Deciphering Squamous Cell Carcinoma Using Multidimensional Genomic Approaches

Figure 3

Multidimensional omics data integration using SIGMA2 software. Combined genetic, epigenetic and gene expression analysis of cancer samples facilitates identification of oncogenes and tumor suppressor genes which are concertedly disrupted. (a) Examples of annotation tracks. (b) Copy number profile from array CGH experiment—a focal DNA amplification of a region on 17q12 is highlighted in yellow. (c) Allelic status (SNP array). This region is also encompassed in a large stretch of allelic imbalance. Blue horizontal bars indicate loci that become homozygous (loss of heterozygosity) in the tumor sample. (d) DNA methylation analysis (MeDIP-microarray) shows a concurrent loss of methylation, as indicated by a peak shifted to left of the center line. (e) Heat map summary of gene expression profile in the region of interest. The gene boxed in blue on the heatmap is ERBB2. It shows the highest level of differential expression between the tumor line and a panel of normal tissue samples. (f) The histogram displays the relative expression of the tumor sample as compared with the normal samples for ERBB2 (i.e., expanded view from heat map).