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This article has been corrected. Correction in: Oncotarget. 2019; 10:5493-5493.

NKp30 expression is a prognostic immune biomarker for stratification of patients with intermediate-risk acute myeloid leukemia

Anne-Sophie Chretien, Cyril Fauriat, Florence Orlanducci, Jerome Rey, Gaelle Bouvier Borg, Emmanuel Gautherot, Samuel Granjeaud, Clemence Demerle, Jean-François Hamel, Adelheid Cerwenka, Elke Pogge von Strandmann, Norbert Ifrah, Catherine Lacombe, Pascale Cornillet-Lefebvre, Jacques Delaunay, Antoine Toubert, Christine Arnoulet, Norbert Vey and Daniel Olive _

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Oncotarget. 2017; 8:49548-49563. https://doi.org/10.18632/oncotarget.17747

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Abstract

Anne-Sophie Chretien1,2, Cyril Fauriat1,2, Florence Orlanducci2, Jerome Rey3, Gaelle Bouvier Borg4, Emmanuel Gautherot4, Samuel Granjeaud5, Clemence Demerle1,2, Jean-François Hamel6, Adelheid Cerwenka7, Elke Pogge von Strandmann8,15, Norbert Ifrah9, Catherine Lacombe10, Pascale Cornillet-Lefebvre11, Jacques Delaunay12, Antoine Toubert13, Christine Arnoulet1,14, Norbert Vey1,3 and Daniel Olive1,2

1Team Immunity and Cancer, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM 105, Marseille, France

2Immunomonitoring Platform, Institut Paoli-Calmettes, Marseille, France

3Hematology Department, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM 105, Marseille, France

4Beckman Coulter Immunotech, Marseille, France

5Systems Biology Platform, Centre de Recherche en Cancérologie de Marseille (CRCM), Inserm, U1068, CNRS, UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, UM 105, Marseille, France

6Biostatistics and Methodology Department, CHU Angers, Angers, France

7Innate Immunity Group, German Cancer Research Center, Heidelberg, Germany

8Department I of Internal Medicine, University Hospital of Cologne, Cologne, Germany

9Hematology Department, CHU Angers, Angers, France

10GOELAMStheque, FILO French Innovative Leukemia Organization, Cochin Hospital, APHP, Paris, France

11Laboratoire d’Hématologie, Centre Hospitalier Universitaire de Reims, Reims, France

12Service d’Hématologie, Centre Catherine de Sienne, Nantes, France

13INSERM UMRS-1160, Univ Paris Diderot, Sorbonne Paris Cité, Institut Universitaire d’Hématologie, Immunology and Histocompatibility Department, Hôpital Saint-Louis, APHP, Paris, France

14Biopathology Department, Institut Paoli Calmettes, Marseille, France

15Clinic for Hematology, Oncology and Immunology, Experimental Tumor Research, Center for Tumor Biology and Immunology, Philipps University, Marburg, Germany

Correspondence to:

Daniel Olive, email: [email protected]

Keywords: AML, prognostic biomarkers, natural killer, NCR, NKp30

Received: January 30, 2017     Accepted: April 26, 2017     Published: May 10, 2017

ABSTRACT

Cytogenetics and European Leukemia Net (ELN) genetic classification predict patients at increased risk of relapse in acute myeloid leukemia (AML) except in the intermediate risk group for which further prognostic determinants are required. We have previously shown that Natural Killer (NK) cell defects in AML are predictors of poor overall survival (OS). This study aimins at validating NKp30, a receptor that mediates NK activation, as a prognostic biomarker for AML patients with intermediate prognosis.

NKp30 expression was prospectively assessed at diagnosis on NK cells from peripheral blood by flow cytometry (N = 201 patients). Clinical outcome was evaluated with regard to NKp30 status.

In patients with intermediate cytogenetic (N = 162), NKp30high phenotype at diagnosis was predictive of better OS (HR = 0.26; 95%CI = [0.14-0.50]; P < 0.0001) and relapse-free survival (RFS) (HR = 0.21; 95%CI = [0.08-0.52]; P = 0.0007). In patients with intermediate ELN (N = 116), NKp30high phenotype at diagnosis was predictive of better OS (HR = 0.33; 95%CI = [0.16–0.67]; P = 0.0019) and RFS (HR = 0.24; 95%CI = [0.08-0.67]; P = 0.0058). In multivariate analysis, high NKp30 expression independently predicted improved OS (HR = 0.56, P = 0.046) and RFS (HR = 0.37, P = 0.048). Consistently, cumulative incidence of relapse (CIR) was lower in patients with high NKp30 expression (HR = 0.37, P = 0.026).

In conclusion, we propose NKp30 status as a simple and early prognostic biomarker that identifies intermediate-risk patients with poor prognosis who otherwise may not be identified with existing risk stratification systems.


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