Journal of Hematology & Oncology

Myeloproliferative neoplasms (MPN) are chronic hematologic malignancies characterized by clonal myeloid expansion, inflammation, oxidative stress, and progressive bone marrow (BM) remodeling that may culminate in fibrosis and secondary acute leukemia. Here, we evaluated the therapeutic efficacy and the underlying mechanisms of melatonin (MT) and liposomal melatonin (nano-MT) in preclinical MPN models. MT selectively inhibited clonogenic growth of patient-derived peripheral blood mononuclear cells and induced pluripotent stem cell-derived CD34 hematopoietic stem and progenitor cells in comparison to healthy controls. This effect was associated with increased apoptosis, reduced reactive oxygen species (ROS), and decreased glucose uptake, independently of MT receptor signaling. Transcriptomic profiling of primary MPN CD34 cells revealed suppression of MYC targets, G2M checkpoint signaling, ROS, and glycolysis pathways. In co-culture models, MT reduced stromal -smooth muscle actin and phosphorylated SMAD2/3, indicating inhibition of TGF-{beta}-driven mesenchymal stromal cell-to-myofibroblast formation. In tamoxifen-inducible SclCreER;JAK2V617F mice, nano-MT achieved efficient spleen and BM targeting. Therapeutically, nano-MT reduced erythrocytosis, myeloid progenitor expansion, and BM IL-1{beta} levels. Longitudinal micro-computed tomography and histological analyses demonstrated normalization of BM architecture, reduced osteosclerotic remodeling and splenomegaly, decreased reticulin deposition and megakaryocyte numbers. In a dose-escalation study, nano-MT restored erythrocyte, hematocrit, and platelet counts and normalized megakaryocyte-erythroid progenitors. Combination treatment with ruxolitinib further reduced leukocytosis, neutrophilia, and monocytosis. Collectively, these findings demonstrate that (nano-)MT attenuates MPN and BM remodeling by targeting metabolic, inflammatory, and fibrotic pathways. This study provides the first evidence for a therapeutic benefit of nano-MT in MPN and establishes a rationale for further translational evaluation.

Despite the success of chimeric antigen receptor (CAR) T cell therapy for treatment of B cell acute lymphoblastic leukemia (B-ALL), its translation to acute myeloid leukemia (AML) has been hindered by limited efficacy and significant toxicity. Interferon-gamma (IFN{gamma}) blockade with emapalumab has recently emerged as a promising strategy to mitigate CAR T cell-related toxicities in B cell malignancies, based on evidence that IFN{gamma} is largely dispensable for optimal CAR T cell activity in B-ALL. Whether IFN{gamma} signaling is similarly non-essential in the AML context remains unclear. Here, we demonstrate that disruption of the IFN{gamma} axis impedes anti-AML CAR T cell function and prevents upregulation of target antigen CD123, the apoptotic mediator Fas, and the adhesion molecule ICAM-1 on AML cells. Conversely, exogenous IFN{gamma} enhances CAR T cell cytotoxicity and increases CAR T cell avidity for AML targets. These findings identify IFN{gamma} as a critical mediator of CAR T cell efficacy against AML by promoting increased target antigen expression, enhanced cytotoxicity, and stable CAR T/tumor interactions. Our results suggest that therapeutic IFN{gamma} blockade, including with emapalumab, may compromise CAR T cell responses in AML and should be approached with caution in this disease context.

Chemoradiotherapy (CRT) is the standard-of-care therapy for many solid malignancies, yet predictive biomarkers of treatment response remain limited. We identified a germline single nucleotide polymorphism (SNP) in an intrinsically disordered region of the lysine demethylase KDM3C/JMJD1C (p.S464T) that is associated with CRT outcomes in locally advanced rectal cancers (LARC) and head and neck squamous cell carcinoma (LA-HNSCC). In silico modeling with AlphaFold predicted S464T substitution influenced interaction between phosphorylated KDM3C and RNF8 FHA domain. In cellular models, conversion of S464 to T464 increased sensitivity to DNA-damaging agents. S464T substitution impaired damage-induced MDC1-RAP80 signaling and downstream RAP80-BRCA1 colocalization. SNP carrying cells impaired DNA repair causing genotoxic stress that is associated with increased cGAS-cGAMP innate immune signaling and increased apoptosis. Population analyses with the SNP highlighted an increase incidence of UV-induced skin and other cancers, linking inherited variation in the chromatin regulatory gene KDM3C to genome instability, cancer risk, and therapeutic vulnerability.

Outcomes for high-grade pediatric brain tumor patients remain poor, but there is optimism that chimeric antigen receptor (CAR) T cell therapy can improve prognosis. We present the results from a phase I clinical trial of IL13BBz-CAR T cells infused weekly into the cerebral ventricles in pediatric and young adult patients with recurrent or refractory brain tumors. The trial met its primary objectives of feasibility, safety, and tolerability, with one dose-limiting toxicity. 8 of 16 patients evaluable for response experienced radiographic size decreases consistent with biologic activity and with an anti-tumor response. Two patients met protocol criteria for response. Median survival for patients receiving lymphodepletion was 20.5 months from diagnosis and 6.9 months from treatment for patients with midline glioma, and 187 months from diagnosis and 7.5 months from treatment for patients with ependymoma. Importantly, patients who did not receive lymphodepletion developed anti-CAR humoral and cellular immune responses detectable in the CSF and peripheral blood, whereas patients receiving lymphodepletion had no evidence of CSF anti-CAR immunity. Taken together, these findings demonstrate the safety, tolerability, and biological activity of locoregionally-delivered IL13BBz-CAR T cells for children and young adults with CNS tumors. Moreover, we show that anti-CAR immune responses arise in patients not receiving lymphodepletion, but not in the CSF of patients receiving systemic lymphodepletion. Further investigation of adoptive cellular therapies combined with immunosuppression is warranted in this patient population. ClinicalTrials.gov registration: NCT04510051.

Large genomically annotated acute myeloid leukaemia (AML) datasets exist, but population-based contemporary cohorts remain scarce. Here we report clinicopathological, genomic, and outcome data from Danish AML patients. 2,512 AML patients were identified between 2015-2022, of whom 33.8% had available NGS data (NGS+). In patients [≤]70 years, baseline characteristics and outcomes were comparable between NGS+ and NGS- groups. In patients >70 years, more NGS+ patients received intensive treatment, but survival was similar among intensively treated patients. The distribution of mutations varied significantly by age and sex, with older age and male sex exhibiting higher frequencies of adverse-risk gene mutations. In intensively treated NGS+ patients, ELN2017 stratified 5-year OS: 58.4% (favorable), 43.4% (intermediate), and 28.2% (adverse), with hazard ratios (HRs) of 0.63 (favorable) and 1.45 (adverse) relative to intermediate. ELN2022 yielded corresponding OS rates of 56.9%, 51.8%, and 29.7%, with HRs of 0.78 and 1.86. The two models had comparable predictive performance for OS in a time-dependent model. In conclusion, outcomes of intensively treated AML patients were comparable irrespective of NGS status, underscoring the representativeness of the REFORM-AML database for the Danish AML population. Age and male sex correlated with adverse-risk mutations, and both ELN2017 and ELN2022 robustly predicted survival.

IMPORTANCE: A recent meta-analysis showed that chemoimmunotherapy was associated with improved overall survival (OS) compared with immune checkpoint inhibitor (ICI) monotherapy for programmed death-ligand 1 (PD-L1) tumor proportion score (TPS) [&ge;] 50% advanced non-small-cell lung cancer (NSCLC). However, whether this benefit reflects chemotherapy effect or ICI heterogeneity remains unclear. OBJECTIVE: To reassess the survival benefit of adding chemotherapy to ICI monotherapy using agent-stratified comparisons anchored to chemotherapy. DATA SOURCES: The 24 phase 3 randomized clinical trials included in the original meta-analysis (search date, August 3, 2025). DATA EXTRACTION AND SYNTHESIS: Hazard ratios (HRs) for OS and progression-free survival (PFS) were extracted from each trial in the original meta-analysis. Two analytic frameworks were used: within-agent comparisons (same ICI in both chemoimmunotherapy and monotherapy) and across-agent comparisons (ICI in one treatment strategy only). For within-agent comparisons, a two-stage random-effects meta-analysis was conducted. In stage 1, ICI-specific HRs for chemoimmunotherapy and ICI monotherapy versus chemotherapy were pooled and their ratio was calculated (RHR = HRchemoimmuno/HRmono; RHR < 1 favors chemoimmunotherapy). The RHRs were pooled in stage 2. For across-agent comparisons, RHR was derived from pooled HRs by treatment strategy. MAIN OUTCOMES AND MEASURES: Endpoints were OS and PFS. RESULTS: In within-agent comparisons (4 ICIs; 13 trials; N = 3252), pooled RHR was 0.94 (95% CI, 0.78-1.13; P = .48; I2 = 0.0%) for OS and 0.85 (95% CI, 0.68-1.06; P = .14; I2 = 0.0%) for PFS. In across-agent comparisons (7 ICIs; 11 trials; N = 2231), RHR favored chemoimmunotherapy for OS (0.68; 95% CI, 0.50-0.92; P = .01) and PFS (0.46; 95% CI, 0.37-0.58; P < .001). In a sensitivity analysis restricted to trials of NCCN-recommended regimens, pooled RHR was 1.02 (95% CI, 0.81-1.28; P = .87) for OS. CONCLUSIONS AND RELEVANCE: In the within-agent comparisons, adding chemotherapy to ICI monotherapy did not improve OS or PFS in patients with PD-L1 TPS [&ge;] 50% advanced NSCLC. The benefit in the original meta-analysis appears driven by across-ICI heterogeneity. These findings are consistent with ICI monotherapy as a standard first-line option and underscore the need for agent-level stratification in across-trial comparisons.

The role of UBE2N in myeloid cell-mediated immune suppression in cancer remains undefined. Here, we examined the function of UBE2N in myeloid cell-mediated tumor progression using a temporally inducible myeloid-specific knockout model (LysMCreERUbe2nfl/fl). Temporally induced deletion of Ube2n in myeloid cells (Ube2nMyeKO) significantly hindered growth of YUMM1.7 melanoma. This was accompanied by reduced myeloid cell burden within the tumor microenvironment. We observed altered abundance of PD-1, PD-L1, and SPP1 in the Ube2nMyeKO tumor microenvironment at the tissue level. In vitro analysis showed that knock-in expression of a catalytically deficient UBE2NC87S mutant in bone marrow-derived macrophages (BMDMs) markedly decreased expression of Spp1. We observed decreased SPP1 secretion in Ube2nMyeKO BMDM-conditioned media (CM). Treatment with Ube2nMyeKO BMDM-CM decreased co-expression of PD-1, TIM-3, and LAG-3 on chronically stimulated T cells. Antibody-mediated neutralization of SPP1 in Ube2nWT BMDM-CM decreased PD-1 expression on CD8+ T cells. Together, these findings suggest a role for myeloid UBE2N in YUMM1.7 progression.

Lineage-restricted transcriptional programs establish cell identity and can create selective dependencies in cancer. Here, we identify POU2AF2, encoding the transcriptional co-activator OCA-T1, as a critical lineage-specific dependency in a subset of diffuse large B-cell lymphoma (DLBCL). Pan-cancer dependency analyses and patient cohorts reveal elevated POU2AF2 expression in genetically aggressive DLBCL, where its depletion markedly suppresses tumor growth in vitro and in vivo. Mechanistically, POU2AF2 cooperates with the B-cell lineage-defining transcription factor POU2F2 (OCT2) to activate lymphocyte activation gene programs through direct chromatin engagement, thereby sustaining malignant transcriptional networks. We further identified a key epigenetic regulatory axis composed of the lineage-specific transcription factor TCF3 and the histone methyltransferase SET1A-COMPASS that drives POU2AF2 expression downstream of B-cell receptor signaling. Single-cell transcriptomic analysis reveals that POU2AF2 marks and sustains an innate-like B1 B-cell population in vivo, a candidate cell of origin for lymphoma. Together, these findings define a lineage-restricted POU2AF2/POU2F2 transcriptional module, controlled by a TCF3/SET1A epigenetic network, that sustains both innate-like B-cell identity and malignant fitness in DLBCL. Our study uncovers a previously unrecognized lineage-specific transcriptional dependency and highlights POU2AF2 and its associated regulatory circuitry as potential therapeutic targets in aggressive B-cell malignancies.

Abstract Background: Cytolytic activity (CYT), a widely used transcriptomic surrogate of anti-tumor immune cytotoxicity derived from GZMA (granzyme A) and PRF1 (Perforin 1) expression, is associated with clinical outcomes across cancers. MicroRNAs (miRNAs) are key post-transcriptional regulators of tumor immunity, yet their pan-cancer roles in modulating cytolytic activity remain incompletely understood. Objective: This study aimed to identify conserved miRNA regulators of tumor cytolytic activity and their downstream gene-mediated networks across diverse cancer types, while evaluating their clinical and therapeutic relevance. Methods: Matched miRNA and mRNA expression profiles from 9,288 primary tumors across 31 TCGA cancer types were analyzed. A multi-stage framework was applied: per-cancer Spearman correlations (|{rho}| >= 0.30, FDR < 0.05) identified recurrent CYT-associated miRNAs (at least 3 cancer types); these were integrated with TargetScan-predicted targets and subjected to pan-cancer and cross-cancer triple filtering (miRNA-gene and gene-CYT associations). All associations underwent tumor purity adjustment using Consensus Purity Estimate (CPE), with LUMP (Leukocytes Unmethylation for Purity) as sensitivity analysis. Candidates were further prioritized by random forest modeling with bootstrap stability, cancer-type-adjusted Cox regression, mediation analysis, immune cell deconvolution, k-means molecular subtyping, pathway enrichment, and DGIdb-based drug-target prioritization. Results: The analysis converged on 38 high-confidence miRNA-gene-CYT regulatory triplets involving 9 conserved miRNAs and 31 target genes after stringent purity adjustment and multi-layer validation. All nine miRNAs exhibited complete bootstrap stability. Mediation analysis confirmed significant gene-level mediation in 37 of 38 triplets (FDR < 0.01), with mediated proportions up to 94%. The final miRNA signature defined two distinct pan-cancer immune subtypes (immune-hot vs. immune-cold) with significantly different cytolytic activity and overall survival (OS) (HR = 0.754, FDR = 1.12 x 10^-4). The network was enriched for T-cell activation and lymphocyte differentiation pathways and highlighted multiple druggable targets, including CTLA4 and CD274 (PD-L1), nominating 124 candidate compounds. Conclusions: In conclusion, this tumor purity-adjusted pan-cancer study defines a compact, reproducible, and clinically relevant miRNA network that regulates cytolytic activity across diverse malignancies. By linking miRNA biology to immune subtyping and actionable therapeutic targets, the present work provides a valuable foundation for advancing precision immuno-oncology.

Disseminated cancer cells (DCC) in non-metastatic carcinoma patient bone marrow (BM) are predictive of metastasis. Those detected by epithelial cytokeratin or EpCAM expression have poorly-characterized transcription profiles due to their extreme rarity: 1~2 cells per two million BM cells in every third non-metastatic patient. We here characterize the transcriptomes of DCCs. Single-cell RNA-sequencing (scRNA-seq) of 864 EpCAM-positive cells (from 1,151 cancer patients) in BM or lymph nodes (LN) revealed plasma, immune, myeloid, erythroid progenitor cells and two candidate DCC populations, termed M0-DCC and M1-DCC. M0-DCC, mostly from non-metastatic M0-stage patients, displayed the highest known adult stemness scores, and were transcriptomically reminiscent of human cleavage-stage, preimplantation embryos. M1-DCC represented cancer cells undergoing the epithelial-mesenchymal transition (EMT), corresponding to later, implanting and gastrulating embryos. Detection of early-embryo-like DCC categorised patients at highest risk for metastatic progression. Furthermore, high M0-DCC scores predicted the metastatic potential of human cell lines from the Cancer Cell Line Encyclopedia. M0-DCC gene expression profiles can be reversibly induced from M1-DCC-like cells in vitro. The close correspondence between gene expression profiles in immediate early embryonic development and metastatic founder cell candidates provides strong evidence that the onset of cancer and metastasis recruits mechanisms employed in fertilization.

Next-generation sequencing (NGS) for the detection of somatic variants has become the method of choice in a variety of molecular oncology fields and in the clinic. Its use ranges from sequencing entire tumor genomes and transcriptomes to targeted clinical diagnostic gene panels. The NYU Langone Genome PACT (Profiling of Actionable Cancer Targets, LG-PACT) assay is a qualitative in vitro diagnostic test that uses targeted next generation sequencing (NGS) of formalin-fixed paraffin-embedded (FFPE) tumor tissue matched with normal specimens from patients to detect gene alterations in a targeted panel covering 606 genes and the TERT promoter. Indications for testing are cancer (solid tumors and hematological malignancies) where a mutational profile from multiple genes would be informative for disease stratification, prognosis, or treatment options including targeted therapies and eligibility for clinical trials. The test is intended to provide information on somatic mutations including point mutations, small insertions/deletions (indels), and copy number aberrations for diagnostic and treatment decisions. LG-PACT is a United States Food and Drug Administration (FDA) cleared diagnostic test (510K: K202304). The clinical interpretation of sequencing data of molecular tumor markers from NGS encompasses automated variant calling tools with human interpretation. This final mostly manual review of data step is intensive, involving highly trained scientists, encompassing literature review, interpretation and clinical tier classification by pathologists, who then provide a complete molecular diagnostic report to the treating oncologists. We provide analysis of 1339 clinical genomic profiles from 31 different cancers and their subtypes, comprising of central nervous system (CNS) 792 (59%) cases (incl. meningioma, glioma and glioblastoma), with 267 (20%) cases predominantly of lung, pancreatic and colorectal and 280 of others (21%). Here, we present the technical challenges of validating an NGS oncological diagnostic targeted assay for clinical grade accuracy and sensitivity for patient care. We show how copy number alterations provide a more comprehensive description of the tumors genomic profile. We then outline the utility of targeted panel sequencing based on certified pathologist selection of reportable variants for our current patient cohort. Where analysis of variant detection has led to 49.4% (661/1339) of our clinical tumor samples containing mutations in known therapy targeted genes, 35.6% (477/1339) with mutation detected in other genes, and 15% (201/1339) cases being negative.

DNMT3A is a de novo DNA methyltransferase whose recruitment to chromatin regulates its function. Missense mutations within the chromatin-binding PWWP domain are associated with diverse human disorders, yet how mutations in the same domain produce distinct phenotypes remains unclear. Here we systematically characterise 19 clinically reported mutations in the PWWP domain of DNMT3A that are associated with Heyn-Sproul-Jackson syndrome (HESJAS), paraganglioma (PG) and clonal haematopoiesis (CH). We show that all PWWP-domain mutations associated with HESJAS abolished interaction with H3K36me2 modified nucleosomes, defining this as a consistent biochemical feature of HESJAS. In contrast, mutations from all disease classes differentially altered DNA binding of the PWWP domain, driven by alterations in the net charge of the domain. However, these effects are largely overcome by inclusion of the DNNMT3A1 N-terminal region, which is absent from its embryonic isoform, suggesting that PWWP mutations may differentially affect DNMT3A function through development. Changes in the thermal stability of the isolated PWWP domain mutants did not directly translate into altered stability of full-length DNMT3A1 in cells. We show that HESJAS mutations can affect the intramolecular interaction between the PWWP and adjacent ADD domain, an interaction proposed to contribute to the autoinhibitory function of the ADD domain. However, not all mutations behaved in the same way, suggesting that multiple factors govern the intramolecular autoinhibition of DNMT3A. Together, this study advances our understanding of the molecular mechanisms by which DNMT3A PWWP-domain mutations are mechanistically heterogeneous, providing a biochemical framework that contributes to distinct disease phenotypes.

Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis have shown great promise in treating bladder cancer and are now part of the standard treatment for advanced disease. However, many patients still fail to respond to treatment and at present many biomarkers are assessed but have yet shown only limited results. Therefore, with the advent of combination treatments and the increase of immune related adverse event, the search for reliable predictive biomarkers is paramount. Using a multiplexed enhanced FRET-FLIM based technique (QF-Pro) we quantified the interaction of PD-1/PD-L1, CTLA-4/CD80 and TIGIT/CD155 immune checkpoints in a pre-treatment TMA of 46 patients treated with atezolizumab. The association between higher PD-1/PD-L1 ICP interaction state and treatment efficacy was demonstrated in the male sample cohort, where it identified patients with better PFS. Conversely, patients exhibiting higher CTLA-4/CD80 engagement had a worse response to atezolizumab. Remarkably, the dual assessment of patients with high PD-1/PD-L1 and low CTLA-4/CD80 allowed to identify the best responders. These results indicate that the monitoring of patients immune profile in urothelial carcinoma might be critical in identifying patients who may benefit from combination therapy.

Background: Biochemical recurrence (BCR) occurs in 20-40% of men after radical prostatectomy. Existing postoperative recurrence risk tools based on PSA and pathology are clinically useful but show only moderate and variable discrimination, highlighting the need for biomarkers that improve risk stratification and consequent treatment decisions. We hypothesized that the prostate microenvironment, including both the tumor and non-cancerous adjacent tissue, may contain prognostic features associated with adverse postoperative PSA outcomes. Methods: We assembled a cohort of matched tumor-adjacent benign and tumor prostate tissue from 243 men across three institutions to establish a discovery cohort (n=123; 43 postoperative PSA events, 35%) and validation cohort (n=120; 46 events, 38%). For primary binary analyses, a postoperative PSA event included BCR, defined as two consecutive postoperative PSA values >=0.2 ng/mL, or PSA persistence. We performed RNA sequencing of matched tumor-adjacent benign and tumor tissues, quantified immune signatures, and developed an integrated model combining the adjacent-tissue B-cell signature, preoperative PSA, and radical prostatectomy Gleason score (BRIGADE). CAPRA-S-adjusted Cox analyses excluding recurrence-time-0 cases evaluated time to BCR, and CD19 multiplex immunofluorescence provided tissue-level confirmation (n=10). Results: In prostatectomy specimens, tumors from patients without a postoperative PSA event were enriched for B-cell transcriptional programs, whereas tumors from event-positive patients showed elevated proliferation signatures. B-cell-related transcriptional programs were correlated between tumor and adjacent tissue. Tumor-adjacent benign B-cell scores were higher in no-event cases and discriminated postoperative PSA-event status in PCBN discovery (AUC 0.63) and BM validation (AUC 0.81) cohorts, outperforming numerous other immune-related signatures. In CAPRA-S-adjusted Cox sensitivity analyses excluding recurrence-time-0 cases, higher adjacent-tissue B-cell activity was associated with reduced recurrence risk in PCBN (HR 0.42, 95% CI 0.19-0.94; BH-adjusted p=0.035) and BM (HR 0.54, 95% CI 0.30-0.95; BH-adjusted p=0.034). Tissue-based validation showed that CD19+ B-cell density in adjacent benign tissue was higher in no-event than event-positive patients (median 0.1145 vs 0.0471; p=0.008). BRIGADE achieved an AUC of 0.68 in cross-validation and 0.83 in independent validation, compared to AUCs of 0.54-0.63 and 0.44-0.78 for the tested clinical predictors, respectively. At the fixed classification threshold, the validation-cohort odds ratio for BRIGADE was 2.75. The adjacent B-cell score remained associated with lower odds of a postoperative PSA event after adjustment for PSA and Gleason score. Conclusions: B-cell infiltration in tumor-adjacent benign prostate tissue may complement existing clinicopathologic models for stratifying adverse postoperative PSA outcomes and subsequent BCR after radical prostatectomy. The transcriptomic signal was recapitulated by CD19-based tissue staining, supporting further development of a pathology-based assay.

Background: Immunochemotherapy (ICT) is considered standard in regards to care for small-cell lung cancer (SCLC) in extensive stages, yet reliable biomarkers for treatment response remain elusive. While previous univariate analyses suggest specific peripheral lymphocyte subsets correlate with survival, the systemic immune response involves complex, multivariate interactions that require advanced analytical approaches. Methods: This paper analysed high-dimensional flow cytometry data from 32 patients with stage IV SCLC treated with carboplatin, etoposide, and atezolizumab. Peripheral blood was analysed at baseline (V0) and longitudinally during treatment. To identify potential early predictive biomarkers and mitigate sample attrition in later cycles, we focused on baseline and measurements after two cycles of ICT (V1). We employed a rigorous machine learning framework utilising nested cross-validation, bootstrapping, and permutation-based statistical testing to evaluate eleven different regression and survival models. Results: Under model-appropriate metrics, regressors did not generalise (R2 <0); conversely, censoring-aware Random Survival Forests (RSF) successfully extracted robust prognostic signatures. Baseline immune profiles (V0) achieved a concordance index (C-index) of 0.66 (p= 0.015), while dynamic changes from V0 to V1 ({triangleup}V) achieved a C-index of 0.65 (p= 0.022). Crucially, absolute values measured after two cycles of ICT (V1) yielded no significant signal (p= 0.445). Feature importance analysis confirmed the prognostic value of Th17 normalisation and identified Naive Regulatory T cells and Memory B cells as candidate components. Conclusion: Machine learning validation confirms a predictive signal in the peripheral immune profile of SCLC patients. Early dynamic shifts in the balance between regulatory and effector immune arms are associated with prognosis, contrasting with the lack of signal in absolute counts after two cycles of ICT. These findings establish a proof of concept for multivariate liquid biopsy immune profiling, warranting confirmation in larger cohorts and highlighting the necessity of integrating systemic and tumour-intrinsic data.

Prognostic models in oncology are developed one cancer at a time, from that cancer's own labelled outcomes, and fail where prognostic information is scarcest. Rare cancers account for roughly a fifth of diagnoses and most paediatric malignancies, yet seldom supply enough events for a reliable time-to-event model. We therefore asked whether a representation learned without outcome labels can supply what those cohorts cannot. A Transformer encoder was pretrained by masked field-value modelling on 9425135 tumour records from the SEER 17 registries, diagnosed in 2000 to 2023. Only diagnosis-time fields passing a fail-closed coding-verification gate were admitted, and each record was emitted as an era-specific and a harmonised view, keeping two decades of recoding auditable. The encoder was then frozen and read by a linear Cox head for overall survival. Nine rare cancers were removed from the pretraining corpus entirely, each requiring an independent pretraining run. On a sealed test partition, all nine exceeded an architecture-identical random frozen encoder in Harrell concordance by +0.0034 to +0.0368, every lower confidence limit above zero. At 256 labelled patients, all 67 cancers favoured the pretrained representation over budget-matched Cox regression, median difference +0.0283. The advantage was bounded: given the entire training set, Cox regression was favoured in seven of nine rare cancers. The encoder did not outperform a field-frequency baseline on its own objective, so upstream reconstruction did not predict downstream transfer. Outcome-agnostic registry pretraining carries prognostic signal into cancers it has never seen, and is most useful where labels are fewest, without establishing clinical utility.

Background Elexacaftor-tezacaftor-ivacaftor (ETI) has been demonstrated to improve lung function in clinical trials; however, evidence describing effects on trajectories and whether long-term improvements are sustained (>1-year) is lacking. We estimated within-person lung clearance index (LCI) trajectories before and after ETI initiation, assessing changes in level and rate of change, alongside acute LCI change, up to three years after ETI initiation. Methods Prospective observational study of children at a tertiary hospital. Children aged 3-17 years with [&ge;]2 LCI testing occasions (i) before and (ii) after starting ETI were used to describe lung function trajectories. Children with [&ge;]1 pre-ETI and [&ge;]1 post-ETI LCI occasion(s) were used to describe acute LCI change after ETI initiation. Age-adjusted LCI trajectories for time periods (i) before and (ii) after ETI initiation were estimated using linear mixed-effects models, and pre- and post-ETI LCIs were compared using paired Wilcoxon tests. Results Mean pre-ETI and post-ETI longitudinal changes in LCI were -0.007 (95% CI: -0.28, 0.27; n=35) and 0.12 (95% CI: -0.17, 0.41; n=20) turnovers per year, respectively. Before ETI initiation, 57% (30/53) of patients had an LCI[&ge;]7.1 turnovers (indicating impaired lung function), compared to 26% (14/53) post-ETI, with a median LCI difference of -0.70 (95% CI -0.84, -0.46; p<0.001) turnovers. Within-individual variability in LCI decreased post-ETI. Conclusions Our real-world data within a unique longitudinal study provide a comprehensive picture of ETI benefit by outlining not only acute improvement in LCI but maintained stability in LCI trajectories and improved LCI stability sustained up to three years post-initiation.

Artificial intelligence applied to routine electrocardiograms (ECGs) has largely focused on detecting existing disease or predicting individual cardiovascular outcomes. Whether ECGs can support prediction of multiple future diseases across organ systems remains unclear. We developed ECG-RISK, a multitask survival model for 67 incident three-character ICD-10 endpoints using ECG waveforms, demographic characteristics and routinely collected laboratory data from 86,673 MIMIC-IV patients. Discrimination was highest for heart, brain, kidney and lung endpoints, with organ-level C-indices ranging from 0.796 to 0.825, whereas liver and pancreatic endpoints showed lower discrimination. The ECG-only model achieved strong discrimination across most endpoints, whereas the incremental improvement gained by incorporating ECG and laboratory inputs beyond demographic information varied substantially across endpoints. Across the nine exploratory aggregated outcomes, Kaplan Meier curves showed clear separation among model-score tertiles. Discrimination was highest for dementia (C-index, 0.891) and heart failure (C-index, 0.857). These findings support the feasibility of ECG-based longitudinal risk prediction across multiple diseases. External validation and competing-risk analyses are required to assess generalisability and clinical utility.

Objectives To evaluate whether access to a certified large language model (LLM)-based clinical decision support system improves physician diagnostic performance in rheumatology compared with conventional diagnostic resources alone. Methods In this multicentre, open-label, randomised controlled trial, 82 physicians from seven hospitals in two countries were randomised 1:1 to conventional diagnostic resources plus Prof. Valmed or conventional resources alone. Participants assessed three rheumatology vignettes before and after assistance. The primary outcome was top-1 diagnostic accuracy. Secondary outcomes included top-3 accuracy, diagnostic reasoning, confidence, case-processing time and perceived support quality. Results Top-1 accuracy increased from 22.2% to 33.3% in the intervention group and from 23.3% to 35.0% in the control group, with no between-group difference in improvement (adjusted OR 0.99, 95% CI 0.45 to 2.19; p=0.979). Differences in top-3 accuracy, diagnostic reasoning and confidence were also not significant. Assisted case-processing time was substantially shorter with LLM support (94 vs 206 s; adjusted mean difference -112 s, 95% CI -141 to -83; p<0.001). Information timeliness and perceived diagnostic support quality were rated significantly higher in the intervention group. Exploratory analyses showed persistent overconfidence and substantial AI over-reliance. Conclusions Certified LLM-based diagnostic support did not improve diagnostic accuracy compared with conventional resources, but substantially reduced case-processing time and improved perceived support quality. These findings suggest potential workflow benefits while highlighting overconfidence and over-reliance as important safety considerations.

Purpose: To evaluate the safety, procedural performance, sample recovery, and surgeon preference of an ophthalmic needle designed specifically for anterior chamber (AC) paracentesis. Methods: In this multicenter study, AC paracentesis was performed in clinic and operating-room settings using a 32-gauge x 4-mm needle with low dead space. The procedure was evaluated using a standardized physician survey. Prespecified outcomes included procedure-related adverse events (primary outcome), needle entry and handling, aspiration and sample recovery, comparative performance versus a 30-gauge needle, and physician preference for future use. Results: A total of 110 needle uses by eight surgeons were included. No ocular complications occurred, including lens or iris injury, hyphema, AC collapse, wound leak, hypotony, infection, or retinal complication, and no procedure required needle exchange or conversion to another device. Two technical events without ocular sequelae were noted, in which needle entry was partial thickness and did not reach the AC (1.8%; exact 95% CI, 0.2%-6.4%). Physicians rated needle entry, handling and sample recovery as good or excellent. Compared with a 30-gauge needle, the study needle was rated as at least comparable across all assessed domains. All surgeons rated it better or much better for intra-procedural safety and preferred it for future AC taps. Conclusions and Relevance: This short, 32-gauge low-dead-space ophthalmic needle demonstrated a favorable safety profile and was preferred over a 30-gauge needle by all surgeons. As aqueous humor liquid biopsy expands in clinical diagnostics and trials, an ophthalmic-specific needle design may help improve the consistency and safety of aqueous humor collection for molecular analysis and broader clinical use. Keywords: Anterior chamber paracentesis; Aqueous humor; Liquid biopsy; Low dead space; Ophthalmic needle