Article Text

Download PDFPDF

507 High dimensional flow cytometry analysis in newly diagnosed acute myeloid leukemia predicts patients outcomes
  1. Francesco Mazziotta1,
  2. Rupkatha Mukhopadhyay1,
  3. Hanna A Knaus2,
  4. Anish Chowdhury1,
  5. Amanda Blackford1,
  6. Ivana Gojo1 and
  7. Leo Luznik1
  1. 1Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD, USA
  2. 2Medical University of Vienna, Vienna, Austria


Background We have previously characterized phenotypic and transcriptional profile of CD8+ T cells in acute myeloid leukemia (AML) and their differences between responders vs. nonresponders to chemotherapy.1 Goal of ongoing work was to further probe uniqueness of AML in sculpting CD8+ T cell responses and the plasticity of their signatures upon chemotherapy response.

Methods We first examined the cumulative expression of multiple inhibitory receptors (IRs) (detected by 2 different panels) on CD8+ T cells and created an IR-score which summarizes the relative amount of PD-1, Tim3, KLRG1, 2B4, CD160, CD57, and BTLA-positive CD8+ T-cells in relation to the well-characterized maturation states of CD8+ T cells. Serial bone marrow samples from 33 newly diagnosed AML patients with well-annotated clinical data (21 complete responders (CR) and 12 nonresponders (NR) to chemotherapy) and 11 healthy controls (HC) were analyzed. FInally, using custom made R code, we performed dimensionality reduction, clustering, and pseudotime analysis.

Results The IR-score discriminated NR and CR (p = 3e-02, AUC 0.84) after treatment with CD57 and KLRG1 accounting for most of this difference (p = 2e-02, AUC = 0.79). Next we investigated CD8+ T cell populations that best correlated with response to chemotherapy. FlowSOM revealed seven major clusters: naive and naive-like, CD28+KLRG1+ activated-effector, CD28+KLRG1+PD1+ dysfunctional, PD1+CD57+ senescent effector-memory and two clusters of terminally differentiated CD45RA+KLRG1+ cells. Since the activation and differentiation states accounted for most of the subpopulation variability, we grouped the clusters into resting (naive, naive-like), activated (activated-effector, dysfunctional), and terminally differentiated cells (senescent effector-memory, terminally differentiated). UMAP, developmental trajectories and differential abundance testing showed increased frequency of activated cells at diagnosis (p-adj = 2.9e-05) and of resting cells after treatment (p-adj = 1.3e-02) in CR, while terminally differentiated T cells prevailed in NR (p-adj = 5.3e-08) after treatment (figures 1 and 2).

Abstract 507 Figure 1

UMAP embedding of T cells in CR, NR, at diagnosis (BM_DG) and after chemotherapy (BM_post), HC colored by T cell state (resting, activated, terminal differentiated), overlaid with a contour plot

Abstract 507 Figure 2

Boxplots showing the differential cluster abundance and adjusted p-values for CR, NR, at diagnosis (BM_DG) and after chemotherapy (BM_post), HC in the three different T cell states (resting, activated, terminal differentiated)

Conclusions The increased number of functional activated T cells at diagnosis and the persistence of a naive/naive-like reservoir at the time of response is a signature associated with achievement of CR. Lack of response (NR) correlates with accumulation of the terminally differentiated and senescent cells in the bone marrow. These results uncover an intertwined relationship between skewing of T cell differentiation and clinical response to chemotherapy. The data provide rationale to either remove senescent or augment activity of naïve/naïve-like T cells as a strategy to reinforce antileukemia immunity.


  1. Knaus HA, Berglund S, Hackl H, et al. Signatures of CD8+ T cell dysfunction in AML patients and their reversibility with response to chemotherapy. JCI Insight 2018; 3(21).

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.