Additional file 2: Figure S1. of A transcriptome-based protein network that identifies new therapeutic targets in colorectal cancer

Hierarchical clustering of colorectal carcinoma (CRC) and normal colon tissue (NT) based on gene expression profiling obtained from each type of PCR array. Log2-transformed fold-change values from genes fulfilling the criteria of PCR Data Analysis (Qiagen) obtained for each specific PCR array (fold-change > 1.7 and q < 0.05) were analyzed with Cluster and Treeview, using centered correlation and average linkage [63]. Red and green colors indicate transcript levels above and below the median values, respectively. NT, normal colon tissue (n=19) and CRC, colorectal carcinoma (n=95). Tumor samples were identified by a number followed by the Tumor Bank running number (S0, S1, S2, S3, S4) corresponding to the grading stage according to the pathological classification. Genes identified by their gene symbol appear on the right side of each panel. Each column gives the gene expression profile of a sample, and each line indicates the variations in the level of expression of a given gene among tissue samples. The length of the branches of the trees forming the dendrograms on the top of each panel reflects the degree of similarity between samples; the longer the branch, the larger the difference in gene expression. A, Hierarchical clustering based on 14 deregulated genes from the “Apoptosis” PCR array; B, Hierarchical clustering based on 33 deregulated genes from the “Cancer Pathway” PCR array; C, Hierarchical clustering based on 29 deregulated genes from the “Lipoprotein signaling and cholesterol metabolism” PCR array; D, Hierarchical clustering based on 23 deregulated genes from the “Drug metabolism” PCR array; E, Hierarchical clustering based on 18 deregulated genes from the “Wnt pathway” PCR array. (ZIP 2488 kb)