Transcriptional dosimetry is an emergent field of radiobiology aimed at developing robust methods for detecting and quantifying absorbed doses using radiation-induced fluctuations in gene expression. A combination of RNA sequencing, array-based and quantitative PCR transcriptomics in cellular, murine and various ex vivo human models has led to a comprehensive description of a fundamental set of genes with demonstrable dosimetric qualities. However, these are yet to be validated in human tissue due to the scarcity of in situ-irradiated source material. This represents a major hurdle to the continued development of transcriptional dosimetry. In this study, we present a novel evaluation of a previously reported set of dosimetric genes in human tissue exposed to a large therapeutic dose of radiation. To do this, we evaluated the quantitative changes of a set of dosimetric transcripts consisting of FDXR, BAX, BCL2, CDKN1A, DDB2, BBC3, GADD45A, GDF15, MDM2, SERPINE1, TNFRSF10B, PLK3, SESN2 and VWCE in guided pre- and post-radiation (2 weeks) prostate cancer biopsies from seven patients. We confirmed the prolonged dose-responsivity of most of these transcripts in in situ-irradiated tissue. BCL2, GDF15, and to some extent TNFRSF10B, were markedly unreliable single markers of radiation exposure. Nevertheless, as a full set, these genes reliably segregated non-irradiated and irradiated tissues and predicted radiation absorption on a patient-specific basis. We also confirmed changes in the translated protein product for a small subset of these dosimeters. This study provides the first confirmatory evidence of an existing dosimetric gene set in less-accessible tissues—ensuring peripheral responses reflect tissue-specific effects. Further work will be required to determine if these changes are conserved in different tissue types, post-radiation times and doses.
|Number of pages||9|
|Journal||Radiation and Environmental Biophysics|
|Publication status||Published - Aug 2018|
Monash Proteomics & Metabolomics Facility
Ralf Schittenhelm (Manager)Faculty of Medicine Nursing and Health Sciences Research Platforms