The shaping and functional consequences of the microRNA landscape in breast cancer View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-05

AUTHORS

Heidi Dvinge, Anna Git, Stefan Gräf, Mali Salmon-Divon, Christina Curtis, Andrea Sottoriva, Yongjun Zhao, Martin Hirst, Javier Armisen, Eric A. Miska, Suet-Feung Chin, Elena Provenzano, Gulisa Turashvili, Andrew Green, Ian Ellis, Sam Aparicio, Carlos Caldas

ABSTRACT

MicroRNAs (miRNAs) show differential expression across breast cancer subtypes, and have both oncogenic and tumour-suppressive roles. Here we report the miRNA expression profiles of 1,302 breast tumours with matching detailed clinical annotation, long-term follow-up and genomic and messenger RNA expression data. This provides a comprehensive overview of the quantity, distribution and variation of the miRNA population and provides information on the extent to which genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture, suggesting an important role for post-transcriptional regulation. The key clinical parameters and cellular pathways related to the miRNA landscape are characterized, revealing context-dependent interactions, for example with regards to cell adhesion and Wnt signalling. Notably, only prognostic miRNA signatures derived from breast tumours devoid of somatic copy-number aberrations (CNA-devoid) are consistently prognostic across several other subtypes and can be validated in external cohorts. We then use a data-driven approach to seek the effects of miRNAs associated with differential co-expression of mRNAs, and find that miRNAs act as modulators of mRNA-mRNA interactions rather than as on-off molecular switches. We demonstrate such an important modulatory role for miRNAs in the biology of CNA-devoid breast cancers, a common subtype in which the immune response is prominent. These findings represent a new framework for studying the biology of miRNAs in human breast cancer. More... »

PAGES

378

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nature12108

DOI

http://dx.doi.org/10.1038/nature12108

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1027957670

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23644459


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