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Abstract Radiation injury, either from radiotherapy or a mass-casualty event requires a health care system that can efficiently allocate resources to patients. We conducted a comprehensive transcriptome analysis of whole blood from a nonhuman primate model that received upper thoracic radiation (9.8–10.7 Gy). Blood samples were collected at multiple time points, extending up to 270 days post-irradiation with a minimum n = 6 for initial time points (Day 3-Day 40) and a total number of n = 28 primates. No males receiving the higher dose survived to Day 270. Using the Elastic Net model in R we found that pooling biomarkers from Day 3–21 increased our accuracy in discerning survival time, pleural effusion or dose compared to using biomarkers specific to a single day. For survival data, in predicting short term (less than 90 day), medium term (Day 91–269) or long-term survival (Day 270), prediction accuracy using only Day 3 data was 0.14 (95% Confidence Interval (CI) 0.1, 0.19) while pooled data for Male and Female was 0.76 (CI 0.69, 0.82). When pooled data was divided by biological sex, accuracy was 0.7 (CI 0.58, 0.8) for pooled data from Males and 0.84 (CI 0.76, 0.91) for Females. The development of RNA biomarkers as a tool to aid in clinical decision-making could significantly improve patient care in cases of radiation injury, whether from radiotherapy or mass-casualty events. Further validation and clinical translation of these findings could lead to improved patient care and management strategies in cases of radiation exposure.

Abstract In a mass radiation exposure, the healthcare system may rely on differential expression of miRNA to determine exposure and effectively allocate resources. To this end, miRNome analysis was performed on non-human primate serum after whole thorax photon beam irradiation of 9.8 or 10.7 Gy with dose rate 600 cGy/min. Serum was collected up to 270 days after irradiation and sequenced to determine immediate and delayed effects on miRNA expression. Elastic net based GLM methods were used to develop models that predicted the dose vs. controls at 81% accuracy at Day 15. A three-group model at Day 9 achieved 71% accuracy in determining if an animal would die in less than 90 days, between 90 and 269 days, or survive the length of the study. At Day 21, we achieved 100% accuracy in determining whether an animal would later develop pleural effusion. These results demonstrate the potential ability of miRNAs to determine thorax partial-body irradiation dose and forecast survival or complications early following whole thorax irradiation in large animal models. Future experiments incorporating additional doses and independent animal cohorts are warranted to validate these results. Development of a serum miRNA assay will facilitate the administration of medical countermeasures to increase survival and limit normal tissue damage following a mass exposure.