Radiation-Induced Gene Expression Changes Used for Biodosimetry and Clinical Outcome Prediction: Challenges and Promises

Abstract

As the war in Ukraine progresses, the radiological and nuclear threat has never been as real as now. The formation of life-threatening acute radiation syndrome (ARS), in particular after the deployment of a nuclear weapon or an attack on a nuclear power station, must be considered realistic. ARS is caused by massive cell death, leading to functional organ deficits and, via systemic inflammatory responses, finally aggravates into multiple organ failure. As a deterministic effect, the severity of the disease dictates the clinical outcome. Hence, predicting ARS severity via biodosimetry or alternative approaches appears straightforward. Because the disease occurs delayed, therapy starting as early as possible has the most significant benefit. A clinically relevant diagnosis should be carried out within the diagnostic time window of about 3 days after exposure. Biodosimetry assays providing retrospective dose estimations within this time frame will support medical management decision-making. However, how closely can dose estimates be associated with the later developing ARS severity degrees when considering dose as one among other determinants of radiation exposure and cell death? From a clinical/triage point of view, ARS severity degrees can be further aggregated into unexposed, weakly diseased (no acute health effects expected), and strongly diseased patient groups, with the latter requiring hospitalization as well as an early and intensive treatment. Radiation-induced gene expression (GE) changes occur early after exposure and can be quickly quantified. GE can be used for biodosimetry purposes. Can GE be used to predict later developing ARS severity degrees and allocate individuals to the three clinically relevant groups as well?