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 and Han Liang ()
Additional contact information
Yang Yang: The University of Texas Health Science Center at Houston, School of Public Health
Leng Han: The University of Texas MD Anderson Cancer Center
Yuan Yuan: The University of Texas MD Anderson Cancer Center
Jun Li: The University of Texas MD Anderson Cancer Center
Nainan Hei: The University of Texas Health Science Center at Houston, School of Public Health
Han Liang: The University of Texas MD Anderson Cancer Center

Nature Communications, 2014, vol. 5, issue 1, 1-9

Abstract: 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.

Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.nature.com/articles/ncomms4231 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4231

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/ncomms4231

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().