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Immune dysfunction signatures predict outcomes and define checkpoint blockade–unresponsive microenvironments in acute myeloid leukemia
Sergio Rutella, … , Ivana Gojo, Leo Luznik
Sergio Rutella, … , Ivana Gojo, Leo Luznik
Published September 13, 2022
Citation Information: J Clin Invest. 2022;132(21):e159579. https://doi.org/10.1172/JCI159579.
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Clinical Research and Public Health Hematology Article has an altmetric score of 1169

Immune dysfunction signatures predict outcomes and define checkpoint blockade–unresponsive microenvironments in acute myeloid leukemia

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Abstract

Background Immune exhaustion and senescence are dominant dysfunctional states of effector T cells and major hurdles for the success of cancer immunotherapy. In the current study, we characterized how acute myeloid leukemia (AML) promotes the generation of senescent-like CD8+ T cells and whether they have prognostic relevance.METHODS We analyzed NanoString, bulk RNA-Seq and single-cell RNA-Seq data from independent clinical cohorts comprising 1,896 patients treated with chemotherapy and/or immune checkpoint blockade (ICB).Results We show that senescent-like bone marrow CD8+ T cells were impaired in killing autologous AML blasts and that their proportion negatively correlated with overall survival (OS). We defined what we believe to be new immune effector dysfunction (IED) signatures using 2 gene expression profiling platforms and reported that IED scores correlated with adverse-risk molecular lesions, stemness, and poor outcomes; these scores were a more powerful predictor of OS than 2017-ELN risk or leukemia stem cell (LSC17) scores. IED expression signatures also identified an ICB-unresponsive tumor microenvironment and predicted significantly shorter OS.Conclusion The IED scores provided improved AML-risk stratification and could facilitate the delivery of personalized immunotherapies to patients who are most likely to benefit.TRIAL REGISTRATION ClinicalTrials.gov; NCT02845297.FUNDING John and Lucille van Geest Foundation, Nottingham Trent University’s Health & Wellbeing Strategic Research Theme, NIH/NCI P01CA225618, Genentech-imCORE ML40354, Qatar National Research Fund (NPRP8-2297-3-494).

Authors

Sergio Rutella, Jayakumar Vadakekolathu, Francesco Mazziotta, Stephen Reeder, Tung-On Yau, Rupkatha Mukhopadhyay, Benjamin Dickins, Heidi Altmann, Michael Kramer, Hanna A. Knaus, Bruce R. Blazar, Vedran Radojcic, Joshua F. Zeidner, Andrea Arruda, Bofei Wang, Hussein A. Abbas, Mark D. Minden, Sarah K. Tasian, Martin Bornhäuser, Ivana Gojo, Leo Luznik

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Figure 9

Immune effector dysfunction scores predict response to AZA+Pembro in clinical trial NCT02845297.

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Immune effector dysfunction scores predict response to AZA+Pembro in cli...
(A) Differentially expressed genes (DEGs) at baseline associated with complete response (CResp) to AZA+Pembro (n = 33 patients). The heatmap annotation track shows the prognostic index (PI20) group and response status (complete remission [CR] and nonresponder [NR]) after 2 cycles of azacitidine and pembrolizumab. Complete response was defined as CR, CR with partial hematologic recovery (CRh), CR with incomplete hematologic recovery (CRi), or morphological leukemia-free state (MLFS) at the end of cycle 2. Patients with partial response (PR; >50% decrease in bone marrow blasts from baseline to 5%–25% at the end of cycle 1) were categorized as NRs. C, cluster. (B) Area under the receiver operating characteristic (AUROC) curve measuring the predictive ability of IED68 genes for response to AZA+Pembro. CI, confidence interval. (C) Kaplan-Meier estimate of overall survival (OS) in patients with above-median and below-median PI20. Survival curves were compared using the Gehan-Breslow-Wilcoxon’s test, a generalization of the Wilcoxon’s rank-sum test that attributes more weight to deaths at early time points. HR, hazard ratio. (D) Kaplan-Meier estimate of OS in patients with above-median and below-median IFN scores, which were computed as previously published (2). Survival curves were compared using the Gehan-Breslow-Wilcoxon’s test. (E) Volcano plot showing DEGs between baseline and end-of-cycle 2 (EO2) bone marrow samples. The top 20 DEGs are named. (F) The overlap between DEGs post-reatment versus baseline in the chemotherapy (CT; SAL and JHU2) and AZA+Pembro patient series is shown as a Venn diagram. Nonredundant, enriched gene ontologies in DEGs between the CT and AZA+Pembro cohorts were visualized as a network diagram (cnetplot) with color nodes using the cnetplot function of the GOSemSim package in R (67).

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ISSN: 0021-9738 (print), 1558-8238 (online)

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