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Abstract Background Predictive modeling based on multi-omics data, which incorporates several types of omics data for the same patients, has shown potential to outperform single-omics predictive modeling. Most research in this domain focuses on incorporating numerous data types, despite the complexity and cost of acquiring them. The prevailing assumption is that increasing the number of data types necessarily improves predictive performance. However, the integration of less informative or redundant data types could potentially hinder this performance. Therefore, identifying the most effective combinations of omics data types that enhance predictive performance is critical for cost-effective and accurate predictions. Methods In this study, we systematically evaluated the predictive performance of all 31 possible combinations including at least one of five genomic data types (mRNA, miRNA, methylation, DNAseq, and copy number variation) using 14 cancer datasets with right-censored survival outcomes, publicly available from the TCGA database. We employed various prediction methods and up-weighted clinical data in every model to leverage their predictive importance. Harrell’s C-index and the integrated Brier Score were used as performance measures. To assess the robustness of our findings, we performed a bootstrap analysis at the level of the included datasets. Statistical testing was conducted for key results, limiting the number of tests to ensure a low risk of false positives. Results Contrary to expectations, we found that using only mRNA data or a combination of mRNA and miRNA data was sufficient for most cancer types. For some cancer types, the additional inclusion of methylation data led to improved prediction results. Far from enhancing performance, the introduction of more data types most often resulted in a decline in performance, which varied between the two performance measures. Conclusions Our findings challenge the prevailing notion that combining multiple omics data types in multi-omics survival prediction improves predictive performance. Thus, the widespread approach in multi-omics prediction of incorporating as many data types as possible should be reconsidered to avoid suboptimal prediction results and unnecessary expenditure.

Abstract Patients with cytogenetically normal acute myeloid leukemia (CN-AML) may harbor prognostically relevant gene mutations and thus be categorized into one of the three 2022 European LeukemiaNet (ELN) genetic-risk groups. Nevertheless, there remains heterogeneity with respect to relapse-free survival (RFS) within these genetic-risk groups. Our training set included 306 adults on Alliance for Clinical Trials in Oncology studies with de novo CN-AML aged

Abstract Background Acute leukemias represent deadly malignancies that require better treatment. As a challenge, treatment is counteracted by a microenvironment protecting dormant leukemia stem cells. Methods To identify responsible surface proteins, we performed deep proteome profiling on minute numbers of dormant patient-derived xenograft (PDX) leukemia stem cells isolated from mice. Candidates were functionally screened by establishing a comprehensive CRISPR‒Cas9 pipeline in PDX models in vivo. Results A disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) was identified as an essential vulnerability required for the survival and growth of different types of acute leukemias in vivo, and reconstitution assays in PDX models confirmed the relevance of its sheddase activity. Of translational importance, molecular or pharmacological targeting of ADAM10 reduced PDX leukemia burden, cell homing to the murine bone marrow and stem cell frequency, and increased leukemia response to conventional chemotherapy in vivo. Conclusions These findings identify ADAM10 as an attractive therapeutic target for the future treatment of acute leukemias.

Abstract 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.

Activating colony-stimulating factor-3 receptor gene (CSF3R) mutations are recurrent in acute myeloid leukemia (AML) with t(8;21) translocation. However, the nature of oncogenic collaboration between alterations of CSF3R and the t(8;21) associated RUNX1-RUNX1T1 fusion remains unclear. In CD34+ hematopoietic stem and progenitor cells from healthy donors, double oncogene expression led to a clonal advantage, increased self-renewal potential, and blast-like morphology and distinct immunophenotype. Gene expression profiling revealed hedgehog signaling as a potential mechanism, with upregulation of GLI2 constituting a putative pharmacological target. Both primary hematopoietic cells and the t(8;21) positive AML cell line SKNO-1 showed increased sensitivity to the GLI inhibitor GANT61 when expressing CSF3R T618I. Our findings suggest that during leukemogenesis, the RUNX1-RUNXT1 fusion and CSF3R mutation act in a synergistic manner to alter hedgehog signaling, which can be exploited therapeutically.

Abstract 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.

Abstract Background Patients with chronic lymphocytic leukemia (CLL) may be more susceptible to COVID-19 related poor outcomes, including thrombosis and death, due to the advanced age, the presence of comorbidities, and the disease and treatment-related immune deficiency. The aim of this study was to assess the risk of thrombosis and bleeding in patients with CLL affected by severe COVID-19. Methods This is a retrospective multicenter study conducted by ERIC, the European Research Initiative on CLL, including patients from 79 centers across 22 countries. Data collection was conducted between April and May 2021. The COVID-19 diagnosis was confirmed by the real-time polymerase chain reaction (RT-PCR) assay for SARS-CoV-2 on nasal or pharyngeal swabs. Severe cases of COVID-19 were defined by hospitalization and the need of oxygen or admission into ICU. Development and type of thrombotic events, presence and severity of bleeding complications were reported during treatment for COVID-19. Bleeding events were classified using ISTH definition. STROBE recommendations were used in order to enhance reporting. Results A total of 793 patients from 79 centers were included in the study with 593 being hospitalized (74.8%). Among these, 511 were defined as having severe COVID: 162 were admitted to the ICU while 349 received oxygen supplementation outside the ICU. Most patients (90.5%) were receiving thromboprophylaxis. During COVID-19 treatment, 11.1% developed a thromboembolic event, while 5.0% experienced bleeding. Thrombosis developed in 21.6% of patients who were not receiving thromboprophylaxis, in contrast to 10.6% of patients who were on thromboprophylaxis. Bleeding episodes were more frequent in patients receiving intermediate/therapeutic versus prophylactic doses of low-molecular-weight heparin (LWMH) (8.1% vs. 3.8%, respectively) and in elderly. In multivariate analysis, peak D-dimer level and C-reactive protein to albumin ratio were poor prognostic factors for thrombosis occurrence (OR = 1.022, 95%CI 1.007‒1.038 and OR = 1.025, 95%CI 1.001‒1.051, respectively), while thromboprophylaxis use was protective (OR = 0.199, 95%CI 0.061‒0.645). Age and LMWH intermediate/therapeutic dose administration were prognostic factors in multivariate model for bleeding (OR = 1.062, 95%CI 1.017–1.109 and OR = 2.438, 95%CI 1.023–5.813, respectively). Conclusions Patients with CLL affected by severe COVID-19 are at a high risk of thrombosis if thromboprophylaxis is not used, but also at increased risk of bleeding under the LMWH intermediate/therapeutic dose administration.

Abstract Acute myeloid leukemia (AML) patients suffer dismal prognosis upon treatment resistance. To study functional heterogeneity of resistance, we generated serially transplantable patient-derived xenograft (PDX) models from one patient with AML and twelve clones thereof, each derived from a single stem cell, as proven by genetic barcoding. Transcriptome and exome sequencing segregated clones according to their origin from relapse one or two. Undetectable for sequencing, multiplex fluorochrome-guided competitive in vivo treatment trials identified a subset of relapse two clones as uniquely resistant to cytarabine treatment. Transcriptional and proteomic profiles obtained from resistant PDX clones and refractory AML patients defined a 16-gene score that was predictive of clinical outcome in a large independent patient cohort. Thus, we identified novel genes related to cytarabine resistance and provide proof of concept that intra-tumor heterogeneity reflects inter-tumor heterogeneity in AML.

Abstract Acute lymphoblastic leukemia (ALL) represents the most frequent malignancy in children, and relapse/refractory (r/r) disease is difficult to treat, both in children and adults. In search for novel treatment options against r/r ALL, we studied inhibitor of apoptosis proteins (IAP) and Smac mimetics (SM). SM‐sensitized r/r ALL cells towards conventional chemotherapy, even upon resistance against SM alone. The combination of SM and chemotherapy‐induced cell death via caspases and PARP, but independent from cIAP‐1/2, RIPK1, TNFα or NF‐κB. Instead, XIAP was identified to mediate SM effects. Molecular manipulation of XIAP in vivo using microRNA‐30 flanked shRNA expression in cell lines and patient‐derived xenograft (PDX) models of r/r ALL mimicked SM effects and intermediate XIAP knockdown‐sensitized r/r ALL cells towards chemotherapy‐induced apoptosis. Interestingly, upon strong XIAP knockdown, PDX r/r ALL cells were outcompeted in vivo, even in the absence of chemotherapy. Our results indicate a yet unknown essential function of XIAP in r/r ALL and reveal XIAP as a promising therapeutic target for r/r ALL.

IntroductionThere are many different chronic lymphoblastic leukemia (CLL) survival prediction models and scores. But none provide information on expression of immune-related genes in the CLL cells.MethodsWe interrogated data from the Gene Expression Omnibus database (GEO, GSE22762; Number = 151; training) and International Cancer Genome Consortium database (ICGC, CLLE-ES; Number = 491; validation) to develop an immune risk score (IRS) using Least absolute shrinkage and selection operator (LASSO) Cox regression analyses based on expression of immune-related genes in CLL cells. The accuracy of the predicted nomogram we developed using the IRS, Binet stage, and del(17p) cytogenetic data was subsequently assessed using calibration curves.ResultsA survival model based on expression of 5 immune-related genes was constructed. Areas under the curve (AUC) for 1-year survivals were 0.90 (95% confidence interval, 0.78, 0.99) and 0.75 (0.54, 0.87) in the training and validation datasets, respectively. 5-year survivals of low- and high-risk subjects were 89% (83, 95%) vs. 6% (0, 17%; p < 0.001) and 98% (95, 100%) vs. 92% (88, 96%; p < 0.001) in two datasets. The IRS was an independent survival predictor of both datasets. A calibration curve showed good performance of the nomogram. In vitro, the high expression of CDKN2A and SREBF2 in the bone marrow of patients with CLL was verified by immunohistochemistry analysis (IHC), which were associated with poor prognosis and may play an important role in the complex bone marrow immune environment.ConclusionThe IRS is an accurate independent survival predictor with a high C-statistic. A combined nomogram had good survival prediction accuracy in calibration curves. These data demonstrate the potential impact of immune related genes on survival in CLL.

Preclinical molecular models are useful that mimic a patient´s response to targeted therapy. Here, the authors establish an in vivo inducible RNAi-mediated gene silencing system in patient-derived xenograft models of acute leukemia to identify individual vulnerabilities and therapeutic targets.

Antibody-dependent cellular phagocytosis (ADCP) by macrophages, an important effector function of tumor targeting antibodies, is hampered by ‘Don´t Eat Me!’ signals such as CD47 expressed by cancer cells. Yet, human leukocyte antigen (HLA) class I expression may also impair ADCP by engaging leukocyte immunoglobulin-like receptor subfamily B (LILRB) member 1 (LILRB1) or LILRB2. Analysis of different lymphoma cell lines revealed that the ratio of CD20 to HLA class I cell surface molecules determined the sensitivity to ADCP by the combination of rituximab and an Fc-silent variant of the CD47 antibody magrolimab (CD47-IgGσ). To boost ADCP, Fc-silent antibodies against LILRB1 and LILRB2 were generated (LILRB1-IgGσ and LILRB2-IgGσ, respectively). While LILRB2-IgGσ was not effective, LILRB1-IgGσ significantly enhanced ADCP of lymphoma cell lines when combined with both rituximab and CD47-IgGσ. LILRB1-IgGσ promoted serial engulfment of lymphoma cells and potentiated ADCP by non-polarized M0 as well as polarized M1 and M2 macrophages, but required CD47 co-blockade and the presence of the CD20 antibody. Importantly, complementing rituximab and CD47-IgGσ, LILRB1-IgGσ increased ADCP of chronic lymphocytic leukemia (CLL) or lymphoma cells isolated from patients. Thus, dual checkpoint blockade of CD47 and LILRB1 may be promising to improve antibody therapy of CLL and lymphomas through enhancing ADCP by macrophages.

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.

Abstract Chemotherapy resistance is the main impediment in the treatment of acute myeloid leukaemia (AML). Despite rapid advances, the various mechanisms inducing resistance development remain to be defined in detail. Here we report that loss-of-function mutations (LOF) in the histone methyltransferase EZH2 have the potential to confer resistance against the chemotherapeutic agent cytarabine. We identify seven distinct EZH2 mutations leading to loss of H3K27 trimethylation via multiple mechanisms. Analysis of matched diagnosis and relapse samples reveal a heterogenous regulation of EZH2 and a loss of EZH2 in 50% of patients. We confirm that loss of EZH2 induces resistance against cytarabine in the cell lines HEK293T and K562 as well as in a patient-derived xenograft model. Proteomics and transcriptomics analysis reveal that resistance is conferred by upregulation of multiple direct and indirect EZH2 target genes that are involved in apoptosis evasion, augmentation of proliferation and alteration of transmembrane transporter function. Our data indicate that loss of EZH2 results in upregulation of its target genes, providing the cell with a selective growth advantage, which mediates chemotherapy resistance.

Abstract Background Clinically relevant methods are not available that prioritize and validate potential therapeutic targets for individual tumors, from the vast amount of tumor descriptive expression data. Methods We established inducible transgene expression in clinically relevant patient-derived xenograft (PDX) models in vivo to fill this gap. Results With this technique at hand, we analyzed the role of the transcription factor Krüppel-like factor 4 (KLF4) in B-cell acute lymphoblastic leukemia (B-ALL) PDX models at different disease stages. In competitive preclinical in vivo trials, we found that re-expression of wild type KLF4 reduced the leukemia load in PDX models of B-ALL, with the strongest effects being observed after conventional chemotherapy in minimal residual disease (MRD). A nonfunctional KLF4 mutant had no effect on this model. The re-expression of KLF4 sensitized tumor cells in the PDX model towards systemic chemotherapy in vivo. It is of major translational relevance that azacitidine upregulated KLF4 levels in the PDX model and a KLF4 knockout reduced azacitidine-induced cell death, suggesting that azacitidine can regulate KLF4 re-expression. These results support the application of azacitidine in patients with B-ALL as a therapeutic option to regulate KLF4. Conclusion Genetic engineering of PDX models allows the examination of the function of dysregulated genes like KLF4 in a highly clinically relevant translational context, and it also enables the selection of therapeutic targets in individual tumors and links their functions to clinically available drugs, which will facilitate personalized treatment in the future.

Aberrant expression of Ecotropic Viral Integration Site 1 (EVI1) is a hallmark of acute myeloid leukemia (AML) with inv(3) or t(3;3), which is a disease subtype with especially poor outcome. In studying transcriptomes from AML patients with chromosome 3q rearrangements, we identified a significant upregulation of the Nuclear Receptor Interacting Protein 1 (NRIP1) as well as its adjacent non-coding RNA LOC101927745. Utilizing transcriptomic and epigenomic data from over 900 primary samples from patients as well as genetic and transcriptional engineering approaches, we have identified several mechanisms that can lead to upregulation of NRIP1 in AML. We hypothesize that the LOC101927745 transcription start site harbors a context-dependent enhancer that is bound by EVI1, causing upregulation of NRIP1 in AML with chromosome 3 abnormalities. Furthermore, we showed that NRIP1 knockdown negatively affects the proliferation and survival of 3qrearranged AML cells and increases their sensitivity to all-trans retinoic acid, suggesting that NRIP1 is relevant for the pathogenesis of inv(3)/t(3;3) AML and could serve as a novel therapeutic target in myeloid malignancies with 3q abnormalities.

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

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.

Abstract: Acute erythroid leukemia (AEL) is a rare and aggressive form of acute leukemia, the biology of which remains poorly understood. Here we demonstrate that the ParaHox gene CDX4 is expressed in patients with acute erythroid leukemia, and that aberrant expression of Cdx4 induced homogenously a transplantable acute erythroid leukemia in mice. Gene expression analyses demonstrated upregulation of genes involved in stemness and leukemogenesis, with parallel downregulation of target genes of Gata1 and Gata2 responsible for erythroid differentiation. Cdx4 induced a proteomic profile that overlapped with a cluster of proteins previously defined to represent the most primitive human erythroid progenitors. Whole-exome sequencing of diseased mice identified recurrent mutations significantly enriched for transcription factors involved in erythroid lineage specification, as well as TP53 target genes partly identical to the ones reported in patients with AEL. In summary, our data indicate that Cdx4 is able to induce stemness and inhibit terminal erythroid differentiation, leading to the development of AEL in association with co-occurring mutations.

Abstract Background Acute myeloid leukemia (AML) patients with a high allelic burden of an internal tandem duplication (ITD)-mutated FMS-like Tyrosine Kinase-3 (FLT3) have a dismal outcome. FLT3ITD triggers the proliferation of the quiescent hematopoietic stem cell (HSC) pool but fails to directly transform HSCs. While the inflammatory transcription factor nuclear factor of activated T-cells 2 (NFAT2, NFATC1) is overexpressed in AML, it is unknown whether it plays a role in FLT3ITD-induced HSC transformation. Methods We generated a triple transgenic mouse model, in which tamoxifen-inducible Cre-recombinase targets expression of a constitutively nuclear transcription factor NFATC1 to FLT3 ITD positive HSC. Emerging genotypes were phenotypically, biochemically, and also transcriptionally characterized using RNA sequencing. We also retrospectively analyzed the overall survival of AML patients with different NFATC1 expression status. Results We find that NFATC1 governs FLT3ITD-driven precursor cell expansion and transformation, causing a fully penetrant lethal AML. FLT3ITD/NFATC1-AML is re-transplantable in secondary recipients and shows primary resistance to the FLT3ITD-kinase inhibitor quizartinib. Mechanistically, NFATC1 rewires FLT3ITD-dependent signaling output in HSC, involving augmented K-RAS signaling and a selective de novo recruitment of key HSC-transforming signaling pathways such as the Hedgehog- and WNT/B-Catenin signaling pathways. In human AML, NFATC1 overexpression is associated with poor overall survival. Conclusions NFATC1 expression causes FLT3ITD-induced transcriptome changes, which are associated with HSC transformation, quizartinib resistance, and a poor prognosis in AML.

Abstract Patients with Myelodysplastic Syndromes (MDS) and secondary Acute Myeloid Leukemia (sAML) have a very poor prognosis after failure of hypomethylating agents (HMA). Stem cell transplantation is the only effective salvage therapy, for which only a limited number of patients are eligible due to age and comorbidity. Combination therapy of venetoclax and azacitidine (5-AZA) seems to be a promising approach in myeloid malignancies, but data from patients with HMA failure are lacking. Furthermore, a considerable concern of combination regimens in elderly AML and MDS patients is the toxicity on the remaining healthy hematopoiesis. Here, we report in vitro data showing the impact of venetoclax and 5-AZA, alone or in combination, in a larger cohort of MDS/sAML patients (n = 21), even after HMA failure (n = 13). We especially focused on the effects on healthy hematopoiesis and the impact on colony forming capacity as a parameter for long-term effects. To the best of our knowledge, we show for the first time that venetoclax in combination with capped dose of 5-AZA targets cell malignancies, while sparing healthy hematopoiesis.

In an effort to identify target genes in acute myeloid leukemia (AML), we compared gene expression profiles between normal and AML cells from various publicly available datasets. We identified CD99, a gene that is up-regulated in AML patients. In 186 patients from The Cancer Genome Atlas AML dataset, CD99 was over-expressed in patients with FLT3-ITD and was down-regulated in patients with TP53 mutations. CD99 is a trans-membrane protein expressed on leukocytes and plays a role in cell adhesion, trans-endothelial migration, and T-cell differentiation. The CD99 gene encodes two isoforms with distinct expression and functional profiles in both normal and malignant tissues. Here we report that, although the CD99 long isoform initially induces an increase in cell proliferation, it also induces higher levels of reactive oxygen species, DNA damage, apoptosis and a subsequent decrease in cell viability. In several leukemia murine models, the CD99 long isoform delayed disease progression and resulted in lower leukemia engraftment in the bone marrow. Furthermore, the CD99 monoclonal antibody reduced cell viability, colony formation, and cell migration, and induced cell differentiation and apoptosis in leukemia cell lines and primary blasts. Mechanistically, CD99 long isoform resulted in transient induction followed by a dramatic decrease in both ERK and SRC phosphorylation. Altogether, our study provides new insights into the role of CD99 isoforms in AML that could potentially be relevant for the preclinical development of CD99 targeted therapy.

Abstract Background The inclusion of high-dimensional omics data in prediction models has become a well-studied topic in the last decades. Although most of these methods do not account for possibly different types of variables in the set of covariates available in the same dataset, there are many such scenarios where the variables can be structured in blocks of different types, e.g., clinical, transcriptomic, and methylation data. To date, there exist a few computationally intensive approaches that make use of block structures of this kind. Results In this paper we present priority-Lasso, an intuitive and practical analysis strategy for building prediction models based on Lasso that takes such block structures into account. It requires the definition of a priority order of blocks of data. Lasso models are calculated successively for every block and the fitted values of every step are included as an offset in the fit of the next step. We apply priority-Lasso in different settings on an acute myeloid leukemia (AML) dataset consisting of clinical variables, cytogenetics, gene mutations and expression variables, and compare its performance on an independent validation dataset to the performance of standard Lasso models. Conclusion The results show that priority-Lasso is able to keep pace with Lasso in terms of prediction accuracy. Variables of blocks with higher priorities are favored over variables of blocks with lower priority, which results in easily usable and transportable models for clinical practice.

The t(8;21) translocation is often found in acute myeloid leukaemia but is not sufficient for development of the disease. In this study, the authors identify frequent mutations in the transcriptional repressor, ZBTB7A, in these patients and show that the mutations reduce DNA binding activity.

Mir-22 has been shown to be an oncogenic microRNA in breast cancer and myelodysplastic syndrome. Here, the authors show that mir-22 functions as a tumour suppressor in de novoacute myeloid leukaemia by inhibiting the expression of several oncogenes and that restoring mir-22 expression suppresses AML progression.

A cute myeloid leukemia is a disease of the elderly (median age at diagnosis, 65–70 years). The prognosis of older acute myeloid leukemia patients is generally poor. While genetic markers have become important tools for risk stratification and treatment selection in young and middle-aged patients, their applicability in very old patients is less clear. We sought to validate existing genetic risk classification systems and identify additional factors associated with outcomes in intensively treated patients aged ≥75 years. In 151 patients who received induction chemotherapy in the AMLCG-1999 trial, we investigated recurrently mutated genes using a targeted sequencing assay covering 64 genes. The median number of mutated genes per patient was four. The most commonly mutated genes were TET2 (42%), DNMT3A (35%), NPM1 (32%), SRSF2 (25%) and ASXL1 (21%). The complete remission rate was 44% and the 3-year survival was 21% for the entire cohort. While adverse-risk cytogenetics (MRC classification) were associated with shorter overall survival (P=0.001), NPM1 and FLT3-ITD mutations (present in 18%) did not have a significant impact on overall survival. Notably, none of the 13 IDH1-mutated patients (9%) reached complete remission. Consequently, the overall survival of this subgroup was significantly shorter than that of IDH1-wildtype patients (P

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

Diagnostic and prognostic evaluation of chronic lymphocytic leukemia (CLL) involves blood cell counts, immunophenotyping, IgVH mutation status, and cytogenetic analyses. We generated B-cell associated gene-signatures (BAGS) based on six naturally occurring B-cell subsets within normal bone marrow. Our hypothesis is that by segregating CLL according to BAGS, we can identify subtypes with prognostic implications in support of pathogenetic value of BAGS. Microarray-based gene-expression samples from eight independent CLL cohorts (1,024 untreated patients) were BAGS-stratified into pre-BI, pre-BII, immature, naïve, memory, or plasma cell subtypes; the majority falling within the memory (24.5-45.8%) or naïve (14.5-32.3%) categories. For a subset of CLL patients (n = 296), time to treatment (TTT) was shorter amongst early differentiation subtypes (pre-BI/pre-BII/immature) compared to late subtypes (memory/plasma cell, HR: 0.53 [0.35-0.78]). Particularly, pre-BII subtype patients had the shortest TTT among all subtypes. Correlates derived for BAGS subtype and IgVH mutation (n = 405) revealed an elevated mutation frequency in late vs. early subtypes (71% vs. 45%, P < .001). Predictions for BAGS subtype resistance towards rituximab and cyclophosphamide varied for rituximab, whereas all subtypes were sensitive to cyclophosphamide. This study supports our hypothesis that BAGS-subtyping may be of tangible prognostic and pathogenetic value for CLL patients.

Philadelphia-like B-cell precursor acute lymphoblastic leukemia (Ph-like ALL) is characterized by distinct genetic alterations and inferior prognosis in children and younger adults. The purpose of this study was a genetic and clinical characterization of Ph-like ALL in adults. Twenty-six (13%) of 207 adult patients (median age: 42 years) with B-cell precursor ALL (BCP-ALL) were classified as having Ph-like ALL using gene expression profiling. The frequency of Ph-like ALL was 27% among 95 BCP-ALL patients negative for BCR-ABL1 and KMT2A-rearrangements. IGH-CRLF2 rearrangements (6/16; P=0.002) and mutations in JAK2 (7/16; P

About 30% of patients with acute myeloid leukemia (AML) harbour mutations of the receptor tyrosine kinase FLT3, mostly internal tandem duplications (ITD) and point mutations of the second tyrosine kinase domain (TKD). It was the aim of this study to comprehensively analyze clinical and functional properties of various FLT3 mutants. In 672 normal karyotype AML patients FLT3-ITD, but not FLT3-TKD mutations were associated with a worse relapse free and overall survival in multivariate analysis. In paired diagnosis-relapse samples FLT3-ITD showed higher stability (70%) compared to FLT3-TKD (30%). In vitro, FLT3-ITD induced a strong activating phenotype in Ba/F3 cells. In contrast, FLT3-TKD mutations and other point mutations--including two novel mutations--showed a weaker but clear gain-of-function phenotype with gradual increase in proliferation and protection from apoptosis. The pro-proliferative capacity of the investigated FLT3 mutants was associated with cell surface expression and tyrosine 591 phosphorylation of the FLT3 receptor. Western blot experiments revealed STAT5 activation only in FLT3-ITD positive cell lines, in contrast to FLT3-non-ITD mutants, which displayed an enhanced signal of AKT and MAPK activation. Gene expression analysis revealed distinct difference between FLT3-ITD and FLT3-TKD for STAT5 target gene expression as well as deregulation of SOCS2, ENPP2, PRUNE2 and ART3. FLT3-ITD and FLT3 point mutations show a gain-of-function phenotype with distinct signalling properties in vitro. Although poor prognosis in AML is only associated with FLT3-ITD, all activating FLT3 mutations can contribute to leukemogenesis and are thus potential targets for therapeutic interventions.

Background The RUNX1 (AML1) gene is a frequent mutational target in myelodysplastic syndromes and acute myeloid leukemia. Previous studies suggested that RUNX1 mutations may have pathological and prognostic implications.Design and Methods We screened 93 patients with cytogenetically normal acute myeloid leukemia for RUNX1 mutations by capillary sequencing of genomic DNA. Mutation status was then correlated with clinical data and gene expression profiles.Results We found that 15 out of 93 (16.1%) patients with cytogenetically normal acute myeloid leukemia had RUNX1 mutations. Seventy-three patients were enrolled in the AMLCG-99 trial and carried ten RUNX1 mutations (13.7%). Among these 73 patients RUNX1 mutations were significantly associated with older age, male sex, absence of NPM1 mutations and presence of MLL-partial tandem duplications. Moreover, RUNX1-mutated patients had a lower complete remission rate (30% versus 73% P=0.01), lower relapse-free survival rate (3-year relapse-free survival 0% versus 30.4%; P=0.002) and lower overall survival rate (3-year overall survival 0% versus 34.4%; P