Comprehensive Detection of Chromosomal and Genomic Abnormalities via Next-Generation Sequencing-Based Genomic Proximity Mapping Improves Diagnostic Classification of Hematologic Neoplasms

<b>Background/Objectives:</b> Accurate detection of all classes of genomic structural variants (SVs), including chromosomal rearrangements and copy number alterations (CNAs), is essential for the diagnosis and classification of hematologic neoplasms. Conventional cytogenetic methods currently serve as routine clinical tools for detecting SVs. However, each commonly used cytogenetic test has specific limitations, and sequential application of these different tests may delay timely diagnosis and treatment. <b>Methods</b>: In this study, we evaluated the feasibility and utility of genomic proximity mapping (GPM), a novel high-throughput chromosome conformation capture (Hi-C)-based next-generation sequencing (NGS) method, to identify chromosomal and genetic aberrations in hematologic neoplasms in the clinical setting. GPM was performed on 18 cases of hematologic neoplasms (fresh/frozen cells or formalin-fixed paraffin-embedded tissue), and concordance with other methodologies was assessed, including karyotyping, FISH, RT-PCR, chromosomal microarray analysis (CMA), and/or RNA sequencing. <b>Results:</b> GPM reliably detected balanced and unbalanced chromosomal rearrangements, including chimeric gene fusions and gene juxtapositions, with 95.2% concordance with previously applied methods in cases with >10% tumor burden. Additionally, GPM can detect CNAs and copy-neutral loss of heterozygosity (cnLOH) simultaneously in a single assay. Furthermore, detection of genomic rearrangements not identified by other methods improved the accuracy of disease classification. <b>Conclusions:</b> These findings demonstrate that GPM is a powerful method for identifying clinically actionable variants in hematologic neoplasms, overcoming some limitations of current cytogenetic technologies and improving the diagnostic accuracy and classification in challenging cases.

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Publication Details

Journal
Cancers
Published
2025-11-26
DOI
https://doi.org/10.3390/cancers17233775
Primary Topic
Acute Myeloid Leukemia Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Comprehensive Detection of Chromosomal and Genomic Abnormalities via Next-Generation Sequencing-Based Genomic Proximity Mapping Improves Diagnostic Classification of Hematologic Neoplasms

Kyle W. Langford, Kikkeri N. Naresh, Stephen Eacker, Yajuan J. Liu et al.
Cancers
Acute Myeloid Leukemia Research
article

Comprehensive Detection of Chromosomal and Genomic Abnormalities via Next-Generation Sequencing-Based Genomic Proximity Mapping Improves Diagnostic Classification of Hematologic Neoplasms

Kyle W. Langford, Kikkeri N. Naresh, Stephen Eacker, Yajuan J. Liu, Soheil Meshinchi, He Fang, Yu Wu, Emily Reister, X. Chen
article en

Abstract

<b>Background/Objectives:</b> Accurate detection of all classes of genomic structural variants (SVs), including chromosomal rearrangements and copy number alterations (CNAs), is essential for the diagnosis and classification of hematologic neoplasms. Conventional cytogenetic methods currently serve as routine clinical tools for detecting SVs. However, each commonly used cytogenetic test has specific limitations, and sequential application of these different tests may delay timely diagnosis and treatment. <b>Methods</b>: In this study, we evaluated the feasibility and utility of genomic proximity mapping (GPM), a novel high-throughput chromosome conformation capture (Hi-C)-based next-generation sequencing (NGS) method, to identify chromosomal and genetic aberrations in hematologic neoplasms in the clinical setting. GPM was performed on 18 cases of hematologic neoplasms (fresh/frozen cells or formalin-fixed paraffin-embedded tissue), and concordance with other methodologies was assessed, including karyotyping, FISH, RT-PCR, chromosomal microarray analysis (CMA), and/or RNA sequencing. <b>Results:</b> GPM reliably detected balanced and unbalanced chromosomal rearrangements, including chimeric gene fusions and gene juxtapositions, with 95.2% concordance with previously applied methods in cases with >10% tumor burden. Additionally, GPM can detect CNAs and copy-neutral loss of heterozygosity (cnLOH) simultaneously in a single assay. Furthermore, detection of genomic rearrangements not identified by other methods improved the accuracy of disease classification. <b>Conclusions:</b> These findings demonstrate that GPM is a powerful method for identifying clinically actionable variants in hematologic neoplasms, overcoming some limitations of current cytogenetic technologies and improving the diagnostic accuracy and classification in challenging cases.

CancersVol. 17(23)
University of Washington (US), Fred Hutch Cancer Center (US), ID Genomics (United States) (US)
National Cancer Institute
Openalex Percentile: Top 52%
Acute Myeloid Leukemia Research
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