Leukemia

Richter transformation of Chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) into classic Hodgkin lymphoma (CHL-RT) is rare and remains incompletely understood. Two histologic subtypes are recognized: type 1 (CLL/SLL with scattered Hodgkin/Reed-Sternberg (HRS) cells) and type 2 (HRS cells within a polymorphous inflammatory background). In this multi institutional study of 77 patients with CHL-RT (27 type 1 and 50 type 2), we characterized immune evasion markers, PD-L1/PD-L2 copy number alterations, tumor microenvironment, and performed targeted next-generation sequencing on 37 CLL/SLL samples. HRS cells in CHL-RT displayed immune evasion phenotypes similar to de novo CHL, though PD-L1 expression was lower in type 1 cases. PD-L1/PD-L2 gain/polysomy were frequent (83.3%). CLL/SLL with CHL-RT harbored increased mutations in XPO1, FBXW7, BIRC3, TRAF3, and HLA-A versus reference CLL/SLL. Similar mutational profiles, demographics, and survival outcomes support a biological continuum between type 1 and type 2 CHL-RT, with distinct genetic features in CLL/SLL predisposing to CHL transformation.

Chronic lymphocytic leukemia (CLL) is a lymphoid neoplasm with very heterogeneous clinical and biological behavior. Among molecular variables, TP53 alterations are well-established adverse prognostic markers; however, MYC activation, which has been linked to disease progression, has not been completely defined in terms of clinical and biological impact, particularly in relation to TP53 status. Here, we investigated the effects of MYC overexpression according to TP53 status using clinical and transcriptomic data from CLL patients and novel cellular models. CLL patients with TP53WT and MYC overexpression exhibited significantly shorter time to first treatment and overall survival, indicating an aggressive disease course comparable to that of patients with TP53 alterations. Consistently, MYC overexpression in in vitro TP53WTmodels was associated with increased proliferation, enrichment of AKT/mTOR signaling and upregulation of genes involved in leukemogenesis and tumor progression such as FOXO6. Moreover, MYC overexpression was associated with increased sensitivity to venetoclax in TP53WT cells. By contrast, the concurrence of MYC overexpression and TP53 dysfunction conferred resistance to conventional CLL therapies such as BCL2 or BTK inhibitors. Of note, we identified a glycolysis inhibitor, in monotherapy or combined with BKT inhibitors, as a potential therapeutic strategy for CLL patients harboring MYC overexpression and TP53 alterations.

Curative-intent immunochemotherapy fails in ~30% of patients with large B-cell lymphoma (LBCL), yet no validated molecular tool enables early identification of high-risk individuals to guide treatment intensification. Using shallow whole genome sequencing (sWGS) of plasma cell-free DNA from 190 LBCL patients, we developed and validated the ACT score (Aberrations, fragment Composition, Terminal motifs), a composite classifier integrating genomic and fragmentomic features from a single post-cycle-1 sample. ACT-positive patients had worse 2-year outcomes versus ACT-negative patients: time-to-progression 29% vs. 83% (HR 4.4, 95% CI 1.9 - 10.0; P = 1.5 x 10 - 4) and overall survival 47% vs. 93% (HR 8.7, 95% CI 3.0 - 25.4; P = 1.8 x 10-6). ACT score was independently prognostic of the International Prognostic Index, and their combination identified the highest-risk patients. Unlike mutation-based approaches, this assay requires neither tumor tissue, germline control nor a baseline plasma sample. Built on open-source tools and sWGS, the ACT score offers a feasible scalable strategy for early risk stratification in aggressive LBCL.

Germline variants in DDX41 are the most frequent genetic predisposition to adult hematologic malignancies. The most common variants are truncating, implicating loss of function in the pathogenesis. However, non-truncating variants account for 30-40% of cases, and their impact on essential DDX41 functions remains unknown. We utilized a genetic complementation assay to assess the functionality of 10 recurrent germline non-truncating variants of DDX41. All variants restored viability to Ddx41-deficient hematopoietic progenitor cells at exogenous expression levels. In contrast, the hotspot mutant p.R525H, which is somatically acquired at disease onset in >50% of patients, failed to restore viability. CRISPR-based modeling in cell lines and mice revealed heterogeneity: some variants were non-functional at endogenous expression levels whereas others maintained complete functionality, supporting normal cell proliferation and even lifelong hematopoiesis in a homozygous setting. Notably, co-expression of p.R525H with some variants caused impaired hematopoietic progenitor cell viability, indicating a dominant-negative effect of p.R525H. In contrast, other variants, all classified as variants of unknown significance, were unaffected by the presence of p.R525H. A screen of 100 disease-associated variants confirmed that many non-truncating germline variants are susceptible to p.R525H-mediated dominant-negative effects, whereas wild-type DDX41 is not. These findings indicate that DDX41 variant curation is complicated by variable effects on functionality and variant-specific interactions with somatically-acquired DDX41 mutations. The dominant-negative effect of p.R525H provides a mechanistic basis for the conclusion of recent patient cohort analyses that co-occurrence with a somatic hotspot mutation is a reliable indicator of DDX41-driven disease in carriers of non-truncating variants.

Background: Modern therapy for childhood and adolescent leukemia requires accurate risk classification of genomic subtype. Although short-read next-generation sequencing (NGS)- based approaches provide comprehensive clinical diagnostics in limited, highly resourced settings, they remain expensive, slow, and inaccessible to most children worldwide. Transformative approaches are needed to improve diagnostic classification for leukemia globally. Methods: We simultaneously continued to develop an analytical pipeline NASVar (Nanopore variant calling for adaptive sampling), and conducted a multicenter, type-two hybrid clinical validation study of an Oxford Nanopore Technologies (ONT) adaptive-sampling whole-genome sequencing (asWGS) assay across hospitals with varying diagnostic resources. In preparation for implementation, a global panel developed a leukemia-based standardized gene set and consensus laboratory-developed test (LDT) validation guidelines. Measures of assay effectiveness compared to both conventional and orthogonal NGS methods, where available, were simultaneously collected with data to measure the implementation outcomes of feasibility, fidelity, appropriateness, and cost. Results: All four centers successfully completed the LDT validation, with minimal adaptations required for regulatory compliance. A total of 457 specimens were sequenced (331 B-ALL, 83 AML, 43 T-ALL). For the 210 B-ALL cases with locally resolved genomic subtypes defined by DNA alterations, asWGS was 100% concordant (210/210). Cases locally defined as B-other were resolved via asWGS with disease-defining DNA alterations in 47% (49/105) of cases. An additional 41% (43/105) of locally defined B-other cases were classified by incorporation of DNA methylation, and all 16 B-ALL patient-derived xenograft controls were correct, for a total of 96% (318/331) of all B-ALL cases in the cohort resolved with single assay asWGS. For AML, 97% (56/58) of cases with locally resolved genomic subtypes were identified by automated asWGS analysis, while an additional two cases were identified after targeted manual review. At Indus Hospital in Pakistan, the B-ALL and AML diagnostic genomic subtype yield increased from 28% with local standard of care diagnostic testing, to 84% with asWGS. The cost of reagents and consumables in the United States, assuming pooled three-plexing, was $343/sample. Based on the combined hybrid validation results, all centers are independently preparing for clinical return of results. Conclusions: ONT asWGS was successfully validated as a clinical assay in four diverse hospital settings. As a single, multi-omic platform that delivers value across the continuum of high-resource to resource-limited contexts, the approach offers a disruptive solution to address the global equity gap in cancer diagnostics.

Relapse during treatment of B-cell acute lymphoblastic leukemia (B-ALL) is a harbinger of poor outcomes. Identifying biomarkers for subsequent relapse risk which are detectable at B-ALL diagnosis remains a priority. Off-target recombination-activating gene (RAG)-mediated structural variants (SVs) generate genomic instability that drives leukemogenesis and may underlie treatment resistance. Leveraging sequencing data in 1,496 pediatric B-ALL patients enriched for relapse status (relapse n=532; non-relapse n=964), we characterized RAG-mediated SVs across B-ALL molecular subtypes and examined their association with patient characteristics and their impact on clinical outcomes. Off-target RAG-mediated SVs were overall frequent, particularly in ETV6::RUNX1, ETV6::RUNX1-like, and Ph-like B-ALL subtypes, while increasing age-at-diagnosis was positively associated with burden of off-target RAG-mediated SVs (P<.001). Off-target RAG-mediated SVs with a recombination signal sequence (RSS) at one breakpoint, a hallmark of off-target RAG activity, were significantly more frequent at diagnosis in patients who subsequently relapsed (P=.001). This association remained significant in multivariable regression analysis (per SV odds ratio [OR]:1.08, 95%CI:1.04-1.12), in minimal residual disease (MRD)-negative patients (OR:1.09, 95%CI:1.04-1.14) and across subtypes. Excluding deletions, MRD-negative ETV6::RUNX1 patients with 3 off-target RAG-mediated SVs had a >3-fold risk of relapse (hazard ratio:3.47, 95%CI:1.86- 6.49). RAG-mediated SVs were also associated with relapse risk in T-cell ALL patients. Off-target RAG-mediated SV burden at diagnosis is a risk factor of relapse in pediatric ALL across molecular subtypes and independent of MRD status.

The JAK2V617F (JAK2VF) driver mutation is found in 95% of patients with polycythemia vera (PV), a progressive myeloproliferative neoplasm. Current treatments suppress excessive hematopoiesis but lack specificity for targeting JAK2VF cells, are unable to deplete mutant stem/progenitor cells and ultimately result in drug resistance. We discovered that the FDA-approved antibiotic, linezolid (LZD), ameliorates the PV phenotype across multiple model systems. LZD suppressed cell proliferation and STAT5 signaling, altered the cell cycle, and increased apoptosis of JAK2VF-harboring human erythroleukemia cells, but not in wild-type acute leukemia cells. Computational modelling indicated that LZD interacts specifically with mutant JAK2VF but not with wild-type JAK2 protein. We further showed that, in JAK2VF mice that faithfully recapitulate human PV, LZD mitigates disease burden by selectively targeting JAK2VF stem cells thereby normalizing spleen size and blood counts. LZD also inhibited hematopoietic colony formation by patient-derived peripheral blood mononuclear cells, with the more primitive progenitors being preferred targets. Importantly, LZD selectively decreased JAK2VF+ colony numbers, without impacting wild-type JAK2 colonies. In all, the data provide a firm foundation for evaluating LZD-like molecules as an effective therapy for PV and other myeloproliferative neoplasms. Key pointsO_LILinezolid acts as a JAK2V617FIZselective inhibitor in PV mouse models and PV patient samples while sparing wildIZtype hematopoiesis. C_LIO_LILinezolid acts directly on JAK2V617F hematopoietic stem cells. C_LI

Therapy-driven genomic changes in multiple myeloma (MM) remain poorly defined. We analyzed whole-genome sequencing (WGS) data from relapsed/refractory MM (rrMM, N=386) and identified regional 1p31.1-p12 (hereafter 1pCEN, a region proximal to the centromere) loss-of-heterozygosity (LOH) as the only enriched aberration showing strong therapy-associated clonal selection (clonal timing rank fold-change = 3.7, P<2.2x10-16). This event showed enriched co-occurrence with 1qGain (OR = 2.3 (1.5-3.8), P=2x10-4) forming a recurrent "double-hit" in rrMM. To validate the clonal selection process, we examined three longitudinal cohorts (180 patients, 390 samples) and confirmed clonal expansion of 1pCEN and consistent prevalence of the 1pCEN+1q double-hit (20-24%). Survival analyses demonstrated significantly reduced progression-free survival in rrMM patients with this double-hit compared with those without. Comparison with a large newly diagnosed MM (ndMM) cohort confirmed previously-described 1p32 LOH is the prognostic locus at baseline, whereas 1pCEN is therapy-selected and largely independent of the 1p32 locus. Thus, 1pCEN+1q represents a recurrent double-hit event that clonally emerges in rrMM, conferring selective advantage under drug exposure and is distinct from the ndMM high-risk markers defined by current consensus guidelines. These findings nominate 1pCEN as a new genomic biomarker in rrMM and 1pCEN+1q may help patient stratification for therapeutic monitoring. Key PointsA therapy-driven common genomic double-hit (1p31.1-p12 LOH with 1q gain) clonally emerges in relapsed/refractory myeloma.

BackgroundAcute myeloid leukemia (AML) remains the most lethal acute leukemia in adults, with 5-year overall survival below 32% despite recent advances including venetoclax-, FLT3-, IDH1/2-, and Menin-targeted therapies. Clinical outcomes remain highly heterogeneous across patients, highlighting the need for robust molecular biomarkers capable of improving prognostic precision. MicroRNAs (miRNAs) are critical regulators of hematopoietic differentiation, apoptosis, and therapeutic resistance and are differentially expressed across AML subtypes. However, their clinical translation has been limited by high dimensionality, feature redundancy, and relatively small cohort sizes. MethodsWe developed and evaluated the AML Survival Estimator (AMLS), an inheritable bi-objective combinatorial genetic algorithm integrated with support vector regression (SVR), using TCGA-LAML miRNA expression profiles (n = 156). AMLS was benchmarked against ten widely used machine-learning approaches, including penalized regression, tree-based ensembles, support-vector regression, k-nearest neighbors, and multilayer perceptron models. Performance was assessed using stratified cross-validation with Pearson correlation (R), Harrells concordance index (C-index), and mean absolute error (MAE). Functional characterization of the derived miRNA signature was performed through consensus target integration followed by pathway enrichment, gene ontology analysis, network reconstruction, and Kaplan-Meier risk stratification. ResultsAMLS achieved superior prognostic performance with pooled out-of-fold metrics of Pearson R = 0.86, C-index = 0.788, and MAE = 7.49 months, substantially outperforming all comparator models. Restricting analyses to the AMLS-derived 28-miRNA signature improved all baseline learners by approximately 2-4-fold, with the multilayer perceptron achieving R = 0.674; however, none matched the native AMLS framework, indicating that the evolutionary optimization strategy contributes predictive information beyond feature selection alone. The prognostic signature included biologically established AML-associated miRNAs, including hsa-miR-191, hsa-miR-29c, hsa-miR-125b, hsa-miR-148a, hsa-miR-15b, hsa-miR-10b, and hsa-miR-30c, linked to DNA methylation, apoptosis, cell-cycle regulation, and oncogenic Wnt/MAPK signaling pathways. Functional analyses demonstrated significant enrichment of canonical AML-associated pathways, including p53, PI3K-AKT, TGF-{beta}, JAK-STAT, FoxO, and hematopoietic lineage signaling. ConclusionsOur findings demonstrate that evolutionary learning integrated with SVR can recover a compact and biologically interpretable miRNA prognostic signature that substantially outperforms conventional machine-learning approaches for AML survival prediction. The identified miRNA network converged on key leukemogenic pathways involved in apoptosis, cell-cycle regulation, and oncogenic signaling, supporting both the biological relevance and prognostic utility of the framework. Given the minimally invasive and quantitatively scalable nature of miRNA profiling, this approach may provide a practical molecular adjunct for improving prognostic assessment and precision medicine strategies in AML. Abstract FigureSchematic overview of the AMLS framework. Left: acute myeloid leukemia, a clonal hematological malignancy with persistent prognostic heterogeneity. Middle: AMLS couples an evolutionary learning-based feature selection algorithms to support vector regression for miRNA-based survival modeling. Right: AMLS recovers a 28-miRNA prognostic signature that predicts overall survival with Pearson R = 0.86 and MAE = 7.5 months. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=86 SRC="FIGDIR/small/727196v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@11ead1org.highwire.dtl.DTLVardef@4f5c19org.highwire.dtl.DTLVardef@277de1org.highwire.dtl.DTLVardef@b95c9a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background: Diabetes mellitus (DM) worsens pulmonary tuberculosis (TB) and drives systemic hyper-inflammation, but the underlying mechanisms remain unknown. Neutrophils have key roles in TB immunopathology and lung cavitation. Here, we determine the role of neutrophils in DMTB patients and in driving TB immunopathology. Methods: Sputum and plasma from 30 TB and 30 DMTB patients were analysed for proteases and cytokines using Luminex bead array. Whole blood transcriptomics identified transcriptional differences. Single-cell RNA sequencing characterised neutrophil subsets and dysregulated pathways. Neutrophil function of poorly-controlled DM patients (HbA1c>8%) and healthy controls (HC) were examined following Mycobacterium tuberculosis stimulation, including reactive oxygen species (ROS), neutrophil extracellular traps (NETs), and phagocytosis. Pathways were interrogated using chemical inhibitors, protein array and western blot. Results: Compared to non-diabetic TB patients, poorly-controlled DMTB patients showed up-regulated sputum MMP-8 and MMP-9, associated with increased collagen-destruction and lung cavity formation. Circulating neutrophil count and neutrophil-derived plasma MMP-8 were up-regulated, alongside transcriptional enrichment of extracellular matrix degradation and inflammatory pathways including TNF and RAGE. Single-cell profiling identified reduced cycling neutrophil subset and myelocytes in DMTB, with overall reduced antibacterial and cell-killing signatures. Ex vivo mycobacterial stimulation of DM neutrophils increased ROS and MMP-9 with impaired NETs and delayed phagocytosis. TNFR1, TNFR2, and RAGE were up-regulated. RAGE inhibition with rosiglitazone mitigated Mtb-induced ROS and MMP-8 release. Conclusion: DM worsens neutrophil-driven tissue destruction and inflammation in TB via dysregulated TNF and RAGE-signalling, priming neutrophils towards immunopathology. Targeting RAGE alongside tight glycaemic control may dampen neutrophil hyper-inflammatory responses to limit tissue destruction.

Antigen density critically influences CAR T-cell efficacy. We show that ibrutinib induces CD19 upregulation in B-cell lymphoma models, enhancing CAR T-cell cytotoxicity. Pharmacologic modulation of target antigen expression represents a promising strategy to overcome resistance.

Measurable (or minimal) residual disease (MRD) predicts relapse in patients with acute myeloid leukemia (AML). However, the biological and spatial characteristics of the AML bone marrow (BM) microenvironment (BMME) in which MRD cells survive remain largely unexplored; in particular, little is known of the BMME in TP53 mutant (TP53mut) AML. Here, we applied sequential immunofluorescence to whole BM biopsy specimens obtained from patients with TP53 wild-type (TP53WT) AML and TP53mut AML at diagnosis and in morphological complete remission (CR) to generate a comprehensive spatial map of the hematopoietic and BMME components. We identified TP53mut leukemia cells based on high p53 expression and delineated their spatial organization relative to stromal and immune niches. Biopsy-based cell composition analysis revealed marked B-cell depletion and an increased abundance of regulatory T-cells (Tregs) in TP53mut BM at CR. Unlike TP53WT BM, TP53mut BM at CR exhibited persistent TP53mut erythroid and immature leukemia cell clusters, spatially segregated from T-cell clusters, in perisinusoidal niches, suggesting niche-level immune evasion. Spatial profiling further revealed that Tregs characterized by FOXP3 upregulation were enriched near TP53mut MRD cells, indicating a locally enhanced immunosuppressive activity. Single-cell RNA sequencing-based cell-cell communication analysis identified erythroid-T-cell interactions mediated by the GDF15-CD48 axis as a potential mechanism of T-cell suppression, suggesting that the erythroid differentiation of TP53mut AML cells enhances local immunosuppression. Collectively, our results show a spatially organized immunosuppressive BMME in TP53mut AML and highlight the potential of spatial proteomics to identify actionable MRD niches in leukemias. Key pointsO_LITP53 mutant erythroid and immature leukemia cells form spatial clusters segregated from T-cells in complete remission. C_LIO_LIAn erythroblast-centered immunosuppressive niche characterizes TP53 mutant leukemia cells. C_LI

IntroductionClonal hematopoiesis of indeterminate potential (CHIP) is a recognized risk factor for hematologic malignancies, but its contribution to different types of solid cancers remains incompletely defined. MethodsHere, we performed a systematic, gene-specific analysis of CHIP across 19 common solid cancer types using two large population-based cohorts, the UK Biobank and All of Us with Cox proportional hazards models and nested case-control logistic models. ResultsWe demonstrate that the relationship between CHIP and solid tumors is highly cancer-type specific, with lung cancer exhibiting the strongest association. In lung cancer, this association is largely driven by ASXL1-mutant clones. Specifically, high variant allele fraction (high-VAF) ASXL1 conferring a significantly increased risk (hazard ratio = 3.2), and the associations remained robust after adjustment for age, sex, body mass index (BMI), smoking status, and genetic ancestry. Notably, ASXL1 CHIP was substantially enriched among smokers, and its association with lung cancer risk was restricted to ever-smokers, highlighting a key interaction between CHIP and environmental exposure. The enrichment of ASXL1 CHIP in lung cancer was further validated in two independent cancer-only cohorts, including MSK-IMPACT and TCGA. In addition, rare germline variant association analysis revealed that germline variation in ASXL1 had the strongest association with lung cancer susceptibility among all solid tumors. ConclusionsCollectively, our findings support a model in which smoking-associated expansion of ASXL1-mutant clones contributes to lung cancer development and suggest that gene-specific CHIP metrics may enhance risk stratification and early detection strategies.

Tyrosine kinase inhibitors (TKIs) are the first-line therapy for chronic myeloid leukemia (CML), yet fail to eliminate quiescent CML cells residing in the bone marrow (BM). While transcriptome adaptation and metabolic rewiring have been recognized as mechanisms enabling CML survival, the contribution of RNA processing, known to expand the repertoire of isoforms and directly mediate therapy resistance in leukemia, is poorly characterized. We previously found that a subset of alternative splicing (AS) changes detected in CML cells surviving months of therapy are initiated within hours of treatment onset. Here, we developed a humanized BM stromal niche in vivo to investigate the influence of the human BM microenvironment on gene expression and AS in CML cells. Stroma-facilitated transcriptome adaptation targeted transcription regulation, transmembrane transport, lipid metabolism, respiration and energy production. We identified RNA-binding protein TIAR (T-cell intracellular antigen-related protein) as a key mediator of CML survival and determined that TIAR-dependent post-transcriptional regulation coordinates RNA processing-metabolism program induced by stromal interaction. Quantitative nascent proteome analysis confirmed that TIAR is a translational regulator of metabolic enzymes and proteins involved in imatinib-induced erythroid differentiation. In hypoxic co-culture with BM stromal cells, TIAR knockdown reduced the viable erythroid-differentiated cell population in association with increased lipid peroxidation and decreased redox potential. Taken together, these findings identify TIAR-dependent RNA processing within the BM niche as a previously unrecognized mechanism of CML therapy resistance and potential therapeutic vulnerability.

Background: Severe cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) are major dose-limiting toxicities of chimeric antigen receptor (CAR) T-cell therapy. Existing pre-infusion biomarkers offer modest discrimination, motivating non-invasive alternatives. Methods: We prospectively enrolled 26 patients with relapsed/refractory large B-cell lymphoma receiving axicabtagene ciloleucel. Pre-infusion (day -1) exhaled breath samples were analyzed by gas chromatography-mass spectrometry for 40 volatile organic compounds (VOCs). Candidates with univariate AUC > 0.65 for severe (grade >=2) CRS or ICANS were carried forward to sensitivity-maximization-at-given-specificity with LASSO regularization (SMAGS-LASSO), which selected separate panels for each outcome. Model performance was assessed by leave-one-out cross-validation with permutation p-values and Harrell bootstrap optimism correction. Results: The 4-VOC CRS panel (heptanal, benzaldehyde, 2-butanone, ethylbenzene) achieved LOOCV AUC 82.5% (80% sensitivity at 88% specificity) and the 3-VOC ICANS panel (nonanal, allyl methyl sulfide, levomenthol) achieved AUC 86.3% (67% sensitivity at 86% specificity). By tertile, severe CRS occurred in 8/9 (89%) high-risk versus 2/9 (22%) low-risk patients (Cox HR 6.82, 95% CI 1.41-32.9, p=0.017) and severe ICANS occurred in 8/9 (89%) versus 2/9 (22%) (HR 8.28, 95% CI 1.73-39.6, p=0.008). Each 1-SD score increase corresponded to a 3.80-fold higher hazard of severe CRS (p<0.001) and 4.36-fold higher hazard of severe ICANS (p<0.001). In head-to-head comparison, the 3-VOC ICANS panel outperformed the modified Endothelial Activation and Stress Index (mEASIX) (delta-AUC +0.36, DeLong 1-sided p=0.008). The 4-VOC CRS panel had numerically higher AUC than mEASIX (delta-AUC +0.19, p=0.150). Conclusions: Pre-infusion exhaled breath VOC panels stratify CAR T-cell recipients by severity and timing of severe CRS and ICANS, providing a non-invasive complement to existing serum biomarkers. Multi-institutional validation is warranted.

Clonal haematopoiesis (CH) becomes ubiquitous as humans age. The role of somatic driver mutations in its development has been studied widely, but little is known about CH without identified genetic drivers, also known as "CH with unknown drivers" (CH-UD). A fundamental unresolved question is whether CH-UD is driven by undiscovered somatic genetic drivers or by other cell-heritable traits. Here, to investigate this, we develop a new machine learning classifier to improve CH-UD detection from whole-genome sequencing data. After excluding 77,885 individuals with previously documented driver CH or mosaic chromosomal alterations (mCA), we applied our classifier to 407,512 UK Biobank participants and identified 26,963 (6.6%) with CH-UD. A genome-wide association study (GWAS) of common germline variants identified 31 polymorphic loci associated with predisposition to CH-UD. Of these, 25 were associated with other forms of CH at genome-wide significance. Linkage Disequilibrium Score Regression analyses revealed an unexpectedly high genetic correlation (rg=0.794) between CH-UD and non-DNMT3A driver CH, indicative of a remarkable overlap between the genetic aetiologies of the two phenomena. Analysis of 2,941 plasma protein measurements in 47,757 individuals revealed that TCL1A was the most significantly elevated plasma protein in CH-UD, mirroring the finding that the TCL1A locus was in the top two most significant associations of CH-UD GWAS and TET2-CH and ASXL1-CH GWAS, the two most common forms of non-DNMT3A-CH. Furthermore, TCL1A plasma levels rose steadily with age even in those without detectable CH, particularly among carriers of the common TCL1A risk variant (rs2887399-G), potentially via stochastic promoter demethylation as described in TET2-CH and ASXL1-CH. Phenome-wide association analysis of 13,225 binary and 1,682 quantitative traits revealed that, similarly to non-DNMT3A-CH, CH-UD was significantly associated with several malignant (haematological and solid organ) and non-malignant (including cardiovascular and renal) diseases. Our findings reveal striking genetic and phenotypic similarities between CH-UD and non-DNMT3A driver CH, including a strong dependence on TCL1A, a protein recently found to inhibit DNA methylation. Collectively, these observations propose that CH-UD develops through selection acting on ageing-associated epigenetic changes that mirror those of non-DNMT3A-CH, but without the need for somatic genetic drivers.

Multiple myeloma remains a fatal, incurable disease. Most therapies are targeted to the cancer cell or T cell engagement. Little is known about the supporting myeloma microenvironment and its contribution to tumor fitness. Here, we expand upon the observation of human mast cells in the NSG-hIL6 myeloma patient derived xenograft mouse model to show mast cells decrease time to engraftment, promote increased myeloma engraftment and cause myeloma bone disease. We identify 10 mast cell secreted factors that together improve the survival of patient myeloma cells in vitro. Our results highlight the versatility of the NSG-hIL6 model to study microenvironmental interactions between human bone marrow cells and myeloma and confirm prior suggestions that clinical signs of disease, such as osteolytic lesions, may at least partially be related to non-malignant bone marrow microenvironmental cells, such as mast cells.

Today, advancements in our understanding of cancer biology are increasingly attributed to large-scale clinical-molecular datasets. The case in point for multiple myeloma, the second-most prevalent haematological malignancy, is the CoMMpass study, a dataset with the paired clinical and sequencing data of 1,143 patients. Given its complexity, the multi-omics data of CoMMpass demands programming skills which imposes a hurdle for experimental myeloma researchers who want to validate their hypotheses on population data. The rise of agentic AI over the past few years presents unparalleled opportunities to bridge this technical gap. We propose MyeGPT (Myeloma Generative Pretrained Transformer), an AI bioinformatician for multiple myeloma that relies on the CoMMpass dataset as its ground truth. MyeGPT converts natural language queries such as 'What are the characteristics of patients who relapse after induction therapy' or 'Compare the overall survival of high vs normal NSD2 expression' into de novo analyses backed on real data, then pro-actively generates plots to visualize the results. We develop a set of evaluation questions based on CoMMpass, complete with scoring criteria, and ran benchmarks to identify the best choice for LLMs and text-embedding models. We package MyeGPT as a ready-to-use browser application, enabling CoMMpass-grounded hypothesis validation from a smartphone.

Viral pneumonia is perpetuated by inflammatory circuits between activated T cells and monocyte-derived alveolar macrophages (MoAM). T cells and macrophages express ORAI1 and STIM1, which form calcium release-activated calcium (CRAC) channels that allow extracellular calcium entry in response to endoplasmic reticulum calcium store depletion. In a randomized, placebo-controlled, multicenter phase 2 trial (CARDEA), Auxora, a CRAC channel inhibitor, reduced all-cause 30-day mortality by 56% in patients with severe SARS-CoV-2 pneumonia. Here, we report a multi-omics analysis of serially collected alveolar samples from unvaccinated patients with severe SARS-CoV-2 pneumonia treated with Auxora versus placebo. We found reductions in plasma levels of the monocyte- and T cell-chemokines, CCL8 and PDGF-AA. Using peripheral blood mononuclear cells (PBMC) from healthy volunteers, we show that Auxora directly targets T cells to inhibit the transcription of CCL8 and PDGFA in monocyte-derived macrophages, supporting a mechanism for its effects and a potential intermediate biomarker of efficacy.

Macrophage activation syndrome (MAS) is driven by a hyperinflammatory response characterized by aberrant activation of lymphocytes and phagocytes. While monocytes and macrophages are thought to be important in MAS pathogenesis, their role remains poorly understood. We used bulk and single-cell RNA sequencing (RNA-Seq) on sorted monocytes from children with MAS and healthy controls to identify transcriptional changes during MAS. We defined a MAS signature in classical monocytes that correlated with ferritin and was elevated in monocytes from systemic lupus erythematosus and COVID-19 patients. We also identified a subset of classical monocytes with high levels of interferon-stimulated genes (ISGs) that expanded during MAS. Surprisingly, the transcriptional signature of these cells was driven by type I IFNs, rather than IFN{gamma}. Consistent with this finding, we detected increased levels of circulating IFN{beta} during MAS, suggesting that IFN{beta} plays an unrecognized role in driving MAS monocyte responses. We also identified a MAS-associated CD8+ T cell population with a distinctive transcriptional signature. We used cell-cell communication algorithms to predict increased immunoregulatory interactions between monocytes and T cells during MAS. Together, these results provide new evidence for a role for type I IFN during MAS and identify a unique CD8+ T cell population that may contribute to MAS pathophysiology.