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Artificial intelligence (AI) is about to make itself indispensable in the health care sector. Examples of successful applications or promising approaches range from the application of pattern recognition software to pre-process and analyze digital medical images, to deep learning algorithms for subtype or disease classification, and digital twin technology and in silico clinical trials. Moreover, machine-learning techniques are used to identify patterns and anomalies in electronic health records and to perform ad-hoc evaluations of gathered data from wearable health tracking devices for deep longitudinal phenotyping. In the last years, substantial progress has been made in automated image classification, reaching even superhuman level in some instances. Despite the increasing awareness of the importance of the genetic context, the diagnosis in hematology is still mainly based on the evaluation of the phenotype. Either by the analysis of microscopic images of cells in cytomorphology or by the analysis of cell populations in bidimensional plots obtained by flow cytometry. Here, AI algorithms not only spot details that might escape the human eye, but might also identify entirely new ways of interpreting these images. With the introduction of high-throughput next-generation sequencing in molecular genetics, the amount of available information is increasing exponentially, priming the field for the application of machine learning approaches. The goal of all the approaches is to allow personalized and informed interventions, to enhance treatment success, to improve the timeliness and accuracy of diagnoses, and to minimize technically induced misclassifications. The potential of AI-based applications is virtually endless but where do we stand in hematology and how far can we go?

Chromosomal rearrangements are a frequent cause of oncogene deregulation in human malignancies. Overexpression of EVI1 is found in a subgroup of acute myeloid leukemia (AML) with 3q26 chromosomal rearrangements, which is often therapy resistant. In AMLs harboring a t(3;8)(q26;q24), we observed the translocation of a MYC super-enhancer ( MYC SE) to the EVI1 locus. We generated an in vitro model mimicking a patient-based t(3;8)(q26;q24) using CRISPR-Cas9 technology and demonstrated hyperactivation of EVI1 by the hijacked MYC SE. This MYC SE contains multiple enhancer modules, of which only one recruits transcription factors active in early hematopoiesis. This enhancer module is critical for EVI1 overexpression as well as enhancer-promoter interaction. Multiple CTCF binding regions in the MYC SE facilitate this enhancer-promoter interaction, which also involves a CTCF binding site upstream of the EVI1 promoter. We hypothesize that this CTCF site acts as an enhancer-docking site in t(3;8) AML. Genomic analyses of other 3q26-rearranged AML patient cells point to a common mechanism by which EVI1 uses this docking site to hijack enhancers active in early hematopoiesis. Chromosome rearrangements can be a cause of altered oncogene expression in cancer, such as a 3q26 translocation in some acute myeloid leukemias (AML) that leads to overexpression of EVI1. Here the authors engineer this rearrangement in a cell line and show that EVI1 overexpression is a result of ‘enhancer hijacking’ of the MYC superenhancer, which is facilitated by CTCF-mediated loops.

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.

Risk stratification is critical in the care of patients with myelodysplastic syndromes (MDS). Approximately 10% have a complex karyotype (CK), defined as more than two cytogenetic abnormalities, which is a highly adverse prognostic marker. However, CK-MDS can carry a wide range of chromosomal abnormalities and somatic mutations. To refine risk stratification of CK-MDS patients, we examined data from 359 CK-MDS patients shared by the International Working Group for MDS. Mutations were underrepresented with the exception of TP53 mutations, identified in 55% of patients. TP53 mutated patients had even fewer co-mutated genes but were enriched for the del(5q) chromosomal abnormality (p < 0.005), monosomal karyotype (p < 0.001), and high complexity, defined as more than 4 cytogenetic abnormalities (p < 0.001). Monosomal karyotype, high complexity, and TP53 mutation were individually associated with shorter overall survival, but monosomal status was not significant in a multivariable model. Multivariable survival modeling identified severe anemia (hemoglobin < 8.0 g/dL), NRAS mutation, SF3B1 mutation, TP53 mutation, elevated blast percentage (>10%), abnormal 3q, abnormal 9, and monosomy 7 as having the greatest survival risk. The poor risk associated with CK-MDS is driven by its association with prognostically adverse TP53 mutations and can be refined by considering clinical and karyotype features.

Myeloid neoplasms are characterized by frequent mutations in at least seven components of the spliceosome that have distinct roles in the process of pre-mRNA splicing. Hotspot mutations in SF3B1 , SRSF2 , U2AF1 and loss of function mutations in ZRSR2 have revealed widely different aberrant splicing signatures with little overlap. However, previous studies lacked the power necessary to identify commonly mis-spliced transcripts in heterogeneous patient cohorts. By performing RNA-Seq on bone marrow samples from 1258 myeloid neoplasm patients and 63 healthy bone marrow donors, we identified transcripts frequently mis-spliced by mutated splicing factors (SF), rare SF mutations with common alternative splicing (AS) signatures, and SF-dependent neojunctions. We characterized 17,300 dysregulated AS events using a pipeline designed to predict the impact of mis-splicing on protein function. Meta-splicing analysis revealed a pattern of reduced levels of retained introns among disease samples that was exacerbated in patients with splicing factor mutations. These introns share characteristics with “detained introns,” a class of introns that have been shown to promote differentiation by detaining pro-proliferative transcripts in the nucleus. In this study, we have functionally characterized 17,300 targets of mis-splicing by the SF mutations, identifying a common pathway by which AS may promote maintenance of a proliferative state.

In AML patients, recurrent mutations were shown to persist in remission, however, only some have a prognostic value and persistent mutations might therefore reflect a re-established premalignant state or truly active disease causing relapse. We aimed to dissect the nature of co-mutations in NPM1 mutated AML where the detection of NPM1 transcripts allows highly specific and sensitive detection of complete molecular remission (CMR). We analysed 150 consecutive patients who achieved CMR following intensive treatment by next generation sequencing on paired samples at diagnosis, CMR and relapse (38/150 patients). Patients with persistence or the acquisition of non-DTA (DNMT3A, TET2, ASXL1) mutations at CMR (23/150 patients, 15%) have a significantly worse prognosis (EFS HR = 2.7, p = 0.003; OS HR = 3.6, p = 0.012). Based on clonal evolution analysis of diagnostic, CMR and relapse samples, we redefine pre-malignant mutations and include IDH1, IDH2 and SRSF2 with the DTA genes in this newly defined group. Only the persistence or acquisition of CHOP-like (clonal hematopoiesis of oncogenic potential) mutations was significantly associated with an inferior outcome (EFS HR = 4.5, p = 0.0002; OS HR = 5.5, p = 0.002). Moreover, the detection of CHOP-like mutations at relapse was detrimental (HR = 4.5, p = 0.01). We confirmed these findings in a second independent whole genome sequencing cohort.

Jaroslaw Maciejewski, Seishi Ogawa and colleagues examine the clonal dynamics of myelodysplastic syndromes (MDS) by analyzing whole-exome and targeted sequencing data from a large patient collection. They find that progression steps previously defined by pathologic criteria are accompanied by distinct molecular changes, and they show that driver genes can be classified into molecular subtypes differentially associated with low-risk MDS, high-risk MDS or secondary acute myeloid leukemia. To elucidate differential roles of mutations in myelodysplastic syndromes (MDS), we investigated clonal dynamics using whole-exome and/or targeted sequencing of 699 patients, of whom 122 were analyzed longitudinally. Including the results from previous reports, we assessed a total of 2,250 patients for mutational enrichment patterns. During progression, the number of mutations, their diversity and clone sizes increased, with alterations frequently present in dominant clones with or without their sweeping previous clones. Enriched in secondary acute myeloid leukemia (sAML; in comparison to high-risk MDS), FLT3 , PTPN11 , WT1 , IDH1 , NPM1 , IDH2 and NRAS mutations (type 1) tended to be newly acquired, and were associated with faster sAML progression and a shorter overall survival time. Significantly enriched in high-risk MDS (in comparison to low-risk MDS), TP53 , GATA2 , KRAS , RUNX1 , STAG2 , ASXL1 , ZRSR2 and TET2 mutations (type 2) had a weaker impact on sAML progression and overall survival than type-1 mutations. The distinct roles of type-1 and type-2 mutations suggest their potential utility in disease monitoring.

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.

Myelodysplastic syndromes and related disorders (myelodysplasia) are a heterogeneous group of myeloid neoplasms showing deregulated blood cell production with evidence of myeloid dysplasia and a predisposition to acute myeloid leukaemia, whose pathogenesis is only incompletely understood. Here we report whole-exome sequencing of 29 myelodysplasia specimens, which unexpectedly revealed novel pathway mutations involving multiple components of the RNA splicing machinery, including U2AF35 , ZRSR2 , SRSF2 and SF3B1 . In a large series analysis, these splicing pathway mutations were frequent (∼45 to ∼85%) in, and highly specific to, myeloid neoplasms showing features of myelodysplasia. Conspicuously, most of the mutations, which occurred in a mutually exclusive manner, affected genes involved in the 3′-splice site recognition during pre-mRNA processing, inducing abnormal RNA splicing and compromised haematopoiesis. Our results provide the first evidence indicating that genetic alterations of the major splicing components could be involved in human pathogenesis, also implicating a novel therapeutic possibility for myelodysplasia. RNA-splicing defects in blood disorders Exome sequencing and analysis of myelodysplasia specimens identified frequent non-overlapping alterations in multiple components of the RNA splicing machinery, including mutations in U2AF35 , ZRSR2 , SRSF2 and SF3B1 . Most affected genes are involved in recognition of the 3′ splice site during pre-messenger RNA processing, and are thought to cause abnormal RNA splicing and compromised haematopoiesis. The results demonstrate the role of aberrant splicing in human pathogenesis.