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Background: Acute myeloid leukemia (AML) is a highly heterogeneous malignancy and risk stratification based on genetic and clinical variables is standard practice. However, current models incorporating these factors accurately predict clinical outcomes for only 64-80% of patients and fail to provide clear treatment guidelines for patients with intermediate genetic risk. A plethora of prognostic gene expression signatures (PGES) have been proposed to improve outcome predictions but none of these have entered routine clinical practice and their role remains uncertain. Methods: To clarify clinical utility, we performed a systematic evaluation of eight highly-cited PGES i.e. Marcucci-7, Ng-17, Li-24, Herold-29, Eppert-LSCR-48, Metzeler-86, Eppert-HSCR-105, and Bullinger-133. We investigated their constituent genes, methodological frameworks and prognostic performance in four cohorts of non-FAB M3 AML patients (n= 1175). All patients received intensive anthracycline and cytarabine based chemotherapy and were part of studies conducted in the United States of America (TCGA), the Netherlands (HOVON) and Germany (AMLCG). Results: There was a minimal overlap of individual genes and component pathways between different PGES and their performance was inconsistent when applied across different patient cohorts. Concerningly, different PGES often assigned the same patient into opposing adverse- or favorable- risk groups (Figure 1A: Rand index analysis; RI=1 if all patients were assigned to equal risk groups and RI =0 if all patients were assigned to different risk groups). Differences in the underlying methodological framework of different PGES and the molecular heterogeneity between AMLs contributed to these low-fidelity risk assignments. However, all PGES consistently assigned a significant subset of patients into the same adverse- or favorable-risk groups (40%-70%; Figure 1B: Principal component analysis of the gene components from the eight tested PGES). These patients shared intrinsic and measurable transcriptome characteristics (Figure 1C: Hierarchical cluster analysis of the differentially expressed genes) and could be prospectively identified using a high-fidelity prediction algorithm (FPA). In the training set (i.e. from the HOVON), the FPA achieved an accuracy of ~80% (10-fold cross-validation) and an AUC of 0.79 (receiver-operating characteristics). High-fidelity patients were dichotomized into adverse- or favorable- risk groups with significant differences in overall survival (OS) by all eight PGES (Figure 1D) and low-fidelity patients by two of the eight PGES (Figure 1E). In the three independent test sets (i.e. form the TCGA and AMLCG), patients with predicted high-fidelity were consistently dichotomized into the same adverse- or favorable- risk groups with significant differences in OS by all eight PGES. However, in-line with our previous analysis, patients with predicted low-fidelity were dichotomized into opposing adverse- or favorable- risk groups by the eight tested PGES. Conclusion: With appropriate patient selection, existing PGES improve outcome predictions and could guide treatment recommendations for patients without accurate genetic risk predictions (~18-25%) and for those with intermediate genetic risk (~32-35%). Figure 1 Disclosures Hiddemann: Celgene: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Research Funding; Bayer: Research Funding; Vector Therapeutics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Metzeler:Celgene: Honoraria, Research Funding; Otsuka: Honoraria; Daiichi Sankyo: Honoraria. Pimanda:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Beck:Gilead: Research Funding.

Inherited gene variants play an important role in malignant diseases. The transcriptional repressor growth factor independence 1 (GFI1) regulates hematopoietic stem cell (HSC) self-renewal and differentiation. A single-nucleotide polymorphism of GFI1 (rs34631763) generates a protein with an asparagine (N) instead of a serine (S) at position 36 (GFI136N) and has a prevalence of 3%–5% among Caucasians. Because GFI1 regulates myeloid development, we examined the role of GFI136N on the course of MDS disease. To this end, we determined allele frequencies of GFI136N in four independent MDS cohorts from the Netherlands and Belgium, Germany, the ICGC consortium, and the United States. The GFI136N allele frequency in the 723 MDS patients genotyped ranged between 9% and 12%. GFI136N was an independent adverse prognostic factor for overall survival, acute myeloid leukemia-free survival, and event-free survival in a univariate analysis. After adjustment for age, bone marrow blast percentage, IPSS score, mutational status, and cytogenetic findings, GFI136N remained an independent adverse prognostic marker. GFI136S homozygous patients exhibited a sustained response to treatment with hypomethylating agents, whereas GFI136N patients had a poor sustained response to this therapy. Because allele status of GFI136N is readily determined using basic molecular techniques, we propose inclusion of GFI136N status in future prospective studies for MDS patients to better predict prognosis and guide therapeutic decisions., Graphical abstract, Highlights • GFI136N is present in about 9%–12% of all Caucasian patients with myelodysplastic syndrome. • GFI136N is an independent, adverse prognostic factor for survival. • GFI136N patients with myelodysplastic syndrome respond poorly to hypomethylating agents.

Glucocorticoids play a critical role in the therapy of lymphoid malignancies, including pediatric acute lymphoblastic leukemia (ALL), although the mechanisms underlying cellular resistance remain unclear. We report glucocorticoid resistance attributable to epigenetic silencing of the BIM gene in pediatric ALL biopsies and xenografts established in immune-deficient mice from direct patient explants as well as a therapeutic approach to reverse resistance in vivo. Glucocorticoid resistance in ALL xenografts was consistently associated with failure to up-regulate BIM expression after dexamethasone exposure despite confirmation of a functional glucocorticoid receptor. Although a comprehensive assessment of BIM CpG island methylation revealed no consistent changes, glucocorticoid resistance in xenografts and patient biopsies significantly correlated with decreased histone H3 acetylation. Moreover, the histone deacetylase inhibitor vorinostat relieved BIM repression and exerted synergistic antileukemic efficacy with dexamethasone in vitro and in vivo. These findings provide a novel therapeutic strategy to reverse glucocorticoid resistance and improve outcome for high-risk pediatric ALL.

Abstract 939 Introduction: The glucocorticoids dexamethasone and prednisolone are critical components of combination chemotherapy regimens used to treat pediatric acute lymphoblastic leukemia (ALL). While approximately 80% of patients are cured, poor response to upfront prednisolone monotherapy in 5-10% of patients is a strong predictor of adverse treatment outcome. A greater understanding of the mechanisms responsible for glucocorticoid resistance in pediatric ALL is likely to result in the design of novel strategies to overcome resistance and improve outcome for patients with refractory disease. The pro-apoptotic BH3-only BCL-2 family member BIM (BCL-2L11) has previously been identified as a critical component of glucocorticoid-induced apoptosis in normal and malignant lymphocytes. The purpose of this study was to elucidate clinically relevant mechanisms of glucocorticoid resistance in pediatric ALL, and design and test resistance reversal strategies. Patients and Methods: The study included biopsy specimens obtained at diagnosis from a cohort of patients who received 7 days of prednisolone monotherapy (60 mg/m⋀2/day) and a single age-related dose of intrathecal methotrexate, and whose prednisolone response was determined on Day 8 to be Good (PGR, peripheral blast count < 1 × 10⋀9/L, n=11) or Poor (PPR, peripheral blast count >= 1 × 10⋀9/L, n=11). The study also included biopsies from a cohort of patients who experienced early relapse (within 2 years of diagnosis, n=12). Experimental models of the disease included xenografts (n=12) established in immune-deficient (NOD/SCID) mice using direct explants of patient biopsies. Methods of analysis included: real-time quantitative RT-PCR and immunoblotting of glucocorticoid-induced mRNA and proteins following dexamethasone treatment of ex vivo cultured xenograft cells; DNA methylation analysis of the BIM 5' Untranslated Region (5'UTR) by methylated DNA immunoprecipitation (MeDIP), bisulfite sequencing, and SEQUENOM MassArray Epityper analysis; real time and array based chromatin immunoprecipitation (ChIP) analysis of histone-H3K9 acetylation, H3K4 and H3K27 tri-methylation across the entire BIM locus; as well as assessment of the histone deacetylase inhibitor SAHA (Vorinostat) to reverse dexamethasone resistance both in vitro and in vivo. Results: Dexamethasone resistance in pediatric ALL xenografts was consistently associated with failure to up-regulate BIM mRNA and protein in response to dexamethasone treatment, despite verification that other known glucocorticoid-responsive genes (GILZ, FKBP5) were highly induced in all xenografts. These results indicate specific silencing of BIM in dexamethasone-resistant xenografts rather than a dysfunctional glucocorticoid receptor, leading us to focus on epigenetic regulation of BIM transcription. DNA methylation of the BIM 5'UTR was variable between xenografts, and showed no clear association with dexamethasone resistance. In contrast, the extent of H3K9 acetylation at the BIM locus significantly correlated with the ability of dexamethasone to up-regulate BIM expression in ALL xenografts (R=0.90; P Conclusions: Poor response to glucocorticoid therapy in pediatric ALL is significantly associated with epigenetic silencing of the BIM gene locus, and strategies aimed at improving glucocorticoid sensitivity and clinical outcome should consider incorporating epigenetic modifiers. Disclosures: No relevant conflicts of interest to declare.