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

Long-read epigenomic diagnosis and prognosis of Acute Myeloid Leukemia

Acute Myeloid Leukemia (AML) is an aggressive cancer with dismal outcomes, vast subtype heterogeneity, and suboptimal risk stratification. In this study, we harmonized DNA methylation data from 3,314 patients across 11 cohorts to develop the Acute Leukemia Methylome Atlas (ALMA) of diagnostic relevance that predicted 27 WHO 2022 acute leukemia subtypes with an overall accuracy of 96.3% in discovery and 90.1% in validation cohorts. Specifically, for AML, we also developed AML Epigenomic Risk, a prognostic classifier of overall survival (OS) (HR=4.40; 95% CI=3.45-5.61; P<0.0001), and a targeted 38CpG AML signature using a stepwise EWAS-CoxPH-LASSO model predictive of OS (HR=3.84; 95% CI=3.01-4.91; P<0.0001). Finally, we developed a specimen-to-result protocol for simultaneous whole-genome and epigenome sequencing that accurately predicted diagnoses and prognoses from twelve prospectively collected patient samples using long-read sequencing. Our study unveils a new paradigm in acute leukemia management by leveraging DNA methylation for diagnostic and prognostic applications.

ARMH1 is a novel marker associated with poor pediatric AML outcomes that affect the fatty acid synthesis and cell cycle pathways

Introduction

Despite remarkable progress in Pediatric Acute Myeloid Leukemia (pAML) treatments, the relapsed disease remains difficult to treat, making it pertinent to identify novel biomarkers of prognostic/therapeutic significance.

Material and methods

Bone marrow samples from 21 pAML patients were analyzed using single cell RNA sequencing, functional assays with ARMH1 knockdown and overexpression were performed in leukemia cell lines to evaluate impact on proliferation and migration, and chemotherapy sensitivity. Mitochondrial function was assessed via Seahorse assay, ARMH1 interacting proteins were studied using co-immunoprecipitation. Bulk RNA-seq was performed on ARMH1knockdown and over expressing cell lines to evaluate the pathways and networks impacted by ARMH1.

Results

Our data shows that ARMH1, a novel cancer-associated gene, is highly expressed in the malignant blast cells of multiple pediatric hematologic malignancies, including AML, T/B-ALL, and T/B-MPAL. Notably, ARMH1 expression is significantly elevated in blast cells of patients who relapsed or have a high-risk cytogenetic profile (MLL) compared to standard-risk (RUNX1, inv (16)). ARMH1 expression is also significantly correlated with the pediatric leukemia stem cell score of 6 genes (LSC6) associated with poor outcomes. Perturbation of ARMH1 (knockdown and overexpression) in leukemia cell lines significantly impacted cell proliferation and migration. The RNA-sequencing analysis on multiple ARMH1 knockdown and overexpressing cell lines established an association with mitochondrial fatty acid synthesis and cell cycle pathways.The investigation of the mitochondrial matrix shows that pharmacological inhibition of a key enzyme in fatty acid synthesis regulation, CPT1A, resulted in ARMH1 downregulation. ARMH1 knockdown also led to a significant reduction in CPT1A and ATP production as well as Oxygen Consumption Rate. Our data indicates that downregulating ARMH1 impacts cell proliferation by reducing key cell cycle regulators such as CDCA7 and EZH2. Further, we also established that ARMH1 is a key physical interactant of EZH2, associated with multiple cancers.

Conclusion

Our findings underscore further evaluation of ARMH1 as a potential candidate for targeted therapies and stratification of aggressive pAML to improve outcomes.

Defective ribosome assembly impairs leukemia progression in a murine model of acute myeloid leukemia

Despite an advanced understanding of disease mechanisms, the current therapeutic regimen fails to cure most patients with acute myeloid leukemia (AML). In the present study, we address the role of ribosome assembly in leukemia cell function. We apply patient datasets and murine models to demonstrate that immature leukemia cells in mixed-lineage leukemia-rearranged AML are characterized by relatively high ribosome biogenesis and protein synthesis rates. Using a model with inducible regulation of ribosomal subunit joining, we show that defective ribosome assembly extends survival in mice with AML. Single-cell RNA sequencing and proteomic analyses reveal that leukemia cell adaptation to defective ribosome assembly is associated with an increase in ribosome biogenesis and deregulation of the transcription factor landscape. Finally, we demonstrate that defective ribosome assembly shows antileukemia efficacy in p53-deficient AML. Our study unveils the critical requirement of a high protein synthesis rate for leukemia progression and highlights ribosome assembly as a therapeutic target in AML.

High CD44 expression and enhanced E-selectin binding identified as biomarkers of chemoresistant leukemic cells in human T-ALL

T-cell acute lymphoblastic leukemia (T-ALL) is a hematopoietic malignancy characterized by increased proliferation and incomplete maturation of T-cell progenitors, for which relapse is often of poor prognosis. To improve patient outcomes, it is critical to understand the chemoresistance mechanisms arising from cell plasticity induced by the bone marrow (BM) microenvironment. Single-cell RNA sequencing of human T-ALL cells from adipocyte-rich and adipocyte-poor BM revealed a distinct leukemic cell population defined by quiescence and high CD44 expression (Ki67neg/lowCD44high). During in vivo treatment, these cells evaded chemotherapy, and were further called Chemotherapy-resistant Leukemic Cells (CLCs). Patient sample analysis revealed Ki67neg/lowCD44high CLCs at diagnosis and during relapse, with each displaying a specific transcriptomic signature. Interestingly, CD44high expression in T-ALL Ki67neg/low CLCs was associated with E-selectin binding. Analysis of 39 human T-ALL samples revealed significantly enhanced E-selectin binding activity in relapse/refractory samples compared with drug-sensitive samples. These characteristics of chemoresistant T-ALL CLCs provide key insights for prognostic stratification and novel therapeutic options.

A simplified and robust risk stratification model for stem cell transplantation in pediatric acute myeloid leukemia

The efficacy of stem cell transplantation (SCT) in pediatric acute myeloid leukemia (pAML) remains unsatisfactory due to the limitations of existing prognostic models in predicting efficacy and selecting suitable candidates. This study aims to develop a cytomolecular risk stratification-independent prognostic model for SCT in pAML patients at CR1 stage. The pAML SCT model, based on age, KMT2A rearrangement (KMT2A-r), and minimal residual disease at end of course 1 (MRD1), effectively classifies patients into low-, intermediate-, and high-risk groups. We validate the effectiveness in an internal validation cohort and in four external validation cohorts, consisting of different graft sources and donors. Moreover, by incorporating the FMS-like tyrosine kinase 3/internal tandem duplication (FLT3/ITD) allelic ratio, the pAML SCT model is refined, enhancing its ability to effectively select suitable candidates. We develop a simple and robust risk stratification model for pAML patients undergoing SCT, to aid in risk stratification and inform pretransplant decision-making at CR1 stage.

Metabolic dependencies of acute myeloid leukemia stem cells

Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy primarily driven by an immature population of AML cells termed leukemia stem cells (LSCs) that are implicated in AML development, chemoresistance, and relapse. An emerging area of research in AML focuses on identifying and targeting the aberrant metabolism in LSCs. Dysregulated metabolism is involved in sustaining functional properties of LSCs, impeding myeloid differentiation, and evading programmed cell death, both in the process of leukemogenesis and in response to chemotherapy. This review discusses recent discoveries regarding the aberrant metabolic processes of AML LSCs that have begun to change the therapeutic landscape of AML.

The Proteasome-Family-Members-Based Prognostic Model Improves the Risk Classification for Adult Acute Myeloid Leukemia

Background: The accumulation of diverse molecular and cytogenetic variations contributes to the heterogeneity of acute myeloid leukemia (AML), a cluster of hematologic malignancies that necessitates enhanced risk evaluation for prognostic prediction and therapeutic guidance. The ubiquitin-proteasome system plays a crucial role in AML; however, the specific contributions of 49 core proteasome family members (PSMs) in this context remain largely unexplored. Methods: The expression and survival significance of 49 PSMs in AML were evaluated using the data from BeatAML2.0, TCGA, and the GEO database, mainly through the K-M plots, differential genes enrichment analysis, and candidate compounds screening via R language and statistical software. Results: we employed LASSO and Cox regression analyses and developed a model comprising three PSMs (PSMB8, PSMG1, and PSMG4) aimed at predicting OS in adult AML patients, utilizing expression profiles from the BeatAML2.0 training datasets. Patients with higher risk scores were predominantly found in the AML-M2 subtype, exhibited poorer ELN stratification, showed no complete remission following induction therapies, and had a higher mortality status. Consistently, significantly worse OS was observed in high-risk patients across both the training and three validation datasets, underscoring the robust predictive capability of the three-PSMs model for AML outcomes. This model elucidated the distinct genetic abnormalities landscape between high- and low-risk groups and enhanced the ELN risk stratification system. Ultimately, the three-PSMs risk score captured AML-specific gene expression signatures, providing a molecular basis for selecting potential therapeutic agents. Conclusions: In summary, these findings manifested the significant potential of the PSM model for predicting AML survival and informed treatment strategies.

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.

MiRNA expression as outcome predictor in pediatric AML: systematic evaluation of a new model

Accurately predicting patient outcomes is essential for optimizing treatment and improving outcomes in pediatric acute myeloid leukemia (AML). In recent years, microRNAs have emerged as a promising prognostic marker, with a growing body of evidence supporting their potential predictive value. We systematically reviewed all previous studies that have analyzed the expression of microRNAs as predictors of survival in pediatric AML and found 16 microRNAs and 4 microRNA signatures previously proposed as predictors of survival. We then used a public access cohort of 1414 pediatric AML patients from the TARGET project to develop a new predictive model using penalized lasso Cox regression based on microRNA expression. Here we propose a new score based on a 37-microRNA signature that is associated with AML and is able to predict survival more accurately than previous microRNA-based methods.

Integrated drug resistance and leukemic stemness gene-expression scores predict outcomes in large cohort of over 3500 AML patients from 10 trials

In this study, we leveraged machine-learning tools by evaluating expression of genes of pharmacological relevance to standard-AML chemotherapy (ara-C/daunorubicin/etoposide) in a discovery-cohort of pediatric AML patients (N = 163; NCT00136084 ) and defined a 5-gene-drug resistance score (ADE-RS5) that was predictive of outcome (high MRD1 positivity p = 0.013; lower EFS p < 0.0001 and OS p < 0.0001). ADE-RS5 was integrated with a previously defined leukemic-stemness signature (pLSC6) to classify patients into four groups. ADE-RS5, pLSC6 and integrated-score was evaluated for association with outcome in one of the largest assembly of ~3600 AML patients from 10 independent cohorts (1861 pediatric and 1773 adult AML). Patients with high ADE-RS5 had poor outcome in validation cohorts and the previously reported pLSC6 maintained strong significant association in all validation cohorts. For pLSC6/ADE-RS5-integrated-score analysis, using Group-1 (low-scores for ADE-RS5 and pLSC6) as reference, Group-4 (high-scores for ADE-RS5 and pLSC6) showed worst outcome (EFS: p < 0.0001 and OS: p < 0.0001). Groups-2/3 (one high and one low-score) showed intermediate outcome (p < 0.001). Integrated score groups remained an independent predictor of outcome in multivariable-analysis after adjusting for established prognostic factors (EFS: Group 2 vs. 1, HR = 4.68, p < 0.001, Group 3 vs. 1, HR = 3.22, p = 0.01, and Group 4 vs. 1, HR = 7.26, p < 0.001). These results highlight the significant prognostic value of transcriptomics-based scores capturing disease aggressiveness through pLSC6 and drug resistance via ADE-RS5. The pLSC6 stemness score is a significant predictor of outcome and associates with high-risk group features, the ADE-RS5 drug resistance score adds further value, reflecting the clinical utility of simultaneous testing of both for optimizing treatment strategies.

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.

Preclinical efficacy of targeting epigenetic mechanisms in AML with 3q26 lesions and EVI1 overexpression

AML with chromosomal alterations involving 3q26 overexpresses the transcription factor (TF) EVI1, associated with therapy refractoriness and inferior overall survival in AML. Consistent with a CRISPR screen highlighting BRD4 dependency, treatment with BET inhibitor (BETi) repressed EVI1, LEF1, c-Myc, c-Myb, CDK4/6, and MCL1, and induced apoptosis of AML cells with 3q26 lesions. Tegavivint (TV, BC-2059), known to disrupt the binding of nuclear β-catenin and TCF7L2/LEF1 with TBL1, also inhibited co-localization of EVI1 with TBL1 and dose-dependently induced apoptosis in AML cell lines and patient-derived (PD) AML cells with 3q26.2 lesions. TV treatment repressed EVI1, attenuated enhancer activity at ERG, TCF7L2, GATA2 and MECOM loci, abolished interactions between MYC enhancers, repressing AML stemness while upregulating mRNA gene-sets of interferon/inflammatory response, TGF-β signaling and apoptosis-regulation. Co-treatment with TV and BETi or venetoclax induced synergistic in vitro lethality and reduced AML burden, improving survival of NSG mice harboring xenografts of AML with 3q26.2 lesions.

Cellular hierarchy insights reveal leukemic stem-like cells and early death risk in acute promyelocytic leukemia

Acute promyelocytic leukemia (APL) represents a paradigm for targeted differentiation therapy, with a minority of patients experiencing treatment failure and even early death. We here report a comprehensive single-cell analysis of 16 APL patients, uncovering cellular compositions and their impact on all-trans retinoic acid (ATRA) response in vivo and early death. We unveil a cellular differentiation hierarchy within APL blasts, rooted in leukemic stem-like cells. The oncogenic PML/RARα fusion protein exerts branch-specific regulation in the APL trajectory, including stem-like cells. APL cohort analysis establishes an association of leukemic stemness with elevated white blood cell counts and FLT3-ITD mutations. Furthermore, we construct an APL-specific stemness score, which proves effective in assessing early death risk. Finally, we show that ATRA induces differentiation of primitive blasts and patients with early death exhibit distinct stemness-associated transcriptional programs. Our work provides a thorough survey of APL cellular hierarchies, offering insights into cellular dynamics during targeted therapy.

Integrative single-cell expression and functional studies unravels a sensitization to cytarabine-based chemotherapy through HIF pathway inhibition in AML leukemia stem cells

Relapse remains a major challenge in the clinical management of acute myeloid leukemia (AML) and is driven by rare therapy-resistant leukemia stem cells (LSCs) that reside in specific bone marrow niches. Hypoxia signaling maintains cells in a quiescent and metabolically relaxed state, desensitizing them to chemotherapy. This suggests the hypothesis that hypoxia contributes to the chemoresistance of AML-LSCs and may represent a therapeutic target to sensitize AML-LSCs to chemotherapy. Here, we identify HIFhigh and HIFlow specific AML subgroups (inv(16)/t(8;21) and MLLr, respectively) and provide a comprehensive single-cell expression atlas of 119,000 AML cells and AML-LSCs in paired diagnostic-relapse samples from these molecular subgroups. The HIF/hypoxia pathway signature is attenuated in AML-LSCs compared with more differentiated AML cells but is more expressed than in healthy hematopoietic cells. Importantly, chemical inhibition of HIF cooperates with standard-of-care chemotherapy to impair AML growth and to substantially eliminate AML-LSCs in vitro and in vivo. These findings support the HIF pathway in the stem cell-driven drug resistance of AML and unravel avenues for combinatorial targeted and chemotherapy-based approaches to specifically eliminate AML-LSCs.

A new genomic framework to categorize pediatric acute myeloid leukemia

Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 887 pAML into 23 mutually distinct molecular categories, including new major entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a new prognostic framework for pAML based on these updated molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.

Development and validation of a promising 5-gene prognostic model for pediatric acute myeloid leukemia

Risk classification in pediatric acute myeloid leukemia (P-AML) is crucial for personalizing treatments. Thus, we aimed to establish a risk-stratification tool for P-AML patients and eventually guide individual treatment. A total of 256 P-AML patients with accredited mRNA-seq data from the TARGET database were divided into training and internal validation datasets. A gene-expression-based prognostic score was constructed for overall survival (OS), by using univariate Cox analysis, LASSO regression analysis, Kaplan-Meier (K-M) survival, and multivariate Cox analysis. A P-AML-5G prognostic score bioinformatically derived from expression levels of 5 genes (ZNF775, RNFT1, CRNDE, COL23A1, and TTC38), clustered P-AML patients in training dataset into high-risk group (above optimal cut-off) with shorter OS, and low-risk group (below optimal cut-off) with longer OS (p < 0.0001). Meanwhile, similar results were obtained in internal validation dataset (p = 0.005), combination dataset (p < 0.001), two treatment sub-groups (p < 0.05), intermediate-risk group defined with the Children's Oncology Group (COG) (p < 0.05) and an external Japanese P-AML dataset (p = 0.005). The model was further validated in the COG study AAML1031(p = 0.001), and based on transcriptomic analysis of 943 pediatric patients and 70 normal bone marrow samples from this dataset, two genes in the model demonstrated significant differential expression between the groups [all log2(foldchange) > 3, p < 0.001]. Independent of other prognostic factors, the P-AML-5G groups presented the highest concordance-index values in training dataset, chemo-therapy only treatment subgroups of the training and internal validation datasets, and whole genome-sequencing subgroup of the combined dataset, outperforming two Children's Oncology Group (COG) risk stratification systems, 2022 European LeukemiaNet (ELN) risk classification tool and two leukemic stem cell expression-based models. The 5-gene prognostic model generated by a single assay can further refine the current COG risk stratification system that relies on numerous tests and may have the potential for the risk judgment and identification of the high-risk pediatric AML patients receiving chemo-therapy only treatment.

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.

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.

MRD-directed and risk-adapted individualized stratified treatment of AML

Measurable residual disease (MRD) has been widely recognized as a biomarker for deeply evaluating complete remission (CR), predicting relapse, guiding pre-emptive interventions, and serving as an endpoint surrogate for drug testing. However, despite the emergence of new technologies, there remains a lack of comprehensive understanding regarding the proper techniques, sample materials, and optimal time points for MRD assessment. In this review, we summarized the MRD methods, sample sources, and evaluation frequency according to the risk category of the European Leukemia Net (ELN) 2022. Additionally, we emphasize the importance of properly utilizing and combining these technologies. We have also refined the flowchart outlining each time point for pre-emptive interventions and intervention paths. The evaluation of MRD in acute myeloid leukemia (AML) is sophisticated, clinically applicable, and technology-dependent, and necessitates standardized approaches and further research.

A urine extracellular vesicle lncRNA classifier for high-grade prostate cancer and increased risk of progression: A multi-center study

To construct a urine extracellular vesicle long non-coding RNA (lncRNA) classifier that can detect high-grade prostate cancer (PCa) of grade group 2 or greater and estimate the risk of progression during active surveillance, we identify high-grade PCa-specific lncRNAs by combined analyses of cohorts from TAHSY, TCGA, and the GEO database. We develop and validate a 3-lncRNA diagnostic model (Clnc, being made of AC015987.1, CTD-2589M5.4, RP11-363E6.3) that can detect high-grade PCa. Clnc shows higher accuracy than prostate cancer antigen 3 (PCA3), multiparametric magnetic resonance imaging (mpMRI), and two risk calculators (Prostate Cancer Prevention Trial [PCPT]-RC 2.0 and European Randomized Study of Screening for Prostate Cancer [ERSPC]-RC) in the training cohort (n = 350), two independent cohorts (n = 232; n = 251), and TCGA cohort (n = 499). In the prospective active surveillance cohort (n = 182), Clnc at diagnosis remains a powerful independent predictor for overall active surveillance progression. Thus, Clnc is a potential biomarker for high-grade PCa and can also serve as a biomarker for improved selection of candidates for active surveillance.

Single-cell analysis reveals altered tumor microenvironments of relapse- and remission-associated pediatric acute myeloid leukemia

Acute myeloid leukemia (AML) microenvironment exhibits cellular and molecular differences among various subtypes. Here, we utilize single-cell RNA sequencing (scRNA-seq) to analyze pediatric AML bone marrow (BM) samples from diagnosis (Dx), end of induction (EOI), and relapse timepoints. Analysis of Dx, EOI scRNA-seq, and TARGET AML RNA-seq datasets reveals an AML blasts-associated 7-gene signature (CLEC11A, PRAME, AZU1, NREP, ARMH1, C1QBP, TRH), which we validate on independent datasets. The analysis reveals distinct clusters of Dx relapse- and continuous complete remission (CCR)-associated AML-blasts with differential expression of genes associated with survival. At Dx, relapse-associated samples have more exhausted T cells while CCR-associated samples have more inflammatory M1 macrophages. Post-therapy EOI residual blasts overexpress fatty acid oxidation, tumor growth, and stemness genes. Also, a post-therapy T-cell cluster associated with relapse samples exhibits downregulation of MHC Class I and T-cell regulatory genes. Altogether, this study deeply characterizes pediatric AML relapse- and CCR-associated samples to provide insights into the BM microenvironment landscape.

Relapsed pediatric acute myeloid leukaemia: state-of-the-art in 2023

Although outcomes of children and adolescents with newly diagnosed acute myeloid leukemia (AML) have improved significantly over the past two decades, more than one-third of patients continue to relapse and experience suboptimal long-term outcomes. Given the small numbers of patients with relapsed AML and historical logistical barriers to international collaboration including poor trial funding and drug availability, the management of AML relapse has varied among pediatric oncology cooperative groups with several salvage regimens utilized and a lack of universally defined response criteria. The landscape of relapsed pediatric AML treatment is changing rapidly, however, as the international AML community harnesses collective knowledge and resources to characterize the genetic and immunophenotypic heterogeneity of relapsed disease, identify biological targets of interest within specific AML subtypes, develop new precision medicine approaches for collaborative investigation in early-phase clinical trials, and tackle challenges of universal drug access across the globe. This review provides a comprehensive overview of progress achieved to date in the treatment of pediatric patients with relapsed AML and highlights modern, state-of-the-art therapeutic approaches under active and emerging clinical investigation that have been facilitated by international collaboration among academic pediatric oncologists, laboratory scientists, regulatory agencies, pharmaceutical partners, cancer research sponsors, and patient advocates.

Effective Prognostic Model for Therapy Response Prediction in Acute Myeloid Leukemia Patients

Acute myeloid leukemia (AML) is a hematopoietic disorder characterized by the malignant transformation of bone marrow-derived myeloid progenitor cells with extremely short survival. To select the optimal treatment options and predict the response to therapy, the stratification of AML patients into risk groups based on genetic factors along with clinical characteristics is carried out. Despite this thorough approach, the therapy response and disease outcome for a particular patient with AML depends on several patient- and tumor-associated factors. Among these, tumor cell resistance to chemotherapeutic agents represents one of the main obstacles for improving survival outcomes in AML patients. In our study, a new prognostic scale for the risk stratification of AML patients based on the detection of the sensitivity or resistance of tumor cells to chemotherapeutic drugs in vitro as well as MDR1 mRNA/P-glycoprotein expression, tumor origin (primary or secondary), cytogenetic abnormalities, and aberrant immunophenotype was developed. This study included 53 patients diagnosed with AML. Patients who received intensive or non-intensive induction therapy were analyzed separately. Using correlation, ROC, and Cox regression analyses, we show that the risk stratification of AML patients in accordance with the developed prognostic scale correlates well with the response to therapy and represents an independent predictive factor for the overall survival of patients with newly diagnosed AML.

Therapeutic targeting of leukemia stem cells in acute myeloid leukemia

One of the distinguishing properties of hematopoietic stem cells is their ability to self-renew. Since self-renewal is important for the continuous replenishment of the hematopoietic stem cell pool, this property is often hijacked in blood cancers. Acute myeloid leukemia (AML) is believed to be arranged in a hierarchy, with self-renewing leukemia stem cells (LSCs) giving rise to the bulk tumor. Some of the earliest characterizations of LSCs were made in seminal studies that assessed the ability of prospectively isolated candidate AML stem cells to repopulate the entire heterogeneity of the tumor in mice. Further studies indicated that LSCs may be responsible for chemotherapy resistance and therefore act as a reservoir for secondary disease and leukemia relapse. In recent years, a number of studies have helped illuminate the complexity of clonality in bone marrow pathologies, including leukemias. Many features distinguishing LSCs from normal hematopoietic stem cells have been identified, and these studies have opened up diverse avenues for targeting LSCs, with an impact on the clinical management of AML patients. This review will discuss the role of self-renewal in AML and its implications, distinguishing characteristics between normal and leukemia stem cells, and opportunities for therapeutic targeting of AML LSCs.

Temporary serine protease inhibition and the role of SPINK2 in human bone marrow

Protease temporary inhibitors are true substrates that bind the catalytic site with high affinity but are slowly degraded, thus acting as inhibitor for a defined time window. Serine peptidase inhibitor Kazal type (SPINK) family is endowed with such functional property whose physiological meaning is poorly explored. High expression of SPINK2 in some hematopoietic malignancies prompted us to investigate its role in adult human bone marrow. We report here the physiological expression of SPINK2 in hematopoietic stem and progenitor cells (HSPCs) and mobilized cluster differentiation 34 (CD34)⁺ cells. We determined the SPINK2 degradation constant and derived a mathematical relationship predicting the zone of inhibited target protease activity surrounding the SPINK2-secreting HSPCs. Analysis of putative target proteases for SPINK2 revealed the expression of PRSS2 and PRSS57 in HSPCs. Our combined results suggest that SPINK2 and its target serine proteases might play a role in the intercellular communication within the hematopoietic stem cell niche.

SPINK2 Protein Expression Is an Independent Adverse Prognostic Marker in AML and Is Potentially Implicated in the Regulation of Ferroptosis and Immune Response

There is an urgent need for the identification as well as clinicopathological and functional characterization of potent prognostic biomarkers and therapeutic targets in acute myeloid leukemia (AML). Using immunohistochemistry and next-generation sequencing, we investigated the protein expression as well as clinicopathological and prognostic associations of serine protease inhibitor Kazal type 2 (SPINK2) in AML and examined its potential biological functions. High SPINK2 protein expression was an independent adverse biomarker for survival and an indicator of elevated therapy resistance and relapse risk. SPINK2 expression was associated with AML with an NPM1 mutation and an intermediate risk by cytogenetics and European LeukemiaNet (ELN) 2022 criteria. Furthermore, SPINK2 expression could refine the ELN2022prognostic stratification. Functionally, an RNA sequencing analysis uncovered a potential link of SPINK2 with ferroptosis and immune response. SPINK2 regulated the expression of certain P53 targets and ferroptosis-related genes, including SLC7A11 and STEAP3, and affected cystine uptake, intracellular iron levels and sensitivity to erastin, a specific ferroptosis inducer. Furthermore, SPINK2 inhibition consistently increased the expression of ALCAM, an immune response enhancer and promoter of T-cell activity. Additionally, we identified a potential small-molecule inhibitor of SPINK2, which requires further characterization. In summary, high SPINK2 protein expression was a potent adverse prognostic marker in AML and might represent a druggable target.

A Novel Fatty Acid Metabolism-Associated Risk Model for Prognosis Prediction in Acute Myeloid Leukaemia

Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults, with an unfavourable outcome and a high rate of recurrence due to its heterogeneity. Dysregulation of fatty acid metabolism plays a crucial role in the development of several tumours. However, the value of fatty acid metabolism (FAM) in the progression of AML remains unclear. In this study, we obtained RNA sequencing and corresponding clinicopathological information from the TCGA and GEO databases. Univariate Cox regression analysis and subsequent LASSO Cox regression analysis were utilized to identify prognostic FAM-related genes and develop a potential prognostic risk model. Kaplan-Meier analysis was used for prognostic significances. We also performed ROC curve to illustrate that the risk model in prognostic prediction has good performance. Moreover, significant differences in immune infiltration landscape were found between high-risk and low-risk groups using ESTIMATE and CIBERSOT algorithms. In the end, differential expressed genes (DEGs) were analyzed by gene set enrichment analysis (GSEA) to preliminarily explore the possible signaling pathways related to the prognosis of FAM and AML. The results of our study may provide potential prognostic biomarkers and therapeutic targets for AML patients, which is conducive to individualized precision therapy.

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.

A DNA Damage Response Related Signature to Predict Prognosis in Patients with Acute Myeloid Leukemia

The prognosis of acute myeloid leukemia (AML) is disappointing in most subtypes and varies widely. DNA damage response (DDR) is associated with prognosis and immunotherapy in multiple cancers. Here, we identify a signature of eight DDR-related genes associated with overall survival, which stratifies AML patients into high- and low-risk groups. Patients in low-risk group were more likely to respond to sorafenib. The signature could be an independent prognostic predictor for patients treated with ADE and ADE plus gemtuzumab ozogamicin. Therefore, this DDR prognostic signature might be applied to prognostic stratification and treatment selection in AML patients, which warrants further studies.

Chasing leukemia differentiation through induction therapy, relapse and transplantation

Despite rapid advances in our understanding of acute myeloid leukemia (AML), the disease remains challenging to treat with 5-year survival for adult patients 20 years or older estimated to be 26% (Cancer 2021). The use of new targeted therapies including BCL2, IDH1/IDH2, and FLT3 inhibitors has revolutionized treatment approaches but also changed the disease trajectory with unique modes of resistance. Recent studies have shown that stem cell maturation state drives expression level and/or dependence on various pathways, critical to determining drug response. Instead of anticipating these changes, we remain behind the curve chasing the next expanded clone. This review will focus on current approaches to treatment in AML, including defining the significance of blast differentiation state on chemotherapeutic response, signaling pathway dependence, metabolism, immune response, and phenotypic changes. We conclude that multimodal treatment approaches are necessary to target both the immature and mature clones, thereby, sustaining drug response.

Integrated single-cell transcriptome analysis of CD34 + enriched leukemic stem cells revealed intra- and inter-patient transcriptional heterogeneity in pediatric acute myeloid leukemia

To gain insights into the idiosyncrasies of CD34 + enriched leukemic stem cells, we investigated the nature and extent of transcriptional heterogeneity by single-cell sequencing in pediatric AML. Whole transcriptome analysis of 28,029 AML single cells was performed using the nanowell cartridge-based barcoding technology. Integrated transcriptional analysis identified unique leukemic stem cell clusters of each patient and intra-patient heterogeneity was revealed by multiple LSC-enriched clusters differing in their cell cycle processes and BCL2 expression. All LSC-enriched clusters exhibited gene expression profile of dormancy and self-renewal. Upregulation of genes involved in non-coding RNA processing and ribonucleoprotein assembly were observed in LSC-enriched clusters relative to HSC. The genes involved in regulation of apoptotic processes, response to cytokine stimulus, and negative regulation of transcription were upregulated in LSC-enriched clusters as compared to the blasts. Validation of top altered genes in LSC-enriched clusters confirmed upregulation of TCF7L2, JUP, ARHGAP25, LPAR6, and PRDX1 genes, and serine/threonine kinases (STK24, STK26). Upregulation of LPAR6 showed trend towards MRD positive status (Odds ratio = 0.126; 95% CI = 0.0144-1.10; p = 0.067) and increased expression of STK26 significantly correlated with higher RFS (HR = 0.231; 95% CI = 0.0506-1.052; p = 0.04). Our findings addressed the inter- and intra-patient diversity within AML LSC and potential signaling and chemoresistance-associated targets that warrant investigation in larger cohort that may guide precision medicine in the near future.

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.

An immunity and pyroptosis gene-pair signature predicts overall survival in acute myeloid leukemia

Treatment responses of patients with acute myeloid leukemia (AML) are known to be heterogeneous, posing challenges for risk scoring and treatment stratification. In this retrospective multi-cohort study, we investigated whether combining pyroptosis- and immune-related genes improves prognostic classification of AML patients. Using a robust gene pairing approach, which effectively eliminates batch effects across heterogeneous patient cohorts and transcriptomic data, we developed an immunity and pyroptosis-related prognostic (IPRP) signature that consists of 15 genes. Using 5 AML cohorts (n = 1327 patients total), we demonstrate that the IPRP score leads to more consistent and accurate survival prediction performance, compared with 10 existing signatures, and that IPRP scoring is widely applicable to various patient cohorts, treatment procedures and transcriptomic technologies. Compared to current standards for AML patient stratification, such as age or ELN2017 risk classification, we demonstrate an added prognostic value of the IPRP risk score for providing improved prediction of AML patients. Our web-tool implementation of the IPRP score and a simple 4-factor nomogram enables practical and robust risk scoring for AML patients. Even though developed for AML patients, our pan-cancer analyses demonstrate a wider application of the IPRP signature for prognostic prediction and analysis of tumor-immune interplay also in multiple solid tumors.

Integrative analysis of drug response and clinical outcome in acute myeloid leukemia

Acute myeloid leukemia (AML) is a cancer of myeloid-lineage cells with limited therapeutic options. We previously combined ex vivo drug sensitivity with genomic, transcriptomic, and clinical annotations for a large cohort of AML patients, which facilitated discovery of functional genomic correlates. Here, we present a dataset that has been harmonized with our initial report to yield a cumulative cohort of 805 patients (942 specimens). We show strong cross-cohort concordance and identify features of drug response. Further, deconvoluting transcriptomic data shows that drug sensitivity is governed broadly by AML cell differentiation state, sometimes conditionally affecting other correlates of response. Finally, modeling of clinical outcome reveals a single gene, PEAR1, to be among the strongest predictors of patient survival, especially for young patients. Collectively, this report expands a large functional genomic resource, offers avenues for mechanistic exploration and drug development, and reveals tools for predicting outcome in AML.

A ten-gene DNA-damage response pathway gene expression signature predicts gemtuzumab ozogamicin response in pediatric AML patients treated on COGAAML0531 and AAML03P1 trials

Gemtuzumab ozogamicin (GO) is an anti-CD33 monoclonal antibody linked to calicheamicin, a DNA damaging agent, and is a well-established therapeutic for treating acute myeloid leukemia (AML). In this study, we used LASSO regression modeling to develop a 10-gene DNA damage response gene expression score (CalDDR-GEx10) predictive of clinical outcome in pediatric AML patients treated with treatment regimen containing GO from the AAML03P1 and AAML0531 trials (ADE + GO arm, N = 301). When treated with ADE + GO, patients with a high CalDDR-GEx10 score had lower complete remission rates (62.8% vs. 85.5%, P = 1.7 7 * 10-5) and worse event-free survival (28.7% vs. 56.5% P = 4.08 * 10-8) compared to those with a low CalDDR-GEx10 score. However, the CalDDR-GEx10 score was not associated with clinical outcome in patients treated with standard chemotherapy alone (ADE, N = 242), implying the specificity of the CalDDR-GEx10 score to calicheamicin-induced DNA damage response. In multivariable models adjusted for risk group, FLT3-status, white blood cell count, and age, the CalDDR-GEx10 score remained a significant predictor of outcome in patients treated with ADE + GO. Our findings present a potential tool that can specifically assess response to calicheamicin-induced DNA damage preemptively via assessing diagnostic leukemic cell gene expression and guide clinical decisions related to treatment using GO.

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.

Development and validation of a prognostic scoring model to risk stratify childhood acute myeloid leukaemia

To create a personal prognostic model and modify the risk stratification of paediatric acute myeloid leukaemia, we downloaded the clinical data of 597 patients from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database as a training set and included 189 patients from our centre as a validation set. In the training set, age at diagnosis, -7/del(7q) or -5/del(5q), core binding factor fusion genes, FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD)/nucleophosmin 1 (NPM1) status, Wilms tumour 1 (WT1) mutation, biallelic CCAAT enhancer binding protein alpha (CEBPA) mutation were strongly correlated with overall survival and included to construct the model. The prognostic model demonstrated excellent discriminative ability with the Harrell's concordance index of 0.68, 3- and 5-year area under the receiver operating characteristic curve of 0.71 and 0.72 respectively. The model was validated in the validation set and outperformed existing prognostic systems. Additionally, patients were stratified into three risk groups (low, intermediate and high risk) with significantly distinct prognosis, and the model successfully identified candidates for haematopoietic stem cell transplantation. The newly developed prognostic model showed robust ability and utility in survival prediction and risk stratification, which could be helpful in modifying treatment selection in clinical routine.

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.

A cellular hierarchy framework for understanding heterogeneity and predicting drug response in acute myeloid leukemia

The treatment landscape of acute myeloid leukemia (AML) is evolving, with promising therapies entering clinical translation, yet patient responses remain heterogeneous, and biomarkers for tailoring treatment are lacking. To understand how disease heterogeneity links with therapy response, we determined the leukemia cell hierarchy makeup from bulk transcriptomes of more than 1,000 patients through deconvolution using single-cell reference profiles of leukemia stem, progenitor and mature cell types. Leukemia hierarchy composition was associated with functional, genomic and clinical properties and converged into four overall classes, spanning Primitive, Mature, GMP and Intermediate. Critically, variation in hierarchy composition along the Primitive versus GMP or Primitive versus Mature axes were associated with response to chemotherapy or drug sensitivity profiles of targeted therapies, respectively. A seven-gene biomarker derived from the Primitive versus Mature axis was associated with response to 105 investigational drugs. Cellular hierarchy composition constitutes a novel framework for understanding disease biology and advancing precision medicine in AML.

DesA Prognostic Risk Model of LncRNAs in Patients With Acute Myeloid Leukaemia Based on TCGA Data

Purpose: This study aimed to combine the clinical data of acute myeloid leukaemia (AML) from The Cancer Genome Atlas (TCGA) database to obtain prognosis-related biomarkers, construct a prognostic risk model using long non-coding RNAs (lncRNAs) in AML and help patients with AML make clinical treatment decisions.

Methods: We analysed the transcriptional group information of 151 patients with AML obtained from TCGA and extracted the expressions of lncRNAs. According to the mutation frequency, the patients were divided into the high mutation group (genomic unstable group, top 25% of mutation frequency) and low mutation group (genomic stable group, 25% after mutation frequency). The ‘limma’ R package was used to analyse the difference in lncRNA expressions between the two groups, and the “survival,” “caret,” and “glmnet” R packages were used to screen lncRNAs that are related to clinical prognosis. Subsequently, a prognosis-related risk model was constructed and verified through different methods.

Results: According to the lncRNA expression data in TCGA, we found that seven lncRNAs (i.e. AL645608.6, LINC01436, AL645608.2, AC073534.2, LINC02593, AL512413.1, and AL645608.4) were highly correlated with the clinical prognosis of patients with AML, so we constructed a prognostic risk model of lncRNAs based on LINC01436, AC073534.2, and LINC02593. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of differentially expressed lncRNA-related target genes were performed, receiver operating characteristic (ROC) curves were created, the applicability of the model in children was assessed using the TARGET database and the model was externally verified using the GEO database. Furthermore, different expression patterns of lncRNAs were validated in various AML cell lines derived from Homo sapiens.

Conclusions: We have established a lncRNA prognostic model that can predict the survival of patients with AML. The Kaplan-Meier analysis showed that this model distinguished survival differences between patients with high- and low-risk status. The ROC analysis confirmed this finding and showed that the model had high prediction accuracy. The Kaplan-Meier analysis of the clinical subgroups showed that this model can predict prognosis independent of clinicopathological factors. Therefore, the proposed prognostic lncRNA risk model can be used as an independent biomarker of AML.

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.

Integrative Genomic Analysis of Pediatric Myeloid-Related Acute Leukemias Identifies Novel Subtypes and Prognostic Indicators

Integrating somatic mutation analysis and gene expression profiling distinguishes pediatric AML subtypes with differential prognoses and clinical risks.

Genomic characterization of pediatric patients with acute myeloid leukemia (AML) has led to the discovery of somatic mutations with prognostic implications. Although gene-expression profiling can differentiate subsets of pediatric AML, its clinical utility in risk stratification remains limited. Here, we evaluate gene expression, pathogenic somatic mutations, and outcome in a cohort of 435 pediatric patients with a spectrum of pediatric myeloid-related acute leukemias for biological subtype discovery. This analysis revealed 63 patients with varying immunophenotypes that span a T-lineage and myeloid continuum designated as acute myeloid/T-lymphoblastic leukemia (AMTL). Within AMTL, two patient subgroups distinguished by FLT3-ITD and PRC2 mutations have different outcomes, demonstrating the impact of mutational composition on survival. Across the cohort, variability in outcomes of patients within isomutational subsets is influenced by transcriptional identity and the presence of a stem cell–like gene-expression signature. Integration of gene expression and somatic mutations leads to improved risk stratification.

Prevalence and Risk Factors for Multifocality in Pediatric Thyroid Cancer

Importance

Current guidelines recommend total thyroidectomy for the majority of pediatric thyroid cancer owing to an increased prevalence of multifocality. However, there is a paucity of information on the exact prevalence and risk factors for multifocal disease-knowledge that is critical to improving pediatric thyroid cancer management and outcomes.

Objective

To determine the prevalence and risk factors for multifocal disease in pediatric patients with papillary thyroid carcinoma (PTC).

Design, Setting, and Participants

This multicenter retrospective cohort study included patients 18 years or younger who underwent thyroidectomy for PTC from 2010 to 2020 at 3 tertiary pediatric hospitals and 2 tertiary adult and pediatric hospitals in the US.

Main Outcomes and Measures

Demographic and clinical variables, including age, family history of thyroid cancer, autoimmune thyroiditis, prior radiation exposure, cancer predisposition syndrome, tumor size, tumor and nodal stage, PTC pathologic variant, and preoperative imaging, were assessed for association with presence of any multifocal, unilateral multifocal, and bilateral multifocal disease using multiple logistic regression analyses. Least absolute shrinkage and selection operator analysis was performed to develop a model of variables that may predict multifocal disease.

Results

Of 212 patients, the mean age was 14.1 years, with 23 patients 10 years or younger; 173 (82%) patients were female. Any multifocal disease was present in 98 (46%) patients, with bilateral multifocal disease in 73 (34%). Bilateral multifocal disease was more accurately predicted on preoperative imaging than unilateral multifocal disease (48 of 73 [66%] patients vs 9 of 25 [36%] patients). Being 10 years or younger, T3 tumor stage, and N1b nodal stage were identified as predictors for multifocal and bilateral multifocal disease.

Conclusions and Relevance

This large, multicenter cohort study demonstrated a high prevalence of multifocal disease in pediatric patients with PTC. Additionally, several potential predictors of multifocal disease, including age and advanced T and N stages, were identified. These risk factors and the high prevalence of multifocal disease should be considered when weighing the risks and benefits of surgical management options in pediatric patients with PTC.

Gene expression signature predicts relapse in adult patients with cytogenetically normal acute myeloid leukemia

Although ∼80% of adult patients with cytogenetically normal acute myeloid leukemia (CN-AML) achieve a complete remission (CR), more than half of them relapse. Better identification of patients who are likely to relapse can help to inform clinical decisions. We performed RNA sequencing on pretreatment samples from 268 adults with de novo CN-AML who were younger than 60 years of age and achieved a CR after induction treatment with standard "7+3" chemotherapy. After filtering for genes whose expressions were associated with gene mutations known to impact outcome (ie, CEBPA, NPM1, and FLT3-internal tandem duplication [FLT3-ITD]), we identified a 10-gene signature that was strongly predictive of patient relapse (area under the receiver operating characteristics curve [AUC], 0.81). The signature consisted of 7 coding genes (GAS6, PSD3, PLCB4, DEXI, JMY, NRP1, C10orf55) and 3 long noncoding RNAs. In multivariable analysis, the 10-gene signature was strongly associated with relapse (P < .001), after adjustment for the FLT3-ITD, CEBPA, and NPM1 mutational status. Validation of the expression signature in an independent patient set from The Cancer Genome Atlas showed the signature's strong predictive value, with AUC = 0.78. Implementation of the 10-gene signature into clinical prognostic stratification could be useful for identifying patients who are likely to relapse.

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.

Single-Cell Transcriptome Analysis Identifies Ligand-Receptor Pairs Associated With BCP-ALL Prognosis

B cell precursor acute lymphoblastic leukemia (BCP-ALL) is a blood cancer that originates from the abnormal proliferation of B-lymphoid progenitors. Cell population components and cell–cell interaction in the bone marrow microenvironment are significant factors for progression, relapse, and therapy resistance of BCP-ALL. In this study, we identified specifically expressed genes in B cells and myeloid cells by analyzing single-cell RNA sequencing data for seven BCP-ALL samples and four healthy samples obtained from a public database. Integrating 1356 bulk RNA sequencing samples from a public database and our previous study, we found a total of 57 significant ligand–receptor pairs (24 upregulated and 33 downregulated) in the autocrine crosstalk network of B cells. Via assessment of the communication between B cells and myeloid cells, another 29 ligand–receptor pairs were discovered, some of which notably affected survival outcomes. A score-based model was constructed with least absolute shrinkage and selection operator (LASSO) using these ligand–receptor pairs. Patients with higher scores had poorer prognoses. This model can be applied to create predictions for both pediatric and adult BCP-ALL patients.

Performances of Targeted RNA Sequencing for the Analysis of Fusion Transcripts, Gene Mutation, and Expression in Hematological Malignancies

RNA sequencing holds great promise to improve the diagnostic of hematological malignancies, because this technique enables to detect fusion transcripts, to look for somatic mutations in oncogenes, and to capture transcriptomic signatures of nosological entities. However, the analytical performances of targeted RNA sequencing have not been extensively described in diagnostic samples. Using a targeted panel of 1385 cancer-related genes in a series of 100 diagnosis samples and 8 controls, we detected all the already known fusion transcripts and also discovered unknown and/or unsuspected fusion transcripts in 12 samples. Regarding the analysis of transcriptomic profiles, we show that targeted RNA sequencing is performant to discriminate acute lymphoblastic leukemia entities driven by different oncogenic translocations. Additionally, we show that 86% of the mutations identified at the DNA level are also detectable at the messenger RNA (mRNA) level, except for nonsense mutations that are subjected to mRNA decay. We conclude that targeted RNA sequencing might improve the diagnosis of hematological malignancies. Standardization of the preanalytical steps and further refinements of the panel design and of the bioinformatical pipelines will be an important step towards its use in standard diagnostic procedures.