Acute myeloid leukemia (AML) is a complex disease characterized by diverse molecular pathogenesis. Genetic alterations, including germline and somatic variants in the DEAD box helicase 41 gene ( DDX41) located on chromosome 5 play an increasingly recognized role. Recent reports indicate that 5% of intensively treated adult AML patients harbor DDX41 germline mutations ( DDX41MutGL), and their precise impact remains incompletely understood. These studies suggest that DDX41MutGL may define a distinct biological subgroup, associated with e.g. older age, male gender, low blast, and low white blood cell count (WBC). To further elucidate the role of DDX41 in AML, we performed a retrospective analysis of 906 unselected adult AML patients from the AML Cooperative Group (AMLCG) registry (2015-2022), by targeted sequencing. As DDX41MutGL are typically “null mutations”, leading to reduced DDX41 expression, we additionally investigated whether DDX41 gene expression correlates or resembles the observed germline phenotype. Our analysis encompassed >1000 independent gene expression profiles (GSE37642, GSE14468, and GSE106291) of intensively treated adult AML patients. We identified a sub-cohort with low DDX41 ( DDX41-low) expression and re-analyzed them with next-generation sequencing to detect DDX41MutGL. Additionally, we correlated gene expression data with 198 DNA methylation profiles (from patients who had undergone both analyses) to identify potential epigenetic mechanisms underlying DDX41-low expression. Among the 906 patients (median age 61 years; range 18-98 years), we identified 11 unrelated individuals with suspected DDX41MutGL (VAF > 40%). Notably, the overall frequency of DDX41MutGL in the German unselected AML patient population was merely 1%, considerably lower than previously reported (p<0.0001 in comparison to Duployez et al. 2022). Characteristically, DDX41MutGL patients in this cohort were mostly male (73%), with a median age of 67 years displaying low WBC (average 1,3G/l) and a normal karyotype (80%) at initial diagnosis. Remarkably, our analysis of independent large gene expression cohorts revealed a pattern of phenotypic association in patients with decreased DDX41 expression ( DDX41-low) closely resembling those with DDX41MutGL. These associations were consistent across different datasets and included e.g. older age, low WBC, and low blast count. Furthermore, DDX41-low patients had poor overall survival. The DDX41-low subgroup constituted almost 10% of all AML patients, surpassing the reported frequencies of DDX41MutGL. In an exploratory pilot study, we screened 48 patients exhibiting the lowest DDX41 gene expression by sequencing the coding regions for DDX41 mutations but found none, suggesting alternative mechanisms, such as copy number changes, non-coding alterations or aberrant DNA methylation patterns that may replicate the phenotypic effects associated with DDX41MutGL. To further elucidate this mechanism, we correlated the gene expression of DDX41 with all DNA methylation loci (CpG sites covered by the EPIC array) on chromosome 5 using Spearman correlation analysis (GSE106291). We plotted the correlations against the sorted chromosome length, identifying a peak at a specific location corresponding to the PCDH (Protocadherin) cluster (Figure). Thus, DDX41-low was associated with reduced methylation at the PCDH loci and linked to higher PCDH gene expression. Across several data sets, we confirmed the association between higher PCDH cluster gene expression and low DDX41 expression. In summary, our study reveals that the frequency of DDX41MutGL in an unselected population of German AML patients is considerably lower than previously reported. Additionally, we found that apart from DDX41MutGL, DDX41-low exhibits a comparable clinical profile and is linked to specific methylation and gene expression patterns, with a notable emphasis on the PCDH complex located on chromosome 5. Understanding the functional implications of PCDH genes and their interaction with DDX41 in AML may significantly advance our knowledge of AML pathogenesis. Gaining insights into DDX41 alterations may open avenues for personalized therapeutic approaches and further prognostic stratification for AML patients with distinct molecular characteristics.

Clinical outcome of patients with acute myeloid leukemia (AML) is associated with demographic and genetic features. Although the associations of acquired genetic alterations with patients’ sex have been recently analyzed, their impact on outcome of female and male patients has not yet been comprehensively assessed. We performed mutational profiling, cytogenetic and outcome analyses in 1726 adults with AML (749 female and 977 male) treated on frontline Alliance for Clinical Trials in Oncology protocols. A validation cohort comprised 465 women and 489 men treated on frontline protocols of the German AML Cooperative Group. Compared with men, women more often had normal karyotype, FLT3 -ITD, DNMT3A , NPM1 and WT1 mutations and less often complex karyotype, ASXL1 , SRSF2 , U2AF1 , RUNX1 , or KIT mutations. More women were in the 2022 European LeukemiaNet intermediate-risk group and more men in adverse-risk group. We found sex differences in co-occurring mutation patterns and prognostic impact of select genetic alterations. The mutation-associated splicing events and gene-expression profiles also differed between sexes. In patients aged <60 years, SF3B1 mutations were male-specific adverse outcome prognosticators. We conclude that sex differences in AML-associated genetic alterations and mutation-specific differential splicing events highlight the importance of patients’ sex in analyses of AML biology and prognostication.

Secondary-type mutations (STM) are defined as alterations in ASXL1, BCOR, EZH2, SF3B1, SRSF2, STAG2, U2AF1, and ZRSR2 in the recent update of the WHO classification on myeloid neoplasms. The International Consensus Classification (ICC) extends its definition to also include alterations of RUNX1. Patients bearing STMs are considered adverse risk in the absence of other class-defining markers according to the recent update of the European LeukemiaNet (ELN) 2022 recommendations. However, it is unclear if all STMs convey an equally adverse prognostic effect or if individual STMs have a differential prognostic impact. We pooled data on molecular genetics, cytogenetics, and outcomes of 5311 newly diagnosed and intensively treated AML patients from previous randomized multicenter trials of the German SAL (n=1606), the German-Austrian AMLSG (n=1354, dataset from Gerstung et al., Nature Genetics 2017), the German AMLCG (n=1138), the French DATAML (n=1040), and the Czech CELL (n=173). Patients were retrospectively categorized into ELN2022. All analyses were carried out for WHO 2022 definitions (STMWHO) and ICC 2022 definitions (STMICC). We found 1485 (28%) of patients to harbor STMWHO and 1698 patients (32.0%) with STMICC. Patients with STMWHO and STMICC were significantly older than non-STM patients (median 60 vs 53 and 59 vs 52 years, p<0.001) and more frequently male (STMWHO: 62.5% and STMICC: 61.1% male vs 48.3% and 48.1%, p<0.001). STM-bearing patients had significantly higher rates of secondary AML (STMWHO: 19.8% and STMICC: 19.2% vs 6.9% and 6.3%) while de novo AML rates were significantly lower (STMWHO: 75.5% and STMICC: 75.8% vs 87.7% and 88.3%) compared to non-STM patients. Patients with STMs presented with significantly lower white blood cell count as well as significantly lower bone marrow and peripheral blood blast counts. After intensive induction therapy, 65.1% or 65.7% of patients with STMWHO or STMICC achieved complete remission (CR) compared to 77.2% or 77.7% of patients without STM according to either definition (OR 0.55 and p<0.001 for both). To test whether STMs constitute an individual risk group aside from ELN2022 adverse, these groups were separated. Patients with STMs and co-occurring defining favorable or intermediate risk features were assigned to ELN2022 favorable or intermediate risk, respectively. Patients with STM and no other class-defining alterations had longer event-free survival (EFS; STMWHO: 4.7 months, hazard ratio [HR] 1.66, p<0.001; STMICC: 4.9 months. HR 1.69, p<0.001) than ELN2022 adverse risk patients (3.0 months, HR 2.02, p<0.001, and 2.7 months, HR 2.12, p<0.001, respectively), longer relapse-free survival (RFS; STMWHO: 12.6 months, HR 1.53, p<0.001, STMICC: 11.9 months, HR 1.60, p<0.001 vs 8.0 months, HR 1.91, p<0.001 and 7.4 months, HR 1.93, p<0.01, respectively), and longer overall survival (OS; STMWHO: 14.6 months, HR 1.64, p<0.01 and STMICC: 14.7 months, HR 1.68, p<0.01 vs 9.5 months, HR 2.09, p<0.001 and 8.3 months, HR 2.22, p<0.001, respectively). The odds of achieving CR were significantly decreased for alterations in ASXL1, BCOR, SF3B1, SRSF2, STAG2, U2AF1, or RUNX1 compared to wildtype (univariable OR range: 0.38-0.68; BCOR p=0.003; all other p<0.001), with no significant differences for EZH2 (OR: 0.87, p=0.387) or ZRSR2 (OR: 0.96, p=0.882). Median EFS was significantly reduced for patients harboring alterations in ASXL1, BCOR, SF3B1, SRSF2, STAG2, U2AF1, or RUNX1 (HR range: 1.17-1.79; STAG2 p=0.017, all other p<0.001) while there was no difference for EZH2 (HR: 1.11, p=0.167) or ZRSR2 (HR: 1.17, p=0.232) compared to wildtype patients. Significantly reduced median RFS was found for patients with altered ASXL1, BCOR, SF3B1, SRSF2, U2AF1, and RUNX1 (HR range: 1.28-1.88, BCOR p=0.007, SF3B1 p=0.005, all other p<0.001) while EZH2, STAG2, and ZRSR2 showed no significant differences (HR range: 0.93-1.17). Finally, OS was significantly reduced for patients harboring alterations in ASXL1, BCOR, SF3B1, SRSF2, U2AF1, and RUNX1 (HR range: 1.26-1.87, BCOR p=0.002, all other p<0.001) again with no difference for alterations of EZH2, STAG2, and ZRSR2 (HR range: 1.16-1.28). Our analysis highlights that STMs represent an unfavorable risk level between the ELN2022 intermediate and adverse categories while contrasts between individual STMs exist, as not all alterations convey the same degree of adverse prognostic impact.

Introduction: In 2022, the ELN risk classification for AML was updated for the second time. One of the major novelties of the ELN2022 is that all secondary-type mutations (STMs, i.e., mutations in the genes SRSF2, SF3B1, U2AF1, ZRSR2, ASXL1, EZH2, BCOR, and STAG2) were now added to the adverse risk characteristics. However, a pertinent question also raised by the ELN expert panel is whether STMs abrogate the positive prognostic value of co-occurring, favorable NPM1 mutations. Aim: The aim of this study was to analyze the prognostic value of STMs in AML patients (pts) who also harbor an NPM1 mutation. Methods: We investigated a pooled cohort of 936 NPM1-mutated AML pts who were treated in previously reported multicenter trials of the Study Alliance Leukemia or the AML Cooperative Group. Eligibility was determined based on diagnosis of non-APL, age ≥ 18 years, NPM1 mutation detected in targeted sequencing, curative treatment intent, and available biomaterial at diagnosis. Standard techniques for chromosome banding and fluorescence-in-situ-hybridization (FISH) were used for karyotyping. Next-generation panel sequencing was performed to detect genetic alterations that are recurrently found in myeloid neoplasms. Results: In our multicenter cohort of 936 NPM1-mutated AML pts, median follow-up for the entire cohort was 8.0 years. We found 125 patients (13.4%) harboring at least one STM ( SRSF2 [n=48; 5.1%], STAG2 [n=32; 3.2%], EZH2 [n=22, 2.4%], BCOR [n=16; 1.7%], SF3B1 [n=13; 1.4%], ASXL1 [n=12; 1.3%], ZRSR2 [n=5; 0.5%], and U2AF1 [n=4; 0,4%]). A comparison of pretreatment clinical and genetic features revealed that pts with a STM were significantly older ( p=.003, median 59 vs. 55 years), had lower white blood cell counts ( p<.001, 22.2*10 9/L vs. 39.7*10 9/L,) and platelet counts ( p<.001, 46.5*10 9/L vs. 65.0 10 9/L). The strongest pair-wise associations between gene mutations were observed between U2AF1 and RUNX1 ( p<.001) as well as SRSF2 and IDH2 ( p<.001). With respect to outcome, complete remission (CR) rate did not differ significantly between NPM1-mutated patients with or without additional STMs ( p=.41, 74.4% vs. 77.7%, OR 0.83 [95%-CI 0.54-1.29]). Median RFS for NPM1-mutated pts with STMs was 32.9 months (95%-CI: 13.0-46.0) while patients without STMs had a median RFS of 24.3 months (95%-CI: 18.7-33.3) corresponding to a HR of 1.04 ( p=0.80, 95%-CI 0.79-1.37; Figure A). Median OS for NPM1-mutated pts with or without STMs was 27.2 months (95%-CI: 14.2-49.0) and 29.1 months (95%-CI: 23.5-41.4), respectively, corresponding to a HR of 1.11 ( p=.37, 95%-CI 0.88-1.41; Figure B). To focus solely on the impact of STMs, we subsequently excluded patients with co-occurring mutations in TP53 or myelodysplasia-related cytogenetics, which all define an ELN adverse risk. Again, we observed no differences in CR rate ( p=.54, 78% vs. 75.4%), RFS ( p=.59, median 33.2 months vs. 26.6 months), or OS ( p=.33, median 27.4 month vs. 32.6 month) between NPM1-mutated patients with or without STMs. Next, we restricted our analysis to pts who are classified favorable risk according to ELN2022. Again, we found no significant outcome differences based on the STM status (unmutated vs. mutated: CR rate, 80% vs. 70.7% [ p=.072]; RFS, median 49.7 months vs. 46.0 months [ p=.702]; OS, median 45.3 months vs. 59.8 months [ p=.092]). Conclusion: NPM1 mutations rank as the second most frequent mutations in AMLand the most common in patients with a normal karyotype and serve as an established favorable prognostic marker. Our data from a large cohort demonstrate that additional STMs have no adverse effect on the clinical outcome of NPM1-mutated patients. As a result, these patients should still be considered ELN favorable risk.

Mutations in RUNX1 ( RUNX1mut) occur in ~15% of intensively treated AML cases. RUNX1mut have no specific hotspot and various types of alteration are observed. The European LeukemiaNet (ELN) risk stratification assigns adverse prognosis to RUNX1mut if they do not co-occur with favorable-risk genotypes. Considering the biological complexity of RUNX1 it seems implausible that all alterations have similar consequences. Using clinical and genetic variables, we developed a prognostic risk stratification model for ELN adverse-risk RUNX1mut AML patients. We combined data from five groups, totaling 609 patients with intensively treated RUNX1mut AML, to develop the model. Our training set included 448 patients treated on trials of the AML Cooperative Group (AMLCG; Herold et al, Leukemia, 2020; (n=178)), AML Study Group (Gerstung et al, NEJM, 2016; (n=116)) and Study Alliance Leukemia (n=154). Patients from the Munich Leukemia Laboratory (MLL; (n=107)) and of the Alliance group (trials NCT00048958, NCT00899223, NCT00900224; Support: U10CA180821, U10CA180882, U24CA196171; https://acknowledgments.alliancefound.org; (n=54)) served as independent validation cohorts. Additionally, 955 patients without RUNX1mut treated on AMLCG trials served as controls. Patients with t(15;17), prior treatment, or RUNX1mut with co-occurring favorable-risk genotypes according to ELN 2017 were excluded. Differences between RUNX1mut patients and controls were investigated using univariate logistic regression. Testing was performed using likelihood ratio tests and adjusted for study group. Univariate analyses were adjusted for multiple testing using the Benjamini-Hochberg procedure. We obtained risk prediction models using multivariate Cox regression. Missing values were imputed using the missForest approach. Model selection was performed using forward selection based on the Bayesian information criterion. Cut-offs were based on the 25 th- 50 th- and 75 th-percentile score values obtained in the training data. Performance was evaluated using Kaplan-Meier curves. For internal validation Harrell's C index was estimated using cross-study validation. For external validation, the final risk prediction models were separately applied to the external datasets. RUNX1mut were more common in older, male patients and sAML (table). White blood cells, lactate dehydrogenase and bone marrow blasts were lower in RUNX1mut patients. Mutations in several myelodysplasia-related genes were enriched in RUNX1mut patients ( ASXL1, BCOR, BCORL1, EZH2, KMT2A, PHF6, and STAG2, SF3B1, SRSF2, and U2AF1), whereas DNMT3A, NPM1 and FLT3 were more frequently altered in controls. A strong association with mutations of the splicing factor complex was identified (49% vs. 13%, p<0.0001). Contradicting previous reports, we found no association with IDH mutations. The risk prediction score we obtained for OS is as follows: 0.03054 x age (y) + 0.74996 x adverse MRC + 0.43779 x FLT3-ITD + 0.00317 x WBC count (10^9/L) - 0.00158 x platelet count (10^9/L) + 0.37401 x NRAS-mutation, where the obtained cut-off values are: <1.592 (low risk); 1.592 to 2.303 (moderate risk) >2.303 (high risk). Binary variables are coded as 0 or 1. Harrell's C index estimated using internal validation was 0.6. Kaplan-Meier curves estimated using the training set suggest strong differences in survival between the risk categories. Median overall survival (OS) was 2.5, 1.0 and 0.6 years for low-, intermediate-, and high-risk. External validation using the Alliance cohort shows similar results (Figure). Results obtained for the MLL cohort show smaller differences. However, we still observe clear separation of risk groups with a significant difference between low- and high-risk groups (adjusted p-value: 0.0266). Scores for relapse-free survival (RFS) as well as for OS and RFS censored for allogeneic transplant show similar results. We analyzed a large collection of intensively treated RUNX1mut AML patients and observed heterogenous outcomes that could be predicted by applying few variables (age, MRC-score, FLT3/NRAS mutation-status, and WBC/platelet count). The OS of RUNX1mut high-risk patients is discouraging, highlighting the unmet need of these patients. In addition, our work demonstrates that ELN risk groups can be further stratified and that integrated approaches using routinely available variables can further advance risk prediction.

Background: Splicing factor (SF) mutations are recurrent events in Acute Myeloid Leukemia (AML) and identified in up to 20 % of adult patients. SF mutations lead to differential gene expression and alternative splicing events that contribute to pathogenesis. The characterization of these differential gene expression, splicing events and alternative isoforms using current standard sequencing approaches is difficult and requires bioinformatic reconstruction of the original molecules due to the short read length. Aims: To gain further insights into the functional consequences of SF mutations we applied long-read sequencing in a large cohort of AML patients with and without SF mutations to achieve an unprecedented level of accuracy. Methods: We analyzed 93 intensively treated adult AML patients enrolled in the multicenter German AML Cooperative Group (AMLCG) 2008 trial or Registry (DRKS00020816) between 2008 and 2019 and 6 healthy controls. Patients and controls were profiled for molecular features via targeted sequencing platforms. The ONT PromethION platform was used for transcriptome sequencing from full-length poly-A+ RNA. Samples were sequenced to a depth of at least 5 million reads and had to pass several quality parameters. 65 AML samples with the most frequent SF mutations passed our QC criteria including SRSF2 p.P95H (n=19), SRSF2 p.P95L (n=10), SRSF2 p.P95R (n=5), SRSF2 other (n=1), SF3B1 (n=12), SF3A1 (n=2), U2AF1 (n=7) and ZRSR2 (n=9). As control 28 AML samples without SF mutation and 6 samples from donors without myeloid malignancy or clonal hematopoiesis were analyzed. For the identification of differential gene expression, alternative transcripts, and novel isoforms we used the state-of-the-art workflow wf-transcriptomes epi2me labs from Oxford Nanopore. This pipeline provides a differential expression part based on DESeq and an isoform analysis part based on DEXSeq. Results: The initial analysis focused on the homogenous subgroup of male AML patients with the most common SF mutation SRSF2 p.P95H (n=19) and compared those to 16 male AML patients without SF mutations. Our analysis revealed 220 upregulated and 185 downregulated genes with at least two fold change and a FDR of ≤0.05 (Figure 1A). The DEXSeq analysis revealed also remarkable changes on splicing and alternative isoform expression between patients with hot spot mutation SRSF2 p.P95H and AML patients without SF mutation. We found 13,836 transcripts differentially expressed corresponding to 4,371 genes. A p-value <0.05 was defined as differentially expressed. Gene Ontology showed enrichment of gene sets associated with RNA-processing, histone modification and several other cellular processes. After the stageR analysis, 1,727 differentially used transcripts remained, which can be assigned to 66 different gene loci. Figure 1B shows an example of a sashimi plot for one of these genes. Summary/Outlook: To our knowledge, this is the first large scale analysis of splicing and isoform patterns in AML by long read sequencing. Our study demonstrates that individual splicing mutations result in unique patterns of differential gene expression, splicing and isoform profiles that are remarkably consistent between patients. Given the stability of the profiles and the early appearance of SF mutations as founding clones these findings may help to identify vulnerabilities and targets not only for the treatment of AML but also applying for premalignant myeloid states like CHIP, CCUS and other myeloid neoplasia like MDS. Comparative analyses of AML samples with other SF hot-spot mutations in SRSF2, SF3A1, SF3B1, U2AF1, ZRSR2 are currently ongoing as well as comparisons to healthy control samples.Keywords: Acute myeloid leukemia, Genomics, Alternative splicing, RNA-seq

Acute megakaryoblastic leukaemia (AMKL) is associated with poor prognosis. Limited information is available on its cytogenetics, molecular genetics and clinical outcome. We performed genetic analyses, evaluated prognostic factors and the value of allogeneic haematopoietic stem cell transplantation (allo-HSCT) in a homogenous adult AMKL patient cohort. We retrospectively analysed 38 adult patients with AMKL (median age: 58 years, range: 21-80). Most received intensive treatment in AML Cooperative Group (AMLCG) trials between 2001 and 2016. Cytogenetic data showed an accumulation of adverse risk markers according to ELN 2017 and an unexpected high frequency of structural aberrations on chromosome arm 1q (33%). Most frequently, mutations occurred in TET2 (23%), TP53 (23%), JAK2 (19%), PTPN11 (19%) and RUNX1 (15%). Complete remission rate in 33 patients receiving intensive chemotherapy was 33% and median overall survival (OS) was 33 weeks (95% CI: 21-45). Patients undergoing allo-HSCT (n = 14) had a superior median OS (68 weeks; 95% CI: 11-126) and relapse-free survival (RFS) of 27 weeks (95% CI: 4-50), although cumulative incidence of relapse after allo-HSCT was high (62%). The prognosis of AMKL is determined by adverse genetic risk factors and therapy resistance. So far allo-HSCT is the only potentially curative treatment option in this dismal AML subgroup.

Background and Methods In the German AMLCG Survivorship study, we included former AML patients from the AMLCG 1999, 2004, 2008 trials and the AMLCG patient registry, who survived at least 5 years after their initial diagnosis (AML-LTS). Our participants provided information on life satisfaction, quality of life as well as a number of psychological outcomes. Here, we analyzed the hospital anxiety and depression scale questionnaire and present results with respect to severity of observed anxiety (HADS-A) and depression scores (HADS-D), as well as an exploratory analysis to identify major risk factors. We analyzed our data using absolute and relative frequencies. Categorical variables were compared by chi-squared tests. Univariate and multivariable logistic regression models were fitted to analyze the risk of increased anxiety or depression scores. Results 427 AML-LTS participated in this study 5 to 18.6 years after their initial AML diagnosis. Overall, long term survivors showed HADS depression values between 0 and 19 with higher values indicating more severe depression. On average, former patients scored 4.35 (SD=3.8) points. Based on the classification proposed by Zigmond et al., 77.5% (331/420) showed normal depression scores (range: 0-7), 12.9% (55/420) borderline depression scores (8-10) and 8% (34/420) high scores (>10). Anxiety scores ranged between 0 and 20. Average score was 5.55 (SD: 4.01). Anxiety seem to be a more prominent problem in former AML patients. 73.3% (313/418) showed a normal score, 13.3% (57/418) a borderline score and 11.2% (48/418) a high score. While depression severity was equally distributed between sexes (P >.05), anxiety is more prominent in women (male cases 10/182, 5.5% vs. female cases 38/236, 16.1%, P = .003). Older participants show a decreased risk for high (>10) anxiety scores (odds ratio per 10 years of age (OR): .776, 95% confidence interval (CI): .618-.970), but not for depression (P >.05). Time since initial diagnosis did not associate with depression or anxiety (P > .05). The equivalence income (household income in EUR, dependent on household size) was associated with depression risk (OR: .54, 95%CI: .34-.88, per 1000 EUR), but not with anxiety (P > .05). Changes in the occupational situation (due to AML) impacts the chance for high depression (P = .001) and high anxiety scores (P < .001). Especially, being unable to work at all showed an elevated risk for high depression (5/24, 21%) and anxiety (9/24, 37%) scores. Worsening of the participant's financial situation was associated with an increased risk for high depression (19/128, 14.8%, P < .001) and high anxiety (25/127, 19.7%, P < .001). Furthermore, AML- and therapy-related variables (de novo AML, cytogenetic risk, allogeneic stem cell transplantation vs chemotherapy only, as well as experiencing one or more relapses) were not associated with depression or anxiety (P > .05) in this univariate analysis. All factors analyzed above were also used as risk factors in multivariable logistic regression models, within a backward variable selection approach with likelihoods ratio test. The final model for increased depression scores (HADS-D >10) contained the equivalence income (P = .056) as well as change in the financial situation (OR: 2.7, 95%CI: 1.28-5.69, P = .009) (Figure 1A). The latter confirmed the univariate finding that worsening financial situation is a risk factor for increased depression risk in long term survivors. The final model for increased anxiety scores (HADS-A >10) confirmed female sex (OR: 2.79, 95%CI: 1.29-6.02, P = .009), change in the occupational situation (P < .001, ORs are given in Figure 1B for the individual characteristics) as major risk factors for increased anxiety. Experiencing one or more relapses after AML seems to reduce the risk for anxiety (OR: .23, 95%CI: .08-.64, P = .005) (Figure 1B). Discussion Our data shows that anxiety and depression are relevant health problems for ca. 20%-25% of long-term survivors. Furthermore, women seems to be more prone to exhibit anxiety after AML. Interestingly, experiencing at least one relapse seems to reduce the chance for increased anxiety. The association of occupational and/or financial situation with increased anxiety or depression risk suggests a need for the management of these factors to mitigate adverse effects. Overall, our data may be useful to guide aftercare for former AML patients with respect to their psychological well-being. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Durch modernere Behandlungsoptionen hat sich die Prognose der akuten myeloischen Leukämie (AML) verbessert. Dadurch gewinnen Spätfolgen der Erkrankung und ihrer Behandlung immer mehr an Bedeutung. Zurzeit ist keine umfassende Nachsorgeempfehlung verfügbar, da die Datengewinnung unter anderem durch die relative Seltenheit der Erkrankung erschwert wird. Aus Untersuchungen von Langzeitüberlebenden verschiedener anderer Tumorentitäten sind bereits häufig auftretende gesundheitliche Spätfolgen und Problembereiche bekannt. Einige davon konnten auch bei AML-Überlebenden identifiziert werden. Aus psychosozialer Sicht können basierend auf den vorhandenen Daten eine erhöhte Prävalenz von Depression, Angst und Fatigue sowie vermehrte finanzielle Sorgen beobachtet werden. Zudem ist das Risiko für verschiedene somatische Komorbiditäten wie kardiovaskuläre Erkrankungen und Sekundärmalignome bei AML-Langzeitüberlebenden erhöht. Ergänzend zu regelmäßigen Kontrollen des Remissionsstatus sollten bei der Behandlung von Langzeitüberlebenden einer AML auch psychosoziale und somatische Begleit- und Folgeerkrankungen in der Nachsorge berücksichtigt werden. Außerdem sollte eine Ausweitung des intensiven Nachsorgeintervalls länger als fünf Jahre seit der Erstdiagnose erwogen werden. Weitere Studien zu Langzeitfolgen der Erkrankung sind zur Optimierung der Nachsorge von ehemaligen AML-Patienten nötig.

Introduction: As outcomes of patients with acute myeloid leukemia (AML) have improved, the fraction of patients surviving long-term is increasing. Information on somatic and psycho-social health consequences of AML and its treatment is sparse. The aim of our study was to perform a multi- dimensional analysis of health outcomes in AML long-term survivors (AML-LTS). This report focuses on secondary neoplasms (SN) after AML. Data on psychosocial outcomes and clonal hematopoiesis are presented by Telzerow et al., Görlich et al. and Krauss et al. Methods: We conducted a cross-sectional study including AML survivors who had been enrolled in clinical trials or the patient registry of the AML-CG study group, and were alive ≥5 years after initial diagnosis. Data concerning somatic health status were collected through patient questionnaires, assessments by the patients' physicians, and medical and laboratory reports. (DRKS00023991) Results: Data on somatic health status is available for 355 AML-LTS, 58% female, aged 28 to 93 years [y] (median 60y), 5 to 19y after initial diagnosis (median, 11.6y). Sixteen percent were initially diagnosed with secondary AML (sAML) or therapy-related AML (tAML) and 38% were treated with chemotherapy only while 62% had undergone allogeneic stem cell transplantation (alloHSCT). Fifty-five AML-LTS (15.5%) had developed SN after AML, that manifested 3 months to 18y after initial diagnosis (median, 12.4y), at age 31 to 83y (median 59y). Forty-two percent of AML-LTS with SN were female, 66% had undergone alloHSCT and 24% were initially diagnosed with sAML or tAML. At the time of study participation, 96% percent of all AML-LTS and 90 % of those diagnosed with SN fulfilled CR criteria (neutrophils >1G/L and thrombocytes >100G/L). Most common tumor types were non-melanoma skin cancers (30%), breast cancer (11%, all female, 25% of female AML-LTS with SN), head and neck cancers (7%) and, in 5% each, cancers of the esophagus, lung, bladder and prostate (9.4% of male AML-LTS with SN). Kaplan-Meier-Analyses show a 20%-risk of AML-LTS to develop SN 15 years after initial diagnosis, with no significant difference between patients treated by alloHSCT or chemotherapy only (log-rank p=.26; Fig. 1). However, 10y-risk was 5.6% and 15y-risk was 18.5% for AML-LTS treated with chemotherapy only, whereas for AML-LTS treated with alloHSCT 10y-risk was 12% and 15y-risk was 21%. AML-LTS >60y at the time of AML diagnosis had a significantly higher risk to develop secondary cancer, with a 10y-risk of 17.7% compared to 7.9% for AML-LTS aged 30-60y and 6.6% aged <30y at initial diagnosis (Fig. 2). Using Cox regression models, we analyzed the influence of age at AML diagnosis, sex, smoking status, sAML/tAML vs. de novo-AML, AML relapse (as time-dependent covariable) and treatment with alloHSCT vs. chemotherapy only on the risk of developing secondary malignancies after AML. Only older age at initial diagnosis (OR=1.03 per year, 95% CI: 1.01 - 1.05, p=.01) and male sex (OR=1.93, 95%-CI: 1.12 - 3.37, p=.02), but none of the diagnosis- and treatment-related factors significantly associated with higher risks for secondary malignancies. However, AML-LTS diagnosed with sAML/tAML tended to develop SN earlier after initial diagnosis than those diagnosed with de novo AML. Ten-years-risk was 9% and 15y-risk was 20% for AML-LTS diagnosed with de-novo-AML, whereas for AML-LTS diagnosed with sAML/tAML 10y-risk was 14% and 15y-risk was 23% (log-rank p=.08). Conclusion: Our study includes a large cohort of AML-LTS representing a wide age range, a long follow-up period of 5 to nearly 20 years, and heterogeneous therapy regimens (chemotherapy + autoHSCT vs. alloHSCT), close to real-life clinical settings. We found that the 15y-risk to develop a SN after AML is ~20%, with men having a 2-fold higher risk, and older age at the time of diagnosis being a negative predictor. We did not identify diagnosis- or treatment-related factors associated with increased risks for SN, although SN tended to occur earlier in patients who received alloHSCT compared to those treated with chemo only. We hope that our results may guide future recommendations for risk-adapted follow-up of AML-LTS. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

BACKGROUND: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. METHODS: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%). RESULTS: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. CONCLUSIONS: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.

Background With the increasing number of long-term survivors after acute myeloid leukemia (AML), long-term effects of the disease and its treatment become increasingly important. Due to various factors, like the rareness of the disease, guidelines for survivorship care plans are difficult to establish on the basis of existing studies. Results Looking at various studies including cancer survivors of various cancer entities, different problem areas have already been identified in long-term survivors. Some of those can be added to the data available for AML long-term survivors. From a psychosocial point of view, higher prevalence for depression, anxiety, fatigue and financial toxicity have been observed. In addition, the risk for certain somatic comorbidities, like cardiovascular comorbidities and secondary malignancies, is increased. Conclusion Aside from regular monitoring of the remission status, psychosocial and somatic comorbidities should also be monitored by the physician when caring for long-term survivors after AML. In addition, intensive aftercare intervals should be extended further than 5 years after initial diagnosis. Future research on long-term effects of the disease is still needed to optimize care for AML long-term survivors.

AbstractPrevious studies demonstrated that splicing factor mutations are recurrent events in hematopoietic malignancies with both clinical and functional implications. However, their aberrant splicing patterns in acute myeloid leukaemia remain largely unexplored. In this study we characterized mutations inSRSF2, U2AF1andSF3B1, the most commonly mutated splicing factors. In our clinical analysis of 2678 patients, splicing factor mutations showed inferior relapse-free and overall survival, however, these mutations did not represent independent prognostic markers. RNA-sequencing of 246 and independent validation in 177 patients revealed an isoform expression profile highly characteristic for each individual mutation, with several isoforms showing a strong dysregulation. By establishing a custom differential splice junction usage pipeline we accurately detected aberrant splicing in splicing factor mutated samples. Mutated samples were characterized predominantly by decreased junction usage. A large proportion of differentially used junctions were novel. Targets of splicing dysregulation included several genes with a known role in leukaemia. InSRSF2(P95H) mutants we further explored the possibility of a cascading effect through the dysregulation of the splicing pathway. We conclude that splicing factor mutations do 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 <60 years, estimated 5-year overall survival (OS) was 64% for ELN-2017 favorable, 42% for intermediate-risk and 20% for adverse-risk patients. Among 517 patients aged ≥60 years, corresponding 5-year OS rates were 37, 16, and 6%. Patients with biallelic 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.

The fusion genes CBFB / MYH11 and RUNX1 / RUNX1T1 block differentiation through disruption of the core binding factor (CBF) complex and are found in 10–15% of adult de novo acute myeloid leukemia (AML) cases. This AML subtype is associated with a favorable prognosis; however, nearly half of CBF-rearranged patients cannot be cured with chemotherapy. This divergent outcome might be due to additional mutations, whose spectrum and prognostic relevance remains hardly defined. Here, we identify nonsilent mutations, which may collaborate with CBF-rearrangements during leukemogenesis by targeted sequencing of 129 genes in 292 adult CBF leukemia patients, and thus provide a comprehensive overview of the mutational spectrum (‘mutatome’) in CBF leukemia. Thereby, we detected fundamental differences between CBFB/MYH11 - and RUNX1/RUNX1T1 -rearranged patients with ASXL2 , JAK2, JAK3, RAD21 , TET2, and ZBTB7A being strongly correlated with the latter subgroup. We found prognostic relevance of mutations in genes previously known to be AML-associated such as KIT , SMC1A, and DHX15 and identified novel, recurrent mutations in NFE2 (3%), MN1 (4%), HERC1 (3%), and ZFHX4 (5%). Furthermore, age >60 years, nonprimary AML and loss of the Y-chromosomes are important predictors of survival. These findings are important for refinement of treatment stratification and development of targeted therapy approaches in CBF leukemia.

Previous studies demonstrated that splicing factor mutations are recurrent events in hematopoietic malignancies with both clinical and functional implications. However, their aberrant splicing patterns in acute myeloid leukemia remain largely unexplored. In this study, we characterized mutations in SRSF2, U2AF1, and SF3B1, the most commonly mutated splicing factors. In our clinical analysis of 2678 patients, splicing factor mutations showed inferior relapse-free and overall survival, however, these mutations did not represent independent prognostic markers. RNA-sequencing of 246 and independent validation in 177 patients revealed an isoform expression profile which is highly characteristic for each individual mutation, with several isoforms showing a strong dysregulation. By establishing a custom differential splice junction usage pipeline, we accurately detected aberrant splicing in splicing factor mutated samples. A large proportion of differentially used junctions were novel, including several junctions in leukemia-associated genes. In SRSF2(P95H) mutants, we further explored the possibility of a cascading effect through the dysregulation of the splicing pathway. Furthermore, we observed a validated impact on overall survival for two junctions overused in SRSF2(P95H) mutants. We conclude that splicing factor mutations do not represent independent prognostic markers. However, they do have genome-wide consequences on gene splicing leading to dysregulated isoform expression of several genes.

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.