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. 2013;8(1):e54213.
doi: 10.1371/journal.pone.0054213. Epub 2013 Jan 23.

Role of deregulated microRNAs in breast cancer progression using FFPE tissue

Affiliations

Role of deregulated microRNAs in breast cancer progression using FFPE tissue

Liang Chen et al. PLoS One. 2013.

Abstract

MicroRNAs (miRNAs) contribute to cancer initiation and progression by silencing the expression of their target genes, causing either mRNA molecule degradation or translational inhibition. Intraductal epithelial proliferations of the breast are histologically and clinically classified into normal, atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC). To better understand the progression of ductal breast cancer development, we attempt to identify deregulated miRNAs in this process using Formalin-Fixed, Paraffin-Embedded (FFPE) tissues from breast cancer patients. Following tissue microdissection, we obtained 8 normal, 4 ADH, 6 DCIS and 7 IDC samples, which were subject to RNA isolation and miRNA expression profiling analysis. We found that miR-21, miR-200b/c, miR-141, and miR-183 were consistently up-regulated in ADH, DCIS and IDC compared to normal, while miR-557 was uniquely down-regulated in DCIS. Interestingly, the most significant miRNA deregulations occurred during the transition from normal to ADH. However, the data did not reveal a step-wise miRNA alteration among discrete steps along tumor progression, which is in accordance with previous reports of mRNA profiling of different stages of breast cancer. Furthermore, the expression of MSH2 and SMAD7, two important molecules involving TGF-β pathway, was restored following miR-21 knockdown in both MCF-7 and Hs578T breast cancer cells. In this study, we have not only identified a number of potential candidate miRNAs for breast cancer, but also found that deregulation of miRNA expression during breast tumorigenesis might be an early event since it occurred significantly during normal to ADH transition. Consequently, we have demonstrated the feasibility of miRNA expression profiling analysis using archived FFPE tissues, typically with rich clinical information, as a means of miRNA biomarker discovery.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Unsupervised clustering results on both miRNAs and conditions of the 23 samples.
One solid color box represents a certain condition. The clustering dendrogram indicates stages from the same patient were more closely clustered than those from the same stages.
Figure 2
Figure 2. Unsupervised clustering results on ANOVA identified miRNAs and conditions of the 23 samples.
Each solid color box represents a certain condition. The clustering result indicates the significantly altered miRNA entities identified by ANOVA test have more potential to distinguish different stages of breast cancer than broad-wide miRNAs. Seven individual clusters were clearly discerned by the clustering algorithms and the miRNAs circled by red rectangles representing their discrete clusters.
Figure 3
Figure 3. qRT-PCR results displaying the raw Ct values of let-7a across all samples and stages.
The profile shows that let-7a expression was relatively consistent among different components and patients. The error bars indicate that the standard error of mean (SEM) is n = 4.
Figure 4
Figure 4. QRT-PCR verification of miRNAs expression results from microarray data.
Blue bars represent the results from microarray, while red bars indicate the results from qRT-PCR. The error bars are the standard error of mean (SEM) for each analysis. QRT-PCR results are largely consistent with our microarray data. Five representative miRNAs (miR-21, miR-183, miR-141, and miR-200b/c) were observed up-regulated during the Normal-ADH transition, and their high expression levels were maintained throughout the tumor developmental stages. miR-557 was found to be down-regulated specifically in the DCIS stage.
Figure 5
Figure 5. Venn diagram of ANOVA test results from paired and unpaired miRNA expression analysis.
ANOVA test on the paired miRNA microarray data analysis resulted in 35 deregulated miRNAs, while ANOVA test on the unpaired analysis showed 98 deregulated miRNAs. There are 10 overlapping miRNAs (miR-1268, mir-130a, miR-141, miR-193b, miR-200b, miR-21, miR-320a, miR-370, miR-557 and kshv-mir-K12-3).
Figure 6
Figure 6. Knockdown of miR-21 restores the expression of SMAD7 and MSH2 in MCF-7 and Hs578T breast cancer cell lines.
MCF-7 and Hs578T cells were transfected with miR-21 inhibitor and a negative mock control using the Lipofectamine 2000 kit (Invitrogen). After 48 hrs, miR-21 expression level was knocked down by ∼10 fold as compared to the mock controls in both MCF-7 (Fig. 6A) and Hs578T (Fig. 6B) cell lines using the Invitrogen SYBR green qRT-PCR kit. Untransfected cells were also included in the analysis (WT). With down-regulated miR-21 in both MCF-7 and Hs578T cells, MSH2 and SMAD7 mRNA expression was up-regulated by ∼1.67 and ∼3.6 fold, respectively (Fig. 6A and 6B), while the protein level was increased by ∼35–43% for MSH2 and ∼80–133% for SMAD7 (Fig. 6C).

References

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