Evidence map›Paper›PMID 38433573›Full record

ArticleAnnals of laboratory medicine2024

Comparison of Optical Genome Mapping With Conventional Diagnostic Methods for Structural Variant Detection in Hematologic Malignancies.

Yeeun Shim, Yu-Kyung Koo, Saeam Shin, Seung-Tae Lee, Kyung-A Lee, Jong Rak Choi

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Article in Annals of laboratory medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

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0cells of the map it votes in
9citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yeeun ShimBrain Korea 21 PLUS Project for Medical Science, Yonsei University, Seoul, Korea.ORCID https://orcid.org/0000-0001-7131-3619
Yu-Kyung KooDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-4390-7679
Saeam ShinDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-1501-3923
Seung-Tae LeeDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0003-1047-1415
Kyung-A LeeDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0001-5320-6705
Jong Rak ChoiDepartment of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Korea.ORCID https://orcid.org/0000-0002-0608-2989

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Structural variants (SVs) are currently analyzed using a combination of conventional methods; however, this approach has limitations. Optical genome mapping (OGM), an emerging technology for detecting SVs using a single-molecule strategy, has the potential to replace conventional methods. We compared OGM with conventional diagnostic methods for detecting SVs in various hematologic malignancies. Methods: Residual bone marrow aspirates from 27 patients with hematologic malignancies in whom SVs were observed using conventional methods (chromosomal banding analysis, FISH, an RNA fusion panel, and reverse transcription PCR) were analyzed using OGM. The concordance between the OGM and conventional method results was evaluated. Results: OGM showed concordance in 63% (17/27) and partial concordance in 37% (10/27) of samples. OGM detected 76% (52/68) of the total SVs correctly (concordance rate for each type of SVs: aneuploidies, 83% [15/18]; balanced translocation, 80% [12/15] unbalanced translocation, 54% [7/13] deletions, 81% [13/16]; duplications, 100% [2/2] inversion 100% [1/1]; insertion, 100% [1/1]; marker chromosome, 0% [0/1]; isochromosome, 100% [1/1]). Sixteen discordant results were attributed to the involvement of centromeric/telomeric regions, detection sensitivity, and a low mapping rate and coverage. OGM identified additional SVs, including submicroscopic SVs and novel fusions, in five cases. Conclusions: OGM shows a high level of concordance with conventional diagnostic methods for the detection of SVs and can identify novel variants, suggesting its potential utility in enabling more comprehensive SV analysis in routine diagnostics of hematologic malignancies, although further studies and improvements are required.

Indexed as

Genome, HumanGenomic Structural VariationChromosome InversionChromosome MappingHumansTranslocation, GeneticCopy number variationsGene fusionHematologic neoplasmsOptical genome mappingStructural variations

Identifiers

PMID38433573
PMCPMC10961627

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.