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This article is part of the supplement: Proceedings of the Fourth Annual MCBIOS Conference. Computational Frontiers in Biomedicine

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Computational analysis of biological functions and pathways collectively targeted by co-expressed microRNAs in cancer

Yuriy Gusev1*, Thomas D Schmittgen2, Megan Lerner13, Russell Postier1 and Daniel Brackett13

Author Affiliations

1 Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA

2 Division of Pharmaceutics, Ohio State University, Columbus, Ohio, USA

3 Veterans Affairs Medical Hospital, Oklahoma City, Oklahoma, USA

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BMC Bioinformatics 2007, 8(Suppl 7):S16  doi:10.1186/1471-2105-8-S7-S16

Published: 1 November 2007

Abstract

Background

Multiple recent studies have found aberrant expression profiles of microRNAome in human cancers. While several target genes have been experimentally identified for some microRNAs in various tumors, the global pattern of cellular functions and pathways affected by co-expressed microRNAs in cancer remains elusive. The goal of this study was to develop a computational approach to global analysis of the major biological processes and signaling pathways that are most likely to be affected collectively by co-expressed microRNAs in cancer cells.

Results

We report results of computational analysis of five datasets of aberrantly expressed microRNAs in five human cancers published by the authors (pancreatic cancer) and others (breast cancer, colon cancer, lung cancer and lymphoma). Using the combinatorial target prediction algorithm miRgate and a two-step data reduction procedure we have determined Gene Ontology categories as well as biological functions, disease categories, toxicological categories and signaling pathways that are: targeted by multiple microRNAs; statistically significantly enriched with target genes; and known to be affected in specific cancers.

Conclusion

Our global analysis of predicted miRNA targets suggests that co-expressed miRNAs collectively provide systemic compensatory response to the abnormal phenotypic changes in cancer cells by targeting a broad range of functional categories and signaling pathways known to be affected in a particular cancer. Such systems biology based approach provides new avenues for biological interpretation of miRNA profiling data and generation of experimentally testable hypotheses regarding collective regulatory functions of miRNA in cancer.