Supplementary Material for: Four-Copy Number Intervals in SNP Microarray Analysis: Unique Patterns and Positions

Over the past several years, the utility of microarray technology in delineating copy number changes has become well established. In the past 4 years, we have used the SNP array to detect and analyze allele ratios in 150 cases with 4-copy intervals, confirmed by FISH, offering insight into the underlying mechanisms of formation. These cases may be divided into 5 allele patterns - the first 4 of which involve a single homologue - as detected by the genotyping aspects of the microarray: (1) triplications combining homozygous and heterozygous alleles, with a 3:1 ratio of heterozygotes; (2) triplications with allele patterns combining homozygous and heterozygous alleles, with heterozygote ratios of both 3:1 and 2:2; (3) triplications that have homozygous alleles combined with only 2:2 heterozygous alleles; (4) triplications that are completely homozygous; and (5) homozygous duplications on each homologue with no heterozygous alleles. The implications of copy number variants with diverse allelic segregations are presented in this study

Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Subclassification of Leukemia: Report From the International Microarray Innovations in Leukemia Study Group

Purpose The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. Methods The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling-based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. Results On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods. Conclusion Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias