ALBERT

Description: Myelodysplastic syndrome (MDS) and chronic myelomonocytic leukaemia (CMML) are haematological disorders that develop in haematopoietic stem or progenitor cells (HSPCs) and are characterised by ineffective haematopoiesis. 5'-Azacitidine (AZA) is a DNA demethylating agent that is effective in treating MDS and CMML. However, response rates are less than 50% and the basis for poor response is currently unknown. A patient's potential to respond cannot be currently determined until after multiple cycles of AZA treatment and alternative treatment options for poor responders are limited. To address these fundamental questions, we enrolled patients on a compassionate access program prior to the listing of AZA on the pharmaceuticals benefit scheme in Australia. We have collected bone marrow from 18 patients (10 MDS, 8 CMML) at seven different stages of treatment, starting from before treatment until after six cycles of AZA treatment, and isolated high-purity CD34+ HSPCs at each stage. 10 of these patients (5 MDS and 5 CMML) responded completely to AZA while 8 did not achieve complete response. We performed next-generation sequencing (RNA-seq) of these HSPCs to identify the basis of poor response to AZA therapy. Analysis of the RNA-seq data from pre-treatment HSPCs has revealed a striking differential expression of 1148 genes between patients who were subsequently complete (CR) or non-complete responders (non-CR) to AZA therapy (Figure 1A). Using a Fluidigm nanofluidic system, we have validated the differential expression of a subset of these genes between CR and non-CR patients in two independent cohorts, totalling 67 patients, from the U.K. and Sweden. We have additionally confirmed that our gene signature does not simply segregate patients based on disease severity or poor overall survival, but rather uniquely prognosticates best AZA response. Pathway analyses of the differentially expressed genes indicates that the HSPCs of non-CR patients have decreased cell cycle progression and DNA damage pathways, while concomitantly possessing increased signalling through integrin and mTOR/AKT pathways. Using computational methods, we have determined that the expression of 15 genes (within the 1148 gene set) is sufficient to separate CRs from non-CRs across independent cohorts (Figure 1B). We have also developed a predictive AZA response algorithm that utilises the expression of these genes to identify potential complete and non-complete responders to AZA with high specificity and sensitivity (Figure 1C). Furthermore, we have identified statistically significant correlations between recurrent DNA mutations in MDS and our prognostic gene signature (SF3B1 & TET2 with CR, STAG2 and NUP98 with non-CR, p

Description: 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.

Description: Background: C/EBPa is a lineage determining transcription factor, critical for terminal cell differentiation in different tissues including the bone marrow (BM), lung, liver, and adipocytes. Adequate CEBPA levels are needed to maintain the haematopoietic stem cell (HSC) pool and to promote neutrophilic differentiation. This knowledge points towards the importance of CEBPA dosage at different stages of differentiation. Aim: To investigate how CEBPA dosage is regulated at the transcriptional level by specific enhancer(s) and to study their role in haematopoiesis. Results: Chromatin immunoprecipitation for the active mark H3K27ac followed by deep sequencing (ChIP-seq), revealed eight putative regulatory elements within the CEBPA locus. One enhancer showed marked H3K27ac enrichment at +42Kb downstream of CEBPA particularly in CD34+ haematopoietic stem cells (HSCs), implying a role for CEBPA regulation at earlier stages of haematopoiesis. ChIP-Seq experiments revealed binding of RUNX1, ERG, PU.1, FLI1 and GATA2 to this +42Kb enhancer in CD34+ BM cells. Moreover, myeloid cell lines MOLM1 and U937 also showed H3K27ac enrichment at this enhancer, indicating that its activity is maintained upon myeloid differentiation. In contrast, active histone marks were completely devoid at this element in CEBPA expressing lung (A549) and liver (HepG2) cell lines, indicating hematopoietic specificity of this enhancer. Chromatin looping between the +42Kb enhancer and the CEBPA promoter was demonstrated by 4C-Seq, highlighting the specificity of this enhancer in CEBPA regulation. Furthermore, using CRISPR/Cas9 technology we deleted the +42Kb enhancer in the myeloid cell line THP-1 and showed 70% reduction of CEBPA mRNA levels. The +42Kb enhancer is conserved and located at +37Kb near Cebpa in mice. Using CRISPR/Cas9 system, we deleted the +37Kb enhancer in one-cell stage zygotes. Heterozygous mice were inter-crossed and F1 generation mice were born at normal mendelian ratios. Morphological and flow-cytometric analysis of peripheral blood and BM at 8-10 weeks of age, showed 10-20 fold decrease in (MAC1+/GR1+) neutrophil counts in homozygous +37Kb-/- mice, compared to +37Kbwt/wt and +37Kb-/wt controls. In line with the block of neutrophil development, flow-cytometric analysis revealed an increase (2 fold) in CD34+CD16/32low common myeloid progenitors and a decrease (2 fold) in the CD34+CD16/32high granulocyte/ monocyte progenitorsof +37Kb-/- mice. From these findings we hypothesized that the absence of the +37Kb enhancer disturbs the myeloid differentiation program via reduced Cebpa levels. In fact, Cebpa expression levels were reduced by 60-80% in bone marrow of +37Kb-/- mice, but unchanged in other Cebpa -expressing tissues such as lung and liver, indicating tissue specificity of this enhancer. Diminished Cebpa expression levels were accompanied by decreasedexpression of Cebpa target genes, including Csf3r. In line with this, bone marrow progenitor cells from +37Kb-/- mice were completely unresponsive to Csf3 in a colony forming assay. Given the importance of Cebpa in HSCs maintenance, we investigated the HSC population and found that long-term HSCs (CD48- CD150+) and short-term HSCs (CD48- CD150-) were depleted in the bone marrow of the +37Kb-/- mice. HSC depletion was accompanied by an increase in the CD48+/CD150- multipotent progenitors (MPPs). The +37Kb-/- MPPs, unlike controls, were able to serially replate in vitro under IL-3, GM-CSF, IL-6, SCF growth factor conditions with minimal evidence of differentiation, suggesting a leukemogenic potential. Reintroduction of Cebpa cDNA into +37Kb-/- MPPs fully recovered neutrophil development. Conclusion: We conclude that the +37Kb enhancer is tissue-specific and plays a central role in haematopoiesis regulating Cebpa dosage. Our study reveals that the bone marrow maintains its integrity through the activity of the +37Kb enhancer, which (1) prevents HSC exhaustion and (2) preserves neutrophilic development. The in vitro replating capacity of MPPs isolated from +37Kb-/- animals suggests that aberrant control of this enhancer may be a primary leukaemogenic event. In line with this, it is important to note that the conserved enhancer in humans (+42 KB) is a frequent target for oncogenic transcription factors such as AML1-ETO or EVI1, two oncogenes which are found in two distinct subtypes of AMLs with very low C/EBPa expression. Disclosures No relevant conflicts of interest to declare.

Description: Key Points The glucocorticoid receptor coordinately regulates the antiapoptotic BCL2 and proapoptotic BIM genes in pediatric ALL cells in vivo. GR binding at a novel intronic region is associated with BIM transcription and dexamethasone sensitivity in pediatric ALL cells in vivo.

Description: The Ets-related gene (ERG) is an Ets-transcription factor required for normal blood stem cell development. ERG expression is down-regulated during early T-lymphopoiesis but maintained in T-acute lymphoblastic leukemia (T-ALL), where it is recognized as an independent risk factor for adverse outcome. However, it is unclear whether ERG is directly involved in the pathogenesis of T-ALL and how its expression is regulated. Here we demonstrate that transgenic expression of ERG causes T-ALL in mice and that its knockdown reduces the proliferation of human MOLT4 T-ALL cells. We further demonstrate that ERG expression in primary human T-ALL cells is mediated by the binding of other T-cell oncogenes SCL/TAL1, LMO2, and LYL1 in concert with ERG, FLI1, and GATA3 to the ERG +85 enhancer. This enhancer is not active in normal T cells but in transgenic mice targets expression to fetal liver c-kit+ cells, adult bone marrow stem/progenitors and early CD4−CD8− double-negative thymic progenitors. Taken together, these data illustrate that ERG promotes T-ALL and that failure to extinguish activity of stem cell enhancers associated with regulatory transcription factors such as ERG can contribute to the development of leukemia.

Description: Abstract 3525 Leukaemic transformation is driven by aberrant transcriptional programs often in combination with abnormal proliferative signalling. These programs operate in normal hematopoiesis where they are involved in hematopoietic stem cell (HSC) proliferation and maintenance. ERG is a component of normal and leukemic stem cell signatures and high ERG expression has been proposed as a risk factor for poor prognosis in acute myeloid leukemia (AML). However, mechanisms that underlie ERG expression in AML and how its expression relates to leukemic stemness are unknown. We report that ERG expression in AML is associated with activity of the ERG+85 stem cell enhancer (SCE) and a heptad of transcription factors that combinatorially regulate genes in normal HSCs. Gene expression signatures derived from ERG+85 stem cell enhancer (Fig A) and heptad activity (Fig B) predict clinical outcome in a cytogenetically normal cohort of AML (CN-AML) patients when ERG expression alone fails. The heptad signature is an independent risk factor for poor overall and event-free survival (Fig C). There were no long-term survivors amongst patients with a heptad signature, FLT3 mutations and wild-type NPM1 (Fig D) pointing to a hitherto unappreciated link between aberrant signaling and transcriptional mediators of hematopoietic stem cell identity. In two independent cohorts, the heptad signature was as closely associated with wild-type NPM1 AML as the HOX signature was with mutant NPM1 AML (Fig E–F) suggestive of a collective role for these transcription factors in mediating the leukemic signature in the former. Taken together, these results show that key transcriptional regulators cooperate in establishing stem cell signatures in leukemic cells and that the underlying spectrum of somatic mutations contributes to the development of these signatures and modulate their influence on clinical outcome. Disclosures: No relevant conflicts of interest to declare.

Description: Modulators of epithelial-to-mesenchymal transition (EMT) have recently emerged as novel players in the field of leukemia biology. The mechanisms by which EMT modulators contribute to leukemia pathogenesis, however, remain to be elucidated. Here we show that overexpression of SNAI1, a key modulator of EMT, is a pathologically relevant event in human acute myeloid leukemia (AML) that contributes to impaired differentiation, enhanced self-renewal, and proliferation of immature myeloid cells. We demonstrate that ectopic expression of Snai1 in hematopoietic cells predisposes mice to AML development. This effect is mediated by interaction with the histone demethylase KDM1A/LSD1. Our data shed new light on the role of SNAI1 in leukemia development and identify a novel mechanism of LSD1 corruption in cancer. This is particularly pertinent given the current interest surrounding the use of LSD1 inhibitors in the treatment of multiple different malignancies, including AML.

Description: Key Points Genome-wide binding profiles of FLI1, ERG, GATA2, RUNX1, SCL, LMO2, and LYL1 in human HSPCs reveals patterns of combinatorial TF binding. Integrative analysis of transcription factor binding reveals a densely interconnected network of coding and noncoding genes in human HSPCs.

Description: Background: Myelodysplastic Syndrome (MDS) and Chronic Myelomonocytic Leukaemia (CMML) are haematological disorders that develop in haematopoietic stem or progenitor cells (HSPCs) and are characterised by ineffective haematopoiesis. 5'-Azacitidine (AZA), a DNA demethylating agent, is the primary drug for the treatment of high-risk MDS and CMML and response is associated with improved survival benefits. However, only half of treated patients will ever respond to AZA and the molecular basis for poor response is currently unknown. There are few alternative therapies for the non-responders. Additionally, AZA response is rarely sustained and a substantial fraction of responders will eventually relapse. The in vivo effect of AZA therapy on dysplastic cells in responders is unclear and there are no predictive markers for impending relapse in responders. Methods: To address these fundamental questions, we enrolled 18 high-risk MDS and CMML patients on a compassionate access program for AZA in Australia. Bone marrow was collected at seven different points - before treatment; through 6 cycles of treatment; and at up to two years after initiation - and we isolated high-purity CD34+ HSPCs (Figure A). 10 patients had a complete response while 8 were poorer responders. We performed RNA-seq to query the transcriptomes (and validated by Fluidigm-based PCR) and deduced the clonal evolution in the bone marrow in response to AZA therapy (by whole exome-sequencing, followed by targeted capture resequencing, and genotyping of individual CFU colonies). Our findings were validated in an independent cohort of 57 patients. We used flow cytometry to develop a clinically relevant prognostic assay for AZA resistance and developed a novel stromal co-culture based functional drug testing platform to rationally discover combinational drug therapies to overcome AZA resistance. Results: We hypothesised that primary AZA resistance would be driven by pre-existing molecular differences between responders and non-responders. Analysis of the pre-treatment RNA-seq data strikingly revealed the differential expression of 1148 genes between responders and non-responders (Figure B). Pathway analyses of these genes indicated that cell cycle and DNA damage response pathways were relatively up-regulated in responders compared to non-responders, indicating that HSPCs of non-responders are more quiescent compared to responders (Figure C). We validated these gene expression differences in independent patient cohorts from the U.K. and Sweden (n=57; 27 responders, 30 non-responders). We then adapted a flow cytometry based assay, amenable to prospective use in a clinical diagnostic setting, to directly detect the increased quiescence of CD34+ CD38+ haematopoietic progenitors in unsorted bone marrows of non-responders across all cohorts (Figure D). Finally, to reverse the quiescence of progenitor cells of non-responders, and make them more susceptive to AZA, we leveraged our RNA-seq discoveries to target pathways that were relatively up-regulated in non-responders. Using a stromal co-culture drug testing platform that we developed, we discovered that inhibiting integrin-linked signalling combinatorially with AZA improved the functionality of dysplastic cells (Figure E). Additionally, dysplastic cells were particularly sensitive to the inhibition of the mTOR pathway. To trace the fate of dysplastic cells as patients undergo AZA therapy, and thereby understand the basis of eventual relapse in responders, we performed whole exome sequencing of all patients (Figure F). Using the mutations as "molecular barcodes", we deduced the clonal architecture in each individual and observed the clonal evolution that occurred in response to AZA treatment. Combined with genotyping of CFU colonies grown in vitro, we have discovered that clonal haematopoiesis originating from resistant multipotent cells bearing mutations persists even upon complete response and forms the basis for eventual relapse (Figure G). Conclusions: Our findings, across independent cohorts and relevant to both MDS and CMML, have immediate clinical utility not simply to prospectively identify AZA non-responders but also by suggesting combinatorial therapies that could improve response. Finally, elucidating the in vivo effects of AZA therapy lay the foundation for developing more durable treatments. Figure 1. Figure 1. Disclosures Kulasekararaj: Alexion: Consultancy. Lynch:Celgene: Employment, Equity Ownership. Campbell:14M genomics: Other: Co-founder and consultant.

Description: Key Points The ERG stem cell enhancer is active in acute myeloid leukemia and is regulated by a heptad of transcription factors. Expression signatures derived from ERG promoter–enhancer activity and heptad expression are associated with clinical outcome.