Format

Send to

Choose Destination
See comment in PubMed Commons below
Bioinformatics. 2011 Dec 1;27(23):3300-5. doi: 10.1093/bioinformatics/btr559. Epub 2011 Oct 11.

Gathering insights on disease etiology from gene expression profiles of healthy tissues.

Author information

1
Integrative Genomics of Ageing Group, Institute of Integrative Biology, University of Liverpool, Liverpool, UK.

Abstract

MOTIVATION:

Gene expression profiles have been widely used to study disease states. It may be possible, however, to gather insights into human diseases by comparing gene expression profiles of healthy organs with different disease incidence or severity. We tested this hypothesis and developed an approach to identify candidate genes associated with disease development by focusing on cancer incidence since it varies greatly across human organs.

RESULTS:

We normalized organ-specific cancer incidence by organ weight and found that reproductive organs tend to have a higher mass-normalized cancer incidence, which could be due to evolutionary trade-offs. Next, we performed a genome-wide scan to identify genes whose expression across healthy organs correlates with organ-specific cancer incidence. We identified a large number of genes, including genes previously associated with tumorigenesis and new candidate genes. Most genes exhibiting a positive correlation with cancer incidence were related to ribosomal and transcriptional activity, translation and protein synthesis. Organs with enhanced transcriptional and translational activation may have higher cell proliferation and therefore be more likely to develop cancer. Furthermore, we found that organs with lower cancer incidence tend to express lower levels of known cancer-associated genes. Overall, these results demonstrate how genes and processes that predispose organs to specific diseases can be identified using gene expression profiles from healthy tissues. Our approach can be applied to other diseases and serve as foundation for further oncogenomic analyses.

CONTACT:

jp@senescence.info

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
21994229
DOI:
10.1093/bioinformatics/btr559
[Indexed for MEDLINE]
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Silverchair Information Systems
    Loading ...
    Support Center