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Updated: May 11, 2026

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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.
Molecular Genetics & Genomic Medicine
|March 3, 2026
Summary
This study analyzed the genomic landscape of pediatric B-cell precursor acute lymphoblastic leukemia (BCP-ALL) in Malaysian patients. SNP 6.0 microarray and MLPA revealed copy-number abnormalities, aiding in understanding BCP-ALL genetics.
Area of Science:
- Genetics
- Oncology
- Pediatrics
Background:
- B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is a common pediatric cancer.
- Chromosomal aberrations in BCP-ALL significantly impact patient prognosis.
- Understanding the genomic landscape is crucial for effective treatment.
Purpose of the Study:
- To comprehensively characterize the genomic landscape of BCP-ALL in 55 Malaysian patients.
- To identify and validate copy-number abnormalities (CNAs) in key oncogenes.
- To assess the utility of SNP 6.0 microarray and MLPA in BCP-ALL genetic profiling.
Main Methods:
- Utilized Single-Nucleotide Polymorphism (SNP) 6.0 microarray for CNA detection.
- Employed Multiplex Ligation-dependent Probe Amplification (MLPA) for CNA validation.
- Compared SNP 6.0 microarray with conventional cytogenetic techniques (karyotyping, FISH, RT-PCR).
Main Results:
- Identified 191 CNAs in 55 BCP-ALL patients, including hyperdiploidy and hypodiploidy.
- Detected various CNA types: interstitial (23.0%), terminal (17.2%), focal (37.1%), and intragenic (18.0%).
- SNP 6.0 microarray showed superior resolution for submicroscopic CNAs; MLPA confirmed abnormalities in oncogenes like CDKN2A/B, ETV6, and PAX5.
Conclusions:
- Combined SNP 6.0 microarray and MLPA provide a comprehensive genetic profile of BCP-ALL in Malaysian patients.
- This detailed genomic understanding can improve risk stratification.
- Findings support the development of personalized treatment strategies for BCP-ALL.

