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.

CCAAT-enhancer-binding proteins (C/EBP) are important regulators of myeloid differentiation and cell cycle control. The C/EBP family member CEBPE has been implicated in B precursor acute lymphoblastic leukemia (BCP-ALL) through IGH locus gene fusions and rare germline single nucleotide variants. ‘ZEB2 (p.H1038R)/IGH::CEBPE‘ BCP-ALL is a provisional diagnostic entity in the current ICC classification. However, precise diagnostic definitions for this subtype are lacking. We analyzed n=2,845 BCP-ALL transcriptomic profiles of own (GMALL: n=571; MLL: n=286) and published cohorts (St Jude: n=1,988), including pediatric (n=1,285) and adult cases (n=1,560). Of these, we identified n=43 BCP-ALL patients with either C/EBP family member gene fusions or corresponding gene expression signatures and absence of established subtype definition. To define the molecular profile of C/EBP BCP-ALL, we performed transcriptomic (RNA-Seq, n=31) genomic (WGS / WES: n=16; DNA EuroClonality capture analysis: n=23; SNP arrays: n=18) and epigenomic (DNA methylation arrays: n=17) profiling. Unsupervised data analysis of the largest sub-cohort (n=25; GMALL) identified two distinct gene expression clusters - C1 (n=13) and C2 (n=12) - which shared overlapping gene expression signatures, separating C/EBP candidates from remaining BCP-ALL subtypes and from each other (C1 vs. C2). Robustness of this cluster separation was confirmed on gene expression data of independent cohorts (MLL: n=8; St Jude: n=10) and by unsupervised DNA methylation analysis of GMALL data. Gene fusions involving C/EBP family members were clearly enriched in the novel gene expression clusters (n=36/43 vs. n=3/2,813 in remaining BCP-ALL; p<0.001) with n=7 cases sharing the gene expression profile without a C/EBP driver fusion call. CEBPE fusions were specific for cluster C1 (C1: n=11/25 vs. C2: n=0/18, p<0.001), while IGH::CEBPA (C1: n=8/25 vs. C2: n=11/18; n.s.) and IGH::CEBPB (n=5) or IGH::CEBPD (n=1)fusions occurred in both clusters. IGH locus DNA capture analysis identified in n=6/25 GMALL cases C/EBP fusions which were missed by RNA-Seq. Genomic profiling revealed subtype-specific cooperating events. Cluster C1 was characterized by ZEB2 p.H1038R (84%), NRAS/KRAS activating (74%) single nucleotide variants and CDKN2A deletions (88%; p<0.01 for all comparisons to C2 and to remaining BCP-ALL). C2 showed a less distinctive profile with enrichment of FLT3 activating SNVs (28%; p=0.01 for comparison to remaining BCP-ALL) and a tendency for IKZF1 deletions (42%; n.s.). Notably, ZEB2 p.H1038R was also observed in n=2 C2 cluster cases and in n=10 C cluster cases not harboring a CEBPE gene fusion, indicating that our gene expression clusters extend beyond the suggested genomic definition of ZEB2 (p.H1038R)/IGH::CEBPE. Comparison to normal B lymphopoiesis showed highest proximity of cluster C2 to pre-B I cells whereas C1 was closest to pre-B II cells, suggesting different developmental trajectories of C/EBP ALL subtypes. C/EBP ALL was mainly observed in adults (median age: 46 years, range 13-88 years). A total of n=22 outcome-evaluable C/EBP ALL patients (median age: 49 years, range 18-70 years) were treated on GMALL protocols. One patient died during induction therapy. Complete MRD negativity in n=16/19 (84%) patients with MRD measurement after 1st consolidation indicated an overall favorable therapy response of C/EBP ALL. However, only n=15/22 (68%) patients achieved long-term complete remissions, including cases with allogenic stem cell transplantation in 1st CR (n=2). In total, n=8/22 (36%) patients experienced mostly late relapses with only n=3 patients achieving a durable 2nd complete remission after salvage. Despite favorable initial treatment response, C/EBP ALL patients might harbor an increased risk of late relapse, possibly related to their overall advanced age. Both clusters, C1 and C2 shared this clinical phenotype despite their distinct molecular background. To facilitate diagnostic identification of C/EBP clusters C1 and C2, we trained a machine learning classifier on the GMALL gene expression data set which separated these from remaining BCP-ALL with accuracies of 99.7% in training data and 99.0% (MLL) or 99.4% (St Jude) in independent hold-out cohorts. Integration of genomic, epigenomic and transcriptomic data defined two molecular distinct adult BCP-ALL subtypes harboring C/EBP family gene fusions.

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.

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.

Minimal residual disease (MRD) is the most important outcome predictor in B precursor acute lymphoblastic leukemia (B-ALL), but additional contributing factors are poorly understood. To address the molecular and functional underpinnings of MRD kinetics in KMT2A-rearranged (KMT2A-r) as high-risk disease across all age groups, we analyzed a cohort of 325 KMT2A-r BCP-ALL patients (0-89 years, median: 32 years; n = 59 infants, n = 67 pediatric, n = 179 adults, n = 20 NA). Diagnostic samples were studied by integrating gene expression and gene fusion profiling (RNA-Seq; discovery cohort: n=148, validation cohort: n=177) with karyotyping (SNP-Arrays; n=113), ex-vivo drug-response profiling (n=62) and MRD measurements at follow-up (n=97). To unravel the cell of origin of KMT2A-r ALL, we used the machine learning classifier ALLCatchR to define developmental trajectories and fitted linear slopes on the enrichment across B-cell-developmental stages as a measure for cell stemness. Stemness scores were validated using IG-rearrangement patterns and surface marker expression (FACS). Patients were treated according to the AIEOP-BFM ALL/INTERFANT and GMALL study group protocols, with IG/TR MRD measurements performed in the central reference laboratories. Pediatric-inspired induction therapy protocols in adult patients with comparable MRD sampling time points in pediatric regimens allowed for kinetic definitions of MRD clearance (fast / intermediate / slow) across age groups. Age did not affect the initial MRD clearance (p = 0.96), but the patient age was significantly correlated with the underlying driver gene fusion (p = 9.2e-7) and stemness (p = 1.9e-15); gene fusion and stemness were also interdependent (p= 2.2e-16). Thus, the dissection of these co-factors on MRD clearances is needed to allow a comprehensive understanding of this molecular interplay. Considering the most frequent fusion partners of KMT2A, AFF1 (n=63; 65%), MLLT1 (n=16; 16.5 %), and MLLT3 (n=13; 13.5%), we observed a skewed distribution in the three MRD categories fast / intermediate / slow. KMT2A::AFF1-r cases predominantly showed an intermediate or slow MRD clearance compared to KMT2A::MLLT1 and KMT2A::MLLT3 cases (83%, 38% and 30% slow/intermediate clearance respectively, p = 0.001). Compared to slow/intermediate MRD clearance, ALLs with fast MRD clearance were significantly more mature (p = 0.0018), with closer proximity towards more mature B-precursor stages (Pre-B-II-Large p = 0.037; Pre-B-II-Small p = 0.0047) than towards Pro-B cell-stage (p = 0.0001). Stemness also differed between driver fusions with KMT2A::AFF1-r leukemias being less mature compared to KMT2A::MLLT3 and KMT2A::MLLT1-r ALLs (p = 2.2e-16). Gene expression programs in KMT2A::AFF1 cases revealed highly proliferative, early-B-cell-developmental-stage like signatures, global activation of gene expression and silenced apoptosis and differentiation signals. In contrast, KMT2A::MLLT3 showed downregulation of proliferative signalling and up-regulation of more differentiated B-cell signalling compared to KMT2A::AFF1-r ALL. To assess functional consequences, we analyzed ex-vivo drug response profiles of over 30 drugs on primary cells (n = 62 patients) and correlated the ex-vivo sensitivities with the patient's MRD clearance. MRD clearance correlated with the sensitivity to clinically relevant drugs (Dexamethasone p = 0.002; Daunorubicin p = 0.04, Doxorubicin p = 0.01, Vincristine p = 0.02, Asparaginase p = 0.01). In contrast, Venetoclax showed good response in most samples but no evident correlation with MRD clearance (p = 0.75). Integrating the molecular, functional and metadata layers we detected two distinct gene expression clusters separating patients with faster and slower MRD clearance. Intriguingly, these clusters were most significantly associated with stemness (p < 2.2e-16), and to a lesser extent with age (p = 2.4e-11) and fusion (p = 0.0005), indicating that stemness has the strongest impact on MRD clearance. This age-overriding integrated analysis reveals a complex interplay of the cell of origin, the underlying gene fusion, and the patient age-directing response to frontline therapy in KMT2A-r B-ALL and molecular insights into underlying signalling pathways may better guide adapted treatment innovations in KMT2A-r BCP-ALL.

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.

Current classifications (World Health Organization-HAEM5/ICC) define up to 26 molecular B-cell precursor acute lymphoblastic leukemia (BCP-ALL) disease subtypes by genomic driver aberrations and corresponding gene expression signatures. Identification of driver aberrations by transcriptome sequencing (RNA-Seq) is well established, while systematic approaches for gene expression analysis are less advanced. Therefore, we developed ALLCatchR, a machine learning-based classifier using RNA-Seq gene expression data to allocate BCP-ALL samples to all 21 gene expression-defined molecular subtypes. Trained on n = 1869 transcriptome profiles with established subtype definitions (4 cohorts; 55% pediatric / 45% adult), ALLCatchR allowed subtype allocation in 3 independent hold-out cohorts (n = 1018; 75% pediatric / 25% adult) with 95.7% accuracy (averaged sensitivity across subtypes: 91.1% / specificity: 99.8%). High-confidence predictions were achieved in 83.7% of samples with 98.9% accuracy. Only 1.2% of samples remained unclassified. ALLCatchR outperformed existing tools and identified novel driver candidates in previously unassigned samples. Additional modules provided predictions of samples blast counts, patient's sex, and immunophenotype, allowing the imputation in cases where these information are missing. We established a novel RNA-Seq reference of human B-lymphopoiesis using 7 FACS-sorted progenitor stages from healthy bone marrow donors. Implementation in ALLCatchR enabled projection of BCP-ALL samples to this trajectory. This identified shared proximity patterns of BCP-ALL subtypes to normal lymphopoiesis stages, extending immunophenotypic classifications with a novel framework for developmental comparisons of BCP-ALL. ALLCatchR enables RNA-Seq routine application for BCP-ALL diagnostics with systematic gene expression analysis for accurate subtype allocation and novel insights into underlying developmental trajectories.

Persistence of residual disease after induction chemotherapy is a strong predictor of relapse in acute lymphoblastic leukemia (ALL). The bone marrow microenvironment may support escape from treatment. Using three-dimensional fluorescence imaging of ten primary ALL xenografts we identified sites of predilection in the bone marrow for resistance to induction with dexamethasone, vincristine and doxorubicin. We detected B-cell precursor ALL cells predominantly in the perisinusoidal space at early engraftment and after chemotherapy. The spatial distribution of T-ALL cells was more widespread with contacts to endosteum, nestin+ pericytes and sinusoids. Dispersion of T-ALL cells in the bone marrow increased under chemotherapeutic pressure. A subset of slowly dividing ALL cells was transiently detected upon shortterm chemotherapy, but not at residual disease after chemotherapy, challenging the notion that ALL cells escape treatment by direct induction of a dormant state in the niche. These lineage-dependent differences point to niche interactions that may be more specifically exploitable to improve treatment.

•‘Multilineage’ vs. ‘lymphoid-only’ BCR::ABL1 involvement and distinct cooperating events determine gene expression in BCR::ABL1-positive ALL•Outcome with recent GMALL protocols is similar for BCR::ABL1 lineage clusters, but inferior for an IKZF1-/- enriched ’lymphoid’ subcluster

Two developmental trajectories are acknowledged in BCR::ABL1-positive acute lymphoblastic leukemia (ALL) as distinct diagnostic entities by the ICC classification: ‘lymphoid-only’ with BCR::ABL1 restricted to the leukemic B precursor compartment vs. ‘multilineage’ with BCR::ABL1 involvement also in other hematopoietic lineages. Diagnostic standards for establishing this distinction are lacking and associated biological and clinical features are insufficiently characterized. To establish developmental trajectories, biological phenotypes, and clinical impact we analyzed n=277 BCR::ABL1-positive ALL patients (age: 2-84 years, median: 46) including our GMALL reference data set (n=113) and two independent validation cohorts (MLL: n=61; St Jude's: n=103; Gu Z, et al. Nat Genet. 2019). Unsupervised gene expression analysis (RNA-Seq: n=277) identified two major gene expression clusters with two further sub-clusters each (Figure A). This clustering was confirmed by a machine learning classifier trained on the GMALL data set which achieved similar grouping of samples in the external validation cohorts. BCR:: ABL1-FISH on FACS-sorted bone marrow/peripheral blood samples revealed the presence of BCR::ABL1 in leukemic as well as myeloid cells in n=18/18 samples from the 1 st major cluster (termed 'multilineage'). In the 2 nd major cluster ('lymphoid'), BCR::ABL1 was restricted to the lymphoid lineage in n=13/16 samples (p<0.001), with n=3/16 cases harboring BCR::ABL1-positive myeloid cells at lower frequencies compared to the multilineage cluster. In each cluster, two patients also harbored BCR::ABL1-positive mature B cells. T cells remained BCR::ABL1-negative. Diagnostic FACS data and analysis of proximity to normal human lymphoid gene expression confirmed more frequent myeloid co-expression and higher proximity to normal pro-B cells in the multilineage cluster, whereas lymphoid cases had increased lymphoid surface marker expression and a stronger proximity to normal pre-B I cells. Genomic profiling using WGS/SNParrays (n=160) revealed significant enrichment for genomic events in the four gene expression sub-clusters: focal deletions comprising exons 1 and 2 of HBS1-like translational GTPase ( HBS1L) or monosomy 7 were strongly enriched in the two multilineage sub-clusters ('delHBS1L'; n=20/27 vs. n=3/133 in remaining cohort or 'del7'; n=16/25 vs. n=10/135; p<0.001). Remarkably, a novel alternative HBS1L transcript with a putative TSS in intron 3 was highly expressed in both multilineage sub-clusters but not in BCR::ABL1 negative ALL cases or healthy B lymphoid progenitors, suggesting this transcript as novel cooperating event in multilineage BCR::ABL1-positive ALL. One lymphoid sub-cluster was enriched for homozygous deletions in IKZF1 ('IKZF1'; n=11/55 vs. n=4/105; p=0.008), whereas the other was enriched for homozygous CDKN2A/B deletions (n=21/53 vs. n=3/107; p<0.001) and PAX5 deletions (n=33/53 vs n=26/107; p<0.001; 'CDKN2A/PAX5'). Hyperdiploid karyotypes were exclusive to the lymphoid main cluster, mostly in CDKN2A/PAX5. We analyzed the clinical implications of these newly established BCR::ABL1-positive ALL subtypes in our homogenously treated GMALL adult patient cohort (n=98, first diagnosis 2014-2021) including TKI treatment combined with age-adapted chemotherapy, MRD monitoring and allo-SCT in 1 st CR (n=84/98, 86%). Overall survival (OS) at 3 years was uniformly high in multilineage and lymphoid cases (70%±6% vs. 70%±8%; p=0.890; Figure B). However, analysis of the sub-clusters revealed an inferior 3-years OS for the IKZF1 -/- enriched cluster in contrast to excellent outcome in hyperdiploid cases and intermediate outcomes in the remaining sub-clusters (Figure B). These data highlight that transcriptomic signatures in BCR::ABL1-positive ALL are driven by developmental disease origins (‘lymphoid’ vs. ‘multilineage‘) and specific patterns of corresponding genomic events. Novel molecular subtypes of BCR::ABL1-positive ALL have distinct outcomes in the context of current GMALL treatment protocols. Gene-expression based subtype definitions enable classification of BCR::ABL1-positive ALL according to ICC definitions based on RNA-Seq data alone. These definitions have been implemented in ALLCatchR - our freely available tool for ALL subtype allocation - to facilitate validation and application in clinical diagnostics.

Acute lymphoblastic leukemia (ALL) represents the most frequent malignancy in children, and relapse/refractory (r/r) disease is difficult to treat, both in children and adults. In search for novel treatment options against r/r ALL, we studied inhibitor of apoptosis proteins (IAP) and Smac mimetics (SM). SM‐sensitized r/r ALL cells towards conventional chemotherapy, even upon resistance against SM alone. The combination of SM and chemotherapy‐induced cell death via caspases and PARP, but independent from cIAP‐1/2, RIPK1, TNFα or NF‐κB. Instead, XIAP was identified to mediate SM effects. Molecular manipulation of XIAP in vivo using microRNA‐30 flanked shRNA expression in cell lines and patient‐derived xenograft (PDX) models of r/r ALL mimicked SM effects and intermediate XIAP knockdown‐sensitized r/r ALL cells towards chemotherapy‐induced apoptosis. Interestingly, upon strong XIAP knockdown, PDX r/r ALL cells were outcompeted in vivo, even in the absence of chemotherapy. Our results indicate a yet unknown essential function of XIAP in r/r ALL and reveal XIAP as a promising therapeutic target for r/r ALL. Smac mimetics sensitize relapsed/refractory acute leukemia (r/r ALL) cell lines towards chemotherapy, independently from TNFα, RIPK1, NFκB and cIAP1/2 signaling. Knockdown in PDX models shows that XIAP harbors an essential function in vivo and represents an important therapeutic target for r/r ALL. Smac mimetics sensitize relapsed/refractory acute leukemia (r/r ALL) cell lines towards chemotherapy, independently from TNFα, RIPK1, NFκB and cIAP1/2 signaling. Knockdown in PDX models shows that XIAP harbors an essential function in vivo and represents an important therapeutic target for r/r ALL.

In the byline on page 4052, “Tessa-Lara Skoblyn” should read “Tessa Lara Skroblyn.” Furthermore, the byline and author affiliations omitted an author, Quy A. Ngo. The byline and author affiliations should read as follows: Beat Bornhauser, Gunnar Cario, Anna Rinaldi, Thomas Risch, Virginia Rodriguez Martinez, Moritz Sch€ utte, Hans-J€ org Warnatz, Nastassja Scheidegger, Paulina Mirkowska, Martina Temperli, Claudia M€ oller, Angela Schumich, Michael Dworzak, Andishe Attarbaschi, Monika Br€ uggemann, Mathias Ritgen, Ester Mejstrikova, Andreas Hofmann, Barbara Buldini, Pamela Scarparo, Giuseppe Basso, Oscar Maglia, Giuseppe Gaipa, Tessa Lara Skroblyn, Quy A. Ngo, Geertruij te Kronnie, Elena Vendramini, Renate Panzer-Gr€ umayer, Malwine Jeanette Barz, BlerimMarovca, Mathias Hauri-Hohl, Felix Niggli, Cornelia Eckert, Martin Schrappe, Martin Stanulla, Martin Zimmermann, Bernd Wollscheid, Marie-Laure Yaspo, and Jean-Pierre Bourquin

Chemotherapy is a standard treatment for pediatric acute lymphoblastic leukemia (ALL), which sometimes relapses with chemoresistant features. However, whether acquired drug-resistance mutations in relapsed ALL pre-exist or are induced by treatment remains unknown. Here we provide direct evidence of a specific mechanism by which chemotherapy induces drug-resistance-associated mutations leading to relapse. Using genomic and functional analysis of relapsed ALL we show that thiopurine treatment in mismatch repair (MMR)-deficient leukemias induces hotspot TP53 R248Q mutations through a specific mutational signature (thio-dMMR). Clonal evolution analysis reveals sequential MMR inactivation followed by TP53 mutation in some patients with ALL. Acquired TP53 R248Q mutations are associated with on-treatment relapse, poor treatment response and resistance to multiple chemotherapeutic agents, which could be reversed by pharmacological p53 reactivation. Our findings indicate that TP53 R248Q in relapsed ALL originates through synergistic mutagenesis from thiopurine treatment and MMR deficiency and suggest strategies to prevent or treat TP53 -mutant relapse.

Abstract Chemotherapy is curative for most children with acute lymphoblastic leukemia (ALL). Here we provide direct evidence that thiopurine chemotherapeutics can also directly induce drug resistance mutations leading to relapse. Using a large relapsed ALL cohort assembled from Chinese, US and German patients, we found that TP53 R248Q mutations were highly enriched at relapse compared to diagnosis. Relapse-specific TP53 R248Q was associated with the acquisition of MMR deficiency mutations in MSH2, MSH6, or PMS2 and a novel relapse-specific mutational signature. Using isogenic MCF10A cells with or without engineered MSH2 knockout, and the Nalm6 ALL cell line which has native MMR deficiency, we found that this novel signature was caused by a synergistic mutagenic interaction between thiopurine treatment and mismatch repair (MMR) deficiency (called the thio-dMMR signature) that contributes to a hypermutator phenotype and acquisition of TP53 R248Q in residual ALL during remission. Treatment-induced TP53-mutant clones then expand due to broad chemoresistance, leading to eventual relapse. Indeed, thiopurines preferentially induced C>T mutations at the center of NCG trinucleotides, which can lead to TP53 R248Q, and the thiopurine mutation rate was accelerated 2- to 10-fold in MMR-deficient ALL and cell lines. Thiopurine treatment induced C>T mutations preferentially on the transcribed strand, rather than the untranscribed strand, of mRNAs, which further increased the likelihood of TP53 R248Q induction. Further, experimental thiopurine treatment was able to directly induce TP53 R248Q variants in MMR-deficient cultured cells, including Nalm6 and MCF10A MSH2-/-, by activating the thio-dMMR mutational signature, while MMR-proficient MCF10A cells did not experience R248Q induction. The sequential acquisition of MMR deficiency mutations, followed by TP53 mutations, during post-diagnosis ALL evolution was supported by clonal evolution analysis of serial patient samples. p53 R248Q promoted resistance to multiple ALL chemotherapeutic agents, and was associated with on-treatment relapse and poor relapse-treatment response. Our findings indicate that the enrichment of TP53 R248Q in relapsed ALL is due to synergistic mutagenesis from thiopurine treatment and MMR deficiency, followed by selection for TP53 R248Q's chemoresistance phenotype. This suggests that cancer drug resistance mutations may not always pre-exist subclonally at diagnosis, but may be therapy-induced in some patients. Additionally, the qualitative and quantitative mutational signature output of a mutagen (e.g., thiopurines) can vary based on the genetic background. Finally, our findings suggest potential therapeutic strategies, including avoiding thiopurine treatment in MMR-deficient relapses, and therapeutic p53 mutant reactivation, to deal with this genetically-unstable, chemoresistant disease. Citation Format: Fan Yang, Samuel W. Brady, Huiying Sun, Chao Tang, Lijuan Du, Malwine Barz, Xiaotu Ma, Yao Chen, Houshun Fang, Xiaomeng Li, Pandurang Kolekar, Omkar Pathak, Jiaoyang Cai, Lixia Ding, Tianyi Wang, Arend von Stackelberg, Shuhong Shen, Caiwen Duan, Cornelia Eckert, Hongzhuan Chen, Yu Liu, Jeffery M. Klco, Hui Li, Benshang Li, Jinghui Zhang, Renate Kirschner-Schwabe, Bin-Bing S. Zhou. Thiopurines and mismatch repair deficiency cooperate to fuel TP53 mutagenesis and ALL relapse [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 633.

Activating mutations in cytosolic 59-nucleotidase II (NT5C2) are considered to drive relapse formation in acute lymphoblastic leukemia (ALL) by conferring purine analog resistance. To examine the clinical effects of NT5C2 mutations in relapsed ALL, we analyzed NT5C2 in 455 relapsed B-cell precursor ALL patients treated within the ALL-REZ BFM 2002 relapse trial using sequencing and sensitive allele-specific real-time polymerase chain reaction. We detected 110 NT5C2 mutations in 75 (16.5%) of 455 B-cell precursor ALL relapses. Two-thirds of relapses harbored subclonal mutations and only one-third harbored clonal mutations. Event-free survival after relapse was inferior in patients with relapses with clonal and subclonal NT5C2 mutations compared with those without (19% and 25% vs 53%, P <.001). However, subclonal, but not clonal, NT5C2 mutations were associated with reduced event-free survival in multivariable analysis (hazard ratio, 1.89; 95% confidence interval, 1.28-2.69; P = .001) and with an increased rate of nonresponse to relapse treatment (subclonal 32%, clonal 12%, wild type 9%, P <.001). Nevertheless, 27 (82%) of 33 subclonal NT5C2 mutations became undetectable at the time of nonresponse or second relapse, and in 10 (71%) of 14 patients subclonal NT5C2 mutations were undetectable already after relapse induction treatment. These results show that subclonal NT5C2 mutations define relapses associated with high risk of treatment failure in patients and at the same time emphasize that their role in outcome is complex and goes beyond mutant NT5C2 acting as a targetable driver during relapse progression. Sensitive, prospective identification of NT5C2 mutations is warranted to improve the understanding and treatment of this aggressive ALL relapse subtype.

Most relapses of acute lymphoblastic leukemia (ALL) occur in patients with a medium risk (MR) for relapse on the Associazione Italiana di Ematologia e Oncologia Pediatrica and Berlin-Frankfurt-Münster (AIEOP-BFM) ALL protocol, based on persistence of minimal residual disease (MRD). New insights into biological features that are associated with MRD are needed. Here, we identify the glycosylphosphatidylinositol-anchored cell surface protein vanin-2 (VNN2; GPI-80) by charting the cell surface proteome of MRD very high-risk (HR) B-cell precursor (BCP) ALL using a chemoproteomics strategy. The correlation between VNN2 transcript and surface protein expression enabled a retrospective analysis (ALL-BFM 2000; N = 770 cases) using quantitative polymerase chain reaction to confirm the association of VNN2 with MRD and independent prediction of worse outcome. Using flow cytometry, we detected VNN2 expression in 2 waves, in human adult bone marrow stem and progenitor cells and in the mature myeloid compartment, in line with proposed roles for fetal hematopoietic stem cells and inflammation. Prospective validation by flow cytometry in the ongoing clinical trial (AIEOP-BFM 2009) identified 10% (103/1069) of VNN2+ BCP ALL patients at first diagnosis, primarily in the MRD MR (48/103, 47%) and HR (37/103, 36%) groups, across various cytogenetic subtypes. We also detected frequent mutations in epigenetic regulators in VNN2+ ALLs, including histone H3 methyltransferases MLL2, SETD2, and EZH2 and demethylase KDM6A. Inactivation of the VNN2 gene did not impair leukemia repopulation capacity in xenografts. Taken together, VNN2 marks a cellular state of increased resistance to chemotherapy that warrants further investigations. Therefore, this marker should be included in diagnostic flow cytometry panels.