1Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, NY. 2Intel Corporation, Santa Clara, CA. 3Affymetrix Inc., Santa Clara, CA. 4Lilly Singapore Centre for Drug Discovery, Singapore. 5Molecular Cytogenetics Core Facility, Memorial Sloan-Kettering Cancer Center, New York, NY. 6Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY. 7NuGEN Inc, San Carlos, CA. 8Pathwork Diagnostics, Sunnyvale, CA.
We report a method, Expression-Microarray Copy Number Analysis (ECNA) for the detection of copy number changes using Affymetrix Human Genome U133 Plus 2.0 arrays, starting with as little as 5 ng input genomic DNA. An analytical approach was developed using DNA isolated from cell lines containing various X-chromosome numbers, and validated with DNA from cell lines with defined deletions and amplifications in other chromosomal locations. We applied this method to examine the copy number changes in DNA from 5 frozen gastrointestinal stromal tumors (GIST). We detected known copy number aberrations consistent with previously published results using conventional or BAC-array CGH, as well as novel changes in GIST tumors. These changes were concordant with results from Affymetrix 100K human SNP mapping arrays. Gene expression data for these GIST samples had previously been generated on U133A arrays, allowing us to explore correlations between chromosomal copy number and RNA expression levels. One of the novel aberrations identified in the GIST samples, a previously unreported gain on 1q21.1 containing the PEX11B gene, was confirmed in this study by FISH and was also shown to have significant differences in expression pattern when compared to a control sample. In summary, we have demonstrated the use of gene expression microarrays for the detection of genomic copy number aberrations in tumor samples. This method may be used to study copy number changes in other species for which RNA expression arrays are available, e.g. other mammals, plants, etc., and for which SNPs have not yet been mapped.
PDF (1.49 MB PDF FORMAT)
RIS citation (ENDNOTE, REFERENCE MANAGER, PROCITE, REFWORKS)
BibTex citation (BIBDESK, LATEX)
This is the first time for us to submit a manuscript to Cancer Informatics. We thank the peer reviewers for their insightful comments, which have improved our manuscript markedly. We were pleased to find that the staff were extremely helpful and kept us informed of the progress of the submission step-by-step. Our experience with Cancer Informatics has been tremendous. Thank you very much!