Functional genomic landscape of acute myeloid leukaemia

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.

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.

Driver mutation landscape of acute myeloid leukemia provides insights for neoantigen-based immunotherapy

Acute myeloid leukemia (AML) has lagged in benefiting from immunotherapies, primarily due to the scarcity of actionable AML-specific antigens. Driver mutations represent promising immunogenic targets, but a comprehensive characterization of the AML neoantigen landscape and their impact on patient outcomes and the AML immune microenvironment remain unclear. Herein, we conducted matched DNA and RNA sequencing on 304 AML patients and extensively integrated data from additional ∼2,500 AML cases, identifying 49 driver genes, notably characterized by a significant proportion of insertions and deletions (indels). Neoantigen analysis showed that indels triggered a higher abundance of neoantigens both in quantity and quality compared to single nucleotide variants (SNVs) and gene fusions. By integrating peptide features pertinent to neoantigen presentation and T cell recognition, we developed two robust models of epitope immunogenicity that significantly enriched immunogenic neoepitopes. We validated 30 neoantigens through in vitro direct binding assays of predicted peptides to MHC proteins and confirmed the immunogenicity of 20 neoantigens using interferon-γ ELISpot and tetramer assays. Moreover, we demonstrated that patients with higher neoantigen loads, derived from driver mutations, exhibited poor clinical outcomes and an IFN-driven adaptive immune response, which was associated with immune suppression and tumor evasion. Through deconvolution of large-scale bulk transcriptomes, integration of single-cell RNA sequencing and multiparametric flow cytometry, we confirmed a strong association between neoantigen load and CD8+ T cell exhaustion. This study provides a comprehensive landscape of AML neoantigens derived from driver mutations, offering putative immunogenic targets and emphasizing the need for strategies to revitalize the immunosuppressive milieu.

Landscape of somatic mutations and clonal evolution in NUP98-rearranged adult acute myeloid leukaemia

Acute myeloid leukaemia with NUP98 rearrangement (AML-NUP98) has been previously described in paediatric patients, and the clinical significance in adult AML patients remains largely unexplored. In this study, we identified specific partner fusion genes and examined somatic co-mutations and clonal evolution longitudinally in adult AML-NUP98 patients. Our comprehensive analysis provides an understanding of NUP98 rearrangement and co-mutations influencing clonal evolution and disease progression and offers valuable insights into potential therapeutic strategies. Further multiple centre studies are needed to investigate this entity in adult patients and improve treatment strategy.

lncRNAs maintain the functional phase state of nucleolar prion-like protein to facilitate rRNA processing

Liquid-to-solid phase transition of proteins with prion-like domains (PLDs) has been associated with neurodegenerative diseases and aging. High protein concentration is one important aspect triggering the transition; however, several prion-like proteins, including fibrillarin (FBL), an important phase-separated protein in the nucleolus for pre-rRNA processing, show relatively high expression levels in certain cells, especially cancer cells, without obvious phase transitions and growth arrest. How cells maintain prion-like protein proteostasis is still unknown. Here, we attempt to answer the question, with FBL as an example. We find that lncRNA DNAJC3-AS1 can buffer the behavior of FBL condensation and maintain the state and function of fibrillar component/dense fibrillar component (FC/DFC) units in human cell lines through two mechanisms, not only facilitating FBL condensation but also inhibiting excessive aggregation by binding multiple PLDs and partially blocking their interactions. We propose that lncRNAs could supply buffered systems to sustain functional phase states of prion-like proteins.

LM-Merger: A workflow for merging logical models with an application to gene regulation

Motivation

Gene regulatory network (GRN) models provide mechanistic understanding of genetic interactions that regulate gene expression and, consequently, influence cellular behavior. Dysregulated gene expression plays a critical role in disease progression and treatment response, making GRN models a promising tool for precision medicine. While researchers have built many models to describe specific subsets of gene interactions, more comprehensive models that cover a broader range of genes are challenging to build. This necessitates the development of automated approaches for merging existing models.

Results

We present LM-Merger, a workflow for semi-automatically merging logical GRN models. The workflow consists of five main steps: (a) model identification, (b) model standardization and annotation, (c) model verification, (d) model merging, and (d) model evaluation. We demonstrate the feasibility and benefit of this workflow with two pairs of published models pertaining to acute myeloid leukemia (AML). The integrated models were able to retain the predictive accuracy of the original models, while expanding coverage of the biological system. Notably, when applied to a new dataset, the integrated models outperformed the individual models in predicting patient response. This study highlights the potential of logical model merging to advance systems biology research and our understanding of complex diseases.

Availability and implementation

The workflow and accompanying tools, including modules for model standardization, automated logical model merging, and evaluation, are available at https://github.com/IlyaLab/LogicModelMerger/.

Utilizing insights of DNA repair machinery to discover MMEJ deletions and novel mechanisms

We developed Del-read, an algorithm targeting medium-sized deletions (6-100 bp) in short-reads, which are challenging for current variant callers relying on alignment. Our focus was on Micro-Homolog mediated End Joining deletions (MMEJ-dels), prevalent in myeloid malignancies. MMEJ-dels follow a distinct pattern, occurring between two homologies, allowing us to generate a comprehensive list of MMEJ-dels in the exome. Using Del-read, we identified numerous novel germline and somatic MMEJ-dels in BEAT-AML and TCGA-breast datasets. Validation in 672 healthy individuals confirmed their presence. These novel MMEJ-dels were linked to genomic features associated with replication stress, like G-quadruplexes and minisatellite. Additionally, we observed a new category of MMEJ-dels with an imperfect-match at the flanking sequences of the homologies, suggesting a mechanism involving mispairing in homology alignment. We demonstrated robustness of the repair system despite CRISPR/Cas9-induced mismatches in the homologies. Further analysis of the canonical ASXL1 deletion revealed a diverse array of these imperfect-matches. This suggests a potentially more flexible and error-prone MMEJ repair system than previously understood. Our findings highlight Del-read's potential in uncovering previously undetected deletions and deepen our understanding of repair mechanisms.

Allogeneic hematopoietic stem cell transplantation could overcome the poor prognosis of DNMT3AmutNPM1mutFLT3-ITDmut in acute myeloid leukemia: real-world multicenter analysis in China

The cooccurrence of NPM1, FLT3-ITD, and DNMT3A mutations (i.e., triple mutation) is related to dismal prognosis in patients with acute myeloid leukemia (AML) receiving chemotherapy alone. In this multicenter retrospective cohort study, we aimed to identify whether allogeneic hematopoietic stem cell transplantation (allo-HSCT) could overcome the poor prognosis of DNMT3AmutNPM1mutFLT3-ITDmut AML across four transplant centers in China. Fifty-three patients with triple-mutated AML receiving allo-HSCT in complete remission were enrolled. The 1.5-year probabilities of relapse, leukemia-free survival, and overall survival after allo-HSCT were 11.9%, 80.3%, and 81.8%, respectively. Multivariate analysis revealed that more than one course of induction chemotherapy and allo-HSCT beyond CR1 were associated with poor survival. To our knowledge, this work is the largest study to explore the up-to-date undefined role of allo-HSCT in patients with triple-mutated AML. Our real-world data suggest that allo-HSCT could overcome the poor prognosis of DNMT3AmutNPM1mutFLT3-ITDmut in AML.

Genomic differences of patients with hematologic malignancies in different age groups

Hematologic malignancies cause significant morbidity/mortality in both children and young adults (CYAs) as well as older adults (OAs). Yet their biological underpinnings remain inadequately understood. Here, we analyzed clinical and genomic disparities between CYAs and OAs in various hematologic malignancies. We found substantial differences in clinical features such as patient sex, ethnicity, metastasis rates, and tumor subtypes. Genomically, most CYA hematologic malignancies indicated lower mutational burden. Subsequently, we identified differentially mutated genes (DMGs) with varying mutation rates between CYAs and OAs, noting fewer mutations in CYAs for most genes such as TP53, TET2, and DNMT3A. In contrast, several DMGs (i.e., NRAS, KRAS, SMARCA4, ID3, PTPN11, WT1, and KIT) were overrepresented in CYAs. We further investigated human protein interacting partners of these identified DMGs that were highly mutated in CYAs/OAs, respectively, and found significant differences in network topological and functional roles. Notably, CYA malignancies demonstrated extensive copy number alterations (CNAs) and more driver gene fusions. In particular, four CNA differential genes (i.e., ARID1B, MYB, TP53, and ESR1) were overrepresented as amplifications and deletions in CYAs and OAs, respectively. Ultimately, we demonstrated a landscape comparative view of clinically actionable genetic events in CYAs and OAs, providing clues for age-related personalized treatment.

Nucleic acid metabolism: the key therapeutic target for myeloid tumors

Nucleic acid analogs, including cytarabine, decitabine, and azacitidine, have significantly advanced therapeutic approaches for myeloid tumors over the past five decades. Nucleic acid metabolism is a crucial pathway driving myeloid tumorigenesis, with emerging evidence indicating that myeloid tumors are particularly dependent on the de novo nucleotide synthesis pathway, underscoring its potential as a therapeutic target. This review provides a comprehensive overview of nucleic acid metabolism, focusing on de novo nucleotide synthesis. We then described the range of clinically utilized agents targeting nucleic acid metabolism and discussed our recent findings on the nonepigenetic actions of decitabine, as well as the therapeutic effects of inosine monophosphate dehydrogenase (IMPDH) inhibitors in the treatment of myeloid tumors.

Selective translation of nuclear mitochondrial respiratory proteins reprograms succinate metabolism in AML development and chemoresistance

Mitochondrial adaptations dynamically reprogram cellular bioenergetics and metabolism and confer key properties for human cancers. However, the selective regulation of these mitochondrial responses remains largely elusive. Here, inspired by a genetic screening in acute myeloid leukemia (AML), we identify RAS effector RREB1 as a translational regulator and uncover a unique translation control system for nuclear-encoded mitochondrial proteins in human cancers. RREB1 deletion reduces mitochondrial activities and succinate metabolism, thereby damaging leukemia stem cell (LSC) function and AML development. Replenishing complex II subunit SDHD rectifies these deficiencies. Notably, inhibition of complex II re-sensitizes AML cells to venetoclax treatment. Mechanistically, a short RREB1 variant binds to a conserved motif in the 3' UTRs and cooperates with elongation factor eEF1A1 to enhance protein translation of nuclear-encoded mitochondrial mRNAs. Overall, our findings reveal a unique translation control mechanism for mitochondrial adaptations in AML pathogenesis and provide a potential strategy for targeting this vulnerability of LSCs.

The dynamics of hematopoiesis over the human lifespan

Over a lifetime, hematopoietic stem cells (HSCs) adjust their lineage output to support age-aligned physiology. In model organisms, stereotypic waves of hematopoiesis have been observed corresponding to defined age-biased HSC hallmarks. However, how the properties of hematopoietic stem and progenitor cells change over the human lifespan remains unclear. To address this gap, we profiled individual transcriptome states of human hematopoietic stem and progenitor cells spanning gestation, maturation and aging. Here we define the gene expression networks dictating age-specific differentiation of HSCs and the dynamics of fate decisions and lineage priming throughout life. We additionally identifiy and functionally validate a fetal-specific HSC state with robust engraftment and multilineage capacity. Furthermore, we observe that classification of acute myeloid leukemia against defined transcriptional age states demonstrates that utilization of early life transcriptional programs associates with poor prognosis. Overall, we provide a disease-relevant framework for heterochronic orientation of stem cell ontogeny along the real time axis of the human lifespan.

HMX3 is a critical vulnerability in MECOM-negative KMT2A::MLLT3 acute myelomonocytic leukemia

KMT2A::MLLT3 acute myelomonocytic leukemia (AML) comes in two clinically and biologically different subtypes. One is characterized by inferior outcome, older age, and MECOM oncogene expression. The other is mainly observed in children and young adults, associates with better clinical outcome, but lacks MECOM. To identify cell fate determining transcription factors downstream of KMT2A::MLLT3, we applied a bioinformatic algorithm that integrates gene and enhancer expression from primary MECOM-positive and -negative KMT2A::MLLT3 AML samples. This identified MECOM to be most influential in the MECOM-positive group, while neuronal transcription factor HMX3 was most influential in the MECOM-negative group. In large AML cohorts, HMX3 expression associated with a unique gene expression profile, younger age (p < 0.002) and KMT2A-rearranged and KAT6A-CREBBP leukemia (p < 0.00001). HMX3 was not expressed in other major genetic risk groups and healthy blood cells. RNA-sequencing analyses following forced HMX3 expression in healthy CD34+ cells and its silencing in KMT2A::MLT3 cells showed that HMX3 drives cancer-associated E2F and MYC gene programs (p < 0.001). HMX3 expression in healthy CD34+ cells blocked monocytic but not granulocytic colony formation. Strikingly, HMX3 silencing in KMT2A::MLLT3 patient cells resulted in cell cycle arrest, monocytic differentiation and apoptosis. Thus, the neuronal transcription factor HMX3 is a leukemia-specific vulnerability in KMT2A::MLLT3 AML.

Fusion Genes in Myeloid Malignancies

Fusion genes arise from gross chromosomal rearrangements and have been closely linked to oncogenesis. In myeloid malignancies, fusion genes play an integral role in the establishment of diagnosis and prognostication. In the clinical management of patients with acute myeloid leukemia, fusion genes are deeply incorporated in risk stratification criteria to guide the choice of therapy. As a result of their intrinsic ability to define specific disease entities, oncogenic fusion genes also have immense potential to be developed as therapeutic targets and disease biomarkers. In the current era of genomic medicine, breakthroughs in innovation of sequencing techniques have led to a rise in the detection of novel fusion genes, and the concept of standard-of-care diagnostics continues to evolve in this field. In this review, we outline the molecular basis, mechanisms of action and clinical impact of fusion genes. We also discuss the pros and cons of available methodologies that can be used to detect fusion genes. To contextualize the challenges encountered in clinical practice pertaining to the diagnostic workup and management of myeloid malignancies with fusion genes, we share our experience and insights in the form of three clinical case studies.

Elucidating the immune landscape and potential prognostic model in acute myeloid leukemia with TP53 mutation

OBJECTIVES

The TP53 mutation, a prevalent tumor suppressor gene alteration, is linked to chemotherapy resistance, increased relapse rates and diminished overall survival (OS) in acute myeloid leukemia (AML) patients.

METHODS

In this study, we characterize the TP53 mutation phenotypes across various AML cohorts utilizing The Cancer Genome Atlas (TCGA) data. We devised a TP53-related prognostic signature derived from differentially expressed genes between mutated and wild-type TP53 AML specimens. In-depth analyses were conducted, encompassing genetic variation, immune cell infiltration and prognostic stratification.

RESULTS

A six-gene TP53-related signature was established using least absolute shrinkage and selection operator (LASSO)-Cox regression, demonstrating robust prognostic predictability. This signature exhibited strong performance in both the OHSU validation cohorts, an independent Gene Expression Omnibus (GEO) validation cohort (GSE71014) and proved by results of the in vivo experiment. Finally, we used single cell database (GSE198681) to observe the characteristics of these six genes.

DISCUSSION

Our study may facilitate the development of efficacious therapeutic approaches and provide a novel idea for future research. Conclusion: The TP53-related signature and pattern hold the potential to refine prognostic stratification and underscore emerging targeted therapies.

Redistribution of PU.1 partner transcription factor RUNX1 binding secures cell survival during leukemogenesis

Transcription factors (TFs) orchestrating lineage-development often control genes required for cellular survival. However, it is not well understood how cells survive when such TFs are lost, for example in cancer. PU.1 is an essential TF for myeloid fate, and mice with downregulated PU.1 levels develop acute myeloid leukemia (AML). Combining a multi-omics approach with a functional genetic screen, we reveal that PU.1-downregulated cells fundamentally change their survival control from cytokine-driven pathways to overexpression of an autophagy-predominated stem cell gene program, for which we also find evidence in human AML. Control of this program involves redirected chromatin occupancy of the PU.1 partner TF Runx1 to a lineage-inappropriate binding site repertoire. Hence, genomic reallocation of TF binding upon loss of a partner TF can act as a pro-oncogenic failsafe mechanism by sustaining cell survival during leukemogenesis.

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.

The clinical implications of BCOR mutations in a large cohort of acute myeloid leukemia patients: a 5-year single-center retrospective study

To elucidate the effect of BCOR mutation (BCORmut) on clinical outcomes, we included a total of 899 consecutive AML patients in a single-center during July 2016 to December 2021. Fifty cases (5.6%) had BCOR mutations, which co-occurred with mutations of RUNX1, DNMT3A, IDH2, BCORL1, STAG2, SF3B1 and U2AF1, but were exclusive with KIT and CEBPA mutations. BCORmut was also found to be exclusive with t(8;21)(q22;q22.1) AML in all patients and MLL rearrangements in the European Leukemia Net (ELN) adverse group. In those receiving intensive chemotherapy regimens, BCORmut was associated with lower complete remission (CR) rates and worse prognosis. Subgroup analysis showed that BCORmut mainly conferred a poor prognosis in the intermediate and adverse groups of the ELN2017 risk. These results suggest that BCOR mutation is an independent prognostic parameter in AML, implying BCOR mutation as a novel marker for chemorefractory disease and inferior prognosis.

ASXL1 truncating variants in BOS and myeloid leukemia drive shared disruption of Wnt-signaling pathways but have differential isoform usage of RUNX3

BACKGROUND

Rare variants in epigenes (a.k.a. chromatin modifiers), a class of genes that control epigenetic regulation, are commonly identified in both pediatric neurodevelopmental syndromes and as somatic variants in cancer. However, little is known about the extent of the shared disruption of signaling pathways by the same epigene across different diseases. To address this, we study an epigene, Additional Sex Combs-like 1 (ASXL1), where truncating heterozygous variants cause Bohring-Opitz syndrome (BOS, OMIM #605039), a germline neurodevelopmental disorder, while somatic variants are driver events in acute myeloid leukemia (AML). No BOS patients have been reported to have AML.

METHODS

This study explores common pathways dysregulated by ASXL1 variants in patients with BOS and AML. We analyzed whole blood transcriptomic and DNA methylation data from patients with BOS and AML with ASXL1-variant (AML-ASXL1) and examined differential exon usage and cell proportions.

RESULTS

Our analyses identified common molecular signatures between BOS and AML-ASXL1 and highlighted key biomarkers, including VANGL2, GRIK5 and GREM2, that are dysregulated across samples with ASXL1 variants, regardless of disease type. Notably, our data revealed significant de-repression of posterior homeobox A (HOXA) genes and upregulation of Wnt-signaling and hematopoietic regulator HOXB4. While we discovered many shared epigenetic and transcriptomic features, we also identified differential splice isoforms in RUNX3 where the long isoform, p46, is preferentially expressed in BOS, while the shorter p44 isoform is expressed in AML-ASXL1.

CONCLUSION

Our findings highlight the strong effects of ASXL1 variants that supersede cell-type and even disease states. This is the first direct comparison of transcriptomic and methylation profiles driven by pathogenic variants in a chromatin modifier gene in distinct diseases. Similar to RASopathies, in which pathogenic variants in many genes lead to overlapping phenotypes that can be treated by inhibiting a common pathway, our data identifies common pathways for ASXL1 variants that can be targeted for both disease states. Comparative approaches of high-penetrance genetic variants across cell types and disease states can identify targetable pathways to treat multiple diseases. Finally, our work highlights the connections of epigenes, such as ASXL1, to an underlying stem-cell state in both early development and in malignancy.

bamSliceR: a Bioconductor package for rapid, cross-cohort variant and allelic bias analysis

The NCI Genomic Data Commons (GDC) provides controlled access to sequencing data from thousands of subjects, enabling large-scale study of impactful genetic alterations such as simple and complex germline and structural variants. However, efficient analysis requires significant computational resources and expertise, especially when recalling variants from raw sequence reads. We thus developed bamSliceR , an R/Bioconductor package that builds upon the GenomicDataCommons package to extract aligned sequence reads from cross-GDC meta-cohorts, followed by targeted analysis of variants and effects (including transcript-aware variant annotation from transcriptome-aligned GDC RNA data). Here we demonstrate population-scale genomic & transcriptomic analyses with minimal compute burden via bamSliceR , identifying recurrent, clinically relevant sequence and structural variants in the TARGET AML and BEAT-AML cohorts. We then validate results in the (non-GDC) Leucegene cohort, demonstrating how the bamSliceR pipeline can be seamlessly applied to replicate findings in non-GDC cohorts. These variants directly yield clinically impactful and biologically testable hypotheses for mechanistic investigation. bamSliceR has been submitted to the Bioconductor project, where it is presently under review, and is available on GitHub at https://github.com/trichelab/bamSliceR.

RSK1 dependency in FLT3-ITD acute myeloid leukemia

Internal tandem duplications (ITD) in fms-like tyrosine kinase 3 (FLT3) represent the most common genetic alteration in de novo acute myeloid leukemia (AML). Here, we identify ribosomal protein s6 kinase a1 (RSK1) as a core dependency in FLT3-ITD AML and unveil the existence of crucial bi-directional regulation. RSK1 perturbation resulted in marked apoptosis and abrogated phosphorylation of FLT3 and associated downstream signaling cascades in FLT3-ITD AML cell lines. Using cycloheximide, MG-132, and ubiquitination assays, we further demonstrate mechanistically that RSK1 regulates FLT3-ITD activity, and protein stability through deubiqutinase USP1, which we identify as a second dependency. Importantly, multivariate analysis revealed heightened expression of RPS6KA1 and USP1 to be associated with poor patient prognosis, and these effectors may serve as biomarkers predictive of patient survival and therapeutic response to FLT3-ITD inhibitors. Lastly, RSK1 inhibition utilizing a first-in-class RSK inhibitor, PMD-026, that is currently undergoing Phase 2 development for breast cancer, diminished leukemic disease burden in MV4-11 xenograft and syngeneic Flt3ITDTet2KO leukemia models. These findings illustrate an unconventional and promising therapeutic strategy targeting FLT3-ITD leukemia.

Dynamics of measurable residual disease for risk stratification and guiding allogeneic transplant in acute myeloid leukaemia patients with myelodysplasia-related mutations in first remission

Accurate classification and risk prediction are critical for therapeutic decision-making in patients with acute myeloid leukaemia (AML). Myelodysplasia-related (MR) gene mutations are classified as adverse genetic factors by the European LeukaemiaNet-2022 guidelines. However, their prognostic value in de novo AML remains controversial. This study retrospectively analysed 188 patients with de novo AML-MR, stratifying them into four subgroups based on dynamic measurable residual disease (MRD) after induction, one or two courses of consolidation chemotherapy. The median follow-up was 36.8 months (4.6-73.7). Patients with persistent or recurrent MRD positivity after the second consolidation had the poorest 3-year relapse-free survival (RFS), overall survival (OS) and cumulative incidence of relapse compared to the other groups (p < 0.001). Multivariable analysis identified this high-risk group as an independent risk factor for both RFS and OS. We observed significant heterogeneity of OS benefit from allogeneic stem cell transplantation (allo-SCT) by MRD-risk groups, with substantial OS advantage for patients in subgroup D (3-year OS: allo-SCT 70.0% vs. 18.2% without, p < 0.001) but no benefit for others (p = 0.047 for interaction). This study underscores the importance of dynamic MRD in refining risk stratification and identifying de novo AML patients with MR mutations who would benefit from allo-SCT during the first complete remission.

Integrated molecular and functional characterization of the intrinsic apoptotic machinery identifies therapeutic vulnerabilities in glioma

Genomic profiling often fails to predict therapeutic outcomes in cancer. This failure is, in part, due to a myriad of genetic alterations and the plasticity of cancer signaling networks. Functional profiling, which ascertains signaling dynamics, is an alternative method to anticipate drug responses. It is unclear whether integrating genomic and functional features of solid tumours can provide unique insight into therapeutic vulnerabilities. We perform combined molecular and functional characterization, via BH3 profiling of the intrinsic apoptotic machinery, in glioma patient samples and derivative models. We identify that standard-of-care therapy rapidly rewires apoptotic signaling in a genotype-specific manner, revealing targetable apoptotic vulnerabilities in gliomas containing specific molecular features (e.g., TP53 WT). However, integration of BH3 profiling reveals high mitochondrial priming is also required to induce glioma apoptosis. Accordingly, a machine-learning approach identifies a composite molecular and functional signature that best predicts responses of diverse intracranial glioma models to standard-of-care therapies combined with ABBV-155, a clinical drug targeting intrinsic apoptosis. This work demonstrates how complementary functional and molecular data can robustly predict therapy-induced cell death.

Genotype-immunophenotype relationships in NPM1-mutant AML clonal evolution uncovered by single cell multiomic analysis

Acute myeloid leukemia (AML) is a multi-clonal disease, existing as a milieu of clones with unique but related genotypes as initiating clones acquire subsequent mutations. However, bulk sequencing cannot fully capture AML clonal architecture or the clonal evolution that occurs as patients undergo therapy. To interrogate clonal evolution, we performed simultaneous single cell molecular profiling and immunophenotyping on 43 samples from 32 NPM1-mutant AML patients at different stages of disease. Here we show that diagnosis and relapsed AML samples display similar clonal architecture patterns, but signaling mutations can drive increased clonal diversity specifically at relapse. We uncovered unique genotype-immunophenotype relationships regardless of disease state, suggesting leukemic lineage trajectories can be hard-wired by the mutations present. Analysis of longitudinal samples from patients on therapy identified dynamic clonal, transcriptomic, and immunophenotypic changes. Our studies provide resolved understanding of leukemic clonal evolution and the relationships between genotype and cell state in leukemia biology.

In vivo models of subclonal oncogenesis and dependency in hematopoietic malignancy

Cancer evolution is a multifaceted process leading to dysregulation of cellular expansion and differentiation through somatic mutations and epigenetic dysfunction. Clonal expansion and evolution is driven by cell-intrinsic and -extrinsic selective pressures, which can be captured with increasing resolution by single-cell and bulk DNA sequencing. Despite the extensive genomic alterations revealed in profiling studies, there remain limited experimental systems to model and perturb evolutionary processes. Here, we integrate multi-recombinase tools for reversible, sequential mutagenesis from premalignancy to leukemia. We demonstrate that inducible Flt3 mutations differentially cooperate with Dnmt3a, Idh2, and Npm1 mutant alleles, and that changing the order of mutations influences cellular and transcriptional landscapes. We next use a generalizable, reversible approach to demonstrate that mutation reversion results in rapid leukemic regression with distinct differentiation patterns depending upon co-occurring mutations. These studies provide a path to experimentally model sequential mutagenesis, investigate mechanisms of transformation and probe oncogenic dependency in disease evolution.

Immune-based subgroups uncover diverse tumor immunogenicity and implications for prognosis and precision therapy in acute myeloid leukemia

Background

Although a considerable proportion of acute myeloid leukemia (AML) patients achieve remission through chemotherapy, relapse remains a recurring and significant event leading to treatment failure. This study aims to investigate the immune landscape in AML and its potential implications for prognosis and chemo-/immune-therapy.

Methods

Integrated analyses based on multiple sequencing datasets of AML were performed. Various algorithms estimated immune infiltration in AML samples. A subgroup prediction model was developed, and comprehensive bioinformatics and machine learning algorithms were applied to compare immune-based subgroups in relation to clinical features, mutational landscapes, immune characterizations, drug sensitivities, and cellular hierarchies at the single-cell level.

Results

Two immune-based AML subgroups, G1 and G2, were identified. G1 demonstrated higher immune infiltration, a more monocytic phenotype, increased proportions of monocytes/macrophages, and higher FLT3, DNMT3A, and NPM1 mutation frequencies. It was associated with a poorer prognosis, lower proportions of various immune cell types and a lower T cell infiltration score (TIS). AML T-cell-based immunotherapy target antigens, including CLEC12A, Folate receptor β, IL1RAP and TIM3, showed higher expression levels in G1, while CD117, CD244, CD96, WT and TERT exhibited higher expression levels in G2. G1 samples demonstrated higher sensitivity to elesclomol and panobinostat but increased resistance to venetoclax compared to G2 samples. Moreover, we observed a positive correlation between sample immune infiltration and sample resistance to elesclomol and panobinostat, whereas a negative correlation was found with venetoclax resistance.

Conclusion

Our study enriches the current AML risk stratification and provides guidance for precision medicine in AML.

Measurable residual mutated IDH1 before allogeneic transplant for acute myeloid leukemia

Measurable residual disease (MRD) in adults with acute myeloid leukemia (AML) in complete remission is an important prognostic marker, but detection methodology requires optimization. Persistence of mutated NPM1 or FLT3-ITD in the blood of adult patients with AML in first complete remission (CR1) prior to allogeneic hematopoietic cell transplant (alloHCT) associates with increased relapse and death after transplant. The prognostic implications of persistence of other common AML-associated mutations, such as IDH1, at this treatment landmark however remain incompletely defined. We performed testing for residual IDH1 variants (IDH1m) in pre-transplant CR1 blood of 148 adult patients undergoing alloHCT for IDH1-mutated AML at a CIBMTR reporting site between 2013 and 2019. No statistically significant post-transplant differences were observed between those testing IDH1m positive (n = 53, 36%) and negative pre-transplant (overall survival (OS): p = 0.4; relapse: p = 0.5). For patients with IDH1 mutated AML co-mutated with NPM1 and/or FLT3-ITD, only detection of persistent mutated NPM1 and/or FLT3-ITD was associated with significantly higher rates of relapse (p = 0.01). These data, from the largest study to date, do not support the detection of IDH1 mutation in CR1 blood prior to alloHCT as evidence of AML MRD for increased post-transplant relapse risk.

Improving risk stratification for 2022 European LeukemiaNet favorable-risk patients with acute myeloid leukemia

Assignment of patients diagnosed with acute myeloid leukemia (AML) to the 2022 European LeukemiaNet (ELN) favorable genetic risk group has important clinical implications, as allogeneic stem cell transplantation in first complete remission (CR) is not advised due to a relatively good outcome of patients receiving chemotherapy alone and transplant-associated mortality. However, not all favorable genetic risk patients experience long-term relapse-free survival (RFS), making recognition of patients who would most likely be cured of high importance. We analyzed 297 patients aged <60 years with de novo AML classified as 2022 ELN favorable genetic risk who achieved a CR and had RNA sequencing (RNA-seq) and gene mutation data from diagnostic samples available (Alliance trial A152010). To identify prognostically relevant transcripts that can distinguish patients cured from patients susceptible to lower or higher risk of relapse or death, we fit a regularized mixture cure model (MCM) where RNA-seq expression values were our candidate covariates. To validate the identified transcripts, we analyzed 75 patients with de novo AML aged <60 years included in the 2022 ELN favorable genetic risk group who achieved a CR in an independent test set from Gene Expression Omnibus (GSE37642). Our MCM identified 145 transcripts associated with cure or long-term RFS and 149 transcripts associated with latency or shorter-term time to relapse. The area under the curve and C-statistic were, respectively, 0.946 and 0.856 for our training set and 0.877 and 0.857 for our test set. Our results suggest that the favorable risk group includes distinct transcriptionally defined subgroups with different biological properties, which may be useful for refining this genetic risk category.

Single-cell sequencing applications in acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous group of malignancies with poor prognosis. AML result from the proliferation of immature myeloid cells blocked at a variable stage of differentiation. Beyond inter-patient heterogeneity, AMLs are characterized by genetic and phenotypic intra-patient heterogeneity. Despite major advances in deciphering AML biology with bulk sequencing studies, pivotal questions remain unanswered. Analyses at the single-cell level could thus transform our understanding of these neoplasms. We review recent progresses in single-cell sequencing technologies from cell processing to bioinformatic pipelines. We next discuss how single-cell applications have helped understand the genetic and functional intra-leukemic heterogeneity, emphasizing aspects related to leukemic stem cells, clonal evolution and measurable residual disease (MRD) monitoring. We finally delineate how single-cell technologies could be implemented in routine clinical practice to improve patient management.

89Zr-immunoPET-guided selection of a CD33xIL15 fusion protein optimized for antitumor immune cell activation and in vivo tumour retention in acute myeloid leukaemia

PURPOSE

Immune cells are capable of eliminating leukemic cells, as evidenced by outcomes in hematopoietic cell transplantation (HCT). However, patients who fail induction therapy will not benefit from HCT due to their minimal residual disease (MRD) status. Thus, we aimed to develop an immunomodulatory agent to reduce MRD by activating immune effector cells in the presence of leukaemia cells via a novel fusion protein that chimerises two clinically tolerated biologics: a CD33 antibody and the IL15Ra/IL15 complex (CD33xIL15).

METHODS

We generated a set of CD33xIL15 fusion protein constructs with varying configurations and identified those with the best in vitro AML-binding, T cell activation, and NK cell potentiation. Using 89Zr-immunoPET imaging we then evaluated the biodistribution and in vivo tumour retention of the most favourable CD33xIL15 constructs in an AML xenograft model. Ex vivo biodistribution studies were used to confirm the pharmacokinetics of the constructs.

RESULTS

Two of the generated fusion proteins, CD33xIL15 (N72D) and CD33xIL15wt, demonstrated optimal in vitro behaviour and were further evaluated in vivo. These studies revealed that the CD33xIL15wt candidate was capable of being retained in the tumour for as long as its parental CD33 antibody, Lintuzumab (13.9 ± 3.1%ID/g vs 18.6 ± 1.1%ID/g at 120 h).

CONCLUSION

This work demonstrates that CD33xIL15 fusion proteins are capable of targeting leukemic cells and stimulating local T cells in vitro and of concentrating in the tumour in AML xenografts. It also highlights the importance of 89Zr-immunoPET to guide the development and selection of tumour-targeted antibody-cytokine fusion proteins.

Therapy-Related Myeloid Neoplasms: Complex Interactions among Cytotoxic Therapies, Genetic Factors, and Aberrant Microenvironment

Therapy-related myeloid neoplasm (t-MN), characterized by its association with prior exposure to cytotoxic therapy, remains poorly understood and is a major impediment to long-term survival even in the era of novel targeted therapies due to its aggressive nature and treatment resistance. Previously, cytotoxic therapy-induced genomic changes in hematopoietic stem cells were considered sine qua non in pathogenesis; however, recent research demonstrates a complex interaction between acquired and hereditary genetic predispositions, along with a profoundly senescent bone marrow (BM) microenvironment. We review emerging data on t-MN risk factors and explore the intricate interplay among clonal hematopoiesis, genetic predisposition, and the abnormal BM microenvironment. Significance: t-MN represents a poorly understood blood cancer with extremely poor survival and no effective therapies. We provide a comprehensive review of recent preclinical research highlighting complex interaction among emerging therapies, hereditary and acquired genetic factors, and BM microenvironment. Understanding the risk factors associated with t-MN is crucial for clinicians, molecular pathologists, and cancer biologists to anticipate and potentially reduce its incidence in the future. Moreover, better understanding of the molecular pathogenesis of t-MN may enable preemptive screening and even intervention in high-risk patients.

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.

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.

A View of Myeloid Transformation through the Hallmarks of Cancer

The development of myeloid malignancies is influenced by a range of cell-intrinsic and cell-extrinsic factors, which can be conceptualized using the hallmarks of cancer. Although many facets of myeloid transformation are similar to those in solid tumors, there are also notable differences. Unlike solid tumors, hematologic malignancies typically exhibit fewer genetic mutations, which have been well characterized. However, understanding the cell-extrinsic factors contributing to myeloid malignancies can be challenging due to the complex interactions in the hematopoietic microenvironment. Researchers need to focus on these intricate factors to prevent the early onset of myeloid transformation and develop appropriate interventions. Significance: Myeloid malignancies are common in the elderly, and acute myeloid leukemia has an adverse prognosis in older patients. Investigating cell-extrinsic factors influencing myeloid malignancies is crucial to developing approaches for preventing or halting disease progression and predicting clinical outcomes in patients with advanced disease. Whereas successful intervention may require targeting various mechanisms, understanding the contribution of each cell-extrinsic factor will help prioritize clinical targets.

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.

A multiomics approach reveals RNA dynamics promote cellular sensitivity to DNA hypomethylation

The search for new approaches in cancer therapy requires a mechanistic understanding of cancer vulnerabilities and anti-cancer drug mechanisms of action. Problematically, some effective therapeutics target cancer vulnerabilities that have poorly defined mechanisms of anti-cancer activity. One such drug is decitabine, a frontline therapeutic approved for the treatment of high-risk acute myeloid leukemia (AML). Decitabine is thought to kill cancer cells selectively via inhibition of DNA methyltransferase enzymes, but the genes and mechanisms involved remain unclear. Here, we apply an integrated multiomics and CRISPR functional genomics approach to identify genes and processes associated with response to decitabine in AML cells. Our integrated multiomics approach reveals RNA dynamics are key regulators of DNA hypomethylation induced cell death. Specifically, regulation of RNA decapping, splicing and RNA methylation emerge as important regulators of cellular response to decitabine.

Measurable residual mutated IDH2 before allogeneic transplant for acute myeloid leukemia

Routine genetic profiling of acute myeloid leukemia (AML) at initial diagnosis has allowed subgroup specific prognostication, drug development, and clinical management strategies. The optimal approach for treatment response assessment for AML subgroups has not yet however been determined. A nationwide cohort of 257 adult patients in first remission (CR1) from AML associated with an IDH2 mutation (IDH2m) undergoing allogeneic transplant during the period 2013-2019 in the United States had rates of relapse and survival three years after transplantation of 24% and 71%, respectively. Pre-transplant clinical flow cytometry assessment was not useful in stratifying patients based on risk of post-transplant relapse or death. DNA-sequencing was performed on CR1 blood collected within 100 days before transplant. Persistent detection of IDH2m was common (51%) and associated with increased relapse and death compared to testing negative. Co-mutation at initial diagnosis with mutated NPM1 and/or FLT3-ITD was common in this cohort (41%) and use of these validated MRD markers provided superior stratification compared to IDH2m testing. Patients testing negative for IDH2m prior to transplant had low relapse-related death, regardless of conditioning intensity. Post-transplant relapse rates for those with persistently detectable IDH2m in pre-transplant remission were lower after the FDA approval of enasidenib in August 2017.

Characterization of ligand-receptor pair in acute myeloid leukemia: a scoring model for prognosis, therapeutic response, and T cell dysfunction

Introduction

The significance of ligand-receptor (LR) pair interactions in the progression of acute myeloid leukemia (AML) has been the focus of numerous studies. However, the relationship between LR pairs and the prognosis of AML, as well as their impact on treatment outcomes, is not fully elucidated.

Methods

Leveraging data from the TCGA-LAML cohort, we mapped out the LR pair interactions and distinguished specific molecular subtypes, with each displaying distinct biological characteristics. These subtypes exhibited varying mutation landscapes, pathway characteristics, and immune infiltration levels. Further insight into the immune microenvironment among these subtypes revealed disparities in immune cell abundance.

Results

Notably, one subtype showed a higher prevalence of CD8 T cells and plasma cells, suggesting increased adaptive immune activities. Leveraging a multivariate Lasso regression, we formulated an LR pair-based scoring model, termed "LR.score," to classify patients based on prognostic risk. Our findings underscored the association between elevated LR scores and T-cell dysfunction in AML. This connection highlights the LR score's potential as both a prognostic marker and a guide for personalized therapeutic interventions. Moreover, our LR.score revealed substantial survival prediction capacities in an independent AML cohort. We highlighted CLEC11A, ICAM4, ITGA4, and AVP as notably AML-specific.

Discussion

qRT-PCR analysis on AML versus normal bone marrow samples confirmed the significant downregulation of CLEC11A, ITGA4, ICAM4, and AVP in AML, suggesting their inverse biomarker potential in AML. In summary, this study illuminates the significance of the LR pair network in predicting AML prognosis, offering avenues for more precise treatment strategies tailored to individual patient profiles.

Venetoclax triggers sublethal apoptotic signaling in venetoclax-resistant acute myeloid leukemia cells and induces vulnerability to PARP inhibition and azacitidine

Venetoclax plus azacitidine treatment is clinically beneficial for elderly and unfit acute myeloid leukemia (AML) patients. However, the treatment is rarely curative, and relapse due to resistant disease eventually emerges. Since no current clinically feasible treatments are known to be effective at the state of acquired venetoclax resistance, this is becoming a major challenge in AML treatment. Studying venetoclax-resistant AML cell lines, we observed that venetoclax induced sublethal apoptotic signaling and DNA damage even though cell survival and growth were unaffected. This effect could be due to venetoclax inducing a sublethal degree of mitochondrial outer membrane permeabilization. Based on these results, we hypothesized that the sublethal apoptotic signaling induced by venetoclax could constitute a vulnerability in venetoclax-resistant AML cells. This was supported by screens with a broad collection of drugs, where we observed a synergistic effect between venetoclax and PARP inhibition in venetoclax-resistant cells. Additionally, the venetoclax-PARP inhibitor combination prevented the acquisition of venetoclax resistance in treatment naïve AML cell lines. Furthermore, the addition of azacitidine to the venetoclax-PARP inhibitor combination enhanced venetoclax induced DNA damage and exhibited exceptional sensitivity and long-term responses in the venetoclax-resistant AML cell lines and samples from AML patients that had clinically relapsed under venetoclax-azacitidine therapy. In conclusion, we mechanistically identify a new vulnerability in acquired venetoclax-resistant AML cells and identify PARP inhibition as a potential therapeutic approach to overcome acquired venetoclax resistance in AML.

[Application of high-throughput drug sensitivity testing in children with relapsed and refractory acute leukemia]

OBJECTIVES

To explore the current application of high-throughput drug sensitivity (HDS) testing in children with relapsed and refractory acute leukemia (RR-AL) and analyze the feasibility of salvage treatment plans.

METHODS

A retrospective collection of clinical data from children with RR-AL who underwent HDS testing at the Department of Children's Hematology and Oncology of the First Affiliated Hospital of Zhengzhou University from November 2021 to October 2023 was conducted, followed by an analysis of drug sensitivity results and treatment outcomes.

RESULTS

A total of 17 children with RR-AL underwent HDS testing, including 7 cases of relapsed refractory acute myeloid leukemia and 10 cases of relapsed refractory acute lymphoblastic leukemia. The detection rate of highly sensitive chemotherapy drugs/regimens was 53% (9/17), while the detection rate of moderately sensitive chemotherapy drugs/regimens was 100% (17/17). Among the 17 RR-AL patients with highly and moderately sensitive chemotherapy drugs and regimens, the MOACD regimen (mitoxantrone + vincristine + cytarabine + cyclophosphamide + dexamethasone) accounted for 100%, with the highest inhibition rate for single-agent mitoxantrone (94%, 16/17), and the highest inhibition rate for targeted therapy being bortezomib (94%, 16/17). Nine patients adjusted their chemotherapy based on HDS testing results, with 4 undergoing hematopoietic stem cell transplantation. Four patients achieved disease-free survival, while 5 died. Eight patients received empirical chemotherapy, with 2 undergoing hematopoietic stem cell transplantation; 4 achieved disease-free survival, while 4 died.

CONCLUSIONS

HDS testing can identify highly sensitive drugs/regimens for children with RR-AL, improving the rate of re-remission and creating conditions for subsequent hematopoietic stem cell transplantation.

Autophagy and inflammasome activation are associated with poor response to FLT3 inhibitors in patients with FLT3-ITD acute myeloid leukemia

Beyond its clinical diversity and severity, acute myeloid leukemia (AML) is known for its complex molecular background and for rewiring biological processes to aid disease onset and maintenance. FLT3 mutations are among the most recurring molecular entities that cooperatively drive AML, and their inhibition is a critical molecularly oriented therapeutic strategy. Despite being a promising avenue, it still faces challenges such as intrinsic and acquired drug resistance, which led us to investigate whether and how autophagy and inflammasome interact and whether this interaction could be leveraged to enhance FLT3 inhibition as a therapeutic strategy. We observed a strong and positive correlation between the expression of key genes associated with autophagy and the inflammasome. Gene set enrichment analysis of the FLT3-ITD samples and their ex vivo response to five different FLT3 inhibitors revealed a common molecular signature compatible with autophagy and inflammasome activation across all poor responders. Inflammasome activation was also shown to strongly increase the likelihood of a poor ex vivo response to the FLT3 inhibitors quizartinib and sorafenib. These findings reveal a distinct molecular pattern within FLT3-ITD AML samples that underscores the necessity for further exploration into how approaching these supportive parallel yet altered pathways could improve therapeutic strategies.

Super multiple primary lung cancers harbor high-frequency BRAF and low-frequency EGFR mutations in the MAPK pathway

The incidence of multiple primary lung cancer (MPLC) is increasing, with some of our surgical patients exhibiting numerous lesions. We defined lung cancer with five or more primary lesions as super MPLCs. Elucidating the genomic characteristics of this special MPLC subtype can help reduce disease burden and understand tumor evolution. In our cohort of synchronous super early-stage MPLCs (PUMCH-ssesMPLC), whole-exome sequencing on 130 resected malignant specimens from 18 patients provided comprehensive super-MPLC genomic landscapes. Mutations are enriched in PI3k-Akt and MAPK pathways. Their BRAF mutation frequency (31.5%) is significantly higher than MPLC with fewer lesions and early-stage single-lesion cancer, while EGFR mutations are significantly fewer (13.8%). As lesion counts increase, BRAF mutations gradually become dominant. Also, invasive lesions more tend to have classic super-MPLC mutation patterns. High-frequency BRAF mutations, especially Class II, and low-frequency EGFR mutations could be a reason for the limited effectiveness of targeted therapy in super-MPLC patients.

Differential inflammatory conditioning of the bone marrow by acute myeloid leukemia and its impact on progression

ABSTRACT

Inflammation promotes solid tumor progression, but how regulatory mechanisms of inflammation may affect leukemia is less well studied. Using annexin A5 (ANXA5), a calcium-binding protein known for apoptosis, which we discovered to be differentially expressed in the bone marrow microenvironment (BMM) of mice with acute myeloid (AML) vs chronic myeloid leukemia, as a model system, we unravel here a circuit in which AML-derived tumor necrosis factor α (TNF-α) dose-dependently reduces ANXA5 in the BMM. This creates an inflammatory BMM via elevated levels of prostaglandin E2 (PGE2). Via binding to its EP4 receptor, PGE2 increases β-catenin and hypoxia-inducible factor 1α signaling in AML cells, thereby accelerating PGE2-sensitive AML. Human trephine biopsies may show lower ANXA5 expression and higher PGE2 expression in AML than other hematologic malignancies. Furthermore, syngeneic and xenogeneic transplantation models suggest a survival benefit after treatment with the inhibitor of prostaglandin-endoperoxide synthase 2 (cyclooxygenase 2 [COX2]), celecoxib, plus cytarabine in those AML types highly sensitive to PGE2 compared with cytarabine alone. Taken together, TNF-α/ANXA5/NF-κB/COX2/PGE2-mediated inflammation influences AML course in a highly differential and circular manner, and patients with AML with "inflammatory AML" may benefit from antiphlogistic agents as adjunct therapy.

DEMINING: A deep learning model embedded framework to distinguish RNA editing from DNA mutations in RNA sequencing data

Precise calling of promiscuous adenosine-to-inosine RNA editing sites from transcriptomic datasets is hindered by DNA mutations and sequencing/mapping errors. Here, we present a stepwise computational framework, called DEMINING, to distinguish RNA editing and DNA mutations directly from RNA sequencing datasets, with an embedded deep learning model named DeepDDR. After transfer learning, DEMINING can also classify RNA editing sites and DNA mutations from non-primate sequencing samples. When applied in samples from acute myeloid leukemia patients, DEMINING uncovers previously underappreciated DNA mutation and RNA editing sites; some associated with the upregulated expression of host genes or the production of neoantigens.

CASPER: A Phase I trial combining calaspargase pegol-mnkl and cobimetinib in pancreatic cancer

Asparagine synthetase (ASNS) catalyzes the biosynthesis of asparagine from aspartate and glutamine. Cells lacking ASNS, however, are auxotrophic for asparagine. Use of L-asparaginase to promote asparagine starvation in solid tumors with low ASNS levels, such as pancreatic ductal adenocarcinoma (PDAC), is a rationale treatment strategy. However, tumor cell resistance to L-asparaginase has limited its clinical utility. Our preclinical studies show that RAS/MAPK signaling circumvents L-asparaginase-induced tumor killing, but L-asparaginase and MEK inhibition potentiated tumor killing; suggesting that this combination may provide meaningful clinical benefit to patients with PDAC. This Phase I trial (NCT05034627) will evaluate the safety and tolerability of the MEK inhibitor, cobimetinib, in combination with pegylated L-asparaginase, L calaspargase pegol-mknl, in patients with locally-advanced or metastatic PDAC.

Advancements in genetic analysis: Insights from a case study and review of next-generation sequencing techniques for veterinary oncology applications

Acute myeloid leukemia (AML) poses significant challenges in veterinary medicine, with limited treatment options and poor survival rates. While substantial progress has been made in characterizing human AML, translating these advancements to veterinary practice has been hindered by limited molecular understanding and diagnostic tools. The case study presented illustrates the application of whole genome sequencing in diagnosing AML in a dog, showcasing its potential in veterinary oncology. Our approach facilitated comprehensive genomic analysis, identifying mutations in genes that may be associated with AML pathogenesis in dogs, such as KRAS, IKZF1, and RUNX1. However, without supportive evidence of its clinical utility (eg, association with response to treatment or prognosis), the information is limited to exploration. This article reviews the comparative features of canine AML with human AML and discusses strategies to shrink the knowledge gap between human and veterinary medicine with cost-effective next-generation sequencing (NGS) techniques. By utilizing these approaches, the unique and shared molecular features with human AML can be identified, aiding in molecular classification and therapeutic development for both species. Despite the promise of NGS, challenges exist in implementing it into routine veterinary diagnostics. Cost considerations, turnaround times, and the need for robust bioinformatics pipelines and quality control measures must be addressed. Most importantly, analytical and clinical validation processes are essential to ensure the reliability and clinical utility of NGS-based assays. Overall, integrating NGS technologies into veterinary oncology holds great potential for advancing our understanding of AML and improving disease stratification, in hopes of improving clinical outcomes.