Comparing malignant monocytosis across the updated WHO and ICC classifications of 2022.

ABSTRACT: The World Health Organization (WHO) classification of hematolymphoid tumors and the International Consensus Classification (ICC) of 2022 introduced major changes to the definition of chronic myelomonocytic leukemia (CMML). To assess its qualitative and quantitative implications for patient care, we started with 3311 established CMML cases (according to WHO 2017 criteria) and included 2130 oligomonocytosis cases fulfilling the new CMML diagnostic criteria. Applying both 2022 classification systems, 356 and 241 of oligomonocytosis cases were newly classified as myelodysplastic (MD)-CMML (WHO and ICC 2022, respectively), most of which were diagnosed as myelodysplastic syndrome (MDS) according to the WHO 2017 classification. Importantly, 1.5 times more oligomonocytosis cases were classified as CMML according to WHO 2022 than based on ICC, because of different diagnostic criteria. Genetic analyses of the newly classified CMML cases showed a distinct mutational profile with strong enrichment of MDS-typical alterations, resulting in a transcriptional subgroup separated from established MD and myeloproliferative CMML. Despite a different cytogenetic, molecular, immunophenotypic, and transcriptional landscape, no differences in overall survival were found between newly classified and established MD-CMML cases. To the best of our knowledge, this study represents the most comprehensive analysis of routine CMML cases to date, both in terms of clinical characterization and transcriptomic analysis, placing newly classified CMML cases on a disease continuum between MDS and previously established CMML.

A lineage-specific STAT5BN642H mouse model to study NK-cell leukemia.

ABSTRACT: Patients with T- and natural killer (NK)-cell neoplasms frequently have somatic STAT5B gain-of-function mutations. The most frequent STAT5B mutation is STAT5BN642H, which is known to drive murine T-cell leukemia, although its role in NK-cell malignancies is unclear. Introduction of the STAT5BN642H mutation into human NK-cell lines enhances their potential to induce leukemia in mice. We have generated a mouse model that enables tissue-specific expression of STAT5BN642H and have selectively expressed the mutated STAT5B in hematopoietic cells (N642Hvav/+) or exclusively in NK cells (N642HNK/NK). All N642Hvav/+ mice rapidly develop an aggressive T/NKT-cell leukemia, whereas N642HNK/NK mice display an indolent NK-large granular lymphocytic leukemia (NK-LGLL) that progresses to an aggressive leukemia with age. Samples from patients with NK-cell leukemia have a distinctive transcriptional signature driven by mutant STAT5B, which overlaps with that of murine leukemic N642HNK/NK NK cells. To our knowledge, we have generated the first reliable STAT5BN642H-driven preclinical mouse model that displays an indolent NK-LGLL progressing to aggressive NK-cell leukemia. This novel in vivo tool will enable us to explore the transition from an indolent to an aggressive disease and will thus permit the study of prevention and treatment options for NK-cell malignancies.

Tumor necrosis factor α promotes clonal dominance of KIT D816V+ cells in mastocytosis: role of survivin and impact on prognosis.

ABSTRACT: Systemic mastocytosis (SM) is defined by the expansion and accumulation of neoplastic mast cells (MCs) in the bone marrow (BM) and extracutaneous organs. Most patients harbor a somatic KIT D816V mutation, which leads to growth factor-independent KIT activation and accumulation of MC. Tumor necrosis factor α (TNF) is a proapoptotic and inflammatory cytokine that has been implicated in the clonal selection of neoplastic cells. We found that KIT D816V increases the expression and secretion of TNF. TNF expression in neoplastic MCs is reduced by KIT-targeting drugs. Similarly, knockdown of KIT or targeting the downstream signaling cascade of MAPK and NF-κB signaling reduced TNF expression levels. TNF reduces colony formation in human BM cells, whereas KIT D816V+ cells are less susceptible to the cytokine, potentially contributing to clonal selection. In line, knockout of TNF in neoplastic MC prolonged survival and reduced myelosuppression in a murine xenotransplantation model. Mechanistic studies revealed that the relative resistance of KIT D816V+ cells to TNF is mediated by the apoptosis-regulator BIRC5 (survivin). Expression of BIRC5 in neoplastic MC was confirmed by immunohistochemistry of samples from patients with SM. TNF serum levels are significantly elevated in patients with SM and high TNF levels were identified as a biomarker associated with inferior survival. We here characterized TNF as a KIT D816V-dependent cytokine that promotes clonal dominance. We propose TNF and apoptosis-associated proteins as potential therapeutic targets in SM.

Developmental trajectories and cooperating genomic events define molecular subtypes of BCR::ABL1-positive ALL.

ABSTRACT: Distinct diagnostic entities within BCR::ABL1-positive acute lymphoblastic leukemia (ALL) are currently defined by the International Consensus Classification of myeloid neoplasms and acute leukemias (ICC): "lymphoid only", with BCR::ABL1 observed exclusively in lymphatic precursors, vs "multilineage", where BCR::ABL1 is also present in other hematopoietic lineages. Here, we analyzed transcriptomes of 327 BCR::ABL1-positive patients with ALL (age, 2-84 years; median, 46 years) and identified 2 main gene expression clusters reproducible across 4 independent patient cohorts. Fluorescence in situ hybridization analysis of fluorescence-activated cell-sorted hematopoietic compartments showed distinct BCR::ABL1 involvement in myeloid cells for these clusters (n = 18/18 vs n = 3/16 patients; P < .001), indicating that a multilineage or lymphoid BCR::ABL1 subtype can be inferred from gene expression. Further subclusters grouped samples according to cooperating genomic events (multilineage: HBS1L deletion or monosomy 7; lymphoid: IKZF1-/- or CDKN2A/PAX5 deletions/hyperdiploidy). A novel HSB1L transcript was highly specific for BCR::ABL1 multilineage cases independent of HBS1L genomic aberrations. Treatment on current German Multicenter Study Group for Adult ALL (GMALL) protocols resulted in comparable disease-free survival (DFS) for multilineage vs lymphoid cluster patients (3-year DFS: 70% vs 61%; P = .530; n = 91). However, the IKZF1-/- enriched lymphoid subcluster was associated with inferior DFS, whereas hyperdiploid cases showed a superior outcome. Thus, gene expression clusters define underlying developmental trajectories and distinct patterns of cooperating events in BCR::ABL1-positive ALL with prognostic relevance.

Enhancer retargeting of CDX2 and UBTF::ATXN7L3 define a subtype of high-risk B-progenitor acute lymphoblastic leukemia.

Transcriptome sequencing has identified multiple subtypes of B-progenitor acute lymphoblastic leukemia (B-ALL) of prognostic significance, but a minority of cases lack a known genetic driver. Here, we used integrated whole-genome (WGS) and -transcriptome sequencing (RNA-seq), enhancer mapping, and chromatin topology analysis to identify previously unrecognized genomic drivers in B-ALL. Newly diagnosed (n = 3221) and relapsed (n = 177) B-ALL cases with tumor RNA-seq were studied. WGS was performed to detect mutations, structural variants, and copy number alterations. Integrated analysis of histone 3 lysine 27 acetylation and chromatin looping was performed using HiChIP. We identified a subset of 17 newly diagnosed and 5 relapsed B-ALL cases with a distinct gene expression profile and 2 universal and unique genomic alterations resulting from aberrant recombination-activating gene activation: a focal deletion downstream of PAN3 at 13q12.2 resulting in CDX2 deregulation by the PAN3 enhancer and a focal deletion of exons 18-21 of UBTF at 17q21.31 resulting in a chimeric fusion, UBTF::ATXN7L3. A subset of cases also had rearrangement and increased expression of the PAX5 gene, which is otherwise uncommon in B-ALL. Patients were more commonly female and young adult with median age 35 (range,12-70 years). The immunophenotype was characterized by CD10 negativity and immunoglobulin M positivity. Among 16 patients with known clinical response, 9 (56.3%) had high-risk features including relapse (n = 4) or minimal residual disease >1% at the end of remission induction (n = 5). CDX2-deregulated, UBTF::ATXN7L3 rearranged (CDX2/UBTF) B-ALL is a high-risk subtype of leukemia in young adults for which novel therapeutic approaches are required.

Next-generation diagnostics for precision oncology: Preanalytical considerations, technical challenges, and available technologies.

Molecular diagnostics as the centrepiece of precision oncology has gone through revolutionary developments over the last decade, becoming tremendously broad, deep and precise with still ongoing advancements. In the majority of scenarios, treatment selection for cancer patients without any type of molecular characterization is no longer conceivable. Considering the impact of sample quality on the reliability of molecular analyses and the importance of the results for the fate of an individual patient, it is surprising how sparsely preanalytical and analytical requirements are addressed scientifically. Standardization and rigorous quality assessment continue to play only a marginal role in the field. Within this review, we will systematically discuss influencing preanalytic parameters and technology setups affecting molecular test results. We will shed light on the specifics of different analytes, technical modalities, and analysis pipelines. The review will have a certain focus on broad molecular genetic tumour testing with next generation sequencing but will go beyond that including other molecular diagnostic modalities and will give a glimpse into the future of molecular testing.

Massive parallel sequencing unveils homologous recombination deficiency in follicular dendritic cell sarcoma.

Standardized treatment options are lacking for patients with unresectable or multifocal follicular dendritic cell sarcoma (FDCS) and disease-related mortality is as high as 20%. Applying whole genome sequencing (WGS) in one case and whole exome sequencing (WES) in additional twelve, this study adds information on the molecular landscape of FDCS, expanding knowledge on pathobiological mechanisms and identifying novel markers of potential theragnostic significance. Massive parallel sequencing showed high frequency of mutations on oncosuppressor genes, particularly in RB1, CARS and BRCA2 and unveiled alterations on homologous recombination DNA damage repair related genes in 70% (9/13) of cases. This indicates that patients with high stage FDCS may be eligible for poly ADP ribose polymerase inhibition protocols. Low tumor mutational burden was confirmed in this study despite common PDL1 expression in FDCS arguing on the efficacy of immune checkpoint inhibitors. CDKN2A deletion, detected by WGS and confirmed by FISH in 41% of cases (9/22) indicates that impairment of cell cycle regulation may sustain oncogenesis in FDCS. Absence of mutations in the RAS/RAF/MAPK pathway and lack of clonal hematopoiesis related mutations in FDCS sanction its differences from dendritic cell-derived neoplasms of haematopoietic derivation. WGS and WES in FDCS provides additional information on the molecular landscape of this rare tumor, proposing novel candidate genes for innovative therapeutical approaches to improve survival of patients with multifocal disease.

Clinical application of whole transcriptome sequencing for the classification of patients with acute lymphoblastic leukemia.

BACKGROUND: Considering the clinical and genetic characteristics, acute lymphoblastic leukemia (ALL) is a rather heterogeneous hematological neoplasm for which current standard diagnostics require various analyses encompassing morphology, immunophenotyping, cytogenetics, and molecular analysis of gene fusions and mutations. Hence, it would be desirable to rely on a technique and an analytical workflow that allows the simultaneous analysis and identification of all the genetic alterations in a single approach. Moreover, based on the results with standard methods, a significant amount of patients have no established abnormalities and hence, cannot further be stratified. METHODS: We performed WTS and WGS in 279 acute lymphoblastic leukemia (ALL) patients (B-cell: n = 211; T-cell: n = 68) to assess the accuracy of WTS, to detect relevant genetic markers, and to classify ALL patients. RESULTS: DNA and RNA-based genotyping was used to ensure correct WTS-WGS pairing. Gene expression analysis reliably assigned samples to the B Cell Precursor (BCP)-ALL or the T-ALL group. Subclassification of BCP-ALL samples was done progressively, assessing first the presence of chromosomal rearrangements by the means of fusion detection. Compared to the standard methods, 97% of the recurrent risk-stratifying fusions could be identified by WTS, assigning 76 samples to their respective entities. Additionally, read-through fusions (indicative of CDKN2A and RB1 gene deletions) were recurrently detected in the cohort along with 57 putative novel fusions, with yet untouched diagnostic potentials. Next, copy number variations were inferred from WTS data to identify relevant ploidy groups, classifying an additional of 31 samples. Lastly, gene expression profiling detected a BCR-ABL1-like signature in 27% of the remaining samples. CONCLUSION: As a single assay, WTS allowed a precise genetic classification for the majority of BCP-ALL patients, and is superior to conventional methods in the cases which lack entity defining genetic abnormalities.

Dark-matter matters: Discriminating subtle blood cancers using the darkest DNA.

The confluence of deep sequencing and powerful machine learning is providing an unprecedented peek at the darkest of the dark genomic matter, the non-coding genomic regions lacking any functional annotation. While deep sequencing uncovers rare tumor variants, the heterogeneity of the disease confounds the best of machine learning (ML) algorithms. Here we set out to answer if the dark-matter of the genome encompass signals that can distinguish the fine subtypes of disease that are otherwise genomically indistinguishable. We introduce a novel stochastic regularization, ReVeaL, that empowers ML to discriminate subtle cancer subtypes even from the same 'cell of origin'. Analogous to heritability, implicitly defined on whole genome, we use predictability (F1 score) definable on portions of the genome. In an effort to distinguish cancer subtypes using dark-matter DNA, we applied ReVeaL to a new WGS dataset from 727 patient samples with seven forms of hematological cancers and assessed the predictivity over several genomic regions including genic, non-dark, non-coding, non-genic, and dark. ReVeaL enabled improved discrimination of cancer subtypes for all segments of the genome. The non-genic, non-coding and dark-matter had the highest F1 scores, with dark-matter having the highest level of predictability. Based on ReVeaL's predictability of different genomic regions, dark-matter contains enough signal to significantly discriminate fine subtypes of disease. Hence, the agglomeration of rare variants, even in the hitherto unannotated and ill-understood regions of the genome, may play a substantial role in the disease etiology and deserve much more attention.

False-positive Candida and Aspergillus antigen testing in recipients of allogeneic haematopoietic cell transplantation due to administration of parenteral nutrition and fixed combinations of piperacillin-tazobactam.

False positivity of antigen immunoassays used as an early diagnostic tool to detect invasive fungal infections is known. Interpretation of the assay needs the identification of sources which could affect the specificity of the test. We focused on the influence of parenteral nutrition (PN) and piperacillin-tazobactam (TZP) on fungal immunoassays. Measurable amounts of Candida antigen mannan were detected in several compounds of PN and TZP in a previous in vitro study. In the current study, 84 patients undergoing allogeneic haematopoietic cell transplantation receiving either TZP, PN or both were monitored with Aspergillus and Candida antigen assay. Six patients were analysed closer in a kinetic analysis with more frequent blood sampling to detect mannan. PN in diverse compositions as well as TZP did not increase significantly the amount of mannan and the Aspergillus antigen in serum. We could not confirm the positive results of the in vitro study. Physicians should be aware that mannan antigenemia due to drug infusion could be a transient issue and should be considered in the interpretation of fungal immunoassays, although we could not find clinically relevant effects on mannan levels.

In vitro detection of Candida and Aspergillus antigen in parenteral nutrition and fixed combinations of piperacillin-tazobactam.

BACKGROUND: Screening for Aspergillus (Asp-AG) and Candida antigen (Ca-AG) with immunoassays is established for stem cell recipients at high risk for invasive fungal infections (IFI). While parenteral nutrition (PN) will be applied in case of complications leading to insufficient alimentation, piperacillin-tazobactam (TZP) is started at the onset of febrile neutropenia. OBJECTIVES: The aim of this study was to investigate drug-laboratory interactions between PN and TZP and both immunoassays which could affect the specificity of the assays and lead to the false assumption of an IFI. METHODS: Batches of TZP and PN were tested with both assays in vitro. In total, 380 samples of 83 batches were analysed. RESULTS: None of the examined preparations were tested positive with Asp-AG assay. Measurable amounts of Ca-AG were detected in a lipid emulsion, two different trace element supplements, a fat-soluble vitamin preparation and all tested brands of TZP. CONCLUSIONS: We conclude that false positivity of Asp-AG assay due to TZP and PN does not occur. Cross reactions with Ca-AG assay have been detected in some preparations. The in vivo relevance of Ca-AG positivity has to be reviewed in further studies considering an effect of dilution. Physicians should be aware of a possible cross reaction with Ca-AG assays which could lead to false-positive results.

GOplot: an R package for visually combining expression data with functional analysis.

UNLABELLED: Despite the plethora of methods available for the functional analysis of omics data, obtaining comprehensive-yet detailed understanding of the results remains challenging. This is mainly due to the lack of publicly available tools for the visualization of this type of information. Here we present an R package called GOplot, based on ggplot2, for enhanced graphical representation. Our package takes the output of any general enrichment analysis and generates plots at different levels of detail: from a general overview to identify the most enriched categories (bar plot, bubble plot) to a more detailed view displaying different types of information for molecules in a given set of categories (circle plot, chord plot, cluster plot). The package provides a deeper insight into omics data and allows scientists to generate insightful plots with only a few lines of code to easily communicate the findings. AVAILABILITY AND IMPLEMENTATION: The R package GOplot is available via CRAN-The Comprehensive R Archive Network: http://cran.r-project.org/web/packages/GOplot. The shiny web application of the Venn diagram can be found at: https://wwalter.shinyapps.io/Venn/. A detailed manual of the package with sample figures can be found at https://wencke.github.io/ CONTACT: fscabo@cnic.es or mricote@cnic.es.

Improving the accuracy of expression data analysis in time course experiments using resampling.

BACKGROUND: As time series experiments in higher eukaryotes usually obtain data from different individuals collected at the different time points, a time series sample itself is not equivalent to a true biological replicate but is, rather, a combination of several biological replicates. The analysis of expression data derived from a time series sample is therefore often performed with a low number of replicates due to budget limitations or limitations in sample availability. In addition, most algorithms developed to identify specific patterns in time series dataset do not consider biological variation in samples collected at the same conditions. RESULTS: Using artificial time course datasets, we show that resampling considerably improves the accuracy of transcripts identified as rhythmic. In particular, the number of false positives can be greatly reduced while at the same time the number of true positives can be maintained in the range of other methods currently used to determine rhythmically expressed genes. CONCLUSIONS: The resampling approach described here therefore increases the accuracy of time series expression data analysis and furthermore emphasizes the importance of biological replicates in identifying oscillating genes. Resampling can be used for any time series expression dataset as long as the samples are acquired from independent individuals at each time point.

Collaborative effect of Csnk1a1 haploinsufficiency and mutant p53 in Myc induction can promote leukemic transformation.

ABSTRACT: It is still not fully understood how genetic haploinsufficiency in del(5q) myelodysplastic syndrome (MDS) contributes to malignant transformation of hematopoietic stem cells. We asked how compound haploinsufficiency for Csnk1a1 and Egr1 in the common deleted region on chromosome 5 affects hematopoietic stem cells. Additionally, Trp53 was disrupted as the most frequently comutated gene in del(5q) MDS using CRISPR/Cas9 editing in hematopoietic progenitors of wild-type (WT), Csnk1a1-/+, Egr1-/+, Csnk1a1/Egr1-/+ mice. A transplantable acute leukemia only developed in the Csnk1a1-/+Trp53-edited recipient. Isolated blasts were indefinitely cultured ex vivo and gave rise to leukemia after transplantation, providing a tool to study disease mechanisms or perform drug screenings. In a small-scale drug screening, the collaborative effect of Csnk1a1 haploinsufficiency and Trp53 sensitized blasts to the CSNK1 inhibitor A51 relative to WT or Csnk1a1 haploinsufficient cells. In vivo, A51 treatment significantly reduced blast counts in Csnk1a1 haploinsufficient/Trp53 acute leukemias and restored hematopoiesis in the bone marrow. Transcriptomics on blasts and their normal counterparts showed that the derived leukemia was driven by MAPK and Myc upregulation downstream of Csnk1a1 haploinsufficiency cooperating with a downregulated p53 axis. A collaborative effect of Csnk1a1 haploinsufficiency and p53 loss on MAPK and Myc upregulation was confirmed on the protein level. Downregulation of Myc protein expression correlated with efficient elimination of blasts in A51 treatment. The "Myc signature" closely resembled the transcriptional profile of patients with del(5q) MDS with TP53 mutation.

The E592K variant of SF3B1 creates unique RNA missplicing and associates with high-risk MDS without ring sideroblasts.

Among the most common genetic alterations in the myelodysplastic syndromes (MDS) are mutations in the spliceosome gene SF3B1. Such mutations induce specific RNA missplicing events, directly promote ring sideroblast (RS) formation, and generally associate with more favorable prognosis. However, not all SF3B1 mutations are the same, and little is known about how distinct hotspots influence disease. Here we report that the E592K variant of SF3B1 associates with high-risk disease features in MDS, including a lack of RS, increased myeloblasts, a distinct co-mutation pattern, and a lack of the favorable survival seen with other SF3B1 mutations. Moreover, compared to other hotspot SF3B1 mutations, E592K induces a unique RNA missplicing pattern, retains an interaction with the splicing factor SUGP1, and preserves normal RNA splicing of the sideroblastic anemia genes TMEM14C and ABCB7. These data have implications for our understanding of the functional diversity of spliceosome mutations, as well as the pathobiology, classification, prognosis, and management of SF3B1-mutant MDS.

Challenging gold standard hematology diagnostics through the introduction of whole genome sequencing and artificial intelligence.

The diagnosis of hematological malignancies is rather complex and requires the application of a plethora of different assays, techniques and methodologies. Some of the methods, like cytomorphology, have been in use for decades, while other methods, such as next-generation sequencing or even whole genome sequencing (WGS), are relatively new. The application of the methods and the evaluation of the results require distinct skills and knowledge and place different demands on the practitioner. However, even with experienced hematologists, diagnostic ambiguity remains a regular occurrence and the comprehensive analysis of high-dimensional WGS data soon exceeds any human's capacity. Hence, in order to reduce inter-observer variability and to improve the timeliness and accuracy of diagnoses, machine learning based approaches have been developed to assist in the decision making process. Moreover, to achieve the goal of precision oncology, comprehensive genomic profiling is increasingly being incorporated into routine standard of care.

Identification of a specific immunophenotype associated with a consistent pattern of genetic mutations including SRFS2 and gene expression profile in MDS.

BACKGROUND: Myelodysplastic syndromes (MDS) comprise a heterogeneous group of diseases classified by comprehensive diagnostics. Identification of homogeneous subgroups is desirable to understand differences in clinical course and to develop targeted treatment approaches. We identified a specific CD11b/CD16 expression pattern in granulocytes associated with reduced CD45 expression in myeloid progenitor cells (MPC) in MDS cases and assessed its genetic background by whole genome (WGS) and whole transcriptome sequencing (WTS). METHODS: The cohort consisted of 32 MDS cases with the specific aberrant immunophenotype. Since all these 32 cases were found to be SRSF2 mutated additional 51 SRSF2 mutated MDS cases without this specific immunophenotype were selected as controls. For all cases WGS and WTS were performed. RESULTS: The immunophenotype newly identified in SRSF2 mutated MDS patients is characterized (1) by a specific maturation pattern, i.e. an increase of CD11b expression without CD16 expression followed by an increase in CD16 expression without further CD11b expression and (2) by only dim CD45 expression of MPC. STAG2 mutations were exclusively found in MDS cases with the specific immunophenotype (17/32, 53% vs. 0%, p < 0.001). Hence, >50% of cases with the specific immunophenotype were characterized by co-mutations in SRSF2 and STAG2. In addition, cluster analysis revealed a specific gene expression profile of such cases. CONCLUSION: We here for the first time describe a specific immunophenotype which defines MDS cases with SRSF2 mutations and a consistent and specific mutational and gene expression profile. This comprehensive data warrants analysis of further such cases to assess the feasibility of defining a new sub-entity of MDS.

Artificial intelligence in hematological diagnostics: Game changer or gadget?

The future of clinical diagnosis and treatment of hematologic diseases will inevitably involve the integration of artificial intelligence (AI)-based systems into routine practice to support the hematologists' decision making. Several studies have shown that AI-based models can already be used to automatically differentiate cells, reliably detect malignant cell populations, support chromosome banding analysis, and interpret clinical variants, contributing to early disease detection and prognosis. However, even the best tool can become useless if it is misapplied or the results are misinterpreted. Therefore, in order to comprehensively judge and correctly apply newly developed AI-based systems, the hematologist must have a basic understanding of the general concepts of machine learning. In this review, we provide the hematologist with a comprehensive overview of various machine learning techniques, their current implementations and approaches in different diagnostic subfields (e.g., cytogenetics, molecular genetics), and the limitations and unresolved challenges of the systems.

Novel causative variants of VEXAS in UBA1 detected through whole genome transcriptome sequencing in a large cohort of hematological malignancies.

UBA1 is an X-linked gene and encodes an ubiquitin-activating enzyme. Three somatic mutations altering the alternative start codon (M41) in UBA1 in hematopoietic precursor cells have recently been described, resulting in a syndrome of severe inflammation, cytopenias, and the presence of intracellular vacuoles in hematopoietic precursors - termed VEXAS syndrome, a predominantly male disease. Here we present a patient with clinical features of VEXAS who harbored two novel somatic variants in UBA1 (I894S and N606I). To better understand the clinical relevance and biological consequences of non-M41 (UBA1non-M41) variants, we analyzed the whole genome and transcriptome data of 4168 patients with hematological malignancies and detected an additional 16 UBA1non-M41 putative somatic variants with a clear sex-bias in patients with myeloid malignancies. Patients diagnosed with myeloid malignancies carrying UBA1non-M41 putative somatic variants either had vacuoles or immunodysregulatory symptoms. Analysis of the transcriptome confirmed neutrophil activation in VEXAS patients compared to healthy controls but did not result in a specific transcriptomic signature of UBA1M41 patients in comparison with MDS patients. In summary, we have described multiple putative novel UBA1non-M41 variants in patients with various hematological malignancies expanding the genomic spectrum of VEXAS syndrome.