Comprehensive multi-omics analysis reveals aberrant metabolism of epstein-barr-virus-associated gastric carcinoma

  • Sang Jun Yoon
  • , Jun Yeob Kim
  • , Nguyen Phuoc Long
  • , Jung Eun Min
  • , Hyung Min Kim
  • , Jae Hee Yoon
  • , Nguyen Hoang Anh
  • , Myung Chan Park
  • , Sung Won Kwon*
  • , Suk Kyeong Lee
  • *Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

30 Scopus citations

Abstract

The metabolic landscape of Epstein-Barr-virus-associated gastric cancer (EBVaGC) remains to be elucidated. In this study, we used transcriptomics, metabolomics, and lipidomics to comprehensively investigate aberrant metabolism in EBVaGC. Specifically, we conducted gene expression analyses using microarray-based data from gastric adenocarcinoma epithelial cell lines and tissue samples from patients with clinically advanced gastric carcinoma. We also conducted complementary metabolomics and lipidomics using various mass spectrometry platforms. We found a significant downregulation of genes related to metabolic pathways, especially the metabolism of amino acids, lipids, and carbohydrates. The effect of dysregulated metabolic genes was confirmed in a survival analysis of 3951 gastric cancer patients. We found 57 upregulated metabolites and 31 metabolites that were downregulated in EBVaGC compared with EBV-negative gastric cancer. Sixty-nine lipids, mainly ether-linked phospholipids and triacylglycerols, were downregulated, whereas 45 lipids, mainly phospholipids, were upregulated. In total, 15 metabolisms related to polar metabolites and 15 lipid-associated pathways were involved in alteration of metabolites by EBV in gastric cancer. In this work, we have described the metabolic landscape of EBVaGC at the multi-omics level. These findings could help elucidate the mechanism of EBVaGC oncogenesis.

Original languageEnglish
Article number1220
JournalCells
Volume8
Issue number10
DOIs
StatePublished - 10 2019
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2019 by the authors.

Keywords

  • Cancer metabolism
  • Epstein-Barr-virus-associated gastric cancer
  • Lipidomics
  • Metabolomics
  • Transcriptomics

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