Interactome-transcriptome Analysis Reveals the High Centrality of Genes Differentially Expressed in Lung Cancer Tissues

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2005 Sep 29

PMID 16188928

Citations 173

Authors

Shinichiro Wachi

Ken Yoneda

Reen Wu

Affiliations

Soon will be listed here.

Abstract

Motivation: Global protein interaction network (interactome) analysis provides an effective way to understand the relationships between 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, whereas 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.

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