alexa Cancer Proteomics for Biomarker Development
ISSN: 0974-276X

Journal of Proteomics & Bioinformatics
Open Access

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Research Article

Cancer Proteomics for Biomarker Development

Tadashi Kondo*

Proteome Bioinformatics Project, 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
Fax:
+81-3-3547-5298
E-mail: [email protected]

Received Date: August 09, 2008; Accepted Date: September 19, 2008; Published Date: December 05, 2008

Citation: Tadashi K (2008) Cancer Proteomics for Biomarker Development. J Proteomics Bioinform 1: 477-484. doi: 10.4172/jpb.1000055

Copyright: © 2008 Tadashi K. 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

Cancer is a diverse disease, and biomarkers reflecting this diversity will lead to better therapeutic strategies. By linking proteomic data and clinico-pathological parameters, we are identifying proteins informative for features of clinical relevance to cancer patients. To obtain proteome data, we developed a large format system for two-dimensional difference gel electrophoresis and an application of highly sensitive fluorescent dye for laser microdissection. Following the comprehensive proteome study of more than 1,000 surgical specimens and corresponding clinico-pathological data, we concluded that the proteome reflects the major cancer phenotypes such as histological differentiation, poor prognosis, and response to treatment. Furthermore, we found that certain single proteins predict the clinical outcome in many types of malignancies including esophageal cancer, lung adenocarcinoma, gastrointestinal stromal tumor, hepatocellular carcinoma, Ewing's sarcoma and osteosarcoma. By monitoring biomarker proteins to predict the clinical outcome, we will be able to optimize the therapeutic strategy, either by intensifying treatment or by avoiding over-treatment. The results of the cancer proteomics studies are integrated into a proteome database named Genome Medicine Database of Japan Proteomics. The above establish proteomics as a primary tool in the development of novel diagnostic modalities for personalized medicine.

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