The TLK-ASF1 histone chaperone pathway plays a critical role in IL-1ß-mediated AML progression.

ABSTRACT: Identifying and targeting microenvironment-driven pathways that are active across acute myeloid leukemia (AML) genetic subtypes should allow the development of more broadly effective therapies. The proinflammatory cytokine interleukin-1ß (IL-1ß) is abundant in the AML microenvironment and promotes leukemic growth. Through RNA-sequencing analysis, we identify that IL-1ß-upregulated ASF1B (antisilencing function-1B), a histone chaperone, in AML progenitors compared with healthy progenitors. ASF1B, along with its paralogous protein ASF1A, recruits H3-H4 histones onto the replication fork during S-phase, a process regulated by Tousled-like kinase 1 and 2 (TLKs). Although ASF1s and TLKs are known to be overexpressed in multiple solid tumors and associated with poor prognosis, their functional roles in hematopoiesis and inflammation-driven leukemia remain unexplored. In this study, we identify that ASF1s and TLKs are overexpressed in multiple genetic subtypes of AML. We demonstrate that depletion of ASF1s significantly reduces leukemic cell growth in both in vitro and in vivo models using human cells. Using a murine model, we show that overexpression of ASF1B accelerates leukemia progression. Moreover, Asf1b or Tlk2 deletion delayed leukemia progression, whereas these proteins are dispensable for normal hematopoiesis. Through proteomics and phosphoproteomics analyses, we uncover that the TLK-ASF1 pathway promotes leukemogenesis by affecting the cell cycle and DNA damage pathways. Collectively, our findings identify the TLK1-ASF1 pathway as a novel mediator of inflammatory signaling and a promising therapeutic target for AML treatment across diverse genetic subtypes. Selective inhibition of this pathway offers potential opportunities to intervene effectively, address intratumoral heterogeneity, and ultimately improve clinical outcomes in AML.

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.

Identification and prioritization of myeloid malignancy germline variants in a large cohort of adult patients with AML.

Inherited predisposition to myeloid malignancies is more common than previously appreciated. We analyzed the whole-exome sequencing data of paired leukemia and skin biopsy samples from 391 adult patients from the Beat AML 1.0 consortium. Using the 2015 American College of Medical Genetics and Genomics (ACMG) guidelines for variant interpretation, we curated 1547 unique variants from 228 genes. The pathogenic/likely pathogenic (P/LP) germline variants were identified in 53 acute myeloid leukemia (AML) patients (13.6%) in 34 genes, including 6.39% (25/391) of patients harboring P/LP variants in genes considered clinically actionable (tier 1). 41.5% of the 53 patients with P/LP variants were in genes associated with the DNA damage response. The most frequently mutated genes were CHEK2 (8 patients) and DDX41 (7 patients). Pathogenic germline variants were also found in new candidate genes (DNAH5, DNAH9, DNMT3A, and SUZ12). No strong correlation was found between the germline mutational rate and age of AML onset. Among 49 patients who have a reported history of at least one family member affected with hematological malignancies, 6 patients harbored known P/LP germline variants and the remaining patients had at least one variant of uncertain significance, suggesting a need for further functional validation studies. Using CHEK2 as an example, we show that three-dimensional protein modeling can be one of the effective methodologies to prioritize variants of unknown significance for functional studies. Further, we evaluated an in silico approach that applies ACMG curation in an automated manner using the tool for assessment and (TAPES) prioritization in exome studies, which can minimize manual curation time for variants. Overall, our findings suggest a need to comprehensively understand the predisposition potential of many germline variants in order to enable closer monitoring for disease management and treatment interventions for affected patients and families.

Functional genomic landscape of acute myeloid leukaemia.

The implementation of targeted therapies for acute myeloid leukaemia (AML) has been challenging because of the complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. Here we report initial findings from the Beat AML programme on a cohort of 672 tumour specimens collected from 562 patients. We assessed these specimens using whole-exome sequencing, RNA sequencing and analyses of ex vivo drug sensitivity. Our data reveal mutational events that have not previously been detected in AML. We show that the response to drugs is associated with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA sequencing also revealed gene expression signatures, which predict a role for specific gene networks in the drug response. Collectively, we have generated a dataset-accessible through the Beat AML data viewer (Vizome)-that can be leveraged to address clinical, genomic, transcriptomic and functional analyses of the biology of AML.

Secondary fusion proteins as a mechanism of BCR::ABL1 kinase-independent resistance in chronic myeloid leukaemia.

Drug resistance in chronic myeloid leukaemia (CML) may occur via mutations in the causative BCR::ABL1 fusion or BCR::ABL1-independent mechanisms. We analysed 48 patients with BCR::ABL1-independent resistance for the presence of secondary fusion genes by RNA sequencing. We identified 10 of the most frequently detected secondary fusions in 21 patients. Validation studies, cell line models, gene expression analysis and drug screening revealed differences with respect to proliferation rate, differentiation and drug sensitivity. Notably, expression of RUNX1::MECOM led to resistance to ABL1 tyrosine kinase inhibitors in vitro. These results suggest secondary fusions contribute to BCR::ABL1-independent resistance and may be amenable to combined therapies.

Discovery and characterization of targetable NTRK point mutations in hematologic neoplasms.

Much of what is known about the neurotrophic receptor tyrosine kinase (NTRK) genes in cancer was revealed through identification and characterization of activating Trk fusions across many tumor types. A resurgence of interest in these receptors has emerged owing to the realization that they are promising therapeutic targets. The remarkable efficacy of pan-Trk inhibitors larotrectinib and entrectinib in clinical trials led to their accelerated, tissue-agnostic US Food and Drug Administration (FDA) approval for adult and pediatric patients with Trk-driven solid tumors. Despite our enhanced understanding of Trk biology in solid tumors, the importance of Trk signaling in hematological malignancies is underexplored and warrants further investigation. Herein, we describe mutations in NTRK2 and NTRK3 identified via deep sequencing of 185 patients with hematological malignancies. Ten patients contained a point mutation in NTRK2 or NTRK3; among these, we identified 9 unique point mutations. Of these 9 mutations, 4 were oncogenic (NTRK2A203T, NTRK2R458G, NTRK3E176D, and NTRK3L449F), determined via cytokine-independent cellular assays. Our data demonstrate that these mutations have transformative potential to promote downstream survival signaling and leukemogenesis. Specifically, the 3 mutations located within extracellular (ie, NTRK2A203T and NTRK3E176D) and transmembrane (ie, NTRK3L449F) domains increased receptor dimerization and cell-surface abundance. The fourth mutation, NTRK2R458G, residing in the juxtamembrane domain, activates TrkB via noncanonical mechanisms that may involve altered interactions between the mutant receptor and lipids in the surrounding environment. Importantly, these 4 activating mutations can be clinically targeted using entrectinib. Our findings contribute to ongoing efforts to define the mutational landscape driving hematological malignancies and underscore the utility of FDA-approved Trk inhibitors for patients with aggressive Trk-driven leukemias.

Genome-wide CRISPR screen identifies regulators of MAPK and MTOR pathways mediating sorafenib resistance in acute myeloid leukemia.

Drug resistance impedes the long-term effect of targeted therapies in acute myeloid leukemia (AML), necessitating the identification of mechanisms underlying resistance. Approximately 25% of AML patients carry FLT3 mutations and develop post-treatment insensitivity to FLT3 inhibitors, including sorafenib. Using a genome-wide CRISPR screen, we identified LZTR1, NF1, TSC1 or TSC2, negative regulators of the MAPK and MTOR pathways, as mediators of sorafenib resistance. Analyses of ex vivo drug sensitivity assays in FLT3-ITD AML patient samples revealed lower expression of LZTR1, NF1, and TSC2 correlated with sorafenib sensitivity. Importantly, MAPK and/or MTOR complex1 (MTORC1) activity were upregulated in AML cells made resistant to several FLT3 inhibitors, including crenolanib, quizartinib, or sorafenib. These cells were sensitive to MEK inhibitors, and the combination of FLT3 and MEK inhibitors showed enhanced efficacy, suggesting its effectiveness in AML patients with FLT3 mutations and those with resistance to FLT3 inhibitors.

Genomic landscape of neutrophilic leukemias of ambiguous diagnosis.

Chronic neutrophilic leukemia (CNL), atypical chronic myeloid leukemia (aCML), and myelodysplastic/myeloproliferative neoplasms, unclassifiable (MDS/MPN-U) are a group of rare and heterogeneous myeloid disorders. There is strong morphologic resemblance among these distinct diagnostic entities as well as a lack of specific molecular markers and limited understanding of disease pathogenesis, which has made diagnosis challenging in certain cases. The treatment has remained empirical, resulting in dismal outcomes. We, therefore, performed whole-exome and RNA sequencing of these rare hematologic malignancies and present the most complete survey of the genomic landscape of these diseases to date. We observed a diversity of combinatorial mutational patterns that generally do not cluster within any one diagnosis. Gene expression analysis reveals enrichment, but not cosegregation, of clinical and genetic disease features with transcriptional clusters. In conclusion, these groups of diseases represent a continuum of related diseases rather than discrete diagnostic entities.

HitWalker2: visual analytics for precision medicine and beyond.

UNLABELLED: The lack of visualization frameworks to guide interpretation and facilitate discovery is a potential bottleneck for precision medicine, systems genetics and other studies. To address this we have developed an interactive, reproducible, web-based prioritization approach that builds on our earlier work. HitWalker2 is highly flexible and can utilize many data types and prioritization methods based upon available data and desired questions, allowing it to be utilized in a diverse range of studies such as cancer, infectious disease and psychiatric disorders. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/biodev/HitWalker2 and implemented using Python/Django, Neo4j and Javascript (D3.js and jQuery). We support major open source browsers (e.g. Firefox and Chromium/Chrome). CONTACT: wilmotb@ohsu.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Additional information/instructions are available at https://github.com/biodev/HitWalker2/wiki.

Oncogenic CSF3R mutations in chronic neutrophilic leukemia and atypical CML.

BACKGROUND: The molecular causes of many hematologic cancers remain unclear. Among these cancers are chronic neutrophilic leukemia (CNL) and atypical (BCR-ABL1-negative) chronic myeloid leukemia (CML), both of which are diagnosed on the basis of neoplastic expansion of granulocytic cells and exclusion of genetic drivers that are known to occur in other myeloproliferative neoplasms and myeloproliferative-myelodysplastic overlap neoplasms. METHODS: To identify potential genetic drivers in these disorders, we used an integrated approach of deep sequencing coupled with the screening of primary leukemia cells obtained from patients with CNL or atypical CML against panels of tyrosine kinase-specific small interfering RNAs or small-molecule kinase inhibitors. We validated candidate oncogenes using in vitro transformation assays, and drug sensitivities were validated with the use of assays of primary-cell colonies. RESULTS: We identified activating mutations in the gene encoding the receptor for colony-stimulating factor 3 (CSF3R) in 16 of 27 patients (59%) with CNL or atypical CML. These mutations segregate within two distinct regions of CSF3R and lead to preferential downstream kinase signaling through SRC family-TNK2 or JAK kinases and differential sensitivity to kinase inhibitors. A patient with CNL carrying a JAK-activating CSF3R mutation had marked clinical improvement after the administration of the JAK1/2 inhibitor ruxolitinib. CONCLUSIONS: Mutations in CSF3R are common in patients with CNL or atypical CML and represent a potentially useful criterion for diagnosing these neoplasms. (Funded by the Leukemia and Lymphoma Society and others.).

plethy: management of whole body plethysmography data in R.

BACKGROUND: Characterization of respiratory phenotypes can enhance complex trait and genomic studies involving allergic/autoimmune and infectious diseases. Many aspects of respiration can be measured using devices known as plethysmographs that can measure thoracic movement. One such approach (the Buxco platform) performs unrestrained whole body plethysmography on mice which infers thoracic movements from pressure differences from the act of inhalation and exhalation. While proprietary software is available to perform basic statistical analysis as part of machine's bundled software, it is desirable to be able to incorporate these analyses into high-throughput pipelines and integrate them with other data types, as well as leverage the wealth of analytic and visualization approaches provided by the R statistical computing environment. RESULTS: This manuscript describes the plethy package which is an R/Bioconductor framework for pre-processing and analysis of plethysmography data with emphasis on larger scale longitudinal experiments. The plethy package was designed to facilitate quality control and exploratory data analysis. We provide a demonstration of the features of plethy using a dataset assessing the respiratory effects over time of SARS and Influenza infection in mice. CONCLUSION: The plethy package provides functionality for users to import, perform quality assessment and exploratory data analysis in a manner that allows interoperability with existing modelling tools. Our package is implemented in R and is freely available as part of the Bioconductor project http://www.bioconductor.org/packages/release/bioc/html/plethy.html .

Modeling host genetic regulation of influenza pathogenesis in the collaborative cross.

Genetic variation contributes to host responses and outcomes following infection by influenza A virus or other viral infections. Yet narrow windows of disease symptoms and confounding environmental factors have made it difficult to identify polymorphic genes that contribute to differential disease outcomes in human populations. Therefore, to control for these confounding environmental variables in a system that models the levels of genetic diversity found in outbred populations such as humans, we used incipient lines of the highly genetically diverse Collaborative Cross (CC) recombinant inbred (RI) panel (the pre-CC population) to study how genetic variation impacts influenza associated disease across a genetically diverse population. A wide range of variation in influenza disease related phenotypes including virus replication, virus-induced inflammation, and weight loss was observed. Many of the disease associated phenotypes were correlated, with viral replication and virus-induced inflammation being predictors of virus-induced weight loss. Despite these correlations, pre-CC mice with unique and novel disease phenotype combinations were observed. We also identified sets of transcripts (modules) that were correlated with aspects of disease. In order to identify how host genetic polymorphisms contribute to the observed variation in disease, we conducted quantitative trait loci (QTL) mapping. We identified several QTL contributing to specific aspects of the host response including virus-induced weight loss, titer, pulmonary edema, neutrophil recruitment to the airways, and transcriptional expression. Existing whole-genome sequence data was applied to identify high priority candidate genes within QTL regions. A key host response QTL was located at the site of the known anti-influenza Mx1 gene. We sequenced the coding regions of Mx1 in the eight CC founder strains, and identified a novel Mx1 allele that showed reduced ability to inhibit viral replication, while maintaining protection from weight loss.

The genetics of gene expression in complex mouse crosses as a tool to study the molecular underpinnings of behavior traits.

Complex Mus musculus crosses provide increased resolution to examine the relationships between gene expression and behavior. While the advantages are clear, there are numerous analytical and technological concerns that arise from the increased genetic complexity that must be considered. Each of these issues is discussed, providing an initial framework for complex cross study design and planning.

HitWalker: variant prioritization for personalized functional cancer genomics.

SUMMARY: Determining the functional relevance of identified sequence variants in cancer is a prerequisite to ultimately matching specific therapies with individual patients. This level of mechanistic understanding requires integration of genomic information with complementary functional analyses to identify oncogenic targets and relies on the development of computational frameworks to aid in the prioritization and visualization of these diverse data types. In response to this, we have developed HitWalker, which prioritizes patient variants relative to their weighted proximity to functional assay results in a protein-protein interaction network. It is highly extensible, allowing incorporation of diverse data types to refine prioritization. In addition to a ranked list of variants, we have also devised a simple shortest path-based approach of visualizing the results in an intuitive manner to provide biological interpretation. AVAILABILITY AND IMPLEMENTATION: The program, documentation and example data are available as an R package from www.biodevlab.org/HitWalker.html.

Just how transformative will AI/ML be for immuno-oncology?

Immuno-oncology involves the study of approaches which harness the patient's immune system to fight malignancies. Immuno-oncology, as with every other biomedical and clinical research field as well as clinical operations, is in the midst of technological revolutions, which vastly increase the amount of available data. Recent advances in artificial intelligence and machine learning (AI/ML) have received much attention in terms of their potential to harness available data to improve insights and outcomes in many areas including immuno-oncology. In this review, we discuss important aspects to consider when evaluating the potential impact of AI/ML applications in the clinic. We highlight four clinical/biomedical challenges relevant to immuno-oncology and how they may be able to be addressed by the latest advancements in AI/ML. These challenges include (1) efficiency in clinical workflows, (2) curation of high-quality image data, (3) finding, extracting and synthesizing text knowledge as well as addressing, and (4) small cohort size in immunotherapeutic evaluation cohorts. Finally, we outline how advancements in reinforcement and federated learning, as well as the development of best practices for ethical and unbiased data generation, are likely to drive future innovations.

Targeting CCL2/CCR2 Signaling Overcomes MEK Inhibitor Resistance in Acute Myeloid Leukemia.

PURPOSE: Emerging evidence underscores the critical role of extrinsic factors within the microenvironment in protecting leukemia cells from therapeutic interventions, driving disease progression, and promoting drug resistance in acute myeloid leukemia (AML). This finding emphasizes the need for the identification of targeted therapies that inhibit intrinsic and extrinsic signaling to overcome drug resistance in AML. EXPERIMENTAL DESIGN: We performed a comprehensive analysis utilizing a cohort of ∼300 AML patient samples. This analysis encompassed the evaluation of secreted cytokines/growth factors, gene expression, and ex vivo drug sensitivity to small molecules. Our investigation pinpointed a notable association between elevated levels of CCL2 and diminished sensitivity to the MEK inhibitors (MEKi). We validated this association through loss-of-function and pharmacologic inhibition studies. Further, we deployed global phosphoproteomics and CRISPR/Cas9 screening to identify the mechanism of CCR2-mediated MEKi resistance in AML. RESULTS: Our multifaceted analysis unveiled that CCL2 activates multiple prosurvival pathways, including MAPK and cell-cycle regulation in MEKi-resistant cells. Employing combination strategies to simultaneously target these pathways heightened growth inhibition in AML cells. Both genetic and pharmacologic inhibition of CCR2 sensitized AML cells to trametinib, suppressing proliferation while enhancing apoptosis. These findings underscore a new role for CCL2 in MEKi resistance, offering combination therapies as an avenue to circumvent this resistance. CONCLUSIONS: Our study demonstrates a compelling rationale for translating CCL2/CCR2 axis inhibitors in combination with MEK pathway-targeting therapies, as a potent strategy for combating drug resistance in AML. This approach has the potential to enhance the efficacy of treatments to improve AML patient outcomes.

Utilizing RNA-Seq data for de novo coexpression network inference.

MOTIVATION: RNA-Seq experiments have shown great potential for transcriptome profiling. While sequencing increases the level of biological detail, integrative data analysis is also important. One avenue is the construction of coexpression networks. Because the capacity of RNA-Seq data for network construction has not been previously evaluated, we constructed a coexpression network using striatal samples, derived its network properties and compared it with microarray-based networks. RESULTS: The RNA-Seq coexpression network displayed scale-free, hierarchical network structure. We detected transcripts groups (modules) with correlated profiles; modules overlap distinct ontology categories. Neuroanatomical data from the Allen Brain Atlas reveal several modules with spatial colocalization. The network was compared with microarray-derived networks; correlations from RNA-Seq data were higher, likely because greater sensitivity and dynamic range. Higher correlations result in higher network connectivity, heterogeneity and centrality. For transcripts present across platforms, network structure appeared largely preserved. From this study, we present the first RNA-Seq data de novo network inference.

Immune cell proportions correlate with clinicogenomic features and ex vivo drug responses in acute myeloid leukemia.

Introduction: The implementation of small-molecule and immunotherapies in acute myeloid leukemia (AML) has been challenging due to genetic and epigenetic variability amongst patients. There are many potential mechanisms by which immune cells could influence small-molecule or immunotherapy responses, yet, this area remains understudied. Methods: Here we performed cell type enrichment analysis from over 560 AML patient bone marrow and peripheral blood samples from the Beat AML dataset to describe the functional immune landscape of AML. Results: We identify multiple cell types that significantly correlate with AML clinical and genetic features, and we also observe significant correlations of immune cell proportions with ex vivo small-molecule and immunotherapy responses. Additionally, we generated a signature of terminally exhausted T cells (Tex) and identified AML with high monocytic proportions as strongly correlating with increased proportions of these immunosuppressive T cells. Discussion: Our work, which is accessible through a new "Cell Type" module in our visualization platform (Vizome; http://vizome.org/), can be leveraged to investigate potential contributions of different immune cells on many facets of the biology of AML.

Comparison and validation of the 2022 European LeukemiaNet guidelines in acute myeloid leukemia.

Risk stratification in acute myeloid leukemia (AML) remains principle in survival prognostication and treatment selection. The 2022 European LeukemiaNet (ELN) recommendations were recently published, with notable updates to risk group assignment. The complexity of risk stratification and comparative outcomes between the 2022 and 2017 ELN guidelines remains unknown. This comparative analysis evaluated outcomes between the 2017 and 2022 ELN criteria in patients enrolled within the multicenter Beat AML cohort. Five hundred thirteen patients were included. Most patients had 1 or 2 ELN risk-defining abnormalities. In patients with ≥2 ELN risk-defining mutations, 44% (n = 132) had mutations spanning multiple ELN risk categories. Compared with ELN 2017 criteria, the updated ELN 2022 guidelines changed the assigned risk group in 15% of patients, including 10%, 26%, and 6% of patients categorized as being at ELN 2017 favorable-, intermediate-, and adverse-risk, respectively. The median overall survival across ELN 2022 favorable-, intermediate-, and adverse-risk groups was not reached, 16.8, and 9.7 months, respectively. The ELN 2022 guidelines more accurately stratified survival between patients with intermediate- or adverse-risk AML treated with induction chemotherapy compared with ELN 2017 guidelines. The updated ELN 2022 guidelines better stratify survival between patients with intermediate- or adverse-risk AML treated with induction chemotherapy. The increased complexity of risk stratification with inclusion of additional cytogenetic and molecular aberrations necessitates clinical workflows simplifying risk stratification.