Citations

Background Pancreatic ductal adenocarcinoma (PDAC), the most common malignant type of pancreatic cancer, is characterized by a dense desmoplastic stroma, low neoantigen burden, and a highly immunosuppressive tumor microenvironment (TME). Methods We present a novel strategy harnessing acute transplant rejection mechanisms by employing a recombinant oncolytic rVMG vector engineered to express murine alloantigens H-2Kb (rVMG-H-2Kb) or H-2Kk (rVMG-H-2Kk), thereby inducing tumor-specific antigenic mismatch responses. Results In vitro, rVMG-H-2Kb and rVMG-H-2Kk exhibited strong replication and cytolytic activity while inducing cell surface expression of both H-2Kk and endogenous H-2Kb, in addition to upregulation of antigen presentation genes (β2-microglobulin, Tap1, and Tapbp). In two immunocompetent PDAC models, intratumoral and systemic delivery of rVMG-H-2Kb and rVMG-H-2Kk delayed tumor progression, with rVMG-H-2Kk conferring a survival advantage. Multiplex immunohistochemistry and immunophenotyping revealed substantial TME remodeling, marked by increased effector T-cell infiltration, regulatory T-cell depletion, and reduced fibrosis. Spatial transcriptomics further showed compartment-specific immune activation and epithelial metabolic reprogramming, corroborating with enhanced tumor immunogenicity. Despite these effects, rVMG-H-2Kk also induced compensatory immunosuppressive pathways, including upregulation of antiviral response genes and immune checkpoint receptors such as programmed death-ligand-2. Importantly, combination therapy with rVMG-H-2Kk and murine checkpoint blockade (anti-programmed cell death protein-1 and anti-cytotoxic T-lymphocyte-associated protein 4) drastically improved survival compared to checkpoint blockade alone. Strikingly, surviving mice resisted tumor rechallenge, indicating the establishment of durable antitumor memory. Conclusion These findings establish rVMG-mediated alloantigen delivery as a novel immunotherapeutic platform capable of converting immune-cold tumors into immune-hot, sensitizing tumors to immune checkpoint inhibitors, and establishing durable antitumor immunity in PDAC.

Abstract Aims SCN5A-E1784K (c.5350G>A) is the most common variant associated with the long QT (LQTS) and Brugada syndromes (BrS). It can manifest variably as LQTS, BrS, and/or conduction disorders. This presents a challenge for risk stratification. We aimed to describe clinical and ECG characteristics and identify risk markers that associate with arrhythmic events. Methods and results We undertook a retrospective observational multicentre study of a large cohort of 231 subjects with SCN5A-E1784K from Europe, USA, and Japan. Comprehensive demographic and clinical data, including initial presentation ECG and follow-up, were collected. ‘Lethal events’ were defined as sudden death, non-fatal cardiac arrest, and documented sustained VT or VF. ‘Cardiac events’ were defined as arrhythmic syncope plus any lethal events. Clinical characteristics and ECG parameters corrected for age were investigated for association with lethal and/or cardiac events. Fourteen (6%) subjects experienced a lethal event and 45 (19%) a cardiac event. PR interval and QRS duration were associated with lethal and cardiac events. In multivariable models, both PR interval and QRS duration were associated with lethal events, but only QRS duration was associated with cardiac events. Only age-corrected QRS (rQRS) was associated with lethal and cardiac event-free survival from birth after correction for multiple testing. Conclusion Ventricular myocardial conduction appears likely to play a role in the risk of arrhythmic events in patients with SCN5A-E1784K. This provides an important opportunity for the personalization of management and has the potential to guide preventative therapies.

Summary Cancer genome sequencing is essential for understanding tumor evolution and advancing precision medicine. 1 However, reference gaps and germline variants obscure detection of small and large somatic variants and methylation in repetitive regions. 1–3 It is common for tumor cells to gain or lose chromosome arms due to somatic structural changes that occur inside highly repetitive satellite DNA sequences in the centromeres. 4 To identify the full spectrum of somatic variants, including complex rearrangements, we construct and curate near-complete, haplotype-resolved assemblies of the most recent common ancestor of an early-passage broadly-consented hypodiploid pancreatic cancer cell line and matched normal tissues. The tumor assembly completely recapitulates all 35 tumor chromosomes observed with karyotyping, with multiple translocation-induced hybrid chromosomes. The hybrid chromosomes contain putative functional dicentric and fused centromeres, nested foldback inversions causing 14 breakpoints with a haplotype switch in a single event, and centromeric satellite tandem duplications up to 136 kbp. Direct comparison of tumor and normal assembly haplotypes uncovers >7,000 variants altering >1 Mbp of sequence in repetitive regions that have been hidden by reference gaps and germline variants. 44 % of somatic small variants change representation because they alter germline variants on GRCh38, impacting mutational signatures and kataegis/omikli clusters. Most somatic LINE insertions originate from two hypomethylated non-reference germline LINE insertions, highlighting their impact on insertion mutation burden. These assemblies demonstrate that centromeric, acrocentric, and telomeric regions conventionally excluded from analysis harbor extensive somatic and epigenetic changes. Resolving complete tumor genomes enables a deeper understanding of cancer structural plasticity and the endpoints of breakage-fusion-bridge cycles. These assembled, curated paired normal-tumor benchmarks will serve as a critical foundation for developing future algorithms to characterize the most intractable regions of cancer genomes.

Abstract INTRODUCTION Naturalistic driving provides real‐world behavioral indicators of early cognitive and functional changes. This study integrated naturalistic driving GPS trajectories collected from in‐vehicle sensors with points of interest (POIs) to quantify daily environmental engagement among older adults who were cognitively normal at enrollment. METHODS Data from 438 participants enrolled in the Driving Real‐world in‐Vehicle Evaluation System Project were used to generate daily POI share vectors and model latent engagement patterns using a logistic‐normal hidden Markov model (HMM). Thirteen latent states described distinct modes of environmental interaction. From each participant's inferred state sequence, we derived mobility features – state occupancy, dwell time, transition entropy, and self‐transition probability – and examined their differences across clinical status groups and associations with Preclinical Alzheimer's Cognitive Composite (PACC) performance. RESULTS Transition entropy and several state‐specific occupancy and dwelling metrics differed across clinical groups, but none of the mobility features were significantly associated with PACC scores. DISCUSSION Mobility‐derived behavioral features differentiate clinical status groups and may reflect early functional changes preceding cognitive decline.

Abstract We present chromosome-level, phased diploid genome assemblies of two widely used human fibroblast cell lines: BJ (46,XY) and IMR-90 (46,XX). Using Oxford Nanopore, PacBio HiFi, and Hi-C sequencing data, we generated assemblies spanning 5.9 and 6.0 Gbp with diploid quality values exceeding QV 60. To validate structural integrity, we developed KaryoScope, an alignment-free tool for generating computational karyograms from k-mer feature databases. We identify >50 000 structural variants relative to T2T-CHM13v2.0, the majority of which are heterozygous and cell-line-specific. Combining reference-based and de novo gene annotation, we uncover a previously unreported 1 Mbp homozygous duplication at the 16p11.2 locus in BJ, demonstrating that even karyotypically normal cell lines can harbor clinically relevant submicroscopic rearrangements. We show that mapping publicly available short-read, RNA-seq, and ChIP-seq data to sample-matched diploid assemblies substantially improves read alignment and enables haplotype phasing of 23%–28% of short reads. The BJ and IMR-90 assemblies and associated variant calls are publicly available as a resource for the research community.

Background/Objectives: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluation. However, current automated approaches for lesion detection and segmentation are typically designed for specific MRI contrasts or acquisition sites, limiting their generalizability in real-world clinical settings where imaging protocols vary widely. This work proposes a robust multi-site, multi-contrast segmentation framework for spinal cord lesions. Methods: The segmentation model was trained and evaluated on a large-scale dataset comprising 4428 annotated images from 1849 persons with MS across 23 imaging centers, encompassing six MRI contrasts (T1w, T2w, T2*w, PSIR, STIR, and UNIT1) acquired at 1.5 tesla (T), 3 T, and 7 T. Results: Likert-type assessment performed by neuroradiologist ratings demonstrated superior generalization of the model compared to existing contrast-specific pipelines ( p < 0.01). Additional experiments evaluated robustness across spinal levels, acquisition resolutions, binarization thresholds, and quantitative evaluation on external labeled datasets. Conclusions: The proposed model can achieve accurate and reliable spinal cord MS lesion segmentation across heterogeneous MRI data, addressing a key barrier to clinical translation. The model is available in the Spinal Cord Toolbox v7.2 and higher. Code repository: https://github.com/ivadomed/seg-sc-ms-lesion-multicontrast

Abstract Pancreatic cancer disproportionately affects Black individuals in the United States, but they have limited representation in genetic studies of pancreatic ductal adenocarcinoma (PDAC). To address this gap, we performed admixture mapping and genome-wide association analysis (GWAS) in genetically inferred African ancestry individuals (1,030 cases and 889 controls). Admixture mapping identified three regions with a significantly higher proportion of African ancestry in cases compared to controls (5q33.3, 10p1, 22q12.3). GWAS identified a genome-wide significant association at 5p15.33 ( CLPTM1L , rs383009:T>C, T Allele Frequency=0.51, OR:1.45, P value=1.24×10 -8 ), a locus previously associated with PDAC. Known loci at 5p15.33, 7q32.3, 8q24.21 and 7q25.1 also replicated (P value <0.01). Multi-ancestral fine-mapping identified two potential causal SNPs (rs3830069 and rs2735940) at 5p15.33. Collectively these findings identified novel PDAC risk loci and expanded our understanding of this deadly cancer in underrepresented populations, emphasizing the multifactorial nature of PDAC risk including inherited genetic and non-genetic factors. Statement of Significance To understand how genetic variation contributes to PDAC risk in Black people in North American, we studied individuals of genetically-inferred African ancestry. We identified novel risk loci and differences in the contribution of known loci. This demonstrates that ancestry-informed genetic analyses improve our understanding of PDAC risk and enhances discovery.