The Urine Proteome as a Radiation Biodosimeter

Serum Proteomic and Oxidative Modification Profiling in Mice Exposed to Total Body X-Irradiation

The details of the dose-dependent response of serum proteins exposed to ionizing radiation, especially the oxidative modification response in amino acid sequences of albumin, the most abundant protein, are unknown. Thus, a proteomic analysis of the serum components from mice exposed to total body X-irradiation (TBI) ranging from 0.5 Gy to 3.0 Gy was conducted using LC-MS/MS. The analysis of oxidative modification sequences of albumin (mOMSA) in TBI mouse serum revealed significant moderate or strong correlations between the X-irradiation exposure dose and modification of 11 mOMSAs (especially the 97th, 267th and 499th lysine residues, 159th methionine residue and 287th tyrosine residues). In the case of X-irradiation of serum alone, significant correlations were also found in the 14 mOMSAs. In addition, a dose-dependent variation in six proteins (Angiotensinogen, Odorant-binding protein 1a, Serine protease inhibitor A3K, Serum paraoxonase/arylesterase 1, Prothrombin and Epidermal growth factor receptor) was detected in the serum of mice exposed to TBI. These findings suggest the possibility that the protein variation and serum albumin oxidative modification responses found in exposed individuals are important indicators for considering the effects of radiation on living organisms, along with DNA damage, and suggests their possible application as biomarkers of radiation dose estimation.

Screening of Lipids for Early Triage and Dose Estimation after Acute Radiation Exposure in Rat Plasma Based on Targeted Lipidomics Analysis

Rapid early triage and dose estimation is vital for limited medical resource allocation and treatment of a large number of the wounded after radiological accidents. Lipidomics has been utilized to delineate biofluid lipid signatures after irradiation. Here, high-coverage targeted lipidomics was employed to screen radiosensitive lipids after 0, 1, 2, 3, 5, and 8 Gy total body irradiation at 4, 24, and 72 h postirradiation in rat plasma. Ultra-performance liquid chromatography-tandem mass spectrometry with a multiple reaction monitoring method was utilized. In total, 416 individual lipids from 18 major classes were quantified and those biomarkers altered in a dose-dependent manner constituted panel A-panel D. Receiver operator characteristic curve analysis using combined lipids showed good to excellent sensitivity and specificity in triaging different radiation exposure levels (area under curve = 0.814-1.000). The equations for dose estimation were established by stepwise regression analysis for three time points. A novel strategy for radiation early triage and dose estimation was first established and validated using panels of lipids. Our study suggests that it is feasible to acquire quantitative lipid biomarker panels using targeted lipidomics platforms for rapid, high-throughput triage, which can provide further insights in developing lipidomics strategies for radiation biodosimetry in humans.

Transcriptomic responses in mouse blood during the first week after in vivo gamma irradiation

Due to limitations of available human models for development of gene expression based radiation biodosimetry, many such studies have made use of mouse models. To provide a broad view of the gene expression response to irradiation in the mouse, we have exposed male C57BL/6 mice to 0, 1.5, 3, 6 or 10 Gy of gamma rays, sacrificing groups of the mice at 1, 2, 3, 5, or 7 days after exposure. We then profiled global gene expression in blood from individual mice using Agilent microarrays. In general, we found increasing numbers of genes differentially expressed with increasing dose, with more prolonged responses after the higher doses. Gene ontology analysis showed a similar pattern, with more biological processes enriched among the genes responding to higher doses, and at later times after exposure. Clustering the timecourse expression data using maSigPro identified four broad patterns of response, representing different gene ontology functions. The largest of these clusters included genes with initially decreased expression followed by increased expression at later times, a pattern of expression previously reported for several genes following neutron exposure. Another gene cluster showing consistent down regulation suggests genes useful for biodosimetry throughout the first week after exposure can be identified.

Serum lipidomic analysis from mixed neutron/X-ray radiation fields reveals a hyperlipidemic and pro-inflammatory phenotype

Heightened threats for nuclear terrorism using improvised nuclear devices (IND) necessitate the development of biodosimetry assays that could rapidly assess thousands of individuals. However, the radiation exposures from an IND may be complex due to mixed fields of neutrons and photons (γ-rays), shielding from buildings, and proximity to the epicenter among others. In this study we utilized lipidomics to analyze serum samples from mice exposed to various percentages of neutrons and X-rays to a total dose of 3 Gy. Triacylglycerides, phosphatidylserines, lysophosphatidylethanolamines, lysophosphatidylcholines (LPCs), sphingolipids, and cholesteryl esters all showed delayed increases at day 7 compared to day 1 after irradiation, while diacylglycerides decreased in mixed field exposures and phosphatidylcholines (PCs) remained largely unchanged. Individual lipid molecules with a high degree of unsaturation exhibited the highest fold changes in mixed fields compared to photons alone. More importantly, the increased ratio of LPCs to PCs of each irradiation group compared to control could be used as a radiation biomarker and highlights the existence of a pro-inflammatory phenotype. The results showed that even a small percentage of neutrons in a mixed field can lead to high biological responses with implications for accurate biodosimetry, triage and medical managements of exposed populations.

Candidate gene biodosimetry markers of exposure to external ionizing radiation in human blood: A systematic review

Purpose

To compile a list of genes that have been reported to be affected by external ionizing radiation (IR) and to assess their performance as candidate biomarkers for individual human radiation dosimetry.

Methods

Eligible studies were identified through extensive searches of the online databases from 1978 to 2017. Original English-language publications of microarray studies assessing radiation-induced changes in gene expression levels in human blood after external IR were included. Genes identified in at least half of the selected studies were retained for bio-statistical analysis in order to evaluate their diagnostic ability.

Results

24 studies met the criteria and were included in this study. Radiation-induced expression of 10,170 unique genes was identified and the 31 genes that have been identified in at least 50% of studies (12/24 studies) were selected for diagnostic power analysis. Twenty-seven genes showed a significant Spearman’s correlation with radiation dose. Individually, TNFSF4, FDXR, MYC, ZMAT3 and GADD45A provided the best discrimination of radiation dose < 2 Gy and dose ≥ 2 Gy according to according to their maximized Youden’s index (0.67, 0.55, 0.55, 0.55 and 0.53 respectively). Moreover, 12 combinations of three genes display an area under the Receiver Operating Curve (ROC) curve (AUC) = 1 reinforcing the concept of biomarker combinations instead of looking for an ideal and unique biomarker.

Conclusion

Gene expression is a promising approach for radiation dosimetry assessment. A list of robust candidate biomarkers has been identified from analysis of the studies published to date, confirming for example the potential of well-known genes such as FDXR and TNFSF4 or highlighting other promising gene such as ZMAT3. However, heterogeneity in protocols and analysis methods will require additional studies to confirm these results.

Gene Expression in Parp1 Deficient Mice Exposed to a Median Lethal Dose of Gamma Rays

There is a current interest in the development of biodosimetric methods for rapidly assessing radiation exposure in the wake of a large-scale radiological event. This work was initially focused on determining the exposure dose to an individual using biological indicators. Gene expression signatures show promise for biodosimetric application, but little is known about how these signatures might translate for the assessment of radiological injury in radiosensitive individuals, who comprise a significant proportion of the general population, and who would likely require treatment after exposure to lower doses. Using Parp1^-/- mice as a model radiation-sensitive genotype, we have investigated the effect of this DNA repair deficiency on the gene expression response to radiation. Although Parp1 is known to play general roles in regulating transcription, the pattern of gene expression changes observed in Parp1^-/- mice 24 h postirradiation to a LD_50/30 was remarkably similar to that in wild-type mice after exposure to LD_50/30. Similar levels of activation of both the p53 and NFκB radiation response pathways were indicated in both strains. In contrast, exposure of wild-type mice to a sublethal dose that was equal to the Parp1^-/- LD_50/30 resulted in a lower magnitude gene expression response. Thus, Parp1^-/- mice displayed a heightened gene expression response to radiation, which was more similar to the wild-type response to an equitoxic dose than to an equal absorbed dose. Gene expression classifiers trained on the wild-type data correctly identified all wild-type samples as unexposed, exposed to a sublethal dose or exposed to an LD_50/30. All unexposed samples from Parp1^-/- mice were also correctly classified with the same gene set, and 80% of irradiated Parp1^-/- samples were identified as exposed to an LD_50/30. The results of this study suggest that, at least for some pathways that may influence radiosensitivity in humans, specific gene expression signatures have the potential to accurately detect the extent of radiological injury, rather than serving only as a surrogate of physical radiation dose.

Developing Human Radiation Biodosimetry Models: Testing Cross-Species Conversion Approaches Using an Ex Vivo Model System

In the event of a large-scale radiation exposure, accurate and quick assessment of radiation dose received would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to the limited availability of appropriate human samples, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate (NHP) models to build and test a biodosimetry algorithm for use in humans, we irradiated ex vivo peripheral blood samples from both humans and rhesus macaques with doses of 0, 2, 5, 6 and 7 Gy, and compared the gene expression profiles 24 h later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using NHP data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the NHP model. A "multi-gene" approach utilizing all gene values for cross-species conversion and applying the converted values on the NHP biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primates. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the NHP model.

Metabolomic applications in radiation biodosimetry: exploring radiation effects through small molecules

PURPOSE

Exposure of the general population to ionizing radiation has increased in the past decades, primarily due to long distance travel and medical procedures. On the other hand, accidental exposures, nuclear accidents, and elevated threats of terrorism with the potential detonation of a radiological dispersal device or improvised nuclear device in a major city, all have led to increased needs for rapid biodosimetry and assessment of exposure to different radiation qualities and scenarios. Metabolomics, the qualitative and quantitative assessment of small molecules in a given biological specimen, has emerged as a promising technology to allow for rapid determination of an individual's exposure level and metabolic phenotype. Advancements in mass spectrometry techniques have led to untargeted (discovery phase, global assessment) and targeted (quantitative phase) methods not only to identify biomarkers of radiation exposure, but also to assess general perturbations of metabolism with potential long-term consequences, such as cancer, cardiovascular, and pulmonary disease.

CONCLUSIONS

Metabolomics of radiation exposure has provided a highly informative snapshot of metabolic dysregulation. Biomarkers in easily accessible biofluids and biospecimens (urine, blood, saliva, sebum, fecal material) from mouse, rat, and minipig models, to non-human primates and humans have provided the basis for determination of a radiation signature to assess the need for medical intervention. Here we provide a comprehensive description of the current status of radiation metabolomic studies for the purpose of rapid high-throughput radiation biodosimetry in easily accessible biofluids and discuss future directions of radiation metabolomics research.

Proteomic analysis of irradiated lung tissue of mice using gel-based proteomic approach

PURPOSE

Exposure to radiation causes severe alterations of protein expression level inside the cell, thus it may influence the biological events and stress response. In the present investigation, we have demonstrated the effect of radiation on mice lung tissues.

MATERIALS AND METHODS

Two-dimensional gel electrophoresis (2-DE) coupled with MALDI-TOF/TOF was used to check the expression changes in lung proteome profile of strain 'A' female mice after exposure to lethal doses of gamma irradiation at different time periods (24 and 48 h). Identified proteins were analysed for their altered expression and were further validated by Western blotting and enzyme-linked immunosorbent assay (ELISA).

RESULTS

Nine significant differentially expressed proteins were identified from irradiated lungs tissues. The expression level of zinc finger protein was found to be up regulated at 24 h irradiation in comparison to 48 h irradiation.

CONCLUSIONS

Zinc finger protein may be considered as a radiation responsive protein. Alteration in its expression pattern may primarily affect binding specificity of the protein that can further result in the interference in transcriptional control of multiple stress responsive genes.

State-of-the-Art Advances in Radiation Biodosimetry for Mass Casualty Events Involving Radiation Exposure

With the possibility of large-scale terrorist attacks around the world, the need for modeling and development of new medical countermeasures for potential future chemical, biological, radiological and nuclear (CBRN) has been well established. Project Bioshield, initiated in 2004, provided a framework to develop and expedite research in the field of CBRN exposures. To respond to large-scale population exposures from a nuclear event or radiation dispersal device (RDD), new methods for determining received dose using biological modeling became necessary. The field of biodosimetry has advanced significantly beyond this original initiative, with expansion into the fields of genomics, proteomics, metabolomics and transcriptomics. Studies are ongoing to evaluate the use of lymphocyte kinetics for dose assessment, as well as the development of field-deployable EPR technology. In addition, expansion of traditional cytogenetic assessment methods through the use of automated platforms and the development of laboratory surge capacity networks have helped to advance our biodefense preparedness. In this review of the latest advances in the field of biodosimetry we evaluate our progress and identify areas that still need to be addressed to achieve true field-deployment readiness.

Targeted Metabolomics of Nonhuman Primate Serum after Exposure to Ionizing Radiation: Potential Tools for High-throughput Biodosimetry

There is a need for research to rapidly determine an individual's absorbed dose and its potential health effects after a potential radiological or nuclear event that could expose large portions of a population to ionizing radiation (IR). Studies on biomarker identification after radiation exposure could aid in biodosimetry, identifying individual dose absorbed, as well as biologic response, and administering immediate and proper medical care. Metabolomics on easily accessible biofluids is an emerging field with potential for high-throughput biodosimetry. While tremendous effort has been put into obtaining discovery based global radiation signatures from a number of biofluids and model organisms, quantitative targeted analysis on a subset of known radiation biomarkers is required to develop an optimized panel of biomarkers for future clinical applications. The current study analyzes levels of several known broad chemical groups (acylcarnitines, amino acids, phosphatidylcholines, and biogenic amines) affected by IR in serum from nonhuman primates (NHP) 7 days after exposure through multiple reaction monitoring (MRM) analysis with a triple quadrupole mass spectrometry (MS) platform. We identified several novel metabolites affected by IR exposure through univariate and unsupervised multivariate analyses. Levels of acylcarnitines, amino acids, and phospholipids were perturbed indicating altered protein metabolism, fatty acid β-oxidation, and inflammation. Fold changes in carnitine and short-chain acylcarnitines (acetylcarnitine, propionylcarnitine, butyrylcarnitine, and valerylcarnitine) complement previous global radiation signatures on NHP; notably, the levels of change were lower than previously observed in urine. Decreased levels of glutamate, citrulline, and arginine after IR are biomarkers indicating gastrointestinal syndrome and perturbations to the urea cycle. Sex differences were also assessed and were more prevalent in circulating acylcarnitines and phospholipids after IR exposure. These biomarkers may be combined with previously described compounds from DNA damage to develop a defined metabolomic biodosimetry panel to be analyzed by MS platforms, which are increasingly available in clinical laboratories.

Investigation of relative metabolic changes in the organs and plasma of rats exposed to X-ray radiation using HR-MAS (1)H NMR and solution (1)H NMR

Excess exposure to ionizing radiation generates reactive oxygen species and increases the cellular inflammatory response by modifying various metabolic pathways. However, an investigation of metabolic perturbations and organ-specific responses based on the amount of radiation during the acute phase has not been conducted. In this study, high-resolution magic-angle-spinning (HR-MAS) NMR and solution NMR-based metabolic profiling were used to investigate dose-dependent metabolic changes in multiple organs and tissues--including the jejunum, spleen, liver, and plasma--of rats exposed to X-ray radiation. The organs, tissues, and blood samples were obtained 24, 48, and 72 h after exposure to low-dose (2 Gy) and high-dose (6 Gy) X-ray radiation and subjected to metabolite profiling and multivariate analyses. The results showed the time course of the metabolic responses, and many significant changes were detected in the high-dose compared with the low-dose group. Metabolites with antioxidant properties showed acute responses in the jejunum and spleen after radiation exposure. The levels of metabolites related to lipid and protein metabolism were decreased in the jejunum. In addition, amino acid levels increased consistently at all post-irradiation time points as a consequence of activated protein breakdown. Consistent with these changes, plasma levels of tricarboxylic acid cycle intermediate metabolites decreased. The liver did not appear to undergo remarkable metabolic changes after radiation exposure. These results may provide insight into the major metabolic perturbations and mechanisms of the biological systems in response to pathophysiological damage caused by X-ray radiation.

Radiation Dose-Rate Effects on Gene Expression in a Mouse Biodosimetry Model

In the event of a nuclear accident or radiological terrorist attack, there will be a pressing need for biodosimetry to triage a large, potentially exposed population and to assign individuals to appropriate treatment. Exposures from fallout are likely, resulting in protracted dose delivery that would, in turn, impact the extent of injury. Biodosimetry approaches that can distinguish such low-dose-rate (LDR) exposures from acute exposures have not yet been developed. In this study, we used the C57BL/6 mouse model in an initial investigation of the impact of low-dose-rate delivery on the transcriptomic response in blood. While a large number of the same genes responded to LDR and acute radiation exposures, for many genes the magnitude of response was lower after LDR exposures. Some genes, however, were differentially expressed (P < 0.001, false discovery rate <5%) in mice exposed to LDR compared with mice exposed to acute radiation. We identified a set of 164 genes that correctly classified 97% of the samples in this experiment as exposed to acute or LDR radiation using a support vector machine algorithm. Gene expression is a promising approach to radiation biodosimetry, enhanced greatly by this first demonstration of its potential for distinguishing between acute and LDR exposures. Further development of this aspect of radiation biodosimetry, either as part of a complete gene expression biodosimetry test or as an adjunct to other methods, could provide vital triage information in a mass radiological casualty event.

Glutathione S-transferase P protects against cyclophosphamide-induced cardiotoxicity in mice

High-dose chemotherapy regimens using cyclophosphamide (CY) are frequently associated with cardiotoxicity that could lead to myocyte damage and congestive heart failure. However, the mechanisms regulating the cardiotoxic effects of CY remain unclear. Because CY is converted to an unsaturated aldehyde acrolein, a toxic, reactive CY metabolite that induces extensive protein modification and myocardial injury, we examined the role of glutathione S-transferase P (GSTP), an acrolein-metabolizing enzyme, in CY cardiotoxicity in wild-type (WT) and GSTP-null mice. Treatment with CY (100-300 mg/kg) increased plasma levels of creatine kinase-MB isoform (CK · MB) and heart-to-body weight ratio to a significantly greater extent in GSTP-null than WT mice. In addition to modest yet significant echocardiographic changes following acute CY-treatment, GSTP insufficiency was associated with greater phosphorylation of c-Jun and p38 as well as greater accumulation of albumin and protein-acrolein adducts in the heart. Mass spectrometric analysis revealed likely prominent modification of albumin, kallikrein-1-related peptidase, myoglobin and transgelin-2 by acrolein in the hearts of CY-treated mice. Treatment with acrolein (low dose, 1-5 mg/kg) also led to increased heart-to-body weight ratio and myocardial contractility changes. Acrolein induced similar hypotension in GSTP-null and WT mice. GSTP-null mice also were more susceptible than WT mice to mortality associated with high-dose acrolein (10-20 mg/kg). Collectively, these results suggest that CY cardiotoxicity is regulated, in part, by GSTP, which prevents CY toxicity by detoxifying acrolein. Thus, humans with low cardiac GSTP levels or polymorphic forms of GSTP with low acrolein-metabolizing capacity may be more sensitive to CY toxicity.

2013 Dade W. Moeller lecture: medical countermeasures against radiological terrorism

Soon after the 9-11 attacks, politicians and scientists began to question our ability to cope with a large-scale radiological terrorism incident. The outline of what was needed was fairly obvious: the ability to prevent such an attack, methods to cope with the medical consequences, the ability to clean up afterward, and the tools to figure out who perpetrated the attack and bring them to justice. The medical response needed three components: the technology to determine rapidly the radiation doses received by a large number of people, methods for alleviating acute hematological radiation injuries, and therapies for mitigation and treatment of chronic radiation injuries. Research done to date has shown that a realistic medical response plan is scientifically possible, but the regulatory and financial barriers to achieving this may currently be insurmountable.

Assessment of early triage for acute radiation injury in rat model based on urinary amino acid target analysis

Rapid radiation injury early triage after a radiological or nuclear exposure is vital for treatment of a large number of wounded people. Owing to the high-throughput analysis and minimally invasive nature of sample collection, radiation metabolomics has been recently applied to radiation damage research. In the present study, exploring the feasibility of estimating the acute radiation injury for early triage by means of urinary amino acid target analysis was attempted using a high performance liquid chromatography electrospray tandem mass spectrometry (HPLC-ESI-MS/MS) technique combined with multivariate statistical analysis. The non-linear kernel partial least squares (KPLS) model was used to separate the control and different radiation dose groups. The classification of different groups was performed after feature selection instead of before feature selection, because of its better separation. The classification accuracy at various radiation injury levels at different time points (5, 24, 48 and 72 h) post-irradiation exposure was investigated. For most of the radiation damage levels, the classification accuracy at 72 h after exposure was superior to that at earlier time points. Additionally, the potential radiation injury biomarkers selected suggested that the urea cycle, glycine, serine and threonine metabolism, alanine, aspartate and glutamine metabolism and related metabolic pathways were involved. The findings suggest that non-invasive urinary biomarkers have great potential for serving as an effective tool for rapid triage of mass casualties in nuclear accidents and understanding the pathogenesis of radiation injury.

Intragenic controls utilizing radiation-induced alternative transcript regions improves gene expression biodosimetry

Ionizing-radiation exposure can be life threatening if given to the whole body. In addition, whole body radiation exposure can affect large numbers of people such as after a nuclear reactor accident, a nuclear explosion or a radiological terrorist attack. In these cases, an accurate biodosimeter is essential for triage management. One of the problems for biodosimetry in general is the interindividual variation before and after exposure, which can make it challenging to assign an accurate dose. To begin to address this challenge, lymphocyte cell lines were exposed to 0, 1, 2 and 5 Gy ionizing radiation from a ¹³⁷Cs source at a dose rate of 0.6 Gy/min. Alternative transcripts with regions showing large differential responses to ionizing radiation were determined from exon array data. Gene expression analysis was then performed on isolated mRNA using qRT-PCR with normalization to intergenic (PGK1, GAPDH) and novel intragenic regions for candidate radiation-responsive genes, PPM1D and MDM2. Our studies show that the use of a cis-associated expression reference improved the potential dose prediction approximately 2.3-8.3 fold and provided an advantage for dose prediction compared to distantly or trans-located control ionizing radiation nonresponsive genes. This approach also provides an alternative gene expression normalization method to potentially reduce interindividual variations when untreated basal gene expression levels are unavailable. Using associated noninduced regions of ionizing radiation-induced genes provides a way to estimate basal gene expression in the irradiated sample. This strategy can be utilized as a biodosimeter on its own or to enhance other gene expression candidates for biodosimetry. This normalization strategy may also be generally applicable for other quantitative PCR strategies where normalization is required for a particular response.

Proteomics in radiation research: present status and future perspectives

Rapidly developing postgenome research has made proteins an attractive target for biological analysis. The well-established term of proteome is defined as the complete set of proteins expressed in a given cell, tissue or organism. Unlike the genome, a proteome is rapidly changing as it tends to adapt to microenvironmental signals. The systematic analysis of the proteome at a given time and state is referred to as proteomics. This technique provides information on the molecular and cellular mechanisms that regulate physiology and pathophysiology of the cell. Applications of proteome profiling in radiation research are increasing. However, the large-scale proteomics data sets generated need to be integrated into other fields of radiation biology to facilitate the interpretation of radiation-induced cellular and tissue effects. The aim of this review is to introduce the most recent developments in the field of radiation proteomics.

Serum Proteome Analysis for Profiling Predictive Protein Markers Associated with the Severity of Skin Lesions Induced by Ionizing Radiation

The finding of new diagnostic and prognostic markers of local radiation injury, and particularly of the cutaneous radiation syndrome, is crucial for its medical management, in the case of both accidental exposure and radiotherapy side effects. Especially, a fast high-throughput method is still needed for triage of people accidentally exposed to ionizing radiation. In this study, we investigated the impact of localized irradiation of the skin on the early alteration of the serum proteome of mice in an effort to discover markers associated with the exposure and severity of impending damage. Using two different large-scale quantitative proteomic approaches, 2D-DIGE-MS and SELDI-TOF-MS, we performed global analyses of serum proteins collected in the clinical latency phase (days 3 and 7) from non-irradiated and locally irradiated mice exposed to high doses of 20, 40 and 80 Gy which will develop respectively erythema, moist desquamation and necrosis. Unsupervised and supervised multivariate statistical analyses (principal component analysis, partial-least square discriminant analysis and Random Forest analysis) using 2D-DIGE quantitative protein data allowed us to discriminate early between non-irradiated and irradiated animals, and between uninjured/slightly injured animals and animals that will develop severe lesions. On the other hand, despite a high number of animal replicates, PLS-DA and Random Forest analyses of SELDI-TOF-MS data failed to reveal sets of MS peaks able to discriminate between the different groups of animals. Our results show that, unlike SELDI-TOF-MS, the 2D-DIGE approach remains a powerful and promising method for the discovery of sets of proteins that could be used for the development of clinical tests for triage and the prognosis of the severity of radiation-induced skin lesions. We propose a list of 15 proteins which constitutes a set of candidate proteins for triage and prognosis of skin lesion outcomes.