Biological markers of radiation exposure play a crucial role in the triage of suspected exposed persons following a radiation accident or incident. They can also estimate individual doses that enable assessment of late radiation effects in affected individuals. In recent years the gene expression assay has been shown to be a sensitive biological marker of radiation exposure with the potential to be used for truly individualised dosimetry. The possibility for this gene expression assay to be used in a large scale mass-casualty scenario has been proposed and tested in a recent intercomparison exercise. Classic cytogenetic techniques, and in particular the gold standard dicentric assay, have two main disadvantages: (1) lack of high-throughput and (2) delays of several days between blood sampling and the availability of results. Although more work needs to be done to further assess its suitability for triage purposes, it is clear that gene expression analysis in blood samples can provide valuable information, as there is a window of time (i.e. 12-48 hours) following radiation exposure where specific radiation-responsive genes have linear dose responses (0-5 Gy). Most work to date has focused on developing sensitive assays for studying gene expression modifications using state of the art technology, i.e. multiplex quantitative, digital polymerase chain reaction (qPCR) and molecular counting systems.

At Public Health England (PHE), recently established technology allows direct counting of nucleic acid molecules (DNA, mRNA, miRNA and lncRNA) without the need for enzymatic reaction or amplification steps hence reducing time for data collection. The system offers multiplexing capacity comparable to microarrays but with greater precision and sensitivity. Another unique advantage of this technology is that there is no need for long, time consuming bioinformatic analyses as the results are obtained as counted number of events. This new gene expression analysis technique has been assessed for radiation biodosimetry applications with promising results. Furthermore, gene expression has shown a high degree of promise as a marker for late effects of radiation, for instance normal tissue reactions following curative radiotherapy for breast cancer. Clinical data suggest that systemic inflammatory responses plays a critical role in the progression of radiation effects: for instance, the neutrophil-to-lymphocyte ratio represents a marker of systemic inflammation pre-treatment and is an independent prognostic factor useful for individual risk assessment in breast cancer patients undergoing radiotherapy. Genes relevant to inflammatory responses are thus interesting candidates for further investigation. Linearity of the transcriptional dose-response for specific radiation-responsive genes in ex vivo exposed human blood samples has recently been demonstrated for the first time, and inter-individual variability in the response after low doses and high doses exposures has been newly assessed. The logical next stage for biological development of the gene expression assay is to validate these new techniques with human blood samples exposed to radiation in vivo.

The use of samples from patients undergoing radiotherapy for validation of techniques has been gaining popularity in recent years. Sophisticated treatment planning for clinical radiotherapy leads to very accurate individual dose calculations that allow for validation of biological estimates of dose. The range of standard radiotherapy schedules chosen for inclusion in this study will provide a wide range of doses for assessment of the gene expression assay alone and in combination with the other cytogenetic assays, to simulate a range of potential exposure scenarios.

Peripheral blood samples will be taken with informed consent from patients undergoing standard radiotherapy before and during treatment for breast, lung, gastrointestinal and genitourinary tumours. Responses from panels of up to 800 coding and non-coding RNAs will be assessed in the samples using the nCounter system. Candidate genes identified by PHE, Columbia and/or in the literature as being specific to radiation responses will be included, together with genes relevant to systemic inflammatory responses, to identify transcriptional responses for a range of doses and exposures on an inter-individual basis. Data will be analysed using existing and new statistical tools focused on count data modelling. The intended outcome is identification of a radiation specific panel of genes to inform individual radiation responses and if the results are favourable, a large scale follow up to this proposed pilot is expected in due course.