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The Pancreatic Expression Database (PED, http://www.pancreasexpression.org) continues to be a major resource for mining pancreatic -omics data a decade after its initial release. Here, we present recent updates to PED and describe its evolution into a comprehensive resource for extracting, analysing and integrating publicly available multi-omics datasets. A new analytical module has been implemented to run in parallel with the existing literature mining functions. This analytical module has been created using rich data content derived from pancreas-related specimens available through the major data repositories (GEO, ArrayExpress) and international initiatives (TCGA, GENIE, CCLE). Researchers have access to a host of functions to tailor analyses to meet their needs. Results are presented using interactive graphics that allow the molecular data to be visualized in a user-friendly manner. Furthermore, researchers are provided with the means to superimpose layers of molecular information to gain greater insight into alterations and the relationships between them. The literature-mining module has been improved with a redesigned web appearance, restructured query platforms and updated annotations. These updates to PED are in preparation for its integration with the Pancreatic Cancer Research Fund Tissue Bank (PCRFTB), a vital resource of pancreas cancer tissue for researchers to support and promote cutting-edge research., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The Pancreatic Expression Database (PED, http://www.pancreasexpression.org) is the only device currently available for mining of pancreatic cancer literature data. It brings together the largest collection of multidimensional pancreatic data from the literature including genomic, proteomic, microRNA, methylomic and transcriptomic profiles. PED allows the user to ask specific questions on the observed levels of deregulation among a broad range of specimen/experimental types including healthy/patient tissue and body fluid specimens, cell lines and murine models as well as related treatments/drugs data. Here we provide an update to PED, which has been previously featured in the Database issue of this journal. Briefly, PED data content has been substantially increased and expanded to cover methylomics studies. We introduced an extensive controlled vocabulary that records specific details on the samples and added data from large-scale meta-analysis studies. The web interface has been improved/redesigned with a quick search option to rapidly extract information about a gene/protein of interest and an upload option allowing users to add their own data to PED. We added a user guide and implemented integrated graphical tools to overlay and visualize retrieved information. Interoperability with biomart-compatible data sets was significantly improved to allow integrative queries with pancreatic cancer data.

The Pancreatic Expression database (PED, http://www.pancreasexpression.org) has established itself as the main repository for pancreatic-derived -omics data. For the past 3 years, its data content and access have increased substantially. Here we describe several of its new and improved features, such as data content, which now includes over 60,000 measurements derived from transcriptomics, proteomics, genomics and miRNA profiles from various pancreas-centred reports on a broad range of specimen and experimental types. We also illustrate the capabilities of its interface, which allows integrative queries that can combine PED data with a growing number of biological resources such as NCBI, Ensembl, UniProt and Reactome. Thus, PED is capable of retrieving and integrating different types of -omics, annotations and clinical data. We also focus on the importance of data sharing and interoperability in the cancer field, and the integration of PED into the International Cancer Genome Consortium (ICGC) data portal.

Background and Aims: We have recently constructed the pancreatic expression database (http://www.pancreasexpression.org/). It is a freely available web-based tool that currently holds 7,636 gene expression measurements from various pancreatic cancer types, precursor lesions (PanINs) and chronic pancreatitis. It was constructed with the aim of enabling mining of the large body of publicly available genomic/proteomic data in the pancreatic field and thus furthering our understanding of the complex basis of pancreatic cancer within the realm of systems biology., Methods and Results: Annotated, integrated pancreatic datasets were stored in a data management system based on the BioMart technology alongside public annotations. Within our first database report we incorporated 32 datasets and have also included several easy examples of its usage. We now provide further, more sophisticated query types that we hope will serve as a prototype for possible questions of interest that might be addressed in the pancreatic biology community., Conclusion: The systematic understanding of the pathobiology underlying pancreatic cancer initiation and progression is a prerequisite for devising timely diagnostic tools and successful drug target discovery. As the database is only as comprehensive as its contents and as user-friendly as its query engine, we invite the pancreatic biology community for feedback and submission of further datasets., (Copyright 2009 S. Karger AG, Basel.)

Background: Pancreatic cancer is the 5th leading cause of cancer death in both males and females. In recent years, a wealth of gene and protein expression studies have been published broadening our understanding of pancreatic cancer biology. Due to the explosive growth in publicly available data from multiple different sources it is becoming increasingly difficult for individual researchers to integrate these into their current research programmes. The Pancreatic Expression database, a generic web-based system, is aiming to close this gap by providing the research community with an open access tool, not only to mine currently available pancreatic cancer data sets but also to include their own data in the database., Description: Currently, the database holds 32 datasets comprising 7636 gene expression measurements extracted from 20 different published gene or protein expression studies from various pancreatic cancer types, pancreatic precursor lesions (PanINs) and chronic pancreatitis. The pancreatic data are stored in a data management system based on the BioMart technology alongside the human genome gene and protein annotations, sequence, homologue, SNP and antibody data. Interrogation of the database can be achieved through both a web-based query interface and through web services using combined criteria from pancreatic (disease stages, regulation, differential expression, expression, platform technology, publication) and/or public data (antibodies, genomic region, gene-related accessions, ontology, expression patterns, multi-species comparisons, protein data, SNPs). Thus, our database enables connections between otherwise disparate data sources and allows relatively simple navigation between all data types and annotations., Conclusion: The database structure and content provides a powerful and high-speed data-mining tool for cancer research. It can be used for target discovery i.e. of biomarkers from body fluids, identification and analysis of genes associated with the progression of cancer, cross-platform meta-analysis, SNP selection for pancreatic cancer association studies, cancer gene promoter analysis as well as mining cancer ontology information. The data model is generic and can be easily extended and applied to other types of cancer. The database is available online with no restrictions for the scientific community at http://www.pancreasexpression.org/.

Background: More than 700 million people worldwide suffer from diseases of the pancreas, such as diabetes, pancreatitis and pancreatic cancer. Often dysregulation of potassium (K+) channels, co-transporters and pumps can promote development and progression of many types of these diseases. The role of K+ transport system in pancreatic cell homeostasis and disease development remains largely unexplored. Potassium isotope analysis (δ41K), however, might have the potential to detect minute changes in metabolic processes relevant for pancreatic diseases. Methods: We assessed urinary K isotope composition in a case-control study by measuring K concentrations and d41K in spot urines collected from patients diagnosed with pancreatic cancer (n=18), other pancreas-related diseases (n=14) and compared those data to healthy controls (n=16). Results: Our results show that urinary K+ levels for patients with diseased pancreas (benign and pancreatic cancer) are significantly lower than the healthy controls. For δ41K, the values tend to be higher for individuals with pancreatic cancer (mean δ41K = -0.58 ± 0.33‰) than for healthy individuals (mean δ41K= -0.78 ± 0.19‰) but the difference is not significant (p=0.08). For diabetics, urinary K+ levels are significantly lower (p=0.03) and δ41K is significantly higher (p=0.009) than for the healthy controls. These results suggest that urinary K+ levels and K isotopes can help identify K disturbances related to diabetes, an associated factors of all-cause mortality for diabetics. Conclusion: Although the K isotope results should be considered exploratory and hypothesis-generating and future studies should focus on larger sample size and δ41K analysis of other K-disrupting diseases (e.g., chronic kidney disease), our data hold great promise for K isotopes as disease marker. [ABSTRACT FROM AUTHOR]

Peanut-like 1 (PNUTL1) is a septin gene which is expressed at high levels in human brain. There it plays a role in the process of membrane fusion during exocytosis by interacting with syntaxin and synaptophysin. As the secretory apparatus of pancreatic islet cells closely resembles that of neurons, we decided to study the expression of PNUTL1 in the human endocrine pancreas, both in normal islets and in pancreatic endocrine tumors (PETs). Normal pancreatic tissue, purified islets, 11 PETs and two cell lines were used to evaluate the presence of PNUTL1 by RT-PCR and Western blot. The expression of the PNUTL1 protein was also evaluated by immunohistochemistry on normal pancreas, additional 26 PETs, eight pancreatic adenocarcinomas, one mixed endocrine-exocrine pancreatic neoplasm, a specimen of solid papillary pseudomucinous tumor, an adult islet cell hyperplasia and a case of neonatal nesidioblastosis. In addition, a tissue array (LandMark High Density Cancer Tissue MicroArray) comprising 280 various tumor and matched normal specimens was utilized. In PETs, the expression of pancreatic hormones, chromogranin-A, synaptophysin and Ki-67 were also evaluated. In the normal pancreas PNUTL1 expression is almost exclusively confined to the islet cells, weak expression was occasionally seen in some acinar cells, while immunoreactivity was completely absent in the ductal epithelia. PNUTL1 expression is maintained at similar high levels in hyperplastic and neoplastic islet cells, but this did not correlate with any of the clinicopathological data nor with proliferation status in PETs. Weak immunoreactivity was also noted in a proportion of exocrine neoplasms. Our findings describe for the first time the high expression levels of PNUTL1 in human pancreatic endocrine cells that suggests a similar role of this protein in islet cells to that demonstrated in neuronal tissues, and warrants further functional studies of this protein. Copyright © 2005 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Gene expression studies were undertaken in normal pancreas and pancreatic adenocarcinomas to determine new candidate genes that can potentially be used as markers of the disease. The characteristic desmoplastic stromal reaction of pancreatic adenocarcinoma greatly hampers expression studies in this tumour type, and usually necessitates time-consuming tissue microdissection for enrichment of the tumour cell population. We show that fine needle aspiration of cancer provides a fast and efficient way of obtaining samples highly enriched in tumour cells with sufficient yields of RNA. Using Atlas cancer cDNA arrays with 588 cancer-related genes, we describe gene expression profiles of normal pancreas, bulk pancreatic tumour tissues and pancreatic tumour aspirates containing more than 95% tumour cells. Analysis of bulk tissue specimens revealed differentially expressed genes belonging predominantly to the stromal component of the tumour. This contrasted with the results obtained from tumour-cell enriched samples. Several genes already described in pancreatic cancer (caspase 8, TIMP1, CD9, IL-13) were also differentially expressed in our study. Furthermore, we found dysregulated expression of genes not previously associated with pancreatic adenocarcinoma, such as Rac 1, GLG1, NEDD5, RPL-13a, RPS9 and members of the Wnt5A gene family. In summary, we present a panel of genes newly identified in the pathogenesis of pancreatic adenocarcinoma and demonstrate that fine needle aspirates of the tumour mass are a convenient source of material for gene expression studies in tumours accompanied by desmoplastic reactions. Oncogene (2001) 20, 7437–7446. [ABSTRACT FROM AUTHOR]