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- Li, Jingmei, et al.
(författare)
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Breast cancer genetic risk profile is differentially associated with interval and screen-detected breast cancers
- 2015
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Ingår i: Annals of Oncology. - Stockholm : Karolinska Institutet, Dept of Medical Epidemiology and Biostatistics. - 0923-7534. ; 26:3, s. 517-522
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Tidskriftsartikel (refereegranskat)abstract
- Background: Polygenic risk profiles computed from multiple common susceptibility alleles for breast cancer have been shown to identify women at different levels of breast cancer risk. We evaluated whether this genetic risk stratification can also be applied to discriminate between screen-detected and interval cancers, which are usually associated with clinicopathological and survival differences. Patients and methods: A 77-SNP polygenic risk score (PRS) was constructed for breast cancer overall and by estrogen-receptor (ER) status. PRS was inspected as a continuous (per standard deviation increment) variable in a case-only design. Modification of the PRS by mammographic density was evaluated by fitting an additional interaction term. Results: PRS weighted by breast cancer overall estimates was found to be differentially associated with 1,865 screen-detected and 782 interval cancers in the LIBRO-1 study (age-adjusted ORperSD [95% confidence interval]=0.91 [0.83-0.99], p=0.023). The association was found to be more significant for PRS weighted by ER-positive breast cancer estimates (ORperSD=0.90 [0.82-0.98], p=0.011). This result was corroborated by two independent studies (combined ORperSD=0.87 [0.76-1.00], p=0.058) with no evidence of heterogeneity. When enriched for “true” interval cancers among nondense breasts, the difference in the association with PRS in screen-detected and interval cancers became more pronounced (ORperSD=0.74 [0.62-0.89], p=0.001), with a significant interaction effect between PRS and mammographic density (pinteraction=0.017). Conclusion: To our knowledge, this is the first report looking into the genetic differences between screendetected and interval cancers. It is an affirmation that the two types of breast cancer may have unique underlying biology.
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| 2. |
- Mavaddat, Nasim, et al.
(författare)
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Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants
- 2015
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 1460-2105 .- 0027-8874. ; 107:5, s. 036-036
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Tidskriftsartikel (refereegranskat)abstract
- Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.
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| 3. |
- Trinh, Thang, et al.
(författare)
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Background risk of breast cancer and the association between physical activity and mammographic density
- 2015
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Ingår i: Breast Cancer Research. - : BIOMED CENTRAL LTD. - 1465-5411 .- 1465-542X. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Introduction High physical activity has been shown to decrease the risk of breast cancer, potentially by a mechanism that also reduces mammographic density. We tested the hypothesis that the risk of developing breast cancer in the next 10 years according to the Tyrer-Cuzick prediction model influences the association between physical activity and mammographic density. Methods We conducted a population-based cross-sectional study of 38,913 Swedish women aged 4074 years. Physical activity was assessed using the validated web-questionnaire Active-Q and mammographic density was measured by the fully automated volumetric Volpara method. The 10-year risk of breast cancer was estimated using the Tyrer-Cuzick (TC) prediction model. Linear regression analyses were performed to assess the association between physical activity and volumetric mammographic density and the potential interaction with the TC breast cancer risk. Results Overall, high physical activity was associated with lower absolute dense volume. As compared to women with the lowest total activity level (<40 metabolic equivalent hours [MET-h] per day), women with the highest total activity level (>= 50 MET-h/day) had an estimated 3.4 cm(3) (95% confidence interval, 2.3-4.7) lower absolute dense volume. The inverse association was seen for any type of physical activity among women with <3.0% TC 10-year risk, but only for total and vigorous activities among women with 3.0-4.9% TC risk, and only for vigorous activity among women with >= 5.0% TC risk. The association between total activity and absolute dense volume was modified by the TC breast cancer risk (P-interaction = 0.05). As anticipated, high physical activity was also associated with lower non-dense volume. No consistent association was found between physical activity and percent dense volume. Conclusions Our results suggest that physical activity may decrease breast cancer risk through reducing mammographic density, and that the physical activity needed to reduce mammographic density may depend on background risk of breast cancer.
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