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Bioinformatics Advance Access originally published online on December 17, 2008
Bioinformatics 2009 25(4):430-434; doi:10.1093/bioinformatics/btn646
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© The Author 2008. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Computational analysis of microRNA profiles and their target genes suggests significant involvement in breast cancer antiestrogen resistance

Fuxiao Xin 1, Meng Li 1,2,3, Curt Balch 2,4, Michael Thomson 5, Meiyun Fan 6, Yunlong Liu 7, Scott M. Hammond 8, Sun Kim 1,9,* and Kenneth P. Nephew 2,3,4,6,10,*

1School of Informatics, 2Medical Sciences, School of Medicine, 3Interdisciplinary Biochemistry Program, 4IU Simon Cancer Center, Indiana University, Bloomington, IN 47405, 5Department of Cancer Biology, Vanderbilt University Medical Center, Nashville, TN 37232, 6Department of Pathology and Laboratory Medicine, and the Center for Cancer Research, University of Tennessee Health Science Center, Memphis, TN 38163, 7Division of Biostatistics, School of Medicine, Indiana University, Indianapolis, IN 46202, 8Cell and Developmental Biology, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, 9Center for Genomics and Bioinformatics, Indiana University, Bloomington, IN 47404 and 10Department of Cellular and Integrative Physiology, School of Medicine, Indiana University, Indianapolis, IN 46202, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Recent evidence shows significant involvement of microRNAs (miRNAs) in the initiation and progression of numerous cancers; however, the role of these in tumor drug resistance remains unknown.

Results: By comparing global miRNA and mRNA expression patterns, we examined the role of miRNAs in resistance to the ‘pure antiestrogen’ fulvestrant, using fulvestrant-resistant MCF7-FR cells and their drug-sensitive parental estrogen receptor (ER)-positive MCF7 cells. We identified 14 miRNAs downregulated in MCF7-FR cells and then used both TargetScan and PITA to predict potential target genes. We found a negative correlation between expression of these miRNAs and their predicted target mRNA transcripts. In genes regulated by multiple miRNAs or having multiple miRNA-targeting sites, an even stronger negative correlation was found. Pathway analyses predicted these miRNAs to regulate specific cancer-associated signal cascades. These results suggest a significant role for miRNA-regulated gene expression in the onset of breast cancer antiestrogen resistance, and an improved understanding of this phenomenon could lead to better therapies for this often fatal condition.

Contact: knephew{at}indiana.edu; sunkim2{at}indiana.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Ivo Hofacker

Received on August 7, 2008; revised on December 9, 2008; accepted on December 12, 2008

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[Abstract] [Full Text] [PDF]


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