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.
Highlights
From the ‡Medizinisches Proteom-Center, Ruhr-Universitat Bochum, Bochum, Germany; §Department of General, Visceral and Transplantation Surgery, University Hospital of Essen, Essen, Germany; ¶Department of Medicine (Cancer Research), Molecular Oncology Risk-Profile Evaluation, West German Cancer Centre, University Hospital of Essen, Essen, Germany; ʈDepartment of Gastroenterology and Hepatology, University Hospital of Essen, Essen, Germany; **Department of Pathology and Neuropathology, University Hospital of Essen, Essen, Germany
The authors could show that based on its proteomic signature, hepatocellular carcinoma can be discriminated with high accuracy from liver metastasis samples or other cancer types [21] as well as liver cirrhosis [22]
In our study we compared the proteomic profile of Hepatocellular carcinoma (HCC) tumor tissue (n ϭ 7) with nontumorous liver tissue (n ϭ 7) by following a 2D-DIGE approach and a label-free LC-MS-based quantification strategy
Summary
From the ‡Medizinisches Proteom-Center, Ruhr-Universitat Bochum, Bochum, Germany; §Department of General, Visceral and Transplantation Surgery, University Hospital of Essen, Essen, Germany; ¶Department of Medicine (Cancer Research), Molecular Oncology Risk-Profile Evaluation, West German Cancer Centre, University Hospital of Essen, Essen, Germany; ʈDepartment of Gastroenterology and Hepatology, University Hospital of Essen, Essen, Germany; **Department of Pathology and Neuropathology, University Hospital of Essen, Essen, Germany. Label-free proteomics approaches based on quantification by ion-intensities or spectral counting offer another possibility for biomarker discovery These approaches are relatively cheap compared with the labeling approaches, because they do not require any labeling reagents and they allow for high-throughput and sensitive analyses in a mass spectrometer. We report a quantitative proteomic study that combines two different techniques, namely the well-established 2D-DIGE approach and a label-free ion-intensity-based quantification via mass spectrometry and liquid chromatography. To our knowledge this is the first time such a combined study was performed with regard to hepatocellular carcinoma. To verify the differential protein expressions detected in our proteomic studies we performed additional immunological verifications for selected proteins within two different sample sets (Fig. 1)
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