A Web-Based Platform for Mining Pancreatic Expression Datasets

Vol. 9, No. 4, 2009

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Molecular Diagnosis of Pancreatic Cancer: Review Series

A Web-Based Platform for Mining Pancreatic Expression Datasets
Claude Chelala^a, Nicholas R. Lemoine^a, Stephan A. Hahn^b, Tatjana Crnogorac-Jurcevic^a

^aCentre for Molecular Oncology, Institute of Cancer and CR-UK Clinical Centre, Barts and The London School of Medicine (QMUL), London, UK;
^bMolecular GI-Oncology (MGO) and Department of Internal Medicine, University of Bochum, Bochum, Germany

Address of Corresponding Author

Pancreatology 2009;9:340-343 (DOI: 10.1159/000212082)

Key Words

Pancreas
Cancer
Pancreatic Expression database
Integration

Abstract

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.

Author Contacts

Claude Chelala
Barts and The London School of Medicine (QMUL)
Charterhouse Square, London EC1M 6BQ (UK)
Tel. +44 20 7014 0474, Fax +44 20 7014 0431
E-Mail Claude.Chelala@cancer.org.uk

Article Information

Published online: May 18, 2009
Number of Print Pages : 4
Number of Figures : 1, Number of Tables : 0, Number of References : 10

Medline Abstract (ID 19451743)

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