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Ultra-Sensitive CSF3R Deep Sequencing in Patients With Severe Congenital Neutropenia.

Authors :
Klimiankou M
Uenalan M
Kandabarau S
Nustede R
Steiert I
Mellor-Heineke S
Zeidler C
Skokowa J
Welte K
Source :
Frontiers in immunology [Front Immunol] 2019 Feb 28; Vol. 10, pp. 116. Date of Electronic Publication: 2019 Feb 28 (Print Publication: 2019).
Publication Year :
2019

Abstract

High frequency of acquired CSF3R (colony stimulating factor 3 receptor, granulocyte) mutations has been described in patients with severe congenital neutropenia (CN) at pre-leukemia stage and overt acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS). Here, we report the establishment of an ultra-sensitive deep sequencing of a CSF3R segment encoding the intracellular "critical region" of the G-CSFR known to be mutated in CN-MDS/AML patients. Using this method, we achieved a mutant allele frequency (MAF) detection rate of 0.01%. We detected CSF3R mutations in CN patients with different genetic backgrounds, but not in patients with other types of bone marrow failure syndromes chronically treated with G-CSF (e.g., Shwachman-Diamond Syndrome). Comparison of CSF3R deep sequencing results of DNA and cDNA from the bone marrow and peripheral blood cells revealed the highest sensitivity of cDNA from the peripheral blood polymorphonuclear neutrophils. This approach enables the identification of low-frequency CSF3R mutant clones, increases sensitivity, and earlier detection of CSF3R mutations acquired during the course of leukemogenic evolution of pre-leukemia HSCs of CN patients. We suggest application of sequencing of the entire CSF3R gene at diagnosis to identify patients with inherited lost-of-function CSF3R mutations and annual ultra-deep sequencing of the critical region of CSF3R to monitor acquisition of CSF3R mutations.

Details

Language :
English
ISSN :
1664-3224
Volume :
10
Database :
MEDLINE
Journal :
Frontiers in immunology
Publication Type :
Academic Journal
Accession number :
30891028
Full Text :
https://doi.org/10.3389/fimmu.2019.00116