Abstract: The aim of this study was to characterize the mutational landscape of patients with FLT3 -mutated acute myeloid leukemia (AML) treated within the randomized CALGB 10603/RATIFY trial evaluating intensive chemotherapy plus the multi-kinase inhibitor midostaurin versus placebo. We performed sequencing of 262 genes in 475 patients: mutations occurring concurrently with the FLT3 -mutation were most frequent in NPM1 (61%), DNMT3A (39%), WT1 (21%), TET2 (12%), NRAS (11%), RUNX1 (11%), PTPN11 (10%), and ASXL1 (8%) genes. To assess effects of clinical and genetic features and their possible interactions, we fitted random survival forests and interpreted the resulting variable importance. Highest prognostic impact was found for WT1 and NPM1 mutations, followed by white blood cell count, FLT3 mutation type (internal tandem duplications vs. tyrosine kinase domain mutations), treatment (midostaurin vs. placebo), ASXL1 mutation, and ECOG performance status. When evaluating two-fold variable combinations the most striking effects were found for WT1 : NPM1 (with NPM1 mutation abrogating the negative effect of WT1 mutation), and for WT1 :treatment (with midostaurin exerting a beneficial effect in WT1 -mutated AML). This targeted gene sequencing study provides important, novel insights into the genomic background of FLT3 -mutated AML including the prognostic impact of co-mutations, specific gene–gene interactions, and possible treatment effects of midostaurin.

Abstract: To characterize the genomic landscape and leukemogenic pathways of older, newly diagnosed, non-intensively treated patients with AML and to study the clinical implications, comprehensive genetics analyses were performed including targeted DNA sequencing of 263 genes in 604 patients treated in a prospective Phase III clinical trial. Leukemic trajectories were delineated using oncogenetic tree modeling and hierarchical clustering, and prognostic groups were derived from multivariable Cox regression models. Clonal hematopoiesis-related genes ( ASXL1 , TET2 , SRSF2 , DNMT3A ) were most frequently mutated. The oncogenetic modeling algorithm produced a tree with five branches with ASXL1 , DDX41 , DNMT3A , TET2 , and TP53 emanating from the root suggesting leukemia-initiating events which gave rise to further subbranches with distinct subclones. Unsupervised clustering mirrored the genetic groups identified by the tree model. Multivariable analysis identified FLT3 internal tandem duplications (ITD), SRSF2 , and TP53 mutations as poor prognostic factors, while DDX41 mutations exerted an exceptionally favorable effect. Subsequent backwards elimination based on the Akaike information criterion delineated three genetic risk groups: DDX41 mutations (favorable-risk), DDX41 wildtype / FLT3 -ITD neg / TP53 wildtype (intermediate-risk), and FLT3 -ITD or TP53 mutations (high-risk). Our data identified distinct trajectories of leukemia development in older AML patients and provide a basis for a clinically meaningful genetic outcome stratification for patients receiving less intensive therapies.

Abstract: Aging is associated with increased mutational burden in every tissue studied. Occasionally, fitness-increasing mutations will arise, leading to stem cell clonal expansion. This process occurs in several tissues but has been best studied in blood. Clonal hematopoiesis is associated with an increased risk of blood cancers, such as acute myeloid leukemia, which result if additional cooperating mutations occur. Surprisingly, it is also associated with an increased risk of nonmalignant diseases, such as atherosclerotic cardiovascular disease. This may be due to enhanced inflammation in mutated innate immune cells, which could be targeted clinically with anti-inflammatory drugs. Recent studies have uncovered other factors that predict poor outcomes in patients with clonal hematopoiesis, such as size of the mutant clone, mutated driver genes, and epigenetic aging. Though clonality is inevitable and largely a function of time, recent work has shown that inherited genetic variation can also influence this process. Clonal hematopoiesis provides a paradigm for understanding how age-related changes in tissue stem cell composition and function influence human health.

Abstract: BRCA1/BRCA2-containing complex 3 ( BRCC3 ) is a Lysine 63-specific deubiquitinating enzyme (DUB) involved in inflammasome activity, interferon signaling, and DNA damage repair. Recurrent mutations in BRCC3 have been reported in myelodysplastic syndromes (MDS) but not in de novo AML. In one of our recent studies, we found BRCC3 mutations selectively in 9/191 (4.7%) cases with t(8;21)(q22;q22.1) AML but not in 160 cases of inv(16)(p13.1q22) AML. Clinically, AML patients with BRCC3 mutations had an excellent outcome with an event-free survival of 100%. Inactivation of BRCC3 by CRISPR/Cas9 resulted in improved proliferation in t(8;21)(q22;q22.1) positive AML cell lines and together with expression of AML1-ETO induced unlimited self-renewal in mouse hematopoietic progenitor cells in vitro. Mutations in BRCC3 abrogated its deubiquitinating activity on IFNAR1 resulting in an impaired interferon response and led to diminished inflammasome activity. In addition, BRCC3 inactivation increased release of several cytokines including G-CSF which enhanced proliferation of AML cell lines with t(8;21)(q22;q22.1). Cell lines and primary mouse cells with inactivation of BRCC3 had a higher sensitivity to doxorubicin due to an impaired DNA damage response providing a possible explanation for the favorable outcome of BRCC3 mutated AML patients.

Abstract: Acute promyelocytic leukemia, a subtype of acute myeloid leukemia, is highly curable. In subgroup of patients with non-high-risk acute promyelocytic leukemia, intravenous arsenic trioxide plus all-trans-retinoic acid is considered the preferred regimen for acute promyelocytic leukemia. Recently, there are interests in the use of the oral form of arsenic, named the Realgar-Indigo naturalis formula, but the data on its efficacy and safety are still relatively limited. The current study was conducted with the aims to identify and summarize the results of all available randomized-controlled studies. A systematic review was conducted in the 2 major databases, utilizing the terms for arsenic and acute promyelocytic leukemia. Eligible studies had to be randomized-controlled studies that compared efficacy and/or adverse effects of oral arsenic versus intravenous arsenic for treatment of patients with acute promyelocytic leukemia. The Mantel-Haenszel method was used to pool the effect estimates and 95% confidence intervals of the included studies together. A total of 4 randomized controlled studies with 482 patients with acute promyelocytic leukemia (258 in Realgar-Indigo naturalis formula group and 224 in intravenous arsenic trioxide group) were included in the meta-analysis. The chances of achieving complete remission were numerically higher in the Realgar-Indigo naturalis formula group but the difference was not statistically significant (pooled odds ratio: 4.59, 95% CI: 0.74-28.57, I 2 = 0%). Similarly, other efficacy outcomes, including 30-day mortality rate, overall survival, and event-free survival, also tended to favor the Realgar-Indigo naturalis formula group but the difference was not statistically significant. There was no significant difference in the chance of developing differentiation syndrome, cardiac complications, grades 3 to 4 liver toxicity, grades 3 to 4 renal toxicity, and infection between the 2 groups. The results may suggest that all-trans-retinoic acid plus oral Realgar-Indigo naturalis formula regimen is, at minimum, not a worse alternative to the standard all-trans-retinoic acid plus intravenous intravenous arsenic trioxide regimen for treatment of acute promyelocytic leukemia, especially for patients with low-to-intermediate risk.

Abstract: Background: FLT3-ITD occurs in ~25% of adult AML patients (pts) and is associated with poor prognosis. MRD monitoring is of high prognostic relevance, but restricted to certain AML subtypes. FLT3-ITD represents an attractive target for MRD monitoring in particular in pts treated with a tyrosine kinase inhibitor. FLT3-ITD MRD monitoring is hampered by the broad heterogeneity of ITD length and insertion site (IS). NGS may overcome these limitations offering the opportunity for MRD monitoring in FLT3-ITD+ AML. Aims: To validate our recently established NGS-based FLT3-ITD MRD assay in a defined cohort of FLT3-ITD+ AML pts treated within the AMLSG16-10 trial (NCT01477606) combining intensive chemotherapy with midostaurin followed by midostaurin maintenance and to evaluate the prognostic impact of FLT3-ITD MRD monitoring. Methods: Using FLT3-ITD paired-end NGS (Illumina MiSeq) with a variant allele frequency (VAF) sensitivity of 10-4-10-5 (Blätte et al., Leukemia 2019), 227 bone marrow (BM) and 17 peripheral blood samples from 61 FLT3-ITD+ AML pts were analyzed at diagnosis (Dx), after two cycles of chemotherapy (Cy2), at the end of treatment (EOT), and during 3-6 months follow-up (FU). All pts achieved complete remission (CR) after Cy2. Allogeneic hematopoietic cell transplantation in first CR was performed in 40 (66%) pts. Mutational status for NPM1 and DNMT3A was available for all pts (NPM1mut, n=48; DNMT3Amut, n=33; NPM1mut/DNMT3Amut, n=31), and NPM1mut MRD data for 41 pts. Results: At Dx we identified 191 ITDs; median length was 45 nucleotides (range, 9-194) and median VAF 0.279% (range, 0.006-90.21). Of the 191 ITDs, 133 (70%) located in the juxtamembrane domain (JMD) and 58 (30%) in the tyrosine kinase domain-1 (TKD1). There was no correlation of VAF with length or IS, whereas ITD size correlated with IS: the more C-terminal the IS, the longer the ITD (Rho=0.51; p & lt;.001). Total ITD VAF per pt was in median 34.3% (range, 0.007-90.21) and correlated positively with white blood cell count (WBC, Rho=0.314; p=.021) and lactate dehydrogenase serum level (LDH, Rho=0.274; p=.04), and inversely with the number of ITDs (Rho=-0.265; p=.04). Most pts (67%) exhibited & gt;1 ITD at Dx (median 2; range, 1-16). Categorizing pts according to IS as JMDsole (46%), JMD/TKD1 (34%), and TKD1sole (20%) revealed that JMD/TKD1 pts exhibited more ITD subclones (p & lt;.001) and a lower total VAF at Dx (p=.03). There were no correlations with any other clinical or genetic features. Pts' total ITD VAF significantly decreased after Cy2 and at EOT (median log10 reduction: 4.4 and 4.7; p & lt;.001, each), and MRD negativity (MRD-) was achieved in 67% and 87% of pts, respectively. According to subgroups, pts with JMDsole or TKD1sole showed deeper MRD reduction compared to JMD/TKD1 pts after Cy2 (4.6 vs 4.7 vs 3.7 log10; p=.06) and at EOT (4.8 vs 4.8 vs 4.0 log10; p=.02) but this did not result in a significant difference in achievement of MRD-. Concurrent NPM1mut was of favorable impact for log10 VAF reduction (median, 4.7 for DNMT3Amut/NPM1mut vs 4.6 for NPM1mut vs 2.8 others; p=.003) and MRD- (77 vs 76 vs 31%; p=.01) after Cy2, but exerted no impact at EOT. Correlating NPM1mut and FLT3-ITD MRD course revealed a positive correlation after Cy2 (Rho=0.327; p=.03), but not at EOT (Rho=0.250; p=.10), likely due to the higher sensitivity of the real-time quantitative PCR-based NPM1mut MRD assay. Median follow-up was 3.4 years (95% CI, 2.6-4.6). Survival analyses with respect to cumulative incidence of relapse (CIR; n=60) and overall survival (OS; n=61) revealed significantly lower CIR for total VAF at Dx & gt;34.3% (p=.03), a VAF reduction & gt;4.7 log10 (MR4.7) at EOT (p=.001), and for MRD- pts at EOT (p=.001). There was no impact on OS. In preliminary exploratory Cox regression (n=48), including BM blasts, WBC, LDH, age, and NPM1mut as covariables, MRD- at EOT was the only consistent favorable variable for CIR (HR, 0.1; p=.001) and OS (HR, 0.27; p=.03). During FU, 5/8 (63%) MRD+ pts at EOT became MRD- and 4/53 (8%) MRD- pts converted to MRD+ resulting in consecutive relapse in 2 pts. Conclusion: In this first cohort of FLT3-ITD+ AML pts treated with intensive chemotherapy and midostaurin in the prospective AMLSG16-10 trial we could demonstrate that FLT3-ITD NGS-based MRD monitoring is feasible and represents a promising tool to evaluate therapy response and identification of pts at a higher risk of relapse. Further analysis of the study cohort is ongoing. Disclosures Kapp-Schwoerer: Jazz Pharmaceuticals: Honoraria, Research Funding. Paschka:Sunesis Pharmaceuticals: Consultancy; BerGenBio ASA: Research Funding; Novartis: Consultancy, Speakers Bureau; Otsuka: Consultancy; Pfizer: Consultancy, Speakers Bureau; Astellas Pharma: Consultancy, Speakers Bureau; Celgene: Consultancy, Other: Travel, accommodations or expenses; Astex Pharmaceuticals: Consultancy; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Agios Pharmaceuticals: Consultancy, Speakers Bureau; Amgen: Other; Janssen Oncology: Other; AbbVie: Other: Travel, accommodation or expenses, Speakers Bureau. Fiedler:Ariad/Incyte: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accomodations; Novartis: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: support in medical writing; Daiichi Sankyo Oncology: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accomodations; Morphosys: Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: support in medical writing; Servier: Honoraria, Other; BerGenBio ASA: Research Funding; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: travel accomodations, support in medical writing, Research Funding; Gilead: Honoraria. Salih:Novartis: Consultancy; Pfizer: Consultancy; Philogen: Consultancy; Medigene: Consultancy; Synimmune: Consultancy, Research Funding. Salwender:Bristol-Myers Squibb/Celgene: Honoraria; Janssen-Cilag: Honoraria; Amgen: Honoraria; Takeda: Honoraria; Oncopeptides: Honoraria; Sanofi: Honoraria; GlaxoSmithKline: Honoraria; AbbVie: Honoraria. Götze:Celgene: Research Funding. Luebbert:Janssen: Research Funding. Schlenk:PharmaMar: Research Funding; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees, Other: Travel, Accomodations, Expenses, Research Funding, Speakers Bureau; Novartis: Speakers Bureau; Roche: Research Funding; AstraZeneca: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Thol:Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Heuser:Daiichi Sankyo: Consultancy, Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Karyopharm: Research Funding; Abbvie: Consultancy; PriME Oncology: Honoraria; Amgen: Research Funding; Astellas: Research Funding; Roche: Research Funding; Stemline Therapeutics: Consultancy; Novartis: Consultancy, Honoraria, Research Funding; Janssen: Consultancy; BerGenBio ASA: Research Funding; Bayer: Consultancy, Research Funding. Ganser:Novartis: Consultancy; Celgene: Consultancy. Döhner:AstraZeneca: Consultancy, Honoraria; Sunesis: Research Funding; Roche: Consultancy, Honoraria; Pfizer: Research Funding; Oxford Biomedicals: Consultancy, Honoraria; 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; Astellas: Consultancy, Honoraria, Research Funding; AROG: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria; GEMoaB: Consultancy, Honoraria. Bullinger: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; Pfizer: Membership on an entity's Board of Directors or advisory committees; Novartis: 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; Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: 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; Amgen: Membership on an entity's Board of Directors or advisory committees; Sanofi: 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. Döhner:Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Honoraria; Celgene: Consultancy, Honoraria; Sunesis Pharmaceuticals: Research Funding; Novartis: Honoraria, Research Funding; Pfizer: Research Funding; Bristol-Myers Squibb: Research Funding; Arog: Research Funding; Roche: Consultancy; Astex Pharmaceuticals: Consultancy; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Research Funding; Astellas Pharma: Consultancy; Agios: Consultancy; Abbvie: Consultancy.

Abstract: Background: Recently, the oral multitargeted small molecule FLT3 inhibitor midostaurin (M) was approved for treatment of FLT3-mutated AML in combination with standard chemotherapy. In the international RATIFY (NCT00651261) trial, addition of M led to superior overall and event-free survival compared to placebo, thus defining a new standard of care in this AML subset (Stone RM et al. NEJM 2017). Although not powered for subgroup analyses, M showed consistent effects across all FLT3 mutation strata [tyrosine kinase domain (TKD); internal tandem duplication (ITD) with low (0.05-0.7; ITDlow) or high ( 〉 0.7; ITDhigh) allelic ratio] suggesting significant off-target activity beyond FLT3 inhibition. Aim: We aimed to comprehensively profile the mutational landscape of FLT3 mutated (FLT3mut) AML in a large, well characterized cohort of patients (pts) treated within the RATIFY trial using a high-throughput targeted sequencing (HTS) approach. Methods: HTS was performed on the entire coding region of 262 genes involved in hematologic malignancies including 20 genes that encode kinases targeted by M (M kinome, MK). Pretreatment peripheral blood (PB; 14%) or bone marrow (BM; 86%) specimens were available from 475 (66%) of 717 FLT3mut AML RATIFY pts. Libraries were prepared using SureSelectXT custom solutions (Agilent). Paired-end sequencing was carried out on a HiSeq platform (Illumina). FLT3 mutation (mut) status was available for all pts [TKD: 24%; ITD: 76% (ITDlow: 45%; ITDhigh:31%)], and cytogenetic data for 454 pts (96%). Results: An average sequencing depth of 978x was obtained for all pts. In sum, 1815 mut (missense: 49%; indels: 40%; nonsense: 7%; other: 3%) were identified with a mean of 3.8 mut per pt (FLT3 strata; TKD: 4; ITDlow: 4; ITDhigh: 3.6).Overall, recurrent mut ( 〉 5% of all pts) were found in NPM1 (61%), DNMT3A (39%), WT1 (21%), TET2 (12%), RUNX1 (11%), NRAS (11%), PTPN11 (9%), ASXL1 (8%), IDH1 (8%), IDH2 (7%; R140 only), and SMC1A (6%). In contrast, TP53 (1%) and biallelic CEPBA (1%) mut were rare events. This was also true for aberrations of the MK (7% in total) with KIT (2%), MAP3K11 (1%), and NTRK3 (1%) being most frequently mutated. When stratified according to FLT3mut type, mut in NRAS (24% vs 7%, p 〈 .0001), SMC1A (10% vs 4%, p=.02), and KIT (4% vs 1%, p=.02) occurred significantly more often in TKD than ITD groups, respectively, whereas WT1 (13% vs 24%, p=.018) was more frequently co-mutated in the ITD group. In general, pts in the TKD group had significantly more mut in genes encoding for cohesin (TKD: 29% vs ITD: 16%, p=.004) and signaling (TKD: 40% vs ITD: 24%, p=.001) proteins compared to ITD pts, who had significantly more mut in transcription genes (TKD: 37% vs ITD: 48%, p=.03). Based on the mut and cytogenetic data, we next sought to assign all FLT3mut pts to the 11 recently defined molecular AML classes (Papaemmanuil E et al. NEJM 2016). The majority fell into two classes, namely the NPM1 (N; 62%) and the chromatin-spliceosome (CS; 15%) classes, underscoring the significance of FLT3mut as the driver in these particular genomic classes. Other class-defining lesions were rare or absent in this cohort [inv(16): 2%; t(8;21): 2%; t(11q23;x): 2%; t(6;9): 1%, TP53-aneuploidy: 1%; CEBPAbiallelic: 1%; IDH2R172: 0%]. In 14% of all pts categorization was not possible (no or 〉 1 class-defining lesion), emphasizing the need for further refinement of this classification. When focusing on these two groups, N and CS had comparable FLT3mut patterns (TKD: 24% vs 21%; ITDlow: 44% vs 45%; ITDhigh: 32% vs 33%), whereas N more frequently correlated with a normal karyotype (N: 91% vs CS: 63%). With respect to clinical characteristics, no differences between N and CS in terms of age, white blood cells, platelets, PB and BM blasts, as well as history of MDS were observed. Conclusion: In this comprehensive sequencing approach, we could further delineate the molecular pattern of FLT3mut AML. Here, FLT3-ITD and -TKD groups exhibited remarkable differences in cooperating pathways, highlighting distinct biologic features in the leukemogenesis of FLT3mut AML. Overall, mut of MK genes were rare events, not fully explaining the complexity of M off-target effects. Understanding the underlying disease mechanism will potentially provide useful information on prognosis and prediction of response to M. Further analyses including correlation with clinical outcome are ongoing. Support: U10CA180821, U10CA180861, U10CA180882, U24CA196171 Disclosures Bullinger: Janssen: Speakers Bureau; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers Squibb: Speakers Bureau; Pfizer: Speakers Bureau; Sanofi: Research Funding, Speakers Bureau; Amgen: Honoraria, Speakers Bureau; Bayer Oncology: Research Funding. Gathmann:Novartis: Employment. Larson:Ariad/Takeda: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; BristolMyers Squibb: Consultancy, Research Funding. Medeiros:Genentech: Employment; Celgene: Consultancy, Research Funding. Tallman:ADC Therapeutics: Research Funding; AROG: Research Funding; BioSight: Other: Advisory board; Orsenix: Other: Advisory board; AbbVie: Research Funding; Daiichi-Sankyo: Other: Advisory board; Cellerant: Research Funding. Tiecke:Novartis: Employment. Pallaud:Novartis: Employment. Ehninger:Cellex Gesellschaft fuer Zellgewinnung mbH: Employment, Equity Ownership; GEMoaB Monoclonals GmbH: Employment, Equity Ownership; Bayer: Research Funding. Ganser:Novartis: Membership on an entity's Board of Directors or advisory committees. Stone:Otsuka: Consultancy; Jazz: Consultancy; Cornerstone: Consultancy; Fujifilm: Consultancy; Arog: Consultancy, Research Funding; Pfizer: Consultancy; Sumitomo: Consultancy; Novartis: Consultancy, Research Funding; Ono: Consultancy; Orsenix: Consultancy; Merck: Consultancy; Argenx: Other: Data and Safety Monitoring Board; AbbVie: Consultancy; Agios: Consultancy, Research Funding; Amgen: Consultancy; Astellas: Consultancy; Celgene: Consultancy, Other: Data and Safety Monitoring Board, Steering Committee. Thiede:AgenDix: Other: Ownership; Novartis: Honoraria, Research Funding. Döhner:AROG Pharmaceuticals: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; AROG Pharmaceuticals: Research Funding; Pfizer: Research Funding; Bristol Myers Squibb: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Celator: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Bristol Myers Squibb: Research Funding; Sunesis: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Astex Pharmaceuticals: Consultancy, Honoraria; Astex Pharmaceuticals: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Pfizer: Research Funding; Seattle Genetics: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Celator: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Jazz: Consultancy, Honoraria.