Abstract Transcriptome sequencing (RNA‐seq) is emerging as a diagnostic standard for B‐cell precursor acute lymphoblastic leukemia (B‐ALL). Expression‐based classifiers reach ~95% accuracy, but reproducible end‐to‐end solutions that also integrate transcript‐derived genomic drivers and quantitative virtual karyotyping are lacking. We developed IntegrateALL, a Snakemake pipeline that standardizes RNA‐seq analysis from FASTQ to rule‐based subtype assignment across 26 WHO‐HAEM5/ICC entities by integrating expression‐based subtype prediction, gene fusion‐/hotspot SNV calling, and virtual karyotyping. We introduce KaryALL, a machine learning classifier that uses normalized expression and minor‐allele‐frequency features (RNASeqCNV), to distinguish near‐haploid, hypodiploid, and high‐hyperdiploid B‐ALL and chromosome‐21 gains/iAMP21 (accuracy: 0.98/F1 score: 0.96 on 615 independent test samples). SNP‐array concordance supported RNA‐based karyotyping. Applied to 774 unselected B‐ALL cases, IntegrateALL yielded unambiguous subtype assignments in 81.5%, based on concordance of gene expression class with a defining driver (75.3% of all cases) or, in selected cases, high‐confidence expression‐based classification alone (6.2%); the remainder (18.5%) were flagged for manual curation. Independent validation (three cohorts; n = 436, including pediatric cases) reproduced these distributions. Across all patients (n = 1210), 2.6% harbored two subtype‐defining drivers, including hyperdiploidy in fusion‐driven subtypes, where it was not expected, or subtype‐defining SNVs (e.g., PAX5 P80R/IKZF1 N159Y) co‐occurring with BCR::ABL1‐positive/‐like, KMT2A‐, or DUX4‐fusions. In most dual‐driver cases, one subtype gene expression signature predominated, consistent with oncogenic hierarchies, but also with the possibility of technical artifacts, which should prompt individual orthogonal validations. IntegrateALL provides an adaptable fully reproducible workflow for molecular B‐ALL characterization by systematically integrating genomic drivers and downstream gene regulation.

Abstract Background Baseline CD20 expression ≥ 20% in B-cell acute lymphoblastic leukemia (B-ALL) has been associated with poorer outcomes, which improved after rituximab introduction into frontline therapy for CD20-positive cases. We investigated the clinical and biological significance of this threshold by monitoring early dynamics of CD20 expression. Methods In the GMALL 08/2013 trial, adults with B-ALL received a cyclophosphamide/dexamethasone prephase, followed by Induction and Consolidation I, which included four rituximab doses in BCR::ABL1 -negative patients, irrespective of CD20 status. CD20 expression was measured by standardized multiparametric flow cytometry in 274 patients in bone marrow and blood at diagnosis and in blood after prephase. IG/TR based measurable residual disease (MRD) was correlated with baseline bone marrow or the highest CD20-positive blast percentage recorded throughout prephase. The historical GMALL 07/2003 cohort treated without rituximab served for comparison. Results Baseline CD20 expression was significantly higher in blood than in bone marrow and increased further during prephase. In paired baseline samples, 6/76 c-/pre-B ALL cases (7.9%) were CD20-negative by bone marrow (< 20%) but positive in blood. In paired blood samples, 14/106 patients crossed the 20% threshold after prephase (12/86 c-/pre-B ALL, 13.9% and 2/20 pro-B ALL, 10.0%). Among 182 BCR::ABL1 -negative patients, highest recorded CD20 across all time points classified 76 (41.8%) as < 20% and 106 (58.2%) as ≥ 20%. Higher CD20 expression was associated with improved MRD response under rituximab. Among MRD-evaluable patients after Induction I ( n = 161), molecular complete remission (MolCR) was achieved in 10.6% of patients with CD20 expression < 20% compared with 30.5% of those with CD20 expression ≥ 20%. After Consolidation I ( n = 159), corresponding MolCR rates were 50.0% and 72.6%, respectively. Associations were weaker when only baseline CD20 bone marrow status was considered. No association with MRD response was observed in GMALL 07/2003 patients treated without rituximab, suggesting a treatment-driven effect in GMALL 08/2013. Conclusions CD20 expression in adult B-ALL varies from diagnostic bone marrow to blood and post-prephase measurements. The highest recorded CD20% value better predicts early MRD responses under rituximab. Post-prephase CD20 reassessment in blood identifies additional patients with eligibility for rituximab. Registry ClinicalTrials.gov, TRN: NCT02881086 (2016-08-23); NCT00198991 (2005-09-12).

ABSTRACT:Lenalidomide, a maintenance treatment in multiple myeloma first-line therapy, increases the risk of secondary malignancies, including B-cell precursor acute lymphoblastic leukemia (B-ALL). We present a comprehensive molecular characterization of 57 patients with lenalidomide-associated B-ALL (LenB-ALL), revealing 3 mutational subgroups: (1) TP53mt (30%); (2) IDH2mt (p.R140Q) (23%); and (3) other, including NRAS/KRASmt. Remarkably, IDH2 R140Q mutations were highly enriched in LenB-ALL compared with those in primary B-ALL (P< .001). Furthermore, IKZF1 intragenic deletions, often subclonal and likely RAG recombinase-mediated, were observed in 54% (7/13) of IDH2mt patients with LenB-ALL. IDH2 mutations were not restricted to the leukemic clone: they persisted during measurable residual disease-negative remission and were identified in lymphoid as well as myeloid cell populations using fluorescence-activated cell sorting and single-cell RNA sequencing. This indicates a preleukemic origin of the IDH2 mutation within the context of clonal hematopoiesis. Transcriptomic and DNA methylation analyses revealed a distinct gene expression profile and a DNA hypermethylation phenotype in IDH2mt LenB-ALL, including IDH2mt-specific as well as lenalidomide-associated features. We propose that lenalidomide promotes the expansion of IDH2-mutated clonal hematopoiesis and, via IKAROS downregulation, induces a maturation arrest at the B-cell precursor stage. Subsequent genetic or epigenetic alterations render leukemogenesis independent of ongoing lenalidomide exposure. All these data define IDH2mt B-ALL as a distinct molecular subtype that is markedly overrepresented after lenalidomide treatment and highlight clonal hematopoiesis as a key contributing factor in the development of LenB-ALL.

T cell acute lymphoblastic leukemia (T-ALL) comprises molecular diverse subtypes, currently lacking robust cross-cohort validations and operational gene expression definitions. To establish a gene expression anchored framework for T-ALL subtyping, we aggregated 2,314 transcriptomes (15 cohorts, age: 0.8 to 90.8 years). An extended unsupervised approach defined 17 main clusters and 3 sub-clusters in high blast fraction samples. Supervised analysis added an overarching immature "ETP-like" definition and resolved the LMO2 gd-like subtype. All clusters were populated by samples from at least two cohorts. Characteristic genomic driver enrichment agreed across cohorts, while gene expression clusters did not correspond exclusively to single driver events but also reflected developmental origins. A machine learning classifier based on ALLCatchR - our B-ALL classifier - identified these 21 transcriptomic definitions with 0.995-1.0 accuracy in a validation set (n=203). Testing the classifier on a hold-out data set (n=265 samples) showed that 92.7% of predictions matched with corresponding driver alterations. Across all samples, 88.5% of cases were high-confidence, 6.5% candidate predictions and 5.0% remained unclassified, largely due to low blast fractions. We identified a novel gene expression cluster markedly enriched (P<0.001) for clonal hematopoiesis mutations (IDH2 R140Q, DNMT3A) and a stem-/progenitor cell-like gene expression. This novel "clonal hematopoiesis-related" T-ALL subtype was observed in six cohorts representing 8.9% of adults and 39.5% of patients aged >50 years. We advanced ALLCatchR, a free R package which now enables B- /T- lineage separation, gene-expression subtyping, blast estimation, and developmental annotation to harmonize T-ALL classification across studies and clinical contexts. ### Competing Interest Statement The authors have declared no competing interest. Deutsche Forschungsgemeinschaft, 444949889, 413490537 Deutsche José Carreras Leukämie-Stiftung, DJCLS 08R/2024 German Cancer Aid, 70115443

Abstract T-cell lymphoblastic lymphoma (T-LBL) and T-cell acute lymphoblastic leukemia (T-ALL) originate from thymic T-cell precursors, with ongoing debate on whether they are variants of the same disease or distinct entities. For 211 patients, including pediatric and adult T-ALL and T-LBL cases, targeted next-generation sequencing and SNP-arrays were performed, and single-nucleotide variants, indels and copy-number variants (CNVs) were analyzed. We aimed to assess genetic differences between T-ALL and T-LBL across age. Generally, mutational landscape analysis identified mutated PHF6 being associated with higher, NOTCH1 with lower age at diagnosis for both T-LBL and T-ALL. Association of CNVs with higher age was evident for T-ALL, but not T-LBL. Analysis of clonal evolution revealed that CNVs – especially deletions and LOH in chromosome 9 (LOH_in_9p) – were observed as first mutational event in both pediatric T-ALL and T-LBL. The sequence of genetic events, starting with LOH_in_9p followed by mutations in NOTCH1, was significantly more frequent in pediatric T-ALL and T-LBL. Detailed evaluation of the patients’ individual clonal evolution indicated that the proportion of malignant cells without NOTCH MT determines the risk of relapse (hazard ratio 1.032, p = 4.65*10−5). In T-ALL, aside from MRD, validated molecular markers for risk-group stratification remain limited. Our data suggest that molecular metrics analogous to those in T-LBL may help refining risk stratification in T-ALL as well.

Prognosis of adult patients with relapsed/refractory (r/r) or measurable residual disease (MRD)–positive B-precursor acute lymphoblastic leukemia (B-ALL) remains poor. Blinatumomab induces complete remissions (CR) and MRD negativity in a subset of patients, yet overall survival remains limited. As BCL2 overexpression contributes to leukemic cell survival and therapy resistance, combining Blinatumomab with the BCL2 inhibitor Venetoclax may enhance therapeutic efficacy. The GMALL-BLIVEN (NCT05182385) phase I multicenter trial evaluated the safety and feasibility of Venetoclax plus Blinatumomab in adults with CD19⁺, Philadelphia chromosome–negative r/r or MRD-positive B-ALL. Dose escalation followed a 3 + 3 design across three Venetoclax dose levels (DL-1: 400 mg; DL-2: 600 mg; DL-3: 800 mg) administered from day − 7 to day 42, with Blinatumomab given per label. The primary endpoint was determination of the maximum tolerated dose (MTD); key secondary endpoint was achievement of molecular complete remission (MOL-CR) by centralized IG/TR MRD assessment (sensitivity ≥ 10⁻⁴). Nine patients (median age 52 years, range 22–71) were enrolled across four German centers: four with r/r B-ALL and five with MRD-positive disease. Molecular subtypes included ZNF384-rearranged (n = 2), BCR::ABL1-like (n = 2), CEBP-rearranged (n = 1), hypodiploidy (n = 1), B-ALL NOS (n = 2), and KMT2A-rearranged (n = 1). No dose-limiting toxicities were observed, and the MTD was not reached. Treatment-emergent grade ≥ III toxicities included neutropenia, febrile neutropenia, cytokine release syndrome, and ICANS; no 30- or 60-day mortality occurred. Six patients completed two full cycles without treatment interruptions. The recommended phase II dose (RP2D) was established as Venetoclax 800 mg daily plus standard-dose Blinatumomab. All nine patients were evaluable for response. Among r/r B-ALL, responses included PR (n = 1), CR (n = 1), and PD (n = 2). Among MRD-positive patients, 4/5 achieved MOL-CR. Four patients were successfully bridged to allogeneic stem cell transplantation. After a median follow-up of 17.8 months, median overall survival was 15.0 months (r/r: 6.6 months; MRD-positive: 16.9 months). Non-responders were enriched for adverse molecular subtypes (BCR::ABL1-like and hypodiploid B-ALL). Venetoclax combined with Blinatumomab is safe and feasible in adults with r/r or MRD-positive B-ALL, without increased rates of CRS or neurotoxicity compared with Blinatumomab alone. High rates of MRD clearance were observed in MRD-positive patients. The phase II portion of GMALL-BLIVEN is ongoing at the RP2D of Venetoclax 800 mg daily.

Inflammatory signaling contributes to the progression of acute myeloid leukemia (AML) and impaired hematopoiesis, partly through NF-kB–driven transcription of cytokines, such as IL-6, IL-8, and IL-1β. These factors disrupt the bone marrow niche and support leukemic cell survival. In concordance, low expression of the interleukin-1 receptor (IL1R1), the receptor for IL-1β, has been linked to a more favorable outcome in AML. However, its role in genetically defined subgroups remains unclear. Here, we report that low IL1R1 expression was particularly associated with IDH1-mutated (mut) AML. To characterize IL1R1 in IDH1-mut AML, we combined clinical data with transcriptomic, epigenetic, and cellular analyses using primary AML blasts as well as CRISPR-modified IDH1 p.R132H mutant KG1-a AML cells. Using transcriptome data from the BeatAML2.0 study, we identified significant downregulation of IL1R1 mRNA expression in IDH1-mut compared to IDH1-wild-type (wt) AML cases (log₂ fold change = -1.23; adjusted p-value = 0.017). Given the known epigenetic alterations associated with IDH1 mutations, DNA methylation was examined and revealed significant hypermethylation at 6 out of 18 CpG sites (33%) across the IL1R1 locus in IDH1-mut compared to IDH1-wt AML cases. To analyze the clinical impact of reduced IL1R1 levels, all AML patients from the BeatAML2.0 study were stratified into three IL1R1 expression groups: high (n = 205), medium (n = 205) and low (n = 205). Overall, AML patients with low IL1R1 expression showed significantly higher complete remission (CR) rates (56.2%) compared to those with medium (44.1%) or high expression (38.1%; p = 0.0014). Stratified analyses by IDH1 mutation status confirmed higher CR rates in IL1R1-low cases in IDH1-wt (low 54.2% vs. medium 43.9% vs. high 38.5%, p = 0.003) as well as IDH1-mut subgroups (low 69.2% vs. medium 46.7% vs. high 28.6%, p = 0.046). Independent of the IDH1 genotype, Kaplan-Meier survival analysis demonstrated that low IL1R1 expression was associated with significantly improved overall survival compared to medium and high expression (median 680 vs. 320 vs. 434 days; p = 0.0001). Notably, IDH1-mut cases were significantly enriched in the IL1R1 low expression group (13.4%) compared to medium (7.7%) and high (3.6%) expression groups (p = 0.002), suggesting IL1R1 expression as clinical discriminator with particular relevance in IDH1-mut AML. For functional validation primary AML blasts were treated with IL-1β, the canonical IL1R1 agonist. In IDH1-mut AML blasts, IL-1β exposure led to lower mRNA expression of TNF, IL6, and CCL20 compared to IDH1-wt primary AML blasts. On the protein level, IL-1β stimulation of IDH1-mut KG1-a cells led to significantly lower IL-8 secretion compared to IDH1-wt cells at 6 h and 18 h. Proteomic profiling confirmed reduced secretion of NF-kB–dependent cytokines such as IL-8, CXCL1, and CCL20 in IDH1-mut KG1-a cells. In contrast, IL-1β induced higher secretion of tissue remodeling and immune modulatory proteins such as MMP-1, MMP-10, PLAU and TNFSF10 in IDH1-mut KG1-a cells. To mimic the inflammatory bone marrow microenvironment containing high levels of several pro-inflammatory cytokines, stimulation with conditioned medium (CM) of HS-5 stromal cells was performed. Exposure to HS-5 CM led to a time-dependent increase in caspase-3/7 activation, which was significantly more pronounced in IDH1-mut cells compared to IDH1-wt cells (p = 0.02). The enhanced apoptotic response of IDH1-mut cells to both recombinant IL-1β and HS-5 CM was abrogated by the IL-1 receptor antagonist Anakinra, indicating a selective IL1R1-dependent apoptosis induction in IDH1-mut AML cells.These results suggest that IDH1 mutations in AML remodel IL1R-mediated signaling towards an inflammatory anergy but pro-apoptotic state, revealing a previously unrecognized inflammatory vulnerability in this genetic subtype involving the leukemic microenvironment. This work provides a rationale for further investigation of targeted pro-inflammatory modulation or combination regimens to amplify apoptosis in IDH1-mut AML selectively.

Background:Acute leukaemias are rare but highly aggressive malignancies, but only limited population-level data are available for Germany. We aimed to describe epidemiology, survival, and therapies of acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL) in Germany using nationwide cancer registry data. Methods:We conducted a population-based analysis of all incident cases of AML and ALL in Germany, identified via ICD codes from mandatory cancer registry reporting, to assess incidence, treatment, and survival outcomes. Findings:We identified 25,788 patients with AML and 6480 patients with ALL diagnosed between 2016 and 2021 aged 0-101 years. The age-standardized incidence rate was 4.72/100,000 for AML (median age 72.8 years, IQR 61.0-80.3) and 1.36/100,000 for ALL (median age 19.4 years, IQR 5.2-58.6). The three- and five-year overall survival was 29.0% (95% CI: 28.3-29.7) and 23.8% (95% CI: 23.1-24.7) in AML, and 64% (95% CI: 62.2-65.9) and 58% (95% CI: 55.7-60.2) in ALL. Survival was highly dependent on age, with children (0-18 years) showing the highest three-year survival rates in AML (76.4%, 95% CI: 70.2-83.2) and ALL (91.9%, 95% CI: 89.8-94.1) compared to older adults. Moreover, area-based income and social deprivation were linked to survival, with three-year survival reduced by up to 4% in lower-income counties. Based on German federal population estimates, AML cases are expected to rise by 14.6%, while ALL cases will decline by 2.3% between 2020 and 2050. Interpretation:We provide incidence and survival data to inform future clinical trials, guide resource allocation, and support healthcare planning to improve real-world outcomes and address disparities in acute leukaemia. Funding:German Research Foundation (DFG).

Distinct diagnostic entities within BCR :: ABL1- positive acute lymphoblastic leukemia (ALL) are currently de fi ned by the International Consensus Classi fi cation 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 identi fi ed 2 main gene expression clusters reproducible across 4 independent patient cohorts. Fluorescence in situ hybridization analysis of fl uorescence-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 speci fi c 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 de fi ne underlying developmental trajectories and distinct patterns of cooperating events in BCR :: ABL1- positive ALL with prognostic relevance.

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.

Introduction T-lineage acute lymphoblastic leukemia (T-ALL) is a subtype comprising around 20 - 25% of all ALL cases, which represents specific clinical challenges. Current classification systems are heterogeneous with varying reproducibility. We developed a data-informed classification system of T-ALL. Methods To assess T-ALL immunophenotypes, we analyzed flow cytometry data from T-ALL patients (pts) treated between 1989-2024 within the framework of the German Multicenter ALL (GMALL) Study Group. From a total of 1696 untreated pts, we selected samples based on availability of a sufficient antibody panel (sCD3, cyCD3, CD1a, CD7, CD2, CD5, CD4, CD8, CD34, TdT, CD10, CD117, HLADR, CD13, CD33). Antigen positivity was defined as ≥20% for cell surface and ≥10% for intracellular antigens. We performed hierarchical clustering and UMAP-analyses to identify phenotypic subgroups. Results were compared to established classification systems (i.e. EGIL, GMALL, WHO). GMALL recognizes thymic (CD1a+), early (CD1a-, either CD2- or CD2+, CD5-, CD4-, CD8-, sCD3-) and mature T-ALL (definitions of thymic and early not met). Identified clusters and categorization along established classification schemes were correlated with available T cell receptor (TR) rearrangement profiles in a subset of pts. Results Data from 1177 pts (841/325/11 male/female/unknown) were available. The median age was 35 years (range 15-85). According to GMALL definitions, 304 pts were classified as early, 532 as thymic, and 341 as mature T-ALL. Comparative reclassification according to EGIL and WHO revealed inconsistencies, particularly with respect to mature, early and pre/pro T-ALL, with 61% (n = 208) of mature T-ALL according to GMALL categorized as pre-T according to EGIL. ETP-ALL (n=167) comprised mature (n=32, 20%) and early (n=135; 80%) according to GMALL and mature (n=5; 3%), pre-T (n=130; 78%) and pro-T (n=32; 19%) according to EGIL. Hierarchical clustering based on antigen expression profiles revealed 5 immunophenotypically distinct groups, which we termed early-T-like (n=336; 28%), ETP-like (n=61; 5%), atypical-thymic (n=119; 10%) typical thymic (n=462; 39%), mature-T-like (n=199; 16%) T-ALL. Within the newly identified subgroups atypical/typical thymic T-ALL, we observed a lower median age compared to other subgroups, whereas sex and date of analysis (before 2000 vs. after 2000) showed no significant associations. TR rearrangement data were available in 121 pts. We found that the data-informed classification system showed significantly lower numbers of TR rearrangements per sample in ETP-like compared to typical-thymic T-ALL (median 2 vs 5, p=0.0003) and 97% of typical-thymic T-ALLs had TR rearrangement profiles occurring later within T-cell developmental trajectories (complete TRB and/or TRD). Likewise, the most mature TR profiles were detected in thymic T-ALL according to GMALL and EGIL (≥97% with complete TRB/TRD). The novel identified subgroup of atypical-thymic T-ALL was characterized by a significantly less frequent expression of more mature T-cell antigens (CD2, CD4, CD8), increased CD10 expression and a trend towards more immature TR profiles compared to typical-thymic T-ALL (81% vs. 97% complete TRB/TRD). This finding is in line with a 24% proportion of early/pre/pro-T-ALL according to GMALL/EGIL within the atypical-thymic group with a median expression of 2% for CD1a, 4% CD2, 3% CD4, 2% CD8 and 85% CD10. To further characterize and capture the heterogeneity within thymic T-ALL, we analyzed expression profiles in a subset of 611 T-ALL pts defined as thymic T-ALL by a ≥10% threshold for CD1a positivity, commonly used to define thymic T-ALL in pediatric trials. We discovered that subgroups of thymic T-ALL could be separated by CD2, CD4, CD8 and CD10 expression. CD1a-low (10-19%) cases had a more immature expression profile with lack of either CD2, CD4 and CD8 compared to CD1a-high (p=0.0026 for CD2, p<0.0001 for CD4 and CD8). Conclusion Our findings identified novel immunophenotypic subtypes within T-ALL, especially among CD1a+ thymic cases. TR rearrangement data aligned with immunophenotypic maturation stages, validating our classification. Remarkably, the most mature rearrangement profiles were present in ‘typical-thymic’ T-ALL. It is essential for comparability of clinical data and categorization of molecular data to develop a standardized classification system for T-ALL.

The analysis of clonal evolution allows to reconstruct tumor development over time, explore treatment response, and identify potential reasons for therapy failure. This allows for an in-depth analysis of a patient’s heterogeneous tumor cell composition. Furthermore, phylogenetic trees hold the promise of revealing common patterns conserved across different patients. Several approaches exist, e.g. MASTRO or TreeMHN. However, these focus exclusively on mutated genes, neglecting copy number variants (CNVs). Additionally, TreeMHN requires mutations to be acquired successively. While MASTRO supports mutations of unknown order, the resulting high number of possible relations hinders the analysis of more complex phylogenetic trees due to substantial storage requirements. We propose a novel approach for identifying conserved trajectories in clonal evolution trees: exact SNVs and indels are reduced to the gene they affect. CNVs are transformed to their smallest possible representation, e.g. del9 becomes del_in_9p and del_in_9q, to identify common elements of different CNVs affecting chromosome 9. For each patient, all observed patterns of 2 and 3 levels are determined, and their probabilities are calculated using Laplace-distribution. The total number of possible patterns is defined as n!/(n-k)! (n unique mutations, k levels). The number of observed patterns is considered the number of trials. The occurrence of each pattern across all patients is counted. Statistical significance is determined assuming Poisson binomial distribution. The analysis of 149 patients with T-ALL or T-LBL demonstrates the applicability of our new method even to cases of hypermutation. Common mutational patterns are successfully identified, including both SNVs/indels as well as CNVs.

B cell precursor acute lymphoblastic leukemia (BCP-ALL) molecular subtypes are defined by genomic drivers and corresponding gene expression signatures. Inference of underlying genomic aberrations from transcriptome sequencing (RNA-Seq) enables BCP-ALL subtype allocation based on consistency of driver call and corresponding gene expression signatures. Currently, these features are obtained from individual tools, requiring error-prone manual integration. To facilitate systematic accessibility of all RNA-Seq data levels for BCP-ALL diagnostics and research, we have developed IntegrateALL, a comprehensive analysis pipeline. IntegrateALL uses RNA-Seq raw data FASTQ files to perform quality control (FASTQC, MULTIQC), read alignment (STAR), gene fusion (ARRIBA, FusionCatcher), single nucleotide variant calling (GATK, pysamstats), virtual karyotyping (RNASeqCNV) and gene expression based molecular subtype allocation (ALLCatchR) to provide a holistic molecular landscape. As a novel component, we established a machine learning classifier for virtual karyotypes using data extracted from RNASeqCNV profiles of five ALL patient cohorts (n=384) to achieve an accuracy of 98% for identification of hyperdiploid, low hypodiploid, near haploid, iAMP21 and normal karyotypes. For final subtype assignment, the pipeline uses a parameter-based ruleset for classification according to current WHO-HAEM5 / ICC definitions and flags exceptional cases for manual curation. We applied IntegrateALL to a representative adult BCP-ALL cohort (GMALL; n=653). IntegrateALL allocated n=538 (82%) samples to one of 26 diagnostic BCP-ALL entities based on concordance of gene expression-based subtype prediction, identification of the corresponding genomic driver and absence of secondary drivers. For PAXalt and BCR::ABL1-like ALL, high-confidence gene expression-based predictions were sufficient for automatic classification. These automated subtype allocations confirmed previous manual curation in all cases. The remaining n=115/653 (18%) samples were flagged for manual curation. Among these, n=66 cases had either high confidence (n=6) or candidate (n=60) ALLCatchR subtype predictions without corresponding genomic driver call, identifying samples for validation by genomic profiling. A total of n=16 cases were ‘unclassified’ in previous analysis and remained so after IntegrateALL analysis. In n=30 cases, IntegrateALL improved diagnostic accuracy by identifying secondary drivers in cases with other confirmed subtype allocation (e.g., hyperdiploid karyotypes in PAX5 P80R and KMT2A ALL, CRLF2- and GOPC::ROS1 fusions in non-BCR::ABL1-like ALL cases) or by identifying corresponding genomic drivers in cases with low confidence ALLCatchR predictions. Only n=3 cases had divergent results between prediction and the identified genomic driver. Our new karyotype classifier validated high confidence gene expression-based allocations to aneuploid subtypes in n=40/44 cases and candidate confidence allocations in n=12/30 cases, including two previously misclassified near-haploid cases. This represents the first systematic validation of aneuploid subtypes, which are challenging to classify by gene expression alone. IntegrateALL analysis provided an unprecedented overview of adult BCP-ALL, including frequency distributions of molecular subtypes (e.g., BCR::ABL1 with lymphoid only involvement: 14%; BCR::ABL1-like JAK/STAT activated: 14%; KMT2A: 10%; DUX4: 10%) and identification of actionable targets (BCR::ABL1-like ABL-class ALL: 4%). Patient's age and sex impacted the selection of BCP-ALL driver subtypes (enriched for young age DUX4, hyperdiploid, PAX5 P80R, PAX5alt / advanced age: BCR::ABL1-positive, low hypodiploid; female: CDX2/UBTF, KMT2A, DUX4 / male: CEBP; p<0.05 vs. remaining cohort for all comparisons). Across subtypes, we observed an increase of earlier developmental origins of BCP-ALL with increasing patient age. IntegrateALL is a free open-source pipeline which provides an autonomous end-to-end solution from FASTQ file to interactive HTML report for systematic BCP-ALL subtype allocation based on gene expression and inference of underlying drivers, including a new karyotype classifier for aneuploid subtypes. Automated selection of cases for manual curation supports the identification of ‘double-driver’ subtypes and other rare phenotypes.

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.

In contrast to B-cell precursor acute lymphoblastic leukemia (ALL), molecular subgroups are less well defined in T-lineage ALL. Comprehensive studies on molecular T-ALL subgroups have been predominantly performed in pediatric ALL patients. Currently, molecular characteristics are rarely considered for risk stratification. Herein, we present a homogenously treated cohort of 230 adult T-ALL patients characterized on transcriptome, and partly on DNA methylation and gene mutation level in correlation with clinical outcome. We identified nine molecular subgroups based on aberrant oncogene expression correlating to four distinct DNA methylation patterns. The subgroup distribution differed from reported pediatric T-ALL cohorts with higher frequencies of prognostic unfavorable subgroups like HOXA or LYL1/LMO2. A small subset (3%) of HOXA adult T-ALL patients revealed restricted expression of posterior HOX genes with aberrant activation of lncRNA HOTTIP. With respect to outcome, TLX1 (n = 44) and NKX2-1 (n = 4) had an exceptionally favorable 3-year overall survival (3y-OS) of 94%. Within thymic T-ALL, the non TLX1 patients had an inferior but still good prognosis. To our knowledge this is the largest cohort of adult T-ALL patients characterized by transcriptome sequencing with meaningful clinical follow-up. Risk classification based on molecular subgroups might emerge and contribute to improvements in outcome.

Background: Lenalidomide (Len), approved in 2017 as maintenance therapy for multiple myeloma (MM), is known to increase the cumulative incidence of secondary malignancies, including Len-associated B-cell precursor ALL (LenB-ALL). However, the molecular basis of LenB-ALL leukemogenesis is not yet fully understood. Methods: We present the results of a comprehensive molecular characterization of consecutive diagnostic samples from patients (pts) with secondary B-ALL following Len therapy for MM. Samples were sent in for GMALL (German Multicenter Study Group for Adult ALL) reference ALL diagnostics and were analyzed by gene panel sequencing (seq), IGH rearrangement profiling, SNParray / MLPA and DNA methylation profiling, bulk RNA-seq, and, in selected cases, single-cell RNA-seq. Results: A total of 58 consecutive LenB-ALL pts (median 64.7 years, range 47-78) were included. The mutational profile showed a strong enrichment of clonal hematopoiesis (CH) genes with three mutually exclusive mutation patterns: (1) TP53 mutated in 17/58 pts (29 %), (2) IDH2 p.R140Q mutated in 13/58 pts (22 %), which is rare in primary B-ALL (<1%), and (3) other mutations including DNMT3A, NRAS and KRAS. Unsupervised gene expression analysis of LenB-ALL within the context of our large primary B-ALL cohort (n = 596) grouped TP53 mutated LenB-ALL cases together with low hypodiploid B-ALL cases which frequently harbor TP53 mutations. Consistent with its more heterogeneous genomic makeup, the DNMT3A, N/KRAS cases showed a less distinct gene expression signature. However, IDH2-mutated LenB-ALL cases formed a highly distinct cluster, which could be predicted with 99% accuracy, compared to other LenB-ALL and primary B-ALL cases, establishing a novel IDH2-mutated LenB-ALL subtype. Epigenomic profiling using DNA methylation arrays independently confirmed this cluster separation and showed hypermethylation of top variably methylated CpGs in IDH2 and DNMT3A mutated cases, consistent with the epigenetic functions of these regulators. Interestingly, IKZF1 - encoding Ikaros, a target of Len-induced proteasomal degradation - harbored intragenic deletions in 7/13 (54 %) IDH2-mutated LenB-ALL pts. A loss of Ikaros may lead to a B-cell maturation arrest at the proliferative large pre-B cell stage culminating in (oligo)clonal B-ALL expansion (I Joshi et al Nat Immunol 2014). Consistently, we observed evidence of IGH clonal evolution / oligoclonality in 6/12 IDH2-mutated LenB-ALL (50 %) using amplicon-based IGH NGS, compared to only 24 % in 355 adult primary pre/c-B-ALL. To elucidate the clonal architecture of IDH2-mutated LenB-ALL, we analyzed diagnostic and follow-up samples by IDH2 R140Q- and IKZF1del-specific ddPCR (sensitivity 0.1 %) and compared the results with IGH-based MRD kinetics: IKZF1-specific ddPCR suggested a late onset of IKZF1-deletions during leukemogenesis with sub- and oligoclonality and restriction to the B-ALL compartment. In contrast, the IDH2 mutation was detected as clonal hematopoiesis in 4 of 13 patients during MRD-negativity, where it was confirmed in both, lymphoid and myeloid compartments by ddPCR on FACS-sorted hematopoietic compartments. Single-cell proteotranscriptomics of a diagnostic and remission bone marrow sample evidenced a preleukemic, multilineage IDH2-mutated clone in one patient. In one patient with an available bone marrow aspirate from the time of MM diagnosis, the IDH2 mutation was not detected in the MM. Conclusions: We describe a novel molecular subset of LenB-ALL driven by IDH2-mutated CH. We hypothesize that IDH2-mutated CH expands in the presence of Len and that Len-induced degradation of Ikaros leads to a maturation arrest of IDH2-mutated B-cell progenitors. Subsequent IKZF1 deletions render Ikaros inactivation independent of Len providing the framework for full IDH2-driven leukemic transformation. Prospectively, the prevalence of IDH2-mutated CH in multiple myeloma and its impact on the risk of LenB-ALL are to be evaluated.