Transcriptomics for radiation biodosimetry: progress and challenges

Abstract

Purpose: Transcriptomic-based approaches are being developed to meet the needs for large-scale radiation dose and injury assessment and provide population triage following a radiological or nuclear event. This review provides background and definition of the need for new biodosimetry approaches, and summarizes the major advances in this field. It discusses some of the major model systems used in gene signature development, and highlights some of the remaining challenges, including individual variation in gene expression, potential confounding factors, and accounting for the complexity of realistic exposure scenarios.

Conclusions: Transcriptomic approaches show great promise for both dose reconstruction and for prediction of individual radiological injury. However, further work will be needed to ensure that gene expression signatures will be robust and appropriate for their intended use in radiological or nuclear emergencies.

Keywords: Ionizing radiation; biodosimetry; dose reconstruction; gene expression; radiological triage.

Figure 1.

The use and intercomparison of multiple models is needed for the development and validation of gene expression signatures for radiation biodosimetry. As experiments cannot be performed directly in humans, much development must rely on the comparison of in vivo versus ex vivo models, and of human versus animal models. (Figure created with BioRender.com.)

Figure 2.

Genes appearing in two or more consensus signature studies. A black box indicates a gene selected by the corresponding study. An additional 11 genes were included only by Li et al. (2017), 6 by Lacombe et al. (2018), 19 by Zhao et al. (2018), and 16 by Ghandhi et al. (2019). The complete listing of all these genes is available in Supplementary File 1.