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

Lymphoma and Leukemia Cell Vulnerabilities and Resistance Identified by Compound Library Screens

Response to anticancer agents is often restricted to subsets of patients. Recognition of factors underlying this heterogeneity and identification of biomarkers associated with response to drugs would greatly improve the efficacy of drug treatment. Platforms that can comprehensively map cellular response to compounds in high-throughput provide a unique tool to identify associated biomarkers and provide hypotheses for mechanisms underlying variable response. Such screens can be performed on cell lines and short-term cultures of primary cells to take advantage of the respective models' strength, which include, e.g., the ability to silence genes or introduce somatic mutations to cell lines. Cohorts of patient samples represent the natural diversity of cancers, including rarer mutations and combinatorial patterns of mutations that are often absent from existing cell lines. We here summarize a simple and scalable method for the measurement of viability after drug exposure based on ATP measurements as a surrogate for viability, which we use to measure and understand drug response in cell lines and primary cells.

Single-cell transcriptional mapping reveals genetic and non-genetic determinants of aberrant differentiation in AML

In acute myeloid leukemia (AML), genetic mutations distort hematopoietic differentiation, resulting in the accumulation of leukemic blasts. Yet, it remains unclear how these mutations intersect with cellular origins and whether they converge upon similar differentiation patterns. Single-cell RNA sequencing (scRNA-seq) has enabled high-resolution mapping of the relationship between leukemia and normal cell states, yet this application is hampered by imprecise reference maps of normal hematopoiesis and small sample sizes among patient cohorts. As a first step we constructed a reference atlas of human bone marrow hematopoiesis from 263,519 single-cell transcriptomes spanning 55 cellular states, that was benchmarked against independent datasets of immunophenotypically pure hematopoietic stem and progenitor cells. Using this reference atlas, we mapped over 1.2 million single-cell transcriptomes spanning 318 AML, mixed phenotype acute leukemia (MPAL), and acute erythroid leukemia (AEL) samples. This large-scale analysis, together with systematic mapping of genotype-to-phenotype associations between driver mutations and differentiation landscapes, revealed convergence of diverse genetic alterations on twelve recurrent patterns of aberrant differentiation in AML. This included unconventional lymphoid and erythroid priming linked to RUNX1 and TP53 mutations, respectively. We also identified non-genetic determinants of AML differentiation such as two subgroups of KMT2A-rearranged AML that differ in the identity of their leukemic stem cells (LSCs), likely reflecting distinct cellular origins. Furthermore, distinct LSC-driven hierarchies can co-exist within individual patients, providing insights into AML evolution. Together, precise mapping of normal and malignant cell states provides a framework for advancing the study and disease classification of hematologic malignancies thereby informing therapy development.

FLT3 targeting in the modern era: from clonal selection to combination therapies

Fms-like tyrosine kinase 3 (FLT3) is the most frequently mutated gene in acute myeloid leukemia (AML). Modern targeting of FLT3 with inhibitors has improved clinical outcomes and FLT3 inhibitors have been incorporated into the treatment of AML in all phases of the disease, including the upfront, relapsed/refractory and maintenance settings. This review will discuss the current understanding of FLT3 biology, the clinical use of FLT3 inhibitors, resistance mechanisms and emerging combination treatment strategies.

Cohesin mutations in acute myeloid leukemia

The cohesin complex, encoded by SMC3, SMC1A, RAD21, and STAG2, is a critical regulator of DNA-looping and gene expression. Over a decade has passed since recurrent mutations affecting cohesin subunits were first identified in myeloid malignancies such as Acute Myeloid Leukemia (AML). Since that time there has been tremendous progress in our understanding of chromatin structure and cohesin biology, but critical questions remain because of the multiple critical functions the cohesin complex is responsible for. Recent findings have been particularly noteworthy with the identification of crosstalk between DNA-looping and chromatin domains, a deeper understanding of how cohesin establishes sister chromatid cohesion, a renewed interest in cohesin's role for DNA damage response, and work demonstrating cohesin's importance for Polycomb repression. Despite these exciting findings, the role of cohesin in normal hematopoiesis, and the precise mechanisms by which cohesin mutations promote cancer, remain poorly understood. This review discusses what is known about the role of cohesin in normal hematopoiesis, and how recent findings could shed light on the mechanisms through which cohesin mutations promote leukemic transformation. Important unanswered questions in the field, such as whether cohesin plays a role in HSC heterogeneity, and the mechanisms by which it regulates gene expression at a molecular level, will also be discussed. Particular attention will be given to the potential therapeutic vulnerabilities of leukemic cells with cohesin subunit mutations.

Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia

Deep single-cell multi-omic profiling offers a promising approach to understand and overcome drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML). Here, we combine single-cell ex vivo drug profiling (pharmacoscopy) with single-cell and bulk DNA, RNA, and protein analyses, alongside clinical data from 21 rrAML patients. Unsupervised data integration reveals reduced ex vivo response to the Bcl-2 inhibitor venetoclax (VEN) in patients treated with both a hypomethylating agent (HMA) and VEN, compared to those pre-exposed to chemotherapy or HMA alone. Integrative analysis identifies both known and unreported mechanisms of innate and treatment-related VEN resistance and suggests alternative treatments, like targeting increased proliferation with the PLK inhibitor volasertib. Additionally, high CD36 expression in VEN-resistant blasts associates with sensitivity to CD36-targeted antibody treatment ex vivo. This study demonstrates how single-cell multi-omic profiling can uncover drug resistance mechanisms and treatment vulnerabilities, providing a valuable resource for future AML research.

The present and future of the Cancer Dependency Map

Despite tremendous progress in the past decade, the complex and heterogeneous nature of cancer complicates efforts to identify new therapies and therapeutic combinations that achieve durable responses in most patients. Further advances in cancer therapy will rely, in part, on the development of targeted therapeutics matched with the genetic and molecular characteristics of cancer. The Cancer Dependency Map (DepMap) is a large-scale data repository and research platform, aiming to systematically reveal the landscape of cancer vulnerabilities in thousands of genetically and molecularly annotated cancer models. DepMap is used routinely by cancer researchers and translational scientists and has facilitated the identification of several novel and selective therapeutic strategies for multiple cancer types that are being tested in the clinic. However, it is also clear that the current version of DepMap is not yet comprehensive. In this Perspective, we review (1) the impact and current uses of DepMap, (2) the opportunities to enhance DepMap to overcome its current limitations, and (3) the ongoing efforts to further improve and expand DepMap.

CRISPR Dependency Screens in Primary Hematopoietic Stem Cells Identify KDM3B as a Genotype-specific Vulnerability in IDH2- and TET2-mutant Cells

Clonal hematopoiesis (CH) is a common premalignant state in the blood and confers an increased risk of blood cancers and all-cause mortality. Identification of therapeutic targets in CH has been hindered by the lack of an ex vivo platform amenable for studying primary hematopoietic stem and progenitor cells (HSPCs). Here, we utilize an ex vivo co-culture system of HSPCs with bone marrow endothelial cells to perform CRISPR/Cas9 screens in mutant HSPCs. Our data reveal that loss of the histone demethylase family members Kdm3b and Jmjd1c specifically reduces the fitness of Idh2- and Tet2-mutant HSPCs. Kdm3b loss in mutant cells leads to decreased expression of critical cytokine receptors including Mpl, rendering mutant HSPCs preferentially susceptible to inhibition of downstream JAK2 signaling. Our study nominates an epigenetic regulator and an epigenetically regulated receptor signaling pathway as genotype-specific therapeutic targets and provides a scalable platform to identify genetic dependencies in mutant HSPCs. Significance: Given the broad prevalence, comorbidities, and risk of malignant transformation associated with CH, there is an unmet need to identify therapeutic targets. We develop an ex vivo platform to perform CRISPR/Cas9 screens in primary HSPCs. We identify KDM3B and downstream signaling components as genotype-specific dependencies in CH and myeloid malignancies. See related commentary by Khabusheva and Goodell, p. 1768.

Multiomic profiling identifies predictors of survival in African American patients with acute myeloid leukemia

Genomic profiles and prognostic biomarkers in patients with acute myeloid leukemia (AML) from ancestry-diverse populations are underexplored. We analyzed the exomes and transcriptomes of 100 patients with AML with genomically confirmed African ancestry (Black; Alliance) and compared their somatic mutation frequencies with those of 323 self-reported white patients with AML, 55% of whom had genomically confirmed European ancestry (white; BeatAML). Here we find that 73% of 162 gene mutations recurrent in Black patients, including a hitherto unreported PHIP alteration detected in 7% of patients, were found in one white patient or not detected. Black patients with myelodysplasia-related AML were younger than white patients suggesting intrinsic and/or extrinsic dysplasia-causing stressors. On multivariable analyses of Black patients, NPM1 and NRAS mutations were associated with inferior disease-free and IDH1 and IDH2 mutations with reduced overall survival. Inflammatory profiles, cell type distributions and transcriptional profiles differed between Black and white patients with NPM1 mutations. Incorporation of ancestry-specific risk markers into the 2022 European LeukemiaNet genetic risk stratification changed risk group assignment for one-third of Black patients and improved their outcome prediction.

Multi-omic analysis of longitudinal acute myeloid leukemia patient samples reveals potential prognostic markers linked to disease progression

Relapse remains a determinant of treatment failure and contributes significantly to mortality in acute myeloid leukemia (AML) patients. Despite efforts to understand AML progression and relapse mechanisms, findings on acquired gene mutations in relapse vary, suggesting inherent genetic heterogeneity and emphasizing the role of epigenetic modifications. We conducted a multi-omic analysis using Omni-C, ATAC-seq, and RNA-seq on longitudinal samples from two adult AML patients at diagnosis and relapse. Herein, we characterized genetic and epigenetic changes in AML progression to elucidate the underlying mechanisms of relapse. Differential interaction analysis showed significant 3D chromatin landscape reorganization between relapse and diagnosis samples. Comparing global open chromatin profiles revealed that relapse samples had significantly fewer accessible chromatin regions than diagnosis samples. In addition, we discovered that relapse-related upregulation was achieved either by forming new active enhancer contacts or by losing interactions with poised enhancers/potential silencers. Altogether, our study highlights the impact of genetic and epigenetic changes on AML progression, underlining the importance of multi-omic approaches in understanding disease relapse mechanisms and guiding potential therapeutic interventions.

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

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

Knowledge graphs facilitate prediction of drug response for acute myeloid leukemia

Acute myeloid leukemia (AML) is a highly aggressive and heterogeneous disease, underscoring the need for improved therapeutic options and methods to optimally predict responses. With the wealth of available data resources, including clinical features, multiomics analysis, and ex vivo drug screening from AML patients, development of drug response prediction models has become feasible. Knowledge graphs (KGs) embed the relationships between different entities or features, allowing for explanation of a wide breadth of drug sensitivity and resistance mechanisms. We designed AML drug response prediction models guided by KGs. Our models included engineered features, relative gene expression between marker genes for each drug and regulators (e.g., transcription factors). We identified relative gene expression of FGD4-MIR4519, NPC2-GATA2, and BCL2-NFKB2 as predictive features for venetoclax ex vivo drug response. The KG-guided models provided high accuracy in independent test sets, overcame potential platform batch effects, and provided candidate drug sensitivity biomarkers for further validation.

Merging logical models: An application in Acute Myeloid Leukemia modeling

Gene regulatory network (GRNs) models provide mechanistic understanding of the gene regulations and interactions that control various aspects of cellular behaviors. While researchers have constructed GRNs to model specific sets of gene regulations or interactions, little work has been made to integrate or merge these models into larger, more comprehensive ones that could encompass more genes, and improve the accuracy of predicting biological processes. Here, we present a workflow for merging logical GRN models, which requires sequential steps including model standardization, reproducing, merging and evaluations, and demonstrate its application in acute myeloid leukemia (AML) study. We demonstrate the feasibility and benefits of model merging by integrating two pairs of published models. Our integrated models were able to retain similar accuracy of the original publications, while increasing the coverage and explainability of the biological system. This approach highlights the integration of logical models in advancing system biology and enhancing the understanding of complex diseases.

Multiomic single cell sequencing identifies stemlike nature of mixed phenotype acute leukemia

Despite recent work linking mixed phenotype acute leukemia (MPAL) to certain genetic lesions, specific driver mutations remain undefined for a significant proportion of patients and no genetic subtype is predictive of clinical outcomes. Moreover, therapeutic strategy for MPAL remains unclear, and prognosis is overall poor. We performed multiomic single cell profiling of 14 newly diagnosed adult MPAL patients to characterize the inter- and intra-tumoral transcriptional, immunophenotypic, and genetic landscapes of MPAL. We show that neither genetic profile nor transcriptome reliably correlate with specific MPAL immunophenotypes. Despite this, we find that MPAL blasts express a shared stem cell-like transcriptional profile indicative of high differentiation potential. Patients with the highest differentiation potential demonstrate inferior survival in our dataset. A gene set score, MPAL95, derived from genes highly enriched in the most stem-like MPAL cells, is applicable to bulk RNA sequencing data and is predictive of survival in an independent patient cohort, suggesting a potential strategy for clinical risk stratification.

Combining clinical and molecular data for personalized treatment in acute myeloid leukemia: A machine learning approach

BACKGROUND AND OBJECTIVE

The standard of care in Acute Myeloid Leukemia patients has remained essentially unchanged for nearly 40 years. Due to the complicated mutational patterns within and between individual patients and a lack of targeted agents for most mutational events, implementing individualized treatment for AML has proven difficult. We reanalysed the BeatAML dataset employing Machine Learning algorithms. The BeatAML project entails patients extensively characterized at the molecular and clinical levels and linked to drug sensitivity outputs. Our approach capitalizes on the molecular and clinical data provided by the BeatAML dataset to predict the ex vivo drug sensitivity for the 122 drugs evaluated by the project.

METHODS

We utilized ElasticNet, which produces fully interpretable models, in combination with a two-step training protocol that allowed us to narrow down computations. We automated the genes' filtering step by employing two metrics, and we evaluated all possible data combinations to identify the best training configuration settings per drug.

RESULTS

We report a Pearson correlation across all drugs of 0.36 when clinical and RNA sequencing data were combined, with the best-performing models reaching a Pearson correlation of 0.67. When we trained using the datasets in isolation, we noted that RNA Sequencing data (Pearson: 0.36) attained three times the predictive power of whole exome sequencing data (Pearson: 0.11), with clinical data falling somewhere in between (Pearson 0.26). Lastly, we present a paradigm of clinical significance. We used our models' prediction as a drug sensitivity score to rank an individual's expected response to treatment. We identified 78 patients out of 89 (88 %) that the proposed drug was more potent than the administered one based on their ex vivo drug sensitivity data.

CONCLUSIONS

In conclusion, our reanalysis of the BeatAML dataset using Machine Learning algorithms demonstrates the potential for individualized treatment prediction in Acute Myeloid Leukemia patients, addressing the longstanding challenge of treatment personalization in this disease. By leveraging molecular and clinical data, our approach yields promising correlations between predicted drug sensitivity and actual responses, highlighting a significant step forward in improving therapeutic outcomes for AML patients.

CD8+ T-cell differentiation and dysfunction inform treatment response in acute myeloid leukemia

ABSTRACT

The interplay between T-cell states of differentiation, dysfunction, and treatment response in acute myeloid leukemia (AML) remains unclear. Here, we leveraged a multimodal approach encompassing high-dimensional flow cytometry and single-cell transcriptomics and found that early memory CD8+ T cells are associated with therapy response and exhibit a bifurcation into 2 distinct terminal end states. One state is enriched for markers of activation, whereas the other expresses natural killer (NK)-like and senescence markers. The skewed clonal differentiation trajectory toward CD8+ senescence was also a hallmark indicative of therapy resistance. We validated these findings by generating an AML CD8+ single-cell atlas integrating our data and other independent data sets. Finally, our analysis revealed that an imbalance between CD8+ early memory and senescent-like cells is linked to AML treatment refractoriness and poor survival. Our study provides crucial insights into the dynamics of CD8+ T-cell differentiation and advances our understanding of CD8+ T-cell dysfunction in AML.

New frameworks for hematopoiesis derived from single-cell genomics

ABSTRACT

Recent advancements in single-cell genomics have enriched our understanding of hematopoiesis, providing intricate details about hematopoietic stem cell biology, differentiation, and lineage commitment. Technological advancements have highlighted extensive heterogeneity of cell populations and continuity of differentiation routes. Nevertheless, intermediate "attractor" states signify structure in stem and progenitor populations that link state transition dynamics to fate potential. We discuss how innovative model systems quantify lineage bias and how stress accelerates differentiation, thereby reducing fate plasticity compared with native hematopoiesis. We conclude by offering our perspective on the current model of hematopoiesis and discuss how a more precise understanding can translate to strategies that extend healthy hematopoiesis and prevent disease.

Deciphering genetic and nongenetic factors underlying tumour dormancy: insights from multiomics analysis of two syngeneic MRD models of melanoma and leukemia

BACKGROUND

Tumour dormancy, a resistance mechanism employed by cancer cells, is a significant challenge in cancer treatment, contributing to minimal residual disease (MRD) and potential relapse. Despite its clinical importance, the mechanisms underlying tumour dormancy and MRD remain unclear. In this study, we employed two syngeneic murine models of myeloid leukemia and melanoma to investigate the genetic, epigenetic, transcriptomic and protein signatures associated with tumour dormancy. We used a multiomics approach to elucidate the molecular mechanisms driving MRD and identify potential therapeutic targets.

RESULTS

We conducted an in-depth omics analysis encompassing whole-exome sequencing (WES), copy number variation (CNV) analysis, chromatin immunoprecipitation followed by sequencing (ChIP-seq), transcriptome and proteome investigations. WES analysis revealed a modest overlap of gene mutations between melanoma and leukemia dormancy models, with a significant number of mutated genes found exclusively in dormant cells. These exclusive genetic signatures suggest selective pressure during MRD, potentially conferring resistance to the microenvironment or therapies. CNV, histone marks and transcriptomic gene expression signatures combined with Gene Ontology (GO) enrichment analysis highlighted the potential functional roles of the mutated genes, providing insights into the pathways associated with MRD. In addition, we compared "murine MRD genes" profiles to the corresponding human disease through public datasets and highlighted common features according to disease progression. Proteomic analysis combined with multi-omics genetic investigations, revealed a dysregulated proteins signature in dormant cells with minimal genetic mechanism involvement. Pathway enrichment analysis revealed the metabolic, differentiation and cytoskeletal remodeling processes involved in MRD. Finally, we identified 11 common proteins differentially expressed in dormant cells from both pathologies.

CONCLUSIONS

Our study underscores the complexity of tumour dormancy, implicating both genetic and nongenetic factors. By comparing genomic, transcriptomic, proteomic, and epigenomic datasets, our study provides a comprehensive understanding of the molecular landscape of minimal residual disease. These results provide a robust foundation for forthcoming investigations and offer potential avenues for the advancement of targeted MRD therapies in leukemia and melanoma patients, emphasizing the importance of considering both genetic and nongenetic factors in treatment strategies.

Altered RNA export by SF3B1 mutants confers sensitivity to nuclear export inhibition

SF3B1 mutations frequently occur in cancer yet lack targeted therapies. Clinical trials of XPO1 inhibitors, selinexor and eltanexor, in high-risk myelodysplastic neoplasms (MDS) revealed responders were enriched with SF3B1 mutations. Given that XPO1 (Exportin-1) is a nuclear exporter responsible for the export of proteins and multiple RNA species, this led to the hypothesis that SF3B1-mutant cells are sensitive to XPO1 inhibition, potentially due to altered splicing. Subsequent RNA sequencing after XPO1 inhibition in SF3B1 wildtype and mutant cells showed increased nuclear retention of RNA transcripts and increased alternative splicing in the SF3B1 mutant cells particularly of genes that impact apoptotic pathways. To identify novel drug combinations that synergize with XPO1 inhibition, a forward genetic screen was performed with eltanexor treatment implicating anti-apoptotic targets BCL2 and BCLXL, which were validated by functional testing in vitro and in vivo. These targets were tested in vivo using Sf3b1K700E conditional knock-in mice, which showed that the combination of eltanexor and venetoclax (BCL2 inhibitor) had a preferential sensitivity for SF3B1 mutant cells without excessive toxicity. In this study, we unveil the mechanisms underlying sensitization to XPO1 inhibition in SF3B1-mutant MDS and preclinically rationalize the combination of eltanexor and venetoclax for high-risk MDS.

Early drivers of clonal hematopoiesis shape the evolutionary trajectories of de novo acute myeloid leukemia

Mutations commonly found in AML such as DNMT3A, TET2 and ASXL1 can be found in the peripheral blood of otherwise healthy adults - a phenomenon referred to as clonal hematopoiesis (CH). These mutations are thought to represent the earliest genetic events in the evolution of AML. Genomic studies on samples acquired at diagnosis, remission, and at relapse have demonstrated significant stability of CH mutations following induction chemotherapy. Meanwhile, later mutations in genes such as NPM1 and FLT3, have been shown to contract at remission and in the case of FLT3 often are absent at relapse. We sought to understand how early CH mutations influence subsequent evolutionary trajectories throughout remission and relapse in response to induction chemotherapy. Here, we assembled a retrospective cohort of patients diagnosed with de novo AML at our institution that underwent genomic sequencing at diagnosis as well as at the time of remission and/or relapse (total n = 182 patients). Corroborating prior studies, FLT3 and NPM1 mutations were generally eliminated at the time of cytologic complete remission but subsequently reemerged upon relapse, whereas DNMT3A, TET2 and ASXL1 mutations often persisted through remission. Early CH-related mutations exhibited distinct constellations of co-occurring genetic alterations, with NPM1 and FLT3 mutations enriched in DNMT3A mut AML, while CBL and SRSF2 mutations were enriched in TET2 mut and ASXL1 mut AML, respectively. In the case of NPM1 and FLT3 mutations, these differences vanished at the time of complete remission yet readily reemerged upon relapse, indicating the reproducible nature of these genetic interactions. Thus, early CH-associated mutations that precede malignant transformation subsequently shape the evolutionary trajectories of AML through diagnosis, therapy, and relapse.

PHF6 suppresses self-renewal of leukemic stem cells in AML

Acute myeloid leukemia is characterized by uncontrolled proliferation of self-renewing myeloid progenitors accompanied by a differentiation arrest. PHF6 is a chromatin-binding protein mutated in myeloid leukemias, and its isolated loss increases mouse HSC self-renewal without malignant transformation. We report here that Phf6 knockout increases the aggressiveness of Hoxa9-driven AML over serial transplantation, and increases the frequency of leukemia initiating cells. We define the in vivo hierarchy of Hoxa9-driven AML and identify a population that we term the "LIC-e" (leukemia initiating cells enriched) population. We find that Phf6 loss expands the LIC-e population and skews its transcriptome to a more stem-like state; concordant transcriptome shifts are also observed on PHF6 knockout in a human AML cell line and in PHF6 mutant patient samples from the BEAT AML dataset. We demonstrate that LIC-e accumulation in Phf6 knockout AML occurs not due to effects on cell cycle or apoptosis, but due to an increase in the fraction of its progeny that retain LIC-e identity. Our work indicates that Phf6 loss increases AML self-renewal through context-specific effects on leukemia stem cells.

CRISPR screen of venetoclax response-associated genes identifies transcription factor ZNF740 as a key functional regulator

BCL-2 inhibitors such as venetoclax offer therapeutic promise in acute myeloid leukemia (AML) and other cancers, but drug resistance poses a significant challenge. It is crucial to understand the mechanisms that regulate venetoclax response. While correlative studies have identified numerous genes linked to venetoclax sensitivity, their direct impact on the drug response remains unclear. In this study, we targeted around 1400 genes upregulated in venetoclax-sensitive primary AML samples and carried out a CRISPR knockout screen to evaluate their direct effects on venetoclax response. Our screen identified the transcription factor ZNF740 as a critical regulator, with its expression consistently predicting venetoclax sensitivity across subtypes of the FAB classification. ZNF740 depletion leads to increased resistance to ventoclax, while its overexpression enhances sensitivity to the drug. Mechanistically, our integrative transcriptomic and genomic analysis identifies NOXA as a direct target of ZNF740, which negatively regulates MCL-1 protein stability. Loss of ZNF740 downregulates NOXA and increases the steady state protein levels of MCL-1 in AML cells. Restoring NOXA expression in ZNF740-depleted cells re-sensitizes AML cells to venetoclax treatment. Furthermore, we demonstrated that dual targeting of MCL-1 and BCL-2 effectively treats ZNF740-deficient AML in vivo. Together, our work systematically elucidates the causal relationship between venetoclax response signature genes and establishes ZNF740 as a novel transcription factor regulating venetoclax sensitivity.

The Lactate Receptor GPR81 is a Mechanism of Leukemia-Associated Macrophage Polarization in the Bone Marrow Microenvironment

Interactions between acute myeloid leukemia (AML) and the bone marrow microenvironment (BMME) are critical to leukemia progression and chemoresistance. Altered metabolite levels in the tumor microenvironment contribute to immunosuppression in solid tumors, while this has not been studied yet in the leukemic BMME. Metabolomics of AML patient bone marrow serum detected elevated metabolites, including lactate, compared to age- and sex-matched controls. Excess lactate has been implicated in solid tumors for inducing suppressive tumor-associated macrophages (TAMs) and correlates with poor prognosis. We describe the role of lactate in the polarization of leukemia-associated macrophages (LAMs) using a murine model of blast crisis chronic myelogenous leukemia (bcCML) and mice genetically lacking the lactate receptor GPR81. LAMs were CD206hi and suppressive in transcriptomics and cytokine profiling. Yet, LAMs had a largely unique expression profile from other types of TAMs. We demonstrate GPR81 signaling as a mechanism of both LAM polarization and the direct support of leukemia cell growth and self-repopulation. Furthermore, LAMs and elevated lactate diminished the function of hematopoietic progenitors and stromal support, while knockout of GPR81 had modest protective effects on the hematopoietic system. We report microenvironmental lactate as a critical driver of AML-induced immunosuppression and leukemic progression, thus identifying GPR81 signaling as an exciting and novel therapeutic target for treating this devastating disease.

LOXL2-induced PEAR1 Ser891 phosphorylation suppresses CD44 degradation and promotes triple-negative breast cancer metastasis

CD44 is associated with a high risk of metastasis, recurrence, and drug resistance in various cancers. Here we report that platelet endothelial aggregation receptor 1 (PEAR1) is a CD44 chaperone protein that protected CD44 from endocytosis-mediated degradation and enhances cleavage of the CD44 intracellular domain (CD44-ICD). Furthermore, we found that lysyl oxidase-like protein 2 (LOXL2), an endogenous ligand of PEAR1, bound to the PEAR1-EMI domain and facilitated the interaction between PEAR1 and CD44 by inducing PEAR1 Ser891 phosphorylation in a manner that was independent of its enzyme activity. Levels of PEAR1 protein and PEAR1 phosphorylation at Ser891 were increased in patients with triple-negative breast cancer (TNBC), were positively correlated with expression of LOXL2 and CD44, and were negatively correlated with overall survival. The level of PEAR1 Ser891 phosphorylation was identified as the best independent prognostic factor in TNBC patients. The prognostic efficacy of the combination of PEAR1 phosphorylation at Ser891 and CD44 expression was superior to that of PEAR1 phosphorylation at Ser891 alone. Blocking the interaction between LOXL2 and PEAR1 with monoclonal antibodies significantly inhibited TNBC metastasis, representing a promising therapeutic strategy for TNBC.

Similarities and differences of bone marrow and peripheral blood samples from acute myeloid leukemia patients in terms of cellular heterogeneity and ex-vivo drug sensitivity

Background

Bone marrow (BM) evaluation is the de facto standard for diagnosis, molecular analysis, risk stratification, and therapy response assessment in acute myeloid leukemia (AML), but in patients with a high number of circulating blast cells, the peripheral blood (PB) sample could provide similar information as BM. However, there is no large-scale molecular study comparing the two specimens in terms of their gene expression profiles, cellular heterogeneities, and ex-vivo drug sensitivity.

Methodology

We used (i) the BEAT-AML cohort each with detailed molecular data; (ii) cell-type deconvolution to estimate leukemic and immune cell proportions between specimen types; (iii) differential expression (DE) and drug-cell type association analysis; and (iv) logistic regression models to assess the association between induction therapy response, cell-type composition and first-line drug treatment.

Results

Results: We identified 207 patients having BM and 116 patients having PB samples. There was a total of 1271 DE genes (false discovery rate < 0.05) between BM and PB; the top enriched pathways in terms of DE genes belong to the immune system pathways. Aggregated ex-vivo drug response profiles from the two specimens were largely similar, as were the cellular components, except for the GMP-like cell type (17% in BM vs. 5% in PB, p-value = 2 × 10-7). Among the specimen-specific results, the GMP-like subtype was associated with multiple drug resistance in BM and the ProMono-like subtype in PB. Several cell types were associated with the response to induction therapy, but the impact of specimen type on the interaction of cell type and cytarabine-associated induction therapy was not statistically significant for most cell types.

Results

Conclusions: Even though there are molecular and cellular differences between BM and PB samples, they show many similarities in ex-vivo drug response profiles, indicating the clinical utility of the substantially less-invasive PB samples.

GATA2 deficiency syndrome: A compensatory mechanism gone awry?

In their paper, using zebrafish models, Gioacchino et al. have demonstrated the GATA2 haploinsufficiency, the genetic hallmark of GATA2 deficiency syndrome, promotes erythroid and myeloid cytopenia, and have discovered a self-regulatory mechanism to compensate GATA2 levels and protein function. Commentary on: Gioacchino et al. GATA2 heterozygosity causes an epigenetic feedback mechanism resulting in myeloid and erythroid dysplasia. Br J Haematol 2024;205:580-593.

GATA2 heterozygosity causes an epigenetic feedback mechanism resulting in myeloid and erythroid dysplasia

The transcription factor GATA2 has a pivotal role in haematopoiesis. Heterozygous germline GATA2 mutations result in a syndrome characterized by immunodeficiency, bone marrow failure and predispositions to myelodysplastic syndrome (MDS) and acute myeloid leukaemia. Clinical symptoms in these patients are diverse and mechanisms driving GATA2-related phenotypes are largely unknown. To explore the impact of GATA2 haploinsufficiency on haematopoiesis, we generated a zebrafish model carrying a heterozygous mutation of gata2b (gata2b+/-), an orthologue of GATA2. Morphological analysis revealed myeloid and erythroid dysplasia in gata2b+/- kidney marrow. Because Gata2b could affect both transcription and chromatin accessibility during lineage differentiation, this was assessed by single-cell (sc) RNA-seq and single-nucleus (sn) ATAC-seq. Sn-ATAC-seq showed that the co-accessibility between the transcription start site (TSS) and a -3.5-4.1 kb putative enhancer was more robust in gata2b+/- zebrafish HSPCs compared to wild type, increasing gata2b expression and resulting in higher genome-wide Gata2b motif use in HSPCs. As a result of increased accessibility of the gata2b locus, gata2b+/- chromatin was also more accessible during lineage differentiation. scRNA-seq data revealed myeloid differentiation defects, that is, impaired cell cycle progression, reduced expression of cebpa and cebpb and increased signatures of ribosome biogenesis. These data also revealed a differentiation delay in erythroid progenitors, aberrant proliferative signatures and down-regulation of Gata1a, a master regulator of erythropoiesis, which worsened with age. These findings suggest that cell-intrinsic compensatory mechanisms, needed to obtain normal levels of Gata2b in heterozygous HSPCs to maintain their integrity, result in aberrant lineage differentiation, thereby representing a critical step in the predisposition to MDS.

Machine learning and integrative multi-omics network analysis for survival prediction in acute myeloid leukemia

BACKGROUND

Acute myeloid leukemia (AML) is the most common malignant myeloid disorder in adults and the fifth most common malignancy in children, necessitating advanced technologies for outcome prediction.

METHOD

This study aims to enhance prognostic capabilities in AML by integrating multi-omics data, especially gene expression and methylation, through network-based feature selection methodologies. By employing artificial intelligence and network analysis, we are exploring different methods to build a machine learning model for predicting AML patient survival. We evaluate the effectiveness of combining omics data, identify the most informative method for network integration and compare the performance with standard feature selection methods.

RESULTS

Our findings demonstrate that integrating gene expression and methylation data significantly improves prediction accuracy compared to single omics data. Among network integration methods, our study identifies the best approach that improves informative feature selection for predicting patient outcomes in AML. Comparative analyses demonstrate the superior performance of the proposed network-based methods over standard techniques.

CONCLUSIONS

This research presents an innovative and robust methodology for building a survival prediction model tailored to AML patients. By leveraging multilayer network analysis for feature selection, our approach contributes to improving the understanding and prognostic capabilities in AML and laying the foundation for more effective personalized therapeutic interventions in the future.

Double-crosslinked self-healing hydrogel alleviates osteoarthritis by protecting from wearing and targeting NF-kB signaling

Osteoarthritis (OA) is a chronic disease that causes pain, morbidity, and disability. The main strategy for OA treatment focuses on inflammation suppression, inhibition of osteoclastogenesis, and protection of articular cartilage. These functions cannot be performed effectively by monotherapy. Therefore, an effective drug delivery system is required, capable of containing and controlling the efflux of various drugs to alleviate osteoclastogenesis, protect cartilage and subchondral bone, and suppress inflammation. In this work, an encapsulation system is constructed using a self-healing chitosan hydrogel and allocated compound drugs. The self-healing gel is composed of branched-functionalized chitosan, created by simultaneously using polycaprolactone polyethylene glycol azide as a block polymer and the host-guest assembly of β-cyclodextrin and adamantane. Inhibitors of the NFkB pathway are loaded into the cavities of β-cyclodextrin and the spring-like structure of the block polymer, which can be rapidly released upon joint friction (due to the reassembly of β-cyclodextrin and adamantane by shear stress and the stretch of the block polymer). In vitro experiments using BMMs and the ATDC5 cell line confirm that the developed hydrogel can simultaneously suppress osteoclastogenesis and induce chondrogenesis. Additionally, a model of knee arthritis in C57 mice was used to confirm that this double-crosslinked encapsulation system can lubricate the knee joint surface and provide adequate protection on demand through shear-responsive drug release.

Multi-omics evaluation of the prognostic value and immune signature of FCN1 in pan-cancer and its relationship with proliferation and apoptosis in acute myeloid leukemia

Background

The FCN1 gene encodes the ficolin-1 protein, implicated in the pathogenesis of various diseases, though its precise role in tumorigenesis remains elusive. This study aims to elucidate the prognostic significance, immune signature, and treatment response associated with FCN1 across diverse cancer types.

Methods

Employing multi-omics data, we conducted a comprehensive assessment, encompassing tissue-specific and single-cell-specific expression disparities, pan-cancer expression patterns, epigenetic modifications affecting FCN1 expression, and the immune microenvironment. Our investigation primarily focused on the clinical prognostic attributes, immune profiles, potential molecular mechanisms, and candidate therapeutic agents concerning FCN1 and acute myeloid leukemia (AML). Additionally, in vitro experiments were performed to scrutinize the impact of FCN1 knockdown on cell proliferation, apoptosis, and cell cycle dynamics within the AML cell line U937 and NB4.

Results

FCN1 expression exhibits widespread dysregulation across various cancers. Through both univariate and multivariate Cox regression analyses, FCN1 has been identified as an independent prognostic indicator for AML. Immunological investigations elucidate FCN1's involvement in modulating inflammatory responses within the tumor microenvironment and its correlation with treatment efficacy. Remarkably, the deletion of FCN1 influences the proliferation, apoptosis, and cell cycle dynamics of U937 cells and NB4 cells.

Conclusion

These findings underscore FCN1 as a promising pan-cancer biomarker indicative of macrophage infiltration, intimately linked with the tumor microenvironment and treatment responsiveness, and pivotal for cellular mechanisms within AML cell lines.

Novel insights and therapeutic approaches in secondary AML

Secondary acute myeloid leukemia (sAML) presents as a complex and multifaceted ensemble of disorders, positioning itself as both a challenge and an intriguing frontier within hematologic oncology. Its origins are diverse, stemming from antecedent hematologic conditions, germline predisposing mutations, or the sequelae of cytotoxic therapies, and its development is driven by intricate genetic and epigenetic modifications. This complexity necessitates a diverse array of therapeutic strategies, each meticulously tailored to address the distinctive challenges sAML introduces. Such strategies require a personalized approach, considering the variegated clinical backgrounds of patients and the inherent intricacies of the disease. Allogeneic stem cell transplantation stands as a cornerstone, offering the potential for curative outcomes. This is complemented by the emergence of innovative treatments such as CPX-351, venetoclax, and glasdegib, which have demonstrated promising results in enhancing prognosis. The evolving landscape of sAML treatment underscores the importance of continued research and innovation in the field, aiming not only to improve patient outcomes but also to deepen our understanding of the disease's biological underpinnings, thereby illuminating pathways toward more effective and individualized therapies.

Initiating-clone analysis in patients with acute myeloid leukemia secondary to essential thrombocythemia

Most of essential thrombocythemia (ET) patients have the clone harboring a mutation in one of the JAK2, CALR, or MPL gene, and these clones generally acquire additional mutations at transformation to acute myeloid leukemia (AML). However, the proliferation of triple-negative clones has sometimes been observed at AML transformation. To clarify the clonal evolution of ET to AML, we analyzed paired samples at ET and AML transformation in eight patients. We identified that JAK2-unmutated AML clones proliferated at AML transformation in three patients in whom the JAK2-mutated clone was dominant at ET. In two patients, TET2-mutated, but not JAK2-mutated, clones might be common initiating clones for ET and transformed AML. In a patient with JAK2-mutated ET, SMARCC2, UBR4, and ZNF143, but not JAK2, -mutated clones proliferated at AML transformation. Precise analysis using single-cell sorted CD34+/CD38- fractions suggested that ET clone with JAK2-mutated and AML clone with TP53 mutation was derived from the common clone with these mutations. Although further study is required to clarify the biological significance of SMARCC2, UBR4, and ZNF143 mutations during disease progression of ET and AML transformation, the present results demonstrate the possibility of a common initial clone involved in both ET and transformed AML.

Blockade of the TIGIT-CD155/CD112 axis enhances functionality of NK-92 but not cytokine-induced memory-like NK cells toward CD155-expressing acute myeloid leukemia

TIGIT is an alternative checkpoint receptor (CR) whose inhibition promotes Graft-versus-Leukemia effects of NK cells. Given the significant immune-permissiveness of NK cells circulating in acute myeloid leukemia (AML) patients, we asked whether adoptive transfer of activated NK cells would benefit from additional TIGIT-blockade. Hence, we characterized cytokine-induced memory-like (CIML)-NK cells and NK cell lines for the expression of inhibitory CRs. In addition, we analyzed the transcription of CR ligands in AML patients (CCLE and Beat AML 2.0 cohort) in silico and evaluated the efficacy of CR blockade using in vitro cytotoxicity assays, CD69, CD107a and IFN-γ expression. Alternative but not classical CRs were abundantly expressed on healthy donor NK cells and even further upregulated on CIML-NK cells. In line with our finding that CD155, one important TIGIT-ligand, is reliably expressed on AMLs, we show improved killing of CD155+-AML blasts by NK-92 but interestingly not CIML-NK cells in the presence of TIGIT-blockade. Additionally, our in silico data (n = 671) show that poor prognosis AML patients rather displayed a CD86low CD112/CD155high phenotype, whereas patients with a better outcome rather exhibited a CD86high CD112/CD155low phenotype. Collectively, our data evidence that the complex CR ligand expression profile on AML blasts may be one explanation for the intrinsic NK cell exhaustion observed in AML patients which might be overcome with adoptive NK-92 transfer in combination with TIGIT-blockade.

Mutation order in acute myeloid leukemia identifies uncommon patterns of evolution and illuminates phenotypic heterogeneity

Acute myeloid leukemia (AML) has a poor prognosis and a heterogeneous mutation landscape. Although common mutations are well-studied, little research has characterized how the sequence of mutations relates to clinical features. Using published, single-cell DNA sequencing data from three institutions, we compared clonal evolution patterns in AML to patient characteristics, disease phenotype, and outcomes. Mutation trees, which represent the order of select mutations, were created for 207 patients from targeted panel sequencing data using 1 639 162 cells, 823 mutations, and 275 samples. In 224 distinct orderings of mutated genes, mutations related to DNA methylation typically preceded those related to cell signaling, but signaling-first cases did occur, and had higher peripheral cell counts, increased signaling mutation homozygosity, and younger patient age. Serial sample analysis suggested that NPM1 and DNA methylation mutations provide an advantage to signaling mutations in AML. Interestingly, WT1 mutation evolution shared features with signaling mutations, such as WT1-early being proliferative and occurring in younger individuals, trends that remained in multivariable regression. Some mutation orderings had a worse prognosis, but this was mediated by unfavorable mutations, not mutation order. These findings add a dimension to the mutation landscape of AML, identifying uncommon patterns of leukemogenesis and shedding light on heterogeneous phenotypes.

Upregulation of HOXA3 by isoform-specific Wilms tumour 1 drives chemotherapy resistance in acute myeloid leukaemia

Upregulation of the Wilms' tumour 1 (WT1) gene is common in acute myeloid leukaemia (AML) and is associated with poor prognosis. WT1 generates 12 primary transcripts through different translation initiation sites and alternative splicing. The short WT1 transcripts express abundantly in primary leukaemia samples. We observed that overexpression of short WT1 transcripts lacking exon 5 with and without the KTS motif (sWT1+/- and sWT1-/-) led to reduced cell growth. However, only sWT1+/- overexpression resulted in decreased CD71 expression, G1 arrest, and cytarabine resistance. Primary AML patient cells with low CD71 expression exhibit resistance to cytarabine, suggesting that CD71 may serve as a potential biomarker for chemotherapy. RNAseq differential expressed gene analysis identified two transcription factors, HOXA3 and GATA2, that are specifically upregulated in sWT1+/- cells, whereas CDKN1A is upregulated in sWT1-/- cells. Overexpression of either HOXA3 or GATA2 reproduced the effects of sWT1+/-, including decreased cell growth, G1 arrest, reduced CD71 expression and cytarabine resistance. HOXA3 expression correlates with chemotherapy response and overall survival in NPM1 mutation-negative leukaemia specimens. Overexpression of HOXA3 leads to drug resistance against a broad spectrum of chemotherapeutic agents. Our results suggest that WT1 regulates cell proliferation and drug sensitivity in an isoform-specific manner.

Impact of monocytic differentiation on acute myeloid leukemia patients treated with venetoclax and hypomethylating agents

INTRODUCTION

Although the combination of venetoclax (VEN) and hypomethylating agents (HMAs) results in impressive efficacy in acute myeloid leukemia (AML), there is still a subset of patients who are refractory. We investigated the outcomes of AML patients with monocytic differentiation who were treated with frontline VEN/HMA.

METHODS

A total of 155 patients with newly diagnosed AML treated with frontline VEN/HMA were enrolled in the study. Monocyte-like AML was identified by flow cytometry with typical expression of monocytic markers, and M5 was identified according to French, American, and British category. We compared the outcomes of patients with different characteristics.

RESULTS

The rate of complete remission (CR) and CR with incomplete recovery of blood counts (CRi), progression-free survival (PFS), and overall survival (OS) in monocyte-like AML were inferior to those in nonmonocyte-like AML (CR/CRi rates, 26.7% vs. 80.0%, p < 0.001; median PFS, 2.1 vs. 8.8 months, p < 0.001; median OS, 9.2 vs. 19 months, p = 0.013). CR/CRi rate in M5 was lower than that in non-M5 (60.7% vs. 75.5%, p = 0.049). Multivariate analyses showed that monocyte-like AML was associated with lower odds of CR/CRi and higher risk of progression.

CONCLUSION

Our study suggested that newly diagnosed AML with a monocytic immunophenotype had a poor prognosis with VEN/HMA treatment.

Comprehensive analysis of the HCK gene in myeloid neoplasms: Insights into biological functions, prognosis, and response to antineoplastic agents

Myeloid neoplasms result from molecular alterations in hematopoietic stem cells, with acute myeloid leukemia (AML) being one of the most aggressive and with a poor prognosis. Hematopoietic cell kinase (HCK) is a proto-oncogene that encodes a protein-tyrosine kinase of the Scr family, and it is highly expressed in AML. The present study investigated HCK expression in normal hematopoietic cells across myeloid differentiation stages and myeloid neoplasm patients. Within the AML cohort, we explored the impact of HCK expression on clinical outcomes and its correlation with clinical, genetic, and laboratory characteristics. Furthermore, we evaluated the association between HCK expression and the response to antineoplastic agents using ex vivo assay data from AML patients. HCK expression is higher in differentiated subpopulations of myeloid cells. High HCK expression was observed in patients with chronic myelomonocytic leukemia, chronic myeloid leukemia, and AML. In patients with AML, high levels of HCK negatively impacted overall and disease-free survival. High HCK expression was also associated with worse molecular risk groups and white blood cell count; however, it was not an independent prognostic factor. In functional genomic analyses, high HCK expression was associated with several biological and molecular processes relevant to leukemogenesis. HCK expression was also associated with sensitivity and resistance to several drugs currently used in the clinic. In conclusion, our analysis confirmed the differential expression of HCK in myeloid neoplasms and its potential association with unfavorable molecular risks in AML. We also provide new insights into HCK biological functions, prognosis, and response to antineoplastic agents.

NAD metabolism-related genes provide prognostic value and potential therapeutic insights for acute myeloid leukemia

Introduction

Acute myeloid leukemia (AML) is an aggressive blood cancer with high heterogeneity and poor prognosis. Although the metabolic reprogramming of nicotinamide adenine dinucleotide (NAD) has been reported to play a pivotal role in the pathogenesis of acute myeloid leukemia (AML), the prognostic value of NAD metabolism and its correlation with the immune microenvironment in AML remains unclear.

Methods

We utilized our large-scale RNA-seq data on 655 patients with AML and the NAD metabolism-related genes to establish a prognostic NAD metabolism score based on the sparse regression analysis. The signature was validated across three independent datasets including a total of 1,215 AML patients. ssGSEA and ESTIMATE algorithms were employed to dissect the tumor immune microenvironment. Ex vivo drug screening and in vitro experimental validation were performed to identify potential therapeutic approaches for the high-risk patients. In vitro knockdown and functional experiments were employed to investigate the role of SLC25A51, a mitochondrial NAD+ transporter gene implicated in the signature.

Results

An 8-gene NAD metabolism signature (NADM8) was generated and demonstrated a robust prognostic value in more than 1,800 patients with AML. High NADM8 score could efficiently discriminate AML patients with adverse clinical characteristics and genetic lesions and serve as an independent factor predicting a poor prognosis. Immune microenvironment analysis revealed significant enrichment of distinct tumor-infiltrating immune cells and activation of immune checkpoints in patients with high NADM8 scores, acting as a potential biomarker for immune response evaluation in AML. Furthermore, ex vivo drug screening and in vitro experimental validation in a panel of 9 AML cell lines demonstrated that the patients with high NADM8 scores were more sensitive to the PI3K inhibitor, GDC-0914. Finally, functional experiments also substantiated the critical pathogenic role of the SLC25A51 in AML, which could be a promising therapeutic target.

Conclusion

Our study demonstrated that NAD metabolism-related signature can facilitate risk stratification and prognosis prediction in AML and guide therapeutic decisions including both immunotherapy and targeted therapies.

In vivo Targeting MEK and TNK2/SRC pathways in PTPN11 driven leukemia

PTPN11 encodes for a tyrosine phosphatase implicated in the pathogenesis of hematologic malignancies such as Juvenile Myelomonocytic Leukemia (JMML), Acute Myeloid Leukemia (AML), and Acute Lymphoblastic Leukemia (ALL). Since activating mutations of PTPN11 increase proliferative signaling and cell survival through the RAS/MAPK proliferative pathway there is significant interest in using MEK inhibitors for clinical benefit. Yet, single agent clinical activity has been minimal. Previously, we showed that PTPN11 is further activated by upstream tyrosine kinases TNK2/SRC, and that PTPN11-mutant JMML and AML cells are sensitive to TNK2 inhibition using dasatinib. In order to validate these findings, we adopted a genetically engineered mouse model of PTPN11 driven leukemia using the mouse strain 129S/Sv- Ptpn11 tm6Bgn /Mmucd crossed with B6.129P2- Lyz2 tm1(cre)Ifo /J. The F1 progeny expressing Ptpn11 D61Y within hematopoietic cells destined along the granulocyte-monocyte progenitor lineage developed a fatal myeloproliferative disorder characterized by neutrophilia and monocytosis, and infiltration of myeloid cells into the liver and spleen. Cohorts of Ptpn11 D61Y expressing animals treated with combination of dasatinib and trametinib for an extended period of time was well tolerated and had a significant effect in mitigating disease parameters compared to single agents. Finally, a primary patient-derived xenograft model using a myeloid leukemia with PTPN11 F71L also displayed improved disease response to combination. Collectively, these studies point to combined therapies targeting MEK and TNK2/SRC as a promising therapeutic potential for PTPN11-mutant leukemias.

Key Points

Combining MEK and TNK2/SRC inhibitors has therapeutic potential in PTPN11 mutant JMML and AML.

Mutation Patterns Predict Drug Sensitivity in Acute Myeloid Leukemia

PURPOSE

The inherent genetic heterogeneity of acute myeloid leukemia (AML) has challenged the development of precise and effective therapies. The objective of this study was to elucidate the genomic basis of drug resistance or sensitivity, identify signatures for drug response prediction, and provide resources to the research community.

EXPERIMENTAL DESIGN

We performed targeted sequencing, high-throughput drug screening, and single-cell genomic profiling on leukemia cell samples derived from patients with AML. Statistical approaches and machine learning models were applied to identify signatures for drug response prediction. We also integrated large public datasets to understand the co-occurring mutation patterns and further investigated the mutation profiles in the single cells. The features revealed in the co-occurring or mutual exclusivity pattern were further subjected to machine learning models.

RESULTS

We detected genetic signatures associated with sensitivity or resistance to specific agents, and identified five co-occurring mutation groups. The application of single-cell genomic sequencing unveiled the co-occurrence of variants at the individual cell level, highlighting the presence of distinct subclones within patients with AML. Using the mutation pattern for drug response prediction demonstrates high accuracy in predicting sensitivity to some drug classes, such as MEK inhibitors for RAS-mutated leukemia.

CONCLUSIONS

Our study highlights the importance of considering the gene mutation patterns for the prediction of drug response in AML. It provides a framework for categorizing patients with AML by mutations that enable drug sensitivity prediction.

Application of omics in the diagnosis, prognosis, and treatment of acute myeloid leukemia

Acute myeloid leukemia (AML) is the most frequent leukemia in adults with a high mortality rate. Current diagnostic criteria and selections of therapeutic strategies are generally based on gene mutations and cytogenetic abnormalities. Chemotherapy, targeted therapies, and hematopoietic stem cell transplantation (HSCT) are the major therapeutic strategies for AML. Two dilemmas in the clinical management of AML are related to its poor prognosis. One is the inaccurate risk stratification at diagnosis, leading to incorrect treatment selections. The other is the frequent resistance to chemotherapy and/or targeted therapies. Genomic features have been the focus of AML studies. However, the DNA-level aberrations do not always predict the expression levels of genes and proteins and the latter is more closely linked to disease phenotypes. With the development of high-throughput sequencing and mass spectrometry technologies, studying downstream effectors including RNA, proteins, and metabolites becomes possible. Transcriptomics can reveal gene expression and regulatory networks, proteomics can discover protein expression and signaling pathways intimately associated with the disease, and metabolomics can reflect precise changes in metabolites during disease progression. Moreover, omics profiling at the single-cell level enables studying cellular components and hierarchies of the AML microenvironment. The abundance of data from different omics layers enables the better risk stratification of AML by identifying prognosis-related biomarkers, and has the prospective application in identifying drug targets, therefore potentially discovering solutions to the two dilemmas. In this review, we summarize the existing AML studies using omics methods, both separately and combined, covering research fields of disease diagnosis, risk stratification, prognosis prediction, chemotherapy, as well as targeted therapy. Finally, we discuss the directions and challenges in the application of multi-omics in precision medicine of AML. Our review may inspire both omics researchers and clinical physicians to study AML from a different angle.

circRNAs as prognostic markers in pediatric acute myeloid leukemia

Circular RNAs (circRNAs) arise from precursor mRNA processing through back-splicing and have been increasingly recognized for their functions in various cancers including acute myeloid leukemia (AML). However, the prognostic implications of circRNA in AML remain unclear. We conducted a comprehensive genome-wide analysis of circRNAs using RNA-seq data in pediatric AML. We revealed a group of circRNAs associated with inferior outcomes, exerting effects on cancer-related pathways. Several of these circRNAs were transcribed directly from genes with established functions in AML, such as circRUNX1, circWHSC1, and circFLT3. Further investigations indicated the increased number of circRNAs and linear RNAs splicing were significantly correlated with inferior clinical outcomes, highlighting the pivotal role of splicing dysregulation. Subsequent analysis identified a group of upregulated RNA binding proteins in AMLs associated with high number of circRNAs, with TROVE2 being a prominent candidate, suggesting their involvement in circRNA associated prognosis. Through the integration of drug sensitivity data, we pinpointed 25 drugs that could target high-risk AMLs characterized by aberrant circRNA transcription. These findings underscore prognostic significance of circRNAs in pediatric AML and offer an alternative perspective for treating high-risk cases in this malignancy.

HLA-DM and HLA-DO interplay for the peptide editing of HLA class II in healthy tissues and leukemia

HLA class II antigen presentation is modulated by the activity of the peptide editor HLA-DM and its antagonist HLA-DO, with their interplay controlling the peptide repertoires presented by normal and malignant cells. The role of these molecules in allogeneic hematopoietic cell transplantation (alloHCT) is poorly investigated. Balanced expression of HLA-DM and HLA-DO can influence the presentation of leukemia-associated antigens and peptides targeted by alloreactive T cells, therefore affecting both anti-leukemia immunity and the potential onset of Graft versus Host Disease. We leveraged on a large collection of bulk and single cell RNA sequencing data, available at different repositories, to comprehensively review the level and distribution of HLA-DM and HLA-DO in different cell types and tissues of the human body. The resulting expression atlas will help future investigations aiming to dissect the dual role of HLA class II peptide editing in alloHCT, and their potential impact on its clinical outcome.

DNA damage response defects in hematologic malignancies: mechanistic insights and therapeutic strategies

ABSTRACT

The DNA damage response (DDR) encompasses the detection and repair of DNA lesions and is fundamental to the maintenance of genome integrity. Germ line DDR alterations underlie hereditary chromosome instability syndromes by promoting the acquisition of pathogenic structural variants in hematopoietic cells, resulting in increased predisposition to hematologic malignancies. Also frequent in hematologic malignancies are somatic mutations of DDR genes, typically arising from replication stress triggered by oncogene activation or deregulated tumor proliferation that provides a selective pressure for DDR loss. These defects impair homology-directed DNA repair or replication stress response, leading to an excessive reliance on error-prone DNA repair mechanisms that results in genomic instability and tumor progression. In hematologic malignancies, loss-of-function DDR alterations confer clonal growth advantage and adverse prognostic impact but may also provide therapeutic opportunities. Selective targeting of functional dependencies arising from these defects could achieve synthetic lethality, a therapeutic concept exemplified by inhibition of poly-(adenosine 5'-diphosphate ribose) polymerase or the ataxia telangiectasia and Rad 3 related-CHK1-WEE1 axis in malignancies harboring the BRCAness phenotype or genetic defects that increase replication stress. Furthermore, the role of DDR defects as a source of tumor immunogenicity, as well as their impact on the cross talk between DDR, inflammation, and tumor immunity are increasingly recognized, thus providing rationale for combining DDR modulation with immune modulation. The nature of the DDR-immune interface and the cellular vulnerabilities conferred by DDR defects may nonetheless be disease-specific and remain incompletely understood in many hematologic malignancies. Their comprehensive elucidation will be critical for optimizing therapeutic strategies to target DDR defects in these diseases.

Comprehensive analysis of immune-related lncRNAs in AML patients uncovers potential therapeutic targets and prognostic biomarkers

Purpose

The objective of this study was to provide theoretically feasible strategies by understanding the relationship between the immune microenvironment and the diagnosis and prognosis of AML patients. To this end, we built a ceRNA network with lncRNAs as the core and analyzed the related lncRNAs in the immune microenvironment by bioinformatics analysis.

Methods

AML transcriptome expression data and immune-related gene sets were obtained from TCGA and ImmPort. Utilizing Pearson correlation analysis, differentially expressed immune-related lncRNAs were identified. Then, the LASSO-Cox regression analysis was performed to generate a risk signature consisting immune-related lncRNAs. Accuracy of signature in predicting patient survival was evaluated using univariate and multivariate analysis. Next, GO and KEGG gene enrichment and ssGSEA were carried out for pathway enrichment analysis of 183 differentially expressed genes, followed by drug sensitivity and immune infiltration analysis with pRRophetic and CIBERSORT, respectively. Cytoscape was used to construct the ceRNA network for these lncRNAs.

Results

816 common lncRNAs were selected to acquire the components related to prognosis. The final risk signature established by multivariate Cox and stepwise regression analysis contained 12 lncRNAs engaged in tumor apoptotic and metastatic processes: LINC02595, HCP5, AC020934.2, AC008770.3, LINC01770, AC092718.4, AL589863.1, AC131097.4, AC012368.1, C1RL-AS1, STARD4-AS1, and AC243960.1. Based on this predictive model, high-risk patients exhibited lower overall survival rates than low-risk patients. Signature lncRNAs showed significant correlation with tumor-infiltrating immune cells. In addition, significant differences in PD-1/PD-L1 expression and bleomycin/paclitaxel sensitivity were observed between risk groups.

Conclusion

LncRNAs related to immune microenvironment were prospective prognostic and therapeutic options for AML.