• Journal of Interdisciplinary Genomics
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• v.6 no.2
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• pp.33-36
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• 2024

Chromosomal microarray (CMA) can detect genome-wide small copy number abnormalities (CNAs) and copy-neutral loss of heterozygosity (CN-LOH) better than conventional karyotyping and fluorescence in situ hybridization (FISH) for hematologic malignancies. Apart from the limitations in detecting balanced chromosomal rearrangements and low-level malignant clones, CMA has clinical utility in detecting significant recurrent and novel variants with diagnostic, prognostic, and therapeutic evidence. It can successfully complement conventional cytogenetic tests for several hematological malignancies, including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), and multiple myeloma (MM). An increase in CMA testing for hematologic malignancies is expected to identify novel markers of clinical significance.

• Genomics & Informatics
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• v.20 no.1
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• pp.4.1-4.8
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• 2022

Loss of heterozygosity (LOH) is a genomic aberration. In some cases, LOH can be generated without changing the copy number, which is called copy-neutral LOH (CN-LOH). CN-LOH frequently occurs in various human diseases, including cancer. However, the biological and clinical implications of CN-LOH for human diseases have not been well studied. In this study, we compared the performance of CN-LOH determination using three commonly used tools. For an objective comparison, we analyzed CN-LOH profiles from single-nucleotide polymorphism array data from 10 colon adenocarcinoma patients, which were used as the reference for comparison with the CN-LOHs obtained through whole-exome sequencing (WES) data of the same patients using three different analysis tools (FACETS, Nexus, and Sequenza). The majority of the CN-LOHs identified from the WES data were consistent with the reference data. However, some of the CN-LOHs identified from the WES data were not consistent between the three tools, and the consistency with the reference CN-LOH profile was also different. The Jaccard index of the CN-LOHs using FACETS (0.84 ± 0.29; mean value, 0.73) was significantly higher than that of Nexus (0.55 ± 0.29; mean value, 0.50; p = 0.02) or Sequenza (0 ± 0.41; mean value, 0.34; p = 0.04). FACETS showed the highest area under the curve value. Taken together, of the three CN-LOH analysis tools, FACETS showed the best performance in identifying CN-LOHs from The Cancer Genome Atlas colon adenocarcinoma WES data. Our results will be helpful in exploring the biological or clinical implications of CN-LOH for human diseases.