4.3 Article

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

期刊

ONCOTARGET
卷 8, 期 30, 页码 49548-49563

出版社

IMPACT JOURNALS LLC
DOI: 10.18632/oncotarget.17747

关键词

AML; prognostic biomarkers; natural Killer; NCR; NKp30

资金

  1. INCa
  2. SIRIC Marseille [INCa-DGOS-INSERM 6038]
  3. Canceropole PACA [K_CyTOF 2014, AML_CyTOF 2016]
  4. GS IBiSA
  5. Agence Nationale de la Recherche (PHENOMIN project)

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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), NKp30(high) 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), NKp30(high) 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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