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Proteome Expression Database of Lung Adenocarcinoma: a Segment of the Genome Medicine Database of Japan Proteomics

Seiji Kosaihira1, 2, Yukako Tsunehiro1, Koji Tsuta3, Naobumi Tochigi4, Akihiko Gemma2, Setsuo Hirohahsi1, Tadashi Kondo1*
1Proteome Bioinformatics Project, National Cancer Center Research Institute
2Fourth Internal Department of Medicine, Nippon Medical School
3Clinical Laboratory Division, National Cancer Center Hospital
4Pathology Division, National Cancer Center Research Institute
*Corresponding author: Dr. Tadashi Kondo, MD, PhD,
Proteome Bioinformatics Project, National Cancer Center Research Institute,
5-1- 1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan,
Tel       : +81-3-3542-2511 ext.3004,
Fax     : +81-3-3547-5298,
E-mail: takondo@ncc.go.jp
Received September 26, 2009; Accepted November 23, 2009; Published November 24, 2009
Citation: Kosaihira S, Tsunehiro Y, Tsuta K, Tochigi N, Gemma A, et al. (2009) Proteome Expression Database of Lung Adenocarcinoma: a segment of the Genome Medicine Database of Japan Proteomics. J Proteomics Bioinform 2: 463-465. doi:10.4172/jpb.1000106
Copyright: ©2009 Kosaihira S, 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

Lung cancer is a leading cause of cancer death worldwide, and lung cancer proteomics studies have been carried out to reveal the molecular background of cancer phenotypes and to develop clinically relevant applications. Here, we report an open-access proteome expression database derived from the study of 262 lung cancer cases using data extracted by two-dimensional difference gel electrophoresis (2D-DIGE) and mass spectrometry. Proteins extracted from primary tumor tissues were labeled with CyDye DIGE Fluor saturation dye, and separated using a large format electrophoresis device, generating 3179 protein spots. Mass spectrometry following in-gel digestion identified 487 proteins corresponding to 721 protein spots. Multiple proteins were observed from single protein spots, and single proteins generated multiple protein spots, suggesting diversity of the proteome. The results of 2D-DIGE and protein identification, and part of the corresponding clinico-pathological data are freely accessible in the public proteome database Genome Medicine
Database of Japan Proteomics (GeMDBJ Proteomics, http://gemdbj.nibio.go.jp/dgdb/DigeTop.do).

 
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