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Genome Wide Profiling of Paired Cancerous and Normal Breast Tissues and Rapid Interpretation of Gene Expression Data

derive the identity of potential biomarkers for diagnostic or therapeutic purposes. For example, a number of genes that were not detectable in normal breast tissue samples but showed significant expression in cancerous tissues were identified (partial list shown in Table 3). These genes are potential markers that may be involved in tumor functions. Additionally, it was observed that a number of genes differentially expressed in this study have not been assigned information in the public database but are present in the Celera Discovery System database, meaning that the function of these genes have been less studied or relatively unknown. However, additional information about these genes is present in the Oracle Database. Table 4 shows a partial list of the genes that are not identified in the public database and are significantly differentially expressed with p-values of < 0.001 in this study. Also listed is the Panther families, classification, their associated molecular functions, and biological processes.

Validation with TaqMan Gene Expression Assays

To confirm the expression detected by microarrays, quantitative real-time PCR analysis was conducted for selected genes. These genes were identified (S/N > 3) in all 12 arrays and A. B. Figure 4. Clustering of microarray data. Two-dimensional hierarchical clustering analysis was performed using GeneSpring Software (Silicon Genetics, Redwood City, CA, USA). Red and blue represent high and low expression levels, respectively and yellow represents no, or unchanged, expression. In two-dimensional clustering analysis, arrays or samples (x axis) and genes (y axis) were clustered based on the similarity of their gene expression patterns. A. 2,508 genes generated from ANOVA test p < 0.01. B. Among the 2,508 genes, 200 genes are involved in signal transduction pathways as classified by the Panther gene classification system. < 0.05 5,703 < 0.01 2,508 < 0.001 796 P-value Cutoff Nu
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