Overlapping features of therapy-related and de novo NPM1-mutated AML.

NPM 1-mutated acute myeloid leukemia (AML) shows unique features. However, the characteristics of "therapy-related" NPM1-mutated AML (t-NPM1 AML) are poorly understood. We compared the genetics, transcriptional profile, and clinical outcomes of t-NPM1 AML, de novo NPM1-mutated AML (dn-NPM1 AML), and therapy-related AML (t-AML) with wild-type NPM1 (t-AML). Normal karyotype was more frequent in t-NPM1 AML (n = 78/96, 88%) and dn-NPM1 (n = 1986/2394, 88%) than in t-AML (n = 103/390, 28%; P < .001). DNMT3A and TET2 were mutated in 43% and 40% of t-NPM1 AML (n = 107), similar to dn-NPM1 (n = 88, 48% and 30%; P > 0.1), but more frequently than t-AML (n = 162; 14% and 10%; P < 0.001). Often mutated in t-AML, TP53 and PPM1D were wild-type in 97% and 96% of t-NPM1 AML, respectively. t-NPM1 and dn-NPM1 AML were transcriptionally similar, (including HOX genes upregulation). At 62 months of median follow-up, the 3-year overall survival (OS) for t-NPM1 AML (n = 96), dn-NPM1 AML (n = 2394), and t-AML (n = 390) were 54%, 60%, and 31%, respectively. In multivariable analysis, OS was similar for the NPM1-mutated groups (hazard ratio [HR] 0.9; 95% confidence interval [CI], 0.65-1.25; P = .45), but better in t-NPM1 AML than in t-AML (HR, 1.86; 95% CI, 1.30-2.68; P < .001). Relapse-free survival was similar between t-NPM1 and dn-NPM1 AML (HR, 1.02; 95% CI, 0.72-1.467; P = .90), but significantly higher in t-NPM1 AML versus t-AML (HR, 1.77; 95% CI, 1.19-2.64; P = .0045). t-NPM1 and dn-NPM1 AML have overlapping features, suggesting that they should be classified as a single disease entity.

CEBPA mutations in 4708 patients with acute myeloid leukemia: differential impact of bZIP and TAD mutations on outcome.

Biallelic mutations of the CEBPA gene (CEBPAbi) define a distinct entity associated with favorable prognosis; however, the role of monoallelic mutations (CEBPAsm) is poorly understood. We retrospectively analyzed 4708 adults with acute myeloid leukemia (AML) who had been recruited into the Study Alliance Leukemia trials, to investigate the prognostic impact of CEBPAsm. CEBPA mutations were identified in 240 patients (5.1%): 131 CEBPAbi and 109 CEBPAsm (60 affecting the N-terminal transactivation domains [CEBPAsmTAD] and 49 the C-terminal DNA-binding or basic leucine zipper region [CEBPAsmbZIP]). Interestingly, patients carrying CEBPAbi or CEBPAsmbZIP shared several clinical factors: they were significantly younger (median, 46 and 50 years, respectively) and had higher white blood cell (WBC) counts at diagnosis (median, 23.7 × 109/L and 35.7 × 109/L) than patients with CEBPAsmTAD (median age, 63 years, median WBC 13.1 × 109/L; P < .001). Co-mutations were similar in both groups: GATA2 mutations (35.1% CEBPAbi; 36.7% CEBPAsmbZIP vs 6.7% CEBPAsmTAD; P < .001) or NPM1 mutations (3.1% CEBPAbi; 8.2% CEBPAsmbZIP vs 38.3% CEBPAsmTAD; P < .001). CEBPAbi and CEBPAsmbZIP, but not CEBPAsmTAD were associated with significantly improved overall (OS; median 103 and 63 vs 13 months) and event-free survival (EFS; median, 20.7 and 17.1 months vs 5.7 months), in univariate and multivariable analyses. Additional analyses revealed that the clinical and molecular features as well as the favorable survival were confined to patients with in-frame mutations in bZIP (CEBPAbZIP-inf). When patients were classified according to CEBPAbZIP-inf and CEBPAother (including CEBPAsmTAD and non-CEBPAbZIP-inf), only patients bearing CEBPAbZIP-inf showed superior complete remission rates and the longest median OS and EFS, arguing for a previously undefined prognostic role of this type of mutation.

Prediction of complete remission and survival in acute myeloid leukemia using supervised machine learning.

Achievement of complete remission signifies a crucial milestone in the therapy of acute myeloid leukemia (AML) while refractory disease is associated with dismal outcomes. Hence, accurately identifying patients at risk is essential to tailor treatment concepts individually to disease biology. We used nine machine learning (ML) models to predict complete remission and 2-year overall survival in a large multicenter cohort of 1,383 AML patients who received intensive induction therapy. Clinical, laboratory, cytogenetic and molecular genetic data were incorporated and our results were validated on an external multicenter cohort. Our ML models autonomously selected predictive features including established markers of favorable or adverse risk as well as identifying markers of so-far controversial relevance. De novo AML, extramedullary AML, double-mutated CEBPA, mutations of CEBPA-bZIP, NPM1, FLT3-ITD, ASXL1, RUNX1, SF3B1, IKZF1, TP53, and U2AF1, t(8;21), inv(16)/t(16;16), del(5)/del(5q), del(17)/del(17p), normal or complex karyotypes, age and hemoglobin concentration at initial diagnosis were statistically significant markers predictive of complete remission, while t(8;21), del(5)/del(5q), inv(16)/t(16;16), del(17)/del(17p), double-mutated CEBPA, CEBPA-bZIP, NPM1, FLT3-ITD, DNMT3A, SF3B1, U2AF1, and TP53 mutations, age, white blood cell count, peripheral blast count, serum lactate dehydrogenase level and hemoglobin concentration at initial diagnosis as well as extramedullary manifestations were predictive for 2-year overall survival. For prediction of complete remission and 2-year overall survival areas under the receiver operating characteristic curves ranged between 0.77-0.86 and between 0.63-0.74, respectively in our test set, and between 0.71-0.80 and 0.65-0.75 in the external validation cohort. We demonstrated the feasibility of ML for risk stratification in AML as a model disease for hematologic neoplasms, using a scalable and reusable ML framework. Our study illustrates the clinical applicability of ML as a decision support system in hematology.

Use of Minimal Residual Disease in Acute Myeloid Leukemia Therapy.

OPINION STATEMENT: The expanding availability of minimal or more precisely measurable residual disease (MRD) assessment in acute myeloid leukemia (AML) with its possible implications for therapeutic decisions is of high interest to clinicians treating AML patients. A variety of mostly retrospective studies have shown that AML patients with a positive MRD test, assessed by different techniques at defined cutoffs and time-points, are at significantly higher risk of relapse and experience shorter overall survival compared to MRD-negative patients. How this valuable information may be adapted in the daily routine of patients' treatment to distinguish individuals who need more aggressive therapy from the ones who can be spared additional therapy to avoid treatment-related toxicities is still being investigated. With the exception of MRD analyses in acute promyelocitic leukemia (APL), the clinical implications of MRD tests for the individual AML patient are still mostly unknown. We currently lack hard evidence that MRD-based therapy modulation during treatment or pre-emptive intervention in MRD-positive patients after therapy would improve outcomes in non-APL AML patients. These questions will be evaluated in prospective randomized clinical trials. Today, however, some conclusions with regard to MRD assessment in AML can be drawn from the published data and are reviewed in this article.

Mimicking clinical trials with synthetic acute myeloid leukemia patients using generative artificial intelligence.

Clinical research relies on high-quality patient data, however, obtaining big data sets is costly and access to existing data is often hindered by privacy and regulatory concerns. Synthetic data generation holds the promise of effectively bypassing these boundaries allowing for simplified data accessibility and the prospect of synthetic control cohorts. We employed two different methodologies of generative artificial intelligence - CTAB-GAN+ and normalizing flows (NFlow) - to synthesize patient data derived from 1606 patients with acute myeloid leukemia, a heterogeneous hematological malignancy, that were treated within four multicenter clinical trials. Both generative models accurately captured distributions of demographic, laboratory, molecular and cytogenetic variables, as well as patient outcomes yielding high performance scores regarding fidelity and usability of both synthetic cohorts (n = 1606 each). Survival analysis demonstrated close resemblance of survival curves between original and synthetic cohorts. Inter-variable relationships were preserved in univariable outcome analysis enabling explorative analysis in our synthetic data. Additionally, training sample privacy is safeguarded mitigating possible patient re-identification, which we quantified using Hamming distances. We provide not only a proof-of-concept for synthetic data generation in multimodal clinical data for rare diseases, but also full public access to synthetic data sets to foster further research.

Prognostic impact of CEBPA mutational subgroups in adult AML.

Despite recent refinements in the diagnostic and prognostic assessment of CEBPA mutations in AML, several questions remain open, i.e. implications of different types of basic region leucin zipper (bZIP) mutations, the role of co-mutations and the allelic state. Using pooled primary data analysis on 1010 CEBPA-mutant adult AML patients, a comparison was performed taking into account the type of mutation (bZIP: either typical in-frame insertion/deletion (InDel) mutations (bZIPInDel), frameshift InDel or nonsense mutations inducing translational stop (bZIPSTOP) or single base-pair missense alterations (bZIPms), and transcription activation domain (TAD) mutations) and the allelic state (single (smCEBPA) vs. double mutant (dmCEBPA)). Only bZIPInDel patients had significantly higher rates of complete remission and longer relapse free and overall survival (OS) compared with all other CEBPA-mutant subgroups. Moreover, co-mutations in bZIPInDel patients (e.g. GATA2, FLT3, WT1 as well as ELN2022 adverse risk aberrations) had no independent impact on OS, whereas in non-bZIPInDel patients, grouping according to ELN2022 recommendations added significant prognostic information. In conclusion, these results demonstrate bZIPInDel mutations to be the major independent determinant of outcome in CEBPA-mutant AML, thereby refining current classifications according to WHO (including all dmCEBPA and smCEBPA bZIP) as well as ELN2022 and ICC recommendations (including CEBPA bZIPms).

Adaptation of the hydrocarbonoclastic bacterium Alcanivorax borkumensis SK2 to alkanes and toxic organic compounds: a physiological and transcriptomic approach.

The marine hydrocarbonoclastic bacterium Alcanivorax borkumensis is able to degrade mixtures of n-alkanes as they occur in marine oil spills. However, investigations of growth behavior and physiology of these bacteria when cultivated with n-alkanes of different chain lengths (C6 to C30) as the substrates are still lacking. Growth rates increased with increasing alkane chain length up to a maximum between C12 and C19, with no evident difference between even- and odd-numbered chain lengths, before decreasing with chain lengths greater than C19. Surface hydrophobicity of alkane-grown cells, assessed by determination of the water contact angles, showed a similar pattern, with maximum values associated with growth rates on alkanes with chain lengths between C11 and C19 and significantly lower values for cells grown on pyruvate. A. borkumensis was found to incorporate and modify the fatty acid intermediates generated by the corresponding n-alkane degradation pathway. Cells grown on distinct n-alkanes proved that A. borkumensis is able to not only incorporate but also modify fatty acid intermediates derived from the alkane degradation pathway. Comparing cells grown on pyruvate with those cultivated on hexadecane in terms of their tolerance toward two groups of toxic organic compounds, chlorophenols and alkanols, representing intensely studied organic compounds, revealed similar tolerances toward chlorophenols, whereas the toxicities of different n-alkanols were significantly reduced when hexadecane was used as a carbon source. As one adaptive mechanism of A. borkumensis to these toxic organic solvents, the activity of cis-trans isomerization of unsaturated fatty acids was proven. These findings could be verified by a detailed transcriptomic comparison between cultures grown on hexadecane and pyruvate and including solvent stress caused by the addition of 1-octanol as the most toxic intermediate of n-alkane degradation.

Retained functional normal and preleukemic HSCs at diagnosis are associated with good prognosis in DNMT3AmutNPM1mut AMLs.

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by high rate of relapse and mortality. Current chemotherapies whilst successful in eradicating blasts, are less effective in eliminating relapse-causing leukemic stem cells (LSCs). Although LSCs are usually identified as CD34+CD38- cells, there is significant heterogeneity in surface marker expression, and CD34- LSCs exist particularly in NPM1mut AMLs. By analyzing diagnostic primary DNMT3AmutNPM1mut AML samples, we suggest a novel flow cytometry sorting strategy particularly useful for CD34neg AML subtypes. To enrich for LSCs independently of CD34 status, positive selection for GPR56 and negative selection for NKG2D ligands are used. We show that the functional reconstitution capacity of CD34- and CD34+ LSCs as well as their transcriptomes are very similar which support phenotypic plasticity. Furthermore, we show that although CD34+ subpopulations can contain next to LSCs also normal and/or preleukemic hematopoietic stem cells (HSCs), this is not the case in CD34-GPR56+NKG2DL- enriched LSCs which thus can be isolated with high purity. Finally, we show that patients with AML, who retain at the time of diagnosis a reserve of normal and/or preleukemic HSCs in their bone marrow able to reconstitute immunocompromised mice, have significantly longer relapse-free and overall survival than patients with AML in whom functional HSCs are no longer detectable.

UBTF tandem duplications are rare but recurrent alterations in adult AML and associated with younger age, myelodysplasia, and inferior outcome.

Tandem-duplication mutations of the UBTF gene (UBTF-TDs) coding for the upstream binding transcription factor have recently been described in pediatric patients with acute myeloid leukemia (AML) and were found to be associated with particular genetics (trisomy 8 (+8), FLT3-internal tandem duplications (FLT3-ITD), WT1-mutations) and inferior outcome. Due to limited knowledge on UBTF-TDs in adult AML, we screened 4247 newly diagnosed adult AML and higher-risk myelodysplastic syndrome (MDS) patients using high-resolution fragment analysis. UBTF-TDs were overall rare (n = 52/4247; 1.2%), but significantly enriched in younger patients (median age 41 years) and associated with MDS-related morphology as well as significantly lower hemoglobin and platelet levels. Patients with UBTF-TDs had significantly higher rates of +8 (34% vs. 9%), WT1 (52% vs. 7%) and FLT3-ITD (50% vs. 20.8%) co-mutations, whereas UBTF-TDs were mutually exclusive with several class-defining lesions such as mutant NPM1, in-frame CEBPAbZIP mutations as well as t(8;21). Based on the high-variant allele frequency found and the fact that all relapsed patients analyzed (n = 5) retained the UBTF-TD mutation, UBTF-TDs represent early clonal events and are stable over the disease course. In univariate analysis, UBTF-TDs did not represent a significant factor for overall or relapse-free survival in the entire cohort. However, in patients under 50 years of age, who represent the majority of UBTF-mutant patients, UBTF-TDs were an independent prognostic factor for inferior event-free (EFS), relapse-free (RFS) and overall survival (OS), which was confirmed by multivariable analyses including established risk factors such as age and ELN2022 genetic risk groups (EFS [HR: 2.20; 95% CI 1.52-3.17, p < 0.001], RFS [HR: 1.59; 95% CI 1.02-2.46, p = 0.039] and OS [HR: 1.64; 95% CI 1.08-2.49, p = 0.020]). In summary, UBTF-TDs appear to represent a novel class-defining lesion not only in pediatric AML but also younger adults and are associated with myelodysplasia and inferior outcome in these patients.

Unsupervised meta-clustering identifies risk clusters in acute myeloid leukemia based on clinical and genetic profiles.

BACKGROUND: Increasingly large and complex biomedical data sets challenge conventional hypothesis-driven analytical approaches, however, data-driven unsupervised learning can detect inherent patterns in such data sets. METHODS: While unsupervised analysis in the medical literature commonly only utilizes a single clustering algorithm for a given data set, we developed a large-scale model with 605 different combinations of target dimensionalities as well as transformation and clustering algorithms and subsequent meta-clustering of individual results. With this model, we investigated a large cohort of 1383 patients from 59 centers in Germany with newly diagnosed acute myeloid leukemia for whom 212 clinical, laboratory, cytogenetic and molecular genetic parameters were available. RESULTS: Unsupervised learning identifies four distinct patient clusters, and statistical analysis shows significant differences in rate of complete remissions, event-free, relapse-free and overall survival between the four clusters. In comparison to the standard-of-care hypothesis-driven European Leukemia Net (ELN2017) risk stratification model, we find all three ELN2017 risk categories being represented in all four clusters in varying proportions indicating unappreciated complexity of AML biology in current established risk stratification models. Further, by using assigned clusters as labels we subsequently train a supervised model to validate cluster assignments on a large external multicenter cohort of 664 intensively treated AML patients. CONCLUSIONS: Dynamic data-driven models are likely more suitable for risk stratification in the context of increasingly complex medical data than rigid hypothesis-driven models to allow for a more personalized treatment allocation and gain novel insights into disease biology.

There are various ways in which clinicians can predict the risk of disease progression in patients with leukemia, helping them to treat the patients accordingly. However, these approaches are usually designed by human experts and might not fully capture the complexity of a patient's disease. Here, with a large cohort of patients with acute myeloid leukemia, we design an unsupervised machine learning model ­ a type of computer model that learns from patterns in data without human input­to separate these patients into subgroups according to risk. We identify four distinct groups which differ with regards to patient genetics, laboratory values, and clinical characteristics. These groups have differences in response to treatment and patient survival, and we validate our findings in another dataset. Our approach might help clinicians to better predict outcomes in patients with leukemia and make decisions on treatment.

Alterations of cohesin complex genes in acute myeloid leukemia: differential co-mutations, clinical presentation and impact on outcome.

Functional perturbations of the cohesin complex with subsequent changes in chromatin structure and replication are reported in a multitude of cancers including acute myeloid leukemia (AML). Mutations of its STAG2 subunit may predict unfavorable risk as recognized by the 2022 European Leukemia Net recommendations, but the underlying evidence is limited by small sample sizes and conflicting observations regarding clinical outcomes, as well as scarce information on other cohesion complex subunits. We retrospectively analyzed data from a multi-center cohort of 1615 intensively treated AML patients and identified distinct co-mutational patters for mutations of STAG2, which were associated with normal karyotypes (NK) and concomitant mutations in IDH2, RUNX1, BCOR, ASXL1, and SRSF2. Mutated RAD21 was associated with NK, mutated EZH2, KRAS, CBL, and NPM1. Patients harboring mutated STAG2 were older and presented with decreased white blood cell, bone marrow and peripheral blood blast counts. Overall, neither mutated STAG2, RAD21, SMC1A nor SMC3 displayed any significant, independent effect on clinical outcomes defined as complete remission, event-free, relapse-free or overall survival. However, we found almost complete mutual exclusivity of genetic alterations of individual cohesin subunits. This mutual exclusivity may be the basis for therapeutic strategies via synthetic lethality in cohesin mutated AML.

Mutated IKZF1 is an independent marker of adverse risk in acute myeloid leukemia.

Genetic lesions of IKZF1 are frequent events and well-established markers of adverse risk in acute lymphoblastic leukemia. However, their function in the pathophysiology and impact on patient outcome in acute myeloid leukemia (AML) remains elusive. In a multicenter cohort of 1606 newly diagnosed and intensively treated adult AML patients, we found IKZF1 alterations in 45 cases with a mutational hotspot at N159S. AML with mutated IKZF1 was associated with alterations in RUNX1, GATA2, KRAS, KIT, SF3B1, and ETV6, while alterations of NPM1, TET2, FLT3-ITD, and normal karyotypes were less frequent. The clinical phenotype of IKZF1-mutated AML was dominated by anemia and thrombocytopenia. In both univariable and multivariable analyses adjusting for age, de novo and secondary AML, and ELN2022 risk categories, we found mutated IKZF1 to be an independent marker of adverse risk regarding complete remission rate, event-free, relapse-free, and overall survival. The deleterious effects of mutated IKZF1 also prevailed in patients who underwent allogeneic hematopoietic stem cell transplantation (n = 519) in both univariable and multivariable models. These dismal outcomes are only partially explained by the hotspot mutation N159S. Our findings suggest a role for IKZF1 mutation status in AML risk modeling.

Analysis of Subset Chimerism for MRD-Detection and Pre-Emptive Treatment in AML.

Allogeneic hematopoietic stem cell transplantation (alloHCT) represents the only potentially curative treatment in high-risk AML patients, but up to 40% of patients suffer from relapse after alloHCT. Treatment of overt relapse poses a major therapeutic challenge and long-term disease control is achieved only in a minority of patients. In order to avoid post-allograft relapse, maintenance as well as pre-emptive therapy strategies based on MRD-detection have been used. A prerequisite for the implementation of pre-emptive therapy is the accurate identification of patients at risk for imminent relapse. Detection of measurable residual disease (MRD) represents an effective tool for early relapse prediction in the post-transplant setting. However, using established MRD methods such as multicolor flow cytometry or quantitative PCR, sensitive MRD monitoring is only applicable in about half of the patients with AML and advanced MDS undergoing alloHCT. Donor chimerism analysis, in particular when performed on enriched leukemic stem and progenitor cells, e.g. CD34+ cells, is a sensitive method and has emerged as an alternative option in the post alloHCT setting. In this review, we will focus on the current strategies for lineage specific chimerism analysis, results of pre-emptive treatment using this technology as well as future developments in this field.

Prevalence and variation of CHIP in patients with aggressive lymphomas undergoing CD19-directed CAR T-cell treatment.

Inflammation plays an important role in chimeric antigen receptor (CAR) T-cell therapy, especially in the pathophysiology of cytokine-release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). Clonal hematopoiesis of indetermined potential (CHIP) has also been associated with chronic inflammation. The relevance of CHIP in the context of CAR T-cell treatment is widely unknown. We evaluated the prevalence of CHIP, using a targeted deep sequencing approach, in a cohort of patients with relapsed/refractory (r/r) B-cell non-Hodgkin lymphoma before and after CAR T-cell treatment. The aim was to define the prevalence and variation of CHIP over time and to assess the influence on clinical inflammation syndromes (CRS/ICANS), cytopenia, and outcome. Overall, 32 patients were included. CHIP was found in 11 of 32 patients (34%) before CAR T-cell therapy. CHIP progression was commonly detected in the later course. Patients with CHIP showed a comparable response rate to CAR T-cell treatment but had an improved overall survival (not reached vs 265 days, P = .003). No significant difference was observed in terms of the occurrence and severity of CRS/ICANS, therapeutic use of tocilizumab and glucocorticosteroids, paraclinical markers of inflammation (with the exception of ferritin), or dynamics of hematopoietic recovery. CHIP is commonly observed in patients undergoing CD19-directed CAR T-cell therapy and is not associated with an inferior outcome.

Deep sequencing in CD34+ cells from peripheral blood enables sensitive detection of measurable residual disease in AML.

Monitoring of measurable residual disease (MRD) in patients with acute myeloid leukemia (AML) is predictive of disease recurrence and may identify patients who benefit from treatment intensification. Current MRD techniques rely on multicolor flow cytometry or molecular methods, but are limited in applicability or sensitivity. We evaluated the feasibility of a novel approach for MRD detection in peripheral blood (PB), which combines immunomagnetic preenrichment and fluorescence-activated cell sorting (FACS) for isolation of CD34+ cells with error-reduced targeted next-generation sequencing (NGS). For clinical validation, we retrospectively analyzed 429 PB and 55 bone marrow (BM) samples of 40 patients with AML or high-risk MDS, with/without molecular relapse based on CD34+ donor chimerism (DC), in complete remission after allogeneic stem cell transplantation. Enrichment of CD34+ cells for NGS increased the detection of mutant alleles in PB ∼1000-fold (median variant allele frequency, 1.27% vs 0.0046% in unsorted PB; P < .0001). Although a strong correlation was observed for the parallel analysis of CD34+ PB cells with NGS and DC (r = 0.8601), the combination of FACS and NGS improved sensitivity for MRD detection in dilution experiments ∼10-fold to levels of 10-6. In both assays, MRD detection was superior using PB vs BM for CD34+ enrichment. Importantly, NGS on CD34+ PB cells enabled prediction of molecular relapse with high sensitivity (100%) and specificity (91%), and significantly earlier (median, 48 days; range, 0-281; P = .0011) than by CD34+ DC or NGS of unsorted PB, providing additional time for therapeutic intervention. Moreover, panel sequencing in CD34+ cells allowed for the early assessment of clonal trajectories in hematological complete remission.

Point Mutations in the FLT3-ITD Region Are Rare but Recurrent Alterations in Adult AML and Associated With Concomitant KMT2A-PTD.

FLT3-ITD mutations are common druggable alterations in patients with acute myeloid leukemia (AML) and associated with poor prognosis. Beside typical ITD mutations, point mutations and deletions in the juxtamembrane domain (JMD) have been observed. However, due to the low frequency of these alterations, there is only limited information on molecular and clinical associations. To evaluate the prognostic impact of non-ITD mutations in the FLT3 JMD region, we analyzed a large cohort of 1,539 adult AML patients treated in different protocols of the Study Alliance Leukemia, using next-generation sequencing. Non-ITD point mutations and deletions within the FLT3 JMD were identified with a prevalence of ~1.23% (n = 19). Both FLT3-ITD and non-ITD mutations were associated with a higher rate of NPM1 (42%-61%; p < 0.001) and DNMT3A mutations (37%-43%; p < 0.001), as well as an increased percentage of peripheral blood (54%-65%) and bone marrow blast cells (74%; p < 0.001), compared to FLT3-wild-type patients. Most significantly, AML patients with FLT3 non-ITD mutations had a higher rate of concomitant KMT2A-PTD mutations (37.5%; p < 0.001) as compared to FLT3-ITD (7%) or FLT3-wild-type cases (4.5%). In a multivariable analysis, FLT3 non-ITD mutations were not an independent prognostic factor. However, patients with dual FLT3 non-ITD and KMT2A-PTD mutations showed a trend for inferior outcome, which points at a functional interaction in this subset of AML.

Molecular profiling and clinical implications of patients with acute myeloid leukemia and extramedullary manifestations.

BACKGROUND: Extramedullary manifestations (EM) are rare in acute myeloid leukemia (AML) and their impact on clinical outcomes is controversially discussed. METHODS: We retrospectively analyzed a large multi-center cohort of 1583 newly diagnosed AML patients, of whom 225 (14.21%) had EM. RESULTS: AML patients with EM presented with significantly higher counts of white blood cells (p < 0.0001), peripheral blood blasts (p < 0.0001), bone marrow blasts (p = 0.019), and LDH (p < 0.0001). Regarding molecular genetics, EM AML was associated with mutations of NPM1 (OR: 1.66, p < 0.001), FLT3-ITD (OR: 1.72, p < 0.001) and PTPN11 (OR: 2.46, p < 0.001). With regard to clinical outcomes, EM AML patients were less likely to achieve complete remissions (OR: 0.62, p = 0.004), and had a higher early death rate (OR: 2.23, p = 0.003). Multivariable analysis revealed EM as an independent risk factor for reduced overall survival (hazard ratio [HR]: 1.43, p < 0.001), however, for patients who received allogeneic hematopoietic cell transplantation (HCT) survival did not differ. For patients bearing EM AML, multivariable analysis unveiled mutated TP53 and IKZF1 as independent risk factors for reduced event-free (HR: 4.45, p < 0.001, and HR: 2.05, p = 0.044, respectively) and overall survival (HR: 2.48, p = 0.026, and HR: 2.63, p = 0.008, respectively). CONCLUSION: Our analysis represents one of the largest cohorts of EM AML and establishes key molecular markers linked to EM, providing new evidence that EM is associated with adverse risk in AML and may warrant allogeneic HCT in eligible patients with EM.

Differential impact of IDH1/2 mutational subclasses on outcome in adult AML: results from a large multicenter study.

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.

Impact of IDH1 and IDH2 mutational subgroups in AML patients after allogeneic stem cell transplantation.

BACKGROUND: The role of allogeneic hematopoietic cell transplantation (alloHCT) in acute myeloid leukemia (AML) with mutated IDH1/2 has not been defined. Therefore, we analyzed a large cohort of 3234 AML patients in first complete remission (CR1) undergoing alloHCT or conventional chemo-consolidation and investigated outcome in respect to IDH1/2 mutational subgroups (IDH1 R132C, R132H and IDH2 R140Q, R172K). METHODS: Genomic DNA was extracted from bone marrow or peripheral blood samples at diagnosis and analyzed for IDH mutations with denaturing high-performance liquid chromatography, Sanger sequencing and targeted myeloid panel next-generation sequencing, respectively. Statistical as-treated analyses were performed using R and standard statistical methods (Kruskal-Wallis test for continuous variables, Chi-square test for categorical variables, Cox regression for univariate and multivariable models), incorporating alloHCT as a time-dependent covariate. RESULTS: Among 3234 patients achieving CR1, 7.8% harbored IDH1 mutations (36% R132C and 47% R132H) and 10.9% carried IDH2 mutations (77% R140Q and 19% R172K). 852 patients underwent alloHCT in CR1. Within the alloHCT group, 6.2% had an IDH1 mutation (43.4% R132C and 41.4% R132H) and 10% were characterized by an IDH2 mutation (71.8% R140Q and 24.7% R172K). Variants IDH1 R132C and IDH2 R172K showed a significant benefit from alloHCT for OS (p = .017 and p = .049) and RFS (HR = 0.42, p = .048 and p = .009) compared with chemotherapy only. AlloHCT in IDH2 R140Q mutated AML resulted in longer RFS (HR = 0.4, p = .002). CONCLUSION: In this large as-treated analysis, we showed that alloHCT is able to overcome the negative prognostic impact of certain IDH mutational subclasses in first-line consolidation treatment and could pending prognostic validation, provide prognostic value for AML risk stratification and therapeutic decision making.