Genome-wide analysis of DNA copy-number changes using cDNA microarrays

Abstract

Gene amplifications and deletions frequently contribute to tumorigenesis. Characterization of these DNA copy-number changes is important for both the basic understanding of cancer and its diagnosis. Comparative genomic hybridization (CGH) was developed to survey DNA copy-number variations across a whole genome. With CGH, differentially labelled test and reference genomic DNAs are co-hybridized to normal metaphase chromosomes, and fluorescence ratios along the length of chromosomes provide a cytogenetic representation of DNA copy-number variation. CGH, however, has a limited ( approximately 20 Mb) mapping resolution, and higher-resolution techniques, such as fluorescence in situ hybridization (FISH), are prohibitively labour-intensive on a genomic scale. Array-based CGH, in which fluorescence ratios at arrayed DNA elements provide a locus-by-locus measure of DNA copy-number variation, represents another means of achieving increased mapping resolution. Published array CGH methods have relied on large genomic clone (for example BAC) array targets and have covered only a small fraction of the human genome. cDNAs representing over 30,000 radiation-hybrid (RH)-mapped human genes provide an alternative and readily available genomic resource for mapping DNA copy-number changes. Although cDNA microarrays have been used extensively to characterize variation in human gene expression, human genomic DNA is a far more complex mixture than the mRNA representation of human cells. Therefore, analysis of DNA copy-number variation using cDNA microarrays would require a sensitivity of detection an order of magnitude greater than has been routinely reported. We describe here a cDNA microarray-based CGH method, and its application to DNA copy-number variation analysis in breast cancer cell lines and tumours. Using this assay, we were able to identify gene amplifications and deletions genome-wide and with high resolution, and compare alterations in DNA copy number and gene expression.