Global gene expression analysis of canine cutaneous mast cell tumor

In the present study, canine mast cell tumor (MCT) transcriptome was characterized in order to identify a set of candidate genes potentially useful for MCT classification and prognosis prediction. Fifty-one canine MCT biopsies were enrolled in the study. Isolated and purified total RNAs were individually hybridized to the Agilent Canine V2 4x44k DNA microarray. The comparison of reference differentiated and undifferentiated MCT transcriptome revealed a total of 597 differentially expressed genes (450 up-regulated and 147 down-regulated). The functional analysis of this set of genes provided evidence that they were mainly involved in cell cycle, DNA replication, p53 signaling pathway, nucleotide excision repair and pyrimidine metabolism. Class prediction analysis identified 13 transcripts providing the greatest accuracy of class prediction and divided samples into two categories (differentiated and undifferentiated MCTs). The molecular classification here used was prognostically significant, as the groups were directly correlated with survival time (p = 0.0026). In this study, we analyzed the gene expression profiles of 51 mast cell tumour samples using Agilent Canine V2 4x44k (G2519F, Design ID 021193) DNA microarray platform (60 arrays, 8 replicates) based on single-colour detection (Cyanine-3 only). Microarrays are scanned with Agilent scanner G2565BA (barcode on the left, DNA on the back surface, scanned through the glass) at a resolution of 5 microns; all slides are scanned twice at two different sensitivity settings (XDRHi 100% and XDRLo 10%); the scanner software creates a unique ID for each pair of XDR scans and saves it to both scan image files. Feature Extraction 9.5 uses XDR ID to link the pairs of scans together automatically when extracting data. The signal left, after all the FE processing steps have been completed, is ProcessedSignal that contains the Multiplicatively Detrended, Background-Subtracted Signal.