Fendler Wojciech, Malachowska Beata, Meghani Khyati, Konstantinopoulos Panagiotis A, Guha Chandan, Singh Vijay K, Chowdhury Dipanjan
Department of Biostatistics and Translational Medicine, Medical University of Lodz, Lodz 91-738, Poland.
Department of Radiation Oncology, Harvard Medical School, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
Sci Transl Med. 2017 Mar 1;9(379). doi: 10.1126/scitranslmed.aal2408.
Effective planning for the medical response to a radiological or nuclear accident is complex. Because of limited resources for medical countermeasures, the key would be to accurately triage and identify victims most likely to benefit from treatment. We used a mouse model system to provide evidence that serum microRNAs (miRNAs) may effectively predict the impact of radiation on the long-term viability of animals. We had previously used nonhuman primates (NHPs) to demonstrate that this concept is conserved and serum miRNA signatures have the potential to serve as prediction biomarkers for radiation-induced fatality in a human population. We identified a signature of seven miRNAs that are altered by irradiation in both mice and NHPs. Genomic analysis of these conserved miRNAs revealed that there is a combination of seven transcription factors that are predicted to regulate these miRNAs in human, mice, and NHPs. Moreover, a combination of three miRNAs (miR-133b, miR-215, and miR-375) can identify, with nearly complete accuracy, NHPs exposed to radiation versus unexposed NHPs. Consistent with historical data, female macaques appeared to be more sensitive to radiation, but the difference was not significant. Sex-based stratification allowed us to identify an interaction between gender and miR-16-2 expression, which affected the outcome of radiation exposure. Moreover, we developed a classifier based on two miRNAs (miR-30a and miR-126) that can reproducibly predict radiation-induced mortality. Together, we have obtained a five-miRNA composite signature that can identify irradiated macaques and predict their probability of survival.
针对放射性或核事故进行有效的医疗应对规划十分复杂。由于医疗应对措施的资源有限,关键在于准确分诊并识别最有可能从治疗中受益的受害者。我们使用小鼠模型系统来提供证据,证明血清微小核糖核酸(miRNA)可能有效地预测辐射对动物长期生存能力的影响。我们之前使用非人类灵长类动物(NHP)证明了这一概念具有保守性,血清miRNA特征有潜力作为人群中辐射致死的预测生物标志物。我们鉴定出了七个在小鼠和NHP中均受辐射影响而发生改变的miRNA特征。对这些保守miRNA的基因组分析表明,有七种转录因子的组合被预测可在人类、小鼠和NHP中调控这些miRNA。此外,三种miRNA(miR-133b、miR-215和miR-375)的组合能够几乎完全准确地识别受辐射的NHP与未受辐射的NHP。与历史数据一致,雌性猕猴似乎对辐射更敏感,但差异并不显著。基于性别的分层使我们能够识别性别与miR-16-2表达之间的相互作用,这影响了辐射暴露的结果。此外,我们开发了一种基于两种miRNA(miR-30a和miR-126)的分类器,可重复预测辐射诱导的死亡率。我们共同获得了一个五miRNA复合特征,能够识别受辐射的猕猴并预测其存活概率。