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Updated: Mar 1, 2026

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
NKp30 expression is a prognostic immune biomarker for stratification of patients with intermediate-risk acute myeloid
Anne-Sophie Chretien1,2, Cyril Fauriat1,2, Florence Orlanducci2
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.
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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