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

Fuxiao Xin, Meng Li, Curt Balch, Michael Thomson, Meiyun Fan, Yunlong Liu, Scott M. Hammond, Sun Kim, Kenneth P. Nephew

Research output: Contribution to journalArticle

89 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)430-434
Number of pages5
JournalBioinformatics
Volume25
Issue number4
DOIs
StatePublished - Feb 1 2009

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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