Citations

Abstract Rationale To construct multi-trait polygenic scores (PRS) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validate their performance in diverse cohorts, and identify PRS-related proteins for potential therapeutic targeting. Methods PRSmix+, a multi-trait PRS framework, is used to train a composite PRS (PRSmulti) in COPDGene non-Hispanic white participants (n = 6,647). Associations of PRSmulti with COPD status (GOLD 2-4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American (n = 2,466), ECLIPSE (n = 1,858), MassGeneral Brigham Biobank (n = 15,152), and All of Us (n = 118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRSmulti and were validated with proteomic data in COPDGene (n = 5,173) and UK Biobank (n = 5,012). Results PRSmix+ selected 7 traits for PRSmulti. In multivariable models, PRSmulti was associated with COPD status (meta-analysis random effects (RE) OR 1.58 [95% CI: 1.28-1.94]) and exacerbation frequency (meta-analysis RE beta 0.21 [95% CI: 0.11-0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRSmulti outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRS that were also validated with measured protein levels in COPDGene and UK biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include AGER (RAGE), IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations. Conclusions Multi-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management. Trial registration. COPDGene: NCT00608764; ECLIPSE: NCT00292552. This abstract is funded by: NIH and the COPD Foundation

Background/Objectives: Accurate detection of pulmonary nodules on chest CT is critical for lung cancer screening, yet training robust detectors remains challenging due to the high cost of reliable annotations. In this work, we present a systematic study of curriculum learning for CT-based lung nodule detection on the enhanced LUNA25 benchmark and propose a hybrid curriculum learning framework for data-efficient optimization. Methods: Our approach estimates sample difficulty by fusing clinically interpretable handcrafted factors such as nodule size and count with model-driven signals such as prediction confidence from a teacher model, and constructs a three-stage progressive training curriculum from easy to hard samples. Using YOLOv11s as a strong baseline, the proposed hybrid curriculum is compared against conventional training without curriculum learning and against single-source curricula. Results: On the held-out LUNA25 test set, hybrid curriculum learning increases mAP50 from 0.672 to 0.696, mAP50–95 from 0.369 to 0.385, recall from 0.588 to 0.634, and precision from 0.725 to 0.764. Extensive data-efficiency experiments with proportional reductions (1/2, 1/5, 1/10) and fixed training samples (5000–40,000 slices) further confirm consistent gains across limited-data regimes. Conclusions: These results demonstrate that jointly leveraging intrinsic image complexity and optimization-aware feedback provides effective sample scheduling for robust and data-efficient lung nodule detection.

BACKGROUND: Hemorrhagic risk in dural arteriovenous fistulas (dAVFs) is largely determined by venous anatomy, but the contribution of systemic cardiovascular factors and their medical therapy remains poorly defined. This study examined associations between cardiovascular risk factors and antithrombotic use and hemorrhagic presentation, angiographic obliteration, and early functional outcomes after treatment. METHODS: We analyzed 1350 adults with intracranial dAVFs from the international Consortium for Dural Arteriovenous Fistula Outcomes Research registry, which retrospectively accrued cases across 14 centers in 4 countries between 1990 and 2017. Demographics, cardiovascular comorbidities, antithrombotic use, angioarchitectural features, treatment strategies, and follow-up outcomes were collected from prospectively maintained databases. Primary end points were hemorrhagic presentation, angiographic obliteration, and 90-day functional status after treatment. Univariable and multivariable logistic regressions were performed with model-specific adjustments. RESULTS: Hemorrhage occurred in 375 patients (27.8%) and was most strongly associated with high-grade dAVF classification and male sex; antithrombotic therapy was associated with lower odds of hemorrhagic presentation. Other cardiovascular risk factors showed no independent relationship with bleeding. Angiographic obliteration was achieved in 621 of 845 patients (73.5%). Hemorrhagic onset, high dAVF grade, and surgical treatment were independently associated with angiographic obliteration, whereas smoking and embolization demonstrated only nonsignificant trends after adjustment. At 90 days, 934 patients (88.9%) were functionally independent. Baseline modified Rankin Scale score was the strongest factor associated with 90-day functional outcome, while neither cardiovascular comorbidities nor treatment modality independently influenced functional status. CONCLUSIONS: In this large multicenter dAVF cohort, hemorrhagic presentation was most strongly associated with venous angioarchitecture. Male sex and antithrombotic therapy were also independently associated with hemorrhagic presentation. Angiographic obliteration was common, particularly among surgically treated lesions, and 90-day functional outcome was most strongly associated with baseline functional status.

Abstract The CoMMpass study (NCT01454297) is a prospective, longitudinal observational study involving 1,141 newly diagnosed multiple myeloma (NDMM) patients. Bone marrow aspirates from the study participants were collected for comprehensive molecular characterization of tumor (using bulk RNA sequencing and whole genome sequencing) and tumor immune microenvironment using 3’ single-cell RNA sequencing (scRNA-seq). To support exploration of this rich multi-omic dataset, we developed CoMMpass Explorer (CE), an intuitive interactive platform that enables real-time analysis of clinical and genomic data from CoMMpass. A central feature of CE is cohort building, where users can filter and stratify patients by clinical, genomic, and survival data elements to create custom cohorts for analysis. CE provides five main views: Overall Summary for clinical feature distribution, Kaplan-Meier curves, and multivariate Cox proportional hazards models; Mutational Profile for visualizing and comparing somatic mutations; Tumor Profile for bulk differential expression and gene set enrichment; Immune Microenvironment for comparing cell type abundance and cell cycle dynamics between cohorts using scRNA-seq data; and Pseudo-Bulk, which aggregates single-cell expression by cell type to enable cohort-level comparisons of transcriptional programs using DEseq2. CE reproduces prior CoMMpass studies, including WEE1 expression being associated with poorer progression-free survival (Simhal, et al.) and different mutation frequencies between African American and European American patients (Manojlovic, et al.). We further demonstrate CE’s utility by interrogating the 2025 Consensus Genomic Staging (CGS) risk classification system (Avet-Loiseau, et al). We compared CGS high-risk (HR, n=249) vs. CGS standard-risk (SR, n=573) patients. HR patients have significantly worse progression-free survival, overall survival, and time to second-line therapy compared with SR patients. Univariate models recapitulated expected differences in the clinical features that define CGS risk. Bulk tumor RNA-seq and ssGSEA highlighted a more proliferative and genomically unstable transcriptional program in HR group, with upregulation of angiogenesis and cell-cycle-related pathways. In the immune microenvironment, monocytes were more abundant in the SR group. Pseudo-bulk RNA-seq of plasma cells showed overexpression of ANXA1, NSD2, IGF1R, MAF and related genes in HR. CE democratizes access to the CoMMpass multi-omic resource, allowing researchers to interrogate clinical and molecular heterogeneity. By enabling hypothesis generation and replication of published results, CE serves as a valuable tool for identifying prognostic biomarkers and meaningful patterns in gene expression, mutation profiles, and the immune microenvironment. Citation Format: Wanxing Zhang, Chaitanya R. Acharya, Steven M. Foltz, David E. Avigan, Samir Parekh, Ravi Vij, Shaji Kunnathu Kumar, Taxiarchis Kourelis, Sagar Lonial, Hearn Cho, Ioannis S. Vlachos, Sacha Gnjatic, Li Ding, Manoj Bhasin, George Mulligan. CoMMpass Explorer: An interactive platform to explore clinical and genomic data from newly diagnosed multiple myeloma patients from the landmark CoMMpass observational study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5504.

Background: Acute myeloid leukemia (AML) with CBFB::MYH11 fusion and myeloid/lymphoid neoplasms with eosinophilia and tyrosine kinase gene fusions (MLN-TK) are genetically defined and typically mutually exclusive entities. Case Presentation: We report a unique case of de novo AML harboring two clonal, transcriptionally active class-defining fusions: CBFB::MYH11 and GOLGA4::PDGFRB. A 61-year-old woman presented with leukocytosis with neutrophilia, eosinophilia, and monocytosis; circulating blasts; and a markedly hypercellular marrow. Cytogenetic analysis revealed inv(16)(p13.1q22) and t(3;5)(p21;q32) in all 20 metaphases, and RNA sequencing confirmed expression of both CBFB::MYH11 and GOLGA4::PDGFRB fusions. In addition, an oncogenic WT1 frameshift variant was identified. Hematopathologic findings were largely consistent with AML with CBFB::MYH11 fusion but exhibited features reminiscent of PDGFRB-rearranged MLN-TK. The patient achieved complete remission following the standard 7 + 3 induction chemotherapy regimen for AML with gemtuzumab ozogamicin. Conclusions: This case illustrates the diagnostic challenges posed by concomitant class-defining alterations in hematologic neoplasms and underscores the importance of integrated genomic assessment.

Abstract INTRODUCTION The infectious hypothesis suggests that microbes like herpesviruses may play a role in the pathogenesis of Alzheimer's disease (AD) and other related dementias through methods that may include viral genome integration. The occurrence of herpesvirus genome integration in dementia patients has not been thoroughly characterized. METHODS Over 7500 total whole‐genome sequences from control, frontotemporal dementia/amyotrophic lateral sclerosis spectrum, Lewy body dementia (LBD), multiple system atrophy (MSA), and AD cohorts were screened for the integration of pathogen genomes using the PathSeq computational tool. RESULTS Low PathSeq scores for human herpesvirus 6 (HHV‐6) were consistent with the suspected integration of viral genome segments. The LBD and MSA cohorts had a significantly higher prevalence of this partial HHV‐6 genome integration. DISCUSSION This higher prevalence in both synucleinopathies was not noted in other herpesviruses, suggesting that the integration of HHV‐6 may play a role in a subset of these patients. Highlights Over 7500 whole‐genome sequences from controls and dementia patients were analyzed. Sequences consistent with integrated herpesviruses were identified using PathSeq. Prevalence of partial HHV‐6 integration was higher in synucleinopathies. Herpesviruses genome integration may play a role in subsets of dementia patients.

Elucidating the structure and function of enteropeptidase (EP) is essential for advancing our understanding of its biological significance, particularly in regulating trypsinogen activation. Using cryo-EM and enzymatic activity, we uncovered the significance of the CUB2 domain in mediating the cleavage of macromolecular substrates. We identified crucial binding loops and key residues for EP’s proteolytic function. The mutation E574A enhanced the proteolytic activity of EP, whereas the mutation N619A diminished its cleavage efficiency, highlighting the importance of surface-charged interactions in modulating EP’s activity. A proteolytic cycle was proposed to deepen our understanding of the trypsinogen activation by EP. This work offers valuable insights into the molecular mechanisms underlying EP’s interaction with its substrate, and opens up avenues for therapeutically modulating EP-mediated proteolysis.

Abstract Adoptive T-cell therapies using tumour-specific T-cell receptors (TCRs) are limited by competition with endogenous receptors, which impairs efficacy and poses risks of off-target autoreactivity. Here we present a CRISPR-based platform that completely and selectively eliminates both endogenous TCR-α and -β chains without affecting introduced transgenic TCRs, irrespective of codon optimization. This approach achieves >90% deletion efficiency in Jurkat and primary human T cells, markedly enhancing the expression, pairing fidelity, and functional potency of transgenic receptors. Using a clinically relevant HLA-A*02:01-restricted DMF5 TCR, we show that dual TCR ablation boosts antigen-specific activation and cytotoxicity in vitro and significantly enhances tumor clearance in vivo in human immune system (HIS) mice, while preventing graft-versus-host disease (GVHD). Targeted locus amplification revealed that CRISPR-induced double-strand breaks did not alter lentiviral integration profiles, confirming genomic safety. Extending this approach to four insulin-reactive TCRs demonstrated that removal of endogenous receptors increased transduction efficiency and functional activity, with one (1E6) showing selective activation and infiltration of stem cell–derived islet grafts (SC-islets) in vivo . This study establishes a universal, safe, and scalable genome-editing platform for generating functionally precise human T cells. By integrating cancer immunotherapy and autoimmune disease modelling within a single framework, it provides a strong preclinical rationale for dual endogenous TCR removal as a route to improved specificity, safety, and therapeutic efficacy in TCR-based cell therapies.

BACKGROUND We constructed multi-trait polygenic risk scores (PRSs) predicting chronic obstructive pulmonary disease (COPD) and exacerbations, validated their performance in diverse cohorts, and identified PRS-related proteins for potential therapeutic targeting. METHODS PRSmix + , a multi-trait PRS framework, is used to train a composite PRS (PRS multi ) in COPDGene non-Hispanic White participants ( n = 6,647). Associations of PRS multi with COPD status (GOLD 2–4 vs. GOLD 0 or ICD) and exacerbation frequency were tested in COPDGene African American ( n = 2,466), ECLIPSE ( n = 1,858), Mass General Brigham Biobank ( n = 15,152), and All of Us ( n = 118,566). Protein prediction models were applied to GWAS summary statistics from traits contributing to PRS multi and were validated with proteomic data in COPDGene ( n = 5,173) and UK Biobank ( n = 5,012). RESULTS PRSmix + selected 7 traits for PRS multi . In multivariable models, PRS multi was associated with COPD status (meta-analysis random effects [RE] OR 1.58 [95% CI: 1.28–1.94]) and exacerbation frequency (meta-analysis RE β 0.21 [95% CI: 0.11–0.31]), with higher effect sizes observed in smoking-enriched cohorts. PRS multi outperformed traditional single-trait PRS in all tested cohorts. Using protein prediction models, we identified 73 proteins associated with the PRSs that were also validated with measured protein levels in COPDGene and UK Biobank. Of these proteins, 25 were linked to approved or investigational drugs. Notable targets include RAGE/sRAGE, IL1RL1, and SCARF2, all implicated in COPD pathogenesis and exacerbations. CONCLUSIONS Multi-trait PRS improves prediction of COPD and exacerbation risk. Integration with proteomic data identifies druggable protein targets, offering a promising avenue for precision medicine in COPD management. TRIAL REGISTRATION COPDGene: ClinicalTrials.gov NCT00608764; ECLIPSE: ClinicalTrials.gov NCT00292552.