Molecular subgroups of T-cell acute lymphoblastic leukemia in adults treated according to pediatric-based GMALL protocols.

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.

The Gene Expression Classifier ALLCatchR Identifies B-cell Precursor ALL Subtypes and Underlying Developmental Trajectories Across Age.

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.

Isocitrate dehydrogenase 1 mutation drives leukemogenesis by PDGFRA activation due to insulator disruption in acute myeloid leukemia (AML).

Acute myeloid leukemia (AML) is characterized by complex molecular alterations and driver mutations. Elderly patients show increased frequencies of IDH mutations with high chemoresistance and relapse rates despite recent therapeutic advances. Besides being associated with global promoter hypermethylation, IDH1 mutation facilitated changes in 3D DNA-conformation by CTCF-anchor methylation and upregulated oncogene expression in glioma, correlating with poor prognosis. Here, we investigated the role of IDH1 p.R132H mutation in altering 3D DNA-architecture and subsequent oncogene activation in AML. Using public RNA-Seq data, we identified upregulation of tyrosine kinase PDGFRA in IDH1-mutant patients, correlating with poor prognosis. DNA methylation analysis identified CpG hypermethylation within a CTCF-anchor upstream of PDGFRA in IDH1-mutant patients. Increased PDGFRA expression, PDGFRA-CTCF methylation and decreased CTCF binding were confirmed in AML CRISPR cells with heterozygous IDH1 p.R132H mutation and upon exogenous 2-HG treatment. IDH1-mutant cells showed higher sensitivity to tyrosine kinase inhibitor dasatinib, which was supported by reduced blast count in a patient with refractory IDH1-mutant AML after dasatinib treatment. Our data illustrate that IDH1 p.R132H mutation leads to CTCF hypermethylation, disrupting DNA-looping and insulation of PDGFRA, resulting in PDGFRA upregulation in IDH1-mutant AML. Treatment with dasatinib may offer a novel treatment strategy for IDH1-mutant AML.

Myeloid checkpoint blockade improves killing of T-acute lymphoblastic leukemia cells by an IgA2 variant of daratumumab.

Antibody-based immunotherapy is increasingly employed to treat acute lymphoblastic leukemia (ALL) patients. Many T-ALL cells express CD38 on their surface, which can be targeted by the CD38 antibody daratumumab (DARA), approved for the treatment of multiple myeloma. Tumor cell killing by myeloid cells is relevant for the efficacy of many therapeutic antibodies and can be more efficacious with human IgA than with IgG antibodies. This is demonstrated here by investigating antibody-dependent cellular phagocytosis (ADCP) by macrophages and antibody-dependent cell-mediated cytotoxicity (ADCC) by polymorphonuclear (PMN) cells using DARA (human IgG1) and an IgA2 isotype switch variant (DARA-IgA2) against T-ALL cell lines and primary patient-derived tumor cells. ADCP and ADCC are negatively regulated by interactions between CD47 on tumor cells and signal regulatory protein alpha (SIRPα) on effector cells. In order to investigate the impact of this myeloid checkpoint on T-ALL cell killing, CD47 and glutaminyl-peptide cyclotransferase like (QPCTL) knock-out T-ALL cells were employed. QPTCL is an enzymatic posttranslational modifier of CD47 activity, which can be targeted by small molecule inhibitors. Additionally, we used an IgG2σ variant of the CD47 blocking antibody magrolimab, which is in advanced clinical development. Moreover, treatment of T-ALL cells with all-trans retinoic acid (ATRA) increased CD38 expression leading to further enhanced ADCP and ADCC, particularly when DARA-IgA2 was applied. These studies demonstrate that myeloid checkpoint blockade in combination with IgA2 variants of CD38 antibodies deserves further evaluation for T-ALL immunotherapy.