Non-targeted effects and the dose response for heavy ion tumor induction

被引:57
|
作者
Cucinotta, Francis A. [1 ]
Chappell, Lori J. [2 ]
机构
[1] NASA, Lyndon B Johnson Space Ctr, Space Radiat Program, Houston, TX 77058 USA
[2] USRA Div Life Sci, Houston, TX 77058 USA
关键词
Non-targeted effects; Radiation carcinogenesis; Space radiation; High LET effects; INDUCED GENOMIC INSTABILITY; SISTER-CHROMATID EXCHANGES; INITIATION-PROMOTION MODEL; IONIZING-RADIATION; ALPHA-PARTICLES; IN-VIVO; BIOLOGICAL EFFECTIVENESS; CHROMOSOMAL INSTABILITY; SPACE EXPLORATION; MYELOID-LEUKEMIA;
D O I
10.1016/j.mrfmmm.2010.01.012
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Non-targeted effects (NTE), including bystander effects in neighbor cells of cells directly hit by radiation tracks and genomic instability in the progeny of irradiated cells, challenge traditional radiation protection paradigms on Earth. It is thus of interest to understand how NTE could impact our understanding of cancer risks from galactic cosmic rays (GCR), which are comprised of high-energy protons and heavy ions. The most comprehensive data set for tumor induction by heavy ions is the induction of Harderian gland tumors in mice by high-energy protons, helium, neon, iron and niobium ions after doses of 0.05 to several Gy. We report on an analysis of these data that compares a dose response model motivated by the conventional targeted effects (TE) model to one which includes a dose response term descriptive of non-targeted effects (NTE) in cell culture. Results show that a NTE model provides an improved fit to the Harderian gland data over the TE model. Relative biological effectiveness (RBE) factors are shown to have much larger values at low doses based on a NTE model than the maximum RBE estimates based on estimates of the ratio of initial linear slopes of heavy ions compared to gamma-rays in the TE model. Our analysis provides important in vivo support for the deviation from linear dose responses at low doses for high LET radiation, which are best explained by a NTE model. Published by Elsevier B.V.
引用
收藏
页码:49 / 53
页数:5
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