Assessing karyotype precision by microarray-based comparative genomic hybridization in the myelodysplastic/myeloproliferative syndromes

BACKGROUND: Recent genome-wide microarray-based research investigations have revealed a high frequency of submicroscopic copy number alterations (CNAs) in the myelodysplastic syndromes (MDS), suggesting microarray-based comparative genomic hybridization (aCGH) has the potential to detect new clinically relevant genomic markers in a diagnostic laboratory. RESULTS: We performed an exploratory study on 30 cases of MDS, myeloproliferative neoplasia (MPN) or evolving acute myeloid leukemia (AML) (% bone marrow blasts ≤ 30%, range 0-30%, median, 8%) by aCGH, using a genome-wide bacterial artificial chromosome (BAC) microarray. The sample data were compared to corresponding cytogenetics, fluorescence in situ hybridization (FISH), and clinical-pathological findings. Previously unidentified imbalances, in particular those considered submicroscopic aberrations (< 10 Mb), were confirmed by FISH analysis. CNAs identified by aCGH were concordant with the cytogenetic/FISH results in 25/30 (83%) of the samples tested. aCGH revealed new CNAs in 14/30 (47%) patients, including 28 submicroscopic or hidden aberrations verified by FISH studies. Cryptic 344-kb RUNX1 deletions were found in three patients at time of AML transformation. Other hidden CNAs involved 3q26.2/EVI1, 5q22/APC, 5q32/TCERG1,12p13.1/EMP1, 12q21.3/KITLG, and 17q11.2/NF1. Gains of CCND2/12p13.32 were detected in two patients. aCGH failed to detect a balanced translocation (n = 1) and low-level clonality (n = 4) in five karyotypically aberrant samples, revealing clinically important assay limitations. CONCLUSIONS: The detection of previously known and unknown genomic alterations suggests that aCGH has considerable promise for identification of both recurring microscopic and submicroscopic genomic imbalances that contribute to myeloid disease pathogenesis and progression. These findings suggest that development of higher-resolution microarray platforms could improve karyotyping in clinical practice.