For much of the last century, our knowledge regarding the pancreas in type 1 and type 2 diabetes was largely derived from autopsy studies of individuals with these disorders or investigations ...utilising rodent models of either disease. While many important insights emanated from these efforts, the mode for investigation has increasingly seen change due to the availability of transplant-quality organ-donor tissues, improvements in pancreatic imaging, advances in metabolic assessments of living patients, genetic analyses, technological advances for laboratory investigation and more. As a result, many long-standing notions regarding the role for and the changes that occur in the pancreas in individuals with these disorders have come under question, while, at the same time, new issues (e.g., beta cell persistence, disease heterogeneity, exocrine contributions) have arisen. In this article, we will consider the vital role of the pancreas in human health and physiology, including discussion of its anatomical features and dual (exocrine and endocrine) functions. Specifically, we convey changes that occur in the pancreas of those with either type 1 or type 2 diabetes, with careful attention to the facets that may contribute to the pathogenesis of either disorder. Finally, we discuss the emerging unknowns with the belief that understanding the role of the pancreas in type 1 and type 2 diabetes will lead to improvements in disease diagnosis, understanding of disease heterogeneity and optimisation of treatments at a personalised level.
Graphical abstract
Autoimmune β-cell destruction leads to type 1 diabetes, but the pathophysiological mechanisms remain unclear. To help address this void, we created an open-access online repository, unprecedented in ...its size, composed of large-scale electron microscopy images ('nanotomy') of human pancreas tissue obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD; www.nanotomy.org). Nanotomy allows analyses of complete donor islets with up to macromolecular resolution. Anomalies we found in type 1 diabetes included (i) an increase of 'intermediate cells' containing granules resembling those of exocrine zymogen and endocrine hormone secreting cells; and (ii) elevated presence of innate immune cells. These are our first results of mining the database and support recent findings that suggest that type 1 diabetes includes abnormalities in the exocrine pancreas that may induce endocrine cellular stress as a trigger for autoimmunity.
The culture of live pancreatic tissue slices is a powerful tool for the interrogation of physiology and pathology in an in vitro setting that retains near-intact cytoarchitecture. However, current ...culture conditions for human pancreatic slices (HPSs) have only been tested for short-term applications, which are not permissive for the long-term, longitudinal study of pancreatic endocrine regeneration. Using a culture system designed to mimic the physiological oxygenation of the pancreas, we demonstrate high viability and preserved endocrine and exocrine function in HPS for at least 10 days after sectioning. This extended lifespan allowed us to dynamically lineage trace and quantify the formation of insulin-producing cells in HPS from both non-diabetic and type 2 diabetic donors. This technology is expected to be of great impact for the conduct of real-time regeneration/developmental studies in the human pancreas.
RRM1 encodes the regulatory subunit of ribonucleotide reductase and is a molecular target of gemcitabine. Previous studies showed increased RRM1 expression on continuous exposure of cell lines to ...gemcitabine and suggested improved survival for patients with low as opposed to high tumoral RRM1 expression when treated with gemcitabine-containing chemotherapy. However, the principal hypothesis that intratumoral levels of gene expression are associated with disease response has not been addressed.
We constructed genetically modified lung cancer cell lines with increased and decreased RRM1 expression to investigate the in vitro 50% inhibitory concentration (IC50) for gemcitabine, cisplatin, and carboplatin. A prospective phase II clinical trial in patients with locally advanced non-small-cell lung cancer was conducted with pretreatment tumor collection for determination of RRM1 and ERCC1 expression by real-time reverse transcriptase polymerase chain reaction. The levels of gene expression were correlated with tumor response after two cycles of gemcitabine and carboplatin.
In cell lines with a genetically engineered 15-fold RRM1 expression range, the gemcitabine IC50 had a 100-fold range, and the cisplatin and carboplatin IC50 had a two-fold range. They were highest in constructs with high RRM1 expression. In the prospective clinical trial, RRM1 expression was significantly (P = .002) and inversely correlated (r = -0.498) with disease response. ERCC1 expression showed a similar trend (P = .099).
The results strongly suggest that tumoral RRM1 expression is a major predictor of disease response to gemcitabine/platinum chemotherapy. ERCC1 expression is predictive of response albeit to a lesser degree.
Type 2 diabetes mellitus (T2D) is a chronic age-related disorder characterized by hyperglycemia due to the failure of pancreatic beta cells to compensate for increased insulin demand. Despite decades ...of research, the pathogenic mechanisms underlying T2D remain poorly defined. Here, we use imaging mass cytometry (IMC) with a panel of 34 antibodies to simultaneously quantify markers of pancreatic exocrine, islet, and immune cells and stromal components. We analyze over 2 million cells from 16 pancreata obtained from donors with T2D and 13 pancreata from age-similar non-diabetic controls. In the T2D pancreata, we observe significant alterations in islet architecture, endocrine cell composition, and immune cell constituents. Thus, both HLA-DR-positive CD8 T cells and macrophages are enriched intra-islet in the T2D pancreas. These efforts demonstrate the utility of IMC for investigating complex events at the cellular level in order to provide insights into the pathophysiology of T2D.
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•Imaging mass cytometry profiles of the T2D pancreas with 34 antibodies•There is a relative loss of beta and gain of alpha cells in the T2D pancreas•Advanced neighborhood analysis finds increased macrophage/beta cell contacts in T2D•Activated HLA-DR-positive CD8 T cells are enriched in the T2D islet
Wu et al. use an advanced imaging technique to profile two million cells within the pancreas of healthy people and those with T2D. They identify changes in tissue architecture and immune cell infiltration in the diabetic pancreas that help our understanding of this major health problem.
Aims/hypothesis
Normal cellular prion protein (PrP
C
) is a conserved mammalian glycoprotein found on the outer plasma membrane leaflet through a glycophosphatidylinositol anchor. Although PrP
C
is ...expressed by a wide range of tissues throughout the body, the complete repertoire of its functions has not been fully determined. The misfolded pathogenic isoform PrP
Sc
(the scrapie form of PrP) is a causative agent of neurodegenerative prion diseases. The aim of this study is to evaluate PrP
C
localisation, expression and trafficking in pancreases from organ donors with and without type 1 diabetes and to infer PrP
C
function through studies on interacting protein partners.
Methods
In order to evaluate localisation and trafficking of PrP
C
in the human pancreas, 12 non-diabetic, 12 type 1 diabetic and 12 autoantibody-positive organ donor tissue samples were analysed using immunofluorescence analysis. Furthermore, total RNA was isolated from 29 non-diabetic, 29 type 1 diabetic and 24 autoantibody-positive donors to estimate PrP
C
expression in the human pancreas. Additionally, we performed PrP
C
-specific immunoblot analysis on total pancreatic protein from non-diabetic and type 1 diabetic organ donors to test whether changes in PrP
C
mRNA levels leads to a concomitant increase in PrP
C
protein levels in human pancreases.
Results
In non-diabetic and type 1 diabetic pancreases (the latter displaying both insulin-positive INS(+) and -negative INS(−) islets), we found PrP
C
in islets co-registering with beta cells in all INS(+) islets and, strikingly, unexpected activation of PrP
C
in alpha cells within diabetic INS(−) islets. We found PrP
C
localised to the plasma membrane and endoplasmic reticulum (ER) but not the Golgi, defining two cellular pools and an unconventional protein trafficking mechanism bypassing the Golgi. We demonstrate PrP
C
co-registration with established protein partners, neural cell adhesion molecule 1 (NCAM1) and stress-inducible phosphoprotein 1 (STI1; encoded by
STIP1
) on the plasma membrane and ER, respectively, linking PrP
C
function with cyto-protection, signalling, differentiation and morphogenesis. We demonstrate that both
PRNP
(encoding PrP
C
) and
STIP1
gene expression are dramatically altered in type 1 diabetic and autoantibody-positive pancreases.
Conclusions/interpretation
As the first study to address PrP
C
expression in non-diabetic and type 1 diabetic human pancreas, we provide new insights for PrP
C
in the pathogenesis of type 1 diabetes. We evaluated the cell-type specific expression of PrP
C
in the human pancreas and discovered possible connections with potential interacting proteins that we speculate might address mechanisms relevant to the role of PrP
C
in the human pancreas.
Graphical abstract
Currently, a blood test for lung cancer does not exist. Serum biomarkers that could aid clinicians in making case management decisions would be enormously valuable. We used two proteomic platforms ...and a literature search to select candidate serum markers for the diagnosis of lung cancer.
We initially assayed six serum proteins, four discovered by proteomics and two previously known to be cancer associated, on a training set of sera from 100 patients (50 with a new diagnosis of lung cancer and 50 age- and sex-matched controls). Classification and Regression Tree (CART) analysis selected a panel of four markers that most efficiently predicted which patients had lung cancer. An independent, blinded validation set of sera from 97 patients (49 lung cancer patients and 48 matched controls) determined the accuracy of the four markers to predict which patients had lung cancer.
Four serum proteins-carcinoembryonic antigen, retinol binding protein, alpha1-antitrypsin, and squamous cell carcinoma antigen-were collectively found to correctly classify the majority of lung cancer and control patients in the training set (sensitivity, 89.3%; specificity, 84.7%). These markers also accurately classified patients in the independent validation set (sensitivity, 77.8%; specificity, 75.4%). Remarkably, 90% of patients who fell into any one of three groupings in the CART analysis had lung cancer.
This panel of four serum proteins is valuable in suggesting the diagnosis of lung cancer. These data may be useful for treating patients with an indeterminate pulmonary lesion, and potentially in predicting individuals at high risk for lung cancer.
In type 1 diabetes (T1D), autoimmune destruction of pancreatic β cells leads to insulin deficiency and loss of glycemic control. However, knowledge about human pancreas pathophysiology in T1D remains ...incomplete. To address this limitation, we established a pancreas tissue slice platform of donor organs with and without diabetes, facilitating the first live cell studies of human pancreas in T1D pathogenesis to our knowledge. We show that pancreas tissue slices from organ donors allow thorough assessment of processes critical for disease development, including insulin secretion, β cell physiology, endocrine cell morphology, and immune infiltration within the same donor organ. Using this approach, we compared detailed pathophysiological profiles for 4 pancreata from donors with T1D with 19 nondiabetic control donors. We demonstrate that β cell loss, β cell dysfunction, alterations of β cell physiology, and islet infiltration contributed differently to individual cases of T1D, allowing insight into pathophysiology and heterogeneity of T1D pathogenesis. Thus, our study demonstrates that organ donor pancreas tissue slices represent a promising and potentially novel approach in the search for successful prevention and reversal strategies of T1D.
Human tissue phenotyping generates complex spatial information from numerous imaging modalities, yet images typically become static figures for publication, and original data and metadata are rarely ...available. While comprehensive image maps exist for some organs, most resources have limited support for multiplexed imaging or have non-intuitive user interfaces. Therefore, we built a Pancreatlas resource that integrates several technologies into a unique interface, allowing users to access richly annotated web pages, drill down to individual images, and deeply explore data online. The current version of Pancreatlas contains over 800 unique images acquired by whole-slide scanning, confocal microscopy, and imaging mass cytometry, and is available at https://www.pancreatlas.org. To create this human pancreas-specific biological imaging resource, we developed a React-based web application and Python-based application programming interface, collectively called Flexible Framework for Integrating and Navigating Data (FFIND), which can be adapted beyond Pancreatlas to meet countless imaging or other structured data-management needs.
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•Human organ phenotyping databases benefit from intuitive user interfaces•Pancreatlas resource enables exploration of bioimaging data from human pancreas•The front-end framework of Pancreatlas, FFIND, is modular and easily adaptable•FFIND provides structured data-exploration capabilities across countless domains
Scientists need cost-effective yet fully featured database solutions that facilitate large dataset sharing in a structured and easily digestible manner. Flexible Framework for Integrating and Navigating Data (FFIND) is a data-agnostic web application that is designed to easily connect existing databases with data-browsing clients. We used FFIND to build Pancreatlas, an online imaging resource containing datasets linking imaging data with clinical data to facilitate advances in the understanding of diabetes, pancreatitis, and pancreatic cancer. FFIND architecture, which is available as open-source software, can be easily adapted to meet other field- or project-specific needs; we hope it will help data scientists reach a broader audience by reducing the development life cycle and providing familiar interactivity in communicating data and underlying stories.
Human tissue phenotyping generates complex imaging data that is difficult to share in publications, and many organ-specific databases lack intuitive user interfaces or have limited support for multiplexed imaging. Therefore, we built a Pancreatlas resource (https://www.pancreatlas.org) that integrates several technologies into a unique interface, allowing users to access richly annotated web pages. To create this imaging resource, we developed a data-agnostic, React-based web application and Python-based application programming interface, collectively called Flexible Framework for Integrating and Navigating Data (FFIND; https://github.com/Powers-Brissova-Research-Group/FFIND).
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