HemaSphere

Hyperleukocytosis (white blood cell [WBC] count >100 000/uL) at diagnosis is an important prognostic risk factor in pediatric acute lymphoblastic leukemia (ALL), though its significance with contemporary therapy is unclear. We analyzed 1 826 pediatric ALL patients from a multi-institution cohort to determine whether hyperleukocytosis independently predicts outcomes using multivariable Cox proportional hazard modeling. Hyperleukocytosis occurred in 211 patients (12%), with 121 having B-ALL, and showed no prognostic significance in T-ALL patients. In B-ALL, 5-year event-free survival (EFS) was 65% versus 89% for non-hyperleukocytosis patients, and overall survival (OS) was 78% versus 93%. After adjustment for age, cytogenetic risk, central nervous system disease status, and treatment site, hyperleukocytosis remained an independent predictor of end-of-induction minimal residual disease (MRD) positivity (odds ratio 2.53 [95% confidence interval [CI]: 1.71-3.94; p<0.001]), inferior EFS (hazard ratio [HR] 2.44; 95% CI: 1.77-3.38; p<0.001) and inferior OS (HR 2.00; 95% CI: 1.29-3.12; p=0.002). A continuous dose-response relationship was observed between WBC count and these outcomes. Survival associations persisted across all cytogenetic risk categories and MRD strata. Despite risk-adapted therapy with treatment intensification for high-risk features, hyperleukocytosis identifies an aggressive B-ALL phenotype with persistently inferior outcomes, suggesting these patients may benefit from novel therapeutic approaches.

LZTR1 negatively regulates RAS family proteins via proteasomal degradation. Germline loss-of-function variants cause Noonan syndrome, with emerging evidence implicating LZTR1 in predisposition to childhood acute lymphoblastic leukemia (ALL), though its role in hematopoiesis remains poorly defined. Screening 1,587 children with ALL identified LZTR1 variants in 44 patients (2.8%). Germline variants were detected in 32 patients (2.0%), a frequency comparable to that observed in the general population (1.75%; 1,925/110,017; p=0.50). Somatic LZTR1 alterations were identified in 22 patients (1.4%) and were predominantly bi-allelic, arising through either a germline-plus-somatic or dual somatic configuration. They persisted at relapse. Despite enrichment in favorable-risk subtypes (ETV6::RUNX1, high-hyperdiploid, ERG/DUX4), bi-allelic LZTR1-mutated cases showed delayed minimal residual disease clearance and higher late relapse risk, identifying a subgroup unsuitable for treatment de-escalation. LZTR1 expression was increased in most wild-type leukemias, consistent with a compensatory response to aberrant RAS pathway activation. Bi-allelic LZTR1 inactivation abolished RAS regulation, leading to deregulated canonical RAS expression and ectopic expression of the non-canonical RIT1 protein, whose involvement in ALL has not previously been reported. These findings establish LZTR1 as a classical tumor suppressor in ALL via a two-hit model. Monoallelic alterations show insufficient signaling perturbation and low germline penetrance, whereas bi-allelic inactivation acts as a driver event linked to a high risk of late relapse despite favorable genomics.

Background CD19-directed CAR-T cell therapy can induce durable remissions in chronic lymphocytic leukemia (CLL), but response rates are lower than in other B-cell malignancies, in part because CLL is characterized by T-cell dysfunction, defective immune synapse formation, and impaired target-cell co-stimulation. Lenalidomide is an immunomodulatory drug with the potential to act on both sides of the CAR-T/CLL interface by improving T-cell fitness and modifying malignant B-cell susceptibility to immune engagement. Methods We are conducting an open-label, non-randomized phase I/II clinical trial VTB-CLL002 (ClinicalTrials.gov identifier: NCT06762431) evaluating the safety and efficacy of CD19 CAR-T cell therapy combined with concomitant lenalidomide in patients with relapsed or refractory CLL and small lymphocytic lymphoma followed by lenalidomide maintenance. The primary endpoint was safety. The secondary endpoint included overall response rate (ORR), complete response (CR), progression-free survival (PFS) and overall survival (OS). Results Twelve patients were treated. The median age was 60 years and the median number of prior lines of therapy was 2. All patients were BTK inhibitor-naive, and all had measurable disease at the time of infusion. CAR-T manufacturing was successful in all patients. All treated patients achieved complete remission, with a median time to response of 1 month. CAR T-cells expansion was observed in all patients, with a median peak expansion of 137 cells/L and a median time to peak expansion of 14 days. CAR T-cells remained detectable at the last follow-up in all patients, with persistence documented up to 24 months. At dose levels 2-3, eight of nine patients had ongoing MRD-negative responses at the time of analysis. Toxicity was clinically meaningful. Cytokine release syndrome (CRS) occurred in all patients, with severe CRS observed in 2 of 12 patients. ICANS occurred in 5 of 12 patients, including severe ICANS in 4 of 12 patients. One patient developed late grade 4 ICANS temporally associated with lenalidomide reintroduction and secondary CAR-T expansion. Early and late immune effector cell-associated hematotoxicity were common. In mechanistic studies, lenalidomide enhanced CAR-T proliferation and cytotoxicity, shifted CAR-T cells toward effector-associated phenotypes, reduced selected exhaustion markers during repeated antigen challenge, and increased IL-2 and IFN-{gamma} secretion. Lenalidomide also increased CAR-T/CLL conjugate formation and upregulated CD54/ICAM-1 on CLL target cells without broad induction of CD80, CD86, or CD40, consistent with improved adhesive target-cell engagement rather than classical co-stimulation. Transcriptomic profiling supported enhanced Th1/cytotoxic and T-cell activation-associated programs with lower T reg -associated genes in lenalidomide-treated CAR-T cells. Conclusions Lenalidomide-augmented CD19 CAR-T therapy demonstrated strong early clinical activity in relapsed/refractory CLL, characterized by deep responses, durable CAR-T persistence, and substantial incidence of immune effector-associated toxicities. These findings support further evaluation of lenalidomide as a rational CAR-T partner in CLL and suggest that its activity may involve both improved CAR-T fitness and enhanced target-cell engagement. Future studies should optimize lenalidomide timing and dosing to preserve response depth while reducing delayed immune-effector toxicity.

While therapy resistance in acute myeloid leukemia (AML) is often attributed to leukemic stem cells (LSCs), their functional properties are not fully captured by their well-established genetic landscape and cell lineage transcriptional programs. Here, we explore AML cell states and their associations to drug response and systemic immune context. We performed integrated single-cell transcriptomics and immunophenotyping on diagnostic AML samples (n=6) to define transcriptional cell state gene signatures. These were projected onto bulk RNA-seq data from 448 AML patients to assess associations with drug sensitivity, plasma proteomics, clinical features, and established prognostic scores. Longitudinal single-cell data from external cohorts and cell-cell communication analyses were used to examine treatment dynamics and microenvironmental signaling. We defined nine AML cell states, including progenitor-like, stromal-like, antigen-presenting, and monocytic programs. Stemness features were distributed across multiple states, with lymphoid-primed and stress-adapted progenitors showing the strongest alignment with established stemness scores. Distinct drug sensitivities emerged, including cell cycle checkpoint inhibitor sensitivity in stress-adapted progenitors and kinase inhibitor sensitivity in cycling progenitors, alongside shared resistance to BH3 mimetics in monocytic states. Stress-adapted progenitors were associated with adverse clinical features and expanded following venetoclax-based therapy. Monocytic states acted as immunosuppressive hubs via TIGIT signaling, while stromal-associated states received niche-derived survival signals. Overall, we define a framework that associates AML cell states with stemness, drug response, and microenvironmental interactions. These findings highlight distributed stemness, state-specific vulnerabilities, and niche-driven resistance mechanisms, informing more precise therapeutic strategies in AML.

The circulating blood proteome provides a systemic readout of disease biology and holds promise for advancing diagnostics and disease monitoring in pediatric leukemia. Here, we profiled 3072 proteins in diagnostic serum from 54 children with acute lymphoblastic leukemia (ALL), 21 with acute myeloid leukemia (AML), and 12 healthy controls using the Olink Proximity Extension Assay. We observed profound alterations in circulating protein levels in leukemia patients compared with controls and identified immunophenotype-specific proteins, including SIGLEC15 in B-cell precursor ALL (BCP-ALL), NOTCH1 in T-ALL, and CEBPA in AML, all which remained high even in patients with low (<20%) or no peripheral blood blasts. Within BCP-ALL, molecular subtypes were reflected in the circulating proteome; for example, DSC2 and PTPRK were elevated in ETV6::RUNX1-positive cases, while IL-6R and ADAM8 were higher in High Hyperdiploid cases. Angiogenic growth factors decreased across all leukemia patients compared with controls, suggesting a fragile peripheral vasculature at diagnosis. Integration with external datasets revealed the likely cellular source of abundant proteins and examination of an external cohort validated our subtype-specific findings. Together, these results define shared and distinct proteomic signatures across pediatric acute leukemias and highlight candidate biomarkers for diagnostics and disease monitoring.

Myelodysplastic syndromes (MDS) are driven by somatic mutations in hematopoietic stem and progenitor cells (HSPCs), leading to clonal expansion and ineffective hematopoiesis. Hypomethylating agents (HMAs; azacitidine or decitabine) are the standard of care for higher-risk MDS. However, their effects on the bone marrow (BM) microenvironment, and the extent to which these changes correlate with clinical response, remain poorly understood. We performed longitudinal analyses of BM aspirates, trephine biopsies, and peripheral blood samples from MDS patients treated with azacitidine in a clinical trial (NCT03493646), integrating CyTOF, 5' single-cell RNA and TCR sequencing, plasma proteomics, and multiplex immunofluorescence microscopy to characterize changes associated with azacitidine response. Clinical responders showed expansion of GzmBCD56CD8 T cells together with increased type I and type II interferon signaling within the T-cell compartment. Responders also exhibited marked alterations in circulating platelet- and myeloid-derived factors with the potential to remodel the BM niche. Spatial analyses revealed expansion of neighborhoods enriched for CXCL12-abundant reticular cells and CD8 T cells in responders, whereas HSPC-enriched neighborhoods were largely unchanged. In contrast, several HSPC-enriched neighborhoods expanded in non-responders. These microenvironmental changes were accompanied by evidence of enhanced myelopoiesis in clinical responders. Our findings support a model in which azacitidine response extends beyond direct effects on malignant hematopoietic cells to involve coordinated remodeling of the BM microenvironment which may be reinforced by platelet- and myeloid-derived signals that establish a feed-forward circuit promoting productive hematopoiesis.

Transcription factor CEBPA is mutated in 10-15% of acute myeloid leukaemia (AML), a haematopoietic malignancy with high mortality. CEBPA mutations show a distinct pattern, and most patients are biallelic, carrying both an in frame C-terminal mutation and a frameshift N-terminal mutation on opposing alleles. Rare N-terminal germline cases have 100% penetrance to AML, all with an acquired a C-terminal mutation. This suggests a selective pressure from one CEBPA mutation to develop another. Our zebrafish models faithfully recapitulate the human disease. All biallelic mutant combinations die by 4-6 weeks of age, with pre-leukaemic haematopoietic stem cell (HSC) expansion. C-terminal and N-terminal mutants show phenotypic differences in myeloid primed HSC and differences in the myeloid differentiation block. RNA-Seq identified differentially expressed genes in opposing vectors. We identified phosphatase receptor PTPRJ as a candidate driver of clonal selection, with knock-out of ptprja in our fish accelerating pre leukaemic expansion of HSC in C-terminal mutants, decelerating it in N-terminal mutants. Cebpa mutant murine cells exhibit changes in differentiation and a clonal advantage with loss of Ptprj, which perturbs key signalling pathways. Our data suggest that PTPRJ contributes to the mechanism of leukaemogenesis in CEBPA mutant AML by driving the selective pressure from each mutation to develop the other.

Molecular testing in hematology requires different assays for disease subgroup identification, risk stratification and selection of appropriate treatment regimens. Yet, molecular tests are not necessarily standardized between diagnostic laboratories, resulting in varying turnaround times and potentially divergent results. To resolve this issue and enable single-assay molecular testing, we have developed a hierarchical classification framework that combines epigenetic and genetic data from whole genome nanopore sequencing (WGNS) with machine learning to determine disease entities, epigenetic subgroups (epitypes) and genetic aberrations in hematopoietic neoplasms. We curated DNA methylation data from 5,420 samples and trained a classifier allowing entity-level diagnostics featuring 21 conditions, including healthy controls, acute and chronic myeloid and lymphoid neoplasms. This classifier was subsequently combined with entity-specific epitype classifiers predicting 44 therapeutically or prognostically relevant states, followed by integration of genetic data. Benchmarking of the combined (epi-)genetic testing strategy using WGNS confirmed high accuracy in the detection of diagnostic groups and risk stratification, and identified diagnosis-defining molecular alterations that were not reported by standard-of-care work-up.

Myelofibrosis (MF) originates from the stepwise acquisition of somatic mutations in Hematopoietic Stem and Progenitor Cells (HSPCs). Alongside driver events triggering JAK-STAT pathway hyperactivation, several additional mutations, usually affecting the epigenetic machinery, contribute defining therapeutic response. Specifically, JAK-inhibition (JAKi) relieves MF symptoms but rarely eradicates the neoplastic clone. To elucidate clonal dynamics associated with JAKi, we conducted a longitudinal single-cell proteogenomic study on 6 responders and 6 non-responders MF patients. Mutational analysis revealed that the mutation acquisition order determines JAKi sensitivity. Indeed, driver-only clones are highly sensitive to JAKi, while co-mutated clones persist after treatment. JAKi response is mainly limited to the differentiated myeloid compartment, while mutant HSPCs are often maintained in JAKi-responders. Co-mutated clones may evade JAKi and outcompete other neoplastic cell populations, thus contributing to disease persistence.

Erythroferrone (ERFE) is an erythroblast-secreted hormone that suppresses hepatic hepcidin expression to increase iron availability for erythropoiesis, ensuring recovery from anaemia. ERFE excess drives iron overload in disorders of ineffective erythropoiesis. Despite its pivotal role in systemic iron homeostasis and diseases of erythropoiesis, ERFEs molecular regulation has remained undefined. Here, we applied a genomic approach to characterise the molecular mechanisms governing ERFE expression. Using the HUDEP-2 human erythroid progenitor model, integrative ATAC-seq, CUT&RUN and micro capture-C analysis we identified a stage-specific accessible chromatin region within the ERFE 3 UTR that interacts with the promotor. We also identified enhancer-associated chromatin marks including H3K4me1 and H3K27ac in this region, and demonstrate that this cis-regulatory element is bound by key erythroid transcription factors KLF1, GATA1, TAL1 and STAT5. Functional dissection using CRISPR-Cas9-mediated deletion of the central 3 UTR enhancer element led to marked reduction in ERFE mRNA expression, and we show a corresponding reduction in nascent mRNA, confirming a key role for this region in transcriptional regulation. We define the transcriptional regulatory mechanism by which maturing human erythroblasts activate ERFE, the endocrine signal that coordinates erythropoietic demand with systemic iron mobilisation.

Background: High ambient temperature in early pregnancy has been linked to an increased risk of childhood acute lymphoblastic leukemia (ALL). To better understand biological mechanisms, the current study evaluated potential interaction between temperature and genetic characteristics. Methods: We used data from California birth records (1982-2008) and California Cancer Registry (1988-2011) to identify ALL cases (n=3,353) diagnosed <=14 years of age and non-cancer controls (n=3,530) matched 1:1 on sex, race, ethnicity, and birth year and month. Weekly ambient temperatures throughout pregnancy were assessed on a 1-km grid around the birth address, while genetic data were available from a genome-wide association study using neonatal blood spots. We evaluated the association between ambient temperature and ALL risk by quartiles of established genetic risk score for ALL. Next, we formally tested gene-temperature interactions in the association with ALL, correcting for multiple testing, for genes previously identified with epigenetic changes due to both temperature and ALL. All analyses were adjusted for potential confounders. Results: The elevated risk of ALL per 5 degrees C increase of weekly mean ambient temperature, confined to early pregnancy, was more pronounced among children with the lowest genetic susceptibility to ALL, especially among Latino children (first quartile: odds ratio [OR] = 1.50, 95% confidence interval [CI]: 1.14-1.97); fourth quartile: OR=1.03, 95% CI: 0.83-1.28). There were significant interactions (p<0.002) between ambient temperature and polymorphisms in BNC1 among non-Latino White children, and suggestive interactions (p<0.05) with TBPL2 and NRXN1 in the full population. Conclusions: Our findings suggest that there may be interactions between ambient temperature in early pregnancy and offspring genotype in the risk of childhood ALL. Impact: If replicated, these findings could help elucidate the biological mechanisms linking high ambient temperature in early pregnancy and the risk of childhood ALL.

Recurrent mutations in spliceosomal genes are a hallmark of myeloid malignancies, with SF3B1, SRSF2, U2AF1 and ZRSR2 among the most frequently affected. These alterations are typically heterozygous, mutually exclusive missense mutations targeting highly conserved residues, reflecting a selective pressure to maintain a dysregulated yet essential splicing machinery. This constraint suggests that leukemic cells remain dependent on residual splicing activity, exposing a potential therapeutic vulnerability that extends beyond genetically defined subsets. For example, a previously developed therapeutic, Pladienolide B, is a potent cancer cell growth inhibitor targeting the SF3B1 subunit of the spliceosome. Here we present an RNA decoy- based strategy to disrupt 3' splice site recognition by competitively engaging components of the spliceosomal machinery. We engineered a chemically stabilized RNA decoy that mimics the 3' splice site (3'SS decoy), thereby sequestering proteins involved in 3' splice site recognition from endogenous pre-mRNA targets. Although the decoy is expected to engage multiple components of the 3' splice site recognition complex, U2AF1 was used as the primary molecular readout to assess target engagement and downstream effects. To enable intracellular delivery, decoys were encapsulated in lipid nanoparticles (LNPs), facilitating efficient uptake in leukemic systems. We show that LNP-encapsulated decoys are efficiently delivered into leukemic cells, including established cell lines and patient-derived blasts, and directly engage components of the splicing machinery. Decoy treatment induces widespread alterations in RNA splicing programs and impairs leukemic cell fitness in vitro. Importantly, systemic administration of the 3'SS decoy significantly reduces leukemia burden in an in vivo xenograft model. Notably, these effects are observed independently of spliceosomal mutational status, supporting a broader dependency of leukemic cells on intact splicing factor function. Together, our findings establish decoy-mediated disruption of splicing factor activity as a mechanistically targeted therapeutic strategy and identify LNPs as an effective platform for the delivery of RNA-based modulators of essential RNA-protein interactions in myeloid malignancies.

Background: Multiple myeloma (MM) progression is accompanied by remodeling of the bone marrow immune microenvironment. Local interactions among malignant plasma cells, stromal cells, myeloid cells, and immune cells not only support tumor cell survival, expansion, and immune escape, but are also closely associated with disease progression, therapeutic response, and clinical prognosis. Moreover, T cell exhaustion is a common T cells dysfunction in MM and limited efficacy of T cell-targeting therapies. However, the in situ organization and clinical significance of exhausted T cells in MM patients bone marrow remain insufficiently understood. Methods: In this study, we analyzed bone marrow Xenium 5K spatial transcriptomics data from control (Ctrl), monoclonal gammopathy of undetermined significance (MGUS), smoldering myeloma (SM), and MM samples. After canonical multi-sample integration and celltype annotation, we used Gaussian mixture model (GMM)-based spatial partitioning, and multilayer perceptron (MLP) machine learning for systematic characterization the T cell microenvironment in MM bone marrow. Results: Our results showed that exhaustion-like T cells increased during MM progression and formed spatially discrete T cell-enriched regions in the bone marrow, which we defined as exhaustion-like bone marrow T cell islands (eBM-TIs). These niches were mainly characterized by enhanced T cell-plasma cell communication associated with upregulated Galectin signaling. Pseudobulk analysis further showed enhanced IFN-related signaling in eBM-TIs, accompanied by upregulation of CXCR3 ligands such as CXCL9 and CXCL10, suggesting that the IFN-CXCL9/10 axis may contribute to T cell chemotaxis, maintenance of chronic inflammation, and formation of exhaustion-like states. By transferring spatial niche labels to scRNA-seq cohorts with available clinical staging information using MLP, we further found that the proportion of eBM-TI-like T cells was associated with higher disease risk and unfavorable prognostic outcomes. Conclusions: In summary, this study identifies eBM-TIs as a spatial niche in the MM bone marrow. These niches represent an important immune unit linking chronic inflammation, T cell exhaustion, and clinical risk, and may serve as a potential biomarker of MM disease progression.

Hematologic malignancies are diagnosed through a fragmented, sequential workup of morphology, immunophenotyping, cytogenetics, and molecular testing that can take days to weeks and is unavailable at many centers. DNA methylation profiling has transformed central nervous system tumor diagnosis, yet hematologic classifiers have remained confined to narrow acute leukemia panels. Here we present Lamprey, a deep-learning methylation classifier spanning 86 hematologic malignancy entities, trained on a reference cohort of 8,544 patients and deployed directly from nanopore sequencing. A depth-aware training framework allows confident classification from the first minutes of a run. Against blinded integrated reference diagnoses across retrospective, external, and prospective cohorts, Lamprey exceeded 98% accuracy among classified cases. Lamprey reaches a confident call within minutes, and cost as little as $82 per sample. Lamprey consolidates a sequential diagnostic workup into a single, rapid, same-day molecular readout.

Chromatin regulation critically influences gene expression and cancer progression, yet the functions of chromatin adaptors remain incompletely defined. Using focused CRISPR screening, we identified TRIM28, a multi-domain chromatin adaptor, as a dependency in acute leukemia, where its depletion impaired leukemia cell proliferation in vitro and in vivo, while activating neutrophil differentiation programs. Integrative transcriptomic and chromatin profiling revealed that TRIM28 acts as a co-repressor of neutrophil-associated loci independently of H3K9 methylation, and that TRIM28 loss drives terminal differentiation of leukemia cells into functionally mature neutrophil-like cells with reduced leukemic potential. We developed a selective small-molecule TRIM28 inhibitor that binds the TRIM28 PHD-bromodomain, phenocopies TRIM28 loss across biochemical and cellular assays, exhibits low micromolar anti-leukemia activity, induces neutrophil differentiation, and synergizes with Menin inhibition. Together, these findings, spanning target discovery, mechanism of action, and chemical probe development, establish TRIM28 as a regulator of myeloid cell fate and a promising pro-differentiation therapeutic target in acute leukemia.

Follicular lymphoma (FL) is an incurable, prototypical relapse-remitting cancer, implying the existence of therapy-persistent cells that survive frontline treatment and seed disease recurrence1-3. However, these persister cells remain difficult to study directly in patients because immediate post-treatment sampling is ethically and practically challenging. Using a genetically defined mouse model that allows sampling of persistent cells immediately after frontline R-CHOP therapy, we prospectively isolate and functionally define relapse-founding cancer persister cells (CPC). The CPC is an IgM memory-like B-cell with high germinal center re-entry capacity. This state represents a discrete component of a heterogeneous residual pool indicating that residual disease is polytypic and that relapse potential may depend on which cells persist rather than on residual tumour burden alone. By integrating mouse CPC with human FL datasets, we show that an analogous transcriptional programme is detectable at diagnosis and is enriched in patients with inferior clinical outcome across independent cohorts4,5. These findings support the concept that relapse risk is linked to a conserved, genotype-agnostic CPC programme present before therapy. To explore therapeutic vulnerabilities, we developed a scalable in-vitro platform that models the CPC-like state and used it to identify sensitivity to histone deacetylase inhibition. Romidepsin and panobinostat killed CPC-like cells in-vitro, and decreased therapy-persistent cells after R-CHOP treatment in-vivo and in patient-derived organoids. Together, these data define a tractable CPC state in FL, with a validated clinical readout and an immediately testable therapeutic entry point, opening CPC-directed strategies for durable FL control.

Ex vivo genome editing of human hematopoietic stem and progenitor cells (HSPCs) requires targeted integration strategies that support large therapeutic DNA payloads while preserving stem cell fitness. Although CRISPR/Cas9-mediated homology-directed repair using AAV donors is effective, it is constrained by limited cargo capacity and adverse effects on long-term HSPCs function. Integrase-defective lentiviral vectors (IDLVs) offer an alternative donor platform, yet their precise and controlled genomic integration remains inefficient. Here, we describe TILV (Targeted Integration of Lentiviral Vector), a CRISPR-assisted knock-in strategy that exploits Cas9-mediated linearization of episomal IDLV DNA to expose a single homology arm and engage homology-mediated end-joining repair pathways. TILV enables precise, directional and seamless integration of transgenes in multiple loci, enabling constitutive or physiological expression. Using single-cell clonal analyses and targeted long-read sequencing, we define the molecular features of TILV-mediated integration and demonstrate preferential use of CRISPR-linearized episomal substrates. TILV supports accurate insertion of large therapeutic transgenes, without compromising HSPC viability or multilineage potential. We further show that transient modulation of DNA repair pathway, in combination with extended homology arms, enhances integration efficiency and junctional precision. Importantly, optimized TILV enables targeted integration in phenotypically defined long-term HSPCs, highlighting its potential for scalable and durable gene therapy.

Germinal centers (GCs) support physiological B-cell mutagenesis and are considered lymphoma-permissive; nevertheless, lymphoma development is uncommon. Human in situ follicular neoplasia (ISFN) captures this paradox: premalignant B-cells can persist within GCs for prolonged periods without progressing to overt lymphoma. We found that human ISFN, but not normal GCs, are infiltrated by CD8 T-cells, suggesting that premalignant GC B-cells are locally immune-surveilled. Using mouse models that separate early premalignant fitness from lymphoma-associated evolution, we show that fitness-enhanced premalignant GC B-cells expand transiently but are selectively eliminated by infiltrating cytotoxic CD8 T-cells, while normal GC B-cells are spared. By contrast, evolved premalignant GC B-cells retain their fitness but disable productive CD8 T-cell cytotoxic differentiation, allowing persistence and lymphoma-like transcriptional and genomic evolution. These findings establish GCs as active immune-surveillance sites and show that progression from premalignancy to lymphoma requires both enhanced GC fitness and escape from local immune control. Key findingsGCs undergo active immune-surveillance to detect premalignant B-cells. Premalignant GC B-cells trigger cytotoxic CD8 T-cell responses. Lymphoma-associated evolution enables immune-escape within GCs. Fitness and immune-escape drive evolution from premalignancy to lymphoma. BlurbGerminal centers are considered lymphoma-permissive; however, progression from premalignancy is uncommon. Using models of human in situ follicular neoplasia, Zhang et al. demonstrate that infiltrating CD8 T-cells actively eliminate premalignant GC B-cells. Co-occurrence of lymphoma-like alterations blocks this cytotoxic T-cell response, driving immune escape and lymphoma evolution.

Chemotherapy-induced peripheral neuropathy (CIPN) is a common neurotoxicity of cancer treatment with limited diagnostic, monitoring, and treatment options. Neurofilament light chain (NfL) is an axonal cytoskeletal protein released during neuroaxonal injury and a promising biomarker of CIPN, but prospective evidence for NfL as a marker of CIPN from vincristine-containing lymphoma chemotherapy treatment remains limited. To fill this gap, we conducted a pragmatic single-center prospective observational cohort study of adults with non-Hodgkin lymphoma (NHL) receiving first-line vincristine-containing chemotherapy to evaluate NfL dynamics across multiple pre-cycle visits and assess 68 relationships with patient-reported and clinician-graded neuropathy measures. We followed 25 participants during 4-6 months of chemotherapy, and a small subset of those participants (n=6) for 24-42 months post-chemotherapy. Serial plasma NfL was measured and CIPN symptoms were assessed using patient- and clinician-reported measures. Longitudinal changes were analyzed using mixed-effects models. Plasma NfL increased relative to pre-cycle1 at all timepoints (all p<0.001), increasing more than threefold by pre-cycle4. Patient-reported CIPN scores and clinician-graded neuropathy also increased during treatment. Exploratory pooled visit-level analyses showed a modest NfL-CIPN association (Spearman {rho}=0.393, p=0.004), while timepoint-specific, lagged, and post hoc sensitivity analyses suggested potential to predict persistent CIPN symptoms from early NfL concentrations. To our knowledge, these findings provide the first prospective evidence that NfL is sensitive to vincristine exposure in adults with NHL and may complement patient-reported symptom assessment, clinician grading, and dose-modification context in future CIPN monitoring studies.

BackgroundDrug-tolerant persister (DTP) cell states have been implicated in relapse across multiple cancers, including acute myeloid leukaemia (AML) [1,2]. Methods that score such states from transcriptomic data, generalise to held-out samples, expose calibrated probability outputs, and link predictions to candidate biology are useful for prioritising follow-up experimental work. Existing transcriptomic methods for scoring drug-tolerant or persister-like states largely rely on fixed gene signatures or general-purpose cell-type classifiers adapted post hoc (scPred, scANVI, scClassify); deep-learning approaches developed specifically for AML drug-tolerant persister scoring with calibrated probability outputs, prespecified thresholds, and transparent external validation against ex-vivo drug-response data are, to our knowledge, lacking. Our approach addresses this gap by combining a Transformer teacher with a knowledge-distilled 1,000-gene student, prespecified threshold {tau} = 0.31, and direct evaluation against BeatAML drug-AUC. Our in silico approach aims to fill this gap of non-existent analytical methods to identify and mark the DTP cells. MethodsWe trained a Transformer classifier on a pooled scRNA-seq corpus of nine samples (six from GSE123902-lung adenocarcinoma metastasis, normal, and primary tumour [4]-plus three primary AML samples; 32,342 cells, 13,369 common genes), with stratified 5-fold cross-validation at the cell level, a 20% held-out test split, and a prespecified probability threshold selected on out-of-fold predictions. A 1,000-gene student model was trained by knowledge distillation [5]. For every input cell, the student outputs a probability between 0 and 1 (hereafter "the score") representing predicted membership in the positive training class. The trained model was applied without re-tuning to five external or independent application cohorts: 39 primary AML donors[in-house]; GSE74246[6]; BeatAML (n = 452 with linked ex-vivo drug-AUC; n = 405 with overall-survival metadata)[7]; TCGA-LAML (n = 149)[8]; and an in-house n = 10 scRNA-seq cohort with linked survival. Survival and drug-response data were not used during training, threshold selection, or tuning. The score was anchored mechanistically against CRISPR/DepMap essentiality[9], pathway enrichment, and a normal-tissue-filtered surface-protein candidate list (HPA[11], GTEx[12]). To assess concordance between transcriptomic prioritisation and protein-level evidence, each ranked candidate was additionally annotated with two HPA-derived flags: HPA_surface_protein (Yes/No, derived from HPA Protein class and Subcellular location fields, identifying genes annotated as plasma-membrane, GPCR, ion-channel, transporter, receptor, or CD-marker) and HPA_antibody_reliability (Enhanced, Supported, Approved, Uncertain, or Not available, per HPA antibody validation tier). Annotations were merged on HGNC symbol; 248 of 250 candidates (99.2%) matched. Two candidates using the older CORF nomenclature did not auto-match HPAs lowercase convention and were resolved manually. HPAs per-gene RNA-protein numeric correlation is published only on per-gene web pages and not in the bulk download; we therefore used the detection-level and antibody-reliability tiers as the operational concordance filter. ResultsCross-validation area under the receiver operating characteristic curve (AUROC) was 0.936 +/- 0.014 (held-out test 0.941, Matthews correlation coefficient (MCC) 0.696, F1-score 0.895). The 1,000-gene student showed Spearman {rho} {approx} 0.96 with the teacher and >85% class agreement at the prespecified threshold. The principal external result was in BeatAML: the score correlated with ex-vivo drug-response AUC across seven AML-relevant drugs, with consistent per-drug Spearman correlations (r = 0.41-0.53, all p < 0.05). The aggregate correlation across 3,164 patient-drug pairs from 452 patients was r = +0.482 and is reported as a summary, recognising that pairs from the same patient are not fully independent. The score did not stratify overall survival in TCGA-LAML or in the in-house n = 10 cohort, in part because predicted high-score fractions saturated. At the prespecified threshold the score did not separate cell types in GSE74246, indicating that absolute calibration is cohort-dependent. Compared against logistic regression, random forest, the LSC17 stemness signature, and a mean-expression baseline on the same gene panel, the Transformer was the most stable model under aliquot-grouped cross-validation and the only one to transfer with strong, positive correlation to BeatAML drug-AUC. The mechanistic candidate-target pipeline produced a 250-candidate ranked surface-protein list (full breakdown in Results); FLT3 and CD33 were recovered from the unbiased ranking as positive controls. ConclusionWe present a Transformer-derived transcriptomic score that addresses the lack of validated computational methods for identifying drug-tolerant persister-like states in AML. The score shows external rank-order association with ex-vivo drug response, providing a research-use tool for prioritising candidate persister-associated transcriptional programs for follow-up. Together, these results support the score as a research-use transcriptomic ranking tool for AML drug-response-associated states. The strongest external support comes from the consistent association with BeatAML ex-vivo drug-response AUC. The fixed probability threshold did not transfer reliably across all cohorts, so threshold-based classification should require cohort-specific recalibration. The score is not validated for clinical decision-making and is not proposed as a survival predictor. The candidate-target list is a starting point for functional follow-up.