IntroductionAcute Myeloid Leukemia (AML) is characterized by genetic and epigenetic dysregulation in myeloid progenitor cells. Histone H3 mutations disrupt chromatin and transcription, contributing to disease, but identifying mutations in histone genes is challenging due to sequence duplication. In particular, histone H2A genes H2AC18 and H2AC19, which share identical sequences, have been largely overlooked. MethodsCancer genomic datasets were interrogated to identify novel variants, and in vivo functional assays were conducted using Drosophila melanogaster tumor models.Resultsa recurrent Alanine to Valine substitution at position 127 (H2A-A127V) was identified in AML and also found in solid tumors, suggesting a broader cancer association. Using a Drosophila melanogaster model, H2A-A127V was shown to promote eye tumor phenotypes and, in the eyeful tumor model, intensified tissue overgrowth. The variant also interacts with the Enhancer of zeste (E(z)), a PRC2 complex member. E(z) downregulation in the presence of H2A-A127V enhanced ectopic growth, suggesting PRC2’s role in disease progression. Analysis of the 1000 Genomes Project revealed that H2A-A127V is an uncommon polymorphism (1.44%), potentially predisposing carriers to cancer.DiscussionThese findings uncover a novel cancer-associated histone variant and emphasize the need to consider duplicated histone genes in mutation analyses to better understand cancer development.

Relapse in cancer is frequently driven by therapy-resistant quiescent cancer stem cells. Conventional chemotherapy has been designed to target proliferating tumor cells and is generally presumed to be ineffective against non-cycling cancer stem cells. Using acute myeloid leukemia (AML) as a model, we challenge this prevailing view by showing that inhibition of the mitotic master regulator Polo-like kinase 1 (PLK1), a kinase extensively pursued for antiproliferative cancer therapy, unexpectedly eradicates quiescent leukemia stem cells (LSC) through a mechanism distinct from its canonical mitotic function. In proliferating AML cells, PLK1 inhibition (PLK1i) induced G2/M arrest and mitotic catastrophe. In contrast, quiescent LSC underwent apoptosis independent of mitotic arrest, revealing a cell-state-dependent mode of drug action. Mechanistically, PLK1i initiated a multi-step process through disruption of a previously unrecognized, stem cell-specific interaction between PLK1 and MAP1A, resulting in perturbed vesicle trafficking and endolysosomal homeostasis characterized by altered receptor internalization, vesicle accumulation and lysosomal dysfunction, ultimately culminating in apoptotic cell death. Combinatorial pharmacologic perturbation studies established microtubule regulation as a critical determinant of quiescent LSC survival, while ex vivo and in vivo assays demonstrated depletion of functionally-defined LSC following PLK1i. These findings identify a previously unrecognized role for PLK1 in intracellular trafficking and establish MAP1A-dependent control of vesicle homeostasis as a mechanistic determinant of cancer stem cell survival. More broadly, this study demonstrates that classical antimitotic compounds, including microtubule-targeting agents and PLK1 inhibitors, can eradicate both cycling leukemic blasts and quiescent LSC through distinct, cell state-dependent mechanisms, challenging proliferation-centric models of chemotherapy action.

Despite most acute myeloid leukemia (AML) patients achieving complete remission after induction chemotherapy, two-thirds relapse within 5 years. AML follows a cellular hierarchy sustained by leukemia stem cells (LSCs), which drive tumor progression and relapse. Little is known about the genetic determinants driving LSCs stemness properties. By identifying chromatin variants from accessibility measurements across LSCs, hematopoietic stem cells and downstream progeny, we identified transposable elements (TEs) as genetic determinants of primitive versus mature populations. Accessibility at 121 TE subfamilies distinguished LSCs from mature leukemic cells and stratified AML patients by stemness and survival. Functional assays revealed that these TE subfamilies serve as docking sites for genome topology regulators or lineage-specific transcription factors, including LYL1 in LSCs. Chromatin editing established the necessity of accessibility at LTR12C elements to maintain LSC stemness. Thus, TEs regulate primitive versus mature cell states, with distinct subfamilies underlying stemness in normal versus leukemic stem cells.

In acute myeloid leukemia (AML), genetic mutations distort hematopoietic differentiation, resulting in the accumulation of leukemic blasts. However, it remains unclear how these mutations intersect with the cellular origins of each patient's disease, and whether distinct sets of mutations converge upon similar differentiation patterns. Single-cell RNA sequencing has enabled high-resolution mapping of the relationship between leukemia and normal hematopoietic cell states. Yet, this application has been hampered by imprecise reference maps of normal hematopoiesis, or by small patient cohort sizes which do not adequately capture the extent of inter-patient heterogeneity in AML. To resolve this, we constructed a reference atlas of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes enriched for rare hematopoietic stem and progenitor cells (HSPCs). The resulting reference spans 55 cellular states and has been benchmarked against independent datasets of purified HSPCs. Using this comprehensive reference atlas, we confidently mapped over 1.2 million single-cell transcriptomes from 318 patient samples spanning AML, mixed-phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) diagnoses. Single-cell composition analysis revealed twelve patient subgroups, each reflecting distinct patterns of aberrant differentiation in AML. Strikingly, some AML samples exhibited virtually no overlap in cell state involvement with one another, likely reflecting their disparate cellular origins. One subgroup was enriched for early lymphoid progenitors and featured co-clustering of AML and MPAL samples. Notably, this early lymphoid subgroup included an AML sample which eventually relapsed with lymphoid disease. To understand the genetic determinants of aberrant differentiation in AML, we quantified leukemia cell state abundance in >1,200 patient samples and evaluated genotype-to-phenotype associations to link >40 genetic driver alterations with their specific impacts on AML differentiation. This identified genetic drivers for unconventional lineage phenotypes in AML, including erythroid lineage priming associated with the co-occurrence of complex cytogenetics with TP53 mutations as well as lymphoid lineage priming associated with bi-allelic RUNX1 mutations. We also identified non-genetic determinants of AML differentiation. For example, we identified two subgroups of KMT2A-rearranged AML with distinct cellular origins reflecting either HSPCs or committed myeloid precursors. Last, we show that distinct leukemia cell hierarchies can co-exist within individual patients, providing insights into AML evolution. Together, single-cell reference mapping of malignant cell states provides a framework for understanding the impact of genetic alterations on hematopoietic differentiation across hundreds of individual AML patients. Andy G. Zeng, Ilaria Iacobucci, Sayyam Shah, Amanda Mitchell, Gordon Wong, Suraj Bansal, David Chen, Qingsong Gao, Hyerin Kim, James A. Kennedy, Andrea Arruda, Mark D. Minden, Torsten Haferlach, Charles G. Mullighan, John E. Dick. Single-cell transcriptional mapping reveals genetic and non-genetic determinants of aberrant differentiation in AML [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 3806.

Therapeutic targeting of acute myeloid leukemia (AML) is hampered by intra- and inter-tumoral cell state heterogeneity. To develop a more precise understanding of AML cell states, we constructed a reference atlas of human hematopoiesis from 263,159 single-cell transcriptomes spanning 55 cellular states. Using this atlas, we mapped more than 1.2 million cells spanning 318 leukemia samples, revealing 12 recurrent patterns of aberrant differentiation in AML. Notably, this uncovered unexpected AML cell states resembling lymphoid and erythroid progenitors that were prognostic within the clinically heterogeneous context of normal karyotype AML, independent of genomic classifications. Systematic mapping of genotype-to-phenotype associations revealed specific differentiation landscapes associated with more than 45 genetic drivers. Importantly, distinct cellular hierarchies can arise from samples sharing the same genetic driver, potentially reflecting distinct cellular origins for disease-sustaining leukemia stem cells. Thus, precise mapping of malignant cell states provides insights into leukemogenesis and refines disease classification in acute leukemia. SIGNIFICANCE:We present a single-cell reference atlas of human hematopoiesis and a computational tool for rapid mapping and classification of healthy and leukemic cells. Applied to AML, this has enabled single-cell analysis at the scale of hundreds of patient samples, revealing the full breadth of derailment of differentiation in AML. See related commentary by Berger and Penter, p. 280.

Leukemic stem cells (LSCs) fuel acute myeloid leukemia (AML) growth and relapse, but therapies tailored towards eradicating LSCs without harming normal hematopoietic stem cells (HSCs) are lacking. FLT3 is considered an important therapeutic target due to frequent mutation in AML and association with relapse. However, there has been limited clinical success with FLT3 drug targeting, suggesting either that FLT3 is not a vulnerability in LSC, or that more potent inhibition is required, a scenario where HSC toxicity could become limiting. We tested these possibilities by ablating FLT3 using CRISPR/Cas9-mediated FLT3 knock-out (FLT3-KO) in human LSCs and HSCs followed by functional xenograft assays. FLT3-KO in LSCs from FLT3-ITD mutated, but not FLT3-wild type (WT) AMLs, resulted in short-term leukemic grafts of FLT3-KO edited cells that disappeared by 12 weeks. By contrast, FLT3-KO in HSCs from fetal liver, cord blood and adult bone marrow did not impair multilineage hematopoiesis in primary and secondary xenografts. Our study establishes FLT3 as an ideal therapeutic target where ITD+ LSC are eradicated upon FLT3 deletion, while HSCs are spared. These findings support the development of more potent FLT3-targeting drugs or gene-editing approaches for LSC eradication to improve clinical outcomes.

Acute myeloid leukemia (AML) is associated with differentiation arrest at different stages of the hematopoietic hierarchy. Single-cell RNA-sequencing (scRNA-seq) studies have advanced our understanding of malignant cell states in AML and their relation to prognosis, relapse, and drug response. However, it remains unclear how these transcriptional AML cell states intersect with flow cytometry markers used for clinical characterization of AML. This study aims to nominate existing and new surface markers associated with 12 transcriptionally-defined AML cell states across leukemia cell hierarchies. We developed a novel consensus marker identification framework, IsoMarker, to identify optimal AML cell state markers through integration of classical differential expression with explainable machine learning approaches.We applied IsoMarker to an integrated atlas of scRNA-seq data from over 500,000 cells of 188 iAML patient samples from 8 datasets to nominate a panel of 36 positive and 23 negative cell surface markers of 12 leukemic cell states. We validated these markers by comparing expression levels of each marker with transcriptionally-inferred cell state abundance from 1037 total patients across the TCGA, BEAT-AML, and Leucegene cohorts. Among these candidate cell state markers, 11 surface markers were also associated with functional leukemia stem cell activity, ex vivo drug response, and overall survival outcomes. We are currently validating the top markers by flow cytometry-based quantification compared to transcriptionally-inferred cell state abundance in a local cohort of 80 bone marrow aspirate samples from AML patients. In summary, this study aims to translate insights from single-cell transcriptomics into hematopathology practice by advancing flow cytometry-based identification of leukemic cell states and prediction of clinical outcomes.

Acute myeloid leukemia (AML) is a hematologic malignancy classically associated with an expansion of poorly differentiated myeloid cells. Single-cell RNA-sequencing (scRNA-seq) studies have advanced our understanding of differentiation arrest across the leukemia cell hierarchy and their relation to prognosis, relapse, and drug response. Leukemic cellular hierarchy composition, such as Primitive versus GMP or Primitive versus Mature axes of cell state abundance, can define response to chemotherapy or targeted therapy sensitivity respectively (Zeng et al. Nature Med 2022). However, it remains unclear how these transcriptional AML cell states intersect with existing biomarkers used for clinical characterization of AML, such as cell surface markers used by clinical flow cytometry. This study aims to nominate existing and new surface markers associated with transcriptionally-defined AML cell states across leukemia cell hierarchies. We developed a novel consensus marker identification approach, IsoMarker, to identify a minimal set of enriched (differential expression), specific (auROC), and predictive (SHAP) cell surface markers for each AML cell state. To validate the utility of this approach, we generated an integrated scRNA-seq atlas of 1,079,555 single cells spanning 316 AML patient samples and 21 datasets, identifying 13 consensus leukemia cell states. Using IsoMarker, we identified 56 positive and 33 negative cell surface markers which effectively discern between the 13 leukemia cell states. We validated these markers by confirming that the expression levels of each positive marker were positively correlated with transcriptionally-inferred cell state abundance from 1037 total patients across the TCGA, BEAT-AML, and Leucegene cohorts. Composition of different leukemic cell states is known to govern functional leukemic stem cell activity, leading to heterogeneity in response to therapy and overall survival of AML patients. To extend the diagnostic utility of our nominated cell-state markers to include prediction of clinical outcomes, we conducted an integrative analysis of the positive AML cell state markers in relation to leukemic stem cell activity, ex vivo drug response, and meta-analysis of overall survival. Among the candidate positive cell state markers, 10 markers were associated with functional leukemia stem cell engraftment in mice, 5 markers were associated with the GMP cell state that defines response to chemotherapy, and 4 markers were associated with overall survival outcomes. We conducted a literature review of the 56 candidate positive markers in the context of AML to determine if IsoMarker can resolve both well-known and novel markers of AML cell states. Out of the 59 positive markers identified by IsoMarker, 21 have been previously reported as diagnostic markers of AML cell states. There are 35 positive markers that have not been characterized in the literature review and may serve as candidate, context-specific biomarkers of AML cell states. In summary, this study aims to translate insights from single-cell transcriptomics into hematopathology practice by advancing identification of markers that discern leukemic cell states and predict clinical outcomes. Applied to the task of identifying markers of AML cell states, IsoMarker is able to both resolve well-known markers and nominate novel markers useful for characterization of AML in relation to prognosis, relapse, and drug response. soMarker is a powerful framework for marker identification of cell states in single cell studies that can be generalized to other types of cancer.

The underlying gene regulatory networks (GRN) that govern leukemia stem cells (LSC) in acute myeloid leukemia (AML) and hematopoietic stem cells (HSC) are not well understood. Here, we identified GRNs by integrating gene expression (GE) and chromatin accessibility data derived from functionally defined cell populations enriched for HSC and LSC. We analyzed n=32 LSC+ and n=32 LSC- cell fractions from n=22 AML patients, along with n=7 stem and n=10 progenitor enriched cell populations sorted from human umbilical cord blood (hUCB), producing a database of n≈17,000 transcription factor (TF) regulatory interactions for hUCB-HSPC and AML. We developed an iterative algorithm that associates the degree of chromatin openness with TF binding preferences, and the GE of candidate TF and target genes within 100kb upstream of transcription start sites. A putative regulatory structure was found to be enriched in HSC-enriched cell populations, comprising TF-target gene interactions between ETS1, EGR1, RUNX2, and ZNF683 oriented in a self-reinforcing configuration. A regulatory loop comprising FOXK1 and MEIS1, rather than the 4-factor HSC subnetwork, was detected in the LSC-specific GRN. The core HSC and LSC TF networks were extended using protein-protein interaction (PPI) data to determine connectivity with interacting genes whose expression strongly associated with LSC/HSC frequency estimates, producing a database of n=103,516 PPI target pathways. The effect of perturbing genes along the identified pathways on functional HSC and LSC frequency was predicted based on statistical regression analyses. To validate GRN predictions, we used pharmacologic and CRISPR targeting, in addition to re-examining published functional data associated with several network nodes that were predicted to impact stemness. Notably, we found that inhibition of CDK6 in AML samples markedly reduced LSC numbers as assessed in de novo serial xenotransplantation studies (fold change ≈ 10), as predicted by the LSC GRN model. Additionally, in-house CRISPR-based knockdown of ETS1 resulted in a significant decrease in HSC quiescence-associated microRNA-126 expression, and increased HSC frequency. Taken together, our models provide a comprehensive view of the underlying regulatory structures governing functional human HSC and LSC. This approach has translational potential as it can be used as a high-throughput in-silico screening tool for the systematic identification of gene targets for LSC elimination and HSC expansion. ### Competing Interest Statement The authors have declared no competing interest.

Initial disease classification within acute leukemia relies on identifying morphological and immunophenotypic features of hematopoietic differentiation retained by leukemic blasts. While existing approaches can classify leukemic cells into broad lineages, they lack precision in discerning between specific cell states, particularly at the level of immature blasts. Single-cell (sc) RNA-sequencing (RNA-seq) provides thousands of new markers to enable precise determination of leukemia cell state and provides an opportunity to refine our classification of acute leukemia. To extend our ability to identify leukemia cell states by scRNA-seq, we developed a comprehensive reference map of human bone marrow hematopoiesis. Specifically, we integrated three unsorted bone marrow datasets and three CD34+ hematopoietic stem and progenitor (HSPC) purified datasets to ensure balanced representation of early HSPCs and terminally differentiated immune cells. This culminated in a curated atlas of 263,159 high-quality sc transcriptomes, representing 55 cellular states spanning 45 healthy donors (Fig 1A). We validated our cell state annotations to ensure concordance between transcriptional states and functional populations through reference mapping of bulk and sc transcriptomes from purified HSPC subsets. For example, mapping of scRNA-seq profiles from Lin-CD34+38-45RA-90+49f+ long-term (LT) HSCs revealed 91% concordance between transcriptional HSC and functional LT-HSC. We next performed scRNA-seq profiling on 12 AML patient samples harbouring either myelodysplasia-related genetic features or classical alterations involving NPM1 or KMT2A. By mapping leukemia cells onto our reference atlas, we identified pronounced involvement of early erythroid-like blasts in a subset of AML samples. To further investigate unconventional lineage priming in AML, we processed and mapped scRNA-seq profiles from eleven studies comprising 166 additional AML samples and 9 mixed phenotype acute leukemia (MPAL) samples (Fig 1B). After quality control and exclusion of mature lymphoid cells, we performed composition analysis utilizing 600,570 leukemia cells mapped to 38 cell states to identify patterns of variation among leukemia cell states. Immature leukemia cells map to a range of cellular states spanning HSC/MPP-like, LMPP-like, MLP-like, GMP-like, MEP-like, and EarlyEry-like, among others. Notably, we identified a subset of AMLs with high MLP-like enrichment that co-cluster with MPALs as well as a subset with high EarlyEry-like involvement that co-cluster with acute erythroid leukemias (AEL), thus highlighting the biological continuum between these diseases. We next identified marker genes from each leukemia cell state and trained sparse regression models to estimate their relative abundance within bulk RNA-seq cohorts. Through bulk analysis, we confirmed that MPAL is highly enriched for MLP-like cells compared to AML (p=2.5e-12) and that M6 AELs are highly enriched for EarlyEry-like cells compared to M0-M5 AMLs (p=0.00067). Among 864 AML patients, we found that high MLP-like abundance was associated with NUP98-NSD1 fusions (p=0.0011) and RUNX1 mutations (p=8.0e-10) while high EarlyEry-like abundance was associated with Complex Cytogenetics (p=8e-15) and TP53 mutations (p=2.3e-25). Cellular states of immature leukemic cells captured inter-patient heterogeneity within 136 AEL samples, wherein high EarlyEry-like abundance was associated with TP53 mutations (p=3.6e-9) and Poor cytogenetic risk (p=1.1e-9) while high GMP-like abundance was associated with KMT2A alterations (p=0.00046) and Good/Intermediate risk (p=0.00032). Finally, through integration of sc transcriptomics and targeted DNA profiling, we found examples of genetic subclones impacting the cellular hierarchies of individual patients through induction of early differentiation blocks, skewing of lineage output from myeloid to erythroid, or potentiation of transcriptional self-renewal programs within mature myeloid cells. Together, our high-resolution mapping approach highlights the cellular state continuum between acute leukemias and enumerates the impact of genetic drivers on leukemia cell hierarchies. Precise definitions of cellular states, coupled with the presence or absence of genetic alterations, may help to refine future disease classification, prognostication, and therapy development.

Acute myeloid leukemia (AML) is an aggressively heterogeneous disease with poor survival outcomes. An important checkpoint for AML drug development is ensuring target expression is enriched on leukemia cells compared to normal hematopoietic cells to avoid perturbing normal hematopoiesis. However, drugs satisfying this criterion still face additional challenges attributable to heterogeneity in AML, causing patients to develop resistance and relapse. In AML, chemoresistance and relapse are mediated by adverse genomic drivers and leukemia stem cell (LSC)-enriched cellular hierarchies (Zeng Nat Med 2022). This underscores the importance of identifying targets both enriched in leukemia and associated with sources of AML heterogeneity. Although many transcriptomic tools and pipelines have emerged for AML, none have linked gene expression to deep functional properties and non-genetic sources of intersample heterogeneity to enable informed predictions. To bridge this gap, we introduce ATLAS-AML, an automated bioinformatics pipeline for transcriptomic meta-analysis of genes and gene signatures in adult and pediatric AML. ATLAS-AML integrates 30 bulk (2172 donors) and single-cell (975,220 cells from 283 donors) RNA-sequencing datasets with preconfigured pipelines to streamline three key analyses for genes or gene signatures: (1) expression across normal and leukemic hematopoietic hierarchies, (2) enrichment in functionally-validated LSC+ fractions and (3) associations with relapse, genomics, clinical characteristics and patient survival. For established targets, ATLAS-AML can determine which patients, based on their mutational and cytogenetic profiles, are most likely to respond favorably to a potential treatment. ATLAS-AML is available as a containerized R package that experimental scientists can employ without bioinformatics expertise. To demonstrate how ATLAS-AML can guide target prioritization and characterization, we systematically analyzed published targets in ATLAS-AML. We identified 70 targets reported in the literature to be either enriched in leukemia, associated with LSCs, overexpressed at relapse, or predictive of patient survival. After benchmarking each gene against the aforementioned outcomes in ATLAS-AML, we observed that published targets were often optimized for particular outcomes, potentially overlooking other critical perspectives of AML biology. For example, several genes were enriched on leukemia cells, but not associated with genomics and stemness perspectives of AML heterogeneity nor clinical outcomes like relapse and patient survival. ATLAS-AML also constitutes a powerful framework for accelerating new target discovery. Reinterrogating our dataset with differential expression, we identified genes with enrichment in the same outcomes we benchmarked published targets against. Applying a meta p-value analysis, ATLAS-AML uncovered 13 targets that were overexpressed on leukemia cells compared to normal hematopoietic cells, enriched in functionally-validated LSCs, associated with disease relapse, and predictive of patient survival. For example, ATLAS-AML nominated CNST, a trans-Golgi network receptor for targeting connexins to the plasma membrane. CNST is differentially expressed on leukemia cells (p=0.000043), linked to functional LSC engraftment (p=0.000015), overexpressed at relapse (p=0.00036) and associated with poor prognosis in multivariable survival analysis in three independent cohorts (HR 1.23, p=0.04), lending to CNST's therapeutic viability in AML. Furthermore, ATLAS-AML determined that CNST expression was highest in RUNX1-mutated AMLs, identifying a patient group to prioritize for anti-CNST therapies. Altogether, ATLAS-AML enables scientists to leverage insights from single-cell and bulk transcriptomics to inform preclinical studies towards risk-tailored treatments in AML.

Background: Resistance to standard chemotherapy is a clinical and biological hallmark of leukemic stem cells (LSCs). The ideal therapy to eradicate leukemia would target the unique vulnerabilities of LSCs while preserving normal hematopoiesis. FLT3 is routinely targeted in FLT3-ITD mutated acute myeloid leukemia (AML), a form of AML especially prone to relapse. Surprisingly, little is known about the importance of FLT3 for LSCs or normal hematopoietic stem cells (HSCs), thus raising questions about how effectively we can or should target FLT3. Aims: Here, we investigated, in parallel, the impact of FLT3 on normal human blood production by HSCs and on leukemia propagation by LSCs. Methods: Using CRISPR/Cas9-mediated gene-editing, we knocked out (KO) FLT3 from HSC originating from human fetal liver, cord blood and adult bone marrow, and from primary AML patient samples with and without FLT3-ITD mutations. The stem cell properties of FLT3-KO and control cells were assessed in xenotransplantation assays, using sub-lethally irradiated NSG mice. Results: We found that normal HSCs from fetal, neonatal and adult human tissues with FLT3-KO retained the ability to form persistent multilineage grafts in immunodeficient recipients, even upon serial transplantation. LSCs from FLT3-ITD mutated AMLs could also engraft upon FLT3-KO but leukemic grafts were lost overtime, suggesting that FLT3 is essential for leukemic persistence and propagation. This dependency was unique to FLT3-ITD AML samples as other types of AML were able to form persistent leukemic grafts upon FLT3-KO. In transcriptomic studies, KO of FLT3 was associated with downregulation of cell cycle checkpoints and DNA repair pathways only in FLT3-ITD mutated AMLs - not in normal HSCs or AML cells without FLT3 mutations. Within in vivo functional studies, FLT3 KO in ITD-mutated AML cells was associated with increased cell cycle progression, DNA damage accumulation and cell death. These data suggest that, specifically in FLT3-ITD mutated AMLs, KO of FLT3 leads to uncontrolled cell cycle progression, DNA damage accumulation and LSC exhaustion that, ultimately, results in the extinction of leukemic clones observed in vivo. Competitive repopulation experiments between normal HSCs and FLT3-ITD mutated LSCs, revealed that grafts were invariably composed of leukemic cells with the mice becoming severely sick in the control group; on the contrary, FLT3 KO group was healthy and the grafts were composed of cells from all blood lineages with normal maturation. Summary/Conclusion: Our study suggests that FLT3 has a dual role in normal and leukemic hematopoiesis: whereas normal blood production can be sustained despite FLT3 disruption, leukemic cells, specifically the highly relapsing form of AML that harbors FLT3-ITD mutations, are extinguished upon FLT3 KO. This evidence places FLT3 as an ideal therapeutic target in AML – essential for LSCs but dispensable for normal HSCs – stressing the need to optimize FLT3 targeting in clinical practice.Keywords: FLT3, Acute myeloid leukemia, Hematopoietic stem cell, Leukemic stem cell

Acute myeloid leukemia (AML) is a heterogeneous, aggressive malignancy with dismal prognosis and with limited availability of targeted therapies. Epigenetic deregulation contributes to AML pathogenesis. KDM6 proteins are histone-3-lysine-27-demethylases that play context-dependent roles in AML. We inform that KDM6-demethylase function critically regulates DNA-damage-repair-(DDR) gene expression in AML. Mechanistically, KDM6 expression is regulated by genotoxic stress, with deficiency of KDM6A-(UTX) and KDM6B-(JMJD3) impairing DDR transcriptional activation and compromising repair potential. Acquired KDM6A loss-of-function mutations are implicated in chemoresistance, although a significant percentage of relapsed-AML has upregulated KDM6A. Olaparib treatment reduced engraftment of KDM6A-mutant-AML-patient-derived xenografts, highlighting synthetic lethality using Poly-(ADP-ribose)-polymerase-(PARP)-inhibition. Crucially, a higher KDM6A expression is correlated with venetoclax tolerance. Loss of KDM6A increased mitochondrial activity, BCL2 expression, and sensitized AML cells to venetoclax. Additionally, BCL2A1 associates with venetoclax resistance, and KDM6A loss was accompanied with a downregulated BCL2A1. Corroborating these results, dual targeting of PARP and BCL2 was superior to PARP or BCL2 inhibitor monotherapy in inducing AML apoptosis, and primary AML cells carrying KDM6A-domain mutations were even more sensitive to the combination. Together, our study illustrates a mechanistic rationale in support of a novel combination therapy for AML based on subtype-heterogeneity, and establishes KDM6A as a molecular regulator for determining therapeutic efficacy.

Supplemental Methods Supplemental Table 1 Supplemental Figures 1-6 1. Pretreatment with cytarabine potentiates the effects of FED in AML xenografts. Supplemental Figure 2. PF cytometry analysis of AML samples. Supplemental Figure 3. Immunophenotypic and phosphoprotein signaling heterogeneity of AML patient samples. Supplemental Figure 4. PF analysis of validation cohort samples Supplemental Figure 5. Effects of FED treatment on FLT3 activity. Supplemental Figure 6. Effects of FED and DAS treatment on pSTAT5, pSRC and pTyr in BCR-ABL1+ AML samples. Supplemental Table 1: Characteristics of patient samples studied in initial and validation cohorts.

Supplementary figure legends and full list of materials and methods references

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