Gene co-expression network analysis reveals common system-level properties of prognostic genes across cancer types

Yang Yang, Leng Han, Yuan Yuan, Jun Li, Nainan Hei, Han Liang

Research output: Contribution to journalArticlepeer-review

306 Scopus citations

Abstract

Prognostic genes are key molecules informative for cancer prognosis and treatment. Previous studies have focused on the properties of individual prognostic genes, but have lacked a global view of their system-level properties. Here we examined their properties in gene co-expression networks for four cancer types using data from 'The Cancer Genome Atlas'. We found that prognostic mRNA genes tend not to be hub genes (genes with an extremely high connectivity), and this pattern is unique to the corresponding cancer-type-specific network. In contrast, the prognostic genes are enriched in modules (a group of highly interconnected genes), especially in module genes conserved across different cancer co-expression networks. The target genes of prognostic miRNA genes show similar patterns. We identified the modules enriched in various prognostic genes, some of which show cross-tumour conservation. Given the cancer types surveyed, our study presents a view of emergent properties of prognostic genes.

Original languageEnglish (US)
Article number3231
JournalNature communications
Volume5
DOIs
StatePublished - Feb 3 2014

ASJC Scopus subject areas

  • General Chemistry
  • General Biochemistry, Genetics and Molecular Biology
  • General Physics and Astronomy

MD Anderson CCSG core facilities

  • Bioinformatics Shared Resource

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