Abstract 4843

Background:

All major molecular technology platforms have used cryopreserved samples as a source in biomarker development studies. Such samples enable the conduct of prospectively designed studies using banked samples with relevant clinical annotations, thus potentially reducing the duration of biomarker development. Single Cell Network Profiling (SCNP) is a new technology platform requiring viable cells. It uses multi-parametric flow cytometry to measure biological pathways focusing on intra-cellular signaling and post-translational modulations in response to a variety of modulators (growth factors, cytokines, drugs, etc.). As part of a collaboration between industry, academic institutions, and cooperative groups to improve acute myeloid leukemia (AML) management, we are developing clinical tests based on SCNP to predict induction chemotherapy response or risk of relapse. To date, all the development studies have been performed on DMSO cryopreserved specimens of ficoll fractionated bone marrow (BM) or peripheral blood (PB) mononuclear cells. Demonstrating a correlation of SCNP readouts between fresh and cryopreserved preparations is essential to applying these proteomic signatures to the clinical setting.

Objectives:

To compare the results of SCNP assays between paired fresh and cryopreserved samples in a multicenter prospective study.

Methods:

To date, 13 fresh BM and PB samples were prospectively collected from pediatric or adult non-M3 AML patients at 3 academic centers and shipped over night to the Nodality CLIA lab. Samples were required to have 2 million viable cells per aliquot for SCNP assays, and underwent ficoll separation and mononuclear cells were divided into 2 aliquots - one processed fresh, and the second cryopreserved for 1 month, and then thawed and processed for the SCNP assay. 70 SCNP node-metrics (i.e. proteomic readouts in the presence or absence of modulator), identified previously as candidate proteomic signatures for several assays in development (including PIK3, Jak/STAT and DNA damage/apoptosis pathways) were investigated. The assay readouts for blast cells from a fresh aliquot were compared to the results from a cryopreserved aliquot by linear regression, Bland-Altman, and Lin's concordance analysis.

Results:

The analysis of paired aliquots from 13 patients, with median WBC of 27.9 (3-60) 10e3/ul, showed that cryopreservation did not affect sample quality as measured by percent of cells that were negative for cleaved PARP expression (R2 = 0.92 cryopreserved vs. fresh). The majority of unmodulated node-metrics (59%) and modulated node-metrics (68%, see Table) had a good correlation between the two preparations as measured by linear regression i.e., R2 > 0.64. The node-metrics with a lower R2 were using either a dim fluorophore (i.e. Alexa-647) and/or were within the low signal range (e.g., Erk basal); and therefore were not good candidates for future test development. Results using both Bland Altman and Lin's Concordance methods showed good concordance. Assessment of aliquots with up to 4 years in cryopreservation is ongoing and data from the 6 month time-point will be presented.

Conclusions:

These studies highlight the importance of cryopreservation of AML samples at clinical sites and by cooperative groups. These results demonstrate that cryopreservation maintains the activation signaling potential of AML blasts. SCNP assays developed and validated using cryopreserved samples can be applied to fresh samples and integrated prospectively into frontline clinical trials and clinical practice.

Table 1:

Goodness of fit (R2) values from regressing Cryo against Fresh for modulated node-metrics. Fold and Uu (rank based) metrics measure changes in signaling protein levels due to modulation. A= Alexa

ModulatorAssay Read-outColorR2 for FoldR2 for Uu
Cytarabine + Daunorubicin cPARP FITC 0.71 0.63 
 pChk2 A. 647 0.38 0.37 
Etoposide cPARP FITC 0.78 0.49 
 pChk2 A 647 0.52 0.37 
FLT3L pAkt A 647 0.13 0.09 
 pErk 1/2 PE 0.46 0.55 
 pS6 A 488 0.89 0.94 
G-CSF pStat1 A 488 0.73 0.72 
 pStat3 PE 0.88 0.94 
 pStat5 A 647 0.89 0.85 
H2O2 pAkt A 488 0.79 0.85 
 pPLCy2 PE 0.83 0.89 
 pSlp76 A 647 0.80 0.82 
IL-27 pStat1 A 488 0.92 0.93 
 pStat3 PE 0.94 0.90 
 pStat5 A 647 0.93 0.92 
PMA pCreb PE 0.92 0.93 
 pErk 1/2 A 647 0.94 0.90 
 pS6 A 488 0.93 0.92 
SCF pAkt A 647 0.49 0.09 
 pErk 1/2 PE 0.15 0.18 
 pS6 A 488 0.86 0.75 
ModulatorAssay Read-outColorR2 for FoldR2 for Uu
Cytarabine + Daunorubicin cPARP FITC 0.71 0.63 
 pChk2 A. 647 0.38 0.37 
Etoposide cPARP FITC 0.78 0.49 
 pChk2 A 647 0.52 0.37 
FLT3L pAkt A 647 0.13 0.09 
 pErk 1/2 PE 0.46 0.55 
 pS6 A 488 0.89 0.94 
G-CSF pStat1 A 488 0.73 0.72 
 pStat3 PE 0.88 0.94 
 pStat5 A 647 0.89 0.85 
H2O2 pAkt A 488 0.79 0.85 
 pPLCy2 PE 0.83 0.89 
 pSlp76 A 647 0.80 0.82 
IL-27 pStat1 A 488 0.92 0.93 
 pStat3 PE 0.94 0.90 
 pStat5 A 647 0.93 0.92 
PMA pCreb PE 0.92 0.93 
 pErk 1/2 A 647 0.94 0.90 
 pS6 A 488 0.93 0.92 
SCF pAkt A 647 0.49 0.09 
 pErk 1/2 PE 0.15 0.18 
 pS6 A 488 0.86 0.75 
Disclosures:

Cesano: Nodality Inc.: Employment, Equity Ownership. Gotlib: Nodality Inc.: Honoraria. Lacayo: Nodality Inc.: Honoraria. Putta: Nodality Inc.: Employment, Equity Ownership. Lackey: Nodality Inc.: Employment, Equity Ownership. Gayko: Nodality Inc.: Employment, Equity Ownership. Kornblau: Nodality Inc.: Honoraria.

Author notes

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Asterisk with author names denotes non-ASH members.

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