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The revised 2022 European LeukemiaNet (ELN) AML risk stratification system requires validation in large, homogeneously treated cohorts. We studied 1118 newly diagnosed AML patients (median age, 58 years; range, 18–86 years) who received cytarabine-based induction chemotherapy between 1999 and 2012 and compared ELN-2022 to the previous ELN-2017 risk classification. Key findings were validated in a cohort of 1160 mostly younger patients. ELN-2022 reclassified 15% of patients, 3% into more favorable, and 12% into more adverse risk groups. This was mainly driven by patients reclassified from intermediate- to adverse-risk based on additional myelodysplasia-related mutations being included as adverse-risk markers. These patients (n = 79) had significantly better outcomes than patients with other adverse-risk genotypes (5-year OS, 26% vs. 12%) and resembled the remaining intermediate-risk group. Overall, time-dependent ROC curves and Harrel’s C-index controlling for age, sex, and AML type (de novo vs. sAML/tAML) show slightly worse prognostic discrimination of ELN-2022 compared to ELN-2017 for OS. Further refinement of ELN-2022 without including additional genetic markers is possible, in particular by recognizing TP53-mutated patients with complex karyotypes as “very adverse”. In summary, the ELN-2022 risk classification identifies a larger group of adverse-risk patients at the cost of slightly reduced prognostic accuracy compared to ELN-2017.

Key Points Prediction of induction failure in AML is possible using cytogenetic data and a gene expression–based classifier.Integration of PS29MRC in the clinical routine or trials may be facilitated by gene expression analysis with the NanoString platform., Visual Abstract, Prediction of resistant disease at initial diagnosis of acute myeloid leukemia (AML) can be achieved with high accuracy using cytogenetic data and 29 gene expression markers (Predictive Score 29 Medical Research Council; PS29MRC). Our aim was to establish PS29MRC as a clinically usable assay by using the widely implemented NanoString platform and further validate the classifier in a more recently treated patient cohort. Analyses were performed on 351 patients with newly diagnosed AML intensively treated within the German AML Cooperative Group registry. As a continuous variable, PS29MRC performed best in predicting induction failure in comparison with previously published risk models. The classifier was strongly associated with overall survival. We were able to establish a previously defined cutoff that allows classifier dichotomization (PS29MRCdic). PS29MRCdic significantly identified induction failure with 59% sensitivity, 77% specificity, and 72% overall accuracy (odds ratio, 4.81; P = 4.15 × 10−10). PS29MRCdic was able to improve the European Leukemia Network 2017 (ELN-2017) risk classification within every category. The median overall survival with high PS29MRCdic was 1.8 years compared with 4.3 years for low-risk patients. In multivariate analysis including ELN-2017 and clinical and genetic markers, only age and PS29MRCdic were independent predictors of refractory disease. In patients aged ≥60 years, only PS29MRCdic remained as a significant variable. In summary, we confirmed PS29MRC as a valuable classifier to identify high-risk patients with AML. Risk classification can still be refined beyond ELN-2017, and predictive classifiers might facilitate clinical trials focusing on these high-risk patients with AML.

Acute myeloid leukemia (AML) with initial hyperleukocytosis is associated with high early mortality and a poor prognosis. The aims of this study were to delineate the underlying molecular landscape in the largest cytogenetic risk group, cytogenetically normal acute myeloid leukemia (CN-AML), and to assess the prognostic relevance of recurrent mutations in the context of hyperleukocytosis and clinical risk factors.The authors performed a targeted sequencing of 49 recurrently mutated genes in 56 patients with newly diagnosed CN-AML and initial hyperleukocytosis of ≥100 G/L treated in the AMLCG99 study. The median number of mutated genes per patient was 5. The most common mutations occurred in FLT3 (73%), NPM1 (75%), and TET2 (45%).The predominant pathways affected by mutations were signaling (84% of patients), epigenetic modifiers (75% of patients), and nuclear transport (NPM1; 75%) of patients. AML with hyperleukocytosis was enriched for molecular subtypes that negatively affected the prognosis, including a high percentage of patients presenting with co-occurring mutations in signaling and epigenetic modifiers such as FLT3 internal tandem duplications and TET2 mutations.Despite these unique molecular features, clinical risk factors, including high white blood count, hemoglobin level, and lactate dehydrogenase level at baseline, remained the predictors for overall survival and relapse-free survival in hyperleukocytotic CN-AML.

Clonal hematopoiesis (CH) is characterized by somatic mutations in blood cells of individuals without hematologic disease. While the mutational landscape of CH in peripheral blood (PB) has been well characterized, detailed analyses addressing its spatial and cellular distribution in the bone marrow (BM) compartment are sparse. We studied CH driver mutations in healthy individuals (n = 261) across different anatomical and cellular compartments. Variant allele frequencies were higher in BM than PB and positively correlated with the number of driver variants, yet remained stable during a median of 12 months of follow-up. In CH carriers undergoing simultaneous bilateral hip replacement, we detected ASXL1-mutant clones in one anatomical location but not the contralateral side, indicating intra-patient spatial heterogeneity. Analyses of lineage involvement in ASXL1-mutated CH showed enriched clonality in BM stem and myeloid progenitor cells, while lymphocytes were particularly involved in individuals carrying the c.1934dupG variant, indicating different ASXL1 mutations may have distinct lineage distribution patterns. Patients with overt myeloid malignancies showed higher mutation numbers and allele frequencies and a shifting mutation landscape, notably characterized by increasing prevalence of DNMT3A codon R882 variants. Collectively, our data provide novel insights into the genetics, evolution, and spatial and lineage-specific BM involvement of CH.

Mutations of the isocitrate dehydrogenase-1 (IDH1) and IDH2 genes are among the most frequent alterations in acute myeloid leukemia (AML) and can be found in ∼20% of patients at diagnosis. Among 4930 patients (median age, 56 years; interquartile range, 45-66) with newly diagnosed, intensively treated AML, we identified IDH1 mutations in 423 (8.6%) and IDH2 mutations in 575 (11.7%). Overall, there were no differences in response rates or survival for patients with mutations in IDH1 or IDH2 compared with patients without mutated IDH1/2. However, distinct clinical and comutational phenotypes of the most common subtypes of IDH1/2 mutations could be associated with differences in outcome. IDH1-R132C was associated with increased age, lower white blood cell (WBC) count, less frequent comutation of NPM1 and FLT3 internal tandem mutation (ITD) as well as with lower rate of complete remission and a trend toward reduced overall survival (OS) compared with other IDH1 mutation variants and wild-type (WT) IDH1/2. In our analysis, IDH2-R172K was associated with significantly lower WBC count, more karyotype abnormalities, and less frequent comutations of NPM1 and/or FLT3-ITD. Among patients within the European LeukemiaNet 2017 intermediate- and adverse-risk groups, relapse-free survival and OS were significantly better for those with IDH2-R172K compared with WT IDH, providing evidence that AML with IDH2-R172K could be a distinct entity with a specific comutation pattern and favorable outcome. In summary, the presented data from a large cohort of patients with IDH1/2 mutated AML indicate novel and clinically relevant findings for the most common IDH mutation subtypes.

Previous studies have demonstrated that splicing factor mutations are recurrent events in hematopoietic malignancies. Their clinical characteristics and aberrant splicing patterns have been explored in myelodysplasia, however, their functional consequences in acute myeloid leukaemia are largely unknown. The aim of this study was the comprehensive clinical and functional analysis of mutations in the three most commonly afflicted splicing factor genes: SRSF2 , U2AF1 and SF3B1 . To this end, we examined the prognostic role of splicing factor mutations in two large independent cohorts, encompassing a total of 2678 acute myeloid leukaemia patients treated with intensive chemotherapy. The clinical analysis was complemented by RNA-sequencing of 246 patients to identify targets of splicing dysregulation. Results were validated in an additional RNA-sequencing dataset of 177 patients. Patients with splicing factor mutations show inferior relapse-free and overall survival, however, these mutations do not represent independent prognostic markers. Differential isoform expression analysis revealed a characteristic expression profile for each splicing factor mutation with a strong dysregulation of several isoforms. Furthermore, by establishing a custom differential splice junction usage pipeline we accurately detected aberrant splicing in splicing factor mutated samples. Mutated samples were characterized by predominantly decreased splice junction utilization of a large number of genes. A large proportion of differentially used spliced junctions were novel. Targets of splicing dysregulation included several genes with a known role in acute myeloid leukaemia. In SRSF2 (P95H) mutants we further explored the possibility of a cascading effect through the dysregulation of the splicing pathway. Taken together, our findings suggest that splicing factor mutations does not represent independent prognostic markers. However, they do have genome-wide consequences on gene splicing leading to dysregulated isoform expression of several genes.

The revised 2017 European LeukemiaNet (ELN) recommendations for genetic risk stratification of acute myeloid leukemia have been widely adopted, but have not yet been validated in large cohorts of AML patients. We studied 1116 newly diagnosed AML patients (age range, 18–86 years) who had received induction chemotherapy. Among 771 patients not selected by genetics, the ELN-2017 classification re-assigned 26.5% of patients into a more favorable or, more commonly, a more adverse-risk group compared with the ELN-2010 recommendations. Forty percent of the cohort, and 51% of patients ≥60 years, were classified as adverse-risk by ELN-2017. In 599 patients CEBPA mutations or inv(16) had particularly favorable outcomes, while patients with mutated TP53 and a complex karyotype had especially poor prognosis. DNMT3A mutations associated with inferior OS within each ELN-2017 risk group. Our results validate the prognostic significance of the revised ELN-2017 risk classification in AML patients receiving induction chemotherapy across a broad age range. Further refinement of the ELN-2017 risk classification is possible.

In acute myeloid leukemia (AML), internal tandem duplications (ITDs) of FLT3 are frequent mutations associated with unfavorable prognosis. At diagnosis, the FLT3-ITD status is routinely assessed by fragment analysis, providing information about the length but not the position and sequence of the ITD. To overcome this limitation, we performed cDNA-based high-throughput amplicon sequencing (HTAS) in 250 FLT3-ITD positive AML patients, treated on German AML Cooperative Group (AMLCG) trials. FLT3-ITD status determined by routine diagnostics was confirmed by HTAS in 242 out of 250 patients (97%). The total number of ITDs detected by HTAS was higher than in routine diagnostics (n = 312 vs. n = 274). In particular, HTAS detected a higher number of ITDs per patient compared to fragment analysis, indicating higher sensitivity for subclonal ITDs. Patients with more than one ITD according to HTAS had a significantly shorter overall and relapse free survival. There was a close correlation between FLT3-ITD mRNA levels in fragment analysis and variant allele frequency in HTAS. However, the abundance of long ITDs (≥75nt) was underestimated by HTAS, as the size of the ITD affected the mappability of the corresponding sequence reads. In summary, this study demonstrates that HTAS is a feasible approach for FLT3-ITD detection in AML patients, delivering length, position, sequence and mutational burden of this alteration in a single assay with high sensitivity. Our findings provide insights into the clonal architecture of FLT3-ITD positive AML and have clinical implications.

Primary therapy resistance is a major problem in acute myeloid leukemia treatment. We set out to develop a powerful and robust predictor for therapy resistance for intensively treated adult patients. We used two large gene expression data sets (n=856) to develop a predictor of therapy resistance, which was validated in an independent cohort analyzed by RNA sequencing (n=250). In addition to gene expression markers, standard clinical and laboratory variables as well as the mutation status of 68 genes were considered during construction of the model. The final predictor (PS29MRC) consisted of 29 gene expression markers and a cytogenetic risk classification. A continuous predictor is calculated as a weighted linear sum of the individual variables. In addition, a cut off was defined to divide patients into a high-risk and a low-risk group for resistant disease. PS29MRC was highly significant in the validation set, both as a continuous score (OR=2.39, P=8.63·10−9, AUC=0.76) and as a dichotomous classifier (OR=8.03, P=4.29·10−9); accuracy was 77%. In multivariable models, only TP53 mutation, age and PS29MRC (continuous: OR=1.75, P=0.0011; dichotomous: OR=4.44, P=0.00021) were left as significant variables. PS29MRC dominated all models when compared with currently used predictors, and also predicted overall survival independently of established markers. When integrated into the European LeukemiaNet (ELN) 2017 genetic risk stratification, four groups (median survival of 8, 18, 41 months, and not reached) could be defined (P=4.01·10−10). PS29MRC will make it possible to design trials which stratify induction treatment according to the probability of response, and refines the ELN 2017 classification.

Background: AML is a disease affecting predominantly older patients (pts), but does occur across the entire age spectrum; younger adults [age Methods: We analyzed the molecular profiles of 2,823 adult AML pts enrolled onto clinical frontline protocols of 2 large cooperative study groups from 2 continents [US, Cancer and Leukemia Group B (CALGB)/Alliance for Clinical Trials in Oncology (Alliance), n=1743; Germany, AML Cooperative Group [AMLCG], n=1080] between 1986 and 2016. Treatment of all pts included intensive induction therapy, whereas pts enrolled on CALGB/Alliance protocols precluded allogeneic transplantation in 1 st complete remission. Pts in both cohorts were profiled for molecular features via targeted sequencing platforms. Frequencies of mutations genes and selected cytogenetic findings were then calculated in both datasets for the group of pts aged 18-24 y and for older pts by 5-year intervals until the age of 74 y and for pts older than 75 y. We also analyzed survival outcomes of 1,669 AML pts younger than 60 y using the same age intervals up to age 59 y. Results: Our side-by-side analysis shows remarkable congruence of results between German and US pt populations. Selected AML-associated gene mutations (mutation frequency ≥4%) and recurrent cytogenetic abnormalities followed 3 basic distribution patterns across the age spectrum (Fig. 1A): group 1 with increasing frequency with increasing age [ASXL1, BCOR, IDH1/2, RUNX1, SRSF2, TET2, TP53; complex karyotype and cytogenetically normal AML (CN-AML)]; group 2 with decreasing frequency with increasing age (CEBPA, EZH2, FLT3-TKD, GATA2, KIT, KRAS, PTPN11, NRAS, WT1; inv(16), t(8;21) and 11q23/KMT2A rearrangements) and group 3 with non-linear frequency distribution, which included the 3 most common AML-associated gene mutations (NPM1, DNMT3A, FLT3-ITD), SF3B1 and mutations in the cohesin complex genes (RAD21, SMC1A, SMC3, STAG2) (Fig. 1A). Notably, within the first 2 distribution groups, there seem to be no obvious age that could serve as a cut point separating age groups that are markedly different with regard to their molecular patterns. Particularly, this includes an age group that is commonly used for pt cohort definitions such as pts aged 18-39 y referred to as adolescent and young adults (AYA) or even treatment decisions and eligibility (eg, ages 60 or 65 and older for consideration as elderly AML). With respect to pt outcomes, expectedly, there was almost linear shortening of overall survival (OS) as age increased (p Conclusions: To our knowledge, this is the first large scale depiction of mutational patterns in AML inclusive of the entire adult age spectrum. Our international study demonstrates that patterns of individual mutations based on age are remarkably consistent between countries, and defy assortment based on typical age conventions. Given the continuous distribution of either increasing or decreasing frequency of many mutations, there are distinctly different mutational profiles for the youngest pts compared with older pts, however choosing a precise cut-off, such as age 39 for AYA pts or 59 for consideration as "younger AML", does not seem to be supported by our analyses. This observation supports a more personalized approach that also considers molecular subgroups in clinical practice instead of the age rigidity set in many clinical trials. *shared first: M.C.,K.L.; #last: T.H.,AK.E. Figure 1 Figure 1. Disclosures Berdel: Philogen S.p.A.: Consultancy, Current equity holder in publicly-traded company, Honoraria, Membership on an entity's Board of Directors or advisory committees. Hiddemann: F. Hoffmann-La Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Research Funding. Blachly: KITE: Consultancy, Honoraria; INNATE: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; AstraZeneca: Consultancy, Honoraria. Mims: Glycomemetics: Research Funding; Daiichi Sankyo: Consultancy, Research Funding; Aptevo: Research Funding; Leukemia and Lymphoma Society's Beat AML clinical study: Consultancy, Research Funding; Xencor: Research Funding; Kartos Pharmaceuticals: Research Funding; Genentech: Consultancy; Abbvie: Consultancy; BMS: Consultancy; Kura Oncology: Consultancy; Syndax Pharmaceuticals: Consultancy; BMS: Consultancy; Jazz Pharmaceuticals: Consultancy; Aptevo: Research Funding. Walker: Karyopharm Therapeutics: Current Employment, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company. Blum: Celyad Oncology: Research Funding; Forma Therapeutics: Research Funding; Xencor: Research Funding; Nkarta: Research Funding; Leukemia and Lymphoma Society: Research Funding; Abbvie: Honoraria; AmerisourceBergen: Honoraria; Syndax: Honoraria. Larson: Epizyme: Consultancy; Astellas: Consultancy, Research Funding; Gilead: Research Funding; CVS/Caremark: Consultancy; Takeda: Research Funding; Novartis: Research Funding; Rafael Pharmaceuticals: Research Funding; Cellectis: Research Funding. Stone: Syntrix/ACI: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Research Funding; Astellas: Membership on an entity's Board of Directors or advisory committees; BerGen Bio: Membership on an entity's Board of Directors or advisory committees; Actinium: Membership on an entity's Board of Directors or advisory committees; Elevate Bio: Membership on an entity's Board of Directors or advisory committees; Syndax: Membership on an entity's Board of Directors or advisory committees; Onconova: Consultancy; Jazz: Consultancy; Janssen: Consultancy; Innate: Consultancy; GlaxoSmithKline: Consultancy; Gemoab: Membership on an entity's Board of Directors or advisory committees; Foghorn Therapeutics: Consultancy; Boston Pharmaceuticals: Consultancy; Bristol Myers Squibb: Consultancy; AbbVie: Consultancy; Arog: Consultancy, Research Funding; Aprea: Consultancy; Amgen: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy; Agios: Consultancy, Research Funding; Celgene: Consultancy; Macrogenics: Consultancy. Byrd: Vincerx Pharmaceuticals: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Novartis, Trillium, Astellas, AstraZeneca, Pharmacyclics, Syndax: Consultancy, Honoraria; Newave: Membership on an entity's Board of Directors or advisory committees. Metzeler: Jazz Pharmaceuticals: Consultancy; Novartis: Consultancy; Daiichi Sankyo: Honoraria; Astellas: Honoraria; AbbVie: Honoraria; Pfizer: Consultancy; Celgene/BMS: Consultancy, Honoraria, Research Funding. Eisfeld: Karyopharm (spouse): Current Employment.

Background: Mutations in the protein tyrosine phosphatase gene PTPN11 (also known as SHP2) are found in approximately 10% of adult patients with acute myeloid leukemia (AML). A recent study reported that mutated PTPN11 associates with inferior response rates and shorter survival among intensively treated AML patients, independently of the ELN prognostic groups (Alfayez et al., Leukemia 2020). Earlier analyses of the genomic landscape of AML did not uncover a similar prognostic relevance of PTPN11 mutations. Therefore, our aim was to clarify the prognostic relevance of mutated PTPN11 variants in AML patients receiving intensive front-line therapy. Patients and Methods: We studied 1116 AML patients enrolled on two subsequent multicenter phase III trials of the German AML Cooperative Group (AML-CG 1999, NCT00266136; and AML-CG 2008, NCT01382147) who were genetically characterized by amplicon-based targeted next-generation sequencing (Herold et al., Leukemia 2020). All patients had received induction chemotherapy containing cytarabine and daunorubicin or mitoxantrone. Results: We identified 146 PTPN11 mutations in 114 of 1116 patients (10%). Mutations clustered in two hotspot regions (5': codons 52-79; n=108 and 3': codons 491-512, n=38) as previously reported. Associations of PTPN11 mutations with baseline clinical and genetic patient characteristics are shown in Figure A. PTPN11 mutations were most frequent in the European LeukemiaNet (ELN) "favorable" genetic risk group, and associated with higher leukocyte counts. Patients with mutated PTPN11more commonly had mutated NPM1, IDH1 and DNMT3A, and less frequently had FLT3-ITD, IDH2 and TP53 mutations, compared to patients with wild-type PTPN11. With regard to treatment outcomes, the rate of complete remission was similar among patients with mutated and wild-type PTPN11 (65% vs. 59%, P=.25). In univariate analyses, PTPN11-mutated patients had significantly longer relapse-free survival (RFS; 5-year estimate, 55% vs 33% for PTPN11-wild type patients; P=.001; Figure B) and tended to have longer overall survival (OS; 5-year estimate, 43% vs 32%; P=.06; Figure C). However, in multivariable models adjusting for age, sex, leukocyte count, AML type (de novo/sAML/tAML) and ELN-2017 genetic risk group, mutated PTPN11 no longer associated with RFS (hazard ratio [HR], 0.89, 95% confidence interval [CI], 0.63 - 1.27; P=0.53) or OS (HR, 1.03; 95% CI, 0.80 - 1.33; P=.79). Moreover, PTPN11 mutations did not significantly associate with RFS or OS within any of the ELN genetic risk groups. Finally, we detected no significant differences in baseline characteristics or outcomes between patients with PTPN11 mutations affecting the 5' hotspot region (n=82), the 3' hotspot region (n=21), or mutations at both hotspots (n=11). Conclusion: In our cohort of newly diagnosed and intensively treated AML patients, mutations in PTPN11 occurred in 10% and associated with prognostically favorable genetic characteristics such as mutated NPM1 and absence of FLT3-ITD and TP53mutations. Consequently, PTPN11 mutations were most commonly found within the ELN-2017 favorable risk category. While patients with PTPN11 mutations had relatively favorable survival outcomes, multivariable models suggest this observation is confounded by the frequent co-occurrence of known favorable genetic markers. Our data are in disagreement with a recently published study on 880 newly diagnosed patients that found an unfavourable prognostic impact of mutated PTPN11, particularly among the 410 patients who received intensive treatment. Possible explanations for these discrepant results include differences in treatment regimens between the two cohorts, as well as the play of chance when studying a relatively rare gene mutation in medium-sized cohorts. In summary, our data do not support a role of PTPN11 mutations as an adverse prognostic biomarker in newly diagnosed, intensively treated adult AML patients. Figure Disclosures Metzeler: Daiichi Sankyo: Honoraria; Otsuka Pharma: Consultancy; Pfizer: Consultancy; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy; Jazz Pharmaceuticals: Consultancy; Astellas: Honoraria. Subklewe:AMGEN: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Novartis: Consultancy, Research Funding; Janssen: Consultancy; Morphosys: Research Funding; Seattle Genetics: Research Funding; Roche AG: Consultancy, Research Funding; Gilead Sciences: Consultancy, Honoraria, Research Funding.

Key Points We report longitudinal mutational analyses of 2 patients with high-risk MDS and AML experiencing spontaneous disease remissions. Both patients had persistent clonal hematopoiesis during remission, harboring all but 1 of the mutations from the initial diagnostic sample.

Calcitonin receptor-like (CALCRL) is a G-protein-coupled neuropeptide receptor involved in the regulation of blood pressure, angiogenesis, cell proliferation, and apoptosis, and is currently emerging as a novel target for the treatment of migraine. This study characterizes the role of CALCRL in acute myeloid leukemia (AML). We analyzed CALCRL expression in collectively more than 1500 well-characterized AML patients from five international cohorts (AMLCG, HOVON, TCGA, Leucegene, and UKM) and evaluated associations with survival. In the AMLCG analytic cohort, increasing transcript levels of CALCRL were associated with decreasing complete remission rates (71.5%, 53.7%, 49.6% for low, intermediate, high CALCRL expression), 5-year overall (43.1%, 26.2%, 7.1%), and event-free survival (29.9%, 15.8%, 4.7%) (all P < 0.001). CALCRL levels remained associated with all endpoints on multivariable regression analyses. The prognostic impact was confirmed in all validation sets. Genes highly expressed in CALCRLhigh AML were significantly enriched in leukemic stem cell signatures and CALCRL levels were positively linked to the engraftment capacity of primary patient samples in immunocompromised mice. CRISPR- Cas9-mediated knockout of CALCRL significantly impaired colony formation in human myeloid leukemia cell lines. Overall, our study demonstrates that CALCRL predicts outcome beyond existing risk factors and is a potential therapeutic target in AML.

Acute myeloid leukemia (AML) is an aggressive hematologic neoplasm resulting from the malignant transformation of myeloid progenitors. Despite intensive chemotherapy leading to initial treatment responses, relapse caused by intrinsic or acquired drug resistance represents a major challenge. Here, we report that histone 3 lysine 27 demethylase KDM6A (UTX) is targeted by inactivating mutations and mutation-independent regulation in relapsed AML. Analyses of matched diagnosis and relapse specimens from individuals with KDM6A mutations showed an outgrowth of the KDM6A mutated tumor population at relapse. KDM6A expression is heterogeneously regulated and relapse-specific loss of KDM6A was observed in 45.7% of CN-AML patients. KDM6A-null myeloid leukemia cells were more resistant to treatment with the chemotherapeutic agents cytarabine (AraC) and daunorubicin. Inducible re-expression of KDM6A in KDM6A-null cell lines suppressed proliferation and sensitized cells again to AraC treatment. RNA expression analysis and functional studies revealed that resistance to AraC was conferred by downregulation of the nucleoside membrane transporter ENT1 (SLC29A1) by reduced H3K27 acetylation at the ENT1 locus. Our results show that loss of KDM6A provides cells with a selective advantage during chemotherapy, which ultimately leads to the observed outgrowth of clones with KDM6A mutations or reduced KDM6A expression at relapse.

Alterations of RUNX1 in acute myeloid leukemia (AML) are associated with either a more favorable outcome in the case of the RUNX1/RUNX1T1 fusion or unfavorable prognosis in the case of point mutations. In this project we aimed to identify genes responsible for the observed differences in outcome that are common to both RUNX1 alterations. Analyzing four AML gene expression data sets (n = 1514), a total of 80 patients with RUNX1/RUNX1T1 and 156 patients with point mutations in RUNX1 were compared. Using the statistical tool of mediation analysis we identified the genes CD109, HOPX, and KIAA0125 as candidates for mediator genes. In an analysis of an independent validation cohort, KIAA0125 again showed a significant influence with respect to the impact of the RUNX1/RUNX1T1 fusion. While there were no significant results for the other two genes in this smaller validation cohort, the observed relations linked with mediation effects (i.e., those between alterations, gene expression and survival) were almost without exception as strong as in the main analysis. Our analysis demonstrates that mediation analysis is a powerful tool in the identification of regulative networks in AML subgroups and could be further used to characterize the influence of genetic alterations.

Some patients with acute myeloid leukemia (AML) who are in complete remission after induction chemotherapy harbor persisting pre-leukemic clones, carrying a subset of leukemia-associated somatic mutations. There is conflicting evidence on the prognostic relevance of these clones for AML relapse. Here, we characterized paired pre-treatment and remission samples from 126 AML patients for mutations in 68 leukemia-associated genes. Fifty patients (40%) retained ≥1 mutation during remission at a VAF of ≥2%. Mutation persistence was most frequent in DNMT3A (65% of patients with mutations at diagnosis), SRSF2 (64%), TET2 (55%), and ASXL1 (46%), and significantly associated with older age (p

The CALM/AF10 fusion gene is found in various hematological malignancies including acute myeloid leukemia (AML), T-cell acute lymphoblastic leukemia and malignant lymphoma. We have previously identified the leukemia stem cell (LSC) in a CALM/AF10-driven murine bone marrow transplant AML model as B220+ lymphoid cells with B-cell characteristics. To identify the target cell for leukemic transformation or 'cell of origin of leukemia' (COL) in non-disturbed steady-state hematopoiesis, we inserted the CALM/AF10 fusion gene preceded by a loxP-flanked transcriptional stop cassette into the Rosa26 locus. Vav-Cre-induced panhematopoietic expression of the CALM/AF10 fusion gene led to acute leukemia with a median latency of 12 months. Mice expressing CALM/AF10 in the B-lymphoid compartment using Mb1-Cre or CD19-Cre inducer lines did not develop leukemia. Leukemias had a predominantly myeloid phenotype but showed coexpression of the B-cell marker B220, and had clonal B-cell receptor rearrangements. Using whole-exome sequencing, we identified an average of two to three additional mutations per leukemia, including activating mutations in known oncogenes such as FLT3 and PTPN11. Our results show that the COL for CALM/AF10 leukemia is a stem or early progenitor cell and not a cell of B-cell lineage with a phenotype similar to that of the LSC in CALM/AF10+ leukemia.

About 20-25% of patients with Acute Myeloid Leukemia (AML) have primary drug resistant disease and fail to achieve complete remission after induction therapy. These patients have an extremely poor prognosis and cannot reliably be identified prior to therapy with current methods. The aim of this work was to develop a predictive tool that can identify therapy resistant patients with high accuracy at the time of diagnosis. We used two independent Affymetrix gene expression (GE) data sets and standard molecular and clinical variables to develop a predictive score for response to cytarabine/anthracycline-based induction chemotherapy. The "training set 1" consisted of 407 adult AML patients enrolled in the AMLCG-1999 trial (GSE37642). Training set 2 included 449 adults treated in various HOVON trials (GSE6891). GE-based classifiers for primary treatment resistance were developed in training set 1 using a penalized logistic regression approach (Lasso). A cut off with a specificity of 90% was predefined in training set 1. Training set 2 was used to select the best classifier. The predictive score and cut off were then validated in a third, fully independent data set, comprising 260 patients enrolled in AMLCG-1999 and 2008 trials studied by RNA sequencing. Additionally, targeted amplicon sequencing data for 68 recurrently mutated genes in AML was available for training set 1 and the validation set. The final classifier (Predictive score 29 MRC - PS29MRC) consisted of 29 gene expression values and the cytogenetic risk group (defined according to the United Kingdom Medical Research Council (MRC) classification) and was calculated as a weighted sum of Lasso coefficients and predictor values. PS29MRC was a highly significant predictor of resistant disease in the validation set with an odds ratio of 2.32 (p=1.53x10-8, AUC: 0.75). We tested the signature in a multivariable model including all variables with univariate p-value Since we aimed to develop a clinically useful score, we categorized PS29MRC to distinguish between patients who have a high probability of refractory disease and those who are likely to benefit from induction therapy (complete remission or complete remission with incomplete hematologic recovery). By applying the predefined cut off, we were able to reach a specificity of 90% and sensitivity of 46% in the validation set (OR: 7.83; p=6.06x10-9). The accuracy of PS29MRC was 77%. In the multivariable model the categorized classifier was highly significant (OR: 4.45; p=0.00040) and only age and TP53 mutations were left as significant variables again. Within the cytogenetic subgroups favorable (n=14; refractory: n=0; responders: n=13), intermediate (n=189; refractory: n=43; responders: n=136) and adverse (n=49; refractory: n=29; responders: n=15) the classifier showed an accuracy of 100%, 78% and 66%, respectively. Furthermore, the classifier predicted survival and was able to unravel the intermediate MRC subgroup (Figure). Additionally, genes included in our predictive signature seem to be involved in AML pathogenesis and potentially actively contribute to mechanisms responsible for primary therapeutic resistance. For example MIR-155HG, an already known parameter of inferior outcome in AML, contributed significantly to PS29MRC. There are currently ongoing trials with the novel inhibitor Pevonedistat that aim to modulate this target in AML. In summary we were able to develop a predictive risk classifier summarizing 29 gene expression values and the MRC classification that outperformed all currently used methods to predict refractory disease in intensively treated adult AML patients. PS29MRC demonstrates that it is possible to identify patients at risk of treatment failure in AML at diagnosis with high specificity. Figure 1. Kaplan-Meier estimates showing overall survival of AML patients in the validation set according to PS29MRC Figure 1. Kaplan-Meier estimates showing overall survival of AML patients in the validation set according to PS29MRC Figure 2. Figure 2. Disclosures No relevant conflicts of interest to declare.

Background: Mutations in DNA methyltransferase 3A (DNMT3A) are common in acute myeloid leukemia (AML), affecting ~20% of patients (pts) and 30-40% of those with cytogenetically normal (CN-) AML. Although several groups have investigated their prognostic relevance, most studies focused on younger adults (=60 y) AML pts treated on German AML Cooperative Group (AMLCG) protocols, and studied the association between DNMT3A mutations and outcomes. Patients and Methods: We analyzed pretreatment blood or bone marrow specimens from 660 adult AML pts who received intensive induction chemotherapy on two consecutive phase III trials (AMLCG-1999, n=388, and AMLCG-2008, n=272; median age, 57y, range, 18-86y). Sequence variants in DNMT3A exons 7-23 and other genes known to be mutated in myeloid neoplasms were analyzed by multiplexed amplicon resequencing (Agilent Haloplex). Sequencing was performed on an Illumina MiSeq instrument using 2x250bp paired-end reads. Variants were classified as known/putative driver mutations, variants of unknown significance, or known germline polymorphisms based on published data including dbSNP, the Catalogue Of Somatic Mutations In Cancer (COSMIC) and The Cancer Genome Atlas (TCGA). Cytogenetic analyses were performed centrally. Results: We identified 223 DNMT3A mutations in 207/660 pts (31%), including 180/449 pts (40%) with intermediate-risk cytogenetics according to the MRC classification (P 1 type of DNMT3A mutation. DNMT3A mutations tended to be more frequent in older compared to younger pts (35% vs. 28%, P =.08) and were associated with female sex (38% vs 26% in males; P Conclusion: In our cohort of intensively treated AML pts covering a broad age range, we found that DNMT3A mutations associate with inferior survival and modulate the prognostic impact of mutated NPM1, confirming data recently reported by the MRC group (Gale et al., J Clin Oncol 33:2072). In contrast to this and other published reports, we observed no outcome differences between different types of DNMT3A mutations. Information on DNMT3A mutation status further refined the risk stratification of CN-AML based on the NPM1 mutated / FLT3-ITD negative genotype, supporting a role for DNMT3A mutations as a prognostic marker. Figure 1. Figure 1. Disclosures Subklewe: AMGEN Research (Munich): Research Funding. Krug:Boehringer Ingelheim: Research Funding; Novartis; BMS; Roche; Boehringer Ingelheim; Bayer: Honoraria; Sunesis: Speakers Bureau; Sunesis; Clavis Pharma; usa Pharma, Catapult Cell Therapy, Gilead, Roche: Membership on an entity's Board of Directors or advisory committees.

The fms-related tyrosine kinase 3 (FLT3) receptor has been extensively studied over the past two decades with regard to oncogenic alterations that do not only serve as prognostic markers but also as therapeutic targets in acute myeloid leukemia (AML). Internal tandem duplications (ITDs) became of special interest in this setting as they are associated with unfavorable prognosis. Because of sequence-dependent protein conformational changes FLT3-ITD tends to autophosphorylate and displays a constitutive intracellular localization. Here, we analyzed the effect of tyrosine kinase inhibitors (TKIs) on the localization of the FLT3 receptor and its mutants. TKI treatment increased the surface expression through upregulation of FLT3 and glycosylation of FLT3-ITD and FLT3-D835Y mutants. In T cell-mediated cytotoxicity (TCMC) assays, using a bispecific FLT3 × CD3 antibody construct, the combination with TKI treatment increased TCMC in the FLT3-ITD-positive AML cell lines MOLM-13 and MV4-11, patient-derived xenograft cells and primary patient samples. Our findings provide the basis for rational combination of TKI and FLT3-directed immunotherapy with potential benefit for FLT3-ITD-positive AML patients.