Fig 1.
The overview of the methodology used for gene expression profiling and identification of major networks and pathways associated with canine mammary tumour (CMT).
Fig 2.
Venn diagram analysis showing overlap of dysregulated genes among malignant and benign mammary cancer tissues.
(A) Overlay of up-regulated genes (logFC>1) among benign tumour tissues. (B). Overlay of genes commonly up-regulated in all the malignant and benign tissues. 269 genes were commonly up-regulated in all the benign tissues (n = 4), whereas 90 common genes were up-regulated in all the malignant tissues (n = 6).) Out of these 32 genes were commonly dysregulated in all the malignant (n = 6) and benign tissues (n = 4) studied. (C) Overlay of genes up-regulated in all the malignant tissues and individual benign tissues (1–4). Analysis revealed that there was no such gene which was uniquely up-regulated in all the malignant tissues, as the dysregulated genes which were common in all the malignant tissues were also present in either one or all the benign tissues.
Fig 3.
Fold change concordance of selected dysregulated genes by qPCR.
The expression levels of the selected genes were compared between microarray and qPCR analysis. For microarray analysis, mean normalised signals from malignant and tissues were clubbed separately for comparison of gene expression levels. The expression levels represent log2 fold change values calculated from the normalised signal intensity values using healthy mammary tissues expression data as control. For qPCR analysis, gene expression in each sample was normalized against the expression of β-actin gene. The relative expression of each sample was calculated using the 2−ΔΔCT method with healthy group as calibrator and the log2fold change (log2FC) was plotted.
Fig 4.
2D gel electrophoresis of malignant CMT versus healthy mammary gland tissues.
Upon analysis of 2D gels of malignant versus healthy mammary tissue, 7 differentially expressed spots, (indicated by arrows 1–7) were identified in malignant tissue.
Fig 5.
Top Canonical pathways identified using IPA in benign (A) and malignant (B) CMTs.
Fig 6.
The top-ranked enriched canonical pathway identified in malignant CMTs using IPA: Cyclins and cell cycle regulation pathway.
Fig 7.
Apoptosis signalling pathway: The second-ranked enriched canonical pathway identified in malignant CMTs.
Fig 8.
The top-ranked enriched canonical pathway identified in benign CMTs using IPA: The TREM1 signalling pathway.
Fig 9.
Dendritic cell maturation: Second enriched canonical pathway in benign CMTs, identified using IPA.
Table 1.
Canonical pathways with highest enrichment scores (z-score) in malignant CMTs and associated DEGs.
Table 2.
Canonical pathways with highest enrichment scores (z-score) in benign CMTs and associated DEGs.
Fig 10.
Canonical pathway–G2/M DNA damage checkpoint in (A) malignant and (B) benign CMTs.
Fig 11.
Various genes affected by top activated upstream regulators in malignant (A and B) and benign (C and D) CMTs.
Fig 12.
Various genes affected by top inhibited upstream regulators in malignant (A and B) and benign (C and D) CMTs.
Table 3.
Upstream regulators in malignant CMTs.
Table 4.
Upstream regulators in benign CMTs.
Table 5.
Diseases and bio-functions associated with malignant CMTs and their association with the top signalling pathways.
Table 6.
Diseases and bio-functions associated with benign CMTs and their association with the top signalling pathways.
Fig 13.
Top scoring networks in malignant (A) and benign (B) CMTs. Top scoring network in malignant CMTs involved a central node of BUB1B, while top network amongst benign tumours involved VEGF central hub.