Understanding the physiology of the pancreas and pathology that occurs during diabetes requires knowing transcriptional patterns driving biological activity within the functional structures of the tissue. Previous technologies have not enabled spatially resolved high plex profiling to elucidate these biological pathways. Using the unique ability of GeoMx® Digital Spatial Profiler to resolve functional units within FFPE tissue in situ, we provide whole transcriptome expression data from islets, acini, and ducts from four pancreata of nondiabetes patients.
On average, 6000-8000 genes were detected from functional groups within each histological structure. Data were validated against the independent Human Protein Atlas, with ∼90% concordance between RNA expression and known protein localization. Deconvolution based on single-cell RNASeq enabled calculation of the proportion of distinct cell types within each structure, confirming cell composition. For example, while ductal components consist of small islands punctuating the acini, over 3000 genes were identified to be highly specific to each structure (FDR < 0.05) , and enriched for pathways related to focal adhesion, ECM structure, and diabetic disease processes. Within islets, we identified >300 genes with differences between α- and β-cells (FDR < 0.2) . Functional characterization confirmed enrichment of insulin biosynthesis and secretion pathways, with genes such as insulin, glucagon, and IAPP expression captured accurately with a single assay. Determination of expression in four individual pancreas samples identified variation between tissues, which may be central to health and disease processes.
In conclusion, whole transcriptome data for spatial gene expression profiles of structures of the non-diseased pancreas are publicly available and can be used as standards to inform future profiling studies in normal and diseased tissue.
FOR RESEARCH USE ONLY. Not for use in diagnostic procedures.
W.Yang: None. M.F.Hogan: Employee; NanoString. Y.Liang: None. J.M.Beechem: None.