Single Cell Network Profiling as a Tool to Identify AML Chemotherapy Resistant Cell Phenotypes Under In Vivo Therapeutic Pressure.
Authors: Cesano Alessandra , Woronicz John , Cohen Aileen Cleary , Covey Todd , Putta Santosh , Gayko Urte , Fantl Wendy J. , Kornblau S.M. 
Published: October 2019

Abstract
Abstract 397

Background:
Although most patients with acute myeloid leukemia (AML) have disease that responds initially to standard cytarabine based induction chemotherapy, approximately 2/3 experience leukemia relapse and succumb to the disease. A reliable and reproducible methodology which could identify individual patients at high risk of disease relapse could be used to selectively triage those patients to more intensive post-remission therapies and thereby improve their outcome while minimizing overall toxicity.

Objectives:
his study evaluated whether single cell network profiling (SCNP), in which cells are perturbed with a modulator and their response ascertained by multiparametric flow cytometry, could be used to characterize specific signaling network profiles associated with in vivo AML blast chemotherapy resistance. The initial hypothesis was to determine whether: a) intracellular signaling profiles dominant at relapse could be identified in subpopulations of cells present at diagnosis and b) whether the presence of blasts with these intracellular signaling profiles at diagnosis could predict for disease relapse.

Methods:
Modulated SCNP was evaluated after sample incubation with 14 cytokines (e.g. interleukins and G-CSF), growth factors (e.g. FLT3L, SCF), chemotherapeutic agents (e.g. cytarabine, etoposide), and other modulators. The use of fluorochrome-conjugated antibodies that recognized leukemic blasts and intracellular phospho-epitopes allowed signaling to be measured in specific cell types at the single cell level. In addition, drug transporters and surface receptor levels were measured.

Results:
Four pairs of AML bone marrow or peripheral blood samples were studied. Intra-patient comparison of intracellular signaling profiles were made between diagnostic samples and with either a primary refractory sample after induction chemotherapy or with a sample obtained at first relapse. High morphologic and functional heterogeneity of myeloblasts was observed in all of the samples both at diagnosis and after induction therapy. Notably, a subpopulation of leukemic cells characterized by simultaneous SCF-mediated increases in the levels of phosphorylated (p-) Akt and p-S6, herein defined as “SCF functional signature”, was identified. This functionally defined leukemic cell subpopulation, although dominant in the post induction samples, was present and detectable at a much lower frequency in the diagnostic samples. Cell surface markers, including c-kit expression, were unable to capture these functionally defined cellular subgroups in single defined subpopulations. The value of the newly identified SCF functional signature in predicting early relapse was then assessed in a larger, independent AML sample set of clinically annotated diagnostic samples. This set included 52 AML samples collected from patients whose leukemia achieved a complete remission after induction chemotherapy, 29 of whom experienced disease relapse within 2 years. In seven of the 52 diagnostic AML samples a subpopulation of blasts displaying the SCF functional signature identified above was detected. Six of these patients experienced disease relapse (five patients within ∼1 year and one patient within 2 years from initial CR). The seventh patient of the group, whose AML blasts carried the t(8;21) translocation (a marker of good prognosis), remained in complete continuous remission at 2 years. Noteworthy, the prognostic value of the SCF functional signature was independent of FLT3 mutational status: of the five patients who relapsed in only one case the leukemic blasts carried the FLT3 ITD mutation.

Conclusions
SCNP offers a novel approach to identify subpopulations of cells present at diagnosis with characteristics predictive of higher rates of relapse and this information can be used for monitoring or to guide therapy.

Disclosures:
Cesano: Nodality, Inc.: Employment, Equity Ownership. Woronicz:Nodality, Inc.: Employment, Equity Ownership. Cleary Cohen:Nodality Inc.: Employment, Equity Ownership. Covey:Nodality, Inc.: Employment, Equity Ownership. Putta:Nodality, Inc.: Employment, Equity Ownership. Gayko:Nodality, Inc.: Employment, Equity Ownership. Fantl:Nodality, Inc.: Employment, Equity Ownership. Kornblau:Nodality, Inc.: Consultancy.