The stem cell-associated gene expression signature allows risk stratification in pediatric acute myeloid leukemia

Identification of leukemia stem cell subsets with distinct transcriptional, epigenetic and functional properties

The leukemia stem cell (LSC) compartment is a complex reservoir fueling disease progression in acute myeloid leukemia (AML). The existence of heterogeneity within this compartment is well documented but prior studies have focused on genetic heterogeneity without being able to address functional heterogeneity. Understanding this heterogeneity is critical for the informed design of therapies targeting LSC, but has been hampered by LSC scarcity and the lack of reliable cell surface markers for viable LSC isolation. To overcome these challenges, we turned to the patient-derived OCI-AML22 cell model. This model includes functionally, transcriptionally and epigenetically characterized LSC broadly representative of LSC found in primary AML samples. Focusing on the pool of LSC, we used an integrated approach combining xenograft assays with single-cell analysis to identify two LSC subtypes with distinct transcriptional, epigenetic and functional properties. These LSC subtypes differed in depth of quiescence, differentiation potential, repopulation capacity, sensitivity to chemotherapy and could be isolated based on CD112 expression. A majority of AML patient samples had transcriptional signatures reflective of either LSC subtype, and some even showed coexistence within an individual sample. This work provides a framework for investigating the LSC compartment and designing combinatorial therapeutic strategies in AML.

High DOCK1 expression identifies a distinct prognostic subgroup of pediatric acute myeloid leukemia: Results of the Japanese Pediatric Leukemia/Lymphoma Study Group AML-05 trial

BACKGROUND

The molecular pathogenesis of acute myeloid leukemia (AML) was dramatically clarified over the latest two decades. Several important molecular markers were discovered in patients with AML that have helped to improve the risk stratification. However, developing new treatment strategies for relapsed/refractory acute myeloid leukemia (AML) is crucial due to its poor prognosis.

PROCEDURE

To overcome this difficulty, we performed an assay for transposase-accessible chromatin with sequencing (ATAC-seq) in 10 AML patients with various gene alterations. ATAC-seq is based on direct in vitro sequencing adaptor transposition into native chromatin, and is a rapid and sensitive method for integrative epigenomic analysis. ATAC-seq analysis revealed increased accessibility of the DOCK1 gene in patients with AML harboring poor prognostic factors. Following the ATAC-seq results, quantitative reverse transcription polymerase chain reaction was used to measure DOCK1 gene expression levels in 369 pediatric patients with de novo AML.

RESULTS

High DOCK1 expression was detected in 132 (37%) patients. The overall survival (OS) and event-free survival (EFS) among patients with high DOCK1 expression were significantly worse than those patients with low DOCK1 expression (3-year EFS: 34% vs. 60%, p < .001 and 3-year OS: 60% vs. 80%, p < .001). To investigate the significance of high DOCK1 gene expression, we transduced DOCK1 into MOLM14 cells, and revealed that cytarabine in combination with DOCK1 inhibitor reduced the viability of these leukemic cells.

CONCLUSIONS

Our results indicate that a DOCK1 inhibitor might reinforce the effects of cytarabine and other anti-cancer agents in patients with AML with high DOCK1 expression.

A 69 long noncoding RNA signature predicts relapse and acts as independent prognostic factor in pediatric AML

ABSTRACT

Risk stratification using genetics and minimal residual disease has allowed for an increase in the cure rates of pediatric acute myeloid leukemia (pedAML) to up to 70% in contemporary protocols. Nevertheless, ∼30% of patients still experience relapse, indicating a need to optimize stratification strategies. Recently, long noncoding RNA (lncRNA) expression has been shown to hold prognostic power in multiple cancer types. Here, we aimed at refining relapse prediction in pedAML using lncRNA expression. We built a relapse-related lncRNA prognostic signature, named AMLlnc69, using 871 transcriptomes of patients with pedAML obtained from the Therapeutically Applicable Research to Generate Effective Treatments repository. We identified a 69 lncRNA signature AMLlnc69 that is highly predictive of relapse risk (c-index = 0.73), with area under the receiver operating characteristic curve (AUC) values for predicting the 1-, 2-, and 3-year relapse-free survival (RFS) of 0.78, 0.77, and 0.77, respectively. The internal validation using a bootstrap method (resampling times = 1000) resulted in a c-index of 0.72 and AUC values for predicting the 1-, 2-, and 3-year RFS of 0.77, 0.76, and 0.76, respectively. Through a Cox regression analysis, AMLlnc69, nucleophosmin mutation, and white blood cell at diagnosis were identified as independent predictors of RFS. Finally, a nomogram was build using these 2 parameters, showing a c-index of 0.80 and 0.71 after bootstrapping (n = 1000). In conclusion, the identified AMLlnc69 will, after prospective validation, add important information to guide the management of patients with pedAML. The nomogram is a promising tool for easy stratification of patients into a novel scheme of relapse-risk groups.

Aberrant stem cell and developmental programs in pediatric leukemia

Hematopoiesis is a finely orchestrated process, whereby hematopoietic stem cells give rise to all mature blood cells. Crucially, they maintain the ability to self-renew and/or differentiate to replenish downstream progeny. This process starts at an embryonic stage and continues throughout the human lifespan. Blood cancers such as leukemia occur when normal hematopoiesis is disrupted, leading to uncontrolled proliferation and a block in differentiation of progenitors of a particular lineage (myeloid or lymphoid). Although normal stem cell programs are crucial for tissue homeostasis, these can be co-opted in many cancers, including leukemia. Myeloid or lymphoid leukemias often display stem cell-like properties that not only allow proliferation and survival of leukemic blasts but also enable them to escape treatments currently employed to treat patients. In addition, some leukemias, especially in children, have a fetal stem cell profile, which may reflect the developmental origins of the disease. Aberrant fetal stem cell programs necessary for leukemia maintenance are particularly attractive therapeutic targets. Understanding how hijacked stem cell programs lead to aberrant gene expression in place and time, and drive the biology of leukemia, will help us develop the best treatment strategies for patients.

Emerging and Future Targeted Therapies for Pediatric Acute Myeloid Leukemia: Targeting the Leukemia Stem Cells

Acute myeloid leukemia (AML) is a rare subtype of acute leukemia in the pediatric and adolescent population but causes disproportionate morbidity and mortality in this age group. Standard chemotherapeutic regimens for AML have changed very little in the past 3-4 decades, but the addition of targeted agents in recent years has led to improved survival in select subsets of patients as well as a better biological understanding of the disease. Currently, one key paradigm of bench-to-bedside practice in the context of adult AML is the focus on leukemia stem cell (LSC)-targeted therapies. Here, we review current and emerging immunotherapies and other targeted agents that are in clinical use for pediatric AML through the lens of what is known (and not known) about their LSC-targeting capability. Based on a growing understanding of pediatric LSC biology, we also briefly discuss potential future agents on the horizon.

Integration of Transcriptomic Features to Improve Prognosis Prediction of Pediatric Acute Myeloid Leukemia With KMT2A Rearrangement

Lysine methyltransferase 2A-rearranged acute myeloid leukemia (KMT2A-r AML) is a special entity in the 2022 World Health Organization classification of myeloid neoplasms, characterized by high relapse rate and adverse outcomes. Current risk stratification was established on the treatment response and translocation partner of KMT2A. To study the transcriptomic feature and refine the current stratification of pediatric KMT2A-r AML, we analyzed clinical and RNA sequencing data of 351 patients. By implementing least absolute shrinkage and selection operator algorithm, we identified 7 genes (KIAA1522, SKAP2, EGFL7, GAB2, HEBP1, FAM174B, and STARD8) of which the expression levels were strongly associated with outcomes. We then developed a transcriptome-based score, dividing patients into 2 groups with distinct gene expression patterns and prognosis, which was further validated in an independent cohort and outperformed the LSC17 score. We also found cell cycle, oxidative phosphorylation, and metabolism pathways were upregulated in patients with inferior outcomes. By integrating clinical characteristics, we proposed a simple-to-use prognostic scoring system with excellent discriminability, which allowed us to distinguish allogeneic hematopoietic stem cell transplantation candidates more precisely. In conclusion, pediatric KMT2A-r AML is heterogenous on transcriptomic level and the newly proposed scoring system combining clinical characteristics and transcriptomic features can be instructive in clinical routines.

Identification of a Complex Karyotype Signature with Clinical Implications in AML and MDS-EB Using Gene Expression Profiling

Complex karyotype (CK) is associated with a poor prognosis in both acute myeloid leukemia (AML) and myelodysplastic syndrome with excess blasts (MDS-EB). Transcriptomic analyses have improved our understanding of the disease and risk stratification of myeloid neoplasms; however, CK-specific gene expression signatures have been rarely investigated. In this study, we developed and validated a CK-specific gene expression signature. Differential gene expression analysis between the CK and non-CK groups using data from 348 patients with AML and MDS-EB from four cohorts revealed enrichment of the downregulated genes localized on chromosome 5q or 7q, suggesting that haploinsufficiency due to the deletion of these chromosomes possibly underlies CK pathogenesis. We built a robust transcriptional model for CK prediction using LASSO regression for gene subset selection and validated it using the leave-one-out cross-validation method for fitting the logistic regression model. We established a 10-gene CK signature (CKS) predictive of CK with high predictive accuracy (accuracy 94.22%; AUC 0.977). CKS was significantly associated with shorter overall survival in three independent cohorts, and was comparable to that of previously established risk stratification models for AML. Furthermore, we explored of therapeutic targets among the genes comprising CKS and identified the dysregulated expression of superoxide dismutase 1 (SOD1) gene, which is potentially amenable to SOD1 inhibitors.

LSC17 score complements genetics and measurable residual disease in acute myeloid leukemia: an ALFA study

Whether the LSC17 gene expression can improve risk stratification in the context of next generation sequencing-based risk stratification and measurable residual disease (MRD) in patients with intensively treated AML has not been explored. We analyzed LSC17 in 504 adult patients prospectively treated in the ALFA-0702 trial. RUNX1 or TP53 mutations were associated with higher LSC1 scores while CEBPA and NPM1 mutations were associated with lower scores. Patients with high LSC17 scores had a lower rate of complete response (CR) in a multivariable analysis (odds ratio, 0.41; P = .0007), accounting for European LeukemiaNet 2022 (ELN22), age, and white blood cell count (WBC). LSC17-high status was associated with shorter overall survival (OS) (3-year OS: 70.0% vs 52.7% in patients with LSC17-low status; P < .0001). In a multivariable analysis considering ELN22, age, and WBC, patients with LSC17-high status had shorter disease-free survival (DFS) (hazard ratio [HR], 1.36; P = .048) than those with LSC17-low status. In 123 patients with NPM1-mutated AML in CR, LSC17-high status predicted poorer DFS (HR, 2.34; P = .01), independent of age, WBC, ELN22 risk, and NPM1-MRD. LSC-low status and negative NPM1-MRD identified a subset comprising 48% of patients with mutated NPM1 with a 3-year OS from CR of 93.1% compared with 60.7% in those with LSC17-high status and/or positive NPM1-MRD (P = .0001). Overall, LSC17 assessment refines genetic risk stratification in adult patients with AML treated intensively. Combined with MRD, LSC17 identifies a subset of patients with NPM1-mutated AML with excellent clinical outcome.

Modern Risk Stratification of Acute Myeloid Leukemia in 2023: Integrating Established and Emerging Prognostic Factors

An accurate estimation of AML prognosis is complex since it depends on patient-related factors, AML manifestations at diagnosis, and disease genetics. Furthermore, the depth of response, evaluated using the level of MRD, has been established as a strong prognostic factor in several AML subgroups. In recent years, this rapidly evolving field has made the prognostic evaluation of AML more challenging. Traditional prognostic factors, established in cohorts of patients treated with standard intensive chemotherapy, are becoming less accurate as new effective therapies are emerging. The widespread availability of next-generation sequencing platforms has improved our knowledge of AML biology and, consequently, the recent ELN 2022 recommendations significantly expanded the role of new gene mutations. However, the impact of rare co-mutational patterns remains to be fully disclosed, and large international consortia such as the HARMONY project will hopefully be instrumental to this aim. Moreover, accumulating evidence suggests that clonal architecture plays a significant prognostic role. The integration of clinical, cytogenetic, and molecular factors is essential, but hierarchical methods are reaching their limit. Thus, innovative approaches are being extensively explored, including those based on "knowledge banks". Indeed, more robust prognostic estimations can be obtained by matching each patient's genomic and clinical data with the ones derived from very large cohorts, but further improvements are needed.

Verification of prognostic expression biomarkers is improved by examining enriched leukemic blasts rather than mononuclear cells from acute myeloid leukemia patients

BACKGROUND

Studies have not systematically compared the ability to verify performance of prognostic transcripts in paired bulk mononuclear cells versus viable CD34-expressing leukemic blasts from patients with acute myeloid leukemia. We hypothesized that examining the homogenous leukemic blasts will yield different biological information and may improve prognostic performance of expression biomarkers.

METHODS

To assess the impact of cellular heterogeneity on expression biomarkers in acute myeloid leukemia, we systematically examined paired mononuclear cells and viable CD34-expressing leukemic blasts from SWOG diagnostic specimens. After enrichment, patients were assigned into discovery and validation cohorts based on availability of extracted RNA. Analyses of RNA sequencing data examined how enrichment impacted differentially expressed genes associated with pre-analytic variables, patient characteristics, and clinical outcomes.

RESULTS

Blast enrichment yielded significantly different expression profiles and biological pathways associated with clinical characteristics (e.g., cytogenetics). Although numerous differentially expressed genes were associated with clinical outcomes, most lost their prognostic significance in the mononuclear cells and blasts after adjusting for age and ELN risk, with only 11 genes remaining significant for overall survival in both cell populations (CEP70, COMMD7, DNMT3B, ECE1, LNX2, NEGR1, PIK3C2B, SEMA4D, SMAD2, TAF8, ZNF444). To examine the impact of enrichment on biomarker verification, these 11 candidate biomarkers were examined by quantitative RT/PCR in the validation cohort. After adjusting for ELN risk and age, expression of 4 genes (CEP70, DNMT3B, ECE1, and PIK3CB) remained significantly associated with overall survival in the blasts, while none met statistical significance in mononuclear cells.

CONCLUSIONS

This study provides insights into biological information gained/lost by examining viable CD34-expressing leukemic blasts versus mononuclear cells from the same patient and shows an improved verification rate for expression biomarkers in blasts.

Mitochondrial gene expression signature predicts prognosis of pediatric acute myeloid leukemia patients

Introduction

Gene expression profile of mitochondrial-related genes is not well deciphered in pediatric acute myeloid leukaemia (AML). We aimed to identify mitochondria-related differentially expressed genes (DEGs) in pediatric AML with their prognostic significance.

Methods

Children with de novo AML were included prospectively between July 2016-December 2019. Transcriptomic profiling was done for a subset of samples, stratified by mtDNA copy number. Top mitochondria-related DEGs were identified and validated by real-time PCR. A prognostic gene signature risk score was formulated using DEGs independently predictive of overall survival (OS) in multivariable analysis. Predictive ability of the risk score was estimated along with external validation in The Tumor Genome Atlas (TCGA) AML dataset.

Results

In 143 children with AML, twenty mitochondria-related DEGs were selected for validation, of which 16 were found to be significantly dysregulated. Upregulation of SDHC (p<0.001), CLIC1 (p=0.013) and downregulation of SLC25A29 (p<0.001) were independently predictive of inferior OS, and included for developing prognostic risk score. The risk score model was independently predictive of survival over and above ELN risk categorization (Harrell's c-index: 0.675). High-risk patients (risk score above median) had significantly inferior OS (p<0.001) and event free survival (p<0.001); they were associated with poor-risk cytogenetics (p=0.021), ELN intermediate/poor risk group (p=0.016), absence of RUNX1-RUNX1T1 (p=0.027), and not attaining remission (p=0.016). On external validation, the risk score also predicted OS (p=0.019) in TCGA dataset.

Discussion

We identified and validated mitochondria-related DEGs with prognostic impact in pediatric AML and also developed a novel 3-gene based externally validated gene signature predictive of survival.

Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia

Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach.

Relapsed pediatric acute myeloid leukemia is associated with poor prognosis. Here, the authors use RNA-seq data from 1503 primary samples to create a combined transcriptional and cytomolecular signature to improve relapse risk prediction.

Ferroptosis-related gene signature predicts the clinical outcome in pediatric acute myeloid leukemia patients and refines the 2017 ELN classification system

Background: The prognostic roles of ferroptosis-related mRNAs (FG) and lncRNAs (FL) in pediatric acute myeloid leukemia (P-AML) patients remain unclear.

Methods: RNA-seq and clinical data of P-AML patients were downloaded from the TARGET project. Cox and LASSO regression analyses were performed to identify FG, FL, and FGL (combination of FG and FL) prognostic models, and their performances were compared. Tumor microenvironment, functional enrichment, mutation landscape, and anticancer drug sensitivity were analyzed.

Results: An FGL model of 22 ferroptosis-related signatures was identified as an independent parameter, and it showed performance better than FG, FL, and four additional public prognostic models. The FGL model divided patients in the discovery cohort (N = 145), validation cohort (N = 111), combination cohort (N = 256), and intermediate-risk group (N = 103) defined by the 2017 European LeukemiaNet (ELN) classification system into two groups with distinct survival. The high-risk group was enriched in apoptosis, hypoxia, TNFA signaling via NFKB, reactive oxygen species pathway, oxidative phosphorylation, and p53 pathway and associated with low immunity, while patients in the low-risk group may benefit from anti-TIM3 antibodies. In addition, patients within the FGL high-risk group might benefit from treatment using SB505124_1194 and JAK_8517_1739.

Conclusion: Our established FGL model may refine and provide a reference for clinical prognosis judgment and immunotherapies for P-AML patients.

The 17-gene stemness score associates with relapse risk and long-term outcomes following allogeneic haematopoietic cell transplantation in acute myeloid leukaemia

A 17-gene stemness (LSC17) score determines risk in acute myeloid leukaemia patients treated with standard chemotherapy regimens. The present study further analysed the impact of the LSC17 score at diagnosis on outcomes following allogeneic haematopoietic cell transplantation (HCT). Out of 452 patients with available LSC17 score, 123 patients received allogeneic HCT. Transplant outcomes, including overall (OS), leukaemia-free survival (LFS), relapse incidence (RI) and non-relapse mortality (NRM), were compared according to the LSC17 scored group. The patients with a low LSC17 score had higher OS (56.2%) and LFS (54.4%) at 2 years compared to patients with high LSC17 score (47.2%, p = 0.0237 for OS and 46.0%, p = 0.0181 for LFS). The low LSC17 score group also had a lower relapse rate at 2 years (12.7%) compared to 25.3% in the high LSC17 score group (p = 0.017), but no difference in NRM (p = 0.674). Worse outcomes in the high LSC17 score group for OS, LFS and relapse were consistently observed across all stratified sub-groups. The use of more intensive conditioning did not improve outcomes for either group. In contrast, chronic graft-versus-host-disease was associated with more favourable outcomes in both groups. The 17-gene stemness score is highly prognostic for survival and relapse risk following allogeneic HCT.

Relapsed acute myeloid leukemia in children and adolescents: current treatment options and future strategies

Pediatric acute myeloid leukemia (AML) develops from clonal expansion of hematopoietic precursor cells and is characterized by morphologic and cytomolecular heterogeneity. Although the past 40 years have seen significant improvements in overall survival, the prevailing treatment challenges in pediatric AML are the prevention of relapse and the management of relapsed disease. Approximately 25% of children and adolescents with AML suffer disease relapse and face a poor prognosis. Our greater understanding of the genomic, epigenomic, metabolomic, and immunologic pathophysiology of relapsed AML allows for better therapeutic strategies that are being developed for pediatric clinical trials. The development of biologically rational agents is critical as conventional chemotherapeutic salvage regimens are not effective for all patients and pose risk of organ toxicity in heavily pretreated patients. Another major barrier to improvement in outcomes for relapsed pediatric AML is the historic lack of availability and participation in clinical trials. There are ongoing efforts to launch multinational clinical trials of emerging therapies. The purpose of this review is to summarize currently available and newly developed therapies for relapsed pediatric AML.

Isolation, Maintenance and Expansion of Adult Hematopoietic Stem/Progenitor Cells and Leukemic Stem Cells

Hematopoietic stem cells (HSCs) are rare, self-renewing cells that perch on top of the hematopoietic tree. The HSCs ensure the constant supply of mature blood cells in a tightly regulated process producing peripheral blood cells. Intense efforts are ongoing to optimize HSC engraftment as therapeutic strategy to treat patients suffering from hematopoietic diseases. Preclinical research paves the way by developing methods to maintain, manipulate and expand HSCs ex vivo to understand their regulation and molecular make-up. The generation of a sufficient number of transplantable HSCs is the Holy Grail for clinical therapy. Leukemia stem cells (LSCs) are characterized by their acquired stem cell characteristics and are responsible for disease initiation, progression, and relapse. We summarize efforts, that have been undertaken to increase the number of long-term (LT)-HSCs and to prevent differentiation towards committed progenitors in ex vivo culture. We provide an overview and compare methods currently available to isolate, maintain and enrich HSC subsets, progenitors and LSCs and discuss their individual advantages and drawbacks.

Regulatory T cells promote the stemness of leukemia stem cells through IL10 cytokine-related signaling pathway

Regulatory T cells (Tregs) could maintain the characteristics of stem cells and inhibit the differentiation of normal hematopoietic stem/progenitor cells. Recent studies have shown that Tregs, as an important component of acute myeloid leukemia (AML) microenvironments, can help AML cells to evade immune surveillance. However, their function in directly regulating the stemness of AML cells remains elusive. In this study, the increased stemness of AML cells promoted by Tregs was verified in vitro and in vivo. The cytokines released by Tregs were explored, the highly expressed anti-inflammatory cytokine IL10 was found, which could promote the stemness of AML cells through the activation of PI3K/AKT signal pathway. Moreover, disrupting the IL10/IL10R/PI3K/AKT signal in AML/ETO c-kit^mut (A/Ec) leukemia mice could prolong the mice survival and reduce the stemness of A/Ec leukemia cells. Finally, it was confirmed in patient samples that the proportion of Tregs to leukemia stem cells (LSCs) was positively correlated, and in CD34⁺ primary AML cells, the activation of PI3K/AKT was stronger in patients with high Tregs' infiltration. After rhIL10 treatment, primary AML cells showed increased activation of PI3K/AKT signaling. Therefore, blocking the interaction between Tregs and AML cells may be a new approach to target LSCs in AML treatment.

A primary hierarchically organized patient-derived model enables in depth interrogation of stemness driven by the coding and non-coding genome

Many cancers are organized as cellular hierarchies sustained by cancer stem cells (CSC), whose eradication is crucial for achieving long-term remission. Difficulties to isolate and undertake in vitro and in vivo experimental studies of rare CSC under conditions that preserve their original properties currently constitute a bottleneck for identifying molecular mechanisms involving coding and non-coding genomic regions that govern stemness. We focussed on acute myeloid leukemia (AML) as a paradigm of the CSC model and developed a patient-derived system termed OCI-AML22 that recapitulates the cellular hierarchy driven by leukemia stem cells (LSC). Through classical flow sorting and functional analyses, we established that a single phenotypic population is highly enriched for LSC. The LSC fraction can be easily isolated and serially expanded in culture or in xenografts while faithfully recapitulating functional, transcriptional and epigenetic features of primary LSCs. A novel non-coding regulatory element was identified with a new computational approach using functionally validated primary AML LSC fractions and its role in LSC stemness validated through efficient CRISPR editing using methods optimized for OCI-AML22 LSC. Collectively, OCI-AML22 constitutes a valuable resource to uncover mechanisms governing CSC driven malignancies.

Deconvolution of Bulk Gene Expression Profiles with Single-Cell Transcriptomics to Develop a Cell Type Composition-Based Prognostic Model for Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is one of the malignant hematologic cancers with rapid progress and poor prognosis. Most AML prognostic stratifications focused on genetic abnormalities. However, none of them was established based on the cell type compositions (CTCs) of peripheral blood or bone marrow aspirates from patients at diagnosis. Here we sought to develop a novel prognostic model for AML in adults based on the CTCs. First, we applied the CIBERSORT algorithm to estimate the CTCs for patients from two public datasets (GSE6891 and TCGA-LAML) using a custom gene expression signature reference constructed by an AML single-cell RNA sequencing dataset (GSE116256). Then, a CTC-based prognostic model was established using least absolute shrinkage and selection operator Cox regression, termed CTC score. The constructed prognostic model CTC score comprised 3 cell types, GMP-like, HSC-like, and T. Compared with the low-CTC-score group, the high-CTC-score group showed a 1.57-fold [95% confidence interval (CI), 1.23 to 2.00; p = 0.0002] and a 2.32-fold (95% CI, 1.53 to 3.51; p < 0.0001) higher overall mortality risk in the training set (GSE6891) and validation set (TCGA-LAML), respectively. When adjusting for age at diagnosis, cytogenetic risk, and karyotype, the CTC score remained statistically significant in both the training set [hazard ratio (HR) = 2.25; 95% CI, 1.20 to 4.24; p = 0.0119] and the validation set (HR = 7.97; 95% CI, 2.95 to 21.56; p < 0.0001]. We further compared the performance of the CTC score with two gene expression-based prognostic scores: the 17-gene leukemic stem cell score (LSC17 score) and the AML prognostic score (APS). It turned out that the CTC score achieved comparable performance at 1-, 2-, 3-, and 5-years timepoints and provided independent and additional prognostic information different from the LSC17 score and APS. In conclusion, the CTC score could serve as a powerful prognostic marker for AML and has great potential to assist clinicians to formulate individualized treatment plans.

A Clinical Laboratory-Developed LSC17 Stemness Score Assay for Rapid Risk Assessment of Acute Myeloid Leukemia Patients

Leukemia stem cells (LSC) are linked to relapse in acute myeloid leukemia (AML). The LSC17 gene expression score robustly captures LSC stemness properties in AML and can be used to predict survival outcomes and response to therapy, enabling risk-adapted upfront treatment approaches. The LSC17 score was developed and validated in a research setting. To enable wide use of the LSC17 score in clinical decision-making, we established a Laboratory Developed Test (LDT) for the LSC17 score that can be deployed broadly in clinical molecular diagnostic laboratories. We extensively validated the LSC17 LDT in a College of American Pathologists/Clinical Laboratory Improvements Act (CAP/CLIA)-certified laboratory, determining specimen requirements, a synthetic control, and performance parameters for the assay. Importantly, we correlated values from the LSC17 LDT to clinical outcome for a reference cohort of AML patients, establishing a median assay value that can be used for clinical risk stratification of individual patients with newly-diagnosed AML. The assay was established in a second independent CAP/CLIA-certified laboratory and its technical performance validated using an independent cohort of AML patient samples, demonstrating that the LSC17 LDT can be readily implemented in other settings. This study enables the clinical use of the LSC17 score for upfront risk-adapted management of AML patients.

CircRNF220, not its linear cognate gene RNF220, regulates cell growth and is associated with relapse in pediatric acute myeloid leukemia

Background

Circular RNAs (circRNAs) constitute a family of transcripts with unique structures and have been confirmed to be critical in tumorigenesis and to be potential biomarkers or therapeutic targets. However, only a few circRNAs have been functionally characterized in pediatric acute myeloid leukemia (AML).

Methods

Here, we investigated the expression pattern of circRNAs in pediatric AML using a circRNA microarray. The characteristics, potential diagnostic value, and prognostic significance of circRNF220 were evaluated. A series of functional experiments were performed to investigate the role of circRNF220 in primary pediatric AML cells. Then we investigated the aberrant transcriptional networks regulated by circRNF220 in primary AML cells by RNA-seq. Furthermore, biotin RNA pulldown assays were implemented to verify the relationship between circRNF220 and miR-30a.

Results

We identified a circRNA, circRNF220, which was specifically abundant in and accumulated in the peripheral blood and bone marrow of pediatric patients with AML. It could distinguish AML from ALL and other hematological malignancies with high sensitivity and specificity. Significantly, circRNF220 expression independently predicted prognosis, while high expression of circRNF220 was an unfavorable prognostic marker for relapse. Furthermore, we characterized the function of circRNF220 and found that circRNF220 knockdown specifically inhibited proliferation and promoted apoptosis in AML cell lines and primary cells. Mechanistically, circRNF220 may act as an endogenous sponge of miR-30a to sequester miR-30a and inhibit its activity, which increases the expression of its targets MYSM1 and IER2 and implicated in AML relapse.

Conclusions

Collectively, these findings demonstrated that circRNF220 could be highly efficient and specific for the accurate diagnosis of pediatric AML, with implications for relapse prediction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12943-021-01395-7.

Insights into the molecular profiles of adult and paediatric acute myeloid leukaemia

Acute myeloid leukaemia (AML) is a clinically and molecularly heterogeneous disease characterised by uncontrolled proliferation, block in differentiation and acquired self-renewal of hematopoietic stem and myeloid progenitor cells. This results in the clonal expansion of myeloid blasts within the bone marrow and peripheral blood. The incidence of AML increases with age, and in childhood, AML accounts for 20% of all leukaemias. Whilst there are many clinical and biological similarities between paediatric and adult AML with continuum across the age range, many characteristics of AML are associated with age of disease onset. These include chromosomal aberrations, gene mutations and differentiation lineage. Following chemotherapy, AML cells that survive and result in disease relapse exist in an altered chemoresistant state. Molecular profiling currently represents a powerful avenue of experimentation to study AML cells from adults and children pre- and postchemotherapy as a means of identifying prognostic biomarkers and targetable molecular vulnerabilities that may be age-specific. This review highlights recent advances in our knowledge of the molecular profiles with a focus on transcriptomes and metabolomes, leukaemia stem cells and chemoresistant cells in adult and paediatric AML and focus on areas that hold promise for future therapies.

Quantitative single-cell proteomics as a tool to characterize cellular hierarchies

Large-scale single-cell analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems, but have largely been limited to RNA-based technologies. Here we present a comprehensive benchmarked experimental and computational workflow, which establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses. By exploiting a primary leukemia model system, we demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within this aberrant developmental hierarchy. Our approach is capable of consistently quantifying ~1000 proteins per cell across thousands of individual cells using limited instrument time. Furthermore, we develop a computational workflow (SCeptre) that effectively normalizes the data, integrates available FACS data and facilitates downstream analysis. The approach presented here lays a foundation for implementing global single-cell proteomics studies across the world.

Horizontal meta-analysis identifies common deregulated genes across AML subgroups providing a robust prognostic signature

Advances in transcriptomics have improved our understanding of leukemic development and helped to enhance the stratification of patients. The tendency of transcriptomic studies to combine AML samples, regardless of cytogenetic abnormalities, could lead to bias in differential gene expression analysis because of the differential representation of AML subgroups. Hence, we performed a horizontal meta-analysis that integrated transcriptomic data on AML from multiple studies, to enrich the less frequent cytogenetic subgroups and to uncover common genes involved in the development of AML and response to therapy. A total of 28 Affymetrix microarray data sets containing 3940 AML samples were downloaded from the Gene Expression Omnibus database. After stringent quality control, transcriptomic data on 1534 samples from 11 data sets, covering 10 AML cytogenetically defined subgroups, were retained and merged with the data on 198 healthy bone marrow samples. Differentially expressed genes between each cytogenetic subgroup and normal samples were extracted, enabling the unbiased identification of 330 commonly deregulated genes (CODEGs), which showed enriched profiles of myeloid differentiation, leukemic stem cell status, and relapse. Most of these genes were downregulated, in accordance with DNA hypermethylation. CODEGs were then used to create a prognostic score based on the weighted sum of expression of 22 core genes (CODEG22). The score was validated with microarray data of 5 independent cohorts and by quantitative real time-polymerase chain reaction in a cohort of 142 samples. CODEG22-based stratification of patients, globally and into subpopulations of cytologically healthy and elderly individuals, may complement the European LeukemiaNet classification, for a more accurate prediction of AML outcomes.

Deciphering molecular heterogeneity in pediatric AML using a cancer vs. normal transcriptomic approach

BACKGROUND

Still 30-40% of pediatric acute myeloid leukemia (pedAML) patients relapse. Delineation of the transcriptomic profile of leukemic subpopulations could aid in a better understanding of molecular biology and provide novel biomarkers.

METHODS

Using microarray profiling and quantitative PCR validation, transcript expression was measured in leukemic stem cells (LSC, n = 24) and leukemic blasts (L-blast, n = 25) from pedAML patients in comparison to hematopoietic stem cells (HSCs, n = 19) and control myeloblasts (C-blast, n = 20) sorted from healthy subjects. Gene set enrichment analysis was performed to identify relevant gene set enrichment signatures, and functional protein associations were identified by STRING analysis.

RESULTS

Highly significantly overexpressed genes in LSC and L-blast were identified with a vast majority not studied in AML. CDKN1A, CFP, and CFD (LSC) and HOMER3, CTSA, and GADD45B (L-blast) represent potentially interesting biomarkers and therapeutic targets. Eleven LSC downregulated targets were identified that potentially qualify as tumor suppressor genes, with MYCT1, PBX1, and PTPRD of highest interest. Inflammatory and immune dysregulation appeared to be perturbed biological networks in LSC, whereas dysregulated metabolic profiles were observed in L-blast.

CONCLUSION

Our study illustrates the power of taking into account cell population heterogeneity and reveals novel targets eligible for functional evaluation and therapy in pedAML.

IMPACT

Novel transcriptional targets were discovered showing a significant differential expression in LSCs and blasts from pedAML patients compared to their normal counterparts from healthy controls. Deregulated pathways, including immune and metabolic dysregulation, were addressed for the first time in children, offering a deeper understanding of the molecular pathogenesis. These novel targets have the potential of acting as biomarkers for risk stratification, follow-up, and targeted therapy. Multiple LSC-downregulated targets endow tumor suppressor roles in other cancer entities, and further investigation whether hypomethylating therapy could result into LSC eradication in pedAML is warranted.

Identification of hub genes associated with adult acute myeloid leukemia progression through weighted gene co-expression network analysis

Acute myeloid leukemia (AML) is a malignancy of hematopoietic stem cells. Although many candidate genes such as CEBPA, FLT3, IDH1, and IDH2 have been associated with AML initiation and prognosis, the molecular mechanisms underlying this disease remain unclear. In this study, we used a systemic co-expression analysis method, namely weighted gene co-expression network analysis (WGCNA), to identify new candidate genes associated with adult AML progression and prognosis. We identified around 5,138 differentially expressed genes (DEGs) between AML samples (from The Cancer Genome Atlas database) and normal control samples (from the Genotype-Tissue Expression database). WGCNA identified nine co-expression modules with significant differences based on the DEGs. Among modules, the turquoise and blue ones were the most relevant to AML (P-value: turquoise 0, blue 4.64E-77). GO term and KEGG pathway analyses revealed that pathways that are commonly dysregulated in AML were all enriched in the blue and turquoise modules. A total of 15 hub genes were identified to be crucial for AML progression. PIVOT analysis revealed non-coding RNAs, transcriptional factors, and drugs associated with the hub genes. Finally, survival analysis revealed that one of the hub genes, CEACAM5, was significantly associated with AML prognosis and could serve as a potential target for AML treatment.

Studying leukemia stem cell properties and vulnerabilities with human iPSCs

The reprogramming of cancer cells into induced pluripotent stem cells (iPSCs) can capture entire cancer genomes, and thus create genetically faithful models of human cancers. By providing stringent genetically clonal conditions, iPSC modeling can also unveil non-genetic sources of cancer heterogeneity and provide a unique opportunity to study them separately from genetic sources, as we recently showed in an iPSC-based model of acute myeloid leukemia (AML). Genetically clonal iPSCs, derived from a patient with AML, reproduce, upon hematopoietic differentiation, phenotypic and functional heterogeneity with all the hallmarks of a leukemia stem cell (LSC) hierarchy. Here we discuss the lessons that can be learned about the LSC state, its plasticity, stability and genetic and epigenetic determinants from iPSC modeling. We also discuss the practical and translational implications of exploiting AML-iPSCs to prospectively isolate large numbers of iLSCs for large-scale experiments, such as screens, and for discovery of new therapeutic targets specific to AML LSCs.

Establishing and validating a pathway prognostic signature in pancreatic cancer based on miRNA and mRNA sets using GSVA

Pancreatic cancer (PC) is a severe disease with the highest mortality rate among various cancers. It is urgent to find an effective and accurate way to predict the survival of PC patients. Gene set variation analysis (GSVA) was used to establish and validate a miRNA set-based pathway prognostic signature for PC (miPPSPC) and a mRNA set-based pathway prognostic signature for PC (mPPSPC) in independent datasets. An optimized miPPSPC was constructed by combining clinical parameters. The miPPSPC, optimized miPPSPC and mPPSPC were established and validated to predict the survival of PC patients and showed excellent predictive ability. Four metabolic pathways and one oxidative stress pathway were identified in the miPPSPC, whereas linoleic acid metabolism and the pentose phosphate pathway were identified in the mPPSPC. Key factors of the pentose phosphate pathway and linoleic acid metabolism, G6PD and CYP2C8/9/18/19, respectively, are related to the survival of PC patients according to our tissue microarray. Thus, the miPPSPC, optimized miPPSPC and mPPSPC can predict the survival of PC patients efficiently and precisely. The metabolic and oxidative stress pathways may participate in PC progression.

AML risk stratification models utilizing ELN-2017 guidelines and additional prognostic factors: a SWOG report

Background

The recently updated European LeukemiaNet risk stratification guidelines combine cytogenetic abnormalities and genetic mutations to provide the means to triage patients with acute myeloid leukemia for optimal therapies. Despite the identification of many prognostic factors, relatively few have made their way into clinical practice.

Methods

In order to assess and improve the performance of the European LeukemiaNet guidelines, we developed novel prognostic models using the biomarkers from the guidelines, age, performance status and select transcript biomarkers. The models were developed separately for mononuclear cells and viable leukemic blasts from previously untreated acute myeloid leukemia patients (discovery cohort, N = 185) who received intensive chemotherapy. Models were validated in an independent set of similarly treated patients (validation cohort, N = 166).

Results

Models using European LeukemiaNet guidelines were significantly associated with clinical outcomes and, therefore, utilized as a baseline for comparisons. Models incorporating age and expression of select transcripts with biomarkers from European LeukemiaNet guidelines demonstrated higher area under the curve and C-statistics but did not show a substantial improvement in performance in the validation cohort. Subset analyses demonstrated that models using only the European LeukemiaNet guidelines were a better fit for younger patients (age < 55) than for older patients. Models integrating age and European LeukemiaNet guidelines visually showed more separation between risk groups in older patients. Models excluding results for ASXL1, CEBPA, RUNX1 and TP53, demonstrated that these mutations provide a limited overall contribution to risk stratification across the entire population, given the low frequency of mutations and confounding risk factors.

Conclusions

While European LeukemiaNet guidelines remain a critical tool for triaging patients with acute myeloid leukemia, the findings illustrate the need for additional prognostic factors, including age, to improve risk stratification.

A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort study

Acute myeloid leukemia (AML) is a genetically heterogeneous hematological malignancy with variable responses to chemotherapy. Although recurring cytogenetic abnormalities and gene mutations are important predictors of outcome, 50% to 70% of AMLs harbor normal or risk-indeterminate karyotypes. Therefore, identifying more effective biomarkers predictive of treatment success and failure is essential for informing tailored therapeutic decisions. We applied an artificial neural network (ANN)-based machine learning approach to a publicly available data set for a discovery cohort of 593 adults with nonpromyelocytic AML. ANN analysis identified a parsimonious 3-gene expression signature comprising CALCRL, CD109, and LSP1, which was predictive of event-free survival (EFS) and overall survival (OS). We computed a prognostic index (PI) using normalized gene-expression levels and β-values from subsequently created Cox proportional hazards models, coupled with clinically established prognosticators. Our 3-gene PI separated the adult patients in each European LeukemiaNet cytogenetic risk category into subgroups with different survival probabilities and identified patients with very high-risk features, such as those with a high PI and either FLT3 internal tandem duplication or nonmutated nucleophosmin 1. The PI remained significantly associated with poor EFS and OS after adjusting for established prognosticators, and its ability to stratify survival was validated in 3 independent adult cohorts (n = 905 subjects) and 1 cohort of childhood AML (n = 145 subjects). Further in silico analyses established that AML was the only tumor type among 39 distinct malignancies for which the concomitant upregulation of CALCRL, CD109, and LSP1 predicted survival. Therefore, our ANN-derived 3-gene signature refines the accuracy of patient stratification and the potential to significantly improve outcome prediction.

A six-gene leukemic stem cell score identifies high risk pediatric acute myeloid leukemia

Recently, mRNA-expression signature enriched in LSCs was used to create a 17-gene leukemic stem cell (LSC17) score predictive of prognosis in adult AML. By fitting a Cox-LASSO regression model to the clinical outcome and gene-expression levels of LSC enriched genes in 163 pediatric participants of the AML02 multi-center clinical trial (NCT00136084), we developed a 6-gene LSC score of prognostic value in pediatric AML (pLSC6). In the AML02 cohort, the 5-year event-free survival (EFS) of patients within low-pLSC6 group (n=97) was 78.3 (95% CI=70.5–86.9%) as compared to 34.5(95% CI=24.7–48.2 %) in patients within high-pLSC6 group (n=66 subjects), p<0.00001. pLSC6 remained significantly associated with EFS and overall survival (OS) after adjusting for induction 1-MRD status, risk-group, FLT3-status, WBC-count at diagnosis and age. pLSC6 formula developed in the AML02 cohort was validated in the pediatric AML-TARGET project data (n=205), confirming its prognostic value in both single-predictor and multiple-predictor Cox regression models. In both cohorts, pLSC6 predicted outcome of transplant patients, suggesting it as a useful criterion for transplant referrals. Our results suggest that pLSC6 score holds promise in redefining initial risk-stratification and identifying poor risk AML thereby providing guidance for developing novel treatment strategies.

Cancer Stem Cells in the Development of Novel Therapeutics for Refractory Pediatric Leukemia

Although treatment strategies for pediatric leukemia have improved overall survival rates in the recent past, relapse rates in certain subgroups such as infant leukemia remain unacceptably high. Despite undergoing extensive chemotherapy designed to target the rapidly proliferating leukemia cells, many of these children experience relapse. In refractory leukemia, the existence of cell populations with stemness characteristics, termed leukemia stem cells (LSCs), which remain quiescent and subsequently replenish the blast population, has been described. A significant body of evidence exists, derived largely from xenograft models of adult acute myeloid leukemia, to support the idea that LSCs may play a fundamental role in refractory disease. In addition, clinical studies have also linked LSCs with increased minimal residual disease, higher relapse rate, and decreased survival rates in these patients. Recently, a number of reports have addressed effective ways to utilize new-generation genomic sequencing and transcriptomic analyses to identify targeted therapeutic agents aimed at LSCs, while sparing normal hematopoietic stem cells. These data underscore the value of timely translation of knowledge from adult studies to the unique molecular and physiological characteristics seen in pediatric leukemia. We aim to summarize this article in the rapidly expanding field of stem cell biology in hematopoietic malignancies, focusing particularly on relevant preclinical models and novel targeted therapeutics, and their applicability to childhood leukemia.

CD123 as a Therapeutic Target in the Treatment of Hematological Malignancies

The interleukin-3 receptor alpha chain (IL-3Rα), more commonly referred to as CD123, is widely overexpressed in various hematological malignancies, including acute myeloid leukemia (AML), B-cell acute lymphoblastic leukemia, hairy cell leukemia, Hodgkin lymphoma and particularly, blastic plasmacytoid dendritic neoplasm (BPDCN). Importantly, CD123 is expressed at both the level of leukemic stem cells (LSCs) and more differentiated leukemic blasts, which makes CD123 an attractive therapeutic target. Various agents have been developed as drugs able to target CD123 on malignant leukemic cells and on the normal counterpart. Tagraxofusp (SL401, Stemline Therapeutics), a recombinant protein composed of a truncated diphtheria toxin payload fused to IL-3, was approved for use in patients with BPDCN in December of 2018 and showed some clinical activity in AML. Different monoclonal antibodies directed against CD123 are under evaluation as antileukemic drugs, showing promising results either for the treatment of AML minimal residual disease or of relapsing/refractory AML or BPDCN. Finally, recent studies are exploring T cell expressing CD123 chimeric antigen receptor-modified T-cells (CAR T) as a new immunotherapy for the treatment of refractory/relapsing AML and BPDCN. In December of 2018, MB-102 CD123 CAR T developed by Mustang Bio Inc. received the Orphan Drug Designation for the treatment of BPDCN. In conclusion, these recent studies strongly support CD123 as an important therapeutic target for the treatment of BPDCN, while a possible in the treatment of AML and other hematological malignancies will have to be evaluated by in the ongoing clinical studies.

Not Only Mutations Matter: Molecular Picture of Acute Myeloid Leukemia Emerging from Transcriptome Studies

The last two decades of genome-scale research revealed a complex molecular picture of acute myeloid leukemia (AML). On the one hand, a number of mutations were discovered and associated with AML diagnosis and prognosis; some of them were introduced into diagnostic tests. On the other hand, transcriptome studies, which preceded AML exome and genome sequencing, remained poorly translated into clinics. Nevertheless, gene expression studies significantly contributed to the elucidation of AML pathogenesis and indicated potential therapeutic directions. The power of transcriptomic approach lies in its comprehensiveness; we can observe how genome manifests its function in a particular type of cells and follow many genes in one test. Moreover, gene expression measurement can be combined with mutation detection, as high-impact mutations are often present in transcripts. This review sums up 20 years of transcriptome research devoted to AML. Gene expression profiling (GEP) revealed signatures distinctive for selected AML subtypes and uncovered the additional within-subtype heterogeneity. The results were particularly valuable in the case of AML with normal karyotype which concerns up to 50% of AML cases. With the use of GEP, new classes of the disease were identified and prognostic predictors were proposed. A plenty of genes were detected as overexpressed in AML when compared to healthy control, including KIT, BAALC, ERG, MN1, CDX2, WT1, PRAME, and HOX genes. High expression of these genes constitutes usually an unfavorable prognostic factor. Upregulation of FLT3 and NPM1 genes, independent on their mutation status, was also reported in AML and correlated with poor outcome. However, transcriptome is not limited to the protein-coding genes; other types of RNA molecules exist in a cell and regulate genome function. It was shown that microRNA (miRNA) profiles differentiated AML groups and predicted outcome not worse than protein-coding gene profiles. For example, upregulation of miR-10a, miR-10b, and miR-196b and downregulation of miR-192 were found as typical of AML with NPM1 mutation whereas overexpression of miR-155 was associated with FLT3-internal tandem duplication (FLT3-ITD). Development of high-throughput technologies and microarray replacement by next generation sequencing (RNA-seq) enabled uncovering a real variety of leukemic cell transcriptomes, reflected by gene fusions, chimeric RNAs, alternatively spliced transcripts, miRNAs, piRNAs, long noncoding RNAs (lncRNAs), and their special type, circular RNAs. Many of them can be considered as AML biomarkers and potential therapeutic targets. The relations between particular RNA puzzles and other components of leukemic cells and their microenvironment, such as exosomes, are now under investigation. Hopefully, the results of this research will shed the light on these aspects of AML pathogenesis which are still not completely understood.

Emerging Therapies for Acute Myelogenus Leukemia Patients Targeting Apoptosis and Mitochondrial Metabolism

Acute Myelogenous Leukemia (AML) is a malignant disease of the hematopoietic cells, characterized by impaired differentiation and uncontrolled clonal expansion of myeloid progenitors/precursors, resulting in bone marrow failure and impaired normal hematopoiesis. AML comprises a heterogeneous group of malignancies, characterized by a combination of different somatic genetic abnormalities, some of which act as events driving leukemic development. Studies carried out in the last years have shown that AML cells invariably have abnormalities in one or more apoptotic pathways and have identified some components of the apoptotic pathway that can be targeted by specific drugs. Clinical results deriving from studies using B-cell lymphoma 2 (BCL-2) inhibitors in combination with standard AML agents, such as azacytidine, decitabine, low-dose cytarabine, provided promising results and strongly support the use of these agents in the treatment of AML patients, particularly of elderly patients. TNF-related apoptosis-inducing ligand (TRAIL) and its receptors are frequently deregulated in AML patients and their targeting may represent a promising strategy for development of new treatments. Altered mitochondrial metabolism is a common feature of AML cells, as supported through the discovery of mutations in the isocitrate dehydrogenase gene and in mitochondrial electron transport chain and of numerous abnormalities of oxidative metabolism existing in AML subgroups. Overall, these observations strongly support the view that the targeting of mitochondrial apoptotic or metabolic machinery is an appealing new therapeutic perspective in AML.