Automated Detection of Arm-Level Alterations for Individual Cancer Patients in the Clinical Setting.


Journal

The Journal of molecular diagnostics : JMD
ISSN: 1943-7811
Titre abrégé: J Mol Diagn
Pays: United States
ID NLM: 100893612

Informations de publication

Date de publication:
12 2021
Historique:
received: 03 02 2021
revised: 29 07 2021
accepted: 18 08 2021
pubmed: 29 8 2021
medline: 8 3 2022
entrez: 28 8 2021
Statut: ppublish

Résumé

Copy number alterations are genetic events that promote tumor initiation and progression and are used in clinical care as diagnostic, prognostic, and predictive biomarkers. Based on the length of the alteration, they are roughly classified as focal and arm-level alterations. Although genome-wide techniques to detect arm-level alterations are gaining momentum in hospital laboratories, the high precision and novelty of these techniques pose new challenges: there is no consensus on the definition of an arm-level alteration and there is a lack of tools to compute them for individual patients. Based on 376 clinical samples analyzed with the OncoScan formalin-fixed, paraffin-embedded assay, a bimodal distribution of the percentage of bases with copy number alterations within a chromosomal arm was observed, with the second peak starting at 90% of arm length. Two approaches were tested for the definition of arm-level alterations: sum of altered segments (SoS) >90%, or the longest segment (LS) >90%. These approaches were validated against expert annotation of 25 clinical cases. The SoS method outperformed the LS method as indicated by a higher concordance (SoS, 95.2%; LS, 79.9%). Some of the discordances ultimately were attributed to human error, highlighting the advantages of automation. The increase in reliability led to the development of publicly available software and its inclusion into routine clinical practice at Geneva University Hospitals.

Identifiants

pubmed: 34454110
pii: S1525-1578(21)00255-5
doi: 10.1016/j.jmoldx.2021.08.003
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1722-1731

Informations de copyright

Copyright © 2021 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Auteurs

Yann Christinat (Y)

Division of Pathology, Department of Diagnosis, University of Geneva, Geneva, Switzerland. Electronic address: yann.christinat@hcuge.ch.

Prasad Chaskar (P)

Faculty of Medicine, Department of Medicine, University of Geneva, Geneva, Switzerland; Department of Oncology, Geneva University Hospitals, University of Geneva, Geneva, Switzerland.

Sophie Clément (S)

Division of Pathology, Department of Diagnosis, University of Geneva, Geneva, Switzerland.

Liza Ho (L)

Division of Pathology, Department of Diagnosis, University of Geneva, Geneva, Switzerland.

Mélinda Charrier (M)

Department of Oncology, Geneva University Hospitals, University of Geneva, Geneva, Switzerland.

Thomas McKee (T)

Division of Pathology, Department of Diagnosis, University of Geneva, Geneva, Switzerland.

Petros Tsantoulis (P)

Faculty of Medicine, Department of Medicine, University of Geneva, Geneva, Switzerland; Department of Oncology, Geneva University Hospitals, University of Geneva, Geneva, Switzerland. Electronic address: petros.tsantoulis@hcuge.ch.

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Classifications MeSH