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. 2023 Nov 22;5(1):93-104.
doi: 10.1002/jha2.827. eCollection 2024 Feb.

Prevalence and clinical impact of CD56 and T-cell marker expression in acute myeloid leukaemia: A single-centre retrospective analysis

Inna Shaforostova  1 , Simon Call  1 , Georg Evers  1 , Christian Reicherts  1 , Linus Angenendt  1   2 , Matthias Stelljes  1 , Wolfgang E Berdel  1 , Alexander Pohlmann  1 , Jan-Henrik Mikesch  1 , Frank Rosenbauer  3 , Georg Lenz  1 , Christoph Schliemann  1 , Klaus Wethmar  1
Affiliations

Prevalence and clinical impact of CD56 and T-cell marker expression in acute myeloid leukaemia: A single-centre retrospective analysis

Inna Shaforostova et al. EJHaem. .

Abstract

Flow cytometry-based immunophenotyping is a mainstay of diagnostics in acute myeloid leukaemia (AML). Aberrant CD56 and T-cell antigen expression is observed in a fraction subset of AML cases, but the clinical relevance remains incompletely understood. Here, we retrospectively investigated the association of CD56 and T-cell marker expression with disease-specific characteristics and outcome of 324 AML patients who received intensive induction therapy at our centre between 2011 and 2019. We found that CD2 expression was associated with abnormal non-complex karyotype, NPM1 wild-type status and TP53 mutation. CD2 also correlated with a lower complete remission (CR) rate (47.8% vs. 71.6%, p = 0.03). CyTdT and CD2 were associated with inferior 3-year event-free-survival (EFS) (5.3% vs. 33.5%, p = 0.003 and 17.4% vs. 33.1%, p = 0.02, respectively). CyTdT expression was also correlated with inferior relapse-free survival (27.3% vs. 48.8%, p = 0.04). In multivariable analyses CD2 positivity was an independent adverse factor for EFS (HR 1.72, p = 0.03). These results indicate a biological relevance of aberrant T-cell marker expression in AML and provide a rationale to further characterise the molecular origin in T-lineage-associated AML.

Keywords: CD56; T‐cell marker; acute myeloid leukaemia; clinical impact; flow cytometry.

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Conflict of interest statement

The authors declare no competing interests.

Figures

FIGURE 1
FIGURE 1
Gating strategy of the flow cytometric analysis of CD56 and T‐cell marker expression on AML blasts. Dot‐plots of exemplary flow cytometric data showing (A) separation of bone marrow cells by FSC‐A versus SSC‐A, (B) gating of blast (red) and lymphocyte populations (blue) according to SSC‐A and CD45 expression, (C) how the ‘negative’ lymphocytic internal control population was defined for CD2, (D) CD‐positive (CD2) blast population as defined by the non‐negative lymphocyte gate established in (C).
FIGURE 2
FIGURE 2
T‐cell and CD56 marker positivity of blast populations. Violin plots displaying the proportion of positive blasts for indicated markers in percent (%) for individual patients (dots). The distributions of CD3 and CD8 markers are not shown due to the small number or absence of positive cases, respectively.
FIGURE 3
FIGURE 3
T‐cell and CD56 marker positivity and outcome. Kaplan–Meier curves showing (A) overall survival, (B) relapse‐free survival and (C) event‐free survival according to cyTDT and CD2 expression. Survival curves for CD3, CD4, CD7 and CD56 are shown in supplementary Figure 1.
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