4.7 Article

Characterization of Immune Dysfunction and Identification of Prognostic Immune-Related Risk Factors in Acute Myeloid Leukemia

Journal

CLINICAL CANCER RESEARCH
Volume 26, Issue 7, Pages 1763-1772

Publisher

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/1078-0432.CCR-19-3003

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Funding

  1. National Natural Science Foundation of China [81770132, 81873434]
  2. Major Technological Innovation Special Project of Hubei Province of China [2018ACA141]

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Purpose: This study aims to provide comprehensive insights into longitudinal immune landscape in acute myeloid leukemia (AML) development and treatment, which may contribute to predict prognosis and guide clinical decisions. Experimental Design: Periphery blood samples from 79 patients with AML (at diagnosis or/and after chemotherapy or at relapse) and 24 healthy controls were prospectively collected. We performed phenotypic and functional analysis of various lymphocytes through multiparametric flow cytometry and investigated prognostic immune-related risk factors. Results: Immune defects in AML were reflected in T and natural killer (NK) cells, whereas B-cell function remained unaffected. Both CD8(+) T and CD4(+) T cells exhibited features of senescence and exhaustion at diagnosis. NK dysfunction was supported by excessive maturation and downregulation of NKG2D and NKP30. Diseased gamma delta T cells demonstrated a highly activated or even exhausted state through PD-1 upregulation and NKG2D downregulation. Effective therapeutic response following chemotherapy correlated with T and NK function restoration. Refractory and relapsed patients demonstrated even worse immune impairments, and selective immune signatures apparently correlated clinical outcomes and survival. PD-1 expression in CD8(+) T cells was independently predictive of poor overall survival and event-free survival. Conclusions: T-cell senescence and exhaustion, together with impaired NK and gamma delta T-cell function, are dominant aspects involved in immune dysfunction in AML. Noninvasive immune testing of blood samples could be applied to predict therapeutic reactivity, high risk for relapse, and unfavorable prognosis.

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