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Life Sci Space Res (Amst). 2015 Jul;6:92-103. doi: 10.1016/j.lssr.2015.07.006. Epub 2015 Jul 17.

Concepts and challenges in cancer risk prediction for the space radiation environment.

Author information

1
New York University School of Medicine, New York, NY, USA. Electronic address: mhbarcellos-hoff@nyumc.org.
2
Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
3
University of Texas Southwestern Medical Center, Dallas, TX, USA.
4
Georgetown University, Washington, DC, USA.
5
Case Western Reserve University, Cincinnati, OH, USA.
6
Center of Cancer Systems Biology, Tufts University, Boston, MA, USA.
7
Duke University, Durham, NC, USA.
8
University of California, Irvine, CA, USA.
9
Emory University, Atlanta, GA, USA.
10
Colorado State University, Ft. Collins, CO, USA.

Abstract

Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program.

KEYWORDS:

Cancer; Galactic cosmic radiation; Mouse models; Radiation quality; Risk modeling

PMID:
26256633
DOI:
10.1016/j.lssr.2015.07.006
[Indexed for MEDLINE]
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