Table 1.
Section | Presenter | Key messages | |
---|---|---|---|
Biodosimetry | |||
C. Badie | 1. In a large scale event, high-throughput measurements are required for individual dose estimation for radiobiological triage | ||
2. New sequencing technology: nanopore sequencing to detect radiation-responsive genes in human peripheral blood: portable, rapid, real-time biodosimetry platform | |||
3. Identification of specific FDXR transcript variants responsive to ionizing radiation (IR) –>in vivo validation in blood of radiotherapy patients | |||
4. High responsiveness of FDXR-201 and FDXR-208 | |||
5. New class of gene based radiation exposure markers: FDXR-218 and FDXR-219 without endogenous expression, but a clear detection after IR | |||
B. Terbrueggen | see below | ||
S. Amundson | 1. Development of algorithms to allow translation between animal and human responses, and between in vitro and in vivo responses | ||
2. Exposure modalities relevant for anticipating exposure scenarios: impact of relevant exposure factors such as dose rate, presence of neutrons, or exposure to internal emitters | |||
3. Gene expression (GE) approach shows great promise for dose reconstruction and injury prediction | |||
4. Better understanding and integration of factors that may impact both an individual’s physiological response to radiation and their GE response still needed | |||
P. Ostheim | 1. GE changes in the peripheral blood (mRNA and miRNA) provide indications of the exposure pattern and a suggestion of the percentage of the exposed body area | ||
2. Dose-dependent GE responses to incorporated radionuclides (223Ra) | |||
P. Rogan | 1. GE signatures for radiation exposure are susceptible to nonspecific changes caused by common, confounding hematological disorders | ||
2. Strategy: necessity to identify and mitigate confounder up front, include confounders as controls, exclude genes responsible for false positive calls | |||
A. Evans | 1. Transcriptional biomarker can be used for assessing internalized 131I –>differentiate exposed from unexposed | ||
2. Dose and time dependent GE signature for internalized 131I over a period of 15 days after exposure | |||
D. Bazyka | 1. Examination of 314 Chernobyl cleanup workers, and staff of the ‘Shelter’ and exclusion zone with various doses of external irradiation | ||
2. Demonstration of a dose–response relationship on a molecular level with promising results for biological dosimetry | |||
S. Ghandhi | Examination of molecular response to internal radiation using mice injected with 137Cs –>sustained impact of dose and low dose-rate on immune response | ||
Effect prediction | |||
P. Ostheim | 1. Dose estimates are a ‘surrogate’ for prediction of acute health effects | ||
2. Concept of radiation-related biomarkers for effect prediction: integration of multiple radiation exposure characteristics as well as cell- and molecular-based processes like individual radiosensitivity via molecular changes lying downstream of the exposure and upstream of the effect | |||
3. Integrative approach for more robust and simplified prediction of later occurring acute health effects | |||
M. Gomolka | 1. A radiation specific gene signature was identified in uranium workers 20–30 years after exposure | ||
2. Low and high dose exposure groups of uranium workers can by distinguished by gene expression analysis | |||
3. Deregulated genes are involved in immune response pathways, including interferon and pro-inflammatory responses | |||
High-throughput and point-of-care (POC) diagnostics | |||
B. Terbrueggen | 1. REDI-Dx: high throughput and blood-based biodosimetry test system | ||
2. Measurement of radiation responsive mRNA transcripts for estimation of absorbed radiation dose, extremely low false positive rate | |||
3. Up to 1200 samples within 24 hours and first results are available after 6.5 hours | |||
4. Only biodosimetry test for which the performance has been validated | |||
F. Zenhausern | 1. Advances of paper-based vertical flow multiplex assay system (VeriFAST) for rapid biodosimetry in a mobile environment | ||
2. Simple user interface for self-collection and testing on a low-cost basis | |||
3. High sensitivity for a variety of nucleic acids to proteins multiplex panels of biosignatures for different bioeffects | |||
4. Future work and validation needed | |||
C. Badie | Nanopore sequencing: portable, real-time and high-throughput biodosimetry platform for assessing radiation exposure (see above) | ||
P. Ostheim | 1. Current progress in the development of point-of-care device based on microfluidic technology as a stand-alone platform | ||
2. Limitations in the linearity of GE values miniaturization restrictions have to be overcome | |||
Low-level radiation | |||
L. Kaatsch | 1. Diagnostic and interventional radiology provides alternative exposure model for LLR experiments, here computed tomography | ||
2. Modern CT diagnostics evoke genotoxic alterations with deregulation of well-known genomic biomarkers and DNA damage | |||
3. No increased biological effectiveness of varying X-ray spectra in dual-energy CT | |||
G. Woloschak | 1. Irradiated animals tissue archive hosted at Northwestern University: repository of samples and data collected in the course of large-scale animal studies –>samples and existing datasets available upon request (janus.northwestern.edu) | ||
2. Difficult to do an analysis for the animals with very low dose rates 3. Mostly paraffin embedded tissue of differing quality, mRNA measurements challenging and miRNA measurements promising |
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Methods | |||
P. Ostheim | 1. Saliva, as a noninvasive easily accessible biofluid, contains presumably RNA biomarkers for prediction and diagnosis of several diseases and is poorly characterized for radiation biodosimetry | ||
2. Identification of challenges (high yield of bacterial RNA and low yield of human mRNA) and development of a robust methodology to process human whole saliva for GE analysis | |||
3. Next step: saliva samples from radiotherapy patients used to evaluate the applicability of this workflow for GE analysis for its use in a radiobiological context | |||
R. Ullmann | Introduction of a novel RNASeq analysis strategy for whole genome exon- and not gene-based GE screens: rapid, budget-friendly and reproducible | ||
S. Schüle | 1. Discrepancies in baseline and height of radiation-induced differential GE of commonly used radiation-induced genes have been observed among laboratories and in the validation of GE NGS data (gene-based examination) using qRT-PCR (exon-based examination). | ||
2. Identifying radiation responsive exons and primer-probe designs of genes widely used for biodosimetry and ARS prediction | |||
3. More meaningful comparison of NGS and qRT-PCR measurements (both exon-based) | |||
M. Riego | Alternative transcript or splicing variants of known radiation-responsive genes can be used as a potential source of individually variable response to certain radiation qualities at an exon-level |
The table is ordered per main section of the key session ‘Gene expression for biodosimetry and effect prediction purposes: promise, pitfalls and future directions’ at ConRad 2021 as well as presenters. It summarizes the key contents of each presentation. Details are provided in the text of the manuscript.