Abstract 4049: MiR-187 is a marker of poor prognosis in estrogen receptor-positive breast cancer

Abstract

Abstract Resistance to endocrine-directed therapy represents a significant problem in the management of breast cancer. Here we describe an integrated bioinformatics and translational pathology approach to identifying novel microRNAs (miRNA) controlling this phenomenon. Differential gene expression can, in part, be attributed to the activity of specific miRNAs. Given a database of miRNA binding site motifs and gene expression levels determined by transcriptomic profiling, correspondence analysis, between group analysis and co-inertia analysis can be combined to produce a ranked list of miRNAs associated with a specific gene signature and phenotype. We have applied this approach to examine gene expression data from 69 breast cancer patients treated with tamoxifen (1) and have identified miR-187 as the principle miRNA associated with poor response to anti-estrogen therapy. Expression of miR-187 was subsequently evaluated in a cohort of breast cancer patients (n=111), by locked nucleic acid in situ hybridisation (LNA-ISH) on tissue microarrays, and quantified by automated image analysis. LNA-ISH signal was validated by miR-187-specific Taqman PCR in a subset of tumours. High miR-187 expression was significantly associated with poor outcome in ER+ breast cancer patients (p = 0.05) and correlated with increased tumour size (p=0.009), higher grade (p=0.005) and PR negativity (p=0.014). Additionally, the prognostic significance of the miR-187 target genes OCA2 and HIPK3 was examined in an independent dataset comprising 155 breast cancer patients treated with adjuvant tamoxifen (2). Low mRNA expression of both OCA2 (p=0.0001) and HIPK3 (p=0.016) was found to be significantly associated with poor outcome. These data support the hypothesis that miR-187 and its targets play an important role in anti-estrogen resistance and may be useful as biomarkers to aid treatment options and as potential drug targets to restore tamoxifen sensitivity in resistant patients. 1. Kok M et al. Comparison of gene expression profiles predicting progression in breast cancer patients treated with tamoxifen. Breast Cancer Res Treat 2009;113(2):275 2. Chanrion M et al., A gene expression signature that can predict the recurrence of tamoxifen-treated primary breast cancer. Clin Cancer Res 2008;14(6):1744-52. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4049.