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      Comparison of the Agilent, ROMA/NimbleGen and Illumina platforms for classification of copy number alterations in human breast tumors

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          Abstract

          Background

          Microarray Comparative Genomic Hybridization (array CGH) provides a means to examine DNA copy number aberrations. Various platforms, brands and underlying technologies are available, facing the user with many choices regarding platform sensitivity and number, localization, and density distribution of probes.

          Results

          We evaluate three different platforms presenting different nature and arrangement of the probes: The Agilent Human Genome CGH Microarray 44 k, the ROMA/NimbleGen Representational Oligonucleotide Microarray 82 k, and the Illumina Human-1 Genotyping 109 k BeadChip, with Agilent being gene oriented, ROMA/NimbleGen being genome oriented, and Illumina being genotyping oriented. We investigated copy number changes in 20 human breast tumor samples representing different gene expression subclasses, using a suite of graphical and statistical methods designed to work across platforms. Despite substantial differences in the composition and spatial distribution of probes, the comparison revealed high overall concordance. Notably however, some short amplifications and deletions of potential biological importance were not detected by all platforms. Both correlation and cluster analysis indicate a somewhat higher similarity between ROMA/NimbleGen and Illumina than between Agilent and the other two platforms. The programs developed for the analysis are available from http://www.ifi.uio.no/bioinf/Projects/.

          Conclusion

          We conclude that platforms based on different technology principles reveal similar aberration patterns, although we observed some unique amplification or deletion peaks at various locations, only detected by one of the platforms. The correct platform choice for a particular study is dependent on whether the appointed research intention is gene, genome, or genotype oriented.

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          Most cited references 29

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          Genetic instabilities in human cancers.

          Whether and how human tumours are genetically unstable has been debated for decades. There is now evidence that most cancers may indeed be genetically unstable, but that the instability exists at two distinct levels. In a small subset of tumours, the instability is observed at the nucleotide level and results in base substitutions or deletions or insertions of a few nucleotides. In most other cancers, the instability is observed at the chromosome level, resulting in losses and gains of whole chromosomes or large portions thereof. Recognition and comparison of these instabilities are leading to new insights into tumour pathogenesis.
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            High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays.

            Gene dosage variations occur in many diseases. In cancer, deletions and copy number increases contribute to alterations in the expression of tumour-suppressor genes and oncogenes, respectively. Developmental abnormalities, such as Down, Prader Willi, Angelman and Cri du Chat syndromes, result from gain or loss of one copy of a chromosome or chromosomal region. Thus, detection and mapping of copy number abnormalities provide an approach for associating aberrations with disease phenotype and for localizing critical genes. Comparative genomic hybridization (CGH) was developed for genome-wide analysis of DNA sequence copy number in a single experiment. In CGH, differentially labelled total genomic DNA from a 'test' and a 'reference' cell population are cohybridized to normal metaphase chromosomes, using blocking DNA to suppress signals from repetitive sequences. The resulting ratio of the fluorescence intensities at a location on the 'cytogenetic map', provided by the chromosomes, is approximately proportional to the ratio of the copy numbers of the corresponding DNA sequences in the test and reference genomes. CGH has been broadly applied to human and mouse malignancies. The use of metaphase chromosomes, however, limits detection of events involving small regions (of less than 20 Mb) of the genome, resolution of closely spaced aberrations and linking ratio changes to genomic/genetic markers. Therefore, more laborious locus-by-locus techniques have been required for higher resolution studies. Hybridization to an array of mapped sequences instead of metaphase chromosomes could overcome the limitations of conventional CGH (ref. 6) if adequate performance could be achieved. Copy number would be related to the test/reference fluorescence ratio on the array targets, and genomic resolution could be determined by the map distance between the targets, or by the length of the cloned DNA segments. We describe here our implementation of array CGH. We demonstrate its ability to measure copy number with high precision in the human genome, and to analyse clinical specimens by obtaining new information on chromosome 20 aberrations in breast cancer.
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              Evaluation of gene expression measurements from commercial microarray platforms.

               P. Tan (2003)
              Multiple commercial microarrays for measuring genome-wide gene expression levels are currently available, including oligonucleotide and cDNA, single- and two-channel formats. This study reports on the results of gene expression measurements generated from identical RNA preparations that were obtained using three commercially available microarray platforms. RNA was collected from PANC-1 cells grown in serum-rich medium and at 24 h following the removal of serum. Three biological replicates were prepared for each condition, and three experimental replicates were produced for the first biological replicate. RNA was labeled and hybridized to microarrays from three major suppliers according to manufacturers' protocols, and gene expression measurements were obtained using each platform's standard software. For each platform, gene targets from a subset of 2009 common genes were compared. Correlations in gene expression levels and comparisons for significant gene expression changes in this subset were calculated, and showed considerable divergence across the different platforms, suggesting the need for establishing industrial manufacturing standards, and further independent and thorough validation of the technology.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2008
                8 August 2008
                : 9
                : 379
                Affiliations
                [1 ]Department of Genetics, Institute for Cancer Research, Norwegian Radium Hospital, Rikshospitalet University Hospital, 0310 Oslo, Norway
                [2 ]Department of Pathology, Norwegian Radium Hospital, Rikshospitalet University Hospital, 0310 Oslo, Norway
                [3 ]Biomedical Research Group, Department of Informatics, University of Oslo, P.O. Box 1080 Blindern, 0316 Oslo, Norway
                [4 ]Faculty Division The Norwegian Radium Hospital, University of Oslo, Oslo, Norway
                [5 ]Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
                [6 ]Agilent Technologies, Inc., 5301 Stevens Creek Blvd, Santa Clara, CA 95052, USA
                [7 ]Illumina, Inc., 9885 Towne Centre Drive, San Diego, CA 92121, USA
                [8 ]Department of Oncology, Norwegian Radium Hospital, Rikshospitalet University Hospital, 0310 Oslo, Norway
                [9 ]Centre for Cancer Biomedicine, University of Oslo, Oslo, Norway
                Article
                1471-2164-9-379
                10.1186/1471-2164-9-379
                2547478
                18691401
                Copyright © 2008 Baumbusch et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Categories
                Research Article

                Genetics

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