Genetic Profiling of Adult Acute Lymphoblastic Leukemia Cells by Single Nucleotide Polymorphism Oligonucleotide Microarray.

Abstract

Acute lymphoblastic leukemia (ALL) is a malignant disease of bone marrow cells, resulting from accumulation of genetic alterations of these cells. We analyzed 74 adult ALL samples by single-nucleotide polymorphism DNA microarray (SNP-Chip) using the new algorithm AsCNAR (allele-specific copy-number analysis using anonymous references). 71 samples (96%) showed genomic abnormalities in a mean 4.5 chromosomes including duplications, deletions and loss of heterozygosity with normal copy number [we call this uniparental disomy (UPD)]. About 25% of samples had a normal karyotype but each had genomic changes detectable by SNP-Chip. Importantly, 21 cases (28%) had UPD, and 29% of these had 9p UPD. Other genomic defects included deletions of p16INK4A in 18 cases (24%), deletions of ETV6 in 7 cases (9%), and hyperdiploidy (>50 chromosomes) in 3 cases (4%). In contrast, we also analyzed 399 pediatric ALL samples and deletions occurred in p16INK4A (28%) and ETV6 (22%) and 29% cases had hyperdiploidy. Hyperdiploidy is associated with a good prognosis and occured much more frequency in pediatric ALL (29%) than adult ALL (4%) which may in part explain the better prognosis in pediatric ALL compared to adult ALL. Also, small copy number changes were detected in adult ALL including deletion of B-cell differentiation genes: EBF (4 cases, 5%), Pax5 (5 cases, 7%) and IKZF (Ikaros) (8 cases, 11%), as well as, deletion of miR-15a and miR-16-1 (2 cases, 3%), which is often found in CLL. Amplification of Rel and BCL11A occurred in one case and amplification of Akt2 occurred in another case. Moreover, we found PAX5/ETV6 fusion in one case (1%); in comparison, 14 of 399 pediatric ALL cases (4%) had PAX5 fusion genes. In summary, we discovered hidden abnormalities including small copy number change and UPD in adult ALL and identified differences between adult and pediatric ALLs. In the future, routine SNP-Chip analysis may provide novel subclassification criteria for ALL and identify unique therapeutic targets.