Blood Cancer Journal

Chimeric antigen receptor T-cell (CAR-T) therapy targeting CD19 has transformed outcomes for children with relapsed or refractory (R/R) B-cell acute lymphoblastic leukemia (B-ALL), yet the influence of molecular subtype on outcomes remains unclear. We evaluated the impact of cytogenetic and molecular signatures on complete response (CR), overall survival (OS), and leukemia-free survival (LFS) after CD19 CAR-T therapy in eighty-six pediatric patients with R/R B-ALL treated with tisagenlecleucel. CR was assessed 30 days after infusion. Cytogenetic data were available for 84 patients and molecular profiling for 62. Survival analyses included 72 patients who received CD19 CAR-T as the sole cellular therapy. Seventy-seven patients achieved CR (89.5%). Pre-infusion bone marrow blasts of [&ge;]20% were associated with lower CR rates (53.8% vs 95.9%, p<0.0001) and significantly reduced OS and LFS (both p<0.0001). Among molecular markers, RAS mutations correlated with inferior OS (p=0.0222) and LFS (0.0402). In multivariate analysis, bone marrow blasts >20% and RAS mutations independently predicted inferior OS. Post CAR-T, CD19 negative relapses showed almost twice higher prevalence of RAS mutations (66% vs 37.5%). These findings highlight RAS mutations as a key molecular predictor of outcome after CD19 CAR-T therapy and suggest emergence of unique risk stratification for patients receiving CD19-targeting therapy.

Chimeric antigen receptor (CAR) T-cell therapy has transformed treatment for relapsed /refractory(r/r) lymphoid malignancies. Yet, these cellular immunotherapies are often associated with immune-related adverse events (irAEs), namely cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), that pose significant risks to patient safety and limit broader clinical implementation of CAR T-cell therapies. In the current study, we used proteomics technology to establish circulating protein signatures that would predict severe CRS and ICANS in r/r lymphoma patients that subsequently received CAR T-cell therapy. Initial discovery was performed using plasma samples collected preceding CAR T-cell infusion from 39 r/r lymphoma patients at MD Anderson Cancer Center. A 5-marker and 8-marker protein panel was developed for predicting Grade [&ge;] 2 CRS and ICANS respectively, yielding respective AUCs of 0.85 [95% CI: 0.72-0.98] and 0.91 [95% CI: 0.81-1.00]. Independent testing of the CRS and ICANS panel was performed in a cohort of 59 r/r lymphoma patients from the Moffitt Cancer Center, with resultant AUCs of 0.76 [95% CI: 0.63-0.89] and 0.67 [95% CI: 0.51-0.84] for the CRS and ICANS panel, respectively. Patients were further classified into low-, intermediate-, and high-risk groups based on panel score tertiles. In the combined dataset (MDACC + Moffitt), compared to patients in the low-risk group (reference), patients in the intermediate- and high-risk groups were 3.15 [95% CI: 0.92-12.71] and 13.84 [95% CI: 4.21-56.26] more likely to have Grade [&ge;] 2 CRS, and 1.21 [95% CI: 0.36-4.23] and 8.59 [95% CI: 2.87-29.09] more likely to have Grade [&ge;]2 ICANS. The protein biomarker panels provide a means to risk stratify patients who are at high risk for developing severe CRS and ICANS, to inform on the need for prophylactic interventions and improve patient outcomes.

Waldenstrom macroglobulinemia (WM) is a rare indolent neoplasm characterized by presence of more than 10% lymphoid cells in BM that exhibit plasmacytoid or plasma cell differentiation that secretes an IgM monoclonal protein. This is a retrospective analysis of 89 patients of WM that describes the clinical and laboratory characteristics, treatment patterns and outcome of patients of WM. The median age of the entire cophort was 66 years with male predominance (67.4%). Most common presentations were symptoms pertaining to anemia (77.5%) and constitutional symptoms (33.7%). Median bone marrow lymphoplasmacytic cells were 41%. Positivity for MYD88 and CXCR4 mutations were seen in 81.8% and 2.4% cases. BR was the most common regimen used (52.8%). Overall response rates were seen at 87.8%. Median overall survival, progression free survival and time to next treatment is 8.49 years, 2.15 years and 3.88 years. BR regimen was associated with highest event free survival.

Myeloproliferative neoplasms (MPNs) are characterized by progressive myelofibrosis that drives morbidity and mortality. Liquid biopsy approaches to noninvasively monitor fibrotic progression remain limited. We performed comparative transcriptomic profiling of CD45-depleted platelet-enriched and CD45+ leukocyte-enriched fractions from matched peripheral blood samples of 76 individuals (27 primary myelofibrosis, 17 polycythemia vera, 14 essential thrombocythemia, 18 healthy controls). Platelet RNA sequencing was performed in 2018-2020 on Illumina HiSeq 4000, while WBC RNA sequencing was conducted in 2023 on Illumina NovaSeq 6000 from cryopreserved CD45+ enriched fractions of specimens obtained at the identical time and from the same blood sample as the platelet RNA. Despite comparable library preparation protocols and higher sequencing depth in WBC samples, platelet transcriptomes exhibited 5.1-fold more differential expression in myelofibrosis (3,453 versus 681 genes, adjusted p<0.05, |log2FC|>1). Platelet signatures were enriched for proteostasis pathways including endoplasmic reticulum stress and unfolded protein response, reflecting megakaryocyte dysfunction in the fibrotic bone marrow niche. WBC signatures predominantly featured immune activation and proliferative pathways, indicating systemic inflammatory responses. Multinomial LASSO classification demonstrated superior performance of platelet-based models for myelofibrosis diagnosis (AUROC 0.85) compared to WBC-based (AUROC 0.77) or clinical models (AUROC 0.59). Combined platelet+WBC models did not improve performance (AUROC 0.80), indicating complementary but non-additive information. These findings establish platelet transcriptomic profiling as a superior noninvasive biomarker platform for monitoring myelofibrosis in MPNs, capturing megakaryocyte-driven fibrogenesis with greater sensitivity than peripheral leukocyte-based approaches. HighlightsUsing matched WBC and platelet RNA-seq from MPN patients, we identify myelofibrosis-associated transcriptomic signatures specifically enriched in platelets. Multinomial LASSO modeling highlights platelet-derived gene expression as a dominant and predictive biomarker of myelofibrosis, outperforming clinical parameters and WBC signatures. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/714941v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1d695aborg.highwire.dtl.DTLVardef@fc250forg.highwire.dtl.DTLVardef@1e52e8eorg.highwire.dtl.DTLVardef@15378e3_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background: Large language models (LLMs) perform well on standardized medical exam questions, but their reliability for complex hematology decision making is uncertain. We compared four general-purpose LLMs (GPT-4o, GPT-o3, Claude Sonnet 4, and DeepSeek-V3) with a Virtual MDS Panel (VMP), a coordinated multi-agent AI system in which domain-specialized, rule-bound software agents (WHO/ICC guidelines; IPSS-R/IPSS-M; NCCN) collaborate to generate tumor-board-level recommendations. Methods: Each model generated diagnostic, prognostic, and treatment recommendations for 30 myelodysplastic syndrome cases. Nine international MDS experts from five institutions, blinded to model identity, completed 3,000 structured ratings using 5-point Likert scales for diagnosis, prognosis, and therapy and classified errors by severity. Results: General-purpose LLMs achieved modest expert ratings (overall mean scores: 3.7 for GPT-o3, 3.2 for GPT-4o, 3.1 for DeepSeek, and 3.0 for Claude) and contained major factual errors in at least 24% of responses. The VMP increased the proportion of outputs rated 4 or higher to 87% (vs. 34-66% for general-purpose models), improved mean scores to 4.3 overall (4.3 for diagnosis, 4.4 for prognosis, and 4.1 for therapy), and reduced major errors to 8%. Conclusions: In this blinded evaluation of 30 complex MDS cases, general-purpose LLMs produced clinically important errors at rates that raise safety concerns for autonomous hematology decision making. The VMP, a rule-bound, multi-agent architecture, approached expert-level accuracy supporting its potential role as an effective decision-support tool for MDS in the future.

TP53 mutations represent one of the strongest adverse prognostic factors in myelodysplastic neoplasms (MDS). While multi-hit TP53 (TP53multiHit) alterations uniformly lead to very poor outcomes, the prognostic relevance of monoallelic TP53 (TP53mono) mutations remains controversial. TP53 variants can cause loss-of-function, dominant-negative, or gain-of-function effects. We hypothesized that functional heterogeneity among TP53 variants contributes to the variable clinical behavior observed in monoallelic TP53-mutated MDS. Therefore, we analyzed pretreatment samples from 4,505 patients with MDS from two independent cohorts (IWG, n=3,173; J-MDS, n=1,332), including 271 patients with TP53mono and 499 with TP53multiHit. Functional annotation of TP53 variants was performed using a previously published phenotype score (PS) derived from saturation mutagenesis screens, capturing dominant-negative and loss-of-function effects. Median overall survival (OS) differed significantly by TP53 allelic state (TP53 wild-type (TP53wt) 42.4 months; TP53mono 22.9 months; TP53multiHit 9.2 months; p < 0.001). Within the TP53mono subgroup, functional annotation identified marked heterogeneity. Patients with high PS ([&ge;]7) showed significantly inferior OS compared with those with low PS (median OS: 13.8 vs. 39.2 months; HR 1.68, 95% CI 1.16-2.42; p = 0.006), particularly for IPSS-R and IPSS-M low-risk cases. Combining PS and variant allele frequency (VAF) further improved risk stratification. TP53mono patients with PS [&ge;]7 and VAF [&ge;]22% had outcomes comparable to TP53multiHit (median OS: 8.8, p = 0.2), whereas those with PS <7 and VAF <22% exhibited survival similar to TP53wt (median OS: 49.7, p = 0.9). Overall, functional annotation of TP53 variants refines prognostication in TP53mono-mutated MDS and may enhance individualized risk assessment.

Diffuse large B-cell lymphoma (DLBCL), the most common aggressive lymphoma, encompasses histologically similar but genetically distinct cancers. Recent genetic studies have defined at least six molecular subtypes, yet none account for Epstein-Barr virus (EBV), despite 5-15% of DLBCLs being EBV-associated. By reanalyzing published whole-exome and RNA-sequencing data from 481 tumors, we identified 19 EBV-positive cases. These were significantly enriched in the BN2 subtype (6/19), while most (11/19) remained unclassified. In BN2 tumors, several subtype-defining mutations were reduced in frequency among EBV-positive cases, supporting the hypothesis that EBV oncogenes substitute for specific cellular alterations and may confound DLBCL classification algorithms. Extending our analysis to cell lines, we found that the widely used Val cell line harbors the B95-8 laboratory EBV strain; other EBV-positive lines appeared authentic but modeled only non-BN2 subtypes and expressed an atypical viral latency III program, whereas some DLBCL tumors expressed the atypical latency III program and others latency I or II. Together, these findings demonstrate that EBV-positive DLBCL, like DLBCL itself, is not a single disease, and that current in vitro models only partially capture its biological heterogeneity. Key pointsO_LIEBV-positive DLBCL is not a single disease and EBV status can impact genetic-based classifications. C_LIO_LICurrent EBV-positive DLBCL cell lines do not adequately capture tumor complexity; we determined that Val is a problematic cell line. C_LI

Although several ancillary tests are available in limited laboratories, diagnosis of microphthalmia (MiT)/TFE family translocation renal cell carcinoma (tRCC) could be challenging due to diverse and overlapping tumor morphology and the lack of reliable biomarkers. GPNMB has been recently identified as a diagnostic marker for various renal neoplasms with FLCN/TSC/mTOR-TFE alterations. However, the sensitivity and specificity of GPNMB immunostain are suboptimal and the result interpretation in ambiguous cases could be difficult. To search additional biomarkers that could improve the screening sensitivity and predict genetic aberrations in FLCN/TSC/mTOR-TFE pathway in renal tumors, we performed bioinformatic analysis of publicly available cancer databases and found GPR143, a transmembrane protein regulated by MiT transcription factors, was highly expressed in a subset of renal cell carcinomas (RCCs). In two the Cancer Genome Atlas (TCGA) kidney cancer cohorts, RCCs with high levels of GPR143 expression were enriched for renal neoplasms with FLCN/TSC/mTOR-TFE alterations. Similar to GPNMB labeling, GPR143 immunostain was positive in the majority of tRCC cases and renal tumors with FLCN/TSC/mTOR alterations, suggesting that GPR143 could function as another surrogate marker for FLCN/TSC/mTOR-TFE alterations in certain renal tumors. Interestingly, despite the concordant GPR143 and GPNMB immunoreactivity in most renal neoplasms with FLCN/TSC/mTOR-TFE alterations, diffuse GPR143 immunostain was observed in some cases with negative or focal GPNMB labeling. Taken together, our results indicate GPR143 could serve as a useful adjunct marker to improve the sensitivity for screening renal tumors with FLCN/TSC/mTOR-TFE alterations.

Current clinical management of multiple myeloma (MM) relies on bone marrow (BM) biopsies for minimal residual disease (MRD) assessment. While BM biopsies are the gold standard, their invasive nature and potential to miss extramedullary or patchy disease necessitate sensitive, non-invasive liquid biopsy platforms. In this study, we evaluated the analytical performance of the CellSearch CMMC assay to determine its utility for deep-MRD monitoring. Using a standard 4 mL whole blood input, the assay achieves a WBC-normalized sensitivity of 2.45 x 10-7, supported by a limit of quantitation of 5 cells per run. Given this high analytical sensitivity, the assay provides a robust negative predictive value, rendering false-negative findings highly unlikely in populations with detectable peripheral disease. These findings characterize the CellSearch CMMC assay as a highly sensitive, analytically validated platform for non-invasive deep-MRD level longitudinal surveillance monitoring. When integrated into a clinical workflow that accounts for its specificity profile, the platform offers a patient-friendly complement to serial BM biopsies, with the potential to reduce their frequency in appropriate clinical contexts.

Inflammation is a key driver of hematopoietic dysfunction in myeloid malignancies, but its role in the context of hypomethylating therapy remains incompletely understood. Although 5-Azacytidine is used posttransplant in high-risk myelodysplastic syndrome (MDS), only 50% of patients show a clinical response. We provide evidence that inherent inflammatory properties of healthy donor CD34+ stem cells exist that are likely to contribute to the "response" seen in MDS patients. These are linked to epigenetic priming of the myeloid niche, resulting in S100A8/A9-driven inflammatory program that promotes functionality of immature NK cells. Using in vitro differentiation systems, multi-omic profiling, and a S100A9-/- mouse model, we find that 5-AzaC modulates inflammatory transcriptional programs through epigenetic rewiring of upstream regulatory elements. Loss of S100A9 disrupts myeloid differentiation, impairs NK cell maturation, and alters key developmental regulators including CEBPB, JUN, and NFIL3. In vivo, 5-AzaC restores these defects and primes NK cells in a time- and context-dependent manner. Re-analysis of the published Australian MDS/CMML cohort shows that "responders" display increased S100A8/A9 expression together with enhanced IFN-{gamma}, IL6-JAK-STAT3, and TNF signaling. These findings suggest that inflammatory myeloid programs may serve as predictive biomarkers and therapeutic targets to enhance NK cell-mediated graft-versus-leukemia activity posttransplant. SummaryO_LIWe provide compelling evidence that inherent properties of healthy donor CD34+ hematopoietic stem cells (SCs) exist that are likely to contribute to the "response" seen upon pre-emptive posttransplant 5-AzaC therapy of patients with high-risk myelodysplastic syndrome (MDS). C_LIO_LIThese properties are linked to a distinct form of epigenetic plasticity at upstream-located transcription factor (TF) binding sites. This may indirectly contribute to acute S100A8/A9-driven inflammation, which is demonstrable in distinct monocyte subsets and, importantly, also in NK cells thereby determining the characteristics of inflammatory monocyte-NK cell crosstalk. C_LIO_LIMice with a targeted deletion of S100A9 fail to upregulate CEBPB / JUN and NFIL3 which results in impaired myeloid priming and dysfunctional NK cell maturation, respectively. C_LIO_LIRe-analysis of the Australian MDS/CMML cohort confirms that MDS patients that "respond" to 5-AzaC exhibit activated IFN-{gamma}, IL6-JAK-STAT3, and TNF-signaling pathways in the context of upregulated S100A8/A9 after six months of treatment. C_LIO_LIOur study indicates that screening of healthy donors SCs for specific inflammatory markers in early developing monocytes could be used as a marker to predict which donor will have the potential of generating a S100A8/A9-driven inflammatory response. This may help identify patients with MDS as well as AML who are likely to benefit from low-dose, short-term 5-AzaC therapy as early as day 7 after transplantation, potentially resulting in increased graft-versus-leukemia (GvL) activity. C_LI

The RUNX1 transcription factor is a critical regulator of hematopoiesis and frequently mutated in myeloid malignancies. In the myeloproliferative neoplasm, chronic myeloid leukemia (CML), secondary somatic RUNX1 mutations and RUNX1::MECOM/EVI1, are associated with tyrosine kinase inhibitor (TKI) resistance and progression to the blast-phase (BP-CML). Research has predominantly focussed on transcriptional dysregulation mediated by RUNX1 mutations in myeloid malignancies, whilst post-transcriptional dysregulation remains comparatively unexplored. To address this, we used orthogonal organic phase separation (OOPS), to characterise the RNA-binding proteome of RUNX1 deficient BP-CML cells. RUNX1 depleted BP-CML cells exhibited significant alterations to RBP abundance involved in stress response pathways and translation/ribosome-biogenesis (RiBi). Furthermore, RUNX1 depletion or expression of RUNX1::EVI1 in BP-CML cells induced expression and RNA binding activity of SPATS2L, a component of stress granules (SG); membraneless cytoplasmic condensates protecting mRNAs from degradation, promoting survival under stress. Whilst RUNX1 depletion increased SG-assembly, SPATS2L depletion reduced SG-assembly in BP-CML cells and inhibited the growth and survival of multiple BP-CML cell lines. The translation inhibitor homoharringtonine (HHT), used historically in TKI-resistant CML, ablated SG-assembly in BP-CML cells with RUNX1 depletion, and, primary BP-CML cells with LOF/hypomorphic RUNX1 mutations (characterised by defective DNA-binding/CBF{beta}-interaction) were preferentially sensitised to HHT. Finally, suppressing SPATS2L expression induced by RUNX1 depletion, increased the HHT-sensitivity of RUNX1 depleted BP-CML cells, suggesting SPATS2L contributes to therapeutic resistance in CML with RUNX1 mutations. This study suggests that SPATS2L and SG induction could be critical to RUNX1-mutant leukemias, and, provides preliminary evidence for a mutationally-targeted approach in CML with RUNX1 aberrations.

Children with acute lymphoblastic leukemia (ALL) are treated with multiagent chemotherapy that causes profound changes to the immune system. There are limited data on how disease and therapy impact antigen-specific immune memory, leading to inconsistent guidelines on best practices for revaccination of this population. Here, to inform vaccine guidance, we investigated whether immunity derived from routine childhood measles and varicella zoster virus (VZV) vaccines is maintained during and after therapy for childhood ALL. We report that antibodies against measles and VZV were significantly reduced in children with ALL (n=45) compared to healthy controls (n=13), particularly in older children in whom a longer time had passed since their most recent vaccine dose. However, the avidity of the measles and VZV-specific antibodies was indistinguishable between groups. Despite changes to the composition of the T cell compartment, both overall and antigen-specific T cell function were preserved in children with ALL. These data provide compelling evidence for revaccination of children following ALL treatment. Intact T cell responses suggest that post-treatment revaccination would be effective.

Prognostic stratification in multiple myeloma (MM) relies on staging systems that assign patients to fixed categories at diagnosis and discard the temporal information that accumulates during treatment. We developed a dynamic multimodal framework that predicts residual overall survival using observation windows ranging from 1 to 18 months post-diagnosis. The model integrates DeepInsight-transformed gene expression representation, longitudinal laboratory measurement trajectories across 10 analytes, and treatment history for three drug classes through an adaptive fusion mechanism that accounts for missing clinical observations. On the MMRF CoMMpass cohort (n = 752), five-fold cross-validation yielded a concordance index (C-index) of 0.773 {+/-} 0.024 and a time-dependent AUC at a 1-year prediction horizon (tdAUC1yr) of 0.789 {+/-} 0.021, outperforming all evaluated baseline methods including DeepSurv (0.633 {+/-} 0.095) and random survival forests (0.636 {+/-} 0.024) on matched cross-validation splits. Modality ablation identified longitudinal laboratory measurements as the strongest individual contributor (C-index 0.693); the DeepInsight spatial encoding of gene expression yielded higher discrimination than a multilayer perceptron (MLP) baseline operating on the same features (0.624 vs. 0.596). Kaplan-Meier analysis showed significant prognostic group separation at all primary landmarks (log-rank p < 0.001; hazard ratios 3.46-3.93). A distilled student model retaining only the DeepInsight representation and five baseline clinical features achieved C-index 0.672 and tdAUC1yr 0.740 on an independent microarray cohort (GSE24080, n = 507) without retraining. Interpretability analysis identified prognostic associations consistent with established myeloma biology, including ubiquitin-proteasome pathway genes, endoplasmic reticulum stress markers, and Interferon Alpha Response pathway enrichment.

BackgroundWilms tumour (WT) relapse occurs more frequently in patients with blastemal-type WTs. The presence of cancer stem cells (CSCs) is linked to tumour survival and relapse, and CSCs may be found in greater numbers in blastemal cell foci. CSC-associated phenotypes have been described in untreated WT, but their persistence, organisation and relevance after neoadjuvant chemotherapy is unknown. MethodsWe analysed 23 formalin-fixed paraffin-embedded blocks from 18 chemotherapy-treated patients where WTs were enriched for viable blastema, using human fetal kidney as developmental control. Immunohistochemistry and -fluorescence analysis determined progenitor (PAX2, SIX2, CITED1) and CSC-associated (NCAM, ALDH1, CD133) marker expression. We qualitatively and semi-quantitatively evaluated spatial expression patterns and co-localisation across tumour compartments. ResultsPAX2 and SIX2 were co-expressed in blastema in most cases (15/18), with PAX2 expression higher at the periphery of blastemal foci and SIX2 expression found uniformly in central aspects. CITED1 expression was also associated with SIX2 in blastema tissues (14/18). NCAM was blastema-enriched (15/18) with higher central intensity, frequently adjacent to PAX2-expressing peripheral zones. ALDH1 expression was present across blastema and epithelium while NCAM-, ALDH1-double-positive cells were rarely observed (4/18). CD133 expression was less commonly seen (2/18), localising near epithelial/nephrogenic structures. ConclusionsAfter neoadjuvant chemotherapy, WT blastema retained overlapping but non-identical progenitor/CSC-associated marker landscapes with reproducible peripheral-centre gradients. These spatial arrangements suggest a blastemal niche for CSCs that may sustain a therapy-resistant state. Our analysis provides the foundation for future functional validation and molecular profiling to define key lineage relationships and therapeutic vulnerabilities in post-chemotherapy WT. [250/250 words]

G protein-coupled receptors rely on dynamic conformational changes to coordinate G protein activation and recruitment of regulatory transducers such as G protein-coupled receptor kinases and {beta}-arrestins. The chemotactic receptor GPR183 has been implicated in a context-dependent role in hematological malignancies. Here, we investigated the impact of A338V mutation located within the C-terminal tail of GPR183. This mutation is associated with acute myeloid leukaemia. Using bioluminescence resonance energy transfer-based assays in HEK293A cells, we assessed receptor-proximal signaling events. The A338V variant displayed preserved agonist potency and comparable agonist-induced Gi activation relative to wild type, although constitutive activity towards Gi was modestly reduced. In contrast, recruitment of GRK2 and {beta}-arrestin2 was consistently impaired across multiple assay configurations. These differences were not attributable to altered receptor abundance, as the C-tail untagged mutant exhibited increased plasma membrane expression despite reduced regulatory transducer engagement. While intramolecular conformational biosensor measurements revealed subtle differences in global receptor conformation between WT and A338V, extensive molecular dynamics simulations supported the altered conformational sampling of the C-terminal tail in the A338V variant. Together, these data support a model in which the A338V substitution selectively alters C-terminal structural dynamics, impairing GRK2 and {beta}-arrestin2 recruitment while preserving G protein activation.

BackgroundIn acute myeloid leukemia studies, event-free survival (EFS) is defined as time until treatment failure, relapse, or death, whichever occurs first. Since 2020 and 2022, respectively, the US Food and Drug Administration and the European LeukemiaNet recommend analysing treatment failures as day-1 events. This data modification can lead to a potentially large drop in the estimated EFS at day 1. If censoring occurs, the Kaplan-Meier estimator obtained from the recoded data underestimates this drop. Our aim is to obtain an unbiased estimate for EFS as basis for further inference. MethodsWe define "event on day 1" as one event type and " event after day 1" as a competing event in the original data and use the Aalen-Johansen estimator of the cumulative incidence curve to estimate event-specific transition probabilities, which are combined in one EFS estimate. To analyse effects on day 1 treatment failure and other post-day-1 EFS events separately, a formal link to cure models is established by equating treatment failures with the "cured" proportion in cure model terminology. Additionally, a variance estimator, confidence intervals, confidence bands, and simultaneous testing procedures are derived. ResultsOur new estimation method differs from the Kaplan-Meier estimator in settings in which some treatment failures are censored, as in the interim analysis of the AMLSG 09-09 study. If almost no treatment failures are censored, the two estimation methods do not differ. The cure model and simultaneous testing are able to estimate effects on day 1 treatment failure and other post-day-1 EFS events separately and function independently of whether data is modified. ConclusionsThe Kaplan-Meier estimator evaluated on the recoded data underestimates the drop at day 1 if treatment failures are censored. With sufficient follow-up, this bias disappears, and results coincide with our novel approach.

In both neonates and adults, the presence of malignancy-associated mutations in peripheral blood (PB) correlates with an elevated risk of future neoplastic transformation, with certain mutations, such as KMT2A rearrangements, exhibiting near-complete penetrance. If feasible, pre-malignant screening could enable early intervention and even disease prevention. However, nucleic acid sequencing- and hybridization-based mutation detection have limited cost-efficiency, constraining their use in screening. Here, we introduce a computer vision platform that can identify mutant cells in fresh PB samples that carry KMT2A-MLLT3 (a frequent mutation in pediatric and adult leukemias and detectable in newborn blood samples) or JAK2-V617F (a frequent mutation in myeloproliferative neoplasms and clonal hematopoiesis). This is achieved by high-throughput single-cell imaging and mutation detection by machine learning (ML)-powered morphology recognition. The ML models were developed by cross-species learning of conserved features between mutant cells from mouse genetic models and from human samples, enabling a cost-effective approach for detecting mutations in live blood cells. This platform holds promise for pre-malignant screening in asymptomatic neonates and adults with KMT2A-MLLT3 or JAK2-V617F mutation and is potentially generalizable to the detection other malignancy-associate mutations. Our platform provides a novel single-cell morphological data modality that complements existing single-cell genomics.

BackgroundArtificial intelligence and machine learning (AI/ML) are among the fastest-growing domains in NIH research funding, but whether children have shared equitably in this expansion is unknown. We characterized pediatric representation in NIH AI/ML funding from fiscal years (FY) 2020 to 2024. MethodsNIH grant data were obtained from Research Portfolio Online Reporting Tools Expenditures and Results bulk files for FY2020 to FY2024. AI/ML grants were identified using the NIH Research, Condition, and Disease Categorization "Machine Learning and Artificial Intelligence" category, and pediatric grants using the "Pediatric" category. Subprojects were excluded. Grants were deduplicated within each fiscal year by core project number for trend analyses and across all years retaining the most recent fiscal year for cross-sectional totals. Disease areas were identified by keyword searches of titles and abstracts. ResultsAcross FY2020 to FY2024, 5,624 unique NIH AI/ML grants totaling $3,371 million were identified. Of these, 836 grants (14.9%) were classified as pediatric, representing $401 million (11.9%) of total NIH AI/ML funding. Although this share was consistent with the historically reported overall NIH pediatric funding baseline of approximately 10% to 12%, it remained substantially below the US pediatric population share of approximately 22%. The pediatric share of NIH AI/ML funding declined from 12.3% in FY2020 to 10.8% in FY2024, despite growth in absolute pediatric funding. Indexed to FY2020, pediatric AI/ML funding grew approximately 2.6-fold compared with 3.0-fold growth in the total portfolio. Across disease areas, unadjusted adult/general-to-pediatric funding ratios ranged from 2.0-fold in mental health to 9.8-fold in cancer. ConclusionsPediatric representation in NIH AI/ML funding remained low and declined over time as the overall portfolio expanded. These findings suggest that growth in NIH AI/ML investment has not been matched by proportional gains for pediatric research.

Most patients with acute myeloid leukemia (AML) initially respond to standard chemotherapy. However, relapse and refractory disease remain common. The responses to targeted therapies are often transient and the efficacy of immunotherapy is limited. Although single-cell RNA sequencing (scRNA-seq) studies have provided insights into the cellular diversity and immune landscape of AML, many have primarily focused on limited, or newly diagnosed patient cohorts, leaving cellular dynamics across advanced disease incompletely defined. Here, we profiled 72 samples from AML patients across different disease stages using scRNA-seq and compared these against healthy donor samples. We observed selective enrichment of immature progenitor populations, along with widespread upregulation of oxidative phosphorylation in AML. The immune microenvironment of AML was characterized by CD8+ effector memory T cell expansion with reduced IL2-STAT5 and increased mTORC1 pathways and exhaustion markers, suggesting a functional imbalance. Several AML-specific genes were identified providing potential therapeutic opportunities. Cell communication analysis revealed reduced HLA interactions in relapsed/refractory samples compared to diagnosis samples, suggesting impaired antigen presentation and defective T cell priming. Together, these results improve the understanding of cellular and immune changes in AML during disease progression and provide a basis for new therapeutic strategies.

BackgroundTumor vasculature is a key driver of glioma progression, yet routine quantification depends on subjective histopathologic assessment or resource-intensive ancillary immunohistochemistry. A scalable, objective method for vascular phenotyping from routine histology remains an unmet need. MethodsWe leveraged 10x Genomics Xenium spatial transcriptomics data from a glioblastoma specimen to generate molecularly resolved annotations of GBM-associated endothelial cells and pericytes across 809,041 cells. These annotations were transferred to matched H&E-stained sections to train a DINO-DETR-based object detection model using a binary classification scheme (vascular vs. other). The model was validated on four independent Xenium patient slides and applied to a retrospective cohort of 119 diffuse gliomas spanning WHO grades 2-4 (oligodendroglioma, astrocytoma, and glioblastoma) with linked survival data. ResultsBinary vascular cell detection achieved a precision of 0.78, a recall of 0.63, and an F1 score of 0.70, with an overall accuracy of 98.6%. Orthogonal spatial validation confirmed that predicted vascular cells were preferentially localized within annotated blood vessel regions. In subtype-stratified survival analysis, high AI-derived vascular cell proportion was significantly associated with worse overall survival in astrocytoma patients (log-rank p < 0.019). ConclusionCross-modal AI training using spatial transcriptomics enables scalable, molecularly informed vascular quantification directly from routine H&E slides. Within the astrocytoma subtype, where tumor grade is most heterogeneous and vascular phenotype most variable, objective vascular quantification provides independent prognostic information demonstrating the potential of spatially supervised deep learning to extract clinically meaningful microenvironmental signals from universally available histologic material.