Es of early stage breast cancer could have broadwide miRNA expression

Es of early stage breast cancer could have broadwide miRNA expression signatures. To pursue this hypothesis, unsupervised hierarchical clustering was carried on 23 distinct tumor stage samples and also on all detected miRNAs on the arrays using Euclid correlation and centroid linkage. However, after hierarchical clustering, we failed to readily find distinctA set of samples (-)-Indolactam V site diagnosed with Normal, ADH, DCIS, and IDC (4 of each) were subject to the microarray analysis as we performed for the microdissected groups. In both paired and un-paired analyses, there were more deregulated miRNAs during the Normal-ADH transition compared to other processes. Deregulated miRNAs that appeared in both analyses are bolded. doi:10.1371/journal.pone.0054213.tclusters separated by different stages as expected. Instead, asynchronous stages from the same patient were shown to cluster more closely to each other than to their peer-stages from different patients (Fig. 1). This seems to be consistent with mRNA expression profiling in the progression of human breast cancer as previously reported [29]. This finding is also reasonable as theDeregulated miRNAs in Breast Cancerdistinct stages of breast cancer are evolutionally associated with the same origin tumor colony or tumor stem cell within the individual patient. Therefore the alterations of most miRNA repertories are inherited from that stem cell and differ from others. Furthermore, it might also explain the reason why some patients diagnosed with ADH or DCIS never progress to IDC.MiRNAs as Potential Molecular Markers for Early Stage Breast CancerInstead of persisting on the existence of a stage specific miRNA KS 176 web signature of early breast lesion, we started to focus on whether there will be some individual or combination of unique miRNAsfor each stage. ANOVA test was applied to look for stage specific deregulated miRNAs with statistical significance (p, = 0.05). We successfully found 35 miRNAs with unique expression in one certain stage against the others. Another unsupervised hierarchical clustering based on the identified differentially expressed miRNAs was generated to determine if they can distinguish between the different stages of breast lesion. The clustering results indicated the significantly altered miRNA entities identified by the ANOVA test distinguished between different stages of breast lesion better than broad-wide miRNAs. Seven individual clusters were clearly discerned by the clustering algorithms (Fig. 2). We selected a short list of miRNAs (miR-644, miR-556-3p, miR-557, miR-141, miR-183, miR-200b and miR-21) based on both their represen-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. doi:10.1371/journal.pone.0054213.gDeregulated miRNAs in Breast CancerFigure 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. doi:10.1371/journal.pone.005421.Es of early stage breast cancer could have broadwide miRNA expression signatures. To pursue this hypothesis, unsupervised hierarchical clustering was carried on 23 distinct tumor stage samples and also on all detected miRNAs on the arrays using Euclid correlation and centroid linkage. However, after hierarchical clustering, we failed to readily find distinctA set of samples diagnosed with Normal, ADH, DCIS, and IDC (4 of each) were subject to the microarray analysis as we performed for the microdissected groups. In both paired and un-paired analyses, there were more deregulated miRNAs during the Normal-ADH transition compared to other processes. Deregulated miRNAs that appeared in both analyses are bolded. doi:10.1371/journal.pone.0054213.tclusters separated by different stages as expected. Instead, asynchronous stages from the same patient were shown to cluster more closely to each other than to their peer-stages from different patients (Fig. 1). This seems to be consistent with mRNA expression profiling in the progression of human breast cancer as previously reported [29]. This finding is also reasonable as theDeregulated miRNAs in Breast Cancerdistinct stages of breast cancer are evolutionally associated with the same origin tumor colony or tumor stem cell within the individual patient. Therefore the alterations of most miRNA repertories are inherited from that stem cell and differ from others. Furthermore, it might also explain the reason why some patients diagnosed with ADH or DCIS never progress to IDC.MiRNAs as Potential Molecular Markers for Early Stage Breast CancerInstead of persisting on the existence of a stage specific miRNA signature of early breast lesion, we started to focus on whether there will be some individual or combination of unique miRNAsfor each stage. ANOVA test was applied to look for stage specific deregulated miRNAs with statistical significance (p, = 0.05). We successfully found 35 miRNAs with unique expression in one certain stage against the others. Another unsupervised hierarchical clustering based on the identified differentially expressed miRNAs was generated to determine if they can distinguish between the different stages of breast lesion. The clustering results indicated the significantly altered miRNA entities identified by the ANOVA test distinguished between different stages of breast lesion better than broad-wide miRNAs. Seven individual clusters were clearly discerned by the clustering algorithms (Fig. 2). We selected a short list of miRNAs (miR-644, miR-556-3p, miR-557, miR-141, miR-183, miR-200b and miR-21) based on both their represen-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. doi:10.1371/journal.pone.0054213.gDeregulated miRNAs in Breast CancerFigure 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. doi:10.1371/journal.pone.005421.

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