We found that deficient DNA repair capacity is associated with an increased risk of cancer using meta-analytic methods that summarized data from 55 studies. The magnitude of the associations between DNA repair phenotype and cancer risk is much stronger compared with the effect size measured by genetic variants of DNA repair genes (ORs range from 1 to 2)10. Accurately identifying high-risk individuals is essential for effective primary prevention (e.g., chemoprevention)11, and for risk-based screening options12 which emphasize risk rather than age for optimal screening outcomes. For example, many different risk models exist for breast cancer including the Breast Cancer Risk Assessment Tool (BCRAT, or Gail model)13,14, IBIS15, BOADICEA16 and risk models exist for other common cancers including colorectal and prostate cancer. However, most cancer risk models currently have only modest discriminatory accuracy at the individual level (AUC ~ .6-.65).17 Modest improvements have been achieved by incorporating genetic variants18 and epigenetic markers19 into cancer risk prediction models. Although these studies suggest that some gains can be made through incorporating non-invasive blood markers, no cancer risk model has yet considered incorporating non-invasive phenotypic markers that have substantially greater magnitude of association with breast cancer risk. DNA repair plays an essential role in preventing mutations and genomic instability that are critical for the effects of carcinogen exposure1. Our meta-analysis concluded that individuals with lower DNA repair capacity are at increased susceptibility to cancer development and the capacity to repair DNA damage is therefore an important factor to consider in risk assessment.
When DNA repair machinery is not working efficiently, the generation of DNA damage and mutations leads to carcinogenic transformation and, eventually, to cancer1. We found lower DNA repair phenotype was statistically significantly associated with all cancer types. This suggests that measuring DNA repair phenotype can potentially identify high-risk individuals for effective primary prevention, and for risk-based screening options. However, to potentially integrate DNA repair phenotyping data into risk assessment, more studies are needed to examine intra-individual variability in DNA repair phenotyping over time, to assess whether a single measure at the time of first breast screening is useful or whether multiple measures over time are needed.
In our meta-analysis, we found there was significant heterogeneity across studies, which might be related to different cancer types and different DNA repair phenotyping assays. A potential explanation for why we observed heterogeneity across studies of different cancer types and assays might be related to the complex interplay of genetic and environmental factors in most cancer types. There are substantial differences in the mutational burden between cancer types20. Analysis of the mutation burden of 27 tumor types found that tumor types with higher somatic mutation burden such as melanoma and lung cancers are the result of environmental exposure20. In addition, there is substantial inter-individual variation in tumor mutational burden within individual tumor types20. These observations suggest that both genetic and environmental factors might be involved in most human cancers.
There are numerous methods for measuring DNA repair directly, and each has its strengths and weaknesses21. Most of the assays such as the host-cell reactivation and mutagen sensitivity assays measure nucleotide excision repair capacity22. Nucleotide excision repair eliminates a wide variety of different forms of DNA damage and especially deals with bulky DNA damage/adducts induced by chemical carcinogens and dimers induced by ultraviolet light23. In addition to nucleotide excision repair, other major DNA repair pathways including base excision repair, mismatch repair, homologous recombination and non-homologous end joining are active throughout the different stages of the cell cycle. In our analysis, we found the estimated effect sizes were consistent and of high magnitude across different assays and pathways.
Recently, several assays have been developed to measure multiple repair pathways24. Moreover, functional DNA repair assays are fundamentally more powerful than genotyping. But currently, there are few DNA repair assays available for epidemiologic studies because the assays are labor and time intensive. Thus studies to date are limited and there are no large-scale prospective studies or high-throughput phenotypic assays25. The resultant lack of population studies integrating these potentially informative measures with other factors limits our understanding of the fundamental cellular response to environmental exposures. However, recently our group developed a high-throughput γ-H2AX assay based on imaging flow cytometry (IFC) which is a faster and more efficient technique for assessing global double strand break repair capacity26. This IFC-based γ-H2AX protocol may provide a practical and high-throughput platform for measurements of individual global DNA double strand break repair capacity which can facilitate precision medicine by predicting individual radiosensitivity and risk of developing adverse effects related to radiotherapy treatment.
For over four decades, cancer incidence has been increasing the most in adults under 55 years in the U.S. In our recent report based on Surveillance Epidemiology and End Reports (SEER) data, we found overall cancer incidence increased by 1.15% per year in 25- to 39-year-old women and by 0.46% per year in 25- to 39-year-old men27. Moreover, we forecasted that overall cancer incidence will increase by an additional 11–12% by 2030 in 25- to 39-year-old women and men27. However, most cancer screening guidelines do not recommend screening begins until after age 40 (e.g., mammography is recommended to start at 45 years of age for breast cancer screening)28.
Therefore, developing tools that can accurately predict risk of early onset cancer might be a key factor in addressing these trends. However most of the studies that have been conducted have not stratified by age. However, our previous study compared DNA double strand break repair capacity between breast cancer cases and their unaffected sister controls29. We found there was an association between lower DNA repair capacity and breast cancer risk, and that the largest differences in the mean value of repair between cases and controls were observed in women younger than 40 years29. Moreover, cases younger than 40 years had lower DNA repair capacity than older cases. Results from our sibling studies23,24 suggest that phenotypic measures will be an important determinant of risk over and beyond family history. More studies are needed to better understand if deficiency in DNA repair capacity is an important risk factor for early onset cancer specifically.
Moreover, most studies use PBMC as surrogate tissues, assuming PBMC are a legitimate surrogate for DNA repair in other tissues. The correlation between DNA repair capacity between target and blood is limited to one study that found a good correlation between OGG activity in blood and lung tissues from the same individual30. Although assays using blood samples are more feasible to implement in a clinic setting, more studies needs to evaluate the correlation of DNA repair phenotype between blood and target tissues using different assays.
Cancer susceptibility is inherently complex, and polygenetic risk scores using genetic data have been established and show improvement in prediction accuracy for cancer31. Our meta-analysis supports a strong association between global repair capacity and cancer risk. Measuring DNA repair capacity is a potentially powerful marker to identify subgroups at high risk of cancer. Measuring overall DNA repair capacity markers in blood may be one way of understanding the role of DNA damage and repair in cancer risk and might provide intermediate outcome markers in prevention studies. Measuring DNA repair capacity may provide a potentially robust to identify individuals that can may benefit from individual-based health risk assessment and personalized risk reduction strategies. Established high-through measurement of DNA repair phenotyping may also be more feasible to implement in a clinic setting as opposed to complex genomic and proteomic approaches. Incorporating DNA repair phenotype into risk models may improve model discriminatory accuracy but will need large-scale prospective evidence to understand the role of timing and age at measurement and cancer screening initiation.