Table of Contents Author Guidelines Submit a Manuscript
Advances in Bioinformatics
Volume 2012 (2012), Article ID 373506, 13 pages
Research Article

Detecting Cancer Outlier Genes with Potential Rearrangement Using Gene Expression Data and Biological Networks

1Department of Computer Science, University of Calgary, Calgary, AB, Canada T2N 1N4
2Departments of Pathology, Oncology and Molecular Biology and Biochemistry, Faculty of Medicine, University of Calgary, Calgary, AB, Canada T2N 1N4

Received 5 March 2012; Revised 30 April 2012; Accepted 8 May 2012

Academic Editor: T. Akutsu

Copyright © 2012 Mohammed Alshalalfa et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Gene alterations are a major component of the landscape of tumor genomes. To assess the significance of these alterations in the development of prostate cancer, it is necessary to identify these alterations and analyze them from systems biology perspective. Here, we present a new method (EigFusion) for predicting outlier genes with potential gene rearrangement. EigFusion demonstrated excellent performance in identifying outlier genes with potential rearrangement by testing it to synthetic and real data to evaluate performance. EigFusion was able to identify previously unrecognized genes such as FABP5 and KCNH8 and confirmed their association with primary and metastatic prostate samples while confirmed the metastatic specificity for other genes such as PAH, TOP2A, and SPINK1. We performed protein network based approaches to analyze the network context of potential rearranged genes. Functional gene rearrangement Modules are constructed by integrating functional protein networks. Rearranged genes showed to be highly connected to well-known altered genes in cancer such as AR, RB1, MYC, and BRCA1. Finally, using clinical outcome data of prostate cancer patients, potential rearranged genes demonstrated significant association with prostate cancer specific death.