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Updated: May 11, 2026
Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
Published on: February 21, 2015
Single Nucleotide Polymorphism Microarray Analysis Unveils Copy-Number Abnormalities and Genetic Heterogeneity in
Nor Soleha Mohd Dali1, Nursaedah Abdullah Aziz1, Muhamad Farid Zulkifle1
1Cancer Research Centre, Institute for Medical Research, National Institutes of Health, Ministry of Health, Selangor, Malaysia.
Introduction:
B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is a prevalent pediatric hematologic malignancy characterized by diverse chromosomal aberrations that significantly influence its prognosis. This study aimed to comprehensively characterize the genomic landscape of BCP-ALL in 55 Malaysian patients with BCP-ALL.
Methods:
Single-nucleotide polymorphism (SNP) 6.0 microarray and multiplex ligation-dependent probe amplification were utilized to characterize and validate copy-number abnormalities involving key oncogenes, respectively.
Results:
The SNP 6.0 microarray identified 191 copy-number abnormalities in 55 patients, including common subtypes such as hyperdiploidy (n = 14/191, 7.3%), hypodiploidy (n = 2/191, 1.1%), and various copy-number abnormalities such as interstitial (23.0%), terminal (17.2%), focal (37.1%), and intragenic (18.0%). Notably, intrachromosomal amplification of chromosome 21 (iAMP21) was not observed, suggesting its rarity in this cohort. Comparison with conventional cytogenetic techniques, including Trypsin-Leishman's banding karyotyping, fluorescent in situ hybridization (FISH), and reverse transcription-polymerase chain reaction (RT-PCR), revealed superior resolution of the SNP 6.0 microarray in detecting submicroscopic copy-number abnormalities. Furthermore, MLPA confirmed abnormalities in several oncogenes, including CDKN2A/B, EBF1, ERG, ETV6, IKZF1, JAK2, and PAX5.
Conclusion:
This study demonstrates the utility of combined SNP 6.0 microarray and MLPA in providing a comprehensive and refined understanding of the genetic landscape of BCP-ALL in the Malaysian population. This understanding may facilitate risk stratification and the development of personalized treatment strategies.
