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

Nwosu, Zeribe C. ; Battello, Nadia ; Rothley, Melanie ; Piorońska, Weronika ; Sitek, Barbara ; Ebert, Matthias P. ; Hofmann, Ute ; Sleeman, Jonathan ; Wölfl, Stefan ; Meyer, Christoph ; Megger, Dominik A. ; Dooley, Steven

In: Journal of Experimental & Clinical Cancer Research, 37 (2018), Nr. 211. pp. 1-15. ISSN 1756-9966

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Download (3MB) | Lizenz: Creative Commons LizenzvertragLiver cancer cell lines distinctly mimic the metabolic gene expression pattern of the corresponding human tumours by Nwosu, Zeribe C. ; Battello, Nadia ; Rothley, Melanie ; Piorońska, Weronika ; Sitek, Barbara ; Ebert, Matthias P. ; Hofmann, Ute ; Sleeman, Jonathan ; Wölfl, Stefan ; Meyer, Christoph ; Megger, Dominik A. ; Dooley, Steven underlies the terms of Creative Commons Attribution 4.0

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Download (246kB) | Lizenz: Creative Commons LizenzvertragLiver cancer cell lines distinctly mimic the metabolic gene expression pattern of the corresponding human tumours by Nwosu, Zeribe C. ; Battello, Nadia ; Rothley, Melanie ; Piorońska, Weronika ; Sitek, Barbara ; Ebert, Matthias P. ; Hofmann, Ute ; Sleeman, Jonathan ; Wölfl, Stefan ; Meyer, Christoph ; Megger, Dominik A. ; Dooley, Steven underlies the terms of Creative Commons Attribution 4.0

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Abstract

Background: Although 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.

Methods: We 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.

Results: We 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.

Conclusions: We 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.

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CORRECTION

Published online 2.11.2018 in Journal of Experimental & Clinical Cancer Research, 37 (2018), Nr. 267; DOI: https://doi.org/10.1186/s13046-018-0939-4. In the publication of this article, there was an error in Fig. 5b. This has been updated in the original article on BioMed Central's website. The authors declare that the correction does not change the results or conclusions of this paper.

Document type: Article
Journal or Publication Title: Journal of Experimental & Clinical Cancer Research
Volume: 37
Number: 211
Publisher: BioMed Central
Place of Publication: London
Date Deposited: 25 Oct 2018 12:50
Date: 2018
ISSN: 1756-9966
Page Range: pp. 1-15
Faculties / Institutes: The Faculty of Bio Sciences > Institute of Pharmacy and Molecular Biotechnology
Medizinische Fakultät Mannheim > Zentrum für Biomedizin und Medizintechnik (CBTM)
DDC-classification: 610 Medical sciences Medicine
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