Document Detail


Defining molecular and cellular responses after low and high linear energy transfer radiations to develop biomarkers of carcinogenic risk or therapeutic outcome.
MedLine Citation:
PMID:  23032890     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
ABSTRACT: The variability in radiosensitivity across the human population is governed in part by genetic factors. The ability to predict therapeutic response, identify individuals at greatest risk for adverse clinical responses after therapeutic radiation doses, or identify individuals at high risk for carcinogenesis from environmental or medical radiation exposures has a medical and economic impact on both the individual and society at large. As radiotherapy incorporates particles, particularly particles larger than protons, into therapy, the need for such discriminators, (i.e., biomarkers) will become ever more important. Cellular assays for survival, DNA repair, or chromatid/chromosomal analysis have been used to identify at-risk individuals, but they are not clinically applicable. Newer approaches, such as genome-wide analysis of gene expression or single nucleotide polymorphisms and small copy number variations within chromosomes, are examples of technologies being applied to the discovery process. Gene expression analysis of primary or immortalized human cells suggests that there are distinct gene expression patterns associated with radiation exposure to both low and high linear energy transfer radiations and that those most radiosensitive are discernible by their basal gene expression patterns. However, because the genetic alterations that drive radio response may be subtle and cumulative, the need for large sample sizes of specific cell or tissue types is required. A systems biology approach will ultimately be necessary. Potential biomarkers from cell lines or animal models will require validation in a human setting where possible and before being considered as a credible biomarker some understanding of the molecular mechanism is necessary.
Authors:
Michael Story; Liang-Hao Ding; William A Brock; K Kian Ang; Ghazi Alsbeih; John Minna; Seongmi Park; Amit Das
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Health physics     Volume:  103     ISSN:  1538-5159     ISO Abbreviation:  Health Phys     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-10-03     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  2985093R     Medline TA:  Health Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  596-606     Citation Subset:  IM    
Affiliation:
*University of Texas Southwestern Medical Center, Dallas, TX 75390; †University of Texas M.D. Anderson Cancer Center, Houston, TX 77030; ‡King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia.
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Track-structure simulations for charged particles.
Next Document:  Genetic susceptibility: radiation effects relevant to space travel.