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Identifying radiation exposure biomarkers from mouse blood transcriptome.

ABSTRACT: Ionising radiation is a pleiotropic stress agent that may induce a variety of adverse effects. Molecular biomarker approaches possess promise to assess radiation exposure, however, the pleiotropic nature of ionising radiation induced transcriptional responses and the historically poor inter-laboratory performance of omics-derived biomarkers serve as barriers to identification of unequivocal biomarker sets. Here, we present a whole-genome survey of the murine transcriptomic response to physiologically relevant radiation doses, 2 Gy and 8 Gy. We used this dataset with the Random Forest algorithm to correctly classify independently generated data and to identify putative metabolite biomarkers for radiation exposure.

SUBMITTER: Hyduke DR

PROVIDER: S-EPMC4180524 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Identifying radiation exposure biomarkers from mouse blood transcriptome.

Hyduke Daniel R DR Laiakis Evagelia C EC Li Heng-Hong HH Fornace Albert J AJ

International journal of bioinformatics research and applications 20130101 4

Ionising radiation is a pleiotropic stress agent that may induce a variety of adverse effects. Molecular biomarker approaches possess promise to assess radiation exposure, however, the pleiotropic nature of ionising radiation induced transcriptional responses and the historically poor inter-laboratory performance of omics-derived biomarkers serve as barriers to identification of unequivocal biomarker sets. Here, we present a whole-genome survey of the murine transcriptomic response to physiologi ...[more]

PMID: 23797995

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Project description:The increasing risk of acute large-scale radiological/nuclear exposures of population underlines the necessity of developing new, rapid and high throughput biodosimetric tools for estimation of received dose and initial triage. We aimed to compare the induction and persistence of different radiation exposure biomarkers in human peripheral blood in vivo. Blood samples of patients with indicated radiotherapy (RT) undergoing partial body irradiation (PBI) were obtained soon before the first treatment and then after 24 h, 48 h, and 5 weeks; i.e. after 1, 2, and 25 fractionated RT procedures. We collected circulating peripheral blood from ten patients with tumor of endometrium (1.8 Gy per fraction) and eight patients with tumor of head and neck (2.0-2.121 Gy per fraction). Incidence of dicentrics and micronuclei was monitored as well as determination of apoptosis and the transcription level of selected radiation-responsive genes. Since mitochondrial DNA (mtDNA) has been reported to be a potential indicator of radiation damage in vitro, we also assessed mtDNA content and deletions by novel multiplex quantitative PCR. Cytogenetic data confirmed linear dose-dependent increase in dicentrics (p < 0.01) and micronuclei (p < 0.001) in peripheral blood mononuclear cells after PBI. Significant up-regulations of five previously identified transcriptional biomarkers of radiation exposure (PHPT1, CCNG1, CDKN1A, GADD45, and SESN1) were also found (p < 0.01). No statistical change in mtDNA deletion levels was detected; however, our data indicate that the total mtDNA content decreased with increasing number of RT fractions. Interestingly, the number of micronuclei appears to correlate with late radiation toxicity (r2 = 0.9025) in endometrial patients suggesting the possibility of predicting the severity of RT-related toxicity by monitoring this parameter. Overall, these data represent, to our best knowledge, the first study providing a multiparametric comparison of radiation biomarkers in human blood in vivo, which have potential for improving biological dosimetry.

Project description:PurposeEarly and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI).Methods and materialsFor feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison.ResultsA comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies.ConclusionsExosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures.

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Identifying radiation exposure biomarkers from mouse blood transcriptome.

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Identifying radiation exposure biomarkers from mouse blood transcriptome.

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