Abstract: Background: Allogeneic hematopoietic cell transplantation is a potentially curative therapy for patients with hematological malignancies. However a fraction of patients will develop corticosteroid-refractory (SR) acute (a) and chronic (c) graft-versus-host disease (GVHD) which both cause a high mortality and impaired quality of life. Pre-clinical evidence indicates the potent anti-inflammatory properties of the JAK1/2 inhibitor ruxolitinib by modification of T cells and dendritic cells. Methods: In this retrospective analysis, 19 stem cell transplant centers in Europe and the United States reported clinical outcome data from 95 patients who had received ruxolitinib as salvage-therapy for SR-GVHD. Patients were classified as having SR-aGVHD (n=54, all grade III or IV) or SR-cGvHD (n=41, all moderate or severe). The median number of previous GVHD-therapies was 3 for both SR-aGVHD (1-7) and SR-cGvHD (1-10). The median follow-up times were 26.5 (3-106) for SR-aGVHD and 22.4 (3-135) weeks for SR-cGVHD-patients. Results: The ORR was 81.5% (44/54) in SR-aGVHD including 25 CRs (46.3%), while for SR-cGVHD the ORR was 85.4% (35/41). The median time to response was 1.5 (1-11) and 3 (1-25) weeks after initiation of ruxolitinib treatment in SR-aGVHD and SR-cGVHD, respectively. Of those patients responding to ruxolitinib, the rate of GVHD-relapse was 6.8% (3/44) and 5.7% (2/35) for SR-aGVHD and SR-cGVHD, respectively. The 6-month-survival was 79% (67.3%-90.7%,95% CI) and 97.4% (92.3%-100%,95% CI) for SR-aGVHD and SR-cGVHD, respectively. Cytopenia and CMV reactivation were observed during ruxolitinib-treatment in both SR-aGVHD (30/54, 55.6% and 18/54, 33.3%) and SR-cGVHD (7/41, 17.1% and 6/41, 14.6%) patients. Relapse of the underlying malignancy occurred in 9.3% (5/54) and 2.4% (1/41) of the patients with SR-aGVHD or SR-cGVHD, respectively. Conclusion: Ruxolitinib constitutes a promising new treatment option for SR-aGVHD and SR-cGVHD. Its activity in SR-aGVHD and SR-cGVHD should be validated in a prospective trials in both, SR-aGvHD and cGvHD. Disclosures Bertz: GILEAD Sciences: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Scheid:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bug:TEVA Oncology, Astellas: Other: Travel Grant; NordMedica, Boehringer Ingelheim, Gilead: Membership on an entity's Board of Directors or advisory committees; Celgene, Novartis: Research Funding.

Abstract: Background TP53 mutations are associated with adverse outcome of AML treated with cytarabine-based regimens. Interestingly, DNA-hypomethylating agents (HMAs) induce a higher response rate in TP53-mutated (MUT) compared to TP53 wildtype (WT) AML (Welch et al., N. Engl. J. Med. 2016, Döhner et al., Leukemia 2018). We conducted a randomized phase II trial (NCT00867672, 2x2 factorial design) asking whether the in vitro cooperativity of DAC with VPA or ATRA translates into clinical benefit. While VPA added to DAC affected neither objective response rate (ORR) nor overall survival (OS), ATRA significantly improved ORR and OS, without added toxicity (Lübbert et al., J. Clin. Oncol. 2020). Preclinical data suggest that HMAs and ATRA have cooperative effects also in TP53 MUT AML. We therefore performed a post-hoc analysis to determine the predictive impact of TP53 status. Patients and Methods Key inclusion criteria: newly diagnosed AML pts & gt;60 yr (non-M3) unfit for induction, ECOG performance status (PS) 0-2. Treatment: DAC 20 mg/m 2 day 1-5 (arms A/B/C/D), VPA p.o. from day 6 (arms B/D), ATRA p.o. day 6-28 (arms C/D) of each 28-day course. For TP53 mutation analyses, the Illumina TruSight Myeloid Sequencing Panel was used for library preparation and an Illumina MiSeq device for sequencing. Key endpoints: ORR (CR/CRi/PR, ELN 2010 criteria) and OS. Original sample size calculation of a total of 200 patients (pts) was based on the primary endpoint ORR (Lübbert et al., Haematologica 2012). ORR was analyzed with logistic regression, OS with Cox regression. Odds ratios (OR) for the effect on ORR and hazard ratios (HR) for the effect on death with 95% confidence intervals (CI) are presented in the genetic subgroups TP53 MUT and TP53 WT including tests for interactions (TFI) between treatment and TP53. These are post-hoc exploratory analyses, hence p-values have to be interpreted in a descriptive sense. Results Between 12/2011 and 2/2015, 200 pts were randomized and treated. Information on TP53 status was available for 168 of 200 pts (84%); 155 of them (92%) had died at last follow-up (June 2021). 61% of pts were aged & gt;75 years (range 61-92), ECOG PS 0/1/2: 19/62/19% (a single pt had a PS of 3); 53% had an HCT-CI & gt;3, 19% WBC & gt;30.000/µl, 30% adverse genetics (ELN 2010), 51% an antecedent hematologic disorder. TP53 aberrations were detected in 42 pts (25%), with 1 (n=27) or 2 mutations (n=12, median variant allele frequency 44%, range, 1.3-99%) in 39 pts, and TP53 deletions in 3 additional pts. The 42 pts with TP53 MUT showed a higher ORR (23.8%) than the 126 pts with TP53 WT (ORR 15.1%), with an OR of 2.04 (95% CI 0.83-4.98), p=0.12. OS (irrespective of treatment) in the TP53 MUT v WT pts was not different (HR, adjusted for treatment: 1.14 [95% CI 0.78-1.66], p=0.51; Fig. A). In both genetic groups, the addition of ATRA had a favorable effect on ORR (ATRA v no ATRA in TP53 MUT: 31.3% v 19.2%, OR 1.91 [95% CI 0.45-8.03] ; ATRA v no ATRA in TP53 WT: 18.8% v 10.5%, OR 1.98 [95% CI 0.70-5.61]), TFI p=0.97 (Fig. B). A positive effect of ATRA on OS in both genetic groups was reflected by a median OS of 6.0 v 4.5 months (ATRA v no ATRA in TP53 MUT: HR 0.75 [95% CI 0.38-1.48] ), and a median OS of 8.9 v 4.7 months (ATRA v no ATRA in TP53 WT: HR 0.58 [95% CI 0.39-0.86], all results adjusted for VPA, ECOG, HCT-CI, sLDH, Hb), TFI p=0.49 (Fig. C). VPA did not affect ORR in either of the 2 genetic groups (VPA v no VPA in TP53 MUT: 21.7% v 26.3%, OR 0.76 [95% CI 0.18-3.21] ; VPA v no VPA in TP53 WT: 16.7% v 13.3%, OR 1.34 [95% CI 0.5-3.61]), TFI p=0.53. The impact of VPA on OS differed between TP53 MUT pts (VPA v no VPA: median OS of 4.2 v 5.3 months, HR 1.31 [95% CI 0.69-2.48] , and TP53 WT pts (VPA v no VPA: median OS of 8.4 v 4.8 months, HR 0.67 [95% CI 0.46-0.99], all results adjusted for ATRA, ECOG, HCT-CI, sLDH, Hb; TFI p=0.08, Fig. C). Conclusions Our results confirm the reported higher response rate to DAC in pts with TP53 MUT compared to TP53 WT; the addition of ATRA led to a higher ORR. Improved OS with ATRA was observed particularly in TP53 WT pts. In contrast, VPA did not affect the ORR in either genetic group; TP53 WT pts may benefit from VPA regarding OS. Our exploratory post-hoc results need confirmation in other trials, e.g. in the DECIDER-2 study (adding ATRA or placebo to the recently approved dual treatment of a HMA combined with venetoclax). Cooperative effects of HMAs and retinoids deserve a deeper mechanistic understanding, which may have implications not only for AML but also for other malignancies with impaired TP53. Figure 1 Figure 1. Disclosures Becker: BMS: Honoraria; Pierre Fabre Pharma: Honoraria; Servier: Honoraria; MSD: Honoraria; Novartis: Honoraria. Crysandt: Incyte: Honoraria; Pfizer: Membership on an entity's Board of Directors or advisory committees. Thol: Abbvie: Honoraria; Pfizer: Honoraria; Astellas: Honoraria; Novartis: Honoraria; BMS/Celgene: Honoraria, Research Funding; Jazz: Honoraria. Heuser: Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolremo: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Research Funding; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; BergenBio: Research Funding; BMS/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bayer Pharma AG: Research Funding; Astellas: Research Funding. Goetze: Abbvie: Other: Advisory Board; BMS/Celgene: Other: Advisory Board, Research Funding. Schlenk: Agios: Honoraria; Astellas: Honoraria, Research Funding, Speakers Bureau; Celgene: Honoraria; Daiichi Sankyo: Honoraria, Research Funding; Abbvie: Honoraria; Hexal: Honoraria; Neovio Biotech: Honoraria; Novartis: Honoraria; Pfizer: Honoraria, Research Funding, Speakers Bureau; Roche: Honoraria, Research Funding; AstraZeneca: Research Funding; Boehringer Ingelheim: Research Funding. Salih: Synimmune GmbH: Honoraria; Pfizer: Honoraria; Novartis: Honoraria; Celgene: Honoraria; BMS: Honoraria. Schittenhelm: Takeda: Other: advisory board; Astellas: Other: advisory board; BMS: Other: advisory board; University of Tuebingen: Patents & Royalties: patent for ASPP2k. Müller-Tidow: Pfizer: Research Funding; Janssen: Consultancy, Research Funding; Bioline: Research Funding. Germing: Novartis: Honoraria, Research Funding; Jazz Pharmaceuticals: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria, Other: advisory activity, Research Funding. Giagounidis: Novartis: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Wäsch: Amgen: Consultancy, Honoraria; Pfizer: Consultancy; Sanofi: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Novartis: Consultancy; BMS/Celgene: Consultancy; Gilead: Consultancy. Döhner: Jazz Roche: Consultancy, Honoraria; Celgene/BMS: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Honoraria, Other: Advisory Board; Agios and Astex: Research Funding; Abbvie: Consultancy, Honoraria; Janssen: Honoraria, Other: Advisory Board; Astellas: Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Ganser: Novartis: Honoraria; Jazz Pharmaceuticals: Honoraria; Celgene: Honoraria. Döhner: Astellas: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding; Oxford Biomedicals: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Research Funding; Helsinn: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Berlin-Chemie: Consultancy, Honoraria; Astex: Consultancy, Honoraria; Agios: Consultancy, Honoraria, Research Funding; Ulm University Hospital: Current Employment; Jazz: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Roche: Consultancy, Honoraria; GEMoaB: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Pfizer: Research Funding. Hackanson: Roche: Consultancy, Honoraria; Astra Zeneca: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Boehringer-Ingelheim: Consultancy, Honoraria; MSD: Consultancy, Honoraria. Lübbert: Cheplapharm: Other: study drug (ATRA); TEVA: Other: study drug (valproic acid); Janssen: Consultancy, Other: study drug (decitabine), Research Funding; Syros: Consultancy, Honoraria; Aristopharm: Other: study drug ; Imago BioSciences: Consultancy, Other: study support with study drug; AbbVie: Consultancy, Honoraria; Astex: Consultancy, Honoraria. OffLabel Disclosure: ATRA, in non-M3 AML valproic acid, in non-M3 AML

Abstract: Background: Despite the recent approval of DNA-hypomethylating agents (HMAs) for treatment of elderly AML patients (pts) ineligible for induction, their prognosis is still poor, and rational, effective HMA-based combination treatments are under study. Histone deacetylase inhibitors (HDACi) show synergism with HMAs in vitro. ATRA - as single agent clinically ineffective in non-M3 AML - in combination with HMAs also shows in vitro synergistic antileukemic activity in non-M3 AML cells. We previously conducted a non-randomized phase II trial in elderly non-fit AML pts with DAC (3-dy schedule), given alone or combined with ATRA (45 mg/m2 dy 4-28, only during course 2), with encouraging results (Lübbert et al., Haematologica 2012). We now expanded this approach to a 4-arm randomized phase II study (2x2 factorial design) asking whether the addition of either VPA (HDACi activity) or ATRA or both to DAC as first-line treatment of elderly AML pts might improve the effect of DAC monotherapy (NCT00867672). Patients and Methods: Inclusion criteria: newly diagnosed pts 〉 60 yr unfit for induction (reasons for treatment decision prospectively captured) with non-M3 AML (WHO, de novo or after antecedent hematologic disorder [AHD], therapy-associated [t] AML), ECOG performance status (PS) 0-2. Pts with 〉 30,000 WBC/µl were to receive a short course of hydroxyurea. Treatment: DAC 20 mg/m2 dy 1-5 (treatment arms A/B/C/D), VPA p.o. continuously (target serum levels: 50-110 mg/l) from dy 6 (arms B/D), ATRA p.o. dy 6-28 (arms C/D) of each 28-dy course (repeated until relapse/progression, prohibitive toxicity, withdrawal or death). Key endpoints: objective response rate (ORR): CR/CRi/PR (ELN criteria), overall survival (OS). Sample size calculation was based on the primary endpoint ORR, assuming an ORR of 25% in arm A (Lübbert et al., Haematologica 2012). For a power of 80% (test in this phase II study at 1-sided alpha=0.1) for an increase of ORR to 40% with VPA or ATRA, 176 pts were necessary, planned sample size 200. Efficacy analyses were performed in the intention-to-treat (ITT) population including all randomized pts for whom treatment was started. VPA was investigated by comparing arms B+D vs arms A+C, ATRA by comparing arms C+D vs arms A+B. ORR was analyzed with logistic regression, OS with Cox regression, without adjustment for prognostic factors. Odds ratios (OR) for the effect on ORR and hazard ratios (HR) for the effect on death with 95% confidence intervals (CI), and two-sided p values of the tests of no treatment effect are presented. Central hematopathological review by an independent morphologist was conducted in a blinded fashion as to treatment arms. Results: Between 12/2011 and 2/2015, 204 pts were randomized (4 were excluded from the analysis because no treatment was administered). Median age: 76 yrs (interquartile range 72-79, range 61-92), ECOG PS 0/1/2-3: 19/61/20%: 52% had an HCT-CI 〉 3, 16.5% WBC 〉 30.000/µl, 31.5% poor cytogenetics (ELN), 51% had an AHD, 13.5% tAML (characteristics overall balanced across all 4 treatment arms). A median of 3 DAC courses were administered (per arm: 2/3/5.5/4), however 53 pts (26.5%), who were older, with reduced PS and a higher HCT-CI compared to the other 147 pts, received only a single course. The ORR (usually achieved only after 〉 3 courses) was 17.5%, median OS 6.2 mths (arm A: 8.5% and 4.8 CI [2.8,7.6] mths, arm B: 17.5% and 6.1 CI [3.7,7.2] mths, arm C: 26.1% and 8.4 CI [4.0,14.0] mths, arm D: 18% and 7.7 CI [4.6,11.2] mths, respectively). Effect on ORR of VPA vs no VPA (17.8 vs 17.2%): OR 1.06, CI [0.51,2.21], p=0.88; of ATRA vs no ATRA (21.9 vs 13.5%): OR 1.80, CI [0.86,3.79] , p=0.12. Effect on OS of VPA vs no VPA (6.2 vs 6.4 mths median OS): HR 0.94, CI [0.70,1.28], p=0.70; of ATRA vs no ATRA (8.2 vs 5.1 months median OS): HR 0.65, CI [0.48,0.88] , p=0.006 (after adjustment for PS, HCT-CI, WBC, LDH: HR 0.59, CI [0.43,0.82], p=0.002). Improved survival with ATRA was also seen in pts with poor cytogenetics. Toxicities (predominantly hematologic) did not show relevant differences between the 4 treatment arms. Conclusions: Based on this ITT analysis of a randomized trial, the addition of ATRA to standard-dose DAC resulted in a higher ORR and in a clinically relevant extension of OS, without additional (hematologic and non-hematologic) toxicity. In contrast, the addition of VPA did not affect ORR or OS. Disclosures Lübbert: Celgene: Other: Travel Funding; Janssen-Cilag: Other: Travel Funding, Research Funding; Ratiopharm: Other: Study drug valproic acid. Schlenk:Pfizer: Honoraria, Research Funding; Amgen: Research Funding. Heuser:Pfizer: Research Funding; Tetralogic: Research Funding; BerGenBio: Research Funding; Karyopharm Therapeutics Inc: Research Funding; Bayer Pharma AG: Research Funding; Celgene: Honoraria; Novartis: Consultancy, Research Funding. Bug:Janssen: Other: Travel Grant; Astellas: Other: Travel Grant; Teva Oncology: Other: Travel Grant; Novartis: Honoraria, Research Funding; Celgene: Honoraria, Other: Travel Grant; Nord Medica: Consultancy. Giagounidis:Celgene Corporation: Consultancy. Brugger:Astrazeneca: Employment. Niederwieser:Amgen: Speakers Bureau; Novartis Oncology Europe: Research Funding, Speakers Bureau.

Abstract: Introduction: Treatment of acute myeloid leukemia (AML) in elderly patients remains challenging. Low-dose DNA hypomethylating agents are a therapeutic option in myelodysplastic syndromes and AML. However, the mechanism of action of hypomethylating agents and the role of induction of DNA hypomethylation in the clinical response is still unclear. To unravel the in vivoeffects of sequential cycles of decitabine, we set out to characterize methylomes of leukemic blasts, T cells (presumably not part of the malignant clone) and granulocytes before and during treatment of AML patients enrolled in the randomized phase II DECIDER clinical trial (NCT00867672). We developed a statistical model for longitudinal data analysis to identify the strongest hypomethylation response. Methods: Peripheral blood mononuclear cells (PBMC) from AML patients were collected before and during therapy (i.v. 20 mg/m2 decitabine for 5 days, with or without subsequent oral drug add-on). Leukemic blasts and T-cells were isolated using automatic magnetic sorting of cells (autoMACS) labelled with anti-human CD34, CD117 and CD3 MACS microbeads (Miltenyi Biotec), respectively. Granulocytes were isolated using dextran sedimentation. Cell type specific genome-wide DNA methylation profiles were obtained using Infinium Human Methylation 450 BeadChip arrays. Data were analyzed using R packages RnBeads applying beta mixture quantile dilation for normalization (Teschendorff et al. Bioinformatics, 29:189–196, 2013) and a modified version of NHMMfdr for multiple testing. Results: Peripheral blood blasts (median purity: 92%) were isolated from 20 patients, and T cells (median purity: 94%) from 26 patients before treatment and on days 4 and/or 8 and 15 of treatment cycle 1. From 10 patients, blasts and T cells were also collected during and/or after cycle 2. In total, until now 127 methylomes (46 blasts, 47 T cells, 34 granulocytes) were generated and used for mathematical modelling. Since the trial is still recruiting, genome-wide methylation was interpreted blinded to all clinical data including drug add-on (ATRA, valproic acid). First, the methylation dynamics of each individual CpG site described by a specified summary statistics were identified. Then, inter-probe distance and CpG annotation were incorporated to explain the dependence structure between CpG sites. In order to control the false discovery rate (FDR), we adapted a method proposed for differential DNA methylation (Kuan & Chiang, Biometrics 68: 774–783, 2012). The summary statistics for each CpG site were modelled to follow a non–homogeneous hidden Markov model. Statistical testing was validated by simulations revealing a very high discriminative power for affected CpGs even with very low methylation dynamics. Applying the model to blasts and T cells, extensive differences in the in vivomethylation changes became apparent. In blasts, 13% of CpG (59,920 CpGs of total 460,343 CpGs) showed significant DNA hypomethylation (Δβ 〉 0.1, FDR 〈 0.05) shared between patients by day 8, 75.8% of which (45,428 CpGs) were at least partially remethylated by day 15. Out of the 59,920 CpGs hypomethylated by day 8, 21.2% were located in promoters, 50.1% in gene bodies and 28.7% in intergenic regions. In contrast, in T cells only 2 CpGs out of 460,343 CpGs were significantly hypomethylated. This low number is partially due to the higher inter-individual variance as compared to leukemic blasts. Increases in DNA methylation across all patients were very rare, with only 38 CpGs consistently and significantly hypermethylated in blasts and none in T cells. Methylome analysis in granulocytes is currently ongoing. Conclusions: Our mathematical model revealed significant DNA hypomethylation by day 8, with striking remethylation by day 15 from start of decitabine treatment in AML blasts in vivo. Most of the hypomethylated CpGs resided in non-promoter regions. In contrast, T-cells were much less affected, which might be due to the low cell division rate and the fact that they are non-malignant cells. This model will hopefully allow determination whether the effects of decitabine are targeted or random, by including sequential samples from later treatment cycles. Unblinding of the patients' clinical data will reveal potential biomarkers of response to epigenetic therapy. Disclosures Lübbert: Ratiopharm: received study drug valproic acid, received study drug valproic acid Other; Johnson & Johnson: Honoraria, Membership on an entity's Board of Directors or advisory committees, received study drug decitabine Other.

Abstract: Background: The therapeutic effect of DNA-hypomethylating agents (HMAs) in AML/MDS is discussed to be via its effects on aberrant gene silencing by reactivation (e.g. through promoter hypomethylation). While this has been broadly studied in cell line models, only very few studies have addressed the global effects of HMAs in primary blasts serially isolated from AML patients (pts) undergoing HMA treatment (Claus et al., Leuk. Res. 2013, Klco et al., Blood 2013, Welch et al., N. Engl. J. Med. 2016). We therefore conducted prospective serial methylome and transcriptome analyses on AML blasts from pts of the DECIDER trial (NCT00867672), hypothesizing that both random and non-random effects of the HMA may be observed in vivo. Patients, Materials and Methods: Of a total of 200 newly diagnosed AML pts included into the DECIDER randomized phase II trial (Decitabine/DAC treatment, 20 mg/m2 intravenous 1-hour infusion over 5 days, with add-on drugs Valproic acid and/or ATRA added at day 6; Grishina et al., BMC Cancer 2015), serially obtained peripheral blood (pb) samples from a total of 28 pts yielded sufficient numbers of purified blasts at 3 timepoints (days 0, 8 and 15 from DAC treatment start) to allow a "triplet analysis" of these matched samples. Baseline pt characteristics: median WBC 11,900/µl (range 1,200 - 53,800), median pb blasts 37.5% (range 1% - 93%). Blasts were sorted using anti-CD34, CD117 MACS microbeads, respectively (median purity 〉 90%). Methylomes were obtained using Infinium Human Methylation 450 BeadChip arrays (Illumina). For expression analyses, GeneChip Human Gene 2.0 ST arrays were used. A linear-model based approach was used to identify the differentially methylated CpGs and expressed genes post vs. prior to treatment. Results: To address in vivo methylation changes occurring at day 8 and 15 from DAC treatment start, complete "triplets" of DNA preparations (thus from purified pb blasts of all 3 time points) were interrogated. Significant hypomethylation at day 8 (Δβ 〈 -0.1, FDR 〈 0.05) was achieved for 69,384 CpGs (15% of all 456,789 CpGs). Of these, 536 CpGs (representing 227 genes) became hypomethylated in all 28 pts (Fig. 1A, black curve). By Gene Ontology (GO) terms, there was strong enrichment for genes involved in adhesion; this included a number of genes with proven or putative tumor suppressor function, several of them known to be hypermethylated in AML or other malignancies, such as CDH13, FAT1 and CYP26B1. By day 15, 40129 CpGs (58% of the 69,384 CpGs) became at least partially remethylated (Fig. 2). The median methylation of all CpGs was thus reduced from 0.91 pre-treatment to 0.76 at day 8, and increased to 0.81 at day 15. We next asked whether the CpG methylation changes at different timepoints were random or specific. Compared to 100 randomly chosen sets of CpGs (positive controls for non-specific methylation changes), the number of CpGs commonly hypomethylated (Δβ 〈 -0.1) at day 8 (vs. day 0) across up to 28 pts was much higher, as shown in Fig. 1A (p=3.78e-42), indicating non-random hypomethylation. Similar results were obtained for CpGs hypomethylated at day 15 (vs. day 0, Fig. 1B, p=2.61e-25). In contrast, CpGs remethylated at day 15 (vs. day 8) were similar in numbers to the random controls (Fig. 1C, p=0.42), thus indicating random remethylation. We next investigated whether hypomethylation at day 8 was associated with changes in gene expression. For 12 of the 28 pts, blast RNA yield was sufficient to allow for combined methylation and expression studies both prior to treatment and at day 8. Regarding expression induction upon HMA treatment, a total of 870 genes showed a significant inverse correlation between expression and DNA methylation, thus being both induced and hypomethylated (with, however, limited overall fold changes). GO analysis revealed enrichment for immune response genes. Conclusions: In our study, a subset of genes was specifically targeted by hypomethylation in all pts, arguing against a completely random effect of this treatment on the methylome. Only a limited number of hypomethylating events was associated with gene reactivation. A better understanding of hypo- and remethylation kinetics in vivo may aid in schedule optimization of HMA therapy. Correlative studies on hypomethylation kinetics and treatment outcome in the DECIDER trial are therefore ongoing, as well as serial methylome analyses in the EORTC trial AML21 ("inDACtion vs. induction", NCT02172872). Disclosures Salih: Several patent applications: Patents & Royalties: e.g. EP3064507A1. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Döhner:Jazz: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Jazz: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Bristol Myers Squibb: Research Funding; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; AROG Pharmaceuticals: Research Funding; Astellas: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Astellas: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Pfizer: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Pfizer: Research Funding; Seattle Genetics: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria. Lübbert:Cheplapharm: Other: Study drug; Janssen: Honoraria, Research Funding; TEVA: Other: Study drug; Celgene: Other: Travel Support.

Abstract: Mitochondrial creatine kinase (Mt-CK) is a major determinant of cardiac energetic status and is down-regulated in chronic heart failure, which may contribute to disease progression. We hypothesised that cardiomyocyte-specific overexpression of Mt-CK would mitigate against these changes and thereby preserve cardiac function. Male Mt-CK overexpressing mice (OE) and WT littermates were subjected to transverse aortic constriction (TAC) or sham surgery and assessed by echocardiography at 0, 3 and 6 weeks alongside a final LV haemodynamic assessment. Regardless of genotype, TAC mice developed progressive LV hypertrophy, dilatation and contractile dysfunction commensurate with pressure overload-induced chronic heart failure. There was a trend for improved survival in OE-TAC mice (90% vs 73%, P  = 0.08), however, OE-TAC mice exhibited greater LV dilatation compared to WT and no functional parameters were significantly different under baseline conditions or during dobutamine stress test. CK activity was 37% higher in OE-sham versus WT-sham hearts and reduced in both TAC groups, but was maintained above normal values in the OE-TAC hearts. A separate cohort of mice received in vivo cardiac 31 P-MRS to measure high-energy phosphates. There was no difference in the ratio of phosphocreatine-to-ATP in the sham mice, however, PCr/ATP was reduced in WT-TAC but preserved in OE-TAC (1.04 ± 0.10 vs 2.04 ± 0.22; P  = 0.007). In conclusion, overexpression of Mt-CK activity prevented the changes in cardiac energetics that are considered hallmarks of a failing heart. This had a positive effect on early survival but was not associated with improved LV remodelling or function during the development of chronic heart failure.