Pediatric LSC3 (pLSC3) Score Derived from DNMT3B-CD34-GPR56 As a Prognostic Tool to Predict AML Patient Outcome: Results from Two Independent Pediatric AML Cohorts

Introduction: Resistance and relapse remain major obstacles in the treatment of acute myeloid leukemia (AML). Pre-existence and persistence of drug resistant leukemia stem cells (LSCs) is considered one of the major causes of relapse. A previous study (Ng et al., 2016) reported a prognostic signature of 17 genes (LSC17 score) differentially expressed in LSC+ compared to LSC- cell fractions that predicted outcome in patients with AML thereby classifying patients into high and low risk groups. The goal of this study is to determine the validity of LSC17 score in pediatric AML patients and to enhance its clinical utility by exploring a new score with limited number of stem cell genes. Methods: 150 pediatric patients with AML enrolled in the multicenter AML02 clinical trial (ClinicalTrials.gov Identifier: NCT00136084) with Affymetrix U133A microarray gene expression data and clinical data were included in the study. Since only 14 of the 17 genes were represented on the Affymetrix U133A gene chip we tested the validity of the LSC14 score using the previously defined equation (Ng et al, 2016) with multiple clinical endpoints such as minimum residual disease (MRD), event free survival (EFS) and overall survival (OS). To reduce the model complexity, we applied a penalized regression algorithm called the least absolute shrinkage and selection operator (LASSO) implemented in the glmnet R-package using event free survival (EFS) as an outcome variable. Score of the new equation, which included three genes, was designated as pediatric-LSC3 (pLSC3). pLSC3 was tested in the AML02 cohort for association of high or low pLSC3 (based on the median value) with clinical endpoints mentioned above. pLSC3 score equation was validated using publically available gene-expression data from 117 pediatric relapse enriched AML patient cohort enrolled in Children's Oncology Group (COG) protocol (TARGET database). COX-proportional hazard models and Log rank test were used for survival data analysis. Results: AML02 cohort: Patients with high LSC14 scores (greater than median), had significantly worse MRD (p<0.0001), EFS (HR = 3.72, P <0.00001) and OS (HR = 4.85, P <0.00001) compared to patients with low LSC14 scores. After applying LASSO regression to simplify the score equation, only three genes (DNMT3B, CD34 and GPR56) remained significant to the model fit of the EFS data thus we created a pLSC3 with coefficients as described in the equation: pLSC3_SCORE = (DNMT3B*0.0431) + (CD34*0.00076) + (GPR56*0.0326). Patients were classified as high or low pLSC3 and patients with high pLSC3 scores had significantly worse EFS (HR=3.595, P < 0.0001; Figure 1A) and OS (HR= 4.53, P<0.0001) and higher MRD after induction 1 and induction II, respectively (P<0.00001 and p=0.0001 respectively; Figure 1C). These results were further validated in an independent cohort of patients from TARGET database, where higher pLSC3 score was associated with worse EFS, OS and MRD (EFS: HR=1.64, P=0.0248; Figure 1B, OS: HR = 1.77, P = 0.0349 and MRD p=0.0002, Figure 1D). Consistent results were also observed with high pLSC3 predictive of significantly worse outcome within standard risk group patients within both AML02 and COG cohorts (AML02-EFS: HR = 2.97, P = 0.0153, COG-EFS: HR = 2.22, P = 0.0096; Figure 1E and F respectively). In a multivariate COX regression model, pLSC3 score groups was the only significant covariate (table 1). It explained 13.1% of variability in EFS and 11.6% of variability in OS, while other prognostic factors such as risk groups, FLT3 status, treatment arm and age collectively explained 15.1 and 12.1 % of variability. Discussion: In summary, our results show validity of a previously defined LSC14 score in a pediatric AML population from the multicenter AML02 clinical trial. To enhance the clinical utility, score equation was further simplified and the final score (pLSC3) was derived from three genes: DNMT3B, which encodes for DNA methyltransferase; CD34, an important cell surface marker for early-undifferentiated LSCs; and GPR56, a G protein coupled receptor of significance in AML. Given that there is need to refine classification of a highly heterogeneous group of patients with standard risk AML, we show that differentiating standard risk patients based on pLSC3 score should be considered in the future. We show the relevance of pLSC3 in two independent cohorts, opening up opportunities to improve treatment outcomes of pediatric patients with AML. Disclosures No relevant conflicts of interest to declare.

The Role of B Cell-Activating Factor (BAFF) in the Biology of Multiple Myeloma (MM).

BAFF is a member of the tumor necrosis factor (TNF) family and is critical for the maintenance and homeostasis of normal B-cell development. Importantly, BAFF promotes the generation of rapidly dividing immunoglobulin secreting plasmablasts from activated memory B cells by enhancing their survival. Given that MM is a cancer of plasma cells and that the signaling cascades implicated in receptor ligand interactions of BAFF are crucial in MM cell biology, we hypothesized that this cytokine may play a critical role in MM cell development, survival, and proliferation. We performed gene expression profiling (GEP) on CD 138+ plasma cells isolated from 90 MM patients (45 newly diagnosed and 45 relapsed) and 11 healthy controls using the Affymetrix U133A arrays. Our data demonstrates increased expression of transmembrane activator and calcium modulator and cyclophilin ligand interactor (TACI) and B-cell maturation antigen (BCMA), 2 receptors used by BAFF to exert its effects. Our data also shows an increased expression of a proliferation-inducing ligand (APRIL), another member of the TNF family with homology to BAFF. Expression levels of BAFF and BAFF-R could not be determined because of lack of these probe sets on the Affymetrix U133A arrays. GEP analysis shows increased BCMA expression (p&lt;0.0001, student T test) on newly diagnosed and relapsed MM versus normal plasma cells. Flow cytometry on MM cell lines demonstrated a differential expression of the three receptors of BAFF, with BCMA present on most cell lines but BAFF-R expressed at low levels only on LR5 cells and DOX40 MM cells. In contrast, flow cytometry performed on MM patient cells demonstrated the presence of all 3 receptors on CD 138+ cells. ELISA assays performed on 30 MM sera demonstrated a mean BAFF level of 618 pg/ml (range: 128–2126pg/ml) versus 235pg/ml (range: 158–326pg/ml) in 7 normal donor sera. Fifty six% (17/30) of MM patients had BAFF levels in excess of the highest value noted in normals. To understand the role BAFF might play in the biology of MM, we studied the effects of recombinant BAFF (rh-BAFF) on MM cells directly and in the context of its bone marrow microenvironment. (abstract # 554746) rh-BAFF conferred a survival advantage to MM cells and protected them against dexamethasone-induced cytotoxicity. Importantly, anti-apoptotic proteins Bcl2 and Mcl-1 were upregulated, as were growth and survival signals belonging to the JAK/STAT and MAPKinase pathways. Conversely, neutralizing antibody to BAFF blocked, at least in part, blocked the upregulation of anti-apoptotic proteins with associated growth and survival, confirming that these effects were due to BAFF. Importantly, all of these signals were downregulated even in the presence of bone marrow stromal cells (BMSCs). These data therefore show a role for BAFF mediating MM cell survival and provide the framework for inhibiting BAFF, either alone or in combination with dexamethasone, to improve patient outcome in MM.