1.1 Breast Cancer and miRNA
Breast cancer is a global threat to women health. According to a 2008 survey [1], breast cancer was the leading cause of cancer death in women. Currently, we know some possible risk factors, diagnostic methods and some drug and surgery procedure for treatment, but we don’t know the detail of progression of breast carcinoma, and the most important, how to cure breast cancer.
From previous researches, we knew some risk factors of breast cancer. Early menarche, late menopause, obesity, late first full pregnancy, and hormone replacement therapy were considered as high risk factors of breast cancer [2]. Breast cancer risk was also reported to be related to fat intake when red meats and high-fat dairy foods were main source of fat [3].
For diagnosis, the most widely used measures are mammography, ultrasonography, MRI (magnetic resonance imaging) and PET (positron emission tomography) [2].
Biopsy may be used to confirm the existence of malignant tissue if suspicious results are produced in the diagnosis stage. Further analysis on the tissue obtained from biopsy may point out the best methods for treatment. After breast tumor is confirmed, the patient can be treated by surgery, radiotherapy, chemotherapy, and targeting therapy, depending on the conditions of the patient.
One of the most widely used classifying methods for breast cancer is to use expression state of three biological markers: estrogen receptors (ER), progesterone receptors (PR), and HER2/neu [4]. ER and PR were hormone receptors which may be over-expressed in breast carcinoma. To treat ER positive patients, it is possible to use anti-estrogen therapy or tamoxifen, which is a selective ER modulator [5]. It was
reported that chemotherapy had better performance in ER negative patients than ER positive ones [6]. Her2/neu is a widely used prognostic and predictive marker in breast cancer. For patients with newly diagnosed breast cancer without receiving adjuvant systemic therapy, overexpression of Her2/neu is associated to bad prognosis [7]. A targeting therapy, trastuzumab, which is a Her2/neu targeting antibody, was developed for breast cancer treatment [8].
MicroRNAs (miRNAs), one of the small non-coding RNAs [9], are short endogenous nucleotides which is able to regulate gene expression. After miRNAs precursor are transcribed from the genome, or generated from spliceosomes, they are exported to cytoplasm and further processed by Dicer complex [10]. The mature miRNA would be then bound to Argonaute protein, forming a miRNA-protein complex known as miRNP or RNAi (RNA interference) enzyme complex [11, 12]. The miRNP complex was reported to be able to down-regulate target genes by translational repression [13] or mRNA cleavage [14].
Like other protein-based regulators, miRNAs were known to have important roles in cancer. Calin et al. reported that miR-15 and miR-16 were deleted in leukemia [15], which was believed to be one of the earliest report of the association of miRNA and cancer [16]. After the report, many miRNAs acting as tumor suppressor or oncogenes (which were also known as oncomirs) were found. For example, miR-21 was identified as oncomir at least in hepatocellular cancer [17], breast cancer [18], and kidney cancer [19]. Let-7c was found to be a tumor suppressor in prostate cancer [20]. miR-181a was reported as a tumor suppressor in glioma [21]. MiR-125b [22], and miR-145 [23] were known as tumor suppressors of breast cancer. Mir-125a was found to repress tumor growth in breast cancer [24]. It is thus undeniable that miRNAs play an important role in breast cancer.
1.2 Integrated Analysis of miRNA and mRNA Expression Profiles
Since miRNA functions by regulating its target genes, we may deduce the effect of a miRNA by analyzing its regulated networks. To use such a method to elucidate miRNA functions, targets of miRNAs should be deduced. Currently, predictions in most target prediction database were based on sequence and statistical methods [25]. For example, in TargetScan, seed base pairing, target site context, conservation of target site and miRNA, and site accessibility were considered in the prediction process [26].
Another way to elucidate targets of miRNAs is to integrate expression profiles of miRNA and mRNA. In the work of Huang et al. [27], they developed a Bayesian-based algorithms, GenMiR++, to predict possible targets of 104 miRNAs in human. They also verified their results by RT-PCR and microarray experiments. However, the power of other sequence-based target prediction algorithms was not utilized in their work.
It is also possible to combine sequence-based target prediction and expression-based target prediction methods. By integrating expression data into sequence-based predictions, possible false positives can be reduced. Previously, miRNA-mRNA interactions were explored with splitting-averaging Bayesian networks [28]. In that work, expression profiles of miRNA and mRNA from public databases, miRNA target prediction databases, and miRNA sequence information were integrated together to discover miRNA-mRNA interaction network.
Here, we combined expression profiles of miRNA and mRNA, and 3 target prediction databases, TargetScan, PicTar and miRanda, to obtain confident miRNA-mRNA relationships and construct miRNA-regulated protein-protein networks for breast cancer. Furthermore, we explored the functions of the miRNAs by inspecting
the underlying PINs of the miRNA with functional enrichment analysis. This method was already used previously to find functions of gastric cancer related miRNAs in the work of Tseng et al. [29]. In that research, a gastric cancer related miRNA, miR-148a, were discovered and validated to be related to tumor proliferation, invasion, migration, and survival rate of the patients. By using similar method, we wish to elucidate breast cancer related miRNA-regulated protein interaction networks (PINs) and their functions.
1.3 Specific aims
Main purposes of this work are described as follows:
1. To construct breast cancer-related miRNA-regulated protein interaction networks.
2. To elucidate the function of miRNA-regulated PINs.
3. To validate the results of the previous step by another expression profiles with clinical annotations (such as metastasis, survival).