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The article evaluates the effects of cancer diagnosis on endogenous deoxyribonucleic acid (DNA) damage. It assesses the effect of cancer diagnosis among 26 individuals with breast cancer with blood drawn between 2001 and 2003 and again in 2005 and 2006 after a diagnosis of cancer. The comet assay in prediagnostic and postdiagnostic samples from these people shows no effect of cancer diagnosis on the DNA damage and found slight evidence of reverse causation bias being an important concern in case-control studies.

Abstract: Elucidating the relationship between polymorphic sequences and risk of common disease is a challenge. For example, although it is clear that variation in DNA repair genes is associated with familial cancer, aging and neurological disease, progress toward identifying polymorphisms associated with elevated risk of sporadic disease has been slow. This is partly due to the complexity of the genetic variation, the existence of large numbers of mostly low frequency variants and the contribution of many genes to variation in susceptibility. There has been limited development of methods to find associations between genotypes having many polymorphisms and pathway function or health outcome. We have explored several statistical methods for identifying polymorphisms associated with variation in DNA repair phenotypes. The model system used was 80 cell lines that had been resequenced to identify variation; 191 single nucleotide substitution polymorphisms (SNPs) are included, of which 172 are in 31 base excision repair pathway genes, 19 in 5 anti-oxidation genes, and DNA repair phenotypes based on single strand breaks measured by the alkaline Comet assay. Univariate analyses were of limited value in identifying SNPs associated with phenotype variation. Of the multivariable model selection methods tested: the easiest that provided reduced error of prediction of phenotype was simple counting of the variant alleles predicted to encode proteins with reduced activity, which led to a genotype including 52 SNPs; the best and most parsimonious model was achieved using a two-step analysis without regard to potential functional relevance: first SNPs were ranked by importance determined by random forests regression (RFR), followed by cross-validation in a second round of RFR modeling that included ever more SNPs in declining order of importance. With this approach six SNPs were found to minimize prediction error. The results should encourage research into utilization of multivariate analytical methods for epidemiological studies of the association of genetic variation in complex genotypes with risk of common diseases. [Copyright &y& Elsevier]

Purpose: To conduct a literature review of candidate protein biomarkers for individual radiation biodosimetry of exposure to ionizing radiation.Materials and methods: Reviewed ?300 publications (1973 – April 2006) that reported protein effects in mammalian systems after either in vivo or in vitro radiation exposure.Results: We found 261 radiation-responsive proteins including 173 human proteins. Most of the studies used high doses of ionizing radiation (>4 Gy) and had no information on dose- or time-responses. The majority of the proteins showed increased amounts or changes in phosphorylation states within 24 h after exposure (range: 1.5- to 10-fold). Of the 47 proteins that are responsive at doses of 1 Gy and below, 6 showed phosphorylation changes at doses below 10 cGy. Proteins were assigned to 9 groups based on consistency of response across species, dose- and time-response information and known role in the radiation damage response.Conclusions: ATM (Ataxia telengiectasia mutated), H2AX (histone 2AX), CDKN1A (Cyclin-dependent kinase inhibitor 1A), and TP53 (tumor protein 53) are top candidate radiation protein biomarkers. Furthermore, we recommend a panel of protein biomarkers, each with different dose and time optima, to improve individual radiation biodosimetry for discriminating between low-, moderate-, and high-dose exposures. Our findings have applications for early triage and follow-up medical assessments. [ABSTRACT FROM AUTHOR]

Understanding the significance of somatic mutations requires knowledge of the mutations that occur in vivo in healthy people. The molecular characterization of mutations in the hypoxanthine phosphoribosyltransferase (hprt) gene in 217 independent T-lymphocyte mutants from 172 donors, including smoking and non-smoking males and females, reveals a broad spectrum of in vivo somatic mutation occurring in a population of healthy people. Identification of the DNA alteration in individual mutant clones was accomplished using either one or a combination of multiplex polymerase chain reaction analysis of genomic DNA, sequencing of cDNA, and genomic DNA sequencing. The total spectrum consists of 59% (128/217) base substitutions: 126 simple and two tandem CC>TT base substitutions; 39% (85/217) deletion/insertion type mutations: 30 frameshifts, 26 small (3–200 basepairs) and 27 large deletions, and two duplications; and the remaining 2% (4/217) complex mutations involving the deletion of one to 11 basepairs which are replaced by 1 to 10 basepairs. No significant difference was detected between the base substitution spectra for the smokers and the non-smokers. Analysis of the number of mutations occurring at any one base position led to the identification of three hotspots for mutations at basepairs 197, 508 and 617, in the hprt gene coding region. Spontaneous deamination of CpG may be implicated in the creation of basepair 508 as a hotspot since all mutations detected are C>T transitions resulting in the nonsense mutation, TAG. At basepairs 197 and 617 both G>T transversions and G>A transitions were found indicating that at least two mechanisms were involved in creating mutations at these positions. Comparison of the mutation spectra from two populations can provide insight into the origin of the mutations. This study provides an excellent base for comparison of mutation spectra in other human populations. [ABSTRACT FROM PUBLISHER]