Project description:The detonation of an improvised nuclear device would produce prompt radiation consisting of both photons (gamma-rays) and neutrons. While much effort in recent years has gone into the development of radiation biodosimetry methods suitable for mass triage, the possible effect of neutrons on the endpoints studied has remained largely uninvestigated. We have used a novel neutron irradiator with an energy spectrum based on that 1-1.5 km from the epicenter of the Hiroshima blast to begin examining the effect of neutrons on global gene expression, and the impact this may have on the development of gene expression signatures for radiation biodosimetry. We have exposed peripheral blood from healthy human donors to 0, 0.1, 0.3, 0.5, or 1 Gy of neutrons ex vivo using our neutron irradiator, and compared the transcriptomic response 24 h later to that resulting from exposure to 0.1, 0.3, 0.5, 1, 2 or 4 Gy of photons (x-rays).
Project description:After defining a gene expression signature that predicted radiation exposure dose with high accuracy in human peripheral white blood cells irradiated ex vivo, we now demonstrate the predictive power of gene expression signatures in blood from patients undergoing total body irradiation. Using whole genome microarray analysis, we have identified genes that respond to radiation exposure in cancer patients in vivo. A 3-nearest neighbor classifier built from these genes correctly predicted samples as exposed to 0, 1.25 or 3.75 Gy with 94% accuracy even when samples from healthy donor controls were included. The same samples were classified with 98% accuracy using a signature previously defined from ex vivo irradiation data. The samples could also be classified as exposed or not exposed with 100% accuracy using multiple methods. The demonstration that ex vivo irradiation is an appropriate model that can provide meaningful prediction of in vivo exposure, and that the signatures are robust across diverse disease states, is an important advance in the application of gene expression for biodosimetry. Translation of these signatures to a fully automated “lab-on-a-chip” device will enable high-throughput screening for large-scale radiological emergencies, as well as making such tests practical for clinical uses. Radiation induced gene expression was measured in vivo in TBI patients at 4 hours after 1.25Gy exposure or at 24 hours after 3.75Gy exposure with three 1.25Gy split doses (approximately 4 hours apart). A total of 18 TBI patients, diagnosed with a variety of cancers were used in this study. Blood from 14 healthy control individuals was also used for comparison.
Project description:Gene expression profiling of immortalized human mesenchymal stem cells with hTERT/E6/E7 transfected MSCs. hTERT may change gene expression in MSCs. Goal was to determine the gene expressions of immortalized MSCs.
Project description:Understanding the possible impact of potential confounding factors is necessary for any approach to radiation biodosimetry. Potential confounding factors have not been fully addressed for gene expression-based biodosimetry approaches, such as we are developing. To begin addressing this need, we have used an ex vivo irradiated peripheral blood cell model to investigate the potential effect of smoking on the global radiation gene expression response, and looked for genes that respond to radiation differently in smokers and non-smokers, and also in males and females. The results indicate that only a small number of genes may be significantly confounded by either factor, supporting the idea of developing peripheral blood gene expression strategies for radiation biodosimetry.
Project description:After defining a gene expression signature that predicted radiation exposure dose with high accuracy in human peripheral white blood cells irradiated ex vivo, we now demonstrate the predictive power of gene expression signatures in blood from patients undergoing total body irradiation. Using whole genome microarray analysis, we have identified genes that respond to radiation exposure in cancer patients in vivo. A 3-nearest neighbor classifier built from these genes correctly predicted samples as exposed to 0, 1.25 or 3.75 Gy with 94% accuracy even when samples from healthy donor controls were included. The same samples were classified with 98% accuracy using a signature previously defined from ex vivo irradiation data. The samples could also be classified as exposed or not exposed with 100% accuracy using multiple methods. The demonstration that ex vivo irradiation is an appropriate model that can provide meaningful prediction of in vivo exposure, and that the signatures are robust across diverse disease states, is an important advance in the application of gene expression for biodosimetry. Translation of these signatures to a fully automated “lab-on-a-chip” device will enable high-throughput screening for large-scale radiological emergencies, as well as making such tests practical for clinical uses.
Project description:Transcriptional profiling of human mesenchymal stem cells comparing normoxic MSCs cells with hypoxic MSCs cells. Hypoxia may inhibit senescence of MSCs during expansion. Goal was to determine the effects of hypoxia on global MSCs gene expression.