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Open Access Highly Accessed Research article

Integrated genomic analysis of triple-negative breast cancers reveals novel microRNAs associated with clinical and molecular phenotypes and sheds light on the pathways they control

Emanuele de Rinaldis12*, Patrycja Gazinska1, Anca Mera5, Zora Modrusan5, Grazyna M Fedorowicz5, Brian Burford1, Cheryl Gillett16, Pierfrancesco Marra1, Anita Grigoriadis1, David Dornan7, Lars Holmberg34, Sarah Pinder16 and Andrew Tutt1

Author Affiliations

1 Breakthrough Breast Cancer Research Unit, Division of Cancer Studies, School of Medicine, King’s College London, Guy’s Hospital, London, UK

2 NIHR Biomedical Research Centre - R&D Department, Guy’s Hospital, London, United Kingdom

3 Division of Cancer Studies, School of Medicine, King's College London, Guy’s Hospital, London, UK

4 Regional Oncologic Centre Uppsala/Örebro, Uppsala, Sweden

5 Department of Molecular Biology, Genentech, Inc, South San Francisco, CA, USA

6 Breast Research Pathology, Division of Cancer Studies, School of Medicine, King's College London, Guy’s Hospital, London, UK

7 Department of Molecular Diagnostics and Cancer Cell Biology, Genentech, Inc., South San Francisco, CA, USA

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BMC Genomics 2013, 14:643  doi:10.1186/1471-2164-14-643

Published: 23 September 2013

Abstract

Background

This study focuses on the analysis of miRNAs expression data in a cohort of 181 well characterised breast cancer samples composed primarily of triple-negative (ER/PR/HER2-negative) tumours with associated genome-wide DNA and mRNA data, extensive patient follow-up and pathological information.

Results

We identified 7 miRNAs associated with prognosis in the triple-negative tumours and an additional 7 when the analysis was extended to the set of all ER-negative cases. miRNAs linked to an unfavourable prognosis were associated with a broad spectrum of motility mechanisms involved in the invasion of stromal tissues, such as cell-adhesion, growth factor-mediated signalling pathways, interaction with the extracellular matrix and cytoskeleton remodelling. When we compared different intrinsic molecular subtypes we found 46 miRNAs that were specifically expressed in one or more intrinsic subtypes. Integrated genomic analyses indicated these miRNAs to be influenced by DNA genomic aberrations and to have an overall influence on the expression levels of their predicted targets. Among others, our analyses highlighted the role of miR-17-92 and miR-106b-25, two polycistronic miRNA clusters with known oncogenic functions. We showed that their basal-like subtype specific up-regulation is influenced by increased DNA copy number and contributes to the transcriptional phenotype as well as the activation of oncogenic pathways in basal-like tumours.

Conclusions

This study analyses previously unreported miRNA, mRNA and DNA data and integrates these with pathological and clinical information, from a well-annotated cohort of breast cancers enriched for triple-negative subtypes. It provides a conceptual framework, as well as integrative methods and system-level results and contributes to elucidate the role of miRNAs as biomarkers and modulators of oncogenic processes in these types of tumours.

Keywords:
miRNAs; Breast cancer; Data integration; Pathway analysis