99 research outputs found

    Clinical and molecular characterization of HER2 amplified-pancreatic cancer

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    <p>Background: Pancreatic cancer is one of the most lethal and molecularly diverse malignancies. Repurposing of therapeutics that target specific molecular mechanisms in different disease types offers potential for rapid improvements in outcome. Although HER2 amplification occurs in pancreatic cancer, it is inadequately characterized to exploit the potential of anti-HER2 therapies.</p> <p>Methods: HER2 amplification was detected and further analyzed using multiple genomic sequencing approaches. Standardized reference laboratory assays defined HER2 amplification in a large cohort of patients (n = 469) with pancreatic ductal adenocarcinoma (PDAC).</p> <p>Results: An amplified inversion event (1 MB) was identified at the HER2 locus in a patient with PDAC. Using standardized laboratory assays, we established diagnostic criteria for HER2 amplification in PDAC, and observed a prevalence of 2%. Clinically, HER2- amplified PDAC was characterized by a lack of liver metastases, and a preponderance of lung and brain metastases. Excluding breast and gastric cancer, the incidence of HER2-amplified cancers in the USA is >22,000 per annum.</p> <p>Conclusions: HER2 amplification occurs in 2% of PDAC, and has distinct features with implications for clinical practice. The molecular heterogeneity of PDAC implies that even an incidence of 2% represents an attractive target for anti-HER2 therapies, as options for PDAC are limited. Recruiting patients based on HER2 amplification, rather than organ of origin, could make trials of anti-HER2 therapies feasible in less common cancer types.</p&gt

    Epigenomic characterization of Clostridioides difficile finds a conserved DNA methyltransferase that mediates sporulation and pathogenesis

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    Clostridioides (formerly Clostridium) difficile is a leading cause of healthcare-associated infections. Although considerable progress has been made in the understanding of its genome, the epigenome of C. difficile and its functional impact has not been systematically explored. Here, we perform a comprehensive DNA methylome analysis of C. difficile using 36 human isolates and observe a high level of epigenomic diversity. We discovered an orphan DNA methyltransferase with a well-defined specificity, the corresponding gene of which is highly conserved across our dataset and in all of the approximately 300 global C. difficile genomes examined. Inactivation of the methyltransferase gene negatively impacts sporulation, a key step in C. difficile disease transmission, and these results are consistently supported by multiomics data, genetic experiments and a mouse colonization model. Further experimental and transcriptomic analyses suggest that epigenetic regulation is associated with cell length, biofilm formation and host colonization. These findings provide a unique epigenetic dimension to characterize medically relevant biological processes in this important pathogen. This study also provides a set of methods for comparative epigenomics and integrative analysis, which we expect to be broadly applicable to bacterial epigenomic studies

    New insights into the genetic etiology of Alzheimer's disease and related dementias

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    Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

    Effect of priming interval on reactogenicity, peak immunological response, and waning after homologous and heterologous COVID-19 vaccine schedules: exploratory analyses of Com-COV, a randomised control trial

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    Background: Priming COVID-19 vaccine schedules have been deployed at variable intervals globally, which might influence immune persistence and the relative importance of third-dose booster programmes. Here, we report exploratory analyses from the Com-COV trial, assessing the effect of 4-week versus 12-week priming intervals on reactogenicity and the persistence of immune response up to 6 months after homologous and heterologous priming schedules using the vaccines BNT162b2 (tozinameran, Pfizer/BioNTech) and ChAdOx1 nCoV-19 (AstraZeneca). Methods: Com-COV was a participant-masked, randomised immunogenicity trial. For these exploratory analyses, we used the trial's general cohort, in which adults aged 50 years or older were randomly assigned to four homologous and four heterologous vaccine schedules using BNT162b2 and ChAdOx1 nCoV-19 with 4-week or 12-week priming intervals (eight groups in total). Immunogenicity analyses were done on the intention-to-treat (ITT) population, comprising participants with no evidence of SARS-CoV-2 infection at baseline or for the trial duration, to assess the effect of priming interval on humoral and cellular immune response 28 days and 6 months post-second dose, in addition to the effects on reactogenicity and safety. The Com-COV trial is registered with the ISRCTN registry, 69254139 (EudraCT 2020–005085–33). Findings: Between Feb 11 and 26, 2021, 730 participants were randomly assigned in the general cohort, with 77–89 per group in the ITT analysis. At 28 days and 6 months post-second dose, the geometric mean concentration of anti-SARS-CoV-2 spike IgG was significantly higher in the 12-week interval groups than in the 4-week groups for homologous schedules. In heterologous schedule groups, we observed a significant difference between intervals only for the BNT162b2–ChAdOx1 nCoV-19 group at 28 days. Pseudotyped virus neutralisation titres were significantly higher in all 12-week interval groups versus 4-week groups, 28 days post-second dose, with geometric mean ratios of 1·4 (95% CI 1·1–1·8) for homologous BNT162b2, 1·5 (1·2–1·9) for ChAdOx1 nCoV-19–BNT162b2, 1·6 (1·3–2·1) for BNT162b2–ChAdOx1 nCoV-19, and 2·4 (1·7–3·2) for homologous ChAdOx1 nCoV-19. At 6 months post-second dose, anti-spike IgG geometric mean concentrations fell to 0·17–0·24 of the 28-day post-second dose value across all eight study groups, with only homologous BNT162b2 showing a slightly slower decay for the 12-week versus 4-week interval in the adjusted analysis. The rank order of schedules by humoral response was unaffected by interval, with homologous BNT162b2 remaining the most immunogenic by antibody response. T-cell responses were reduced in all 12-week priming intervals compared with their 4-week counterparts. 12-week schedules for homologous BNT162b2 and ChAdOx1 nCoV-19–BNT162b2 were up to 80% less reactogenic than 4-week schedules. Interpretation: These data support flexibility in priming interval in all studied COVID-19 vaccine schedules. Longer priming intervals might result in lower reactogenicity in schedules with BNT162b2 as a second dose and higher humoral immunogenicity in homologous schedules, but overall lower T-cell responses across all schedules. Future vaccines using these novel platforms might benefit from schedules with long intervals. Funding: UK Vaccine Taskforce and National Institute for Health and Care Research

    Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

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    The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine
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