Dataset Information

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

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 ataxia-telangiectasia mutated , 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.

SUBMITTER: Hu ZZ

PROVIDER: S-EPMC2603135 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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

Hu Zhang-Zhi ZZ Huang Hongzhan H Cheema Amrita A Jung Mira M Dritschilo Anatoly A Wu Cathy H CH

Journal of proteomics & bioinformatics 20080501 2

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 ataxia-telangiectasia mutated , a serine-threonine protein kinase, plays critical roles in radiation responses, including cell cycle arrest and DNA repair. We analyzed radiat ...[more]

PMID: 19088860

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Project description:Many efforts have been made to discover novel bio-markers for early disease detection in oncology. However, the lack of efficient computational strategies impedes the discovery of disease-specific biomarkers for better understanding and management of treatment outcomes. In this study, we propose a novel graph-based scoring function to rank and identify the most robust biomarkers from limited proteomics data. The proposed method measures the proximity between candidate proteins identified by mass spectrometry (MS) analysis utilizing prior reported knowledge in the literature. Recent advances in mass spectrometry provide new opportunities to identify unique biomarkers from peripheral blood samples in complex treatment modalities such as radiation therapy (radiotherapy), which enables early disease detection, disease progression monitoring, and targeted intervention. Specifically, the dose-limiting role of radiation-induced lung injury known as radiation pneumonitis (RP) in lung cancer patients receiving radiotherapy motivates the search for robust predictive biomarkers. In this case study, plasma from 26 locally advanced non-small cell lung cancer (NSCLC) patients treated with radiotherapy in a longitudinal 3 × 3 matched-control cohort was fractionated using in-line, sequential multiaffinity chromatography. The complex peptide mixtures from endoprotease digestions were analyzed using comparative, high-resolution liquid chromatography (LC)-MS to identify and quantify differential peptide signals. Through analysis of survey mass spectra and annotations of peptides from the tandem spectra, we found candidate proteins that appear to be associated with RP. On the basis of the proposed methodology, ?-2-macroglobulin (?2M) was unambiguously ranked as the top candidate protein. As independent validation of this candidate protein, enzyme-linked immunosorbent assay (ELISA) experiments were performed on independent cohort of 20 patients' samples resulting in early significant discrimination between RP and non-RP patients (p = 0.002). These results suggest that the proposed methodology based on longitudinal proteomics analysis and a novel bioinformatics ranking algorithm is a potentially promising approach for the challenging problem of identifying relevant biomarkers in sample-limited clinical applications.

Dataset Information

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

Publications

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

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