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      Prognostic Significance of CD56 Antigen Expression in Patients with De Novo Non-M3 Acute Myeloid Leukemia

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          Abstract

          Acute myeloid leukemia (AML) is a heterogeneous group of disorders with distinct characteristics and prognoses. Although cytogenetic changes and gene mutations are associated with AML prognosis, there is a need to identify further factors. CD56 is considered a prognostic factor for AML, which is abnormally expressed in leukemia cells. However, a clear consensus for this surface molecule is lacking, which has prompted us to investigate its prognostic significance. Bone marrow samples of de novo non-M3 AML were collected to detect CD56 expression using multiparameter flow cytometry (FCM). As a result, the CD56 expression in de novo non-M3 AML was found to be significantly higher than that in acute lymphoma leukemia (ALL, P = 0.017) and healthy controls ( P = 0.02). The X-Tile program produced a CD56 cutoff point at a relative expression level of 24.62%. Based on this cutoff point, high CD56 expression was observed in 29.21% of de novo non-M3 AML patients. CD56 -high patients had a poor overall survival (OS, P = 0.015) compared to CD56 -low patients. Bone marrow transplantation (BMT) improved OS ( P = 0.004), but a poor genetic risk was associated with an inferior OS ( P = 0.002). Compared with CD56 -low patients, CD56 -high patients had lower peripheral blood platelet (PLT) counts ( P = 0.010). Our research confirmed that high CD56 expression is associated with adverse clinical outcomes in de novo non-M3 AML patients, indicating that CD56 could be used as a prognostic marker for a more precise stratification of de novo non-M3 AML patients.

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          Most cited references41

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          The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia.

          The World Health Organization (WHO) classification of tumors of the hematopoietic and lymphoid tissues was last updated in 2008. Since then, there have been numerous advances in the identification of unique biomarkers associated with some myeloid neoplasms and acute leukemias, largely derived from gene expression analysis and next-generation sequencing that can significantly improve the diagnostic criteria as well as the prognostic relevance of entities currently included in the WHO classification and that also suggest new entities that should be added. Therefore, there is a clear need for a revision to the current classification. The revisions to the categories of myeloid neoplasms and acute leukemia will be published in a monograph in 2016 and reflect a consensus of opinion of hematopathologists, hematologists, oncologists, and geneticists. The 2016 edition represents a revision of the prior classification rather than an entirely new classification and attempts to incorporate new clinical, prognostic, morphologic, immunophenotypic, and genetic data that have emerged since the last edition. The major changes in the classification and their rationale are presented here.
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            Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel.

            The first edition of the European LeukemiaNet (ELN) recommendations for diagnosis and management of acute myeloid leukemia (AML) in adults, published in 2010, has found broad acceptance by physicians and investigators caring for patients with AML. Recent advances, for example, in the discovery of the genomic landscape of the disease, in the development of assays for genetic testing and for detecting minimal residual disease (MRD), as well as in the development of novel antileukemic agents, prompted an international panel to provide updated evidence- and expert opinion-based recommendations. The recommendations include a revised version of the ELN genetic categories, a proposal for a response category based on MRD status, and criteria for progressive disease.
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              X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization.

              The ability to parse tumors into subsets based on biomarker expression has many clinical applications; however, there is no global way to visualize the best cut-points for creating such divisions. We have developed a graphical method, the X-tile plot that illustrates the presence of substantial tumor subpopulations and shows the robustness of the relationship between a biomarker and outcome by construction of a two dimensional projection of every possible subpopulation. We validate X-tile plots by examining the expression of several established prognostic markers (human epidermal growth factor receptor-2, estrogen receptor, p53 expression, patient age, tumor size, and node number) in cohorts of breast cancer patients and show how X-tile plots of each marker predict population subsets rooted in the known biology of their expression.
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                Author and article information

                Contributors
                Journal
                Biomed Res Int
                Biomed Res Int
                BMRI
                BioMed Research International
                Hindawi
                2314-6133
                2314-6141
                2021
                8 April 2021
                : 2021
                : 1929357
                Affiliations
                1Center for Hematology, Southwest Hospital, Army Medical University, 400038, China
                2College of Military Preventive Medicine, Army Medical University, Chongqing 400038, China
                Author notes

                Academic Editor: Maciej Gagat

                Author information
                https://orcid.org/0000-0002-4041-9039
                https://orcid.org/0000-0001-9666-2911
                Article
                10.1155/2021/1929357
                8049794
                33928145
                5f8acc2f-8bd5-4836-a6d2-499c5c7e76be
                Copyright © 2021 Yanni Sun et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 May 2020
                : 2 February 2021
                : 20 March 2021
                Funding
                Funded by: Chongqing Science and Technology Commission and Health Commission
                Award ID: 2018QNXM045
                Funded by: Southwest Hospital
                Funded by: National Natural Science Foundation of China
                Award ID: SWH2016YSCXZD-09
                Award ID: 81470324
                Award ID: 81800172
                Categories
                Research Article

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