Project Abstracts - CBDS

Pedro Herrera, PhD, Investigator, University of Geneva
Bernd Bodenmiller, PhD, Investigator, University of Zurich
Harry Nick, PhD, co-Investigator, University of Florida
Fabrizio Thorel, PhD, co-Investigator, University of Geneva

Start Date: September 24, 2015a
End Date: May 31, 2020

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Abstract

Type 1 diabetes (T1D) is a very serious autoimmune disease resulting from self-destruction of the insulin producing pancreatic b cells.  A disorder without a cure, T1D has seen a pronounced increase in its frequency over the last half-century at a global level.  Despite advances in disease management, it remains a disorder that instills major morbidity (e.g., blindness, kidney and heart disease, risk for hypoglycemia) and mortality challenges on those afflicted. We portend a major reason that the community of T1D researchers has seen limited progress, over many decades, in attempts to identify therapies capable of preventing and/or reversing the disease is tied to a collective lack in understanding the mechanisms of disease development in humans; especially in terms of knowing the specific contributions of islet endocrine cells and the immune system to the disorder, including and especially their interplay with each other.  This application proposes to test the hypothesis that a highly innovative technique known as High Multiplexed Imaging (HMI), that when applied to rare but informative pancreatic tissues from those with or at varying levels of risk for T1D as well as control tissues, will unlock research mysteries surrounding the disorder that have existed for many years. That hypothesis will be tested in this proposal by the performance of two interactive specific aims, the first being to establish HMI as a tool for pancreatic tissue analysis, while the second involves characterization of islet and immune system cells in T1D by HMI using validated antibodies.  Importantly, to achieve said goals with maximal probability for success, we have formed a team well poised to address the lofty challenges associated with our proposal.  This proposal combines the efforts of three well-established investigators that developed HMI (Bodenmiller), have provided crucial information regarding islet cell plasticity (Herrera), and helped define the natural history of T1D in both humans and the NOD mouse model of the disease (Atkinson). Our team is committed to not only generate information vital for our own proposed project goals but in addition, to generating data for the entire Human Islet Research Network (HIRN) collective. In sum, we firmly believe this study will result in a technological means for providing novel information regarding the pathogenesis of T1D; knowledge that should prove beneficial for attempts seeking to prevent and/or reverse the disorder.

Publications

• DNA-barcoded signal amplification for imaging mass cytometry enables sensitive and highly multiplexed tissue imaging
• Cancer-associated fibroblast classification in single-cell and spatial proteomics data
• cytoviewer: an R/Bioconductor package for interactive visualization and exploration of highly multiplexed imaging data
• A genomic data archive from the Network for Pancreatic Organ donors with Diabetes
• Substance Use Affects Type 1 Diabetes Pancreas Pathology: Implications for Future Studies
• Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd
• Monogenic Diabetes and Integrated Stress Response Genes Display Altered Gene Expression in Type 1 Diabetes
• Altered cellular localisation and expression, together with unconventional protein trafficking, of prion protein, PrP(C), in type 1 diabetes
• Islet sympathetic innervation and islet neuropathology in patients with type 1 diabetes
• Cytomapper: an R/bioconductor package for visualisation of highly multiplexed imaging data
• A quantitative analysis of the interplay of environment, neighborhood, and cell state in 3D spheroids
• Image-based machine learning algorithms for disease characterization in the human type 1 diabetes pancreas
• Mechanistic Model of Signaling Dynamics Across an Epithelial Mesenchymal Transition
• Expression of SARS-CoV-2 Entry Factors in the Pancreas of Normal Organ Donors and Individuals with COVID-19
• Organisation of the human pancreas in health and in diabetes
• Large-scale electron microscopy database for human type 1 diabetes
• Profiling cell signaling networks at single-cell resolution
• The single-cell pathology landscape of breast cancer
• Uncovering axes of variation among single-cell cancer specimens
• Modeling Cell-Cell Interactions from Spatial Molecular Data with Spatial Variance Component Analysis
• Analysis of the Human Kinome and Phosphatome by Mass Cytometry Reveals Overexpression-Induced Effects on Cancer-Related Signaling
• The Influence of Type 2 Diabetes-Associated Factors on Type 1 Diabetes
• In-Depth Characterization of Monocyte-Derived Macrophages using a Mass Cytometry-Based Phagocytosis Assay
• Diabetes relief in mice by glucose-sensing insulin-secreting human α-cells
• Multiplexed In Situ Imaging Mass Cytometry Analysis of the Human Endocrine Pancreas and Immune System in Type 1 Diabetes
• A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry
• Pancreatic islet-autonomous insulin and smoothened-mediated signalling modulate identity changes of glucagon(+) α-cells
• High-Dimensional Phenotyping Identifies Age-Emergent Cells in Human Mammary Epithelia
• Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry
• β Cell-Specific Deletion of the IL-1 Receptor Antagonist Impairs β Cell Proliferation and Insulin Secretion.
• CellCycleTRACER accounts for cell cycle and volume in mass cytometry data
• α-cell glucokinase suppresses glucose-regulated glucagon secretion
• Simultaneous Multiplexed Imaging of mRNA and Proteins with Subcellular Resolution in Breast Cancer Tissue Samples by Mass Cytometry
• Persistence of Pancreatic Insulin mRNA Expression and Proinsulin Protein in Type 1 Diabetes Pancreata