Development and analytical validation of a next-generation sequencing based microsatellite instability (MSI) assay.

MSI NGS microsatellite instability next-generation sequencing

Journal

Oncotarget
ISSN: 1949-2553
Titre abrégé: Oncotarget
Pays: United States
ID NLM: 101532965

Informations de publication

Date de publication:
27 Aug 2019
Historique:
received: 10 06 2019
accepted: 29 07 2019
entrez: 10 9 2019
pubmed: 10 9 2019
medline: 10 9 2019
Statut: epublish

Résumé

We have developed and analytically validated a next-generation sequencing (NGS) assay to classify microsatellite instability (MSI) in formalin-fixed paraffin-embedded (FFPE) tumor specimens. The assay relies on DNA-seq evaluation of insertion/deletion (indel) variability at 29 highly informative genomic loci to estimate MSI status without the requirement for matched-normal tissue. The assay has a clinically relevant five-day turnaround time and can be conducted on as little as 20 ng genomic DNA with a batch size of up to forty samples in a single run. The MSI detection method was developed on a training set ( This assay provides clinicians with robust and reproducible NGS-based MSI testing without the need of matched normal tissue to inform clinical decision making for patients with solid tumors.

Sections du résumé

BACKGROUND BACKGROUND
We have developed and analytically validated a next-generation sequencing (NGS) assay to classify microsatellite instability (MSI) in formalin-fixed paraffin-embedded (FFPE) tumor specimens.
METHODOLOGY METHODS
The assay relies on DNA-seq evaluation of insertion/deletion (indel) variability at 29 highly informative genomic loci to estimate MSI status without the requirement for matched-normal tissue. The assay has a clinically relevant five-day turnaround time and can be conducted on as little as 20 ng genomic DNA with a batch size of up to forty samples in a single run.
RESULTS RESULTS
The MSI detection method was developed on a training set (
SIGNIFICANCE CONCLUSIONS
This assay provides clinicians with robust and reproducible NGS-based MSI testing without the need of matched normal tissue to inform clinical decision making for patients with solid tumors.

Identifiants

pubmed: 31497248
doi: 10.18632/oncotarget.27142
pii: 27142
pmc: PMC6718258
doi:

Types de publication

Journal Article

Langues

eng

Pagination

5181-5193

Subventions

Organisme : NCI NIH HHS
ID : P30 CA016056
Pays : United States

Déclaration de conflit d'intérêts

CONFLICTS OF INTEREST SP, JA, FLL, BB, JH, VG, MKN, YW, MG, JMC, APS, CM, and STG are employees of OmniSeq, Inc. (Buffalo, NY, USA) and hold restricted stock in OmniSeq, Inc. JMC, CM, and STG are employees of Roswell Park Comprehensive Cancer Center (Buffalo, NY, USA), which is the majority shareholder of OmniSeq, Inc.

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Auteurs

Sarabjot Pabla (S)

OmniSeq Inc., Buffalo, NY 14203, USA.
These authors contributed equally to this work.

Jonathan Andreas (J)

OmniSeq Inc., Buffalo, NY 14203, USA.
These authors contributed equally to this work.

Felicia L Lenzo (FL)

OmniSeq Inc., Buffalo, NY 14203, USA.

Blake Burgher (B)

OmniSeq Inc., Buffalo, NY 14203, USA.

Jacob Hagen (J)

OmniSeq Inc., Buffalo, NY 14203, USA.

Vincent Giamo (V)

OmniSeq Inc., Buffalo, NY 14203, USA.

Mary K Nesline (MK)

OmniSeq Inc., Buffalo, NY 14203, USA.

Yirong Wang (Y)

OmniSeq Inc., Buffalo, NY 14203, USA.

Mark Gardner (M)

OmniSeq Inc., Buffalo, NY 14203, USA.

Jeffrey M Conroy (JM)

OmniSeq Inc., Buffalo, NY 14203, USA.
Center for Personalized Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA.

Antonios Papanicolau-Sengos (A)

OmniSeq Inc., Buffalo, NY 14203, USA.

Carl Morrison (C)

OmniSeq Inc., Buffalo, NY 14203, USA.
Center for Personalized Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA.

Sean T Glenn (ST)

OmniSeq Inc., Buffalo, NY 14203, USA.
Center for Personalized Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA.
Department of Molecular and Cellular Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14263, USA.

Classifications MeSH