Interactions between the estrogen receptor, its cofactors and microRNAs in breast cancer.

The activity of selective estrogen receptor modulators (SERMs) is not fully explained by an estrogen receptor (ER) switch model that simply turns estrogen activity on or off. A better understanding of the mechanisms involved in estrogen signaling and the development of drug resistance could help stratify patients into more coherent treatment groups and identify novel therapeutic candidates. This review describes how interactions between two novel factors known to influence estrogenic activity: nuclear receptor cofactors--protein partners which modulate estrogen action, and microRNAs--a class of recently discovered regulatory elements, may impact hormone-sensitive breast cancer. The role of nuclear receptor cofactors in estrogen signaling and the associations between ER cofactors and breast cancer are described. We outline the activity of microRNAs (miRNAs) and their associations with breast cancer and detail recent evidence of interactions between the ER and its cofactors and miRNA and provide an overview of the emerging field of miRNA-based therapeutics. We propose that previously unrecognised interactions between these two species of regulatory molecules may underlie at least some of the heterogeneity of breast cancer in terms of its clinical course and response to treatment. The exploitation of such associations will have important implications for drug development.

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

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.

Identification of suitable endogenous control genes for microRNA gene expression analysis in human breast cancer.

The discovery of microRNAs (miRNAs) added an extra level of intricacy to the already complex system regulating gene expression. These single-stranded RNA molecules, 18-25 nucleotides in length, negatively regulate gene expression through translational inhibition or mRNA cleavage. The discovery that aberrant expression of specific miRNAs contributes to human disease has fueled much interest in profiling the expression of these molecules. Real-time quantitative PCR (RQ-PCR) is a sensitive and reproducible gene expression quantitation technique which is now being used to profile miRNA expression in cells and tissues. To correct for systematic variables such as amount of starting template, RNA quality and enzymatic efficiencies, RQ-PCR data is commonly normalised to an endogenous control (EC) gene, which ideally, is stably-expressed across the test sample set. A universal endogenous control suitable for every tissue type, treatment and disease stage has not been identified and is unlikely to exist, so, to avoid introducing further error in the quantification of expression data it is necessary that candidate ECs be validated in the samples of interest. While ECs have been validated for quantification of mRNA expression in various experimental settings, to date there is no report of the validation of miRNA ECs for expression profiling in breast tissue. In this study, the expression of five miRNA genes (let-7a, miR-10b, miR-16, miR-21 and miR-26b) and three small nucleolar RNA genes (RNU19, RNU48 and Z30) was examined across malignant, benign and normal breast tissues to determine the most appropriate normalisation strategy. This is the first study to identify reliable ECs for analysis of miRNA by RQ-PCR in human breast tissue.

MicroRNAs as prognostic indicators and therapeutic targets: potential effect on breast cancer management.

The discovery of microRNAs (miRNA) as novel modulators of gene expression has resulted in a rapidly expanding repertoire of molecules in this family, as reflected in the concomitant expansion of scientific literature. MiRNAs are a category of naturally occurring RNA molecules that play important regulatory roles in plants and animals by targeting mRNAs for cleavage or translational repression. Characteristically, miRNAs are noncoding, single-stranded short (18-22 nucleotides) RNAs, features which possibly explain why they had not been intensively investigated until recently. Accumulating experimental evidence indicates that miRNAs play a pivotal role in many cellular functions via the regulation of gene expression. Furthermore, their dysregulation and/or mutation has been shown in carcinogenesis. We provide a brief review of miRNA biogenesis and discuss the technical challenges of modifying experimental techniques to facilitate the identification and characterization of these small RNAs. MiRNA function and their involvement in malignancy, particularly their putative role as oncogenes or tumor suppressors is also discussed, with a specific emphasis on breast cancer. Finally, we comment on the potential role of miRNAs in breast cancer management, particularly in improving current prognostic tools and achieving the goal of individualized cancer treatment.

Evaluation and validation of candidate endogenous control genes for real-time quantitative PCR studies of breast cancer.

BACKGROUND: Real-time quantitative PCR (RQ-PCR) forms the basis of many breast cancer biomarker studies and novel prognostic assays, paving the way towards personalised cancer treatments. Normalisation of relative RQ-PCR data is required to control for non-biological variation introduced during sample preparation. Endogenous control (EC) genes, used in this context, should ideally be expressed constitutively and uniformly across treatments in all test samples. Despite widespread recognition that the accuracy of the normalised data is largely dependent on the reliability of the EC, there are no reports of the systematic validation of genes commonly used for this purpose in the analysis of gene expression by RQ-PCR in primary breast cancer tissues. The aim of this study was to identify the most suitable endogenous control genes for RQ-PCR analysis of primary breast tissue from a panel of eleven candidates in current use. Oestrogen receptor alpha (ESR1) was used a target gene to compare the effect of choice of EC on the estimate of gene quantity. RESULTS: The expression and validity of candidate ECs (GAPDH, TFRC, ABL, PPIA, HPRT1, RPLP0, B2M, GUSB, MRPL19, PUM1 and PSMC4) was determined in 6 benign and 21 malignant primary breast cancer tissues. Gene expression data was analysed using two different statistical models. MRPL19 and PPIA were identified as the most stable and reliable EC genes, while GUSB, RPLP0 and ABL were least stable. There was a highly significant difference in variance between ECs. ESR1 expression was appreciably higher in malignant compared to benign tissues and there was a significant effect of EC on the magnitude of the error associated with the relative quantity of ESR1. CONCLUSION: We have validated two endogenous control genes, MRPL19 and PPIA, for RQ-PCR analysis of gene expression in primary breast tissue. Of the genes in current use in this field, the above combination offers increased accuracy and resolution in the quantitation of gene expression data, facilitating the detection of smaller changes in gene expression than otherwise possible. The combination identified here is a good candidate for use as a two-gene endogenous control in a broad spectrum of future research and diagnostic applications in breast cancer.