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J Clin Pathol. 2018 Apr;71(4):372-378. doi: 10.1136/jclinpath-2017-204823. Epub 2017 Dec 2.

Detection of genome-wide copy number variants in myeloid malignancies using next-generation sequencing.

Author information

1
ARUP Laboratories, Salt Lake City, Utah, USA.
2
Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, USA.
#
Contributed equally

Abstract

AIMS:

Genetic abnormalities, including copy number variants (CNV), copy number neutral loss of heterozygosity (CN-LOH) and gene mutations, underlie the pathogenesis of myeloid malignancies and serve as important diagnostic, prognostic and/or therapeutic markers. Currently, multiple testing strategies are required for comprehensive genetic testing in myeloid malignancies. The aim of this proof-of-principle study was to investigate the feasibility of combining detection of genome-wide large CNVs, CN-LOH and targeted gene mutations into a single assay using next-generation sequencing (NGS).

METHODS:

For genome-wide CNV detection, we designed a single nucleotide polymorphism (SNP) sequencing backbone with 22 762 SNP regions evenly distributed across the entire genome. For targeted mutation detection, 62 frequently mutated genes in myeloid malignancies were targeted. We combined this SNP sequencing backbone with a targeted mutation panel, and sequenced 9 healthy individuals and 16 patients with myeloid malignancies using NGS.

RESULTS:

We detected 52 somatic CNVs, 11 instances of CN-LOH and 39 oncogenic mutations in the 16 patients with myeloid malignancies, and none in the 9 healthy individuals. All CNVs and CN-LOH were confirmed by SNP microarray analysis.

CONCLUSIONS:

We describe a genome-wide SNP sequencing backbone which allows for sensitive detection of genome-wide CNVs and CN-LOH using NGS. This proof-of-principle study has demonstrated that this strategy can provide more comprehensive genetic profiling for patients with myeloid malignancies using a single assay.

KEYWORDS:

chromosomes; leukaemia; molecular oncology

PMID:
29197855
DOI:
10.1136/jclinpath-2017-204823
[Indexed for MEDLINE]

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