Single Cell Network Profiling (SCNP) Signatures Predict Response to Induction Therapy and Relapse Risk In Pediatric Patients with Acute Myeloid Leukemia: Children's Oncology Group (COG) Study POG-9421

About 90% of pediatric patients with newly diagnosed acute myeloid leukemia (AML) have disease responsive to chemotherapy and achieve an initial complete response (CR) with anthracycline/cytarabine-based induction chemotherapy. However, 30–70% of patients of varying risks relapse within 4–5 years. Prospective identification of patients unlikely to benefit from induction therapy or likely to relapse could spare patients from treatment-related toxicities and allow consideration of alternative therapies. Current prognostic factors (e.g., cytogenetics and FLT3 ITD) of value at the population level are imperfect at the individual level. SCNP is a tool used to measure the effects of multiple modulators (including drugs) on signaling pathways at both the single-cell and individual patient level. A set of classifiers has been developed using SCNP technology that predicts the likelihood of response to anthracycline/cytarabine-based induction in adult patients with newly diagnosed AML. This training set has led to the development of classifiers that predict the response to anthracycline/cytarabine-based induction therapy and risk of disease relapse for pediatric patients with newly diagnosed AML. Validation in additional COG cohorts will lead to a novel SCNP classifier that can be used in the clinic.

SCNP assays were performed on 77 bone marrow samples from pediatric AML patients enrolled in POG trial 9421 of which 67 were evaluable/had sufficient data for analysis and were enriched for non-responders (NR). 80 combinations of modulators and intra-cellular proteins (signaling nodes) were investigated including nodes involved in the phosphoinositide 3-kinase (PI3K), Janus Kinases (JAK), signal transducers and activators of transcription (STAT) and the DNA damage response and apoptosis pathways. Basal and modulated protein levels in leukemic blasts were measured using several metrics (e.g., fold change, total level of phosphorylation, and a rank based method Uu measuring the proportion of cells that shift from baseline), and nodes were examined in univariate and multivariate analyses for their ability to discriminate between responders (CR, n=46) and non-responders (NR, n=21) to anthracycline/cytarabine-based induction therapy. Furthermore, nodes were examined for their ability to identify patients likely to be in complete continuous remission (CCR, n=23) or relapse (CR-Rel, n=23) within 4 years.

Univariate analysis revealed 19 nodes associated with disease response to conventional induction therapy and 9 associated with CR-Rel (i.e., area under the operator/receiver curve (AUC of ROC=AUC*) >0.65; p<0.05). As in adult studies, nodes involved in the apoptotic response to agents inducing DNA damage (e.g., etoposide→c-PARP AUC* 0.83, AraC+Daunorubicin→c-PARP AUC* 0.76, AraC+Daunorubicin→p-Chk2 AUC* 0.71) showed higher levels of apoptosis in CR samples than in NR samples. Similarly, FLT3 and SCF phosphorylation levels of PI3K pathway members S6 (AUC* 0.70) and ERK (AUC* 0.65) were also higher in CR samples, while hydrogen peroxide as a modulator (acting either as a reactive oxygen species or as a phosphatase inhibitor) revealed lower p-Akt and p-PLC γ levels in NR samples (AUC* 0.70 for both). In multivariate analysis combination of 2–8 nodes (representing apoptosis, Jak/Stat and PI3K pathways) resulted in classifiers with good performance characteristics (bootstrap adjusted AUC* 0.84 – 0.88) in predicting response to induction therapy. Increased sensitivity to etoposide and anthracycline/cytarabine was also associated with CCR in univariate analysis (AUC* 0.77 and 0.68 respectively). Thapsigargin, a modulator known to raise intracellular calcium, induced p-Erk, p-CREB and p-S6 less in CR-Rel than in CCR samples. To predict the response to therapy, multivariate classifiers were better than individual nodes at discriminating between CR-Rel and CCR groups (adjusted AUC*>0.8). Additional analyses that evaluate independence and ability to combine clinical or molecular predictors (e.g., cytogenetics, FLT3 ITD) with SCNP data will be presented.

The training study data show the value of performing quantitative SCNP under modulated conditions as the basis for developing highly predictive tests for response to induction chemotherapy in pediatric patients with newly diagnosed AML. Independent validation studies will follow.

Lacayo: Nodality Inc.: Honoraria. Cohen:Nodality Inc.: Employment, Equity Ownership. Westfall:Nodality Inc.: Employment, Equity Ownership. Lackey:Nodality Inc.: Employment, Equity Ownership. Xin:Nodality Inc.: Employment, Equity Ownership. Gayko:Nodality Inc.: Employment, Equity Ownership. Putta:Nodality Inc.: Employment, Equity Ownership. Cesano:Nodality Inc.: Employment, Equity Ownership.