Cytogenomic microarray analysis (CMA) offers high resolution, genome-wide copy number information and is widely used in clinical laboratories for diagnosis of constitutional abnormalities. The Cancer Genomics Consortium (CGC) conducted a multiplatform, multicenter clinical validation project to compare the reliability and inter- and intralaboratory reproducibility of this technology for clinical oncology applications. Four specimen types were processed on three different microarray platforms-from Affymetrix, Agilent, and Illumina. Each microarray platform was employed at two independent test sites. The results were compared in a blinded manner with current standard methods, including karyotype, FISH, or morphology. Twenty-nine chronic lymphocytic leukemia blood, 34 myelodysplastic syndrome bone marrow, and 30 fresh frozen renal epithelial tumor samples were assessed by all six laboratories. Thirty formalin fixed paraffin embedded renal tumor samples were analyzed at the Affymetrix and Agilent test sites only. All study samples were initial diagnostic samples. Array data were analyzed at each participating site and were submitted to caArray for central analysis. Laboratory interpretive results were submitted to the central analysis team for comparison with the standard-of-care assays and for calculation of intraplatform reproducibility and cross-platform concordance. The results demonstrated that the three microarray platforms 1) detect clinically actionable genomic changes in cancer compatible to standard-of-care methods; 2) further define cytogenetic aberrations; 3) identify submicroscopic alterations and loss of heterozygosity (LOH); and 4) yield consistent results within and between laboratories. Based on this study, the CGC concludes that CMA is a sensitive and reliable technique for copy number and LOH assessment that may be used for clinical oncology genomic analysis.
Pharmacology, Toxicology and Pharmaceutical Science
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3%
Other
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Unknown
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Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 October 2015.
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#24,994,904
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Outputs of similar age from Cancer Genetics
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