Literature DB >> 28625325

Importance of CD117 in the Assignation of a Myeloid Lineage in Acute Leukemias.

Alan Pomerantz1, Sergio Rodríguez-Rodríguez1, Roberta Demichelis-Gómez2, Georgina Barrera-Lumbreras2, Olga V Barrales-Benítez2, María José Díaz-Huízar3, Monica Goldberg-Murow3, Xavier López-Karpovitch4, Álvaro Aguayo2.   

Abstract

The correct classification of acute leukemias (AL) is an essential part in the evaluation of any patient with this disease. Historically, CD117 has been an important asset in the diagnosis of patients with mixed-phenotype acute leukemia (MPAL). In an attempt to simplify the diagnosis of MPAL with fewer and more lineage specific markers, the World Health Organization (WHO) proposed in 2008 a new criteria for the diagnosis of this type of AL, which excluded CD117 from the myeloid markers that are utilized to diagnose MPAL. In order to assess whether CD117 is necessary in the diagnosis of MPAL, we evaluated the sensitivity and specificity of CD117 for acute myeloid leukemia (AML) in 331 patients with AL. The calculated sensitivity of CD117 for AML was 85.88% (103/120), while the specificity was 83.9% (177/211). Besides myeloperoxidase (MPO), which was used as the gold standard in differentiating AML from other type of ALs, the most specific markers for AML in our study were CD14 and CD64 (99.5 and 95.6%). Although the specificity of CD117 in this study is not as high as CD14 and CD64, markers concomitantly used in this this study and in the WHO classification, based on the results of other researches (i.e. the specificity of CD117 for AML was 100% in one study) and due to the fact that its specificity for AML in this study is relatively high, we recommend the use CD117 in assigning a myeloid lineage in MPAL.
Copyright © 2017 IMSS. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  2008 WHO classification; Acute myeloid leukemia; CD117; EGIL; Mixed-phenotype acute leukemia

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Year:  2017        PMID: 28625325     DOI: 10.1016/j.arcmed.2017.03.009

Source DB:  PubMed          Journal:  Arch Med Res        ISSN: 0188-4409            Impact factor:   2.235


  1 in total

1.  Automated identification of maximal differential cell populations in flow cytometry data.

Authors:  Alice Yue; Cedric Chauve; Maxwell W Libbrecht; Ryan R Brinkman
Journal:  Cytometry A       Date:  2021-10-22       Impact factor: 4.714

  1 in total

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