Abstract: Background: CPX-351, a liposomal formulation of daunorubicin and cytarabine in the fixed molar ratio (1:5), is approved for the treatment of adult patients (pts) with newly diagnosed acute myeloid leukemia (AML) with myelodysplasia-related changes and therapy-related AML (t-AML). To explore the potential benefit of CPX-351 in a broader indication, we initiated a randomized phase III study of CPX-351 vs "3+7" in pts ≥18 years (yrs) of age with AML and intermediate or adverse genetics according to 2017 European LeukemiaNet (ELN) risk categorization (AMLSG 30-18, NCT03897127). In the younger pts (18-60 yrs) we sought to investigate a higher dose of CPX-351. We here report data from an interim safety analysis for this higher CPX-351 dose. Methods: Pts are randomized to receive first induction cycle (ind 1) with either CPX-351 or daunorubicin + cytarabine ("3+7": daunorubicin 60 mg/m2 on days 1, 2, 3 + cytarabine 200 mg/m2 on days 1-7); in pts aged 18-60 yrs (performance status 0-1) CPX-351 is given at a dose of 55 mg/m2 daunorubicin/125 mg/m2 cytarabine (125 U/m²; 1 U/m2=0.44 mg/m2 daunorubicin/1 mg/m2 cytarabine; days 1, 3, 5); pts & gt;60 yrs receive the standard dose CPX-351 100 U/m² (days 1, 3, 5). There was no age-adapted dosing in the control arm. For induction cycle 2 (ind 2), pts on the CPX-351 arm receive the same dosage on day 1+2 only; pts on the control arm receive intermediate-dose cytarabine + daunorubicin (both in age-adapted dosing). Continuous assessment for safety is performed for two endpoints: 60-day mortality with a maximally tolerated rate (MTR) of 15%; and hematologic recovery times with i) neutropenia 4° and / or ii) thrombocytopenia 3° or 4° after each ind lasting longer than day 42 after start of treatment cycle (without evidence of persistent leukemia) with a MTR of 25%. Median hematologic recovery times were analyzed using Kaplan-Meier estimates, p-values are mentioned in a descriptive manner (log-rank test). Results: As of July 20, 2020, 36 patients have been randomized to the study (CPX-351, n=19; "3+7", n=17) with following characteristics: de novo AML, n=27, secondary or t-AML, n=9; median age 60.5 yrs (range 47-75; ≤60 yrs, n=18; & gt;60 yrs, n=18); intermediate and adverse risk genetics were found in 7 and 10 pts, respectively (not available yet, n=19). On the CPX-351 arm, 9 of 19 pts were ≤60 yrs of age and received the higher CPX-351 dose. So far, 36 pts received ind 1, 25 pts ind 2. Overall, the median time to neutrophil recovery with absolute neutrophil count (ANC) & gt;0.5 G/l was longer in the CPX-351 arm compared to the "3+7" arm: 39 vs 28 days (p=0.07) after ind 1, and 26.5 vs 19 days after ind 2 (p=0.06; table 1). Time to platelet recovery & gt;50 G/l was significantly prolonged in the CPX-351 arm after ind 1 (40 vs 26 days; p & lt;0.0001), currently not after ind 2 (33 and 18 days; p=0.35). When comparing the higher dose (125 U/m²; pts 18-60 yrs) with the standard CPX-351 dose (100 U/m², pts & gt;60 yrs), the median time to neutrophil recovery after ind 1 was significantly longer with the higher dose (40 and 31 days, respectively; p=0.03); after ind 2 median times were 38 and 20.5 days (p=0.26); platelet recovery ( & gt;50 G/l) was also significantly delayed after ind 1 with the higher compared to the standard CPX-351 dose (median 43 vs 32 days; p=0.002); platelet recovery after ind 2 was after a median of 38.5 and 26.5 days, respectively (p=0.17). There was no treatment-related death (60-day mortality 0%) in both arms. So far, 6 of the 9 pts (67%) treated with the higher CPX-351 dose reached the safety endpoint of persisting neutropenia (n=4) or thrombocytopenia (n=5) during ind beyond day 42. The MTR was exceeded for thrombocytopenia (0.63; 95% confidence interval (CI) [0.31; 0.86]), but not for neutropenia (0.50; 95% CI [0.22; 0.78] ). Overall, there were 18 serious adverse events (SAEs); among the most frequent SAEs were infections and fever in neutropenia (n=10). Conclusion: The higher dose of CPX-351 administered in pts 18-60 yrs of age led to significantly prolonged hematologic recovery times during ind 1 and 2 exceeding the MTR for thrombocytopenia without treatment-related death. Based on the prolonged hematologic recovery, the protocol will be amended, in that the CPX-351 dose for ind in pts 18-60 yrs of age is reduced to the current Package Insert for CPX-351 44 mg/m2 daunorubicin / 100 mg/m2 cytarabine (100 U/m²). Data on hematologic response as well as on measurable residual disease using multi-parameter flow cytometry will be presented. Disclosures Kapp-Schwoerer: Jazz Pharmaceuticals: Honoraria, Research Funding. 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:Karyopharm: Research Funding; Abbvie: Consultancy; Astellas: Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Roche: Research Funding; BerGenBio ASA: Research Funding; Janssen: Consultancy; Stemline Therapeutics: Consultancy; Bayer: Consultancy, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Amgen: Research Funding; PriME Oncology: Honoraria. Faderl:Jazz Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. Wagner:JAZZ Pharmaceuticals: Current Employment; JAZZ Pharmaceuticals: Current equity holder in publicly-traded company. Ganser:Celgene: Consultancy; Novartis: Consultancy. Döhner:Abbvie: Consultancy; Daiichi Sankyo: Honoraria; Celgene: Consultancy, Honoraria; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Astex Pharmaceuticals: Consultancy; Roche: Consultancy; Bristol-Myers Squibb: Research Funding; Pfizer: Research Funding; Amgen: Consultancy, Research Funding; Astellas Pharma: Consultancy; Janssen: Consultancy, Honoraria; Sunesis Pharmaceuticals: Research Funding; Agios: Consultancy; Arog: Research Funding. Paschka:BerGenBio ASA: Research Funding; Janssen Oncology: Other; Amgen: Other; Otsuka: Consultancy; Novartis: Consultancy, Speakers Bureau; Sunesis Pharmaceuticals: Consultancy; Pfizer: Consultancy, Speakers Bureau; Astellas Pharma: Consultancy, Speakers Bureau; Celgene: Consultancy, Other: Travel, accommodations or expenses; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Agios Pharmaceuticals: Consultancy, Speakers Bureau; Astex Pharmaceuticals: Consultancy; AbbVie: Other: Travel, accommodation or expenses, Speakers Bureau. Döhner:Abbvie: 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; AstraZeneca: Consultancy, Honoraria; AROG: Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Agios: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Astellas: Consultancy, Honoraria, Research Funding; Astex: Consultancy, Honoraria; GEMoaB: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding. OffLabel Disclosure: CPX-351 is approved for the treatment of adult patients with newly diagnosed acute myeloid leukemia (AML) with myelodysplasia-related changes and therapy-related AML (t-AML). To explore the potential benefit of CPX-351 in a broader indication, a randomized phase III study of CPX-351 vs 3+7 in patients older than 18 years of age with AML and intermediate or adverse genetics according to 2017 European LeukemiaNet (ELN) risk categorization (AMLSG 30-18, NCT03897127) was initiated. In the younger patients (18-60 yrs) a higher dose of CPX-351 is evaluated.

Abstract: Background: The decision to perform allogeneic haematopoietic stem cell transplantation (alloHSCT) in acute myeloid leukemia (AML) is based on the risk-benefit ratio (non relapse mortality vs reduction of relapse risk). In 2017, the European LeukemiaNet (ELN) proposed a risk score based on cytogenetic and molecular genetic characteristics to facilitate this decision. Despite this improved classification of the genetic landscape of AML, the assessment of risk of relapse should be more precise. However, large cohorts are needed to analyze the clinical outcome of specific genetic alterations. Within the HARMONY alliance, we have now collected harmonized clinical and analytical data for a large number of AML patients. Aims: This study focuses on AML patients who achieved first complete remission (CR1) that, according to ELN risk (low/intermediate) assessment are not classical candidates for alloHSCT as consolidation therapy. The aim of this study is to create a more accurate risk prediction in this setting based on an on-line tool that can visualize the likelihood of relapse and thereby help to determine in which patient alloHSCT should be performed in CR1. Methods: The data included in the HARMONY alliance database was provided by 100 organisations in 18 European countries. In order to be accepted, they passed through quality control, anonymisation and harmonisation processes before being included in the database. Harmonisation is carried out according to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), which is specially designed to accommodate both administrative claims and medical records, making it possible to bring together all the information from different data sources and to speed up its subsequent analysis. Through the analysis platform, we selected patients from the ~5700 patients available that matched the target population of the study. We filtered out those patients without sufficient information on their clinical course, those who did not achieve complete remission and patients with a poor prognosis (adverse risk according to ELN2017), as the study focuses on patients who a priori did not have an indication for alloHSCT. This process resulted in a sample of 842 patients. In the next steps, variable selection was performed together with the treatment of incomplete cases by imputation. Multiple Machine Learning (ML) techniques, both parametric and non-parametric, were tested for predictions (Random Forest, Weibull distribution), all of them taking into account censored data. Other sets of methods were applied to explain the information handled by the previous models and to present graphically, for each prediction, a breakdown of the influence that each feature had on that prediction. Validation of the results is being performed both by testing by medical specialists and by means of statistical indicators, such as Harrell's index. Results: The study population of 842 AML patients included 47% females and the median age was 49 years. The most frequent mutation was NPM1 (50%), followed by DNMT3A (31%) and NRAS (26%). The tool first displays a panel in which characteristics such as age, gender, and possible mutations and cytogenetic abnormalities are selected from a list based on information in the HARMONY database. Once the desired profile has been selected, graphical results are provided: 1). the probability of Relapse-Free Survival (RFS) over time. In parallel, as a reference, the probability of RFS of patients corresponding to each category of the ELN2017 can be seen. 2). a breakdown of the relative weight of each feature in the model at a specific time point, as well as the positive/negative effect that the presence/absence of these features has on the prognostic factor of relapse, adapting all this information in each individual simulation. This preliminary research tool can integrate new data and be expanded with new tools to provide useful results in a simple and accessible way. Conclusion: Building big data platforms, such as the HARMONY Alliance, are absolutely essential to facilitate the creation of tools to support research and ultimately clinical practice. Big data analysis should be considered a very useful field in disease research and it is necessary to share the results with easy-to-use tools that are available at all times. This new ML tool for AML aims to achieve these goals through its simple design and its implementation in mobile devices. Figure 1 Figure 1. Disclosures Sobas: Novartis: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Heckman: Kronos Bio, Inc.: Research Funding; Oncopeptides: Consultancy, Research Funding; Novartis: Research Funding; Orion Pharma: Research Funding; Celgene/BMS: Research Funding. Dombret: Amgen: Honoraria, Research Funding; Incyte: Honoraria, Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; Novartis: Research Funding; Pfizer: Honoraria, Research Funding; Servier: Research Funding; Abbvie: Honoraria; BMS-Celgene: Honoraria; Daiichi Sankyo: Honoraria. Sierra: Jazz Pharmaceuticals: Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Other: Educational grant; BMS Celgene: Honoraria, Research Funding; Alexion: Other: Educational grant; Novartis: Honoraria, Research Funding, Speakers Bureau; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Other: Educational grant; Janssen: Other: Educational grant; Pfizer: Honoraria. Mayer: Principia: Research Funding. Voso: Celgene: Consultancy, Research Funding, Speakers Bureau; Novartis: Speakers Bureau. Sanz: Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses, Speakers Bureau; Gilead Sciences: Other: Travel, accommodations, and expenses; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Boehringer Ingelheim: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses; Helsinn Healthcare: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses, Research Funding. Calado: Novartis: Current Employment. Döhner: Celgene/BMS: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Honoraria, Other: Advisory Board; Astellas: Research Funding; Jazz Roche: Consultancy, Honoraria; Agios and Astex: Research Funding; Abbvie: Consultancy, Honoraria; Janssen: Honoraria, Other: Advisory Board; Novartis: Consultancy, Honoraria, Research Funding. Gaidzik: Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Speakers Bureau; Janssen: Speakers Bureau. Heuser: Jazz Pharmaceuticals: Consultancy, Honoraria, Other: Research funding for institution; Janssen: Honoraria; Novartis: Consultancy, Honoraria, Other: Research funding for institution; Abbvie: Consultancy; BMS/Celgene: Consultancy; Daiichi Sankyo: Consultancy, Other: Research funding for institution; Pfizer: Consultancy, Other: Research funding for institution; Roche: Consultancy, Other: Research funding for institution; Tolremo: Consultancy; Astellas: Other: Research funding for institution; Bayer Pharma AG: Other: Research funding for institution; BergenBio: Other: Research funding for institution; Karyopharm: Other: Research funding for institution. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Turki: CSL Behring: Consultancy; MSD: Consultancy, Speakers Bureau; Jazz Pharma: Consultancy, Speakers Bureau. Reinhardt: Astellas Pharma Inc.: Research Funding; Eusa: Other: Advisory board; Novartis: Other: Advisory board; BluebirdBio: Other: Advisory board; Janssen: Other: Advisory board; Abbvie: Other: Advisory board; JAZZ: Other: Advisory board; BMS: Other: Advisory board. Schulze-Rath: Bayer: Current Employment. Dohner: Berlin-Chemie: Honoraria; Bristol Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; GEMoaB: Honoraria; Gilead: Honoraria; Helsinn: Honoraria; Janssen: Honoraria; Jazz Pharmaceuticals: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Oxford Biomedica: Honoraria; Pfizer: Research Funding; Roche: Honoraria; AstraZeneca: Honoraria; Astex Pharmaceuticals: Honoraria; Astellas: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding. Ossenkoppele: Abbvie, AGIOS, BMS/Celgene Astellas,AMGEN, Gilead,Servier,JAZZ,Servier Novartis: Consultancy, Honoraria; Agios: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Jazz: Consultancy, Honoraria. Bullinger: Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Menarini: Consultancy; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Astellas: Honoraria; Sanofi: Honoraria; Seattle Genetics: Honoraria; Bayer: Research Funding; Amgen: Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Gilead: Consultancy; Celgene: Consultancy, Honoraria; Hexal: Consultancy. Hernández-Rivas: Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract: Background: The development of new genetic profiling techniques such as Next Generation Sequencing (NGS) have helped to unravel the genomic landscape of a large number of hematological diseases. In acute myeloblastic leukemia (AML), many mutations have been found at diagnosis or during the course of the disease, either alone or in combination. Nevertheless, the clinical significance of most of them has not been well established. That is particularly true regarding infrequent gene mutations and their co-mutations as they are underrepresented in most case series that have been analyzed so far. The big data platform of HARMONY alliance provides the excellent basis for addressing this problem as it assimilates clinical and genomic information about AML patients from over 100 organisations in 18 European countries comprising more than 5000 patients. Anonymised and harmonized using OMOP standards, data collected in HARMONY are optimal for studying the impact of gene-gene-interactions overcoming differences related to data providers. Aims: To identify clinically significant genetic patterns of 2 or more concurrent mutations using the Harmony alliance AML database Methods: From the HARMONY alliance database, we selected ~3600 AML patients with NGS molecular panel analysis. We first performed survival analysis between each gene combination and then we rendered those with statistically significant differences in one easy-to-read graph using the Gephi platform (Fig. A). We then highlighted promising or unexpected associations and analyzed them one by one in greater detail. Finally, these results were validated on an independent cohort. Results: We found that the co-mutation of RAD21 (RAD21mut) in DNMT3A mutated (DNMT3Amut) AML impacted outcome compared to DNMT3Amut alone patients (Fig. B, 3-year survival, 81% vs 52%, p=0.016). However, this effect was exclusively seen in allogeneic transplant recipients. In order to identify possible bias that could be generated if RAD21mut were associated with other well-known favorable prognosis mutations, we compared the frequency of each mutation in our DNMT3Amut / RAD21mut subgroup with the global AML cohort. NPM1 co-mutation was more frequent in the DNMT3Amut / RAD21mut group (Fig. C 3, 84% of patients with NPM1 mutation (NPM1mut) vs 26% in the global cohort), potentially explaining the higher survival. Next, we tried to isolate the positive effect of NPM1 on outcome by comparing DNMT3Amut / NPM1mut patients with and without the RAD21 co-mutation. This analysis showed a favorable outcome only in RAD21mut patients compared to RAD21 wildtype (Fig. D, 3-year survival, 83% in RAD21mut / DNMT3Amut / NPM1mut vs 50% in DNMT3Amut / NPM1mut with RAD21 wildtype, p=0.016), one more time only in allogeneic transplant recipients. Finally in order to validate our results we reproduced this study from the beginning using an independent cohort of 3125 AML patients. The Gephi graph confirmed an association of DNMT3Amut / RAD21mut patients with better survival over DNMT3A alone (3 year-survival, 75% vs 37%, p & lt;0.001). NPM1 co-mutation was again more frequent in the good prognosis group (76% vs 27%) but comparing RAD21mut / DNMT3Amut / NPM1mut patients with DNMT3Amut / NPM1mut alone still revealed good prognosis to be related with RAD21mut (3 year-survival, 87.5% in patients with RAD21mut vs 38% with RAD21 wildtype, p & lt;0.001). Conclusions: Using the HARMONY alliance database we tested for potential gene co-mutations in AML patients, often very infrequently represented in other studies. Our data suggest that RAD21mut has a positive effect on outcome in patients receiving an allogeneic transplant with concurrent mutation of DNMT3A and NPM1. Even though NPM1mut is much more frequent in the DNMT3Amut / RAD21mut group, its association with favourable outcome seems to depend on the presence of an additional RAD21mut Keywords: AML , gene combinations, RAD21, DNMT3A, NPM1, HARMONY, big data. Figure: Graphical results. A. View obtained from the Gephi platform with the gene combinations and their effect on survival. B. Survival curves respectively of the DNMT3A+RAD21 cohort and the DNMT3A-only one. 1. Representation of the proportions of each mutation in the overall cohort (red) compared to the DNMT3A+RAD21 cohort (blue). D. Survival curves respectively of the NPM1+DNMT3A+RAD21 cohort and the NPM1+DNMT3A one. Figure 1 Figure 1. Disclosures Sobas: Novartis: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Heckman: Novartis: Research Funding; Orion Pharma: Research Funding; Celgene/BMS: Research Funding; Oncopeptides: Consultancy, Research Funding; Kronos Bio, Inc.: Research Funding. Ayala: Incyte Corporation: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Astellas: Honoraria; Celgene: Honoraria. Dombret: Amgen: Honoraria, Research Funding; Incyte: Honoraria, Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; Novartis: Research Funding; Pfizer: Honoraria, Research Funding; Servier: Research Funding; Abbvie: Honoraria; Daiichi Sankyo: Honoraria; BMS-Celgene: Honoraria. Sierra: Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz Pharmaceuticals: Research Funding; Novartis: Honoraria, Research Funding, Speakers Bureau; BMS Celgene: Honoraria, Research Funding; Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Honoraria; Roche: Other: Educational grant; Janssen: Other: Educational grant; Amgen: Other: Educational grant; Alexion: Other: Educational grant. Mayer: Principia: Research Funding. Voso: Celgene: Consultancy, Research Funding, Speakers Bureau; Novartis: Speakers Bureau. Sanz: Helsinn Healthcare: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Boehringer Ingelheim: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses, Speakers Bureau; Gilead Sciences: Other: Travel, accommodations, and expenses; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses, Research Funding. Calado: Novartis: Current Employment. Döhner: Janssen: Honoraria, Other: Advisory Board; Jazz Roche: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Astellas: Research Funding; Agios and Astex: Research Funding; Daiichi Sankyo: Honoraria, Other: Advisory Board; Celgene/BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Gaidzik: Janssen: Speakers Bureau; Pfizer: Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Heuser: AbbVie: 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; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Research Funding; BergenBio: Research Funding; BMS/Celgene: 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; Tolremo: Membership on an entity's Board of Directors or advisory committees; Astellas: Research Funding; Bayer Pharma AG: Research Funding. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Turki: Jazz Pharma: Consultancy, Speakers Bureau; MSD: Consultancy, Speakers Bureau; CSL Behring: Consultancy. Schulze-Rath: Bayer: Current Employment. Hernández Rivas: Celgene/BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees. Bullinger: Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Hexal: Consultancy; Gilead: Consultancy; Abbvie: Consultancy, Honoraria; Menarini: Consultancy; Novartis: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Amgen: Honoraria; Astellas: Honoraria; Sanofi: Honoraria; Seattle Genetics: Honoraria; Bayer: Research Funding. Döhner: Jazz: Honoraria, Research Funding; Janssen: Honoraria; GEMoaB: Honoraria; Astellas: Honoraria, Research Funding; Astex: Honoraria; Agios: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; Roche: Honoraria; Pfizer: Research Funding; Novartis: Honoraria, Research Funding; Oxford Biomedicals: Honoraria; Helsinn: Honoraria; BMS: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; AstraZeneca: Honoraria; Berlin-Chemie: Honoraria; Amgen: Honoraria, Research Funding. Ossenkoppele: Servier: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Abbvie, AGIOS, BMS/Celgene Astellas,AMGEN, Gilead,Servier,JAZZ,Servier Novartis: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Gilead: Consultancy, Honoraria.

Abstract: The large acute myeloid leukemia (AML) patient-derived data sets collected within the European HARMONY alliance allows to study the molecular heterogeneity underlying AML in detail. Especially, how cytogenetic and molecular genetic aberrations differentially affect patients. Here, we report first results on the differences in mutational patterns in males and females. We studied a cohort of AML patients characterized by a panel of 70 molecular abnormalities comprising both cytogenetic and genetic observations. We quantified the differences of molecular patterns between sexes in two ways: 1) by comparing the number of gene-gene mutation co-occurrence and mutual mutation exclusivity with a χ 2 test, 2) exploiting the Hierarchical Dirichlet process (HDP) for molecular components discovery. In particular, we added sex as a further layer of the hierarchy allowing the same molecular components to be differently re-weighted based on gender. The HARMONY AML cohort comprised 2796 patients with detailed molecular information from targeted sequencing of 41 genes and detailed cytogenetic information condensed into 29 cytogenetic properties, known, a priori, to be relevant for the disease. Male to female ratio was 52% vs. 48% and median age was 52.0 (18.2 - 91.4) years. The entry data of the analysis were in the form of a binary matrix reporting the presence/absence of a given alteration in a patient. The χ 2 test based on the relative co-occurrence of mutation pairs suggested a significant difference between men and women solely for RUNX1 and NPM1. The number of co-occurrences was higher in male than in females. No significant mutual exclusive mutations were found between the populations. By using a two hierarchic levels HDP clustering we identified 11 overall molecular components shared by all AML patients. Six of these components are characterized by one or more genetic drivers, namely: NPM1, RUNX1, Complex-Karyotype-TP53, FLT3-IDH2, IDH2, CEPBA-biallelic, while the others were driven by cytogenetic abnormalities: t(6;9), t(8;21), inv(3), rearrangement of 11q23, inv(16). These results were in agreement with the current WHO AML classification and with other recent studies, which have attempted to improve stratification/classification of patients based on their molecular aberration patterns. While the molecular components were the same for all patients, major differences were observed in the contribution of NPM1 and RUNX1 components to males' and females' genotypes. On one side, NPM1 component has a double weight in females with respect to males. On the other hand, RUNX1 impacts males much more than females. The other aberrations were equally represented in both sexes. To test the robustness of the differences found between sexes, we compared these results with random splits of the datasets finding no differences in component weights, thereby validating our observations. Big data collections such as the HARMONY Alliance data base ensure data comparability via OMOP common data model harmonization approaches thereby offering the possibility to study large cohort that allow meaningful subgroup analyses such as the one focusing on gender imbalances. Proving the concept of the HARMONY Alliance data hub, our study confirms a female preponderance for NPM1 mutations and an association of RUNX1 mutations with male gender. Impact on patient outcome is currently evaluated and will be presented at the annual meeting. Figure 1 Figure 1. Disclosures Heckman: Celgene/BMS: Research Funding; Orion Pharma: Research Funding; Novartis: Research Funding; Oncopeptides: Consultancy, Research Funding; Kronos Bio, Inc.: Research Funding. Dombret: Abbvie: Honoraria; Amgen: Honoraria, Research Funding; Incyte: Honoraria, Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; NOVARTIS: Research Funding; pfizer: Honoraria, Research Funding; servier: Research Funding; BMS-Celgene: Honoraria; Daiichi Sankyo: Honoraria. Montesinos: Tolero Pharmaceutical: Consultancy; Agios: Consultancy; Stemline/Menarini: Consultancy; Teva: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Sanofi: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Incyte: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Forma Therapeutics: Consultancy; Glycomimetics: Consultancy; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Astellas Pharma, Inc.: Consultancy, Honoraria, Other: Advisory board, Research Funding, Speakers Bureau. Sierra: Astellas: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Honoraria, Research Funding, Speakers Bureau; Jazz Pharmaceuticals: Research Funding; Janssen: Other: Educational grant; Roche: Other: Educational grant; Pfizer: Honoraria; BMS Celgene: Honoraria, Research Funding; Alexion: Other: Educational grant; Amgen: Other: Educational grant; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Mayer: Principia: Research Funding. Voso: Novartis: Speakers Bureau; Celgene: Consultancy, Research Funding, Speakers Bureau. Sanz: Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses, Speakers Bureau; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Boehringer Ingelheim: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Gilead Sciences: Other: Travel, accommodations, and expenses; Helsinn Healthcare: Consultancy, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel, accommodations, and expenses, Research Funding. Calado: Novartis: Current Employment. Döhner: Agios and Astex: Research Funding; Daiichi Sankyo: Honoraria, Other: Advisory Board; Jazz Roche: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Janssen: Honoraria, Other: Advisory Board; Astellas: Research Funding; Celgene/BMS: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding. Gaidzik: Pfizer: Speakers Bureau; Janssen: Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Heuser: BergenBio: Research Funding; Jazz Pharmaceuticals: Honoraria, Research Funding; BMS/Celgene: Research Funding; Bayer AG: Honoraria, Research Funding; Astellas: Research Funding; Daichi Sankyo: Honoraria, Research Funding; Karyopharm: Research Funding; Novartis: Honoraria, Research Funding; Pfizer: Honoraria, Research Funding; Roche: Research Funding; Tolremo: Honoraria; AbbVie: Honoraria; Janssen: Honoraria. Haferlach: MLL Munich Leukemia Laboratory: Other: Part ownership. Sobas: Celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria. Turki: CSL Behring: Consultancy; Jazz Pharma: Consultancy, Speakers Bureau; MSD: Consultancy, Speakers Bureau. Schulze-Rath: Bayer: Current Employment. Hernández Rivas: Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene/BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees. Döhner: Abbvie: Honoraria, Research Funding; Agios: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Astellas: Honoraria, Research Funding; Astex Pharmaceuticals: Honoraria; AstraZeneca: Honoraria; Berlin-Chemie: Honoraria; Bristol Myers Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; GEMoaB: Honoraria; Gilead: Honoraria; Helsinn: Honoraria; Janssen: Honoraria; Jazz Pharmaceuticals: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Oxford Biomedica: Honoraria; Pfizer: Research Funding; Roche: Honoraria. Ossenkoppele: Abbvie, AGIOS, BMS/Celgene Astellas,AMGEN, Gilead,Servier,JAZZ,Servier Novartis: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Agios: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; BMS/Celgene: Consultancy, Honoraria; Jazz: Consultancy, Honoraria; Gilead: Consultancy, Honoraria. Bullinger: Menarini: Consultancy; Amgen: Honoraria; Hexal: Consultancy; Novartis: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Astellas: Honoraria; Abbvie: Consultancy, Honoraria; Gilead: Consultancy; Sanofi: Honoraria; Seattle Genetics: Honoraria; Bayer: Research Funding.

Abstract: High CD33 expression in acute myeloid leukemia (AML) with mutated NPM1 provides a rationale for the evaluation of gemtuzumab ozogamicin (GO) in this AML entity. We conducted a randomized trial to evaluate GO in combination with intensive induction and consolidation therapy in NPM1-mutated AML. PATIENTS AND METHODS Between May 2010 and September 2017, patients ≥ 18 years old and considered eligible for intensive therapy were randomly assigned up front for induction therapy with idarubicin, cytarabine, etoposide, and all- trans-retinoic acid with or without GO. The early ( P = .02) primary end point of event-free survival (EFS) was evaluated 6 months after completion of patient recruitment. RESULTS Five hundred eighty-eight patients were randomly assigned (standard arm, n = 296; GO arm, n = 292). EFS in the GO arm was not significantly different compared with that in the standard arm (hazard ratio, 0.83; 95% CI, 0.65 to 1.04; P = .10). The early death rate during induction therapy was 10.3% in the GO arm and 5.7% in the standard arm ( P = .05). Causes of death in both arms were mainly infections. The cumulative incidence of relapse (CIR) in patients achieving a complete remission (CR) or CR with incomplete hematologic recovery (CRi) was significantly reduced in the GO arm compared with the standard arm ( P = .005), with no difference in the cumulative incidence of death ( P = .80). Subgroup analysis revealed a significant beneficial effect of GO in female, younger (≤ 70 years), and FLT3 internal tandem duplication–negative patients with respect to EFS and CIR. CONCLUSION The trial did not meet its early primary end point of EFS, mainly as a result of a higher early death rate in the GO arm. However, in patients achieving CR/CRi after induction therapy, significantly fewer relapses occurred in the GO compared with the standard arm.

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: Clonal hematopoiesis of indeterminate potential (CHIP) is defined by the detection of mutations in genes like DNA methyltransferase 3A (DNMT3A) and has recently been described to occur in healthy people and to predispose them to myeloid malignancies. DNMT3A is frequently mutated in acute myeloid leukemia (AML) and mutations have been detected in CD3 positive T-cells of some AML patients. In these patients DNMT3A mutations are early events that are likely to arise from CHIP. It is unknown how a history (hx) of CHIP influences the characteristics of AML patients and their response to therapy. We studied this question on the basis of a large cohort of DNMT3A mutated AML patients. Patients and Methods: 171 DNMT3A mutated AML patients (aged 18-87 years) were included in our study. 127 patients were treated intensively in trials of the AMLSHG and AMLSG. 34 patients received non-intensive therapy and for 10 patients the therapy is unknown. 148 patients carried a mutation at arginine R882. At the time of diagnosis and relapse samples were further sequenced for 54 genes involved in leukemia with next generation sequencing (NGS) on the Illumina platform. Library preparation of diagnostic samples was performed with the TruSight Myeloid sequencing panel (Illumina). T-cells (CD3+ CD11b- CD14- CD33-) were purified by flow cytometry from AML samples at the time of diagnosis. DNMT3A mutational analysis of T-cell samples and of mononuclear cells during remission or at relapse was performed also with ultra-deep sequencing using customized DNMT3A NGS primers. Presence of a DNMT3A mutation in sorted T cell populations was used as an indicator of a hx of CHIP. Results: A total of 40 patients (23%) were found to have the DNMT3A mutation in mononuclear cells and T-cells (hx of CHIP), while 131 patients (77%) had a DNMT3A mutation in mononuclear cells, but not T-cells (control cohort). Comparing these two patient cohorts revealed that significantly more patients in the hx of CHIP cohort had secondary AML (p=0.009), were older (p=0.005) and less likely to receive intensive treatment (p=0.047) while other clinical parameters did not significantly differ. Analysing the mutational profile of 54 genes revealed that the number of mutations per patient between these 2 groups was similar (median 5 vs 4 mutations, p=0.39). Patients with a hx of CHIP were significantly more likely to harbour mutations in TET2 (p=0.006), RUNX1 (p=0.004), SF3B1 (p=0.049), U2AF1 (p=0.015) but less likely to be NPM1 mutated (p=0.005). There was no significant difference in the allelic burden of DNMT3A in the CHIP hx (mean 43.6) vs control group (mean 44.5). The mean variant allele frequencies of DNMT3A, RUNX1 and NPM1 were highest (44, 45 and 43 respectively) as compared to other mutated genes like IDH1, IDH2 and FLT3 (32, 37 and 34). In relapse samples (n=11), the identical DNMT3A mutation could always be identified. However, patients with a hx of CHIP (n=2) had comparable allelic frequencies compared to diagnosis of mutated DNMT3A ( 〈 10% difference), but not NPM1 ( 〉 10% difference), while 7 out of 9 patients in the control group had a change in the allelic frequency at the time of relapse (mostly reduction). In all remission samples DNMT3A mutations could be identified with ultra-deep NGS but with variable allelic frequencies (0.13-50.01% in the control group, 0.25-70.14% in the hx of CHIP group). In the cohort of patients with intensive therapy there was no difference in CR rates between hx of CHIP and control groups (82 vs 90%, p=0.31). Overall survival (OS) was not influenced by a hx of CHIP (whole cohort: HR 1.09; 95%CI 0.67-1.79; P=.73; intensively treated cohort: HR 0.72; 95%CI 0.34-1.51; P=.38). Relapse-free survival (RFS) was also not different in the hx of CHIP vs the control group (HR 1.06; 95%CI 0.58-1.93; P=.85; intensively treated cohort only HR 0.91; 95%CI 0.46-1.78; P=.78). However, when looking at the influence of allogeneic stem cell transplantations (HSCT) on outcome in intensively treated patients, patients with a hx of CHIP showed abenefit from HSCT (HR 0.082; 95%CI 0.009-0.75; P= 0.027 Figure 1A) as compared to the control group (HR 0.68; 95%CI 0.39-1.21; P= 0.19, Figure 1B). Conclusion: AML patients with a hx of CHIP, as defined by mutated DNMT3A in T-cells, show a distinct clinical and molecular profile and may benefit from HSCT. Figure 1A. Figure 1A. Figure 1B. Figure 1B. Disclosures 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. Fiedler:Pfizer, Amgen, Kolltan: Research Funding; Teva, Amgen, Astellas: Other: Travel Grant; Karyopharm: Research Funding. Schlenk:Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Research Funding; Arog: Honoraria, Research Funding; Teva: Honoraria, Research Funding; Boehringer-Ingelheim: Honoraria; Janssen: Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Research Funding.

Abstract: Molecular measurable residual disease (MRD) assessment is not established in approximately 60% of acute myeloid leukemia (AML) patients because of the lack of suitable markers for quantitative real-time polymerase chain reaction. To overcome this limitation, we established an error-corrected next-generation sequencing (NGS) MRD approach that can be applied to any somatic gene mutation. The clinical significance of this approach was evaluated in 116 AML patients undergoing allogeneic hematopoietic cell transplantation (alloHCT) in complete morphologic remission (CR). Targeted resequencing at the time of diagnosis identified a suitable mutation in 93% of the patients, covering 24 different genes. MRD was measured in CR samples from peripheral blood or bone marrow before alloHCT and identified 12 patients with persistence of an ancestral clone (variant allele frequency [VAF] & gt;5%). The remaining 96 patients formed the final cohort of which 45% were MRD+ (median VAF, 0.33%; range, 0.016%-4.91%). In competing risk analysis, cumulative incidence of relapse (CIR) was higher in MRD+ than in MRD− patients (hazard ratio [HR], 5.58; P & lt; .001; 5-year CIR, 66% vs 17%), whereas nonrelapse mortality was not significantly different (HR, 0.60; P = .47). In multivariate analysis, MRD positivity was an independent negative predictor of CIR (HR, 5.68; P & lt; .001), in addition to FLT3-ITD and NPM1 mutation status at the time of diagnosis, and of overall survival (HR, 3.0; P = .004), in addition to conditioning regimen and TP53 and KRAS mutation status. In conclusion, NGS-based MRD is widely applicable to AML patients, is highly predictive of relapse and survival, and may help refine transplantation and posttransplantation management in AML patients.

Abstract: For many years, clinical management of Acute Myeloid Leukemia (AML) has relied on patient classification into molecular groups, mostly defined by fusion genes. Recent insights of AML genomes have uncovered extended heterogeneity implicating 〉 100 recurrently mutated genes, many of which are infrequently mutated. In each patient, multiple mutations are present defining unique genetic and clonal constellations. This genetic diversity significantly complicates the translation of molecular findings into routine clinical practice. We present our full analysis on the genomic characterization of 1540 AML patients enrolled in clinical trials of the German-Austrian AML Study Group. Together with cytogenetic profiling we map 5234 pathogenic lesions across 77 genomic loci. Amongst these, we characterise a cluster of hotspot mutations in the MYC oncogene. Overall we find ≥1 driver mutation in 96% patients, and ≥2 in 85%. The earliest mutations in AML evolution implicate genes mutated in age-related clonal hematopoiesis (DNMT3A, ASXL1, TET2) or fusion genes, followed by ordered acquisition of mutations in transcription, chromatin or splicing regulators. RTK/RAS mutations frequently represent late events with evidence of parallel evolution in 14% of AML. We formally model genomic structure and find that AML is subdivided in at least 11 molecular and clinically distinct classes defined by t(15;17), t(8;21), inv(16)/t(16;16), t(6;9), inv(3)/t(3;3), AML defined by MLL- rearrangements, CEBPAbi-allelic, NPM1, TP53/complex karyotype, AML with chromatin/splicing factor mutations, and provisionally AML with 〈 3 aneuploidies. ~87% of patients with acquired mutations are molecularly classified. Each class is defined by a distinct subset of genetic lesions, with evidence of preferred order in mutation acquisition, thus guiding future development of minimal residual disease and combination therapy protocols. 19% (n=291) of patients were classified in the chromatin/spliceosome class. In this group, mutations in splicing factor genes and/or RUNX1 cluster with mutations in chromatin modifiers (ASXL1, EZH2, STAG2, MLLPTD). Patients in this group mostly represented Intermediate risk AML (ELN recommendations), were older, with lower WBC/blasts, inferior response rates to induction chemotherapy, poor long-term clinical outlook, higher rates of secondary AML and MDS-related morphology. Compared to classes defined by fusion genes, classes defined by genes are considerably more complex. We explore whether variability of clinical response (complete remission, relapse, relapse related mortality and overall survival) is at least in part accounted for by the extended genomic landscape. We find that the recurrent secondary and tertiary genotypes (often implicating rare genes/mutation-hotspots) markedly redefine clinical response and long-term curability beyond those predicted by single classifier lesions. To this effect, we apply global statistical models to calculate the contributions of genomic variables to overall risk whilst taking into account demographic, diagnostic and treatment factors. We find that gene-by-gene interactions are associated with additive as well as epistatic effects to patients risk, and contribute ~10% of relapse related mortality risk. We build prognostication models tailored to individual patients molecular, demographic and clinical variables at time of diagnosis and deliver more accurate risk predictions. For example, on the basis of the composite genomic and clinical profiles subsets of patients categorized as Favorable/Intermediate risk AML show risk estimates associated with adverse prognosis. Such patients are evaluated for therapeutic protocol selection tailored to higher risk groups (transplant at first CR instead of relapse), and ascertained for overall survival benefit. We apply same approaches for high-risk patients associated with favorable profiles and collectively deliver a paradigm of personally tailored risk assessment coupled with appropriate selection of therapeutic intervention. Taken together comprehensive genome profiling shows that genetic heterogeneity in AML is not random. Characterization of the extended genetic framework beyond single classifier lesions, informs future strategies for personalized prognostication, minimal residual disease monitoring and combination therapy protocols. Disclosures Schlenk: Janssen: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Research Funding; Boehringer-Ingelheim: Honoraria; Novartis: Honoraria, Research Funding; Daiichi Sankyo: Membership on an entity's Board of Directors or advisory committees; Arog: Honoraria, Research Funding; Teva: Honoraria, Research Funding. Campbell:14M genomics: Other: Co-founder and consultant.