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Signatures of CD8+ T cell dysfunction in AML patients and their reversibility with response to chemotherapy
Hanna A. Knaus, Sofia Berglund, Hubert Hackl, Amanda L. Blackford, Joshua F. Zeidner, Raúl Montiel-Esparza, Rupkatha Mukhopadhyay, Katrina Vanura, Bruce R. Blazar, Judith E. Karp, Leo Luznik, Ivana Gojo
Hanna A. Knaus, Sofia Berglund, Hubert Hackl, Amanda L. Blackford, Joshua F. Zeidner, Raúl Montiel-Esparza, Rupkatha Mukhopadhyay, Katrina Vanura, Bruce R. Blazar, Judith E. Karp, Leo Luznik, Ivana Gojo
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Clinical Research and Public Health Hematology Immunology

Signatures of CD8+ T cell dysfunction in AML patients and their reversibility with response to chemotherapy

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Abstract

BACKGROUND. Our understanding of phenotypic and functional signatures of CD8+ T cell dysfunction in acute myeloid leukemia (AML) is limited. Deciphering these deranged T cell functional states and how they are impacted by induction chemotherapy is essential for incorporation of novel immune-based strategies to restore and maintain antileukemia immunity. METHODS. We utilized high-dimensional immunophenotyping, gene expression, and functional studies to characterize peripheral blood and bone marrow CD8+ T cells in 72 AML patients at diagnosis and after induction chemotherapy. RESULTS. Our data suggest that multiple aspects of deranged T cell function are operative in AML at diagnosis, with exhaustion and senescence being the dominant processes. Following treatment, the phenotypic and transcriptional profile of CD8+ T cells diverged between responders and nonresponders. Response to therapy correlated with upregulation of costimulatory, and downregulation of apoptotic and inhibitory, T cell signaling pathways, indicative of restoration of T cell function. In functional studies, AML blasts directly altered CD8+ T cell viability, expansion, co-signaling and senescence marker expression. This CD8+ T cell dysfunction was in part reversible upon PD-1 blockade or OX40 costimulation in vitro. CONCLUSION. Our findings highlight the uniqueness of AML in sculpting CD8+ T cell responses and the plasticity of their signatures upon chemotherapy response, providing a compelling rationale for integration of novel immunotherapies to augment antileukemia immunity. FUNDING. This work was supported by the Leukemia & Lymphoma Society grant no. 6449-13; NIH grants UM1-CA186691 and R01-HL110907-01; the American Society for Blood and Marrow Transplantation New Investigator Award/Gabrielle’s Angel Foundation; the Vienna Fund for Innovative Cancer Research; and by fellowships from the Wenner-Gren Foundation and the Swedish Society for Medical Research.

Authors

Hanna A. Knaus, Sofia Berglund, Hubert Hackl, Amanda L. Blackford, Joshua F. Zeidner, Raúl Montiel-Esparza, Rupkatha Mukhopadhyay, Katrina Vanura, Bruce R. Blazar, Judith E. Karp, Leo Luznik, Ivana Gojo

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Figure 4

Differential gene expression underscoring CD8+ T cell dysfunction in AML at diagnosis and in nonresponders following induction chemotherapy.

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Differential gene expression underscoring CD8+ T cell dysfunction in AML...
(A–C) Gene expression analysis of PB CD8+ T cells from AML patients at diagnosis (n = 9) and age-matched HCs (n = 4). (A) Hierarchical clustering of 453 DEGs between patients and HC (log2FC > 1 and < –1, and P < 0.01). Log2 intensities are gene-wise Z transformed across all samples and visualized as heatmap. Every row represents a gene, and every column a patient sample. Red indicates an increase over the mean (Z > 0) and blue a decrease (Z < 0). (B) Heatmap of select DEGs grouped into key biological categories (log2FC > 1 and < –1; P < 0.01; *P < 0.05). (C) GO terms and KEGG/BioCarta pathways (P < 0.01) were functionally grouped into networks and interconnected based on the number of shared genes (κ score > 0.4) using ClueGO. The size of the nodes correlates with the number of mapped genes per term and color correlates with P values. (D and E) Gene expression analysis of PB CD8+ T cells from AML patients after induction chemotherapy (n = 6), 3 with complete remission (CR) and 3 nonresponders (NRs), and age-matched HCs (n = 4). (D) Hierarchical clustering of 351 DEGs from CR versus NR patients after treatment (log2FC > 1 or < –1; and P < 0.01). Expression levels for the 351 genes were queried from 4 HCs and included into the hierarchical clustering of the heatmap. Log2 intensities are gene-wise Z transformed across all samples. Every row represents a gene, and every column a patient sample. Red indicates an increase over the mean (Z > 0) and blue a decrease (Z < 0). (E) Heatmap of representative DEGs (CR versus NR) grouped into key biological categories (log2FC > 1 or < –1; P < 0.01; *P < 0.05).

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