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Open Access Highly Accessed Methodology article

Detecting microRNAs of high influence on protein functional interaction networks: a prostate cancer case study

Mohammed Alshalalfa14*, Gary D Bader2, Anna Goldenberg3, Quaid Morris2 and Reda Alhajj1

Author Affiliations

1 Department of Computer Science, University of Calgary, Calgary, AB, Canada

2 University of Toronto, and the Department of Molecular Genetics, University of Toronto, Toronto ON, Canada

3 Genetics and Genome Biology, Toronto, Canada

4 Biotechnology Research Centre, Palestine Polytechnic University, Hebron, Palestine

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BMC Systems Biology 2012, 6:112  doi:10.1186/1752-0509-6-112

Published: 28 August 2012

Abstract

Background

The use of biological molecular network information for diagnostic and prognostic purposes and elucidation of molecular disease mechanism is a key objective in systems biomedicine. The network of regulatory miRNA-target and functional protein interactions is a rich source of information to elucidate the function and the prognostic value of miRNAs in cancer. The objective of this study is to identify miRNAs that have high influence on target protein complexes in prostate cancer as a case study. This could provide biomarkers or therapeutic targets relevant for prostate cancer treatment.

Results

Our findings demonstrate that a miRNA’s functional role can be explained by its target protein connectivity within a physical and functional interaction network. To detect miRNAs with high influence on target protein modules, we integrated miRNA and mRNA expression profiles with a sequence based miRNA-target network and human functional and physical protein interactions (FPI). miRNAs with high influence on target protein complexes play a role in prostate cancer progression and are promising diagnostic or prognostic biomarkers. We uncovered several miRNA-regulated protein modules which were enriched in focal adhesion and prostate cancer genes. Several miRNAs such as miR-96, miR-182, and miR-143 demonstrated high influence on their target protein complexes and could explain most of the gene expression changes in our analyzed prostate cancer data set.

Conclusions

We describe a novel method to identify active miRNA-target modules relevant to prostate cancer progression and outcome. miRNAs with high influence on protein networks are valuable biomarkers that can be used in clinical investigations for prostate cancer treatment.

Keywords:
MiRNA; Protein interactions; Systems biology; High-influence miRNA