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Bioinformatics Advance Access published online on September 27, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti688
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received June 9, 2005
Revised September 7, 2005
Accepted September 21, 2005

Discovery note

Interactome-transcriptome analysis reveals the high centrality of genes differentially expressed in lung cancer tissues

Shinichiro Wachi 1*, Ken Yoneda 1, and Reen Wu 1

1 Center for Comparative Respiratory Biology and Medicine and Division of Pulmonary/Critical Care Medicine, University of California, Davis CA 95616, USA

* To whom correspondence should be addressed.
Shinichiro Wachi, E-mail: swachi{at}ucdavis.edu


  Abstract

Motivation: Global protein interaction network (interactome) analysis provides an effective way to understand the relationships between the genes. Through this approach, it was demonstrated that the essential genes in yeast tend to be highly connected, as well as connected to other highly connected genes. This is in contrast to the genes that are not essential, which share neither of these properties. Using a similar interactome-transcriptome approach, the topological features in the interactome of differentially expressed genes in lung squamous cancer tissues are assessed.

Results: This analysis reveals that the genes that are differentially elevated, as obtained from the microarray gene profiling data, in cancer are well connected, while the suppressed genes and randomly selected ones are less so. These results support the notion that a topological analysis of cancer genes using protein interaction data will allow the placement of the list of genes, often of the disparate nature, into the global, systematic context of the cell. The result of this type of analysis may provide the rationale for therapeutic targets in cancer treatment.

Supplementary information: Available at the journal's web site.


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