81 research outputs found

    Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

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    Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r =-0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r =-0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation

    Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

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    Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

    Intravital imaging technology guides FAK-mediated priming in pancreatic cancer precision medicine according to Merlin status

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    Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic, chemoresistant malignancy and is characterized by a dense, desmoplastic stroma that modulates PDAC progression. Here, we visualized transient manipulation of focal adhesion kinase (FAK), which integrates bidirectional cell-environment signaling, using intravital fluorescence lifetime imaging microscopy of the FAK-based Förster resonance energy transfer biosensor in mouse and patient-derived PDAC models. Parallel real-time quantification of the FUCCI cell cycle reporter guided us to improve PDAC response to standard-of-care chemotherapy at primary and secondary sites. Critically, micropatterned pillar plates and stiffness-tunable matrices were used to pinpoint the contribution of environmental cues to chemosensitization, while fluid flow–induced shear stress assessment, patient-derived matrices, and personalized in vivo models allowed us to deconstruct how FAK inhibition can reduce PDAC spread. Last, stratification of PDAC patient samples via Merlin status revealed a patient subset with poor prognosis that are likely to respond to FAK priming before chemotherapy

    Intravital imaging technology guides FAK-mediated priming in pancreatic cancer precision medicine according to Merlin status

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    Pancreatic ductal adenocarcinoma (PDAC) is a highly metastatic, chemoresistant malignancy and is characterized by a dense, desmoplastic stroma that modulates PDAC progression. Here, we visualized transient manipulation of focal adhesion kinase (FAK), which integrates bidirectional cell-environment signaling, using intravital fluorescence lifetime imaging microscopy of the FAK-based Forster resonance energy transfer biosensor in mouse and patient-derived PDAC models. Parallel real-time quantification of the FUCCI cell cycle reporter guided us to improve PDAC response to standard-of-care chemotherapy at primary and secondary sites. Critically, micro-patterned pillar plates and stiffness-tunable matrices were used to pinpoint the contribution of environmental cues to chemosensitization, while fluid flow-induced shear stress assessment, patient-derived matrices, and personalized in vivo models allowed us to deconstruct how FAK inhibition can reduce PDAC spread. Last, stratification of PDAC patient samples via Merlin status revealed a patient subset with poor prognosis that are likely to respond to FAK priming before chemotherapy

    A multimodal cell census and atlas of the mammalian primary motor cortex

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    ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

    31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

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    Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

    Comparison of GATA3, GCDFP15, Mammaglobin and SOX10 Immunocytochemistry in Aspirates of Metastatic Breast Cancer

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    Introduction: Metastatic cancers are frequently detected on fine-needle aspiration (FNA) cytology, and confirmation of metastatic breast cancer often requires immunocytochemistry. Tissue provisioning for FNA specimens is important. In this study, GATA3, gross cystic disease fluid protein-15 (GCDFP15), mammaglobin (MMG), and SOX10 were performed on cell block preparations from aspirates of histologically confirmed metastatic breast cancers. The diagnostic performance of single markers and combinations of these markers were investigated with the aim to construct a tissue-efficient immunopanel. Methodology: Aspirates of metastatic breast cancer with corresponding histology and biomarker (estrogen receptor (ER), progesterone receptor (PR), HER2 and ki67) profile were retrieved. ER, GATA3, GCDFP15, MMG and SOX10 immunostains were performed on cell block sections and their expressions were assessed and compared. Results: Immunostaining was performed on a total of 115 aspirates. GATA3 showed the highest expression, followed by MMG, GCDFP15 and SOX10. Twenty-three, five and five cases expressed GATA3, MMG and SOX10 only. The five cases expressing SOX10 only were ER negative, and SOX10 expression was negatively associated with ER (p = 0.001), MMG (p = 0.001), GCDFP15 (p = 0.010) and GATA3 (p = 0.002), whereas GATA3 expression showed positive correlation with ER positivity (p &lt; 0.001). MMG and GCDFP15 showed association with high Ki67 (p &lt; 0.05), and no correlations were found with HER2 expression. Conclusion: In this cohort, GATA3 was the most sensitive single marker. The addition of MMG and SOX10 increases the sensitivity for detection of ER positive and ER negative breast cancers, respectively. These findings support the use of a combination of GATA3/MMG/SOX10 for confirmation of metastatic breast cancer

    Andy’s Algorithms: new automated digital image analysis pipelines for FIJI

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    Abstract Quantification of cellular antigens and their interactions via antibody-based detection methods are widely used in scientific research. Accurate high-throughput quantitation of these assays using general image analysis software can be time consuming and challenging, particularly when attempted by users with limited image processing and analysis knowledge. To overcome this, we have designed Andy’s Algorithms, a series of automated image analysis pipelines for FIJI, that permits rapid, accurate and reproducible batch-processing of 3,3′-diaminobenzidine (DAB) immunohistochemistry, proximity ligation assays (PLAs) and other common assays. Andy’s Algorithms incorporates a step-by-step tutorial and optimization pipeline to make batch image analysis simple for the untrained user and adaptable across laboratories. Andy’s algorithms provide a simpler, faster, standardized work flow compared to existing programs, while offering equivalent performance and additional features, in a free to use open-source application of FIJI. Andy’s Algorithms are available at GitHub, publicly accessed at https://github.com/andlaw1841/Andy-s-Algorithm

    PLA Figure 2 Positive Series

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    The second set of images provided is a set of photomicrographs acquired on methanol fixed T47D breast cancer cells and subjected to proximity ligation assays using antibodies to detect interactions between CDK2 and Cyclin E1 and counter stained with ToPro3/DAPI (nuclei) and Phalloidin (cytoplasm
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