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

LSP1 promotes the progression of acute myelogenous leukemia by regulating KSR/ERK signaling pathway and cell migration

We aimed to investigate the role and mechanism of LSP1 in the progression of acute myelogenous leukemia. In this study, we established shLSP1 cell line to analyze the function of LSP1 in AML. We observed high expression of LSP1 in AML patients, whereas it showed no expression in normal adults. Furthermore, we found that LSP1 expression was associated with disease prognosis. Our results indicate that LSP1 plays a crucial role in mediating proliferation and survival of leukemia cells through the KSR/ERK signaling pathway. Additionally, LSP1 promotes cell chemotaxis and homing by enhancing cell adhesion and migration. We also discovered that LSP1 confers chemotactic ability to leukemia cells in vivo. Finally, our study identified 12 genes related to LSP1 in AML, which indicated poor survival outcome in AML patients and were enriched in Ras and cell adhesion signaling pathways. Our results revealed that the overexpression of LSP1 is related to the activation of the KSR/ERK signaling pathway, as well as cell adhesion and migration in AML patients. Reducing LSP1 expression impair AML progression, suggesting that LSP1 may serve as a potential drug therapy target for more effective treatment of AML.

A transcriptomic based deconvolution framework for assessing differentiation stages and drug responses of AML

The diagnostic spectrum for AML patients is increasingly based on genetic abnormalities due to their prognostic and predictive value. However, information on the AML blast phenotype regarding their maturational arrest has started to regain importance due to its predictive power for drug responses. Here, we deconvolute 1350 bulk RNA-seq samples from five independent AML cohorts on a single-cell healthy BM reference and demonstrate that the morphological differentiation stages (FAB) could be faithfully reconstituted using estimated cell compositions (ECCs). Moreover, we show that the ECCs reliably predict ex-vivo drug resistances as demonstrated for Venetoclax, a BCL-2 inhibitor, resistance specifically in AML with CD14+ monocyte phenotype. We validate these predictions using LUMC proteomics data by showing that BCL-2 protein abundance is split into two distinct clusters for NPM1-mutated AML at the extremes of CD14+ monocyte percentages, which could be crucial for the Venetoclax dosing patients. Our results suggest that Venetoclax resistance predictions can also be extended to AML without recurrent genetic abnormalities and possibly to MDS-related and secondary AML. Lastly, we show that CD14+ monocytic dominated Ven/Aza treated patients have significantly lower overall survival. Collectively, we propose a framework for allowing a joint mutation and maturation stage modeling that could be used as a blueprint for testing sensitivity for new agents across the various subtypes of AML.

Selective eradication of venetoclax-resistant monocytic acute myeloid leukemia with iron oxide nanozymes

The clinical treatment of human acute myeloid leukemia (AML) is rapidly progressing from chemotherapy to targeted therapies led by the BCL-2 inhibitor venetoclax (VEN). Despite its unprecedented success, VEN still encounters clinical resistance. Thus, uncovering the biological vulnerability of VEN-resistant AML disease and identifying effective therapies to treat them are urgently needed. We have previously demonstrated that iron oxide nanozymes (IONE) are capable of overcoming chemoresistance in AML. The current study reports a new activity of IONE in overcoming VEN resistance. Specifically, we revealed an aberrant redox balance with excessive intracellular reactive oxygen species (ROS) in VEN-resistant monocytic AML. Treatment with IONE potently induced ROS-dependent cell death in monocytic AML in both cell lines and primary AML models. In primary AML with developmental heterogeneity containing primitive and monocytic subpopulations, IONE selectively eradicated the VEN-resistant ROS-high monocytic subpopulation, successfully resolving the challenge of developmental heterogeneity faced by VEN. Overall, our study revealed an aberrant redox balance as a therapeutic target for monocytic AML and identified a candidate IONE that could selectively and potently eradicate VEN-resistant monocytic disease.

CD37 is a safe chimeric antigen receptor target to treat acute myeloid leukemia

Acute myeloid leukemia (AML) is characterized by the accumulation of immature myeloid cells in the bone marrow and the peripheral blood. Nearly half of the AML patients relapse after standard induction therapy, and new forms of therapy are urgently needed. Chimeric antigen receptor (CAR) T therapy has so far not been successful in AML due to lack of efficacy and safety. Indeed, the most attractive antigen targets are stem cell markers such as CD33 or CD123. We demonstrate that CD37, a mature B cell marker, is expressed in AML samples, and its presence correlates with the European LeukemiaNet (ELN) 2017 risk stratification. We repurpose the anti-lymphoma CD37CAR for the treatment of AML and show that CD37CAR T cells specifically kill AML cells, secrete proinflammatory cytokines, and control cancer progression in vivo. Importantly, CD37CAR T cells display no toxicity toward hematopoietic stem cells. Thus, CD37 is a promising and safe CAR T cell AML target.

A 4-gene prognostic index for enhancing acute myeloid leukaemia survival prediction

Despite advancements in utilizing genetic markers to enhance acute myeloid leukaemia (AML) outcome prediction, significant disease heterogeneity persists, hindering clinical management. To refine survival predictions, we assessed the transcriptome of non-acute promyelocytic leukaemia chemotherapy-treated AML patients from five cohorts (n = 975). This led to the identification of a 4-gene prognostic index (4-PI) comprising CYP2E1, DHCR7, IL2RA and SQLE. The 4-PI effectively stratified patients into risk categories, with the high 4-PI group exhibiting TP53 mutations and cholesterol biosynthesis signatures. Single-cell RNA sequencing revealed enrichment for leukaemia stem cell signatures in high 4-PI cells. Validation across three cohorts (n = 671), including one with childhood AML, demonstrated the reproducibility and clinical utility of the 4-PI, even using cost-effective techniques like real-time quantitative polymerase chain reaction. Comparative analysis with 56 established prognostic indexes revealed the superior performance of the 4-PI, highlighting its potential to enhance AML risk stratification. Finally, the 4-PI demonstrated to be potential marker to reclassified patients from the intermediate ELN2017 category to the adverse category. In conclusion, the 4-PI emerges as a robust and straightforward prognostic tool to improve survival prediction in AML patients.

Unveiling novel insights in acute myeloid leukemia through single-cell RNA sequencing

Acute myeloid leukemia (AML) is a complex and heterogeneous group of aggressive hematopoietic stem cell disease. The presence of diverse and functionally distinct populations of leukemia cells within the same patient's bone marrow or blood poses a significant challenge in diagnosing and treating AML. A substantial proportion of AML patients demonstrate resistance to induction chemotherapy and a grim prognosis upon relapse. The rapid advance in next generation sequencing technologies, such as single-cell RNA-sequencing (scRNA-seq), has revolutionized our understanding of AML pathogenesis by enabling high-resolution interrogation of the cellular heterogeneity in the AML ecosystem, and their transcriptional signatures at a single-cell level. New studies have successfully characterized the inextricably intertwined interactions among AML cells, immune cells and bone marrow microenvironment and their contributions to the AML development, therapeutic resistance and relapse. These findings have deepened and broadened our understanding the complexity and heterogeneity of AML, which are difficult to detect with bulk RNA-seq. This review encapsulates the burgeoning body of knowledge generated through scRNA-seq, providing the novel insights and discoveries it has unveiled in AML biology. Furthermore, we discuss the potential implications of scRNA-seq in therapeutic opportunities, focusing on immunotherapy. Finally, we highlight the current limitations and future direction of scRNA-seq in the field.

Single-cell systems pharmacology identifies development-driven drug response and combination therapy in B cell acute lymphoblastic leukemia

Leukemia can arise at various stages of the hematopoietic differentiation hierarchy, but the impact of developmental arrest on drug sensitivity is unclear. Applying network-based analyses to single-cell transcriptomes of human B cells, we define genome-wide signaling circuitry for each B cell differentiation stage. Using this reference, we comprehensively map the developmental states of B cell acute lymphoblastic leukemia (B-ALL), revealing its strong correlation with sensitivity to asparaginase, a commonly used chemotherapeutic agent. Single-cell multi-omics analyses of primary B-ALL blasts reveal marked intra-leukemia heterogeneity in asparaginase response: resistance is linked to pre-pro-B-like cells, with sensitivity associated with the pro-B-like population. By targeting BCL2, a driver within the pre-pro-B-like cell signaling network, we find that venetoclax significantly potentiates asparaginase efficacy in vitro and in vivo. These findings demonstrate a single-cell systems pharmacology framework to predict effective combination therapies based on intra-leukemia heterogeneity in developmental state, with potentially broad applications beyond B-ALL.

Mapping AML heterogeneity - multi-cohort transcriptomic analysis identifies novel clusters and divergent ex-vivo drug responses

Subtyping of acute myeloid leukaemia (AML) is predominantly based on recurrent genetic abnormalities, but recent literature indicates that transcriptomic phenotyping holds immense potential to further refine AML classification. Here we integrated five AML transcriptomic datasets with corresponding genetic information to provide an overview (n = 1224) of the transcriptomic AML landscape. Consensus clustering identified 17 robust patient clusters which improved identification of CEBPA-mutated patients with favourable outcomes, and uncovered transcriptomic subtypes for KMT2A rearrangements (2), NPM1 mutations (5), and AML with myelodysplasia-related changes (AML-MRC) (5). Transcriptomic subtypes of KMT2A, NPM1 and AML-MRC showed distinct mutational profiles, cell type differentiation arrests and immune properties, suggesting differences in underlying disease biology. Moreover, our transcriptomic clusters show differences in ex-vivo drug responses, even when corrected for differentiation arrest and superiorly capture differences in drug response compared to genetic classification. In conclusion, our findings underscore the importance of transcriptomics in AML subtyping and offer a basis for future research and personalised treatment strategies. Our transcriptomic compendium is publicly available and we supply an R package to project clusters to new transcriptomic studies.

Differential prognostic values of the three AKT isoforms in acute myeloid leukemia

The PI3K-AKT-mTOR pathway lies at the confluence of signaling pathways in which various components are subjected to activating genetic alterations in acute myeloid leukemia (AML), thus contributing to oncogenesis. Three AKT isoforms exist in humans. However, whether one isoform predominates in AML remains unknown. This study reveals that AKT3 behaves very distinctly than AKT1 or AKT2 in both normal myeloid differentiation and AML. During normal differentiation, AKT3 is preferentially expressed in hematopoietic stem cells whilst AKT1 becomes preferentially expressed as cells differentiate into granulocytes or monocytes. AKT2 expression remains unchanged. In AML, AKT3 expression varies widely among patient samples and is counterintuitively high in mature/monocytic leukemia. Furthermore, a low level of AKT3 expression is strongly correlated to genetic alterations associated with a better outcome (NPM1 mutations and RUNX1-RUNX1T1 translocation), while a high level is correlated to alterations associated to a bad outcome (RUNX1 mutations; and SRSF2, U2AF1, SF3B1, ASXL1 and BCOR mutations occurring frequently in MDS and MPN). Consistently, a high AKT3 expression level appears as a very strong predictor of poor survival. Curiously, although modestly varying among AML samples, a high AKT1 expression shows in contrast as a strong predictor of a better patient outcome. These data suggest that AKT3 and AKT1 expressions have strong, yet opposite, prognostic values.

Revealing the role of SPP1+ macrophages in glioma prognosis and therapeutic targeting by investigating tumor-associated macrophage landscape in grade 2 and 3 gliomas

BACKGROUND

Glioma is a highly heterogeneous brain tumor categorized into World Health Organization (WHO) grades 1-4 based on its malignancy. The suppressive immune microenvironment of glioma contributes significantly to unfavourable patient outcomes. However, the cellular composition and their complex interplays within the glioma environment remain poorly understood, and reliable prognostic markers remain elusive. Therefore, in-depth exploration of the tumor microenvironment (TME) and identification of predictive markers are crucial for improving the clinical management of glioma patients.

RESULTS

Our analysis of single-cell RNA-sequencing data from glioma samples unveiled the immunosuppressive role of tumor-associated macrophages (TAMs), mediated through intricate interactions with tumor cells and lymphocytes. We also discovered the heterogeneity within TAMs, among which a group of suppressive TAMs named TAM-SPP1 demonstrated a significant association with Epidermal Growth Factor Receptor (EGFR) amplification, impaired T cell response and unfavourable patient survival outcomes. Furthermore, by leveraging genomic and transcriptomic data from The Cancer Genome Atlas (TCGA) dataset, two distinct molecular subtypes with a different constitution of TAMs, EGFR status and clinical outcomes were identified. Exploiting the molecular differences between these two subtypes, we developed a four-gene-based prognostic model. This model displayed strong associations with an elevated level of suppressive TAMs and could be used to predict anti-tumor immune response and prognosis in glioma patients.

CONCLUSION

Our findings illuminated the molecular and cellular mechanisms that shape the immunosuppressive microenvironment in gliomas, providing novel insights into potential therapeutic targets. Furthermore, the developed prognostic model holds promise for predicting immunotherapy response and assisting in more precise risk stratification for glioma patients.

Mapping single-cell developmental potential in health and disease with interpretable deep learning

Single-cell RNA sequencing (scRNA-seq) has transformed our understanding of cell fate in developmental systems. However, identifying the molecular hallmarks of potency - the capacity of a cell to differentiate into other cell types - has remained challenging. Here, we introduce CytoTRACE 2, an interpretable deep learning framework for characterizing potency and differentiation states on an absolute scale from scRNA-seq data. Across 31 human and mouse scRNA-seq datasets encompassing 28 tissue types, CytoTRACE 2 outperformed existing methods for recovering experimentally determined potency levels and differentiation states covering the entire range of cellular ontogeny. Moreover, it reconstructed the temporal hierarchy of mouse embryogenesis across 62 timepoints; identified pan-tissue expression programs that discriminate major potency levels; and facilitated discovery of cellular phenotypes in cancer linked to survival and immunotherapy resistance. Our results illuminate a fundamental feature of cell biology and provide a broadly applicable platform for delineating single-cell differentiation landscapes in health and disease.

Heterogeneity of hepatocellular carcinoma: from mechanisms to clinical implications

Hepatocellular Carcinoma (HCC) is one of the most common types of primary liver cancer. Current treatment options have limited efficacy against this malignancy, primarily owing to difficulties in early detection and the inherent resistance to existing drugs. Tumor heterogeneity is a pivotal factor contributing significantly to treatment resistance and recurrent manifestations of HCC. Intratumoral heterogeneity is an important aspect of the spectrum of complex tumor heterogeneity and contributes to late diagnosis and treatment failure. Therefore, it is crucial to thoroughly understand the molecular mechanisms of how tumor heterogeneity develops. This review aims to summarize the possible molecular dimensions of tumor heterogeneity with an emphasis on intratumoral heterogeneity, evaluate its profound impact on the diagnosis and therapeutic strategies for HCC, and explore the suitability of appropriate pre-clinical models that can be used to best study tumor heterogeneity; thus, opening new avenues for cancer treatment.

Leukemia aggressiveness is driven by chromatin remodeling and expression changes of core regulators

Molecular mechanisms driving clonal aggressiveness in leukemia are not fully understood. We tracked and analyzed two mouse MLL-rearranged leukemic clones independently evolving towards higher aggressiveness. More aggressive subclones lost their growth differential ex vivo but restored it upon secondary transplantation, suggesting molecular memory of aggressiveness. Development of aggressiveness was associated with clone-specific gradual modulation of chromatin states and expression levels across the genome, with a surprising preferential trend of reversing the earlier changes between normal and leukemic progenitors. To focus on the core aggressiveness program, we identified genes with consistent changes of expression and chromatin marks that were maintained in vivo and ex vivo in both clones. Overexpressing selected core genes (Smad1 as aggressiveness driver, Irx5 and Plag1 as suppressors) affected leukemic progenitor growth in the predicted way and had convergent downstream effects on central transcription factors and repressive epigenetic modifiers, suggesting a broader regulatory network of leukemic aggressiveness.

Propionate promotes ferroptosis and apoptosis through mitophagy and ACSL4-mediated ferroptosis elicits anti-leukemia immunity

Short-chain fatty acids (SCFAs), particularly propionate and butyrate, have been reported in many cancers. However, the relationship between propionate and acute myeloid leukemia (AML) remains unclear. Additionally, Acyl-CoA synthetase long chain family member 4 (ACSL4) has been reported to regulate immunity in solid tumors, but there are still many gaps to be filled in AML. Here, we discovered the underlying mechanism of propionate and ACSL4-mediated ferroptosis for immunotherapy. Our results showed that the level of propionate in the AML patients' feces was decreased, which was correlated to gut microbiota dysbiosis. Moreover, we demonstrated that propionate suppressed AML progression both in vivo and in vitro. In mechanism, propionate induced AML cells apoptosis and ferroptosis. The imbalance of reactive oxygen species (ROS) and redox homeostasis induced by propionate caused mitochondrial fission and mitophagy, which enhanced ferroptosis and apoptosis. Furthermore, ACSL4-mediated ferroptosis caused by propionate increased the immunogenicity of AML cells, induced the release of damage-associated molecular patterns (DAMPs), and promoted the maturation of dendritic cells (DCs). The increased level of immunogenicity due to ferroptosis enable propionate-based whole-cell vaccines to activate immunity, thus further facilitating effective killing of AML cells. Collectively, our study uncovers a crucial role for propionate suppresses AML progression by inducing ferroptosis and the potential mechanisms of ACSL4-mediated ferroptosis in the regulation of AML immunity.

SHP-1 inhibition targets leukaemia stem cells to restore immunosurveillance and enhance chemosensitivity by metabolic reprogramming

Leukaemia stem cells (LSCs) in acute myeloid leukaemia present a considerable treatment challenge due to their resistance to chemotherapy and immunosurveillance. The connection between these properties in LSCs remains poorly understood. Here we demonstrate that inhibition of tyrosine phosphatase SHP-1 in LSCs increases their glycolysis and oxidative phosphorylation, enhancing their sensitivity to chemotherapy and vulnerability to immunosurveillance. Mechanistically, SHP-1 inhibition leads to the upregulation of phosphofructokinase platelet (PFKP) through the AKT-β-catenin pathway. The increase in PFKP elevates energy metabolic activities and, as a consequence, enhances the sensitivity of LSCs to chemotherapeutic agents. Moreover, the upregulation of PFKP promotes MYC degradation and, consequently, reduces the immune evasion abilities of LSCs. Overall, our study demonstrates that targeting SHP-1 disrupts the metabolic balance in LSCs, thereby increasing their vulnerability to chemotherapy and immunosurveillance. This approach offers a promising strategy to overcome LSC resistance in acute myeloid leukaemia.

Comprehensive characterization of IFNγ signaling in acute myeloid leukemia reveals prognostic and therapeutic strategies

Interferon gamma (IFNγ) is a critical cytokine known for its diverse roles in immune regulation, inflammation, and tumor surveillance. However, while IFNγ levels were elevated in sera of most newly diagnosed acute myeloid leukemia (AML) patients, its complex interplay in AML remains insufficiently understood. We aim to characterize these complex interactions through comprehensive bulk and single-cell approaches in bone marrow of newly diagnosed AML patients. We identify monocytic AML as having a unique microenvironment characterized by IFNγ producing T and NK cells, high IFNγ signaling, and immunosuppressive features. IFNγ signaling score strongly correlates with venetoclax resistance in primary AML patient cells. Additionally, IFNγ treatment of primary AML patient cells increased venetoclax resistance. Lastly, a parsimonious 47-gene IFNγ score demonstrates robust prognostic value. In summary, our findings suggest that inhibiting IFNγ is a potential treatment strategy to overcoming venetoclax resistance and immune evasion in AML patients.

A machine learning model identifies M3-like subtype in AML based on PML/RARα targets

The typical genomic feature of acute myeloid leukemia (AML) M3 subtype is the fusion event of PML/RARα, and ATRA/ATO-based combination therapy is current standard treatment regimen for M3 subtype. Here, a machine-learning model based on expressions of PML/RARα targets was developed to identify M3 patients by analyzing 1228 AML patients. Our model exhibited high accuracy. To enable more non-M3 AML patients to potentially benefit from ATRA/ATO therapy, M3-like patients were further identified. We found that M3-like patients had strong GMP features, including the expression patterns of M3 subtype marker genes, the proportion of myeloid progenitor cells, and deconvolution of AML constituent cell populations. M3-like patients exhibited distinct genomic features, low immune activity and better clinical survival. The initiative identification of patients similar to M3 subtype may help to identify more patients that would benefit from ATO/ATRA treatment and deepen our understanding of the molecular mechanism of AML pathogenesis.

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.

Leukemic stem cells activate lineage inappropriate signalling pathways to promote their growth

Acute Myeloid Leukemia (AML) is caused by multiple mutations which dysregulate growth and differentiation of myeloid cells. Cells adopt different gene regulatory networks specific to individual mutations, maintaining a rapidly proliferating blast cell population with fatal consequences for the patient if not treated. The most common treatment option is still chemotherapy which targets such cells. However, patients harbour a population of quiescent leukemic stem cells (LSCs) which can emerge from quiescence to trigger relapse after therapy. The processes that allow such cells to re-grow remain unknown. Here, we examine the well characterised t(8;21) AML sub-type as a model to address this question. Using four primary AML samples and a novel t(8;21) patient-derived xenograft model, we show that t(8;21) LSCs aberrantly activate the VEGF and IL-5 signalling pathways. Both pathways operate within a regulatory circuit consisting of the driver oncoprotein RUNX1::ETO and an AP-1/GATA2 axis allowing LSCs to re-enter the cell cycle while preserving self-renewal capacity.

Addressing a Pre-Clinical Pipeline Gap: Development of the Pediatric Acute Myeloid Leukemia Patient-Derived Xenograft Program at Texas Children's Hospital at Baylor College of Medicine

The survival rate of pediatric acute myeloid leukemia (pAML) is currently around 60%. While survival has slowly increased over the past few decades, the development of novel agents likely to further improve survival for this heterogeneous patient population has been limited by gaps in the pAML pre-clinical pipeline. One of the major hurdles in evaluating new agents for pAML is the lack of pAML patient-derived xenograft (PDX) models. Unlike solid tumors and other types of leukemias, AML is notoriously hard to establish in mouse models, likely due in part to the need for specific human microenvironment elements. Our laboratory at TCH/BCM addressed this gap by establishing a systematic PDX workflow, leveraging advanced immunodeficient hosts and capitalizing on our high volume of pAML patients and close coordination between labs and clinical sections. Patients treated at TCH are offered the chance to participate in specimen banking protocols that allow blood and bone marrow collection as well as the collection of relevant clinical data. All patients who consent and have samples available are trialed for PDX development. In addition, samples from the Children's Oncology Group (COG) are also trialed for PDX generation. Serially transplanting PDX models are validated using short tandem repeat (STR) and characterized using both targeted DNA/RNA next generation sequencing and RNAseq. As of March 2023, this systematic approach has resulted in 26 serially transplanting models. Models have been shared with requesting labs to facilitate external pAML pre-clinical studies. Available PDX models can be located through the BCM PDX Portal. We expect our growing PDX resource to make a significant contribution to expediting the testing of promising novel therapeutics for pAML.

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.

Inherited blood cancer predisposition through altered transcription elongation

Despite advances in defining diverse somatic mutations that cause myeloid malignancies, a significant heritable component for these cancers remains largely unexplained. Here, we perform rare variant association studies in a large population cohort to identify inherited predisposition genes for these blood cancers. CTR9, which encodes a key component of the PAF1 transcription elongation complex, is among the significant genes identified. The risk variants found in the cases cause loss of function and result in a ∼10-fold increased odds of acquiring a myeloid malignancy. Partial CTR9 loss of function expands human hematopoietic stem cells (HSCs) by increased super elongation complex-mediated transcriptional activity, which thereby increases the expression of key regulators of HSC self-renewal. By following up on insights from a human genetic study examining inherited predisposition to the myeloid malignancies, we define a previously unknown antagonistic interaction between the PAF1 and super elongation complexes. These insights could enable targeted approaches for blood cancer prevention.

Transcriptional and phenotypic heterogeneity underpinning venetoclax resistance in AML

The venetoclax BCL2 inhibitor in combination with hypomethylating agents represents a cornerstone of induction therapy for older AML patients, unfit for intensive chemotherapy. Like other targeted therapies, venetoclax-based therapies suffer from innate and acquired resistance. While several mechanisms of resistance have been identified, the heterogeneity of resistance mechanism across patient populations is poorly understood. Here we utilized integrative analysis of transcriptomic and ex-vivo drug response data in AML patients to identify four transcriptionally distinct VEN resistant clusters (VR_C1-4), with distinct phenotypic, genetic and drug response patterns. VR_C1 was characterized by enrichment for differentiated monocytic- and cDC-like blasts, transcriptional activation of PI3K-AKT-mTOR signaling axis, and energy metabolism pathways. They showed sensitivity to mTOR and CDK inhibition. VR_C2 was enriched for NRAS mutations and associated with distinctive transcriptional suppression of HOX expression. VR_C3 was characterized by enrichment for TP53 mutations and higher infiltration by cytotoxic T cells. This cluster showed transcriptional expression of erythroid markers, suggesting tumor cells mimicking erythroid differentiation, activation of JAK-STAT signaling, and sensitivity to JAK inhibition, which in a subset of cases synergized with venetoclax. VR_C4 shared transcriptional similarities with venetoclax-sensitive patients, with modest over-expression of interferon signaling. They were also characterized by high rates of DNMT3A mutations. Finally, we projected venetoclax-resistance states onto single cells profiled from a patient who relapsed under venetoclax therapy capturing multiple resistance states in the tumor and shifts in their abundance under venetoclax selection, suggesting that single tumors may consist of cells mimicking multiple VR_Cs contributing to intra-tumor heterogeneity. Taken together, our results provide a strategy to evaluate inter- and intra-tumor heterogeneity of venetoclax resistance mechanisms and provide insights into approaches to navigate further management of patients who failed therapy with BCL2 inhibitors.

Decoding leukemia at the single-cell level: clonal architecture, classification, microenvironment, and drug resistance

Leukemias are refractory hematological malignancies, characterized by marked intrinsic heterogeneity which poses significant obstacles to effective treatment. However, traditional bulk sequencing techniques have not been able to effectively unravel the heterogeneity among individual tumor cells. With the emergence of single-cell sequencing technology, it has bestowed upon us an unprecedented resolution to comprehend the mechanisms underlying leukemogenesis and drug resistance across various levels, including the genome, epigenome, transcriptome and proteome. Here, we provide an overview of the currently prevalent single-cell sequencing technologies and a detailed summary of single-cell studies conducted on leukemia, with a specific focus on four key aspects: (1) leukemia's clonal architecture, (2) frameworks to determine leukemia subtypes, (3) tumor microenvironment (TME) and (4) the drug-resistant mechanisms of leukemia. This review provides a comprehensive summary of current single-cell studies on leukemia and highlights the markers and mechanisms that show promising clinical implications for the diagnosis and treatment of leukemia.

Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia

Acute myeloid leukemia is a poor-prognosis cancer commonly stratified by genetic aberrations, but these mutations are often heterogeneous and fail to consistently predict therapeutic response. Here, we combine transcriptomic, proteomic, and phosphoproteomic datasets with ex vivo drug sensitivity data to help understand the underlying pathophysiology of AML beyond mutations. We measure the proteome and phosphoproteome of 210 patients and combine them with genomic and transcriptomic measurements to identify four proteogenomic subtypes that complement existing genetic subtypes. We build a predictor to classify samples into subtypes and map them to a "landscape" that identifies specific drug response patterns. We then build a drug response prediction model to identify drugs that target distinct subtypes and validate our findings on cell lines representing various stages of quizartinib resistance. Our results show how multiomics data together with drug sensitivity data can inform therapy stratification and drug combinations in AML.

Epigenetic signature of ionizing radiation in therapy-related AML patients

Therapy-related acute myeloid leukaemia (t-AML) is a late side effect of previous chemotherapy (ct-AML) and/or radiotherapy (rt-AML) or immunosuppressive treatment. t-AMLs, which account for ∼10-20 % of all AML cases, are extremely aggressive and have a poor prognosis compared to de novo AML. Our hypothesis is that exposure to radiation causes genome-wide epigenetic changes in rt-AML. An epigenome-wide association study was undertaken, measuring over 850K methylation sites across the genome from fifteen donors (five healthy, five de novo, and five t-AMLs). The study predominantly focussed on 94K sites that lie in CpG-rich gene promoter regions. Genome-wide hypomethylation was discovered in AML, primarily in intergenic regions. Additionally, genes specific to AML were identified with promoter hypermethylation. A two-step validation was conducted, both internally, using pyrosequencing to measure methylation levels in specific regions across fifteen primary samples, and externally, with an additional eight AML samples. We demonstrated that the MEST and GATA5 gene promoters, which were previously identified as tumour suppressors, were noticeably hypermethylated in rt-AML, as opposed to other subtypes of AML and control samples. These may indicate the epigenetic involvement in the development of rt-AML at the molecular level and could serve as potential targets for drug therapy in rt-AML.

Non-genetic mechanisms of drug resistance in acute leukemias

Acute leukemia is characterized by clonal heterogeneity that contributes to poor drug responses in patients. Despite treatment advances, the occurrence of relapse remains a major barrier to achieving cures as current therapeutic approaches are inadequate to effectively prevent or overcome resistance. Given that only a few genetic mutations are associated with relapse in acute leukemia patients, there is a growing focus on 'non-genetic' mechanisms that affect the hallmarks of cancer to allow leukemic cells to survive post therapy. In this review, we provide an overview of the therapeutic landscape in acute leukemias. Importantly, we discuss non-genetic mechanisms exploited by leukemic cells to promote their survival after treatment. Last, we present current strategies to prevent or overcome drug resistance in this disease.

Precise single-cell transcriptomic mapping of normal and leukemic cell states reveals unconventional lineage priming in acute myeloid leukemia

Initial classification of acute leukemia involves the assignment of blasts to cell states within the hematopoietic hierarchy based on morphological and immunophenotypic features. Yet, these traditional classification approaches lack precision, especially at the level of immature blasts. Single-cell RNA-sequencing (scRNA-seq) enables precise determination of cell state using thousands of markers, thus providing an opportunity to re-examine present-day classification schemes of acute leukemia. Here, we developed a detailed reference map of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes spanning 55 cellular states. Cell state annotations were benchmarked against purified cell populations, and in-depth characterization of gene expression programs underlying hematopoietic differentiation was undertaken. Projection of single-cell transcriptomes from 175 samples spanning acute myeloid leukemia (AML), mixed phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) revealed 11 subtypes involving distinct stages of hematopoietic differentiation. These included AML subtypes with notable lymphoid or erythroid lineage priming, challenging traditional diagnostic boundaries between AML, MPAL, and AEL. Quantification of lineage priming in bulk patient cohorts revealed specific genetic alterations associated with this unconventional lineage priming. Integration of transcriptional and genetic information at the single-cell level revealed how genetic subclones can induce lineage restriction, differentiation blocks, or expansion of mature myeloid cells. Furthermore, we demonstrate that distinct cellular hierarchies can co-exist within individual patients, providing insight into AML evolution in response to varying selection pressures. Together, precise mapping of hematopoietic cell states can serve as a foundation for refining disease classification in acute leukemia and understanding response or resistance to emerging therapies.

Clinical forecasting of acute myeloid leukemia using ex vivo drug-sensitivity profiling

Current treatment selection for acute myeloid leukemia (AML) patients depends on risk stratification based on cytogenetic and genomic markers. However, the forecasting accuracy of treatment response remains modest, with most patients receiving intensive chemotherapy. Recently, ex vivo drug screening has gained traction in personalized treatment selection and as a tool for mapping patient groups based on relevant cancer dependencies. Here, we systematically evaluated the use of drug sensitivity profiling for predicting patient survival and clinical response to chemotherapy in a cohort of AML patients. We compared computational methodologies for scoring drug efficacy and characterized tools to counter noise and batch-related confounders pervasive in high-throughput drug testing. We show that ex vivo drug sensitivity profiling is a robust and versatile approach to patient prognostics that comprehensively maps functional signatures of treatment response and disease progression. In conclusion, ex vivo drug profiling can assess risk for individual AML patients and may guide clinical decision-making.

A longitudinal single-cell atlas of treatment response in pediatric AML

Pediatric acute myeloid leukemia (pAML) is characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains understudied in pediatric patients. We used single-cell RNA sequencing and single-cell ATAC sequencing to profile 28 patients representing different pAML subtypes at diagnosis, remission and relapse. At diagnosis, cellular composition differed between genetic subgroups. Upon relapse, cellular hierarchies transitioned toward a more primitive state regardless of subtype. Primitive cells in the relapsed tumor were distinct compared to cells at diagnosis, with under-representation of myeloid transcriptional programs and over-representation of other lineage programs. In some patients, this was accompanied by the appearance of a B-lymphoid-like hierarchy. Our data thus reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potentially targetable processes.

SINGLE CELL DISSECTION OF DEVELOPMENTAL ORIGINS AND TRANSCRIPTIONAL HETEROGENEITY IN B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA

Sequencing of bulk tumor populations has improved genetic classification and risk assessment of B-ALL, but does not directly examine intratumor heterogeneity or infer leukemia cellular origins. We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) and compared them to a reference map of normal human B-cell development established using both functional and molecular assays. Intra-sample heterogeneity was driven by cell cycle, metabolism, differentiation, and inflammation transcriptional programs. By inference of B lineage developmental state composition, nearly all samples possessed a high abundance of pro-B cells, with variation between samples mainly driven by sub-populations. However, ZNF384- r and DUX4- r B-ALL showed composition enrichment of hematopoietic stem cells, BCR::ABL1 and KMT2A -r ALL of Early Lymphoid progenitors, MEF2D -r and TCF3::PBX1 of Pre-B cells. Enrichment of Early Lymphoid progenitors correlated with high-risk clinical features. Understanding variation in transcriptional programs and developmental states of B-ALL by scRNA-seq refines existing clinical and genomic classifications and improves prediction of treatment outcome.

Epitope-engineered human hematopoietic stem cells are shielded from CD123-targeted immunotherapy

Targeted eradication of transformed or otherwise dysregulated cells using monoclonal antibodies (mAb), antibody-drug conjugates (ADC), T cell engagers (TCE), or chimeric antigen receptor (CAR) cells is very effective for hematologic diseases. Unlike the breakthrough progress achieved for B cell malignancies, there is a pressing need to find suitable antigens for myeloid malignancies. CD123, the interleukin-3 (IL-3) receptor alpha-chain, is highly expressed in various hematological malignancies, including acute myeloid leukemia (AML). However, shared CD123 expression on healthy hematopoietic stem and progenitor cells (HSPCs) bears the risk for myelotoxicity. We demonstrate that epitope-engineered HSPCs were shielded from CD123-targeted immunotherapy but remained functional, while CD123-deficient HSPCs displayed a competitive disadvantage. Transplantation of genome-edited HSPCs could enable tumor-selective targeted immunotherapy while rebuilding a fully functional hematopoietic system. We envision that this approach is broadly applicable to other targets and cells, could render hitherto undruggable targets accessible to immunotherapy, and will allow continued posttransplant therapy, for instance, to treat minimal residual disease (MRD).

Twisted: Escape of epitope-edited healthy cells from immune attack

Hematopoietic stem and progenitor cell-derived neoplasia is challenging to target by cell surface-directed immunotherapy due to lack of tumor cell-specific antigen identification. Marone et al. (2023. J. Exp. Med.https://doi.org/10.1084/jem.20231235) provide a solution by target-epitope resistance editing in healthy hematopoietic stem cells.

Targeted single-cell RNA sequencing analysis reveals metabolic reprogramming and the ferroptosis-resistant state in hematologic malignancies

Hematologic malignancies are the most common hematopoietic diseases and a major public health concern. However, the mechanisms underlying myeloid tumors remain unknown owing to the intricate interplay between mutations and diverse clonal evolution patterns, as evidenced by the analysis of bulk cell-derived omics data. Several single-cell omics techniques have been used to characterize the hierarchies and altered immune microenvironments of hematologic malignancies. The comprehensive single-cell atlas of hematologic malignancies provides novel opportunities for personalized combinatorial targeted treatments, avoiding unwanted chemo-toxicity. In the present study, we performed transcriptome sequencing by combining single-cell RNA sequencing (scRNA-seq) with a targeted oncogenic gene panel for acute myeloid leukemia, overcoming the limitations of scRNA-seq in detecting oncogenic mutations. The distribution of oncogenic IDH1, IDH2, and KRAS mutations in each cell type was identified in the bone marrow (BM) samples of each patient. Our findings suggest that ferroptosis and metabolic reprogramming are involved in the tumorigenesis and chemotherapy resistance of oncogenic mutation-carrying cells. Biological progression via IDH1, IDH2, and KRAS mutations arrests hematopoietic maturation. Our study findings provide a rationale for using primary BM cells for personalized treatment in clinical settings.

Albumin-to-fibrinogen ratio is an independent prognostic parameter in de novo non-M3 acute myeloid leukemia

Inflammation and nutrition related proteins participate in the development of acute myeloid leukemia (AML). It has been reported that the albumin-to-fibrinogen ratio (AFR) could serve as a prognostic indicator in patients with malignancy, but the precise relevance of AML is unclear. This study aimed to evaluate the effect of AFR on survival prognosis in patients with AML. We analyzed 227 patients newly diagnosed with non-M3 AML. AFR was calculated as albumin divided by fibrinogen. Based on the cutoff point from X-tile program, patients were divided into AFR-high (38.8%) and AFR-low (61.2%) groups. AFR-low group showed a poorer complete remission rate (P < 0.001) and median time to relapse (P = 0.026), while the mortality was higher (P = 0.009) than AFR-high ones. According to the log-rank test, AFR-low group had shorter OS (P < 0.001) and DFS (P = 0.034). Multivariate analysis identified AFR, ELN risk, bone marrow transplant, and hemoglobin as independent prognostic variables associated with OS. A visualized nomogram for predicting OS was performed. The C-index (0.75), calibration plots, and decision curve analyses of new model showed better discrimination, calibration, and net benefits than the ELN risk model. The time-dependent receiver operating characteristic (ROC) curve of 1-, 2-, and 3-year also functioned well (AUC, 0.81, 0.93 and 0.90, respectively). Our study provided a comprehensive view of AFR which could be an independent prognostic indicator in AML patients. The prognostic model utilized readily available information from ordinary clinical practice to improve predictive performance, identify risks, and assist in therapeutic decision-making.

A guide to epigenetics in leukaemia stem cells

Leukaemia stem cells (LSCs) are the critical seed for the growth of haematological malignancies, driving the clonal expansion that enables disease initiation, relapse and often resistance. Specifically, they display inherent phenotypic and epigenetic plasticity resulting in complex heterogenic diseases. In this review, we discuss the key principles of deregulation of epigenetic processes that shape this disease evolution. We consider measures to define and quantify clonal heterogeneity, combining information from recent studies assessing mutational, transcriptional and epigenetic landscapes at single cell resolution in myeloid neoplasms (MN). We highlight the importance of integrating epigenetic and genetic information to better understand inter- and intra-patient heterogeneity and discuss how this understanding further informs evolution and progression trajectories and subsequent clinical response in MN. Under this topic, we also discuss efforts to identify mechanisms of resistance, by longitudinal analyses of patient samples. Finally, we highlight how we might target these aberrant epigenetic processes for better therapeutic outcomes and to potentially eradicate LSCs.

Chimeric Antigen Receptor T Cells in Acute Myeloid Leukemia

Up to 30% of patients with acute myeloid leukemia (AML) who undergo chimeric antigen receptor (CAR) T-cell therapy have evidence of response, although trials are highly heterogeneous. These responses are rarely deep or durable. CD123, CD33, and CLL-1 have emerged as the most common targets for CAR T cells in AML. CAR T cells against myeloid antigens cause myeloablation as well as cytokine release syndrome, although neurotoxicity is rarely seen. Future efforts should focus on AML-specific antigen discovery or engineering, and on further enhancing the activity of CAR T cells.

Enhanced TP53 reactivation disrupts MYC transcriptional program and overcomes venetoclax resistance in acute myeloid leukemias

The tumor suppressor TP53 is frequently inactivated in a mutation-independent manner in cancers and is reactivated by inhibiting its negative regulators. We here cotarget MDM2 and the nuclear exporter XPO1 to maximize transcriptional activity of p53. MDM2/XPO1 inhibition accumulated nuclear p53 and elicited a 25- to 60-fold increase of its transcriptional targets. TP53 regulates MYC, and MDM2/XPO1 inhibition disrupted the c-MYC-regulated transcriptome, resulting in the synergistic induction of apoptosis in acute myeloid leukemia (AML). Unexpectedly, venetoclax-resistant AMLs express high levels of c-MYC and are vulnerable to MDM2/XPO1 inhibition in vivo. However, AML cells persisting after MDM2/XPO1 inhibition exhibit a quiescence- and stress response-associated phenotype. Venetoclax overcomes that resistance, as shown by single-cell mass cytometry. The triple inhibition of MDM2, XPO1, and BCL2 was highly effective against venetoclax-resistant AML in vivo. Our results propose a novel, highly translatable therapeutic approach leveraging p53 reactivation to overcome nongenetic, stress-adapted venetoclax resistance.

Evolutionary reversion in tumorigenesis

Cells forming malignant tumors are distinguished from those forming normal tissues based on several features: accelerated/dysregulated cell division, disruption of physiologic apoptosis, maturation/differentiation arrest, loss of polarity, and invasive potential. Among them, accelerated cell division and differentiation arrest make tumor cells similar to stem/progenitor cells, and this is why tumorigenesis is often regarded as developmental reversion. Here, in addition to developmental reversion, we propose another insight into tumorigenesis from a phylogeny viewpoint. Based on the finding that tumor cells also share some features with unicellular organisms, we propose that tumorigenesis can be regarded as "evolutionary reversion". Recent advances in sequencing technologies and the ability to identify gene homologous have made it possible to perform comprehensive cross-species transcriptome comparisons and, in our recent study, we found that leukemic cells resulting from a polycomb dysfunction transcriptionally resemble unicellular organisms. Analyzing tumorigenesis from the viewpoint of phylogeny should reveal new aspects of tumorigenesis in the near future, and contribute to overcoming malignant tumors by developing new therapies.

Design and optimization of selective and potent CDK9 inhibitors with flavonoid scaffold for the treatment of acute myeloid leukemia

Acute myeloid leukemia (AML) is a prevalent hematological tumor associated with a high morbidity and mortality rate. CDK9, functioning as a pivotal transcriptional regulator, facilitates transcriptional elongation through phosphorylation of RNA polymerase II, which further governs the protein levels of Mcl-1 and c-Myc. Therefore, CDK9 has been considered as a promising therapeutic target for AML treatment. Here, we present the design, synthesis, and evaluation of CDK9 inhibitors bearing a flavonoid scaffold. Among them, compound 21a emerged as a highly selective CDK9 inhibitor (IC50 = 6.7 nM), exhibiting over 80-fold selectivity towards most other CDK family members and high kinase selectivity. In Mv4-11 cells, 21a effectively hindered cell proliferation (IC50 = 60 nM) and induced apoptosis by down-regulating Mcl-1 and c-Myc. Notably, 21a demonstrated significant inhibition of tumor growth in the Mv4-11 xenograft tumor model. These findings indicate that compound 21a holds promise as a potential candidate for treating AML.

Acute myeloid leukemia with mixed phenotype is characterized by stemness transcriptomic signatures and limited lineage plasticity

Mixed phenotype (MP) in acute leukemias poses unique classification and management dilemmas and can be seen in entities other than de novo mixed phenotype acute leukemia (MPAL). Although WHO classification empirically recommends excluding AML with myelodysplasia related changes (AML-MRC) and therapy related AML (t-AML) with mixed phenotype (AML-MP) from MPAL, there is lack of studies investigating the clinical, genetic, and biologic features of AML-MP. We report the first cohort of AML-MRC and t-AML with MP integrating their clinical, immunophenotypic, genomic and transcriptomic features with comparison to MPAL and AML-MRC/t-AML without MP. Both AML cohorts with and without MP shared similar clinical features including adverse outcomes but were different from MPAL. The genomic landscape of AML-MP overlaps with AML without MP but differs from MPAL. AML-MP harbors more frequent RUNX1 mutations than AML without MP and MPAL. RUNX1 mutations did not impact the survival of patients with MPAL. Unsupervised hierarchal clustering based on immunophenotype identified biologically distinct clusters with phenotype/genotype correlation and outcome differences. Furthermore, transcriptomic analysis showed an enrichment for stemness signature in AML-MP and AML without MP as compared to MPAL. Lastly, MPAL but not AML-MP often switched to lymphoid only immunophenotype after treatment. Expression of transcription factors critical for lymphoid differentiation were upregulated only in MPAL, but not in AML-MP. Our study for the first time demonstrates that AML-MP clinically and biologically resembles its AML counterpart without MP and differs from MPAL, supporting the recommendation to exclude these patients from the diagnosis of MPAL. Future studies are needed to elucidate the molecular mechanism of mixed phenotype in AML.

Key points

AML-MP clinically and biologically resembles AML but differs from MPAL. AML-MP shows RUNX1 mutations, stemness signatures and limited lymphoid lineage plasticity.

Clinical Correlates of Venetoclax-Based Combination Sensitivities to Augment Acute Myeloid Leukemia Therapy

The BCL2 inhibitor venetoclax combined with the hypomethylating agent azacytidine shows significant clinical benefit in a subset of patients with acute myeloid leukemia (AML); however, resistance limits response and durability. We prospectively profiled the ex vivo activity of 25 venetoclax-inclusive combinations on primary AML patient samples to identify those with improved potency and synergy compared with venetoclax + azacytidine (Ven + azacytidine). Combination sensitivities correlated with tumor cell state to discern three patterns: primitive selectivity resembling Ven + azacytidine, monocytic selectivity, and broad efficacy independent of cell state. Incorporation of immunophenotype, mutation, and cytogenetic features further stratified combination sensitivity for distinct patient subtypes. We dissect the biology underlying the broad, cell state-independent efficacy for the combination of venetoclax plus the JAK1/2 inhibitor ruxolitinib. Together, these findings support opportunities for expanding the impact of venetoclax-based drug combinations in AML by leveraging clinical and molecular biomarkers associated with ex vivo responses.

SIGNIFICANCE

By mapping drug sensitivity data to clinical features and tumor cell state, we identify novel venetoclax combinations targeting patient subtypes who lack sensitivity to Ven + azacytidine. This provides a framework for a taxonomy of AML informed by readily available sets of clinical and genetic features obtained as part of standard care. See related commentary by Becker, p. 437 . This article is featured in Selected Articles from This Issue, p. 419.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals RNA N6-methyladenosine modification associated with prognosis and drug resistance in acute myeloid leukemia

Introduction

Acute myeloid leukemia (AML) is a type of blood cancer that is identified by the unrestricted growth of immature myeloid cells within the bone marrow. Despite therapeutic advances, AML prognosis remains highly variable, and there is a lack of biomarkers for customizing treatment. RNA N6-methyladenosine (m6A) modification is a reversible and dynamic process that plays a critical role in cancer progression and drug resistance.

Methods

To investigate the m6A modification patterns in AML and their potential clinical significance, we used the AUCell method to describe the m6A modification activity of cells in AML patients based on 23 m6A modification enzymes and further integrated with bulk RNA-seq data.

Results

We found that m6A modification was more effective in leukemic cells than in immune cells and induced significant changes in gene expression in leukemic cells rather than immune cells. Furthermore, network analysis revealed a correlation between transcription factor activation and the m6A modification status in leukemia cells, while active m6A-modified immune cells exhibited a higher interaction density in their gene regulatory networks. Hierarchical clustering based on m6A-related genes identified three distinct AML subtypes. The immune dysregulation subtype, characterized by RUNX1 mutation and KMT2A copy number variation, was associated with a worse prognosis and exhibited a specific gene expression pattern with high expression level of IGF2BP3 and FMR1, and low expression level of ELAVL1 and YTHDF2. Notably, patients with the immune dysregulation subtype were sensitive to immunotherapy and chemotherapy.

Discussion

Collectively, our findings suggest that m6A modification could be a potential therapeutic target for AML, and the identified subtypes could guide personalized therapy.

A scoring system based on fusion genes to predict treatment outcomes of the non-acute promyelocytic leukemia pediatric acute myeloid leukemia

Background

Fusion genes are considered to be one of the major drivers behind cancer initiation and progression. Meanwhile, non-acute promyelocytic leukemia (APL) pediatric patients with acute myeloid leukemia (AML) in children had limited treatment efficacy. Hence, we developed and validated a simple clinical scoring system for predicting outcomes in non-APL pediatric patients with AML.

Method

A total of 184 non-APL pediatric patients with AML who were admitted to our hospital and an independent dataset (318 patients) from the TARGET database were included. Least absolute shrinkage and selection operation (LASSO) and Cox regression analysis were used to identify prognostic factors. Then, a nomogram score was developed to predict the 1, 3, and 5 years overall survival (OS) based on their clinical characteristics and fusion genes. The accuracy of the nomogram score was determined by calibration curves and receiver operating characteristic (ROC) curves. Additionally, an internal verification cohort was used to assess its applicability.

Results

Based on Cox and LASSO regression analyses, a nomogram score was constructed using clinical characteristics and OS-related fusion genes (CBFβ::MYH11, RUNX1::RUNX1T1, KMT2A::ELL, and KMT2A::MLLT10), yielded good calibration and concordance for predicting OS of non-APL pediatric patients with AML. Furthermore, patients with higher scores exhibited worse outcomes. The nomogram score also demonstrated good discrimination and calibration in the whole cohort and internal validation. Furthermore, artificial neural networks demonstrated that this nomogram score exhibits good predictive performance.

Conclusion

Our model based on the fusion gene is a prognostic biomarker for non-APL pediatric patients with AML. The nomogram score can provide personalized prognosis prediction, thereby benefiting clinical decision-making.

A Novel Type of Monocytic Leukemia Stem Cell Revealed by the Clinical Use of Venetoclax-Based Therapy

The BCL2 inhibitor venetoclax has recently emerged as an important component of acute myeloid leukemia (AML) therapy. Notably, use of this agent has revealed a previously unrecognized form of pathogenesis characterized by monocytic disease progression. We demonstrate that this form of disease arises from a fundamentally different type of leukemia stem cell (LSC), which we designate as monocytic LSC (m-LSC), that is developmentally and clinically distinct from the more well-described primitive LSC (p-LSC). The m-LSC is distinguished by a unique immunophenotype (CD34-, CD4+, CD11b-, CD14-, CD36-), unique transcriptional state, reliance on purine metabolism, and selective sensitivity to cladribine. Critically, in some instances, m-LSC and p-LSC subtypes can co-reside in the same patient with AML and simultaneously contribute to overall tumor biology. Thus, our findings demonstrate that LSC heterogeneity has direct clinical significance and highlight the need to distinguish and target m-LSCs as a means to improve clinical outcomes with venetoclax-based regimens.

SIGNIFICANCE

These studies identify and characterize a new type of human acute myeloid LSC that is responsible for monocytic disease progression in patients with AML treated with venetoclax-based regimens. Our studies describe the phenotype, molecular properties, and drug sensitivities of this unique LSC subclass. This article is featured in Selected Articles from This Issue, p. 1949.

Deep learning of 2D-Restructured gene expression representations for improved low-sample therapeutic response prediction

Clinical outcome prediction is important for stratified therapeutics. Machine learning (ML) and deep learning (DL) methods facilitate therapeutic response prediction from transcriptomic profiles of cells and clinical samples. Clinical transcriptomic DL is challenged by the low-sample sizes (34-286 subjects), high-dimensionality (up to 21,653 genes) and unordered nature of clinical transcriptomic data. The established methods rely on ML algorithms at accuracy levels of 0.6-0.8 AUC/ACC values. Low-sample DL algorithms are needed for enhanced prediction capability. Here, an unsupervised manifold-guided algorithm was employed for restructuring transcriptomic data into ordered image-like 2D-representations, followed by efficient DL of these 2D-representations with deep ConvNets. Our DL models significantly outperformed the state-of-the-art (SOTA) ML models on 82% of 17 low-sample benchmark datasets (53% with >0.05 AUC/ACC improvement). They are more robust than the SOTA models in cross-cohort prediction tasks, and in identifying robust biomarkers and response-dependent variational patterns consistent with experimental indications.