PLoS ONE: Examination of Apoptosis Signaling in Pancreatic Cancer by Computational Signal Transduction Analysis

Examination of Apoptosis Signaling in Pancreatic Cancer by Computational Signal Transduction Analysis

Felix Rückert1*, Gihan Dawelbait2, Christof Winter2, Arndt Hartmann3, Axel Denz1, Ole Ammerpohl4, Michael Schroeder2, Hans Konrad Schackert5, Bence Sipos6, Günter Klöppel6, Holger Kalthoff4, Hans-Detlev Saeger1, Christian Pilarsky1#, Robert Grützmann1#

1 Department of Visceral, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany, 2 Bioinformatics Group, Biotechnological Centre, Technical University Dresden, Dresden, Germany, 3 Department of Pathology, University of Erlangen, Erlangen, Germany, 4 Division of Molecular Oncology, Clinic for General Surgery and Thoracic Surgery, Schleswig-Holstein University Hospitals, Kiel, Germany, 5 Department of Surgical Research, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany, 6 Division of Molecular Oncology, Institute for Experimental Cancer Research, Schleswig-Holstein University Hospitals, Kiel, Germany

Abstract
Background
Pancreatic ductal adenocarcinoma (PDAC) remains an important cause of cancer death. Changes in apoptosis signaling in pancreatic cancer result in chemotherapy resistance and aggressive growth and metastasizing. The aim of this study was to characterize the apoptosis pathway in pancreatic cancer computationally by evaluation of experimental data from high-throughput technologies and public data bases. Therefore, gene expression analysis of microdissected pancreatic tumor tissue was implemented in a model of the apoptosis pathway obtained by computational protein interaction prediction.

Methodology/Principal Findings
Apoptosis pathway related genes were assembled from electronic databases. To assess expression of these genes we constructed a virtual subarray from a whole genome analysis from microdissected native tumor tissue. To obtain a model of the apoptosis pathway, interactions of members of the apoptosis pathway were analysed using public databases and computational prediction of protein interactions. Gene expression data were implemented in the apoptosis pathway model. 19 genes were found differentially expressed and 12 genes had an already known pathophysiological role in PDAC, such as Survivin/BIRC5, BNIP3 and TNF-R1. Furthermore we validated differential expression of IL1R2 and Livin/BIRC7 by RT-PCR and immunohistochemistry. Implementation of the gene expression data in the apoptosis pathway map suggested two higher level defects of the pathway at the level of cell death receptors and within the intrinsic signaling cascade consistent with references on apoptosis in PDAC. Protein interaction prediction further showed possible new interactions between the single pathway members, which demonstrate the complexity of the apoptosis pathway.

Conclusions/Significance
Our data shows that by computational evaluation of public accessible data an acceptable virtual image of the apoptosis pathway might be given. By this approach we could identify two higher level defects of the apoptosis pathway in PDAC. We could further for the first time identify IL1R2 as possible candidate gene in PDAC.

Citation: Rückert F, Dawelbait G, Winter C, Hartmann A, Denz A, et al. (2010) Examination of Apoptosis Signaling in Pancreatic Cancer by Computational Signal Transduction Analysis. PLoS ONE 5(8): e12243. doi:10.1371/journal.pone.0012243

Editor: Syed A. Aziz, Health Canada, Canada


Received: June 25, 2010; Accepted: July 20, 2010; Published: August 19, 2010

Copyright: © 2010 Rückert et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This study was supported by Deutsche Krebshilfe and the MedDrive38 program of the medical faculty of Technische Universität Dresden. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

* E-mail: Felix.Rueckert@uniklinikum-dresden.de

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PLoS ONE: Examination of Apoptosis Signaling in Pancreatic Cancer by Computational Signal Transduction Analysis