Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers

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Breast cancer risk prediction using a polygenic risk score in the familial setting: a prospective study from the Breast Cancer Family Registry and kConFab.

PURPOSE: This study examined the utility of sets of single-nucleotide polymorphisms (SNPs) in familial but non-BRCA-associated breast cancer (BC). METHODS: We derived a polygenic risk score (PRS) based on 24 known BC risk SNPs for 4,365 women from the Breast Cancer Family Registry and Kathleen Cuningham Consortium Foundation for Research into Familial Breast Cancer familial BC cohorts. We compared scores for women based on cancer status at baseline; 2,599 women unaffected at enrollment were followed-up for an average of 7.4 years. Cox proportional hazards regression was used to analyze the association of PRS with BC risk. The BOADICEA risk prediction algorithm was used to measure risk based on family history alone. RESULTS: The mean PRS at baseline was 2.25 (SD, 0.35) for affected women and was 2.17 (SD, 0.35) for unaffected women from combined cohorts (P < 10-6). During follow-up, 205 BC cases occurred. The hazard ratios for continuous PRS (per SD) and upper versus lower quintiles were 1.38 (95% confidence interval: 1.22-1.56) and 3.18 (95% confidence interval: 1.84-5.23) respectively. Based on their PRS-based predicted risk, management for up to 23% of women could be altered. CONCLUSION: Including BC-associated SNPs in risk assessment can provide more accurate risk prediction than family history alone and can influence recommendations for cancer screening and prevention modalities for high-risk women.Genet Med 19 1, 30-35.National Institutes of HealthThis is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/gim.2016.4

Discordant attitudes and beliefs about cancer clinical trial participation between physicians, research staff, and cancer patients

Background/aims: Essential to bringing innovative cancer treatments to patients is voluntary participation in clinical trials but approximately 8% of American cancer patients are enrolled onto a trial. We used a domain-oriented framework to assess barriers to cancer clinical trial enrollment. Methods: Physicians (MD, DO, fellows, residents) and research staff (physician assistants, nurse practitioners, staff and research nurses, clinical assistants, and program coordinators) involved in clinical research at a comprehensive cancer center completed an online survey in 2017; adult cancer patients not currently enrolled in a trial were interviewed in 2018. To inform the construct of our physician/staff and patient surveys and to assess barriers to clinical trial enrollment, we first conducted in-depth interviews among 14 key informants representing medical, hematologic, gynecologic, neurologic, radiation oncology, as well as members of the clinical research team (one clinical research coordinator, one research nurse practitioner). Perceived structural, provider- and patient-level barriers to clinical trial enrollment were assessed. Differences in perceptions, attitudes, and beliefs toward clinical trial enrollment between (1) physicians and staff, (2) patients by ethnicity, and (3) physicians/staff and patients were examined. Results: In total, 120 physicians/staff involved in clinical research (39.2% physicians, 60.8% staff; 48.0% overall response rate) and 150 cancer patients completed surveys. Nearly three-quarters of physician/staff respondents reported difficulty in keeping track of the eligibility criteria for open studies but was more often cited by physicians than staff (84.4% vs 64.3%, p = 0.02). Physicians more often reported lack of time to present clinical trial information than did staff(p < 0.001); 44.0% of staff versus 18.2% of physicians reported patient family interaction as a clinical trial enrollment barrier (p = 0.007). Hispanic patients more often stated they would join a trial, even if standard therapy was an option compared to non-Hispanic patients (47.7% vs 20.8%, p = 0.002). Comparing the beliefs and perceptions of physicians/staff to those of patients, patients more often reported negative beliefs about clinical trial enrollment (e.g. being in a trial does not help patients personally, 32.9% vs 1.8%, p < 0.001) but less often felt they had no other options when agreeing to join (38.1% vs 85.6%, p < 0.001), and less often refused clinical trial enrollment due to lack of understanding (9.1% vs 63.3%, p = 0.001) than reported by physicians/staff. Conclusion: Our findings indicate a wide gap between physician/staff and patient attitudes and beliefs about clinical trial enrollment and highlight the importance of focusing future initiatives to raise awareness of this incongruency. Reconciling these differences will require tailored education to reduce implicit biases and dispel misperceptions. Strategies to improve the quality of patient-provider communication and address infrastructure and resource issues are also needed to improve patient enrollment onto cancer clinical trials

Evaluation of Polygenic Risk Scores for Breast and Ovarian Cancer Risk Prediction in BRCA1 and BRCA2 Mutation Carriers

$\textbf{Background:}$ Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes $\textit{BRCA1}$ or $\textit{BRCA2}$. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. $\textbf{Methods:}$ We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through populationbased GWAS: for BC (overall, estrogen receptor [ER]–positive, and ER-negative) and for OC. Using data from 15 252 female $\textit{BRCA1}$ and 8211 $\textit{BRCA2}$ carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. $\textbf{Results:}$ The PRS for ER-negative BC displayed the strongest association with BC risk in $\textit{BRCA1}$ carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, $P$ = 8.2 $\times$ 10$^{-53}$). In $\textit{BRCA2}$ carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, $P$ = 7.2 $\times$ 10$^{-20}$). The OC PRS was strongly associated with OC risk for both $\textit{BRCA1}$ and $\textit{BRCA2}$ carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom AR deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for $\textit{BRCA2}$ carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. $\textbf{Conclusions:}$ BC and OC PRS are predictive of cancer risk in $\textit{BRCA1}$ and $\textit{BRCA2}$ carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management.Cancer Research U

Accuracy of Risk Estimates from the iPrevent Breast Cancer Risk Assessment and Management Tool.

BACKGROUND: iPrevent is an online breast cancer (BC) risk management decision support tool. It uses an internal switching algorithm, based on a woman's risk factor data, to estimate her absolute BC risk using either the International Breast Cancer Intervention Study (IBIS) version 7.02, or Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm version 3 models, and then provides tailored risk management information. This study assessed the accuracy of the 10-year risk estimates using prospective data. METHODS: iPrevent-assigned 10-year invasive BC risk was calculated for 15 732 women aged 20-70 years and without BC at recruitment to the Prospective Family Study Cohort. Calibration, the ratio of the expected (E) number of BCs to the observed (O) number and discriminatory accuracy were assessed. RESULTS: During the 10 years of follow-up, 619 women (3.9%) developed BC compared with 702 expected (E/O = 1.13; 95% confidence interval [CI] =1.05 to 1.23). For women younger than 50 years, 50 years and older, and BRCA1/2-mutation carriers and noncarriers, E/O was 1.04 (95% CI = 0.93 to 1.16), 1.24 (95% CI = 1.11 to 1.39), 1.13 (95% CI = 0.96 to 1.34), and 1.13 (95% CI = 1.04 to 1.24), respectively. The C-statistic was 0.70 (95% CI = 0.68 to 0.73) overall and 0.74 (95% CI = 0.71 to 0.77), 0.63 (95% CI = 0.59 to 0.66), 0.59 (95% CI = 0.53 to 0.64), and 0.65 (95% CI = 0.63 to 0.68), respectively, for the subgroups above. Applying the newer IBIS version 8.0b in the iPrevent switching algorithm improved calibration overall (E/O = 1.06, 95% CI = 0.98 to 1.15) and in all subgroups, without changing discriminatory accuracy. CONCLUSIONS: For 10-year BC risk, iPrevent had good discriminatory accuracy overall and was well calibrated for women aged younger than 50 years. Calibration may be improved in the future by incorporating IBIS version 8.0b

Genetic polymorphisms in DNA repair and oxidative stress pathways may modify the association between body size and postmenopausal breast cancer

Obesity is associated with increased bioavailability of estrogen, hyperinsulemia and chronic inflammation, all of which may promote tumor growth. Given DNA repair and oxidative stress pathways may work together with these mechanisms to influence carcinogenesis, we hypothesized that genetic variation in these pathways may modify the obesity-postmenopausal breast cancer association

Genetic variation in multiple biologic pathways, flavonoid intake, and breast cancer

We previously reported an inverse association between flavonoid intake and breast cancer incidence, which has been confirmed by others; but no studies have considered simultaneously potential interactions of flavonoids with multiple genetic polymorphisms involved in biologically-relevant pathways (oxidative stress, carcinogen metabolism, DNA repair, and one-carbon metabolism)

Evaluation of polygenic risk scores for breast and ovarian cancer risk prediction in BRCA1 and BRCA2 mutation carriers

Background: Genome-wide association studies (GWAS) have identified 94 common single-nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk and 18 associated with ovarian cancer (OC) risk. Several of these are also associated with risk of BC or OC for women who carry a pathogenic mutation in the high-risk BC and OC genes BRCA1 or BRCA2. The combined effects of these variants on BC or OC risk for BRCA1 and BRCA2 mutation carriers have not yet been assessed while their clinical management could benefit from improved personalized risk estimates. Methods: We constructed polygenic risk scores (PRS) using BC and OC susceptibility SNPs identified through population-based GWAS: for BC (overall, estrogen receptor [ER]-positive, and ER-negative) and for OC. Using data from 15 252 female BRCA1 and 8211 BRCA2 carriers, the association of each PRS with BC or OC risk was evaluated using a weighted cohort approach, with time to diagnosis as the outcome and estimation of the hazard ratios (HRs) per standard deviation increase in the PRS. Results: The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.27, 95% confidence interval [CI] = 1.23 to 1.31, P = 8.2 x 10(53)). In BRCA2 carriers, the strongest association with BC risk was seen for the overall BC PRS (HR = 1.22, 95% CI = 1.17 to 1.28, P = 7.2 x 10(-20)). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These translate to differences in absolute risks (more than 10% in each case) between the top and bottom deciles of the PRS distribution; for example, the OC risk was 6% by age 80 years for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Conclusions: BC and OC PRS are predictive of cancer risk in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models has promise to better inform decisions on cancer risk management

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A&gt;T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations