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MicroRNAs are a newly discovered class of tiny regulatory RNAs that persuade the stability and translational efficiency of target mRNAs. They have been concerned in an increasing number of neoplasia and as well as biological process. Latest studies have shown a contribution for these regulatory molecules in breast cancer. For instance, microRNA profiling studies have identified microRNAs that are deregulated in breast cancer. Moreover, functional studies have revealed their roles in breast cancer as both oncogenes (e.g. miR-21) and cancer suppressor genes (e.g. miR-335). MicroRNAs deregulated in breast cancer control the translational regulation of entrenched regulative molecules, such as oestrogen receptor-α, which are regulated by novel cancer-related molecules and miR-206 whose functions are not yet completely understood. However, here we present an overview of our up-to-date understanding of microRNAs in breast cancer.
MicroRNA role in cancer in general:
MiRNAs have been associated to the regulation of differentiation, proliferation, apoptosis and even exocytosis (Miska., 2005). Volinia et al has demonstrated that the predicted targets for the differentially expressed miRNAs are significantly enriched for protein-coding tumor suppressors and oncogenes. There is also confirmation to suggest that these miRNAs function in concert with classical tumor suppressors and oncoproteins to regulate key pathways involved in cellular growth control (Volinia et al., 2006 and Zhang et al., 2007). MiRNA profiling has not only the potential to classify tumors, but also augur patient outcome with high accuracy, but this approach needs more validation and detailed studies by using clinical samples (Hernando., 2007). Jian et al showed that profile analysis with a probe set of 201 miRNAs achieved the similar discriminative power as traditional gene array with 8000 mRNA probes (Jiang et al., 2005). Consequently, this would mean that classification of tumors can be achieved with a more manageable amount of data and could potentially diminish the disparity that is often seen with mRNA based classifier systems.
MicroRNAs study in breast cells and tissues:
Since the study of mRNA, various technologies exist that allow the investigation of the expression of either profiling of a large number of miRNAs, or individual miRNAs simultaneously. In general, these observational approaches have implicated individual or groups of miRNAs in pathological or physiological processes, as a result of the detection of changes in their expression, while additional functional experiments are required to gain grasping of their current roles. A few miRNA profiles have been developed using a large number of single miRNA detection experiments, such as northern blotting (Lagos et al., 2001), and these technologies remain the standard against which newer profiling methods are primarily compared. Nevertheless, oligonucleotide microarray-based detection platforms, with their associated ease of use and high throughput nature, have largely supplanted this technique (Wark et al., 2008). Microarrays have been used for miRNAs profiling from a wide range of breast tissue types and cell lines, including formalin-fixed paraffin-embedded (FFPE) clinical samples. It is essential to note that, due to the small size of miRNAs, they are comparatively insensitive to the damage that typifies mRNAs within FFPE. Accordingly, miRNAs present an invaluable new target for studies using archival clinical samples, which can often be linked to extensive clinical background and more importantly, follow-up data or Meta analysis (Nelson et al., 2004). Multiplex real-time RT-PCR and liquid bead-based technologies current alternative strategies for miRNA profiling, and it is claimed that this may have higher sensitivity and specificity (Chen et al., 2005 and Lu et al., 2005). Methodologies based on deep sequencing of small RNA libraries obtained from tissues may also allow miRNA profiling, with the supplementary advantage that these techniques are unbiased with respect to target sequences and may permit detection of novel miRNAs (Hafner et al., 2008).
Profiling data of miRNA and breast cancer:
The expression of miRNAs has been investigated in an extensive range of breast cancer cell lines, tissues and clinical normal. These meta data hints towards functional roles of various miRNAs by association with cellular behavior or particular molecular markers. To gain a best insight into breast cancer, it is also essential to understand miRNA function in normal mammary gland development, and work is under way to address this question in detail (Silveri et al., 2006). A potentially powerful empirical approach is to compare miRNA expression in normal breast versus breast cancer and thereby to differentiate those miRNAs expressed at different levels. According to Iorio et al (2005), in which 76 breast samples were diagnosed for the expression of 246 miRNAs. Out of which 29 miRNAs expression levels were found to be significantly different (i.e. p < 0.05) in cancer versus normal clinical tissue. In which, the majority consistently down-regulated were miR-10b, miR-125b and miR-145, and miR-21, miR-155, which were up-regulated, suggesting that these may act as oncogenes or tumor suppressor genes, respectively (Iorio et al., 2005). They went on to examine whether the expression profile varied accordant to conventional clinical aspects: ER+ /ER−, PR+ /PR−, HER2+ /HER2−, positive and negative lymph node status, presence and absence of vascular invasion, high and low proliferation index, and ductal/lobular histopathological subtype. The majority of comparisons discovered a small number of differentially expressed miRNAs, indicating that miRNAs may have roles in defining the differences between these pathological and molecular profiles. Yet, comparison between ductal/lobular carcinomas and HER2+ and HER2− tumors did not reveal differentially expressed miRNAs.
Similarly, specific miRNA profiles have been associated with breast cancer subgroups of distinct patterns of molecular marker expression. Profiling of 204 miRNAs proved sufficient to allow unsupervised clustering to be used to distinguish HER2+ /ER−, HER2+ /ER− and HER2− /ER+ breast cancers within a cohort of 20 tumours. While this in itself is not an advance, since these cancers are routinely defined using immunohistochemistry, further supervised analysis of the profiles
allowed distinct miRNA subsets to be identified that distinguished HER2+ from HER2− and ER+ from ER− breast cancers, independent of other clinically important parameters. Restricted subsets of miRNAs specific to HER2 status (let-7f, let-7g, miR-107, miR-10b, miR-126, miR-154 and miR-195) and specific to ER/PR status (miR-142-5p, miR-200a, miR-205 and
miR-25) were established .