Dataset Information


Prediction of in vivo radiation dose status in radiotherapy patients using ex vivo and in vivo gene expression signatures.

ABSTRACT: After a large-scale nuclear accident or an attack with an improvised nuclear device, rapid biodosimetry would be needed for triage. As a possible means to address this need, we previously defined a gene expression signature in human peripheral white blood cells irradiated ex vivo that predicts the level of radiation exposure with high accuracy. We now demonstrate this principle in vivo using blood from patients receiving total-body irradiation (TBI). Whole genome microarray analysis has identified genes responding significantly to in vivo radiation exposure in peripheral blood. A 3-nearest neighbor classifier built from the TBI patient data correctly predicted samples as exposed to 0, 1.25 or 3.75 Gy with 94% accuracy (P < 0.001) 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. The demonstration that ex vivo irradiation is an appropriate model that can provide meaningful prediction of in vivo exposure levels, and that the signatures are robust across diverse disease states and independent sample sets, is an important advance in the application of gene expression for biodosimetry.

PROVIDER: S-EPMC3134561 | BioStudies |

REPOSITORIES: biostudies

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