Lawrence Berkeley National Laboratory, Berkeley, CA, United States.
UT Southwestern Medical Center, Dallas, TX, United States.
Life Sci Space Res (Amst). 2016 Jun;9:19-47. doi: 10.1016/j.lssr.2016.05.004. Epub 2016 May 21.
Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing biomarkers and to evaluate the potential for biomarkers to inform models of post exposure cancer risk. Because cellular stress response pathways to space radiation and environmental carcinogens share common nodes, biomarker-driven risk models may be broadly applicable for estimating risks for other carcinogens.
稳健的预测模型对于管理放射性致癌风险至关重要。在复杂的深空环境中,慢性暴露于宇宙射线可能会使宇航员面临高癌症风险。为了估计这种风险,了解辐射诱导的细胞应激如何影响细胞命运决策以及这如何改变致癌风险至关重要。暴露于宇宙射线的重离子成分会根据暴露率、所遭受的损伤类型和个体易感性触发多种细胞变化。剂量、剂量率、辐射质量、能量和粒子通量的异质性导致了风险评估的复杂性。为了阐明这些因素中的每一个因素的影响,识别敏感的生物标志物至关重要,这些生物标志物可以作为稳健的个体癌症风险或其他暴露后长期健康后果的建模输入。生物标志物对剂量和剂量率的敏感性有限,以及纵向监测的复杂性,是增加风险预测模型输出不确定性的一些因素。在这里,我们批判性地评估了辐射暴露的候选早期和晚期生物标志物,并讨论了它们在预测细胞命运决策中的有用性。我们已经审查的一些生物标志物包括复杂的聚集 DNA 损伤、持续的 DNA 修复焦点、活性氧物种、染色体畸变和炎症。其他讨论的生物标志物,通常在暴露后更长的时间点进行检测,包括突变、染色体畸变、活性氧物种和端粒长度变化。我们讨论了生物标志物与不同潜在细胞命运的关系,包括增殖、凋亡、衰老和失去干性,这些命运可以传播基因组不稳定性并改变组织组成和导致细胞命运决策的潜在 mRNA 特征。我们的目标是突出选择生物标志物的重要因素,并评估生物标志物为暴露后癌症风险模型提供信息的潜力。由于空间辐射和环境致癌物的细胞应激反应途径具有共同的节点,基于生物标志物的风险模型可能广泛适用于估计其他致癌物的风险。