Leukemia

CD8 T cells are key mediators of anti-tumor immunity, yet their differentiation states and clonal architecture within the acute myeloid leukemia (AML) bone marrow microenvironment remain incompletely defined. We performed high dimensional immune profiling of bone marrow samples from 46 newly diagnosed AML patients using mass cytometry to probe the microenvironment and T cell states. We used single-cell RNA and T cell receptor (TCR) sequencing to define CD8 T cell phenotypes, transcriptional states, and clonal architecture. AML-associated CD8 T cells were skewed toward terminally differentiated effector memory cells re-expressing CD45RA (TEMRAs), while canonically exhausted T cell populations were rare. Functional studies revealed that TEMRA CD8 T cells robustly produced IFN{gamma} and TNF upon in vitro stimulation. Clonal expansion was concentrated within the TEMRA compartment. Comparison of TCR sequences with known viral epitopes identified a small subset of expanded viral-specific clonotypes, while the majority of highly expanded clonotypes had unknown specificity and may include AML-specific T cells. Differential gene expression analysis revealed shared cytotoxic effector programs during clonal expansion but diverging activation signatures: viral-specific clones upregulated canonical T cell receptor signaling genes, whereas expanded clones of unknown specificity exhibited enrichment of natural killer (NK) receptor-associated genes. These genes comprised the leukemia-associated NK-immune (LaNKi) score which was elevated in an independent AML dataset compared to pan cancer tumor infiltrating lymphocytes. These findings define the CD8 T cell differentiation landscape and clonal architecture in AML marrow at diagnosis and suggest that T cell dysfunction in AML diverges from classical activation and exhaustion paradigms.

Background: Relapse remains the principal cause of treatment failure in pediatric acute leukemia. Clinically validated minimal residual disease (MRD) assays - multiparameter flow cytometry, immunoglobulin/T-cell-receptor rearrangement sequencing, and targeted next-generation sequencing panels -- are highly sensitive but read out predefined features and do not reconstruct clonal architecture or link a cell's genotype to its functional state. We systematically reviewed what single-cell sequencing has revealed about clonal evolution, chemoresistance, the immune microenvironment, and post-therapeutic immune dynamics in this disease. Methods: This review followed PRISMA 2020. PubMed/MEDLINE, the Cochrane Library, and Google Scholar were searched to September 2026 for primary studies applying single-cell DNA, RNA, chromatin-accessibility, surface-protein, or immune-repertoire sequencing to pediatric acute leukemia samples or pediatric-derived models. Risk of bias in non-randomized studies was assessed with ROBINS-I. Because designs, platforms, and outcomes were heterogeneous, findings were synthesized narratively by biologic theme without meta-analysis, following the SWiM guideline. Results: Of 63 records identified, 10 studies were included (published 2016-2026; 6-159 patients or samples per study; up to ~700,000 cells profiled). Single-cell DNA sequencing traced minor NOTCH1-mutant diagnostic subclones into PTEN- or TP53-mutant relapse clones that bulk sequencing missed. Rare dormant, label-retaining cells and developmental-state-dependent drug sensitivity defined chemoresistant compartments. Remodeling of the bone marrow immune microenvironment identified patients with adverse outcome among those classified as MRD-low, and pre-infusion CAR T-cell type 2 functionality and post-transplant cytotoxic memory CD8+ T-cell subsets were associated with durable remission. Of the seven studies assessed with ROBINS-I, four were at moderate and three at serious overall risk of bias, driven chiefly by small, selected cohorts. Conclusions: Single-cell sequencing yields mechanistic insight that complements, rather than replaces, clinically validated MRD assays, and nominates candidate biomarkers for risk stratification, treatment selection, cell-therapy manufacturing, and post-transplant monitoring. The evidence remains preliminary; adequately powered, prospective, and harmonized studies are required before clinical adoption.

Background: The clinical course of acute leukemias and related hematologic neoplasms is defined by aggressive clonal proliferation, severe hematopoietic disruption, and recurrent molecular alterations. Although serial bone marrow biopsies, multiparameter flow cytometry, and next-generation sequencing remain standard surveillance modalities, procedural invasiveness, high costs, and operational turnaround times limit their frequency. Minimally invasive, scalable biomarkers integrating routine hematologic indices, targeted gene expression, circulating oncoprotein levels, and patient compliance metrics may provide an accessible framework for dynamic monitoring. Methods: In this longitudinal cohort study of 66 patients across 272 serial encounters (discrete follow-up intervals: days 0, 14, 41, 71, and 78), we assessed the prognostic value of peripheral complete blood counts (white blood cell count [WBC], hemoglobin [Hb]), molecular indicators (FLT3, NPM1, and DNMT3A transcript levels; targeted soluble FLT3 quantification), and medication adherence. The primary clinical endpoint was longitudinal progression to critical deterioration or disease-related mortality. Generalized linear mixed-effects models (GLMM) with patient-specific random intercepts were constructed to account for intra-subject repeated measures. Predictors were standardized per 1-SD increment. Model performance was assessed via the Akaike Information Criterion (AIC) and the Concordance index (C-index). Results: Leukocyte expansion correlated inversely with hemoglobin concentration (r=-0.877, p<0.001), reflecting bone marrow infiltration and secondary erythroid suppression. Multivariable mixed-effects modeling confirmed that elevated WBC count (adjusted odds ratio [aOR] = 1.52 per 1-SD increase; 95% CI: 1.24-1.86; p<0.001) and reduced medication adherence (aOR = 0.58; 95% CI: 0.44-0.76; p<0.001) independently predicted adverse clinical transition. Integrating targeted molecular markers (FLT3 expression and soluble protein levels) with routine hematologic indices and adherence demonstrated superior calibration and discrimination over single-domain models ({Delta}AIC[&ge;]116; Harrells C-index = 0.81). Conclusions: Readily accessible peripheral hematologic indices, targeted molecular quantification, and medication adherence provide complementary prognostic information regarding disease activity. Integrating these low-burden parameters into clinical workflows offers an efficient, scalable paradigm for early risk stratification in hematologic malignancies.

CBFA2T3-GLIS2 (C/G) defines a high-risk pediatric AML subtype in which de novo enhancer rewiring sustains an aggressive leukemic transcriptional state. The early epigenomic mechanisms reinforcing this program and linking it to leukemic survival remain incompletely defined. Here, we identify enhancer-proximal hypermethylation as a noncanonical, transcription-permissive feature of C/G AML. Using primary C/G-positive AML samples and a developmentally relevant C/G-transformed cord blood hematopoietic stem/progenitor cell model, we integrated DNA methylation, chromatin state, fusion occupancy, and gene expression across early and leukemia-stage contexts. Early C/G-associated hypermethylated regions localized near H3K27ac/H3K4me1-marked active or primed cis-regulatory elements, were enriched for ERG/ETS-like motifs, and showed related architecture in leukemia-stage contexts. DNMT3B was prominently increased in C/G contexts, and its loss selectively altered methylation-associated gene expression without measurably changing global 5mC. Genetic DNMT3B loss increased venetoclax sensitivity in vitro, while pharmacologic DNMT3B inhibition with Nanaomycin-A similarly enhanced venetoclax response. During venetoclax treatment, DNMT3B-deficient xenografts showed reduced disease burden and prolonged survival. To assess whether this interaction extended to clinically used hypomethylating agents, azacitidine or decitabine plus venetoclax induced apoptosis-related transcriptional programs and mitochondrial depolarization. These findings identify hypermethylated active cis-regulatory elements as C/G-associated states linked to transcriptional dysregulation and venetoclax response.

Background: Epigenetic deregulation is a defining feature of leukemia, and DNA methylation and chromatin accessibility profiles encode the cell of origin, lineage and clinical behaviour of the disease. Artificial intelligence (AI) and machine learning (ML) can extract predictive patterns from these high-dimensional data, but the published models have not been systematically appraised. We systematically reviewed AI models built on epigenomic data in leukemia for diagnosis, prognosis, relapse and treatment-response prediction, and measurable residual disease (MRD) detection. Methods: This review followed PRISMA 2020 and the SWiM guideline. PubMed was searched on 7 October 2026 with three structured queries, supplemented by a broader PubMed query, citation searching and web searching. Eligible studies were peer-reviewed primary studies that applied an ML or deep-learning algorithm to DNA methylation, chromatin-accessibility or histone-modification data from human leukemia samples and reported a quantitative diagnostic, prognostic, response or MRD outcome. Risk of bias and applicability were assessed with PROBAST, informed by PROBAST+AI. Owing to heterogeneity, results were synthesized narratively and in structured tables, without meta-analysis. Results: Of 68 unique database records and 32 reports from other sources, 30 studies (2010-2026; 22 since 2020) were included: 16 in acute myeloid leukemia, 4 in acute lymphoblastic leukemia, 2 spanning acute leukemia lineages, 3 in juvenile myelomonocytic leukemia and 5 in chronic lymphocytic leukemia; 10 were pediatric. DNA methylation was the input in 28 studies and chromatin accessibility in 2; no eligible study modelled histone marks. Tree ensembles (n = 9) and support vector machines (n = 5) were the most frequent algorithms. Diagnostic classifiers reported accuracy, concordance or F1 scores of 0.87-1.00, and two classifiers were applied to nanopore sequencing data, one returning acute leukemia subtype calls within about 2 hours. Prognostic epigenomic scores were associated with survival (reported hazard ratios 2.36-10.82), but discrimination fell on transport to independent cohorts (C-index 0.677 internally vs 0.529 in one external cohort). Fifteen studies validated models on an external epigenomic cohort, one prospectively. Overall risk of bias was high in 21 studies, unclear in 8 and low in 1, driven by the analysis domain (small samples, absent calibration, possible data leakage). Calibration was reported in 3 studies and code was available for 11. Conclusions: Epigenomic AI models classify leukemia subtypes with high reported accuracy and can deliver same-day diagnoses, and methylation-based scores add prognostic information. However, the evidence is dominated by retrospective, high-risk-of-bias development studies with limited external validation and almost no prospective or impact evaluation. Prospective, multi-center validation with calibrated, transparently reported models is required before clinical adoption.

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy associated with a poor prognosis and an unmet need for more effective treatment options, particularly after relapse. One potential approach to address this need, which has been used successfully in solid tumors, is adoptive transfer of T cells engineered to express specific T cell receptors (TCRs). Particularly attractive are TCRs that can target epitopes derived from oncogenes on which cancer cells depend while sparing normal cells that do not harbor the mutation. One promising oncogenic target in AML is mutated nucleophosmin 1 (mtNPM1), present in up to 30% of AML cases. Most NPM1 mutations result in a common frameshifted sequence that generates peptides presented by several class I human leukocyte antigens (HLAs), such as HLA-A*11:01. In this study, we vaccinated HLA-A*11:01-transgenic mice with the mtNPM1 peptide AVEEVSLRK and isolated six functional TCRs from mtNPM1-reactive lymphocytes. When engineered into human T cells, two of these TCRs consistently mediated robust and specific lysis of an AML cell line and primary AML cells co-expressing HLA-A*11:01 and mtNPM1. Neither TCR recognized related human peptides, HLA-A*11:01-expressing normal peripheral blood mononuclear cells or stem/progenitor cells, or cells expressing diverse allogeneic HLAs, suggesting a low risk of cross-reactivity and alloreactivity. In an AML xenograft model, both TCRs controlled AML in hematopoietic organs, although extramedullary tumors emerged during treatment, potentially reflecting the aggressive behavior of the model that may not be representative of AML in patients. Together, these data suggest that the two TCRs represent strong candidates for further preclinical development in adoptive T cell therapy for NPM1-mutated, HLA-A*11:01-positive AML. These results also support the use of HLA-transgenic mice as a platform for generating TCRs targeting oncogene-derived epitopes in hematologic malignancies.

Venetoclax and azacitidine (ven-aza) is a standard of care therapy for newly diagnosed acute myeloid leukemia (AML) patients unfit to receive intensive therapy, and may also be appropriate for certain fit patients. Models predicting response to ven-aza currently focus predominantly on genetics. Here, we present two multimodal fusion models: a custom ResNet-34-based model and a pathology foundation model fine-tuned for bone marrow smear (BMS) images that combine clinical and genetic variables with whole slide images. Training on 193 newly diagnosed AML patients who received ven-aza, we obtained an area-under-the-receiver-operating-characteristic (AUROC) of 0.79 and 0.82 for the ResNet-based and fine-tuned foundation models in a heldout test set, and 0.76 and 0.73 in an external validation set, predicting best response to this therapy. Sensitivity analysis showed that fusing image data with clinical and genetic variables outperformed training on either modality alone. In univariable and multivariable analyses, image-based classification was an independent predictive marker, second only in effect size to IDH1/2 mutation status, outperforming other genetic alterations. Image-based explainability showed high model attention on myeloblasts, suggesting previously unrecognized cell-specific patterns associated with response. Our findings suggest BMS images complement genetic biomarkers to refine outcome prediction in ven-aza treatment and incentivize AI-supported outcome prediction, including bone marrow morphology.

Acute myeloid leukemia (AML) remains limited by high relapse rates and a scarcity of biomarker-directed therapies, underscoring the need to identify actionable vulnerabilities and mechanisms of therapeutic resistance. O6-methylguanine-DNA methyltransferase (MGMT), a DNA repair enzyme that directly reverses mutagenic O6-alkylguanine lesions, is epigenetically silenced in multiple cancers. Although MGMT silencing is predictive of temozolomide (TMZ) response in glioblastoma with significant survival advantage, prior clinical trials of TMZ in AML have shown only modest responses. Therefore, the prevalence and therapeutic relevance of MGMT silencing, as well as genetic factors that modify its therapeutic response in AML, remain to be comprehensively investigated. Here, we first profiled MGMT status across a diverse cohort of 23 de novo and 16 relapsed/refractory (R/R) primary AMLs using an integrated analysis of MGMT mRNA expression, promoter methylation, and protein expression. We found that approximately 25-30% of AMLs harbor MGMT silencing, in contrast to consistent MGMT expression in healthy CD34+ hematopoietic stem and progenitor cells. We further identified frequent loss of mismatch repair (MMR) proteins in these AML cohorts, a known resistance mechanism against TMZ in glioblastoma. Using CRISPR knockout screening and genetically engineered AML models, we found that MMR loss also drives both upfront and acquired TMZ resistance in MGMT-silenced AML. These findings identify MMR deficiency as an important and previously underappreciated genetic contributor to the modest responses observed in prior trials of TMZ in AML. To therapeutically exploit MGMT silencing while bypassing genetic determinants of resistance, including MMR deficiency, we evaluated clinically and preclinically characterized MGMT-dependent DNA-alkylating agents and identified a fluoroethylating analog of TMZ, N3-(2-fluoroethyl) imidazotetrazine (KL50), with pronounced and selective activity in MGMT-silenced AML. KL50 retained antileukemic activity irrespective of MMR status, significantly prolonging survival in humanized MISTRG6 mice harboring primary AML patient-derived xenografts. Mechanistically, KL50 induced DNA damage through the time-dependent formation of interstrand DNA crosslinks, bypassing MMR dependence and triggering a replication stress response dominated by ATR signaling. Pharmacologic ATR inhibition synergized with KL50, producing marked antileukemic activity and significantly extending survival across AML models without compromising hematologic safety. Together, these findings establish MGMT silencing as a prevalent and therapeutically actionable biomarker in AML, define MMR status as a key determinant of TMZ response in AML but not KL50 sensitivity, and provide a translational rationale for combining low-dose O6-fluoroethylating imidazotetrazines with ATR inhibitors to target both de novo and R/R AML across diverse genetic backgrounds.

Integrating heterogeneous molecular and clinical data into unified, clinically meaningful patient representations remains a major challenge in precision medicine. Here, we present SurvMOCA-GNN, a biologically informed multi-omics integration framework that explicitly incorporates biological network structure, cross-omics regulatory relationships, and patient-specific clinical information to generate unified patient representations. Using gene expression, microRNA expression, and clinical data from the TCGA-LAML cohort, SurvMOCA-GNN revealed patient representations that identified prognostically distinct patient groups and further stratified patients within established European LeukemiaNet 2022 risk categories. Systematic ablation analyses demonstrated that incorporation of graph-based modeling, cross-omics attention, adaptive clinical integration, and biological prior knowledge progressively improved integration quality, resulting in more structured patient representations and stronger prognostic stratification. Compared with existing multi-omics integration approaches, SurvMOCA-GNN consistently produced more biologically coherent patient representations with improved survival discrimination. Evaluation in an independent AML cohort, together with transfer learning analyses, further demonstrated the robustness and transferability of the integrated representations across heterogeneous patient populations. Together, these findings demonstrate that biologically informed multi-omics integration reveals clinically meaningful patient representations and provides a general framework for integrating heterogeneous molecular and clinical data to improve patient stratification in AML and potentially other diseases. The SurvMOCA-GNN framework is freely available at https://github.com/tjgu/SurvMOCA-GNN.git.

Dual PARP1/2 inhibitors (PARPi) selectively eliminate BRCA1/2-deficient cancers and represent the first targeted therapy for homologous recombination (HR)-deficient cancers. However, their use in maintenance therapy is limited by severe anemia and an increased risk for therapy-related leukemia. These toxicities are unexpected because PARP1 loss, which eliminates most DNA-damage-induced PARylation, does not cause anemia in mice. In contrast, PARP2 loss or catalytic inactivation causes anemia, motivating the development of PARP1-selective inhibitors. Using wild-type (WT), Parp1-/- and Parp2-/- mice, we show that hematopoietic toxicity of FDA-approved PARPi is driven primarily by inactive PARP1 rather than PARP2 inhibition. Accordingly, PARP1-selective inhibitors also cause PARP1-dependent anemia. Somatic expression of catalytically inactive Parp1 (Parp1E988A) causes lethal bone marrow failure, not found with somatic deletion of both Parp1&2. Mechanistically, inactive PARP1 obstructs the repair of diverse DNA lesions, including gaps, nicks, and Top1-cc, in contrast to the nick-selectivity of Parp2. In cells, inactive PARP1 compromises PARP2 recruitment to DNA lesions and causes severe genomic instability and mitotic bridges absent in Parp1&2-null cells. Thus, PARPi-induced hematopoietic toxicity is driven primarily by PARP1 inactivation, informing the design and use of next-generation PARP inhibitors.

Adult T-cell leukemia/lymphoma (ATL) is an aggressive HTLV-1-associated malignancy with poor responses to chemotherapy. Although constitutive NF-kB activation is a hallmark of ATL, its persistence in tax-negative (Type I) ATL, where Tax is irreversibly silenced, remains unresolved. Here, we identify Fra-2 as a coactivator of NF-kB p65 that redirects p65's transcriptional activity toward inflammatory genes. Mechanistically, Fra-2 interacts with the Rel homology domain of p65 via its bZIP domain, enhancing p65 DNA-binding activity without altering nuclear localization. The HTLV-1 antisense protein HBZ disrupts Fra-2/JunD AP-1 complexes while stabilizing Fra-2/p65, as shown by co-immunoprecipitation, BiFC, and PICO assays. This rewiring selectively enhances NF-kB-dependent transcription of IL-1b, which is elevated in ATL patient sera and cells independently of proviral load. Chromatin immunoprecipitation revealed Fra-2 recruitment to NF-kB response elements in the IL1b promoter, an effect amplified by HBZ. Pharmacological inhibition of IL-1 signaling with anakinra or anti-IL-1b antibodies restored doxorubicin sensitivity in primary ATL cells. Together, these findings establish the Fra-2-NF-kB-IL-1b axis as a driver of chemoresistance in tax-negative ATL and a therapeutically targetable vulnerability.

Germline mutations in the RNA helicase DDX41 are the most common genetic predisposition to myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML), representing 5-7% of AML. Over 70% of patients acquire a somatic mutation at specific hotspots (R525H/G530D) in the helicase domain of DDX41 in trans, which is linked to disease progression. DDX41 has diverse cellular functions, including RNA splicing, ribosome biogenesis, R-loop resolution and inflammation. However, the mechanisms by which somatic DDX41 mutations drive MDS/AML pathogenesis are yet to be determined. Here, we systematically evaluated the function of pathogenic, missense germline and somatic DDX41 mutations. We report that DDX41 somatic mutations are gain of function alleles and fail to rescue AML cell growth, distinct from germline DDX41 mutations. DDX41 somatic mutations R525H and G530D drive widespread splicing changes in isogenic AML cell lines, consistent in genetically engineered murine bone marrow HSPCs and CD34+ cells from DDX41-mutant MDS/AML patients. Mechanistically, DDX41-R525H exhibits increased RNA binding affinity compared to wildtype, with aberrantly spliced RNA targets overlapping with enriched binding. Strikingly, aberrant splicing of SEPTIN7 is enriched exclusively in CD34+ HSPCs of patients harboring both germline and somatic DDX41 mutations but absent in samples with germline mutation alone or lacking DDX41 mutations altogether. SEPTIN7 mis-splicing introduces a premature stop codon resulting in its downregulation at the protein level. SEPTIN7 is a known regulator of cytokinesis, HSC polarity and repopulation capacity. Our results identify a novel mis-spliced candidate, SEPTIN7, whose deregulation implicates a mechanism by which the DDX41 somatic mutations promote dysplastic hematopoiesis.

Glucocorticoids (GCs) are foundational to B-cell acute lymphoblastic leukemia (B-ALL) therapy, yet how glucocorticoid receptor (GR) activation interacts with lineage regulatory circuitry to shape therapeutic response remains incompletely understood. Using LEF1 to interrogate canonical Wnt regulatory circuitry, we show that GR activation reorganizes GR+LEF1 elements into recruitment, retention, and dissociation states. LEF1 dissociates from Wnt-responsive regulatory elements while being recruited to GRE-rich GR-associated elements that progressively acquire chromatin accessibility, H3K27ac, BRD4 and BRG1. RUNX1 and AP-1 show class-dependent redistribution across LEF1-defined states, extending organization beyond LEF1. GR+LEF1 reorganization is observed in patient-derived B-ALL. GR+LEF1 elements lose accessibility in GC-resistant B-ALL and during diagnosis-to-relapse evolution, with recruitment elements enriched for remodeling. Perturbation of resistance-associated GR+LEF1 elements at BIM and BMF alters GC-induced apoptotic signaling. Together, these findings identify Wnt/LEF1 circuitry as an interface through which therapeutic GR activation reorganizes the B-ALL regulatory landscape into states associated with glucocorticoid response and resistance.

Background: Metabolic plasticity contributes to therapeutic resistance in T-cell lymphoma, but the metabolic dependencies underlying tyrosine kinase inhibitor (TKI) resistance remain poorly understood. ATP citrate lyase (ACLY), which converts citrate to cytosolic acetyl-CoA, links glucose metabolism to lipogenesis and acetylation-dependent regulation. We hypothesized that ACLY represents an actionable metabolic vulnerability in lymphoma. Methods: Structure-guided drug discovery and biochemical screening were used to identify the novel ACLY inhibitor VCB1. VCB1 was evaluated against recombinant human ACLY and in TKI-sensitive and TKI-resistant lymphoma models. Antitumor activity was assessed by proliferation, cell-cycle analysis, apoptosis, and immunoblotting, followed by integrated transcriptomic, metabolomic, and lipidomic profiling. Results: Our xenograft study showed that ACLY dependence in ALK+ALCL. We discovered novel ACLY inhibitor VCB1 directly inhibited recombinant ACLY with uM potency (IC, 0.9 uM) and strongly suppressed lymphoma cell growth. In ALK inhibitor-sensitive SUPM2, VCB1 showed an IC of 0.299 uM and retained potency in lorlatinib-resistant SUPM2-LR1000 cells (1.62 uM), whereas BMS-303141 was substantially less active (17.46 and 22.07 uM). VCB1 similarly inhibited BTK inhibitor sensitive and resistant mantle cell lymphoma cell growth (IC, 0.28 and 0.278 uM), compared with BMS-303141 (30.5 and 37.01 uM). Multi-omics profiling revealed suppression of de novo lipogenesis, including ACACA, FASN, and PPARGC1B, together with extensive remodeling of triglyceride, phospholipid, cardiolipin, ceramide, and acylcarnitine species and increased expression of fatty-acid oxidation genes. VCB1 activated the integrated stress response (ISR), inducing ATF4, PPP1R15A, DDIT3, DDIT4 and SESN2, while disrupting purine and pyrimidine metabolism and reducing nucleotide biosynthetic genes, including CAD, DHODH, UCK2, and ATIC. VCB1 further activated an ACLY/ISR/CHAC1 axis associated with reduced GCLC/GCLM expression, glutathione depletion, and a decreased GSH/GSSG ratio, indicating impaired redox homeostasis. TKI-resistant cells exhibited distinct lipid-metabolic remodeling consistent with metabolic plasticity. VCB1 also altered immune-regulatory programs involving PDCD1, TIGIT, CD247, CD226, NFATC2, and inflammatory cytokines. Functionally, VCB1 induced cell cycle arrest and apoptosis. Conclusions: ACLY represents an integrated metabolic and signaling vulnerability in lymphoma. VCB1 suppresses lymphoma growth across TKI-sensitive and resistant models by disrupting lipid and nucleotide metabolism, metabolic adaptation and ISR and redox homeostasis supporting ACLY inhibition as a therapeutic strategy for TKI-resistant lymphoma.

Sphingolipids are bioactive lipids that regulate key signaling pathways both directly as ligands and through membrane re-organization. Ceramide sits at the center of this network and is considered pro-death in many contexts, making ceramide accumulation an attractive therapeutic strategy. Given the wide-ranging regulation of cellular responses this network exerts, better understanding ceramide metabolism may promote therapeutic efficacy of sphingolipid-based therapeutics. Ceramide glycosylation, catalyzed by glucosylceramide synthase (GCS; UGCG), is in turn widely regarded as a detoxification route thus limiting efficacy of ceramide- based therapeutics. Here we show the opposite. Delivery of short-chain C6-ceramide via a ceramide nanoliposome (CNL) induced organelle stress and cell death in chronic lymphocytic leukemia (CLL) via the accumulation of glycosphingolipids (GSLs), rather than through ceramide itself. Pharmacologic and genetic blockade of GCS protected B-cell leukemia, breast carcinoma, glioblastoma, lung adenocarcinoma, and non- malignant embryonic kidney cells from CNL-induced death. Conversely, exogenous C8-glucosylceramide was sufficient to kill cells that cannot degrade it. We show that GSL accumulation drives an ordered organelle response beginning with lysosomal deacidification, endoplasmic reticulum stress, followed by mitochondrial respiratory capacity decline, each attenuated by inhibition of GSL synthesis. These effects were accompanied by MLKL phosphorylation, increased activity of the stress sensor JNK and CHOP induction, with JNK inhibition partially protecting from death. These findings invert the prevailing view of ceramide glycosylation as a resistance mechanism and identify glycosphingolipid flux as a required effector arm of ceramide-directed therapy.

Clonal hematopoiesis (CH) can predict treatment outcomes in solid cancers, but the prevalence and clinical impact of CH in previously untreated, aggressive large B-cell lymphomas (LBCL) remains poorly characterized. Moreover, CH may be detected in cell-free DNA (cfDNA)-based biomarker assays, but the longitudinal dynamics of CH mutations during and after immunochemotherapy in LBCL remain unknown. Hence, we characterized the spectrum of CH mutations in 247 patients with high-risk primary LBCL from three phase II clinical trials. We identified CH mutations in 23% of patients. Compared with healthy controls, TET2 mutations were enriched in peripheral blood (PB) samples of LBCL patients (P=0.01). CH clone size showed high concordance between PB and cfDNA (R2=0.59, P<0.0001) but was not associated with circulating tumor DNA (ctDNA) concentration (P-values 0.25-0.86). In contrast with prior reports in the context of recurrent lymphoma, CH mutation status was not associated with overall survival (OS) (P=0.78) or progression-free survival (PFS) (P=0.89) in our primary LBCL cohort. CH clones showed variable longitudinal dynamics during immunochemotherapy, with 18% of evaluable patients developing mutant CH clones, mostly with TP53/PPM1D mutations. Together, CH mutations can be readily detected in cfDNA of lymphoma patients, but they do not predict survival in primary high-risk LBCL.

Bispecific T cell engagers (BTCEs) have transformed the treatment of B cell malignancies, but how they remodel non-conventional T cell circuits in patients, and how they should be ideally combined with existing treatment backbones, remains unclear. Here we show that CD3-engaging BTCEs convert human FOXP3 regulatory T cells (Tregs) into an AP-1-imprinted hybrid cytotoxic state that contributes to tumor clearance. Leveraging longitudinal bone marrow and peripheral blood sampling from patients with newly diagnosed multiple myeloma (NDMM) treated with BTCE-based induction in the phase 2 (GMMG-HD10/DSMM-XX/MajesTEC-5) trial, which achieves uniformly deep, minimal residual disease (MRD)-negative remissions, we integrate single-cell RNA, ATAC and TCR sequencing with functional and metabolic profiling to define the underlying mechanism. BTCE-containing induction drives expansion of cytotoxic CD8 clones and the emergence of a Treg population characterized by GZMA, GNLY and NKG7 expression, enriched cytotoxic gene signatures, and licensed by BATF-AP-1-centered chromatin remodeling. In vitro, BTCE-exposed Tregs acquire bona fide lytic function, killing tumor cells in a target- and dose-dependent manner and undergoing metabolic rewiring towards an effector-like state while retaining canonical Treg lineage markers. Immunomodulatory drugs (IMiDs) do not initiate but quantitatively amplify and qualitatively reshape this BTCE-driven cytotoxic program, providing a mechanistic rationale for BTCE-IMiD combination regimens. Cytotoxic Treg reprogramming is conserved across BTCEs targeting BCMA, GPRC5D, and CD19 and across multiple myeloma, as well as acute lymphoblastic leukemia. These findings reveal unexpected plasticity of human Tregs under synthetic T cell engagement and establish cytotoxic Tregs as active effectors, candidate biomarkers and tractable levers for optimizing T cell-redirecting immunotherapy.

Lenalidomide (Revlimid), bortezomib (Velcade), and dexamethasone, are used alone or in combination (RVd therapy) as first-line therapies for hematologic malignancies including the plasma cell dyscrasia, Multiple Myeloma (MM). The effects of RVd treatment on tumor cells have been documented, but little is known about their impacts on "healthy" immune cells. New therapeutics, including chimeric antigen receptor T cell (CAR-T) and bispecific T-cell engagers (BiTEs) depend on robust T cell function but these are often harvested for cellular therapies after or in tandem with RVd therapy. Understanding the molecular effects of these drugs on healthy T cells is therefore of particular importance. Since the molecular effects of each drug includes regulation of key transcription factors, we used a tri-modal, single-cell assay (TEA-seq), simultaneously profiling mRNA transcripts, cell surface proteins, and chromatin accessibility in primary human peripheral blood T cells treated for 4, 24, or 72 hours in vitro. Synergies and conflicts potentially arising from combinatorial therapy were identified and validated by flow cytometry. Doublet and triplet drug combinations were used to assess effects on cell-surface marker expression and on T cell activation. Our results suggest that T cell function can be optimized by the administration of these drugs individually and that sequential administration may offer an opportunity to enhance T cell function by affecting localization and altering T cell states. This work provides those interested in immunology, oncology, and cell therapies an opportunity to explore molecular pathways that could be manipulated by these commonly used drugs to modify T cell function.

B-cell lymphomas reprogram cellular metabolism to sustain their rapid growth and proliferation. Despite their close proximity to adipose tissue and the paradoxical association between obesity and improved lymphoma outcomes, how fatty-acid availability and dietary fat composition influence B-cell lymphoma remains poorly understood. Importantly, saturated fatty acids of different chain lengths have distinct routes of cellular uptake and metabolic fates and may therefore exert divergent effects on tumour growth. Here, we investigated how medium-chain and long-chain saturated fatty acids, their dietary availability, and their transfer from adipocytes shape B-cell lymphoma metabolism and progression. We found that B-cell lymphoma cells were dependent on fatty-acid uptake, activation, and utilization for proliferation. Additionally, we identified adipocytes as microenvironmental players that transfer fatty acids and suppress cell growth. Interestingly, in most B-cell lymphomas, exogenous palmitate limits lymphoma cell proliferation, while MCFA caprylic acid showed only mild effects. Using a syngeneic B-cell lymphoma orthotopic model, we found that an MCFA-rich diet increased lymphoma burden and accelerated lymph-node progression, whereas LCFA-rich and obesogenic diets restricted lymphoma dissemination. Dietary fatty-acid composition also altered T-cell exhaustion and profoundly remodelled the circulating lipidome, with LCFA-rich and obesogenic diets producing highly concordant lipidomic signatures distinct from MCFA feeding. Across B-cell lymphoma cell lines, low ACSL1 expression was associated with increased palmitate sensitivity, which we computationally modelled as a targetable vulnerability in B-cell lymphoma treatment. Taken together, our results show that lipid metabolism is a metabolic vulnerability that can be targeted through dietary intervention.

VEXAS syndrome is an adult-onset severe autoinflammatory disease caused by somatic mutations in UBA1, yet the cascade mechanisms linking primitive hematopoietic abnormalities to mature myeloid dysfunctions remain largely unknown. Identifying master regulators of a progressive disease, a black-box process, from complex transcriptomic data also remains challenging. To address this challenge, we developed CauNagi, a computational framework for prioritizing cascade candidate regulators (CCRs). CauNagi integrates a causal representation learning module derived from CausCell with an iterative deep learning backbone adapted from UNAGI; in addition, CauNagi extends these two components with a unique downstream module for CCRs analysis designed to characterize regulatory propagation across hierarchical cellular states. Mechanistically, CauNagi iteratively integrates causal disentangled representation learning with (1) disease-stage cell-state trajectory reconstruction and (2) dynamic regulatory analysis. Benchmarking on single-cell transcriptomic datasets showed that CauNagi preserved cell-type structure in idiopathic pulmonary fibrosis (IPF) and enriched known acute myeloid leukemia(AML)-associated genes among its top-ranked global regulators. When applied to VEXAS syndrome, CauNagi readily revealed inflammatory responses, endoplasmic reticulum stress, and myeloid bias, consistent with the disease features. Furthermore, the CCRs analysis module of CauNagi assisted us in identifying 36 causal drivers, with SPI1, NFKB1, STAT3, and FOS prioritized as high-confidence regulatory hubs linking aberrant myeloid differentiation and inflammatory programs. These findings were further supported by an independent single-cell transcriptomic dataset from a murine VEXAS model. Overall, CauNagi provides a computationally efficient and systematic framework for identifying candidate causal regulators. Beyond hematopoietic diseases, CauNagi may also be applicable to other progressive disorders for which multistage single-cell transcriptomic datasets are available. CauNagi is available at https://github.com/steamed-stuffed-bun/CauNagi.