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The Proteomic Profile of Pancreatic Cancer Cell Lines Corresponding to Carcinogenesis and Metastasis

Masayo Yamada1,2, Kiyonaga Fujii1,#, Koji Koyama1, Setsuo Hirohashi1, Tadashi Kondo1*
1Proteome Bioinformatics Project, National Cancer Center Research Institute
2Department of Obstetrics and Gynecology, Hyogo Medical College
*Corresponding author: Dr. Tadashi Kondo, Proteome Bioinformatics Project,
National Cancer Center Research Institute, 5-1-1 Tsukiji,
Chuo-ku, Tokyo 104-0045, Japan,
Phone: +81-3-3542-2511 ext.3004;
Fax: +81-3-3547-5298;
E-mail: takondo@ncc.go.jp
#Present address: Kiyonaga Fujii, Department of Structural Biology, Graduate School of Pharmaceutical Sciences, Hokkaido University
Received November 03, 2008; Accepted December 20, 2008; Published January 10, 2009
Citation: Masayo Y, Kiyonaga F, Koji K, Setsuo H, Tadashi K (2009) The Proteomic Profile of Pancreatic Cancer Cell Lines Corresponding to Carcinogenesis and Metastasis. J Proteomics Bioinform 2: 001-018. doi:10.4172/jpb.1000057
Copyright: ©2009 Masayo Y, 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.
Abstract

To investigate the proteomic background of the carcinogenesis and progression of pancreatic cancer, the protein expression profiles of nine well-characterized pancreatic adenocarcinoma cell lines, whose metastatic potential was previously examined in a mouse xenograft model, and two immortalized pancreatic duct cell lines were examined. Two-dimensional difference gel electrophoresis (2D-DIGE) identified 126 protein spots the intensity of which was significantly different between the normal pancreatic duct cell lines and the pancreatic cancer cell lines with different metastatic potential. Mass spectrometric protein identification demonstrated that these protein spots corresponded to 95 unique genes, which included proteins not previously shown to be aberrant in pancreatic cancer. To characterize the observed proteome, LC-MS/MS identified the proteins corresponding to the 1101 protein spots detected by 2D-DIGE. The top-scoring proteins for all 1101 protein spots corresponded to 459 unique proteins. 561 single protein spots included multiple proteins, and 213 unique proteins were repeatedly detected as a top-scoring proteins in multiple protein spots. These results indicate that 2D-DIGE captures a wide spectrum of the proteome, and has the potential to detect the proteins associated with carcinogenesis and progression of pancreatic cancer. The obtained protein expression and identification data have been included in our public database, the Genome Medicine Database of Japan Proteomics.

 
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