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Mutagen challenge and DNA repair assays have been used in case-control studies for nearly three decades to assess human cancer risk. The findings still engender controversy because blood was drawn after cancer diagnosis so the results may be biased, a type called 'reverse causation'. We therefore used Epstein-Barr virus-transformed lymphoblastoid cell lines established from prospectively collected peripheral blood samples to evaluate lung cancer risk in relation to three DNA repair assays: alkaline Comet assay, host cell reactivation (HCR) assay with the mutagen benzo[a]pyrene diol epoxide and the bleomycin mutagen sensitivity assay. Cases (n = 117) were diagnosed with lung cancer between 0.3 and 6 years after blood collection and controls (n = 117) were frequency matched on calendar year and age at blood collection, gender and smoking history; all races were included. Case and control status was unknown to laboratory investigators. In unconditional logistic regression analyses, statistically significantly increased lung cancer odds ratios (OR(adjusted)) were observed for bleomycin mutagen sensitivity as quartiles of chromatid breaks/cell [relative to the lowest quartile, OR = 1.2, 95% confidence interval (CI): 0.5-2.5; OR = 1.4, 95% CI: 0.7-3.1; OR = 2.1, 95% CI: 1.0-4.4, respectively, P(trend) = 0.04]. The magnitude of the association between the bleomycin assay and lung cancer risk was modest compared with those reported in previous lung cancer studies but was strengthened when we included only incident cases diagnosed more than a year after blood collection (P(trend) = 0.02), supporting the notion the assay may be a measure of cancer susceptibility. The Comet and HCR assays were unrelated to lung cancer risk.

The overwhelming majority of studies that have found increased cancer risk associated with functional deficits in DNA repair used a case-control design, in which measurements were made after cancer diagnosis. However, there are concerns about whether the cancer itself or cancer treatment affected the conclusions (reverse causation bias). We assessed the effect of cancer diagnosis among 26 breast cancer controls who had blood collected during 2001 to 2003 and again in 2005 to 2006 after being diagnosed with cancer. Using the alkaline comet assay, we quantified DNA damage in untreated lymphoblastoid cell lines. Comet distributed moment, olive tail moment, percentage of DNA in tail, and comet tail length were summarized as the geometric mean of 100 cells. For comet distributed moment, olive tail moment, tail DNA, and tail length, the proportions of women with before diagnosis values higher than after diagnosis were 65%, 50%, 50%, and 46%, respectively. We found no significant differences in the before or after diagnosis mean comet values. Median cut-points were determined from the before diagnosis distribution, and we used conditional logistic regression to calculate odds ratios (OR) and upper 95% bounds of the confidence intervals. ORs ranged from 0.6 to 0.9 with upper confidence interval bounds of 1.9 and 2.6, meaning biased ORs above 2.6 are unlikely. We found no evidence that reverse causation bias is an important concern in case-control studies using the comet assay applied to cell lines collected after cancer diagnosis. More work is needed to characterize the effect of cancer diagnosis on other phenotypic assays.

Variation in the detection, signaling, and repair of DNA damage contributes to human cancer risk. To assess capacity to modulate endogenous DNA damage among radiologic technologists who had been diagnosed with breast cancer and another malignancy (breast-other, n=42), early-onset breast cancer (early-onset, age or=75% versus below the median, age-adjusted) was most consistently associated with the highest odds ratios in the breast-other, early-onset, and thyroid cancer groups (with risk increased 10-, 5- or 19-fold, respectively, with wide confidence intervals) and decreased risk among the hyper-normal group. For the other three comet measures, risk of breast-other was elevated approximately three-fold. Risk of early-onset breast cancer was mixed and risk of thyroid cancer ranged from null to a two-fold increase. The hyper-normal group showed decreased odds ratios for tail DNA and OTM, but not CDM. DNA damage, as estimated by all comet measures, was relatively unaffected by survival time, reproductive factors, and prior radiation treatment. We detected a continuum of endogenous DNA damage that was highest among cancer cases, less in controls, and suggestively lowest in hyper-normal individuals. Measuring this DNA damage phenotype may contribute to the identification of susceptible sub-groups. Our observations require replication in a prospective study with a large number of pre-diagnostic samples.

Do second primary cancers in humans arise from radiation-induced somatic genomic instability after radiotherapy for the first malignancy? The amount of truly pertinent human information on this issue is sparse, leading to the conclusion that we cannot confirm or refute that instability induction by radiation is involved. However, the in vitro findings of radiation-induced genomic instability through bystander effects or increased mutation rates in cell progeny of apparently normal but irradiated cells are provocative and their transferability to human in vivo biology deserves further investigation. We describe possible animal and human studies to stimulate ideas, but the collaborative commitment of multiple large institutions to tumor tissue procurement and retrieval will be essential. In addition, detecting the temporal progression of genomic instability and identifying the salient genetic events as being radiation-induced will be pivotal. Execution of some of the studies suggested is not possible now, but applying next-generation methods could bring the concepts to fruition. As nearly one in 10 cancer diagnoses are second (or higher) malignancies, it is important to understand the contribution of radiotherapy to second cancer induction and pursue well-coordinated efforts to determine the role of induced genomic instability.