title: Identification of gene expression biomarkers for predicting radiation exposure.
abstract: A need for more accurate and reliable radiation dosimetry has become increasingly important due to the possibility of a large-scale radiation emergency resulting from terrorism or nuclear accidents. Although traditional approaches provide accurate measurements, such methods usually require tedious effort and at least two days to complete. Therefore, we provide a new method for rapid prediction of radiation exposure. Eleven microarray datasets were classified into two groups based on their radiation doses and utilized as the training samples. For the two groups, Student's t-tests and resampling tests were used to identify biomarkers, and their gene expression ratios were used to develop a prediction model. The performance of the model was evaluated in four independent datasets, and Ingenuity pathway analysis was performed to characterize the associated biological functions. Our meta-analysis identified 29 biomarkers, showing approximately 90% and 80% accuracy in the training and validation samples. Furthermore, the 29 genes significantly participated in the regulation of cell cycle, and 19 of them are regulated by three well-known radiation-modulated transcription factors: TP53, FOXM1 and ERBB2. In conclusion, this study demonstrates a reliable method for identifying biomarkers across independent studies and high and reproducible prediction accuracy was demonstrated in both internal and external datasets.
authors.affiliation: 1] Department of Public Health, National Taiwan University, Taipei, Taiwan [2] Graduate Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.
authors.forename: Tzu-Pin
authors.initials: TP
authors.lastname: Lu
authors.affiliation: Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan.
authors.forename: Yi-Yao
authors.initials: YY
authors.lastname: Hsu
authors.affiliation: 1] Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan [2] Graduate Institute of Physiology, National Taiwan University, Taipei, Taiwan.
authors.forename: Liang-Chuan
authors.initials: LC
authors.lastname: Lai
authors.affiliation: 1] Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan [2] Institute of Biotechnology, National Taiwan University, Taipei, Taiwan.
authors.forename: Mong-Hsun
authors.initials: MH
authors.lastname: Tsai
authors.affiliation: 1] Graduate Institute of Biomedical Electronics and Bioinformatics and Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan [2] Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan.
authors.forename: Eric Y
authors.initials: EY
authors.lastname: Chuang
mesh_terms: D015415:Biomarkers / Q000378:metabolism; D004843:Epistasis, Genetic; D006801:Humans; D011832:Radiation Injuries / Q000235:genetics* / Q000378:metabolism; D059467:Transcriptome
chemical_list: D015415:Biomarkers