Large-scale differential gene expression transcriptomic analysis identifies a metabolic signature shared by all cancer cells

Areej Abu Rmaileh, Balakrishnan Solaimuthu, Mayur Tanna, Anees Khatib, Michal Ben Yosef, Arata Hayashi, Michal Lichtenstein, Yoav D. Shaul*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Cancer-dependent metabolic rewiring is often manifested by selective expression of enzymes essential for the transformed cells’ viability. However, the metabolic variations between normal and transformed cells are not fully characterized, and therefore, a systematic analysis will result in the identification of unknown cellular mechanisms crucial for tumorigenesis. Here, we applied differential gene expression transcriptome analysis to examine the changes in metabolic gene profiles between a wide range of normal tissues and cancer samples. We found that, in contrast to normal tissues which exhibit a tissue-specific expression profile, cancer samples are more homogenous despite their diverse origins. This similarity is due to a “proliferation metabolic signature” (PMS), composed of 158 genes (87 upregulated and 71 downregulated gene sets), where 143 are common to all proliferative cells but 15 are cancer specific. Intriguingly, the PMS gene set is enriched for genes encoding rate-limiting enzymes, and its upregulated set with genes associated with poor patient outcome and essential genes. Among these essential genes is ribulose-5-phosphate-3-epimerase (RPE), which encodes a pentose phosphate pathway enzyme and whose role in cancer is still unclear. Collectively, we identified a set of metabolic genes that can serve as novel cancer biomarkers and potential targets for drug development.

Original languageAmerican English
Article number701
JournalBiomolecules
Volume10
Issue number5
DOIs
StatePublished - May 2020

Bibliographical note

Funding Information:
This research was funded by Israel Science Foundation, grant number 1816/16, and Lady Davis Fellowship Trust (to B.S.).

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • Cancer
  • Cancer metabolism
  • Gene expression analysis
  • Nucleotide biosynthesis

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