Quantitative proteome analysis reveals the correlation between endocytosis-associated proteins and hepatocellular carcinoma dedifferentiation

Naboulsi, Wael; Bracht, Thilo; Megger, Dominik A.; Reis, Henning; Ahrens, Maike; Turewicz, Michael; Eisenacher, Martin; Tautges, Stephanie; Canbay, Ali; Meyer, Helmut E.; Weber, Frank; Baba, Hideo A.; Sitek, Barbara

doi:10.1016/j.bbapap.2016.08.005

Cited by 20 publications

(22 citation statements)

References 29 publications

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“…The remaining cell pellets were stored at − 80 °C until analysis. Proteomic analysis was conducted by mass spectrometry as previously described [14]. Proteins with at least two unique peptides and FDR adjusted P < 0.05 after analysis of variance were considered significant in our analyses, which includes pathway enrichment, GO, and overlap with HMGs.…”

Section: Methodsmentioning

confidence: 99%

Liver cancer cell lines distinctly mimic the metabolic gene expression pattern of the corresponding human tumours

Nwosu

Battello²,

Rothley

et al. 2018

J Exp Clin Cancer Res

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106

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BackgroundAlthough metabolism is profoundly altered in human liver cancer, the extent to which experimental models, e.g. cell lines, mimic those alterations is unresolved. Here, we aimed to determine the resemblance of hepatocellular carcinoma (HCC) cell lines to human liver tumours, specifically in the expression of deregulated metabolic targets in clinical tissue samples.MethodsWe compared the overall gene expression profile of poorly-differentiated (HLE, HLF, SNU-449) to well-differentiated (HUH7, HEPG2, HEP3B) HCC cell lines in three publicly available microarray datasets. Three thousand and eighty-five differentially expressed genes in ≥2 datasets (P < 0.05) were used for pathway enrichment and gene ontology (GO) analyses. Further, we compared the topmost gene expression, pathways, and GO from poorly differentiated cell lines to the pattern from four human HCC datasets (623 tumour tissues). In well- versus poorly differentiated cell lines, and in representative models HLE and HUH7 cells, we specifically assessed the expression pattern of 634 consistently deregulated metabolic genes in human HCC. These data were complemented by quantitative PCR, proteomics, metabolomics and assessment of response to thirteen metabolism-targeting compounds in HLE versus HUH7 cells.ResultsWe found that poorly-differentiated HCC cells display upregulated MAPK/RAS/NFkB signaling, focal adhesion, and downregulated complement/coagulation cascade, PPAR-signaling, among pathway alterations seen in clinical tumour datasets. In HLE cells, 148 downregulated metabolic genes in liver tumours also showed low gene/protein expression – notably in fatty acid β-oxidation (e.g. ACAA1/2, ACADSB, HADH), urea cycle (e.g. CPS1, ARG1, ASL), molecule transport (e.g. SLC2A2, SLC7A1, SLC25A15/20), and amino acid metabolism (e.g. PHGDH, PSAT1, GOT1, GLUD1). In contrast, HUH7 cells showed a higher expression of 98 metabolic targets upregulated in tumours (e.g. HK2, PKM, PSPH, GLUL, ASNS, and fatty acid synthesis enzymes ACLY, FASN). Metabolomics revealed that the genomic portrait of HLE cells co-exist with profound reliance on glutamine to fuel tricarboxylic acid cycle, whereas HUH7 cells use both glucose and glutamine. Targeting glutamine pathway selectively suppressed the proliferation of HLE cells.ConclusionsWe report a yet unappreciated distinct expression pattern of clinically-relevant metabolic genes in HCC cell lines, which could enable the identification and therapeutic targeting of metabolic vulnerabilities at various liver cancer stages.Electronic supplementary materialThe online version of this article (10.1186/s13046-018-0872-6) contains supplementary material, which is available to authorized users.

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Section: Methodsmentioning

confidence: 99%

Liver cancer cell lines distinctly mimic the metabolic gene expression pattern of the corresponding human tumours

Nwosu

Battello²,

Rothley

et al. 2018

J Exp Clin Cancer Res

Self Cite

106

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“…Further details regarding patient characteristics, sample preparation, mass spectrometry, and proteomic data analysis have been extensively described in our prior publications. 37 , 38 …”

Section: Methodsmentioning

confidence: 99%

Identification of the Consistently Altered Metabolic Targets in Human Hepatocellular Carcinoma

Nwosu

Megger

Hammad

et al. 2017

Cellular and Molecular Gastroenterology and Hepatology

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106

121

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Background & AimsCancer 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).MethodsWe 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.ResultsWe 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.ConclusionsWe 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.

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“…Using an in-house written R script (R Foundation for Statistical Computing, Vienna, Austria). Benjamini–Hochberg corrected one-way ANOVA was used for the calculation of the FDR-corrected p -values ( 29 ). For proteins passing a significance level of 0.05, a post hoc test (Tukey’s honest significant difference method) was conducted to obtain p -values for pairwise comparisons.…”

Section: Methodsmentioning

confidence: 99%

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression

et al. 2017

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Interferons (IFNs) are pleotropic cytokines secreted upon encounter of pathogens and tumors. Applying their antipathogenic, antiproliferative, and immune stimulatory capacities, recombinant IFNs are frequently prescribed as drugs to treat different diseases. IFNs act by changing the gene expression profile of cells. Due to characteristics such as rapid gene induction and signaling, IFNs also represent prototypical model systems for various aspects of biomedical research (e.g., signal transduction). In regard to the signaling and activated promoters, IFNs can be subdivided into two groups. Here, alterations of the cellular proteome of human cells treated with IFNα and IFNγ were elucidated in a time-resolved manner by quantitative proteome analysis. The majority of protein regulations were strongly IFN type and time dependent. In addition to the expected upregulation of IFN-responsive proteins, an astonishing number of proteins became profoundly repressed especially by IFNγ. Thus, our comprehensive analysis revealed important insights into the human IFN-regulated proteome and its dynamics of protein induction and repression. Interestingly, the new class of IFN-repressed genes comprises known host factors for highly relevant pathogens such as HIV, dengue virus, and hepatitis C virus.

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Quantitative proteome analysis reveals the correlation between endocytosis-associated proteins and hepatocellular carcinoma dedifferentiation

Cited by 20 publications

References 29 publications

Liver cancer cell lines distinctly mimic the metabolic gene expression pattern of the corresponding human tumours

Liver cancer cell lines distinctly mimic the metabolic gene expression pattern of the corresponding human tumours

Identification of the Consistently Altered Metabolic Targets in Human Hepatocellular Carcinoma

Deciphering of the Human Interferon-Regulated Proteome by Mass Spectrometry-Based Quantitative Analysis Reveals Extent and Dynamics of Protein Induction and Repression

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