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MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype

Cherie Blenkiron1234, Leonard D Goldstein125, Natalie P Thorne125, Inmaculada Spiteri12, Suet-Feung Chin12, Mark J Dunning12, Nuno L Barbosa-Morais12, Andrew E Teschendorff12, Andrew R Green6, Ian O Ellis6, Simon Tavaré125, Carlos Caldas12* and Eric A Miska34*

Author Affiliations

1 Cancer Research UK, Cambridge Research Institute, Li Ka-Shing Centre, Robinson Way, Cambridge CB2 0RE, UK

2 Department of Oncology, University of Cambridge, Hills Road, Cambridge CB2 2XZ, UK

3 Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, The Henry Wellcome Building of Cancer and Developmental Biology, Tennis Court Rd, Cambridge CB2 1QN, UK

4 Department of Biochemistry, University of Cambridge, Tennis Court Rd, Cambridge CB2 1GA, UK

5 Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WA, UK

6 Department of Histopathology, School of Molecular Medical Sciences, University of Nottingham, Nottingham NG5 1PB, UK

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Genome Biology 2007, 8:R214  doi:10.1186/gb-2007-8-10-r214

Published: 8 October 2007

Abstract

Background

MicroRNAs (miRNAs), a class of short non-coding RNAs found in many plants and animals, often act post-transcriptionally to inhibit gene expression.

Results

Here we report the analysis of miRNA expression in 93 primary human breast tumors, using a bead-based flow cytometric miRNA expression profiling method. Of 309 human miRNAs assayed, we identify 133 miRNAs expressed in human breast and breast tumors. We used mRNA expression profiling to classify the breast tumors as luminal A, luminal B, basal-like, HER2+ and normal-like. A number of miRNAs are differentially expressed between these molecular tumor subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumor subtypes in an independent data set. In some cases, changes in miRNA expression correlate with genomic loss or gain; in others, changes in miRNA expression are likely due to changes in primary transcription and or miRNA biogenesis. Finally, the expression of DICER1 and AGO2 is correlated with tumor subtype and may explain some of the changes in miRNA expression observed.

Conclusion

This study represents the first integrated analysis of miRNA expression, mRNA expression and genomic changes in human breast cancer and may serve as a basis for functional studies of the role of miRNAs in the etiology of breast cancer. Furthermore, we demonstrate that bead-based flow cytometric miRNA expression profiling might be a suitable platform to classify breast cancer into prognostic molecular subtypes.