University of Limerick Institutional Repository

MicroRNA signatures predict oestrogen receptor, progesterone receptor and HER2/neu receptor status in breast cancer

DSpace Repository

Show simple item record

dc.contributor.author Lowery, Aoife J.
dc.contributor.author Miller, Nicola
dc.contributor.author Devaney, Amanda
dc.contributor.author McNeill, Roisin E.
dc.contributor.author Davoren, Roisin E.
dc.contributor.author Lemetre, Christophe
dc.contributor.author Benes, Vladimir
dc.contributor.author Schmidt, Sabine
dc.contributor.author Blake, Jonathan
dc.contributor.author Ball, Graham
dc.contributor.author Kerin, Michael J.
dc.date.accessioned 2016-07-12T11:57:06Z
dc.date.available 2016-07-12T11:57:06Z
dc.date.issued 2009
dc.identifier.uri http://hdl.handle.net/10344/5110
dc.description peer-reviewed en_US
dc.description.abstract Introduction Breast cancer is a heterogeneous disease encompassing a number of phenotypically diverse tumours. Expression levels of the oestrogen, progesterone and HER2/ neu receptors which characterize clinically distinct breast tumours have been shown to change during disease progression and in response to systemic therapies. Mi(cro)RNAs play critical roles in diverse biological processes and are aberrantly expressed in several human neoplasms including breast cancer, where they function as regulators of tumour behaviour and progression. The aims of this study were to identify miRNA signatures that accurately predict the oestrogen receptor (ER), progesterone receptor (PR) and HER2/neu receptor status of breast cancer patients to provide insight into the regulation of breast cancer phenotypes and progression. Methods Expression profiling of 453 miRNAs was performed in 29 early-stage breast cancer specimens. miRNA signatures associated with ER, PR and HER2/neu status were generated using artificial neural networks (ANN), and expression of specific miRNAs was validated using RQ-PCR. Results Stepwise ANN analysis identified predictive miRNA signatures corresponding with oestrogen (miR-342, miR-299, miR-217, miR-190, miR-135b, miR-218), progesterone (miR- 520g, miR-377, miR-527-518a, miR-520f-520c) and HER2/ neu (miR-520d, miR-181c, miR-302c, miR-376b, miR-30e) receptor status. MiR-342 and miR-520g expression was further analysed in 95 breast tumours. MiR-342 expression was highest in ER and HER2/neu-positive luminal B tumours and lowest in triple-negative tumours. MiR-520g expression was elevated in ER and PR-negative tumours. Conclusions This study demonstrates that ANN analysis reliably identifies biologically relevant miRNAs associated with specific breast cancer phenotypes. The association of specific miRNAs with ER, PR and HER2/neu status indicates a role for these miRNAs in disease classification of breast cancer. Decreased expression of miR-342 in the therapeutically challenging triple-negative breast tumours, increased miR-342 expression in the luminal B tumours, and downregulated miR- 520g in ER and PR-positive tumours indicates that not only is dysregulated miRNA expression a marker for poorer prognosis breast cancer, but that it could also present an attractive target for therapeutic intervention. en_US
dc.language.iso eng en_US
dc.publisher BioMed Central en_US
dc.relation.ispartofseries Breast Cancer Research;11:R27
dc.subject breast cancer en_US
dc.subject heterogeneous disease en_US
dc.title MicroRNA signatures predict oestrogen receptor, progesterone receptor and HER2/neu receptor status in breast cancer en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1186/bcr2257
dc.contributor.sponsor National Breast Cancer Research Institute en_US
dc.contributor.sponsor John and Lucile Van Geest foundation en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search ULIR


Browse

My Account

Statistics