Sequential high-dose cytarabine and mitoxantrone (S-HAM) versus standard double induction in acute myeloid leukemia-a phase 3 study

Improving long-term outcomes with intensive induction chemotherapy for patients with AML

Intensive chemotherapy in combination with allogeneic hematopoietic cell transplantation and supportive care can induce long-term remissions in around 50% of acute myeloid leukemia patients eligible for intensive treatment. Several treatment optimization trials helped to refine schedule and dosing of the historic "7 + 3" combination. Together with the addition of novel agents, increased efficacy and tolerability led to improved long-term outcomes. Unsatisfactory outcomes in fit elderly patients and unfavorable genetic subgroups have raised the question of whether less-intensive venetoclax-based approaches may be beneficial as an alternative. Although tempting and worth exploring, this issue will remain controversial until the results of randomized comparisons appear. To date, intensive chemotherapy remains the only evident curative treatment option for long-term disease eradication in a fixed treatment time. With the advent of more novel agents and advances in minimal residual disease (MRD) detection and maintenance approaches, the face of intensive treatment could change in many ways. Several are being explored in clinical trials, such as (1) combinations of more than 1 novel agent with the intensive backbone, (2) head-to-head comparisons of novel agents, (3) replacement or dose reduction of cytotoxic components such as anthracyclines, and (4) MRD-guided escalation and de-escalation strategies. The combination of intensive treatment with individualized tailored innovative strategies will most certainly reduce treatment-related toxicities and increase the chances for long-term remission in the future.

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.

Validation and refinement of the 2022 European LeukemiaNet genetic risk stratification of acute myeloid leukemia

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.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13045-022-01339-8.

Prediction of life-threatening and disabling bleeding in patients with AML receiving intensive induction chemotherapy

Bleeding in patients with acute myeloid leukemia (AML) receiving intensive induction chemotherapy is multifactorial and contributes to early death. We sought to define the incidence and risk factors of grade 4 bleeding to support strategies for risk mitigation. Bleeding events were retrospectively assessed between day-14 and day +60 of induction treatment according to the World Health Organization (WHO) bleeding assessment scale, which includes grade 4 bleeding as fatal, life-threatening, retinal with visual impairment, or involving the central nervous system. Predictors were considered pretreatment or prior to grade 4 bleeding. Using multivariable competing-risk regression analysis with grade 4 bleeding as the primary outcome, we identified risk factors in the development cohort (n = 341), which were tested in an independent cohort (n = 143). Grade 4 bleeding occurred in 5.9% and 9.8% of patients in the development and validation cohort, respectively. Risk factors that were independently associated with grade 4 bleeding included baseline platelet count ≤40 × 109/L compared with >40 × 109/L, and baseline international normalized ratio of prothrombin time (PT-INR) >1.5 or 1.3 > 1.5 compared with ≤1.3. These variables were allocated points, which allowed for stratification of patients with low- and high-risk for grade 4 bleeding. Cumulative incidence of grade 4 bleeding at day+60 was significantly higher among patients with high- vs low-risk (development: 31 ± 7% vs 2 ± 1%; P < .001; validation: 25 ± 9% vs 7 ± 2%; P = .008). In both cohorts, high bleeding risk was associated with disseminated intravascular coagulation (DIC) and proliferative disease. We developed and validated a simple risk model for grade 4 bleeding, which enables the development of rational risk mitigation strategies to improve early mortality of intensive induction treatment.

Comparative efficacy and safety of eleven induction chemotherapy regimens for young adult patients with newly diagnosed acute myeloid leukemia: a network meta-analysis

The optimal induction chemotherapy regimens for young adult patients with newly diagnosed acute myeloid leukemia (AML) are not well-defined since the lack of direct comparisons between emerging treatments. Network meta-analysis (NMA) is a statistical tool to integrate direct and indirect evidence to evaluate the effect of multiple interventions. Thus, we conducted an NMA to systematically assess the efficacy and safety of different inductions for these patients. PubMed, Embase, Cochrane Library, and Web of Science were searched from establishment to 2020-03-11. Randomized controlled trials (RCTs) using different inductions were included. We deemed 11 trials eligible, including 11 inductions with 5052 participants. Relative risk (RR) and 95% confidence intervals (CIs) were calculated. In terms of complete remission (CR) rate, DAC ranked highest and was significantly higher than IA (RR = 1.27, 95% CI (1.09-1.48)) and DA (RR = 1.28, 95% CI (1.13-1.46)) (p < 0.05). The ranking of DA + Pioglitazone was second only to that of DAC, followed by HAA. For early mortality, HAD, HAA, and DA + GO were significantly higher than DA/IA (p < 0.05). DAC and DA + Pioglitazone showed similar early mortality compared to DA/IA (p > 0.05). Regarding incidence of early grade 3-4 infection, no significant differences between interventions were observed. To conclude, among the included 11 induction regimens, DAC was potentially the top choice for young adult patients with newly diagnosed AML, with highest CR rate, low early mortality, and incidence of early infection. DA + Pioglitazone and HAA also showed a superiority over the others to achieve higher CR rate, while caution should be kept in mind due to the higher early mortality of HAA.

Fusion gene detection by RNA-sequencing complements diagnostics of acute myeloid leukemia and identifies recurring NRIP1-MIR99AHG rearrangements

Identification of fusion genes in clinical routine is mostly based on cytogenetics and targeted molecular genetics, such as metaphase karyotyping, fluorescence in situ hybridization and reverse-transcriptase polymerase chain reaction. However, sequencing technologies are becoming more important in clinical routine as processing time and costs per sample decrease. To evaluate the performance of fusion gene detection by RNAsequencing compared to standard diagnostic techniques, we analyzed 806 RNA-sequencing samples from patients with acute myeloid leukemia using two state-of-the-art software tools, namely Arriba and FusionCatcher. RNA-sequencing detected 90% of fusion events that were reported by routine with high evidence, while samples in which RNA-sequencing failed to detect fusion genes had overall lower and inhomogeneous sequence coverage. Based on properties of known and unknown fusion events, we developed a workflow with integrated filtering strategies for the identification of robust fusion gene candidates by RNA-sequencing. Thereby, we detected known recurrent fusion events in 26 cases that were not reported by routine and found discrepancies in evidence for known fusion events between routine and RNA-sequencing in three cases. Moreover, we identified 157 fusion genes as novel robust candidates and comparison to entries from ChimerDB or Mitelman Database showed novel recurrence of fusion genes in 14 cases. Finally, we detected the novel recurrent fusion gene NRIP1- MIR99AHG resulting from inv(21)(q11.2;q21.1) in nine patients (1.1%) and LTN1-MX1 resulting from inv(21)(q21.3;q22.3) in two patients (0.25%). We demonstrated that NRIP1-MIR99AHG results in overexpression of the 3' region of MIR99AHG and the disruption of the tricistronic miRNA cluster miR-99a/let-7c/miR-125b-2. Interestingly, upregulation of MIR99AHG and deregulation of the miRNA cluster, residing in the MIR99AHG locus, are known mechanisms of leukemogenesis in acute megakaryoblastic leukemia. Our findings demonstrate that RNA-sequencing has a strong potential to improve the systematic detection of fusion genes in clinical applications and provides a valuable tool for fusion discovery.

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

Patients with IDH1-R132C have a lower complete remission rate and a trend toward reduced OS.

Patients with IDH2-R172K in the European LeukemiaNet intermediate/adverse-risk group have significantly better relapse-free survival and OS.

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.

A Clinically Applicable Gene Expression based Score predicts Resistance to Induction Treatment in Acute Myeloid Leukemia

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.

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.

Deep learning detects acute myeloid leukemia and predicts NPM1 mutation status from bone marrow smears

The evaluation of bone marrow morphology by experienced hematopathologists is essential in the diagnosis of acute myeloid leukemia (AML); however, it suffers from a lack of standardization and inter-observer variability. Deep learning (DL) can process medical image data and provides data-driven class predictions. Here, we apply a multi-step DL approach to automatically segment cells from bone marrow images, distinguish between AML samples and healthy controls with an area under the receiver operating characteristic (AUROC) of 0.9699, and predict the mutation status of Nucleophosmin 1 (NPM1)—one of the most common mutations in AML—with an AUROC of 0.92 using only image data from bone marrow smears. Utilizing occlusion sensitivity maps, we observed so far unreported morphologic cell features such as a pattern of condensed chromatin and perinuclear lightening zones in myeloblasts of NPM1-mutated AML and prominent nucleoli in wild-type NPM1 AML enabling the DL model to provide accurate class predictions.

Clinical and molecular relevance of genetic variants in the non-coding transcriptome of patients with cytogenetically normal acute myeloid leukemia

Expression levels of long non-coding RNA (lncRNA) have been shown to associate with clinical outcome of patients with cytogenetically normal acute myeloid leukemia (CN-AML). However, the frequency and clinical significance of genetic variants in the nucleotide sequences of lncRNA in AML patients is unknown. Herein, we analyzed total RNA sequencing data of 377 younger adults (aged <60 years) with CN-AML, who were comprehensively characterized with regard to clinical outcome. We used available genomic databases and stringent filters to annotate genetic variants unequivocally located in the non-coding transcriptome of AML patients. We detected 981 variants, which are recurrently present in lncRNA that are expressed in leukemic blasts. Among these variants, we identified a cytosine-to-thymidine variant in the lncRNA RP5-1074L1.4 and a cytosine-to-thymidine variant in the lncRNA SNHG15, which independently associated with longer survival of CN-AML patients. The presence of the SNHG15 cytosine-to-thymidine variant was also found to associate with better outcome in an independent dataset of CN-AML patients, despite differences in treatment protocols and RNA sequencing techniques. In order to gain biological insights, we cloned and overexpressed both wild-type and variant versions of the SNHG15 lncRNA. In keeping with its negative prognostic impact, overexpression of the wild-type SNHG15 associated with higher proliferation rate of leukemic blasts when compared with the cytosine-to-thymidine variant. We conclude that recurrent genetic variants of lncRNA that are expressed in the leukemic blasts of CN-AML patients have prognostic and potential biological significance.

AMELIORATE: early intensification in FLT3-mutated acute myeloid leukemia based on peripheral blast clearance - MYNERVA-GIMEMA AML1919 trial

AMELIORATE is a Phase III, randomized trial aiming to personalize treatment intensity in FLT3-mutated acute myeloid leukemia. The current study provides an early appraisal of chemosensitivity based on peripheral blasts clearance, as assessed by multiparameter flow cytometry, from baseline to day 4 of induction. This biomarker was previously demonstrated to predict complete remission achievement and measurable residual disease status. For patients experiencing low peripheral blast cells (i.e., ≤2.0 logs), two major adjustments of treatment as compared with current standard of care are envisioned in the experimental arm: the immediate switch to intensified induction with high-doses cytarabine (1500 mg/m² b.i.d. on days 5-7 of induction); and the early allocation of the patient to high-risk disease category, to be further refined later based on postinduction measurable residual disease status.

Patients with spontaneous remission of high-risk MDS and AML show persistent preleukemic clonal hematopoiesis

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.

Randomized trial comparing standard vs sequential high-dose chemotherapy for inducing early CR in adult AML

Here we evaluated whether sequential high-dose chemotherapy (sHD) increased the early complete remission (CR) rate in acute myelogenous leukemia (AML) compared with standard-intensity idarubicin-cytarabine-etoposide (ICE) chemotherapy. This study enrolled 574 patients (age, 16-73 years; median, 52 years) who were randomly assigned to ICE (n = 286 evaluable) or sHD (2 weekly 3-day blocks with cytarabine 2 g/m² twice a day for 2 days plus idarubicin; n = 286 evaluable). Responsive patients were risk-stratified for a second randomization. Standard-risk patients received autograft or repetitive blood stem cell-supported high-dose courses. High-risk patients (and standard-risk patients not mobilizing stem cells) underwent allotransplantation. CR rates after 2 induction courses were comparable between ICE (80.8%) and sHD (83.6%; P = .38). sHD yielded a higher single-induction CR rate (69.2% vs 81.5%; P = .0007) with lower resistance risk (P < .0001), comparable mortality (P = .39), and improved 5-year overall survival (39% vs 49%; P = .045) and relapse-free survival (36% vs 48%; P = .028), despite greater hematotoxicity delaying or reducing consolidation blocks. sHD improved the early CR rate in high-risk AML (odds ratio, 0.48; 95% confidence interval [CI], 0.31-0.74; P = .0008) and in patients aged 60 years and less with de novo AML (odds ratio, 0.46; 95% CI, 0.27-0.78; P = .003), and also improved overall/relapse-free survival in the latter group (hazard ratio, 0.70; 95% CI, 0.52-0.94; P = .01), in standard-risk AML, and postallograft (hazard ratio, 0.61; 95% CI, 0.39-0.96; P = .03). sHD was feasible, effectively achieved rapid CR, and improved outcomes in AML subsets. This study is registered at www.clinicaltrials.gov as #NCT00495287.

Validation and refinement of the revised 2017 European LeukemiaNet genetic risk stratification of acute myeloid leukemia

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.