Tissue-based quantitative proteome analysis of human hepatocellular carcinoma using tandem mass tags.

CONTEXT AND OBJECTIVE: Human hepatocellular carcinoma (HCC) is a severe malignant disease, and accurate and reliable diagnostic markers are still needed. This study was aimed for the discovery of novel marker candidates by quantitative proteomics. METHODS AND RESULTS: Proteomic differences between HCC and nontumorous liver tissue were studied by mass spectrometry. Among several significantly upregulated proteins, translocator protein 18 (TSPO) and Ras-related protein Rab-1A (RAB1A) were selected for verification by immunohistochemistry in an independent cohort. For RAB1A, a high accuracy for the discrimination of HCC and nontumorous liver tissue was observed. CONCLUSION: RAB1A was verified to be a potent biomarker candidate for HCC.

Systematic analysis of synergistic proteome modulations in a drug combination of cisplatin and MLN4924.

Chemotherapeutic treatment regimens often take advantage of synergistic effects of drug combinations. Anticipating that synergistic effects on the cell biological level likely manifest on the proteome level, the analysis of proteome modulations represents an appropriate strategy to study drug combinations on a molecular level. More specifically, the detection of single proteins exhibiting synergistic abundance changes could be helpful to shed light on key molecules, which contribute in mechanisms facilitating the synergistic interaction and therefore represent potential targets for specific therapeutic approaches. In the reported study we aimed to provide evidence for this assumption and investigated the drug combination of cisplatin and the neddylation inhibitor MLN4924 in HCT-116 cells via cell biological analyses and mass spectrometry-based quantitative proteomics. From 1789 proteins quantified with two unique peptides, activated RNA polymerase II transcriptional coactivator p15 (SUB1) was highlighted as the most synergistically regulated protein using a synergistic scoring approach. Western blotting and analyses of cellular processes associated with this protein (DNA damage, oxidative stress and apoptosis) revealed supporting evidence for the synergistic regulation. Whereas the distinct role of SUB1 in the investigated drug combination needs to be elucidated in future studies, the presented results demonstrated the benefit and feasibility of synergistic scoring of proteome alterations to highlight proteins that likely contribute to the underlying molecular mechanisms of synergistic effects. Data are available via ProteomeXchange with identifier PXD009185.

Identification of the Consistently Altered Metabolic Targets in Human Hepatocellular Carcinoma.

BACKGROUND & AIMS: Cancer cells rely on metabolic alterations to enhance proliferation and survival. Metabolic gene alterations that repeatedly occur in liver cancer are largely unknown. We aimed to identify metabolic genes that are consistently deregulated, and are of potential clinical significance in human hepatocellular carcinoma (HCC). METHODS: We studied the expression of 2,761 metabolic genes in 8 microarray datasets comprising 521 human HCC tissues. Genes exclusively up-regulated or down-regulated in 6 or more datasets were defined as consistently deregulated. The consistent genes that correlated with tumor progression markers (ECM2 and MMP9) (Pearson correlation P < .05) were used for Kaplan-Meier overall survival analysis in a patient cohort. We further compared proteomic expression of metabolic genes in 19 tumors vs adjacent normal liver tissues. RESULTS: We identified 634 consistent metabolic genes, ∼60% of which are not yet described in HCC. The down-regulated genes (n = 350) are mostly involved in physiologic hepatocyte metabolic functions (eg, xenobiotic, fatty acid, and amino acid metabolism). In contrast, among consistently up-regulated metabolic genes (n = 284) are those involved in glycolysis, pentose phosphate pathway, nucleotide biosynthesis, tricarboxylic acid cycle, oxidative phosphorylation, proton transport, membrane lipid, and glycan metabolism. Several metabolic genes (n = 434) correlated with progression markers, and of these, 201 predicted overall survival outcome in the patient cohort analyzed. Over 90% of the metabolic targets significantly altered at the protein level were similarly up- or down-regulated as in genomic profile. CONCLUSIONS: We provide the first exposition of the consistently altered metabolic genes in HCC and show that these genes are potentially relevant targets for onward studies in preclinical and clinical contexts.