Abstract: Abstract 1600 Poster Board I-626 Background The V-ets erythroblastosis virus E26 (ETS) oncogene family is one of the largest families of transcription factors. ETS transcription factors are characterized by two major functional domains, a transcription domain and an evolutionarily highly conserved DNA-binding domain, also known as ETS domain that mediates binding to purine-rich DNA sequences. Most ETS family proteins are nuclear targets for activation of the Ras-MAP kinase signalling pathway. Therefore, they play a significant role in regulating cellular functions such as cell growth, apoptosis, development and differentiation. ETS transcription factors have been implicated in leukemia by chromosomal rearrangement, and more commonly by gene amplification and/or overexpression. Moreover, overexpression of ERG was shown to be an adverse predictor for clinical outcome in AML with normal cytogenetics (CN). In our recent study on complex karyotype AML, array-CGH (comparative genomic hybridization) analysis identified small genomic amplifications affecting ERG/ETS2 in 21q22 and ETS1/FLI1 in 11q23 in about 10% of the cases. Correlation with global gene expression profiling showed that ERG and ETS2 as well as ETS1 and FLI1 were overexpressed in these cases. Aims: To evaluate expression levels of ERG, ETS2, ETS1 and FLI1 in a large cohort of younger (16 to 60 years of age) adult CN-AML patients (pts) and their impact on clinical outcome. Methods The expression of ERG, ETS2, ETS1 and FLI1 was determined by quantitative real-time reverse transcriptase polymerase chain reaction (qPCR) assay in 343 CN-AML pts who were entered on 3 AMLSG treatment protocols (AMLHD93, AML HD98-A, AMLSG 07-04). ERG, ETS2, ETS1, and FLI1 were dichotomized into two major groups according to their expression levels. The upper quartile was chosen as the cut point and the set of patients with gene expression above were defined as Q4 group. Univariable as well as multivariable regression models were used to evaluate the influence of ERG, ETS2, ETS1 and FLI1 on induction success, event-free, relapse-free and overall survival. Multivariable analyses were stratified for AMLSG treatment protocols. Results Partial correlation analysis revealed positive correlations of expression levels between ETS2 and ERG (ρ=0.45) being the strongest, followed by ERG and FLI1 (ρ=0.4), as well as ETS1 and FLI1 (ρ=0.31). Correlation of ERG, ETS2, ETS1 and FLI1 with white blood count (WBC) revealed a significant association between high gene expression (Q4) and elevated WBC (ERG, p=0.004; ETS2, p=0.002, FLI1 p 〈 0.001), whereas high expression of ETS1 was associated with a significantly lower WBC (p 〈 0.001). Univariable as well as multivariable analyses on induction success revealed high ETS2 as an unfavourable marker (OR, 0.29, p=0.01). In univariable analysis, there was a significantly inferior relapse-free survival (RFS) and overall survival (OS) for high ERG (p=.01; p=.06, respectively) and high ETS2 (p=.002; p=.03, respectively) that was even more pronounced when both ERG Q4 and ETS2 Q4 (ERG Q4 ∩ ETS2 Q4) (p 〈 0.001; p=.001, respectively) were included as one variable and compared with the rest. In multivariable analysis for the endpoints event-free survival (EFS), RFS and OS, a significant effect was found for RFS for ERG Q4 ∩ ETS2 Q4 (p=.002); the only significant variables that consistently appeared in the model were NPM1mut, FLT3-ITDpos and WBC. In subgroup analysis for the genotypes CEBPAmut, NPM1mut/FLT3-ITDneg, and all others (NPM1mut/FLT3-ITDpos, NPM1wt/FLT3-ITDpos, NPM1wt/FLT3-ITDneg) according to the hierarchical model, ERG Q4 was associated with an inferior EFS (p=.04) and OS (p=.03) in the favorable CEBPAmut genotype and became even more significant for the variable ERG Q4 ∩ ETS2 Q4 (EFS, p=.007, RFS, p=.002; OS, p=.06, respectively). For the NPM1mut/FLT3-ITDneg subgroup, again ERG Q4 ∩ ETS2 Q4 was associated with an adverse RFS (p=.04), but not with OS (p=0.07). Conclusions In our study on a large cohort of homogenously treated CN-AML patients, ERG and ETS2 expression were highly correlated. Overexpression of both genes had a significant impact on clinical outcome of CN-AML patients. Moreover, adverse effects of high ERG and high ETS2 expression on prognosis were also shown for the genetic AML subgroups CEBPAmut and NPM1mut/FLT3-ITDneg. Disclosures No relevant conflicts of interest to declare.

Abstract: Background Overall survival (OS) in acute myeloid leukemia (AML) treated with intensive chemotherapy has improved over the last 20 year especially in younger adults (18-60 years) but still remains poor in older patients ( 〉 60 years) (Döhner et al. Blood 2010). The German-Austrian AMLSG performed controlled prospective treatment trials since 1993 starting with a risk-adapted approach (phase I, 1993-1997), followed by randomized and risk-adapted treatment strategies based on cytogenetic risk groups (phase II, 1997-2002); since 2003 addition of differentiating agents and HiDAC inhibitors to intensive induction therapy was evaluated (phase III, 2003-2007). Of note, until 2007 younger and older patients ( 〉 60 years) were treated in separate protocols with significantly lower dosages of chemotherapy in older patients. Starting from 2008, risk-adapted therapies were replaced successively by a genotype-adapted approach and the artificial age cut-off at 60 years was abandoned (phase IV, 2008-2012). Aims To evaluate the outcome of adult AML patients within the different time periods. Methods The study included 4705 intensively treated adults (younger, n=3546; older, n=1159) with newly diagnosed AML enrolled on 11 AMLSG treatment trials between 1993 and 2012. Patients with acute promyelocytic leukemia were excluded. All patients received intensive induction and consolidation therapy. Analyzed outcome variables were first complete remission rates (CR1), relapse-free survival (RFS), survival after relapse (SAR) and OS. Analyses were performed according to age groups (18-60 vs. 〉 60 yrs). In younger patients comparisons were performed for the 4 treatment phases (I-IV), whereas for older patients analyses were restricted to phase II-IV. Results In younger patients CR rates did not improve over time (1993-2013) and varied between 72% and 77% (p=0.12), whereas early and hypoplastic (ED/HD) death rates significantly declined from 10% to 5% (p=0.0001). In older patients CR rates significantly improved over time from 44% to 50% between 1998 and 2007 to 67% after 2008 (p 〈 0.0001); ED/HD rates gradually declined from 12% to 8%, but the difference was not statistically significant (p=0.17). The proportion of younger patients receiving an allogeneic hematopoietic stem cell transplantation (alloHSCT) increased from 30% (15% in CR1) in phase I to 58% (29% in CR1) in phase III and remained there in phase IV with 53% (26% CR1), whereas the proportion of patients receiving an autologous HSCT constantly decreased from maximally 16% (15% in CR1) in phase II to 0.4% (0.2% in CR1) in phase IV; the proportion of older patients receiving an alloHSCT steadily increased from 4% (2% CR1) in phase II to 21% (12% CR1) in phase IV; autoHSCT was rarely performed. OS at 4 years in both age groups significantly improved (p 〈 0.0001, each) from 41% to 56% and from 10% to 23% in younger and older patients, respectively. This beneficial effect on OS over time in younger patients was due to a better RFS (p=0.01) and SAR (p 〈 0.0001), whereas in older patients no improvement in RFS (p=0.20) and only in trend for SAR (p=0.07) was noted. In cytogenetically high-risk patients, OS in younger (p=0.001) and in older (p=0.007) patients got better; in older patients mainly driven by increase in CR rates (p=0.001) and in younger patients by an improvement in RFS (p=0.02) and SAR (p=0.05). Nearly the same pattern was identified for cytogenetically intermediate risk patients with a better OS in younger (p 〈 0.0001) and older patients (p=0.01) due to higher CR rates in older patients (p 〈 0.0001), no improvement in RFS in both age groups and a significantly better SAR in younger patients (p=0.0002). In contrast, in low risk patients improvement in OS was only present in older patients (p=0.02), due to a better RFS in older patients (p=0.02) but without any progress in younger patients. Furthermore we performed two subgroup analyses in intermediate risk patients. In the subgroup of patients characterized by the genotype NPM1-mut/FLT3-ITDneg a significant better OS was present only in younger patients (p=0.03); in FLT3-ITD positive AML a better OS was seen in younger patients (p 〈 0.0001) due to a better RFS (p=0.05) and SAR (p=0.01). Conclusions Based on the German-Austrian AMLSG experience the prognosis in younger and older AML patients has improved over time. In older patients this is mainly a result of higher CR rates and in younger patients of better RFS and SAR. Disclosures: Schlenk: Celgene: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Chugai: Research Funding; Amgen: Research Funding; Novartis: Research Funding; Ambit: Honoraria. Off Label Use: Pomalidomide in Myelofibrosis. Greil:Novartis: Honoraria, Research Funding.

Abstract: Background: Internal tandem duplications (ITD) in the receptor tyrosine kinase FLT3 occur in roughly 25% of younger adult patients (pts) with acute myeloid leukemia (AML). The multi-targeted kinase inhibitor midostaurin combined with intensive chemotherapy has shown activity against AML with FLT3 mutations. However, toxicity and potential drug-drug interactions with strong CYP3A4 inhibitors such as posaconazole may necessitate dose reduction. Aims: To evaluate the impact of age and midostaurin dose-adaptation after intensive induction chemotherapy on response and outcome in AML with FLT3-ITD within the AMLSG 16-10 trial (NCT01477606). Methods: The study included adult pts (age 18-70 years (yrs)) with newly diagnosed FLT3-ITD positive AML enrolled in the ongoing single-arm phase-II AMLSG 16-10 trial. Pts with acute promyelocytic leukemia were not eligible. The presence of FLT3-ITD was analyzed within our diagnostic study AMLSG-BiO (NCT01252485) by Genescan-based DNA fragment-length analysis. Induction therapy consisted of daunorubicin (60 mg/m², d1-3) and cytarabine (200 mg/m², continuously, d1-7); midostaurin 50 mg bid was applied from day 8 until 48h before start of the next treatment cycle. A second cycle was allowed in case of partial remission (PR). For consolidation therapy, pts proceeded to allogeneic hematopoietic-cell transplantation (HCT) as first priority; if alloHCT was not feasible, pts received three cycles of age-adapted high-dose cytarabine (HDAC) in combination with midostaurin starting on day 6. In all pts one-year maintenance therapy with midostaurin was intended. The first patient entered the study in June 2012 and in April 2014, after recruitment of n=147 pts, the study was amended including a sample size increase to 284 pts and a dose reduction to 12.5% of the initial dose of midostaurin in case of co-medication with strong CYP3A4 inhibitors (e.g. posaconazole). This report focuses on age and the comparison between the first (n=147) and the second cohort (n=137) of the study in terms midostaurin dose-adaptation. Results: Patient characteristics were as follows: median age 54 yrs (range, 18-70; younger, 68% 〈 60 yrs; older, 32% ≥ 60 yrs); median white cell count 44.7G/l (range 1.1-1543 G/l); karyotype, n=161 normal, n=16 high-risk according to ELN recommendations; mutated NPM1 n=174 (59%). Data on response to first induction therapy were available in 277 pts; complete remission (CR) including CR with incomplete hematological recovery (CRi) 60%, PR 20%, refractory disease (RD) 15%, and death 5%. A second induction cycle was given in 54 pts. Overall response (CR/CRi) after induction therapy was 76% (76%, younger; 76%, older) and death 6% (4%, younger; 10% older). The dose of midostaurin during first induction therapy was reduced in 53% and 71% of patients in cohort-1 and cohort-2, respectively. Reasons for dose reduction were in 58% and 49% toxicity, and in 9% and 23% co-medication in cohort-1 and cohort-2, respectively. No difference in response to induction therapy was noted between cohorts (p=0.81). Median follow-up was 18 months. Overall 146 pts received an alloHCT, 128 in first CR (n=94 younger, n=34 older; n=92 from a matched unrelated and n=36 from a matched related donor). In pts receiving an alloHCT within the protocol in median two chemotherapy cycles were applied before transplant (range 1-4). The cumulative incidence of relapse (CIR) and death after transplant were 13% (SE 3.2%) and 16% (SE 3.5%) without differences (p=0.97, p=0.41, respectively) between younger and older patients. So far maintenance therapy was started in 86 pts, 61 pts after alloHCT and 25 pts after HDAC. Fifty-five adverse events 3°/4° were reported being attributed to midostaurin; cytopenias after alloHCT were the most frequent (29%). CIR in patients starting maintenance therapy was 20% one year after start of maintenance without difference between alloHCT and HiDAC (p=0.99). In addition, no difference in CIR was identified in patients after consolidation with alloHCT or HDAC according to dose reduction of midostaurin during first induction therapy (p=0.43, p=0.98, respectively). Median overall survival was 25 months (younger, 26 months; older 23 months; p=0.15). Conclusions: The addition of midostaurin to intensive induction therapy and as maintenance after alloHCT or HDAC is feasible and effective without an impact of age and dose adaptation on outcome. Disclosures Schlenk: Amgen: Research Funding; Pfizer: Honoraria, Research Funding. Fiedler:GSO: Other: Travel; Pfizer: Research Funding; Kolltan: Research Funding; Amgen: Consultancy, Other: Travel, Patents & Royalties, Research Funding; Gilead: Other: Travel; Ariad/Incyte: Consultancy; Novartis: Consultancy; Teva: Other: Travel. Lübbert:Celgene: Other: Travel Funding; Janssen-Cilag: Other: Travel Funding, Research Funding; Ratiopharm: Other: Study drug valproic acid. Greil:Janssen-Cilag: Honoraria; Genentech: Honoraria, Research Funding; Mundipharma: Honoraria, Research Funding; Merck: Honoraria; AstraZeneca: Honoraria; Boehringer-Ingelheim: Honoraria; GSK: Research Funding; Ratiopharm: Research Funding; Cephalon: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Honoraria; Bristol-Myers-Squibb: Consultancy, Honoraria; Pfizer: Honoraria, Research Funding; Roche: Honoraria, Research Funding; Sanofi Aventis: Honoraria; Eisai: Honoraria; Amgen: Honoraria, Research Funding. Greiner:BMS: Research Funding. Paschka:ASTEX Pharmaceuticals: Consultancy; Novartis: Consultancy; Medupdate GmbH: Honoraria; Bristol-Myers Squibb: Honoraria; Pfizer Pharma GmbH: Honoraria; Celgene: Honoraria. Heuser:Bayer Pharma AG: Research Funding; Karyopharm Therapeutics Inc: Research Funding; Novartis: Consultancy, Research Funding; Celgene: Honoraria; Pfizer: Research Funding; BerGenBio: Research Funding; Tetralogic: Research Funding.

Abstract: Background: Measurable residual disease (MRD), as determined by quantitation of Nucleophosmin 1-mutated (NPM1mut) transcript levels (TL), provides significant prognostic information independent of other risk factors in patients (pts) with acute myeloid leukemia (AML). This is also addressed by the 2017 European LeukemiaNet (ELN) risk stratification system, which recommends taking into account results from MRD monitoring when selecting the appropriate post-remission therapy. Furthermore, MRD monitoring provides a powerful tool to evaluate treatment effects within clinical trials investigating novel therapies. Aims: To determine the impact of the anti-CD33 immunotoxin Gemtuzumab-Ozogamicin (GO) on kinetics of NPM1mut TL in pts with newly diagnosed NPM1mut AML [18 to 82 years (yrs), median age 58 yrs] enrolled in our randomized Phase III AMLSG 09-09 study (NCT00893399). In this study GO was randomized (1:1) to standard chemotherapy plus ATRA. Patients and Methods: In total, 588 evaluable pts were enrolled in the clinical AMLSG 09-09 study. Standard treatment comprised two cycles of induction therapy with A-ICE (ATRA, idarubicin, cytarabine, etoposide; arm A) followed by three consolidation cycles of high-dose cytarabine (n=371, 63%) or allogeneic hematopoietic cell transplantation (n=42, 8%). In the investigational arm (arm B), GO (3 mg/m²) was given at d1 of each induction and in the first consolidation cycle. 296 pts were randomized to arm A and 292 pts to arm B. For this correlative study, outcome analysis was restricted to the clinical endpoint cumulative incidence of relapse (CIR) due to study protocol requirements allowing overall survival analysis to be performed only two years after the last pt had been enrolled. MRD monitoring was performed in a total 503 pts for whom at least one bone marrow (BM) sample was available using RQ-PCR technique; the median follow-up (FU) of the 503 pts was 2.8 yrs. NPM1mut TL (ratio of NPM1mut/ABL1 transcripts x 104) were determined by RQ-PCR (sensitivity 10-5 to 10-6). Results: In total, 3711 BM samples were analyzed (at diagnosis, n=415; during treatment, n=1765; during FU, n=1531). Both study arms were well balanced with regard to pts characteristics and pretreatment NPM1mut TL. First, we evaluated the impact of GO on kinetics of NPM1mut TL during treatment. After the first induction cycle, median NPM1mut TL were significantly lower in the investigational arm (p=.001) and this was true for all subsequent treatment cycles [after induction II (p=.008), consolidation I (p 〈 .001), consolidation II (p=.006), consolidation III (p=.009)]. Next, we evaluated treatment effects on NPM1mut TL after two cycles of induction therapy in pts in complete remission (CR, n=378). At this time point, there was no difference in the proportion of pts achieving RQ-PCR negativity (RQ-PCRneg) [arm A 15% (28/192), vs arm B 17% (32/186); p=.57] between the two treatment arms. However, treatment according to investigational arm B with GO was associated with a significantly lower CIR rate (CIR at 4 yrs: arm B 29% vs arm A 45%, p=.02). In multivariate analysis randomization to arm B revealed as an independent prognostic factor for remission duration (HR 0.63, p=.018). At the end of treatment (EOT, n=288 pts in CR) the proportion of pts achieving RQ-PCRneg was significantly higher (55% vs 41%; p=.02) in the investigational arm; pts treated in arm B had a significantly lower CIR rate compared to arm A (CIR at 4 yrs: arm B 29% vs arm A 45%, p=.04). Conclusion: In our randomized Phase III AMLSG 09-09 study, the addition of GO to intensive chemotherapy plus ATRA was associated with a significantly better reduction of NPM1mut TL after each treatment cycle. This better clearance translated into a significantly lower CIR in the investigational arm with GO. Disclosures Paschka: Otsuka: Membership on an entity's Board of Directors or advisory committees; Bristol-Meyers Squibb: Other: Travel support, Speakers Bureau; Jazz: Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees; Sunesis: Membership on an entity's Board of Directors or advisory committees; Amgen: Other: Travel support; Janssen: Other: Travel support; Celgene: Membership on an entity's Board of Directors or advisory committees, Other: Travel support, Speakers Bureau; Astex: Membership on an entity's Board of Directors or advisory committees; Agios: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees, Travel support; Takeda: Other: Travel support. Krönke:Celgene: Honoraria. Fiedler:Amgen: Other: support for meetíng attendance; GSO: Other: support for meeting attendance; Teva: Other: support for meeting attendance; Gilead: Other: support for meeting attendance; JAZZ Pharmaceuticals: Other: support for meeting attendance; ARIAD/Incyte: Membership on an entity's Board of Directors or advisory committees, support for meeting attendance; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Pfizer: Research Funding; Amgen: Patents & Royalties; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Daiichi Sankyo: Other: support for meeting attendance. Schroeder:Celgene: Consultancy, Honoraria, Research Funding. Lübbert:Janssen: Honoraria, Research Funding; TEVA: Other: Study drug; Cheplapharm: Other: Study drug; Celgene: Other: Travel Support. Götze:JAZZ Pharmaceuticals: Honoraria; Novartis: Honoraria; Takeda: Honoraria, Other: Travel aid ASH 2017; Celgene: Honoraria, Research Funding. Schleicher:Novartis: Membership on an entity's Board of Directors or advisory committees, Other: Investigator; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Ipsen: Membership on an entity's Board of Directors or advisory committees; Eissai: Other: Investigator; Astra Zeneca: Other: Investigator; Pfizer: Speakers Bureau; Janssen: Speakers Bureau; Celgene: Speakers Bureau. Schlenk:Pfizer: Research Funding, Speakers Bureau. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Döhner:Amgen: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Pfizer: Research Funding; Agios: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Celator: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Seattle Genetics: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; AROG Pharmaceuticals: Research Funding; Bristol Myers Squibb: Research Funding; Bristol Myers Squibb: Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Pfizer: Research Funding; Seattle Genetics: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding.

Abstract: Core-binding factor (CBF) acute myeloid leukemia (AML) encompasses AML with inv(16)(p13.1q22) and AML with t(8;21)(q22;q22.1). Despite sharing a common pathogenic mechanism involving rearrangements of the CBF transcriptional complex, there is growing evidence for considerable genotypic heterogeneity. We comprehensively characterized the mutational landscape of 350 adult CBF-AML [inv(16): n = 160, t(8;21): n = 190] performing targeted sequencing of 230 myeloid cancer-associated genes. Apart from common mutations in signaling genes, mainly NRAS, KIT, and FLT3, both CBF-AML entities demonstrated a remarkably diverse pattern with respect to the underlying cooperating molecular events, in particular in genes encoding for epigenetic modifiers and the cohesin complex. In addition, recurrent mutations in novel collaborating candidate genes such as SRCAP (5% overall) and DNM2 (6% of t(8;21) AML) were identified. Moreover, aberrations altering transcription and differentiation occurred at earlier leukemic stages and preceded mutations impairing proliferation. Lasso-penalized models revealed an inferior prognosis for t(8;21) AML, trisomy 8, as well as FLT3 and KIT exon 17 mutations, whereas NRAS and WT1 mutations conferred superior prognosis. Interestingly, clonal heterogeneity was associated with a favorable prognosis. When entering mutations by functional groups in the model, mutations in genes of the methylation group (ie, DNMT3A, TET2) had a strong negative prognostic impact.

Abstract: Background: Acute myeloid leukemias (AML) with rearrangements of core-binding factor (CBF) complex genes (CBF-AML), comprising t(8;21) and inv(16) subgroups, are considered as diseases with favorable outcome. Nevertheless, CBF-AML relapse rates remain high, with ~40% of patients (pts) relapsing after standard intensive chemotherapy. Aim: To dissect the biology of relapse in CBF-AML, we performed whole exome sequencing (WES) in a large cohort of 101 cases at the time of diagnosis and for 47 cases also at the time of relapse. Methods: All pts were treated either with standard chemotherapy or with standard chemotherapy and kinase inhibitor dasatinib within clinical trials of the German-Austrian AML Study Group (AMLSG). Using the Nextera Rapid Capture Exome kit (Illumina) we performed WES of paired diagnostic (dx), remission and relapse samples of 47 pts, namely 21 pts with t(8;21) and 26 pts with inv(16). RNAseq was performed in 18 of these pts using the Ribo Zero RNA-sequencing kit (Illumina). To better define genomic signatures related to CBF-AML relapse, we included WES data previously published by our group (Faber et al. Nat Genet 2016). This set comprised dx samples of 8 t(8;21) and 10 inv(16) pts who relapsed as well as a control group of 20 t(8;21) and 16 inv(16) CBF-AML pts, who did not experience relapse. Results: For the new cohort, WES sequencing of 47 pts was performed with a mean coverage of 127-fold. In t(8;21), we identified a median of 3.5 mutations exclusively present at dx (range: 0-8), 11.6 mutations persistent from dx to relapse (range: 4-19), and 4.0 mutations gained at relapse (range: 2-7). For the inv(16) subgroup a median of 2.0 mutations were dx specific (0-7), 6.0 mutations persisted during tumor evolution (3-26) and 2.5 were gained at relapse (0-9). As previously reported, the spectrum of genes affected by mutations showed little overlap between t(8;21) and inv(16), except for commonly affected 'signaling' genes such as KIT, RAS, FLT3 and epigenetic players such as TET2. In total, in t(8;21) we identified 94 relapse-specific mutations or mutations displaying a strong increase in variant allele frequency (VAF) at relapse, and 63 of such relapse-specific alterations in inv(16) pts. In addition to the previously reported RUNX1 and cohesin complex gene mutations showing an increase in VAF at relapse, we found recurrent novel relapse-specific mutations in LAMC3, which occurred exclusively in the t(8;21) subgroup affecting 9% of pts. In inv(16), recurrent mutations in the tumor suppressor gene WT1 occurred in 12% of pts, either acquired at relapse or already present at dx as a minor subclone. Remarkably, mutations in relapsed t(8;21) pts often affected genes involved in PI3K-AKT and in cell cycle regulation pathways. In the inv(16) relapse group, in addition to dysregulation of the MAPK signaling pathway, we found several non-recurrent mutations in genes involved in ribosomal RNA metabolism, like in PRNAD1. Conclusion: Our WES sequencing results already provide first insights into the molecular composition and mechanisms underlying relapse in CBF-AML which often affect pathways linked to proliferation, such as PI3K-AKT and MAPK signaling. While we are currently validating additional hits, updated results will be provided at the ASH meeting, which will also address combinatorial mutation patterns underlying chemotherapy resistance in t(8;21) and inv(16) positive AML. Disclosures Götze: Celgene: Research Funding. Fiedler:Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria; ARIAD/Incyte: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Other: support for meeting attendance, Patents & Royalties, Research Funding; Daiichi Sankyo: Other: support for meeting attendance; Gilead: Other: support for meeting attendance; Jazz Pharmaceuticals: Honoraria, Other: support for meeting attendance; Abbvie: Membership on an entity's Board of Directors or advisory committees; Morphosys: Consultancy, Honoraria; Celgene: Membership on an entity's Board of Directors or advisory committees. Thol:Celgene: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees. Heuser:PriME Oncology: Honoraria; Abbvie: Consultancy; Stemline Therapeutics: Consultancy; Karyopharm: Research Funding; Roche: Research Funding; Bayer: Consultancy, Research Funding; Amgen: Research Funding; BerGenBio ASA: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Janssen: Consultancy; Daiichi Sankyo: Consultancy, Research Funding; Astellas: Research Funding. Ganser:Novartis: Consultancy; Celgene: Consultancy. Paschka:Agios Pharmaceuticals: Consultancy, Speakers Bureau; Astex Pharmaceuticals: Consultancy; Astellas Pharma: Consultancy, Speakers Bureau; Celgene: Consultancy, Other: Travel, accommodations or expenses; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Otsuka: Consultancy; Pfizer: Consultancy, Speakers Bureau; Sunesis Pharmaceuticals: Consultancy; AbbVie: Other: Travel, accommodation or expenses, Speakers Bureau; Amgen: Other; Janssen Oncology: Other; BerGenBio ASA: Research Funding. Döhner:GEMoaB: Consultancy, Honoraria; AROG: Research Funding; Astellas: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Helsinn: Consultancy, Honoraria; Jazz: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding; Astex: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Pfizer: Research Funding; Oxford Biomedicals: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; AstraZeneca: Consultancy, Honoraria; Sunesis: Research Funding. Döhner:Novartis: Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Daiichi Sankyo: Honoraria; Abbvie: Consultancy; Sunesis Pharmaceuticals: Research Funding; Pfizer: Research Funding; Bristol-Myers Squibb: Research Funding; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Astex Pharmaceuticals: Consultancy; Astellas Pharma: Consultancy; Amgen: Consultancy, Research Funding; Agios: Consultancy; Roche: Consultancy; Arog: Research Funding. Bullinger:Amgen: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Hexal: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Menarini: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees.

Abstract: Activating mutations in the receptor tyrosine kinase FLT3 occur in roughly 30% of acute myeloid leukemia (AML) patients (pts), implicating FLT3 as a potential target for kinase inhibitor therapy. The multi-targeted kinase inhibitor midostaurin (PKC412) shows potent activity against FLT3 as a single agent but also in combination with intensive chemotherapy. Besides its mere presence, the allelic ratio as well as ITD insertion site within the FLT3 gene had been reported as prognostic factors in FLT3-ITD positive AML. Furthermore, pharmacokinetic analyses revealed clinically important interactions between potent CYP3A4 inhibitors, such as azoles, and midostaurin. Aims To evaluate the pharmacodynamic activity of midostaurin measured as inhibition of the degree of phosphorylated FLT3 (pFLT3) in correlation to co-medication and outcome data. Methods The study includes intensively treated adults (age 18-70 years) with newly diagnosed FLT3-ITD positive AML enrolled in the ongoing single-arm phase-II AMLSG 16-10 trial (NCT: NCT01477606). Pts with acute promyelocytic leukemia are not eligible. The presence of FLT3-ITD is analyzed by Genescan-based fragment-length analysis (allelic ratio 〉 0.05 required to be FLT3-ITD positive). Induction therapy consists of daunorubicin (60 mg/m², d1-3) and cytarabine (200 mg/m², continuously, d1-7); midostaurin 50 mg twice daily is applied from day 8 onwards until 48h before start of the next treatment cycle. For consolidation therapy, pts proceed to allogeneic hematopoietic stem cell transplantation (HSCT) as first priority; if allogeneic HSCT is not possible pts receive three cycles of age-adapted high-dose cytarabine in combination with midostaurin from day 6 onwards. In all pts maintenance therapy for one year is intended. A total sample size of n=142 is planned to show an improvement in event-free survival from 25% after 2 years to 37.5%. Plasma inhibitory activity assay (PIA) for pFLT3 is performed as previously described (Levis MJ, et al. Blood 2006; 108:3477-83). For PIA, measured time points include day 15 of induction therapy, the end of each treatment cycle and every three months during maintenance therapy. Results To date, 72 pts (median age, 54.5 years; range, 29-69 years) have been included and PIA was performed so far in 37 pts during induction therapy. Median pFLT3 inhibition after one week of midostaurin intake measured on day 15 of cycle 1 (C1D15) was 57.5% (range, 14.2-93.7%) with 2 of 31 pts showing inhibition 〉 85%. At the end of the first induction cycle (C1end), median inhibition was 60.3% (range, 0-99.8%); here, 6 of 37 pts had an inhibition 〉 85%. Co-medication with azoles was present in 7 of 23 pts at C1D15 and 13 of 28 pts at C1end. There was no significant difference in pFLT3 inhibition either on C1D15 (p=0.79) or at C1end (p=0.70) between pts on (median pFLT3 inhibition: 52.5%) or off (median pFLT3 inhibition 57.5%) azoles. Response data were available in 56 pts: complete remission (CR) was achieved in 78.5%; rates of early death and refractory disease (RD) were 9% and 12.5%, respectively. In first analyses, there was no difference in pFLT3 inhibition in pts achieving CR (n=30) as compared to those with RD (n=3; p=0.99). In contrast to our previously published data from three historical trials without a FLT3 inhibitor which showed that high allelic ratio was associated with low CR rates (Kayser S, et al. Blood 2009;114:2386-92), in the current trial CR rates remained high (81.5%) despite of a high allelic ratio above the median ( 〉 0.58). In addition, we did not see a negative prognostic impact of ITD insertion site within the tyrosine kinase domain of the FLT3 gene (p=0.99). Analyses are currently ongoing, measurement of FLT3 ligand levels and evaluation of pharmacokinetics of midostaurin are also intended. Conclusions The addition of 50 mg midostaurin twice daily to intensive induction therapy resulted in a moderate pFLT3 inhibition during induction therapy. Nonetheless, CR rates are promising, especially in pts with unfavorable FLT3-ITD characteristics. Concomitant azoles do not appear to significantly influence pFLT3 inhibitory activity of midostaurin. Disclosures: Levis: Ambit Biosciences: Consultancy. Schlenk:Ambit: Honoraria; Chugai: Research Funding; Novartis: Research Funding; Pfizer: Research Funding; Amgen: Research Funding.

Abstract: MRD assessment in t(8;21) AML allows identification of patients at high relapse risk at defined time points during treatment and follow-up. MRD− after treatment is the most favorable factor for relapse risk and survival, and serial MRD analyses define cutoffs predicting relapse.

Abstract: Monitoring of measurable residual disease (MRD) provides prognostic information in patients with Nucleophosmin1-mutated (NPM1mut) acute myeloid leukemia (AML) and represents a powerful tool to evaluate treatment effects within clinical trials. We determined NPM1mut transcript levels (TLs) by quantitative reverse-transcription polymerase chain reaction and evaluated the prognostic impact of NPM1mut MRD and the effect of gemtuzumab ozogamicin (GO) on NPM1mut TLs and the cumulative incidence of relapse (CIR) in patients with NPM1mut AML enrolled in the randomized phase 3 AMLSG 09-09 trial. A total of 3733 bone marrow (BM) samples and 3793 peripheral blood (PB) samples from 469 patients were analyzed. NPM1mut TL log10 reduction ≥ 3 and achievement of MRD negativity in BM and PB were significantly associated with a lower CIR rate, after 2 treatment cycles and at end of treatment (EOT). In multivariate analyses, MRD positivity was consistently revealed to be a poor prognostic factor in BM and PB. With regard to treatment effect, the median NPM1mut TLs were significantly lower in the GO-Arm across all treatment cycles, resulting in a significantly greater proportion of patients achieving MRD negativity at EOT (56% vs 41%; P = .01). The better reduction in NPM1mut TLs after 2 treatment cycles in MRD positive patients by the addition of GO led to a significantly lower CIR rate (4-year CIR, 29.3% vs 45.7%, P = .009). In conclusion, the addition of GO to intensive chemotherapy in NPM1mut AML resulted in a significantly better reduction in NPM1mut TLs across all treatment cycles, leading to a significantly lower relapse rate.