23).…”

“…The peptide concentration of the resulting solution was determined by amino acid analysis as previously described (23). For the subsequent liquid chromatography-tandem mass spectrometry experiment, the sample was diluted to a concentration of 0.33 pmol/l, and 5 pmol was analyzed using an UltiMate 3000 RSLCnano system online coupled to a Velos Pro linear ion trap mass spectrometer (both from Thermo Scientific, Bremen, Germany) as described earlier (23). The acquired raw files were further analyzed with Proteome Discoverer software (Thermo Scientific, v1.3.0.339) and searched with Sequest (24) against a self-written database containing the investigated prototype sequence (pt) and S1368P peptides.…”