Integration of whole-genome SNP mapping and transcriptional data in the human metastatic renal carcinoma Caki-1 cell line

We use Caki-1 cell line, derived from a human metastatic clear cell renal carcinoma (HTB-46, ATCC), as an “in vitro“ model for this pathology to study correlations between transcriptomic and genomic profiles analized by high-density oligonucleotide microarray technology. Gene expression analysis was performed on Affymetrix GeneChip® HG-U133 Plus 2.0, using 3 Caki-1 replicates and a Universal Human Reference RNA® (hRefRNA, Stratagene), a commercial pool of total RNA from 10 human tumor cell lines. Genome-wide SNP mapping and analysis for DNA copy number changes in Caki-1 cell line were performed using Affymetrix GeneChip® Human Mapping 100K platform. Transcriptional data were analyzed using Significance Analysis for Microarrays (SAM) algorithm [1], which allowed the identification of more than 3000 differentially expressed genes (DEG) in Caki-1 as compared to hRefRNA. Functional ontology analysis of these DEG showed that most of them are related to some recurrent functional classes, such as apoptosis, cell adhesion, cell cycle and metabolism. We mapped DEG on the human genome according to annotations contained in the NetAffx database. Using the Copy Number Analyzer for Affymetrix GeneChip algorithm (CNAG, v1.1) [2], multiple chromosomal aberrations were found, such as copy number gains in chromosomes 1q, 3q, 4p, 5p-tel, 5q, 7q, 8q, 10, 11p, 12, 16q, 17q and 18p-tel, losses in chromosomes 14, 15p-tel, 17p-tel, 18, 20p, 22 and X, and regions affected by loss of heterozigosity on chromosomes 3p, 4q, 8q, 9, 11q, 14, 15, 17p-tel, 18 and 22. Results from the whole transcriptome and genome analyses were integrated through new bioinformatics strategies able to correlate genome-wide gene expression levels to DNA copy number data. This approach revealed that there is a considerable influence of copy number on gene expression patterns and that organizing gene expression data by genomic mapping location and scanning for regions containing statistically modulated gene expression signals may allow detecting chromosomal aberrations. References [1] Tusher VG et al., Significance analysis of microarrays applied to the ionizing radiation response, PNAS (2001), 98: 5116-5121. [2] Nannya Y et al., A robust algorithm for copy number detection using high-density oligonucleotide single nucleotide polymorphism genotyping arrays, Cancer Research (2005), 65(14): 6071-9. This work was supported by MIUR-FIRB grants n°RBNE01HCKF and n°RBNE01TZZ8.