To further development of our gene expression approach to biodosimetry we have employed whole genome microarray expression profiling as a discovery platform to identify genes with the potential to distinguish radiation dose across an exposure range relevant for medical decision-making in a radiological emergency. Human peripheral blood from healthy donors was irradiated ex vivo and a 74-gene consensus signature was identified that distinguished between four radiation doses (0.5 2 5 and 8 Gy) and control samples. The same set of genes separated samples by exposure level at both six and 24 hours after treatment with overlap evident only at the highest two doses (5 and 8 Gy). Expression of five genes (CDKN1A FDXR SESN1 BBC3 and PHPT1) from this signature was quantified in the same RNA samples by real-time PCR confirming low variability between donors as well as the predicted radiation response pattern. Experiment Overall Design: Radiation induced gene expression in human blood was measured at 6 and 24 hours after exposure to doses of 0 0.5 2 5 and 8 Gy g-rays. Five independent experiments were performed at each time (6 or 24 hours) using different donors for each experiment

Here we present a whole-genome survey of the murine transcriptomic response to physiologically-relevant radiation doses 2 and 8 Gy. There are 18 distinct biological samples here. Mice were exposed to ionizing radiation (Cesium-138 source) and whole blood was collected by cardiac puncture 6 hours post treatment. Doses were 0 (7 samples) 2 (5 samples) and 8 (6 samples) gy.

Analysis of human peripheral blood 48 hours after irradiation ex vivo with graded doses of gamma rays. Results have been used in building and testing classifiers to predict exposure dose for use in radiological triage and also provide insight into immune cell responses. Results were compared with those from earlier times and from patients exposed in vivo. Peripheral blood from 5 healthy donors was exposed ex vivo to 0. 0.5 2 5 or 8 Gy gamma-rays and gene expression was analyzed up to 48 hours after exposure.

Analysis of human peripheral blood 48 hours after irradiation ex vivo with graded doses of gamma rays. Results have been used in building and testing classifiers to predict exposure dose for use in radiological triage and also provide insight into immune cell responses. Results were compared with those from earlier times and from patients exposed in vivo. Peripheral blood from 5 healthy donors was exposed ex vivo to 0. 0.5 2 5 or 8 Gy gamma-rays and gene expression was analyzed up to 48 hours after exposure.

Cesium-137 is a radionuclide of concern in fallout from reactor accidents or nuclear detonations. When ingested or inhaled it can expose the entire body for an extended period of time potentially contributing to serious health consequences ranging from acute radiation syndrome to increased cancer risks. In order to identify changes in gene expression that may be informative for detecting such exposure and to begin examining the molecular responses involved we have profiled global gene expression in mice injected with 137CsCl. We extracted RNA from the blood of control or 137CsCl-injected mice at 2 3 5 20 or 30 days after exposure. Gene expression was measured using Agilent Whole Mouse Genome Microarrays and the data was analyzed using BRB-ArrayTools. Three-month old male C57Bl/6 mice were injected intraperitoneally with 8.0 xc2 xb1 0.3 MBq 137CsCl solution in a volume of 50 xce xbcL or left as controls. Groups of treated and control mice were sacrificed at intervals during the first 2-30 days after exposure and total blood was collected using cardiac puncture. RNA was extracted from the blood globin-transcript reduced and subjected to whole genome expression microarray analysis.

The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation. Little is known about the contribution of genome level changes in neighboring bystander cells to tissue and organ stress after irradiation. The timing of these changes is critical in the physiological context and these questions can only be answered by studying signaling and global transcriptomics in a chronological way. Here we present a strategy to identify different biologically important signaling modules that act in concert in the radiation and bystander responses. We used time series gene expression analysis of normal human fibroblast cells measured at 0.5 hour 1 hour 2 hours 4 hours 6 hours and 24 hours after exposure to radiation coupled with a novel clustering method targeted to short time series Feature Based Partitioning around medoids Algorithm (FBPA) to look for genes that were potentially co-regulated. This method uses biologically meaningful features of the expression profile and dimension augmentation to address the analysis of sparse data sets such as ours. We applied FBPA and Short Time series Expression Miner (STEM) to the same datasets and present the results of our comparisons using computational metrics as well as biological enrichment. Enrichment showed that gene expression in irradiated cells fell into broad categories of signal transduction cell cycle/cell death and inflammation/immunity; but only FBPA clustered functions well. In bystander cells the gene expression response was also broadly categorized into functions associated with cell communication and motility signal transduction and inflammation; but neither STEM nor FBPA separated biological functions as well as in irradiated samples. Network analysis revealed that p53 and NF-kappaB were central players in gene expression in both irradiated and bystander gene clusters. Analysis of individual clusters also suggested new regulators of gene expression in the radiation and bystander response that may act at the epigenetic level such as histone deacetylases (HDAC1 and HDAC2) and methylases (KDM5B) that can act as strong transcription repressors. Based on these results we propose a novel time series clustering method FBPA as a powerful approach that can be applied to sparse data sets (including genomic profiling data) where the choice of features selected for clustering and stringent statistical outcome analysis can augment our knowledge of the underlying cellular mechanisms in biological processes. There are 72 total samples 4 corresponding biological replicates of IMR90 cells that were not irradiated (control=C) irradiated (alpha=A) and bystander (B) cells were harvested at 0.5 hour 1 hour 2 hours 4 hours 6 hours and 24 hours after treatment

One of the most likely risks astronauts on long duration space missions face is exposure to ionizing radiation associated with highly energetic and charged heavy (HZE) particles. Since access to medical expertise on such a mission is limited at best early diagnosis and mitigation of such exposure is critical. In order to accurately determine the dosage within 1 hour post-exposure dose-dependent biomarkers are needed. Therefore we performed a dose-course transcriptional analysis for radiation exposure at 0 0.3 1.5 and 3.0 Gy with corresponding time point at 1 hour (hr) post-exposure using Affymetrix GeneChip Human Gene 1.0 ST v1 Array chips. The analysis of our data suggests a set of sensitive genetic biomarkers specific to each radiation level as well as generic radiation response biomarkers. Upregulated biomarkers can then be used within lab-on-a-chip (LOC) systems to detect exposure to ionizing radiation. A total of sixteen human samples representing radiation exposure at levels 0 Gy 0.3 Gy 1.5 Gy and 3.0 Gy at time point 1 hour (hr) post-exposure were constructed. Blood samples were extracted from four human volunteers and were irradiated. Leukocytes were extracted and gene expression was measured. Samples for all four volunteers were measured at 1 hr for all four dose levels resulting in four replicates at each dose level. Thus a total of 4 samples at each of the four radiation levels were sampled yielding the total of 16 samples.

One of the most likely risks astronauts on long duration space missions face is exposure to ionizing radiation associated with highly energetic and charged heavy (HZE) particles. Since access to medical expertise on such a mission is limited at best early diagnosis and mitigation of such exposure is critical. In order to accurately determine the dosage within 1 hour post-exposure dose-dependent biomarkers are needed. Therefore we performed a dose-course transcriptional analysis for radiation exposure at 0 0.3 1.5 and 3.0 Gy with corresponding time point at 1 hour (hr) post-exposure using Affymetrix GeneChip Human Gene 1.0 ST v1 Array chips. The analysis of our data suggests a set of sensitive genetic biomarkers specific to each radiation level as well as generic radiation response biomarkers. Upregulated biomarkers can then be used within lab-on-a-chip (LOC) systems to detect exposure to ionizing radiation. A total of sixteen human samples representing radiation exposure at levels 0 Gy 0.3 Gy 1.5 Gy and 3.0 Gy at time point 1 hour (hr) post-exposure were constructed. Blood samples were extracted from four human volunteers and were irradiated. Leukocytes were extracted and gene expression was measured. Samples for all four volunteers were measured at 1 hr for all four dose levels resulting in four replicates at each dose level. Thus a total of 4 samples at each of the four radiation levels were sampled yielding the total of 16 samples.

Irradiated cell lines exposed to 1-10 Gy 2 Lymphoblastoid cell lines (GM15510 and GM15036) irradiated 1 2.5 5 7.5 10 Gy RNA is isolated and labeled using a T7 amplification Arcturus kit for hybridization on triplicate arrays.

Radiation affects tissue and cellular integrity at the level of DNA protein and metabolites of the cell and extracellular space. The effects of radiation are not limited to targeted cells and tissue and radiation induced bystander effects are significant to exposed individuals in accidental or therapeutic situations. These non-targeted effects of radiation have been studied extensively at the low dose range where they appear to have adverse effects on cells and surrounding environments. The requirement of cellular contact and shared fluid media has been established as critical to the bystander effect yet there is not much known about the actual signaling mechanism and its ability to transmit the damaging effect over space and time. Experimental cell types and context within the tissue are also quite important to the nature and extent of this bystander effect and must be considered when drawing parallels at the organismal level. Our approach was to use a genomic level analysis of global mRNA expression in primary lung fibroblast cells to understand the cellular triggers and mechanism of the bystander effect. Gene ontology and pathway analyses suggested that the p53 induced transcriptional response appears muted in bystanders while cytokine and cell signaling mechanisms such as those controlled by NFkB and p38 MAPK are highly active in both populations. We validated a large number of genes that are significantly changed at 4hrs after irradiation in both irradiated and bystander populations. We investigated time course gene expression profiles of cyclooxygenase2 (PTGS2) interleukin 8 (IL8) and BCL2 related protein 2 (BCL2A1) as genes that are involved in cellular signaling via the NFkB pathway which revealed that there is a dramatic response at 0.5hr after irradiation followed by another wave at 4hr in both populations. The induction of interleukins such as cytokine IL8 and chemokine IL6 at the transcriptional level is both early and amplified and if followed by translation and secretion of these proteins could explain the concerted response seen in bystander cells. Our results are the first to show that there is a significant and distinct global response of cellular signaling genes in bystander cells with some genes showing a response as early as 0.5hr after irradiation which implies a fast moving intercellular signal that leads to a concerted response in the irradiated and bystander populations. Keywords: gene expression fold change There are 12 total samples 4 corresponding biological replicates of IMR90 cells that were not irradiated (control=C) irradiated (alpha=A) and bystander (B)