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Integrated Bioinformatics for Radiation-Induced Pathway Analysis from Proteomics and Microarray Data

Zhang-Zhi Hu1*, Hongzhan Huang1, Amrita Cheema2, Mira Jung3, Anatoly Dritschilo3, Cathy H. Wu1

1Department of Biochemistry and Molecular & Cellular Biology
2Proteomics and Metabolomics Shared Resource
3Department of Radiation Medicine
Lombardi Comprehensive Cancer Center
Georgetown University Medical Center, Washington, DC 20007, USA
*Corresponding author: Zhang-Zhi Hu, MD, Research Associate Professor and Associate Team Lead, Protein Information Resource (PIR), Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Medical Center3300 Whitehaven Street,NW, Suite 1200 Washington, D.C. 20007
Phone: (202) 687-1255,
Fax: (202) 687-1662,
E-mail: zh9@georgetown.edu
Received May 24, 2008; Accepted May 24, 2008; Published May 24, 2008
Citation:Zhang ZH, Hongzhan H, Amrita C, Mira J, Anatoly D, etal. (2008) Integrated Bioinformatics for Radiation- Induced Pathway Analysis from Proteomics and Microarray Data. J Proteomics Bioinform 1: 047-060. doi:10.4172/jpb.1000009
Copyright: © 2008 Zhang-Zhi H, etal. 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

Functional analysis and interpretation of large-scale proteomics and gene expression data require effective use of bioinformatics tools and public knowledge resources coupled with expert-guided examination. An integrated bioinformatics approach was used to analyze cellular pathways in response to ionizing radiation. ATM, or mutated in ataxia-telangiectasia, a serine-threonine protein kinase, plays critical roles in radiation responses, including cell cycle arrest and DNA repair. We analyzed radiation responsive pathways based on 2D-gel/MS proteomics and microarray gene expression data from fibroblasts expressing wild type or mutant ATM gene. The analysis showed that metabolism was significantly affected by radiation in an ATM dependent manner. In particular, purine metabolic pathways were differentially changed in the two cell lines. The expression of ribonucleoside- diphosphate reductase subunit M2 (RRM2) was increased in ATM-wild type cells at both mRNA and protein levels, but no changes were detected in ATM-mutated cells. Increased expression of p53 was observed 30min after irradiation of the ATM-wild type cells. These results suggest that RRM2 is a downstream target of the ATM-p53 pathway that mediates radiation-induced DNA repair. We demonstrated that the integrated bioinformatics approach facilitated pathway analysis, hypothesis generation and target gene/protein identification.

 
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