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Bioinformatics 2007 23(13):i115-i124; doi:10.1093/bioinformatics/btm188
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Structural templates predict novel protein interactions and targets from pancreas tumour gene expression data

Gihan Dawelbait 1, Christof Winter 1, Yanju Zhang 1, Christian Pilarsky 2, Robert Grützmann 2, Jörg-Christian Heinrich 3 and Michael Schroeder 1,*

1Bioinformatics Group, Biotechnological Centre, TU Dresden, Dresden, Germany, 2Department of Visceral-, Thoracic- and Vascular Surgery, University Hospital, Dresden, Germany and 3RESprotect GmbH, Dresden, Germany

*To whom correspondence should be addressed.


  Abstract

Motivation: Pancreatic ductal adenocarcinoma (PDAC) eludes early detection and is characterized by its aggressiveness and resistance to current therapies. A number of gene expression screens have been carried out to identify genes differentially expressed in cancerous tissue. To identify molecular markers and suitable targets, these genes have been mapped to protein interactions to gain an understanding at systems level.

Results: Here, we take such a network-centric approach to pancreas cancer by re-constructing networks from known interactions and by predicting novel protein interactions from structural templates. The pathways we find to be largely affected are signal transduction, actin cytoskeleton regulation, cell growth and cell communication.

Our analysis indicates that the alteration of the calcium pathway plays an important role in pancreas-specific tumorigenesis. Furthermore, our structural prediction method identifies 40 novel interactions including the tissue factor pathway inhibitor 2 (TFPI2) interacting with the transmembrane protease serine 4 (TMPRSS4). Since TMPRSS4 is involved in metastasis formation, we hypothezise that the upregulation of TMPRSS4 and the downregulation of its predicted inhibitor TFPI2 plays an important role in this process. Moreover, we examine the potential role of BVDU (RP101) as an inhibitor of TMPRSS4. BDVU is known to support apoptosis and prevent the acquisition of chemoresistance. Our results suggest that BVDU might bind to the active site of TMPRSS4, thus reducing its assistance in metastasis.

Contact: ms{at}biotec.tu-dresden.de

Supplementary information: Supplementary data are available atBioinformatics online.


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