Despite extensive efforts, understanding of the mechanisms of type 1 diabetes (T1D) development in human patients is collectively lacking, particularly with regard to contributions of islet endocrine cells, the immune system, and their interplay in the disorder’s development. Until recently, these questions have been particularly challenging to address due to technical limitations in the number of analytes that can be simultaneously measured from a single tissue section (i.e., typically four to six markers per section by immunohistochemistry or immunofluorescence). To address this, we have established Highly Multiplexed Imaging (HMI) methodology based on CyTOF mass cytometry to examine human pancreas samples from organ donors with or at varying levels of risk for T1D as well as control donors. We hypothesize that imaging mass cytometry (IMC) characterization of islet and immune cells in the human pancreas will provide novel clues regarding: 1) the impact of pre-T1D and T1D conditions on islet cell phenotypes and 2) the local intra-islet—immune interface throughout disease progression. Specifically, metal isotope-tagged antibodies serve as reporters allowing for unprecedented multi-parameter measurements of single cells, now in the three-dimensional (3D) tissue microenvironment. At the RNA, protein and protein modification level, 30-100 markers expressed by islet and immune cells can be simultaneously analyzed from human pancreas sections at single-cell resolution in 3D across the lifespan to identify “normal” islet development, islet plasticity, cell reprograming, and pathology throughout T1D disease staging. In this study, we are examining: 1) islet endocrine constituents (i.e., alpha, beta, and delta) to potentially identify reprograming cells or to discover novel subsets within these known cell types; 2) cellular signaling networks in endocrine, acinar, and immune cells; and 3) their interactions at various stages throughout the natural history of T1D. Indeed, we have developed the histoCAT 3D reconstruction toolbox to generate 3D data from serial tissue sections with subcellular (i.e., pixel) resolution. This work is revolutionizing our ability to examine the human pancreas in health and disease and has facilitated new avenues of research with new research questions that were previously impossible. We anticipate that we will identify novel pathways disrupted in human T1D, the cellular and molecular networks altered during disease pathogenesis, and new disease-defining/staging characteristics, each of which may represent a potential target for the development of novel therapies aimed at preventing or halting the disease progression.
