Introduction Ionising radiation (IR) is a ubiquitous environmental agent whose effects on organism are well established. A direct interaction of IR with human cells causes a variety of biological effects including neoplastic transformation. In this context, physical and biological dosimetry could be a key tool for individual monitoring of the absorbed IR. However, since the current dosimetry approaches are not tailored to distinguish the early response and long-term pro-oncogenic effects of low-dose (LD)IR the discovery of inherent biomarkers represents a priority area. We hypothesised that changes of gene expression profiles in blood cells may occur during occupational exposure to LDIR and that the identification of these changes could be potentially useful in the early recognition of pro-oncogenic phenotypes.
Methods We included 9 workers exposed to IR and 3 non-exposed workers, all equipped with dosimeter. Exclusion criteria were smoking, history of cancer diagnosis before occupational exposure, high blood pressure medication and intake of paracetamol. Blood cells were collected from each worker and used to evaluate transcriptional expression of a panel of 624 cancer-related genes by using the Real-Time PCR OpenArray technology.
Results The analysis in radiation workers exposed showed the over-expression of some genes involved in the progression of certain types of tumours and an evident alteration in the expression of the gene involved in a way of regulation, known to predispose to genomic instability and tumorigenesis induced by IR. Intriguingly, we also found that among radiation workers 3 subjects, with occupationally recognised thyroid cancer displayed an up-regulation of the rearranged during transfection (RET) gene, which has been found previously overexpressed in subjects with radiation-induced thyroid cancers.
Discussion Our preliminary data would indicate that exposure to LDIR is able to alter the expression of pro-tumour genes in blood cells, posing questions and opening new scenarios towards a ‘personalised radioprotection’ model.
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