Functional Characterization of FLT3 Receptor Signaling Deregulation in Acute Myeloid Leukemia by Single Cell Network Profiling (SCNP)

Molecular characterization of the FMS-like tyrosine kinase 3 receptor (FLT3) in cytogenetically normal acute myeloid leukemia (AML) has recently been incorporated into clinical guidelines based on correlations between FLT3 internal tandem duplications (FLT3-ITD) and decreased disease-free and overall survival. These mutations result in constitutive activation of FLT3, and FLT3 inhibitors are currently undergoing trials in AML patients selected on FLT3 molecular status. However, the transient and partial responses observed suggest that FLT3 mutational status alone does not provide complete information on FLT3 biological activity at the individual patient level. Examination of variation in cellular responsiveness to signaling modulation may be more informative.Using single cell network profiling (SCNP), cells were treated with extracellular modulators and their functional responses were quantified by multiparametric flow cytometry. Intracellular signaling responses were compared between healthy bone marrow myeloblasts (BMMb) and AML leukemic blasts characterized as FLT3 wild type (FLT3-WT) or FLT3-ITD. Compared to healthy BMMb, FLT3-WT leukemic blasts demonstrated a wide range of signaling responses to FLT3 ligand (FLT3L), including elevated and sustained PI3K and Ras/Raf/Erk signaling. Distinct signaling and apoptosis profiles were observed in FLT3-WT and FLT3-ITD AML samples, with more uniform signaling observed in FLT3-ITD AML samples. Specifically, increased basal p-Stat5 levels, decreased FLT3L induced activation of the PI3K and Ras/Raf/Erk pathways, decreased IL-27 induced activation of the Jak/Stat pathway, and heightened apoptotic responses to agents inducing DNA damage were observed in FLT3-ITD AML samples. Preliminary analysis correlating these findings with clinical outcomes suggests that classification of patient samples based on signaling profiles may more accurately reflect FLT3 signaling deregulation and provide additional information for disease characterization and management.These studies show the feasibility of SCNP to assess modulated intracellular signaling pathways and characterize the biology of individual AML samples in the context of genetic alterations

Functional Pathway Analysis Using SCNP of <em>FLT3</em> Receptor Pathway Deregulation in AML Provides Prognostic Information Independent from Mutational Status

<div><p>FMS-like tyrosine kinase 3 receptor (<i>FLT3</i>) internal tandem duplication (ITD) mutations result in constitutive activation of this receptor and have been shown to increase the risk of relapse in patients with acute myeloid leukemia (AML); however, substantial heterogeneity in clinical outcomes still exists within both the ITD mutated and unmutated AML subgroups, suggesting alternative mechanisms of disease relapse not accounted by <i>FLT3</i> mutational status. Single cell network profiling (SCNP) is a multiparametric flow cytometry based assay that simultaneously measures, in a quantitative fashion and at the single cell level, both extracellular surface marker levels and changes in intracellular signaling proteins in response to extracellular modulators. We previously reported an initial characterization of FLT3 ITD-mediated signaling using SCNP. Herein SCNP was applied sequentially to two separate cohorts of samples collected from elderly AML patients at diagnosis. In the first (training) study, AML samples carrying unmutated, wild-type <i>FLT3</i> (<i>FLT3</i> WT) displayed a wide range of induced signaling, with a fraction having signaling profiles comparable to <i>FLT3</i> ITD AML samples. Conversely, the <i>FLT3</i> ITD AML samples displayed more homogeneous induced signaling, with the exception of patients with low (<40%) mutational load, which had profiles comparable to <i>FLT3</i> WT AML samples. This observation was then confirmed in an independent (verification) cohort. Data from the second cohort were also used to assess the association between SCNP data and disease-free survival (DFS) in the context of <i>FLT3</i> and nucleophosmin (<i>NPM1</i>) mutational status among patients who achieved complete remission (CR) to induction chemotherapy. The combination of SCNP read outs together with <i>FLT3 and NPM1</i> molecular status improved the DFS prediction accuracy of the latter. Taken together, these results emphasize the value of comprehensive functional assessment of biologically relevant signaling pathways in AML as a basis for the development of highly predictive tests for guidance of post-remission therapy.</p> </div

Nodes in combination with molecular characterization improve DFS modeling.

<p>The table displays the <i>p</i>-values for the models (<i>P</i> Model) as well as the components: node (<i>P</i> Node), molecular characterization (<i>P</i> MolChar), and the interaction term (<i>P</i> interaction term).</p><p>p-S6 indicates phosphorylated S6 ribosomal protein; G.CSF, granulocyte colony-stimulating factor; p-STAT3, phosphorylated signal transducer and activator of transcription 3; PMA, phorbol myristate acetate; p-ERK, phosphorylated endoplasmic reticulum kinase; SCF, Skp, Cullin, and F-box containing complex; CD34, cluster of differentiation 34; cPARP, cleaved poly(ADP-ribose) polymerase; and p-Chk2, phosphorylated checkpoint 2 protein kinase.</p><p>Sample size n = 39 for each row</p>*<p>Wald test used.</p>†<p>t-test (H0:Slope = 0). Significant p-value suggests influence of model component on hazard ratio.</p>‡<p>Log of hazard ratio fit of MolChar plus node with interaction term using Cox Proportional -hazards regression: log h(t) = β₀+β₁*FLT3 ITD+β₂*node+β₂*node*FLT3 ITD.</p>§<p>Signaling examined in non-apoptotic Leukemic cells (cPARP negative).</p>∥<p>Interaction term included in model to evaluate simultaneous influence of MolChar and node on hazard ratio.</p

Study Design Diagram.

<p>Influence of <i>FLT3</i> ITD mutation status on functional signaling was studied in two independent data sets; observations made in the first set (training, N = 46) were verified in the second set (Verification, N = 104).</p

Clinical outcomes: verification cohort.

<p>Fisher's exact test was applied to categorical variables.</p><p>NR indicates non-responder; and CR, complete responder.</p