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Women diagnosed with breast cancer have heterogeneous survival outcomes that cannot be fully explained by known prognostic factors, and germline variation is a plausible but unconfirmed risk factor. We used three approaches to test the hypothesis that germline variation drives some differences in survival: mortality loci identification, tumor aggressiveness loci identification, and whole-genome prediction. The 2954 study participants were women diagnosed with breast cancer before age 50, with a median follow-up of 15 years who were genotyped on an exome array. We first searched for loci in gene regions that were associated with all-cause mortality. We next searched for loci in gene regions associated with five histopathological characteristics related to tumor aggressiveness. Last, we also predicted 10-year all-cause mortality on a subset of 1903 participants (3,245,343 variants after imputation) using whole-genome prediction methods. No risk loci for mortality or tumor aggressiveness were identified. This null result persisted when restricting to women with estrogen receptor-positive tumors, when examining suggestive loci in an independent study, and when restricting to previously published risk loci. Additionally, the whole-genome prediction model also found no evidence to support an association. Despite multiple complementary approaches, our study found no evidence that mortality in women with early onset breast cancer is influenced by germline variation.

BACKGROUND Soy foods possess both antiestrogenic and estrogen-like properties. It remains controversial whether women diagnosed with breast cancer should be advised to eat more or less soy foods, especially for those who receive hormone therapies as part of cancer treatment. METHODS The association of dietary intake of isoflavone, the major phytoestrogen in soy, with all-cause mortality was examined in 6235 women with breast cancer enrolled in the Breast Cancer Family Registry. Dietary intake was assessed using a Food Frequency Questionnaire developed for the Hawaii-Los Angeles Multiethnic Cohort among 5178 women who reported prediagnosis diet and 1664 women who reported postdiagnosis diet. Cox proportional-hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS During a median follow-up of 113 months (approximately 9.4 years), 1224 deaths were documented. A 21% decrease was observed in all-cause mortality for women who had the highest versus lowest quartile of dietary isoflavone intake (≥1.5 vs

PurposePathogenic variants (PVs) in a number of genes are known to increase the risk of hereditary renal cancer (hRC). However, many early-onset RC (eoRC) patients undergoing genetic testing lack PVs in hRC genes; thus, their genetic risk remains undefined. To determine if PVs in DNA damage response (DDR) genes are enriched in a convenience sample of eoRC patients undergoing genetic testing.Materials and MethodsRetrospective review of results for 844 unselected eoRC patients, undergoing genetic testing with a multi-gene cancer panel by Ambry Genetics [between July 2012 and December 2016]. The patients were tested with CancerNext and/or CancerNext Expanded panels for a variety of indications. Identified PVs were compared with patient characteristics.ResultsMean age of RC diagnosis was 48 years [range 24-60]. In addition to eoRC, 57.9% patients tested reported at least one additional cancer; breast cancer being the most common (40.1% of females, 2.5% of males). PVs in cancer risk genes were identified in 12.8% of patients—3.7% in RC-specific genes, and 8.55% in DDR genes. DDR gene PVs were most commonly identified in CHEK2, BRCA1/2, and ATM. Among the 2.1% of patients with a BRCA1/2 PV, ConclusionsMulti-gene panel testing including DDR genes may provide a more comprehensive risk assessment in unselected eoRC patients, and their families. Validation in larger datasets is needed to characterize the association with eoRC.

Mammographic screening and prophylactic surgery such as risk-reducing salpingo oophorectomy can potentially reduce breast cancer risks among mutation carriers of BRCA families. The evaluation of these interventions is usually complicated by the fact that their effects on breast cancer may change over time and by the presence of competing risks. We introduce a correlated competing risks model to model breast and ovarian cancer risks within BRCA1 families that accounts for time-varying covariates. Different parametric forms for the effects of time-varying covariates are proposed for more flexibility and a correlated gamma frailty model is specified to account for the correlated competing events.We also introduce a new ascertainment correction approach that accounts for the selection of families through probands affected with either breast or ovarian cancer, or unaffected. Our simulation studies demonstrate the good performances of our proposed approach in terms of bias and precision of the estimators of model parameters and cause-specific penetrances over different levels of familial correlations. We applied our new approach to 498 BRCA1 mutation carrier families recruited through the Breast Cancer Family Registry. Our results demonstrate the importance of the functional form of the time-varying covariate effect when assessing the role of risk-reducing salpingo oophorectomy on breast cancer. In particular, under the best fitting time-varying covariate model, the overall effect of risk-reducing salpingo oophorectomy on breast cancer risk was statistically significant in women with BRCA1 mutation.

Background Sexual concerns are distressing for breast cancer survivors and interfere with their intimate relationships. This study evaluates the efficacy of a four-session couple-based intervention delivered via telephone, called Intimacy Enhancement (IE). The IE intervention is grounded in social cognitive theory and integrates evidence-based techniques from cognitive behavioral couple therapy and sex therapy to address survivors’ sexual concerns and enhance their and their partners’ sexual, relationship, and psychological outcomes. Methods This trial is designed to evaluate the efficacy of the IE intervention in improving survivors’ sexual function, the primary study outcome. Secondary outcomes include survivors’ sexual distress, partners’ sexual function, and survivors’ and partners’ relationship intimacy and quality as well as psychological distress (depressive symptoms and anxiety symptoms). Additional aims are to examine whether treatment effects on patient sexual function are mediated by sexual communication and self-efficacy for coping with sexual concerns and to explore whether survivor age and race/ethnicity moderate intervention effects on survivors’ sexual function. Eligible adult female breast cancer survivors reporting sexual concerns and their intimate partners are recruited from two academic sites in the USA and are randomized to either the IE intervention or to a control condition of equal length offering education and support around breast cancer-related health topics (Living Healthy Together). The target sample size is 120 couples. Self-report outcome measures are administered to participants in both conditions at baseline (T1), post-treatment (T2), 3 months post-treatment (T3), and 6 months post-treatment (T4). Discussion Evidence-based interventions are needed to address sexual concerns for breast cancer survivors and to enhance their and their intimate partners’ sexual, relationship, and psychological well-being. This randomized controlled trial will allow us to examine the efficacy of a novel couple-based intervention delivered via telephone for breast cancer survivors experiencing sexual concerns and their intimate partners, in comparison with an attention control. Findings of this study could influence clinical care for women with breast cancer and inform theory guiding cancer-related sexual rehabilitation. Trial registration ClinicalTrials.gov, NCT03930797. Registered on 24 April 2019.

Pathogenic sequence variants (PSV) in BRCA1 or BRCA2 (BRCA1/2) are associated with increased risk and severity of prostate cancer. We evaluated whether PSVs in BRCA1/2 were associated with risk of overall prostate cancer or high grade (Gleason 8+) prostate cancer using an international sample of 65 BRCA1 and 171 BRCA2 male PSV carriers with prostate cancer, and 3,388 BRCA1 and 2,880 BRCA2 male PSV carriers without prostate cancer. PSVs in the 3′ region of BRCA2 (c.7914+) were significantly associated with elevated risk of prostate cancer compared with reference bin c.1001-c.7913 [HR = 1.78; 95% confidence interval (CI), 1.25–2.52; P = 0.001], as well as elevated risk of Gleason 8+ prostate cancer (HR = 3.11; 95% CI, 1.63–5.95; P = 0.001). c.756-c.1000 was also associated with elevated prostate cancer risk (HR = 2.83; 95% CI, 1.71–4.68; P = 0.00004) and elevated risk of Gleason 8+ prostate cancer (HR = 4.95; 95% CI, 2.12–11.54; P = 0.0002). No genotype–phenotype associations were detected for PSVs in BRCA1. These results demonstrate that specific BRCA2 PSVs may be associated with elevated risk of developing aggressive prostate cancer. Significance: Aggressive prostate cancer risk in BRCA2 mutation carriers may vary according to the specific BRCA2 mutation inherited by the at-risk individual.

The National Comprehensive Cancer Network (NCCN) clinical practice guidelines have become the most recognized standard for clinical policy in cancer care. The Genetic Breast and Ovarian Guideline was introduced in 1999 with an emphasis on BRCA1/2. Based on evidence linking prostate cancer to the BRCA genes, prostate cancer was added to the guideline as a criterion for risk assessment in 2013. The current criteria include aggressive/metastatic disease and family history of BRCA-related cancers.

Purpose To better understand the longitudinal risks and benefits of telephone disclosure of genetic test results in the era of multi-gene panel testing. Patients and Methods Adults who were proceeding with germline cancer genetic testing were randomized to telephone disclosure (TD) with a genetic counselor or in-person disclosure (IPD) of test results (i.e., usual care). All participants who received TD were recommended to return to meet with a physician to discuss medical management recommendations. Results 473 participants were randomized to TD and 497 to IPD. There were no differences between arms for any cognitive, affective or behavioral outcomes at 6 and 12 months. Only 50% of participants in the TD arm returned for the medical follow-up appointment. Returning was associated with site (p

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate PIn-silico analyses showed these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 37.6% for triple-negative and 54.2% for luminal A-like disease. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1–3. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10−8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate (FDR)

Pathogenic sequence variants (PSV) in

Although physical activity is associated with lower breast cancer risk for average-risk women, it is not known if this association applies to women at high familial/genetic risk. We examined the association of recreational physical activity (self-reported by questionnaire) with breast cancer risk using the Prospective Family Study Cohort, which is enriched with women who have a breast cancer family history (N = 15,550). We examined associations of adult and adolescent recreational physical activity (quintiles of age-adjusted total metabolic equivalents per week) with breast cancer risk using multivariable Cox proportional hazards regression, adjusted for demographics, lifestyle factors, and body mass index. We tested for multiplicative interactions of physical activity with predicted absolute breast cancer familial risk based on pedigree data and with BRCA1 and BRCA2 mutation status. Baseline recreational physical activity level in the highest four quintiles compared with the lowest quintile was associated with a 20% lower breast cancer risk (HR, 0.80; 95% confidence interval, 0.68–0.93). The association was not modified by familial risk or BRCA mutation status (P interactions >0.05). No overall association was found for adolescent recreational physical activity. Recreational physical activity in adulthood may lower breast cancer risk for women across the spectrum of familial risk. Significance: These findings suggest that physical activity might reduce breast cancer risk by about 20% for women across the risk continuum, including women at higher-than-average risk due to their family history or genetic susceptibility. See related commentary by Niehoff et al., p. 23

The Risk Assessment Program (RAP) at Fox Chase Cancer Center (Philadelphia, PA) is a multi-generational prospective cohort, enhanced for personal and family history of cancer, consisting of over 10,000 individuals for whom data on personal and family history of cancer, risk factors, genetic and genomic data, health behaviors, and biospecimens are available. The RAP has a broad research agenda including the characterization of genes with known or potential relevance to cancer, gene–gene and gene–environment interactions, and their contribution to clinically useful risk assessment and risk reduction strategies. Increasingly, this body of research is identifying genetic changes which may have clinical significance for RAP research participants, leading us to confront the issue of whether to return genetic results emerging from research laboratories. This review will describe some of the important fundamental points that must be debated as we develop a paradigm for return of research results. The key issues to address as the scientific community moves toward adopting a policy of return of research results include the best criteria for determining which results to offer, the consent document components necessary to ensure that the participant makes a truly informed decision about receiving their results, and associated logistical and cost challenges. See all articles in this Special Collection Honoring Paul F. Engstrom, MD, Champion of Cancer Prevention

BACKGROUND: Tobacco smoking and alcohol consumption have been intensively studied in the general population to assess their effects on the risk of breast cancer (BC), but very few studies have examined these effects in BRCA1 and BRCA2 mutation carriers. Given the high BC risk for mutation carriers and the importance of BRCA1 and BRCA2 in DNA repair, better evidence on the associations of these lifestyle factors with BC risk is essential. METHODS: Using a large international pooled cohort of BRCA1 and BRCA2 mutation carriers, we conducted retrospective (5,707 BRCA1 mutation carriers; 3,525 BRCA2 mutation carriers) and prospective (2,276 BRCA1 mutation carriers; 1,610 BRCA2 mutation carriers) analyses of alcohol and tobacco consumption using Cox proportional hazards models. RESULTS: For both BRCA1 and BRCA2 mutation carriers, none of the smoking-related variables was associated with BC risk, except smoking for more than five years before a first full-term pregnancy (FFTP) when compared to parous women who never smoked. For BRCA1 mutation carriers, the HR from retrospective analysis (HR(R)) was 1.19 (95%CI:1.02,1.39) and the HR from prospective analysis (HR(P)) was 1.36 (95%CI:0.99,1.87). For BRCA2 mutation carriers, smoking for more than five years before a FFTP showed an association of a similar magnitude, but the confidence limits were wider (HR(R)=1.25,95%CI:1.01,1.55 and HR(P)=1.30,95%CI:0.83,2.01). For both carrier groups, alcohol consumption was not associated with BC risk. CONCLUSIONS: The finding that smoking during the pre-reproductive years increases BC risk for mutation carriers warrants further investigation.

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P −6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

Background The use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been associated with reduced breast cancer risk, but it is not known if this association extends to women at familial or genetic risk. We examined the association between regular NSAID use and breast cancer risk using a large cohort of women selected for breast cancer family history, including 1054 BRCA1 or BRCA2 mutation carriers. Methods We analyzed a prospective cohort (N = 5606) and a larger combined, retrospective and prospective, cohort (N = 8233) of women who were aged 18 to 79 years, enrolled before June 30, 2011, with follow-up questionnaire data on medication history. The prospective cohort was further restricted to women without breast cancer when medication history was asked by questionnaire. Women were recruited from seven study centers in the United States, Canada, and Australia. Associations were estimated using multivariable Cox proportional hazards regression models adjusted for demographics, lifestyle factors, family history, and other medication use. Women were classified as regular or non-regular users of aspirin, COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen (control) based on self-report at follow-up of ever using the medication for at least twice a week for ≥1 month prior to breast cancer diagnosis. The main outcome was incident invasive breast cancer, based on self- or relative-report (81% confirmed pathologically). Results From fully adjusted analyses, regular aspirin use was associated with a 39% and 37% reduced risk of breast cancer in the prospective (HR = 0.61; 95% CI = 0.33–1.14) and combined cohorts (HR = 0.63; 95% CI = 0.57–0.71), respectively. Regular use of COX-2 inhibitors was associated with a 61% and 71% reduced risk of breast cancer (prospective HR = 0.39; 95% CI = 0.15–0.97; combined HR = 0.29; 95% CI = 0.23–0.38). Other NSAIDs and acetaminophen were not associated with breast cancer risk in either cohort. Associations were not modified by familial risk, and consistent patterns were found by BRCA1 and BRCA2 carrier status, estrogen receptor status, and attained age. Conclusion Regular use of aspirin and COX-2 inhibitors might reduce breast cancer risk for women at familial or genetic risk. Electronic supplementary material The online version of this article (10.1186/s13058-019-1135-y) contains supplementary material, which is available to authorized users.

Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP). Results: We did not find any variant associated with breast cancer-specific mortality at P < 5 × 10 −8 . For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10 −7 , hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84–0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10 −7 , HR = 1.27, 95% CI = 1.16–1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster. Conclusions: We uncovered germline variants on chromosome 7 at BFDP < 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients.

Background: Early-onset renal cancer (eoRC) is typically associated with significant family history of cancer, and often associated with germline pathogenic variants (PVs) in ‘RC-specific' genes including VHL, MET, FLCN, TSC1, TSC2, FH, SDH, PTEN and BAP1. However, most eoRC patients lack PVs in RC-specific genes; rather, we recently identified an enrichment of likely PVs in DNA repair genes in eoRC patients. Here, using eoRC patient resources (primary and transformed lymphocytes, lymphocyte DNA, and tumor tissue), we functionally evaluated the DNA repair variants identified in eoRC patients. Methods: We performed whole-exome sequencing (WES) on lymphocyte DNA from 22 patients with genetically undefined eoRC, with extensive family history of RC and/or other cancers, provided by Risk Assessment Program and Genitourinary Group at Fox Chase Cancer Center. Prioritized variants were assessed by structural, biochemical and cellular studies. Results: 70% of patients had rare, heterozygous, missense variants in genes that suppress DNA damage. ~18% of the variants were in DNA polymerase genes (POLD1, POLE, POLH, POLK), which mediate DNA replication-repair. Increased tumor mutation burden (>10 mutations/Mb) was observed in tumors carrying predicted damaging polymerase variants. In functional testing, induction of DNA damage in primary lymphocytes from eoRC patients and matched cancer-free controls (n=20 each) selectively elevated γH2AX foci (indicative of DNA damage) in cells from eoRC patients (P Conclusion and future work: Our results indicate that germline variants in DNA repair genes impact suppression of DNA damage in cells from patients with eoRC. Biological studies testing the impact of the identified variants on renal carcinogenesis are warranted. Overall, genetic testing for variation in DNA repair genes may provide a more comprehensive risk assessment in eoRC patients, and provide novel opportunities for targeting DNA repair vulnerabilities in RC. Citation Format: Elena V. Demidova, Waleed Iqbal, Ilya G. Serebriiskii, Andrea F. Forman, Tatiana Kent, Richard T. Pomerantz, Erica A. Golemis, Michael J. Hall, David Y. Chen, Mary B. Daly, Sanjeevani Arora. Functional evaluation of novel germline DNA repair variants identified in patients with early-onset renal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 808.

10537 Background: LS is among the most common hereditary cancer (CA) syndromes. PVs in MSH6 are 2-4 fold more common in the population (1/758) than those in MLH1 (1/1946) or MSH2 (1/2841), and are increasingly regarded as lower penetrance for CRC due to published data supporting later mean age of CRC onset and lower CRC risk. Unlike for MLH1/MSH2, NCCN 2020 CA risk estimates recognize only endometrial CA (EC) and CRC risks in MSH6+ carriers as clearly above SEER population estimates. Further, risks of other LS manifestations such as skin disease/Muir-Torre, ovarian CA (OC), and possible rare tumors in LS like sarcoma, have been minimally characterized in MSH6+ carriers. Methods: Pedigree data for 44 MSH6+ index (first-evaluated family member by our program) pts consecutively ascertained since 2009 at Fox Chase (FCCC) were reviewed. 1 pt w/a rare MSH6 uncertain variant w/personal history (PHx) of MSH6-expression deficient EC (age 50) and MSH6-deficient sebaceous skin CA (age 50) and a strong family history (FHx) c/w LS is also included here. 34% (15/44) index pts were referred to FCCC for cascade testing due to a known MSH6 PV in the family. Of the remaining 29 index pts, ascertainment included: 14% w/positive universal LS tumor screening, 21% w/early-onset or synchronous LS CA, 14% w/multi-gene panel for PHx of OC, 10% w/incidental MSH6+ result (2 had testing for PHx breast CA, 1 tumor genomic profiling), and 28% w/PHx and/or FHx of LS CA warranting genetic testing. Age of CA onset and path data were verified in > 90% index pts. Results: Index pts had a mean age of 55.5 yrs, and 77% were female. Overall, 11% (5/44) of MSH6+ index pts were found to have LS at diagnosis of synchronous primary CAs (3 EC/OC, 1 CRC/CRC, 1 CRC/EC), and 4/5 of these occurred 2 metachronous LS CAs. OC was the presenting CA in 14% (6/44) female index pts; 2 additional index pts had rarer OC variants (Mullerian duct @ 41, primary peritoneal CA @ 50). Skin manifestations of LS were documented in 9.1% (4/44) index pts (3 sebaceous, 1 SCC in-situ/Bowen’s disease); 1 other family had documented sebaceous CAs in an FDR (father) but the 2 daughters seen @FCCC (both 30s) had yet to develop skin lesions. 2 index pts were found to have LS after developing early-onset breast CA (age 39) and contralateral breast CA (ages 50 and 54). Finally, 7% (3/44) index pts had a PHx of sarcoma: 2 were liposarcomas (ages 57 and 67), and 1 was a dermatofibrosarcoma. 2 other index pts had siblings w/childhood sarcomas. Conclusions: Our data, encompassing 44 MSH6+ pts evaluated in our clinic and consecutively ascertained, suggest MSH6 PV carriers develop synchronous primaries (11%), common and rare OC histologic types (18%), sarcomas (7%) and skin disease/Muir-Torre (9%). While common in the population and lower penetrance for CRC, MSH6 PV can behave in uncommon ways and may have significant extra-colonic CA risks such as OC, sarcoma and skin manifestations.

This abstract was not presented at the symposium.

This abstract was withdrawn by the authors.

Item does not contain fulltext Importance: The clinical management of BRCA1 and BRCA2 mutation carriers requires accurate, prospective cancer risk estimates. Objectives: To estimate age-specific risks of breast, ovarian, and contralateral breast cancer for mutation carriers and to evaluate risk modification by family cancer history and mutation location. Design, Setting, and Participants: Prospective cohort study of 6036 BRCA1 and 3820 BRCA2 female carriers (5046 unaffected and 4810 with breast or ovarian cancer or both at baseline) recruited in 1997-2011 through the International BRCA1/2 Carrier Cohort Study, the Breast Cancer Family Registry and the Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer, with ascertainment through family clinics (94%) and population-based studies (6%). The majority were from large national studies in the United Kingdom (EMBRACE), the Netherlands (HEBON), and France (GENEPSO). Follow-up ended December 2013; median follow-up was 5 years. Exposures: BRCA1/2 mutations, family cancer history, and mutation location. Main Outcomes and Measures: Annual incidences, standardized incidence ratios, and cumulative risks of breast, ovarian, and contralateral breast cancer. Results: Among 3886 women (median age, 38 years; interquartile range [IQR], 30-46 years) eligible for the breast cancer analysis, 5066 women (median age, 38 years; IQR, 31-47 years) eligible for the ovarian cancer analysis, and 2213 women (median age, 47 years; IQR, 40-55 years) eligible for the contralateral breast cancer analysis, 426 were diagnosed with breast cancer, 109 with ovarian cancer, and 245 with contralateral breast cancer during follow-up. The cumulative breast cancer risk to age 80 years was 72% (95% CI, 65%-79%) for BRCA1 and 69% (95% CI, 61%-77%) for BRCA2 carriers. Breast cancer incidences increased rapidly in early adulthood until ages 30 to 40 years for BRCA1 and until ages 40 to 50 years for BRCA2 carriers, then remained at a similar, constant incidence (20-30 per 1000 person-years) until age 80 years. The cumulative ovarian cancer risk to age 80 years was 44% (95% CI, 36%-53%) for BRCA1 and 17% (95% CI, 11%-25%) for BRCA2 carriers. For contralateral breast cancer, the cumulative risk 20 years after breast cancer diagnosis was 40% (95% CI, 35%-45%) for BRCA1 and 26% (95% CI, 20%-33%) for BRCA2 carriers (hazard ratio [HR] for comparing BRCA2 vs BRCA1, 0.62; 95% CI, 0.47-0.82; P=.001 for difference). Breast cancer risk increased with increasing number of first- and second-degree relatives diagnosed as having breast cancer for both BRCA1 (HR for >/=2 vs 0 affected relatives, 1.99; 95% CI, 1.41-2.82; P

This study examined the utility of sets of single-nucleotide polymorphisms (SNPs) in familial but non-BRCA-associated breast cancer (BC). 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. 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. 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.

Genetic information is changing the practice of medicine by personalizing prevention and treatment decisions based on the genetic profile of the individual. The impact of personalized genetic-based medicine extends beyond the individual to include the family, where knowledge of a genetic predisposition to a disease condition has implications for individuals, their siblings and offspring, and for the identity of the family itself. The quality of the family communication process is important in assuring accuracy of risk information and in maintaining the cohesion of the family unit. However, there is increasing evidence that the communication of genetic risk information within families is complex, selective, incomplete, and often ineffective. This paper presents an overview of what is known about the strengths and weaknesses of the communication of genetic risk information within families and suggests a framework for both understanding the process of communication and guiding future counseling models.

Obstetrician/gynecologists and gynecologic oncologists serve an integral role in the care of women at increased hereditary risk of cancer. Their contribution includes initial identification of high risk patients, screening procedures like bimanual exam, trans-vaginal ultrasound and endometrial biopsy, prophylaxis via TAH and/or BSO, and chemoprevention. Further, gynecologists also serve a central role in the management of the secondary repercussions of efforts to mitigate increased cancer risks, including vasomotor symptoms, sexual function, bone health, cardiovascular disease, and mental health. The past several years has seen multiple new high and moderate penetrance genes introduced into the clinical care of women at increased risk of gynecologic malignancy. Awareness of these new genes and the availability of new multi-gene panel tests is critical for providers on the front-line of women's health.

Purpose: In the U.S., ovarian cancer is the most fatal of the gynecological cancers with an overall five-year survival rate of 47.6%. While women with a BRCA1 or BRCA2 mutation are at a much higher risk of developing ovarian cancer, mutations in these genes account for less than 50 percent of the familial aggregation of ovarian cancer. Being able to identify women at greatest risk, including those with increased familial risk without a BRCA1 or BRCA2 mutation, is critical for clinical decision-making; however, there is a lack of risk prediction models for ovarian cancer and those that do exist have modest discriminatory power. Therefore, we externally validated the BOADICEA model, a breast and ovarian cancer risk prediction model based on a woman's multigenerational family history and genetic information, for predicting ovarian cancer risk in an independent, prospective cohort of women. Methods: We used data from the Breast Cancer Family Registry (BCFR), a cohort of families with breast and ovarian cancer at baseline that have been prospectively followed. We assessed the 10-year performance of the BOADICEA model (version 3) for ovarian cancer risk overall, and by known BRCA1 or BRCA2 mutation statuses. We included women who did not have an ovarian cancer diagnosis or a bilateral oophorectomy prior to baseline, and who had sufficient data to calculate the 10-year BOADICEA risk score. We assessed model calibration using the ratio of the expected (E) to the observed (O) number of ovarian cancer cases in the cohort (E/O), and model discrimination by the concordance statistics (C-statistic) derived from the receiver operating characteristic curves. Results: There were 125 prospective ovarian cancer cases over a median of 12.3 years of follow-up among 18,534 women eligible for this analysis. For the overall cohort, the BOADICEA model was well calibrated with an E/O of 0.87, 95% confidence interval (CI) (0.70, 1.08). There was a suggestion of model underprediction in the top quartile of assigned risk (1.33% observed risk vs. 1.09% predicted risk), however it was not statistically significant (p=0.15). The C-statistic was 0.77, 95% CI (0.73, 0.82). For known BRCA1 or BRCA2 mutation carriers combined, the E/O was 0.91, 95% CI (0.63, 1.32) and the C-statistic was 0.75, 95% CI (0.67, 0.83). For non-carriers, the E/O was 0.85, 95% CI (0.65, 1.11) and the C-statistic was 0.68, 95% CI (0.59, 0.74). Conclusion: The BOADICEA model is well-calibrated in predicting ovarian cancer risk over 10 years and has good discriminatory power for women at increased familial risk of breast and ovarian cancer, with or without a known mutation in BRCA1 or BRCA2. Therefore, BOADICEA has clinical utility for evaluating ovarian cancer risk based on a woman's family cancer history and genetic information. Citation Format: Jennifer S. Ferris, Jeanine M. Genkinger, Mary Beth Terry, Yuyan Liao, Robert J. MacInnis, Irene L. Andrulis, Saundra S. Buys, Mary B. Daly, Esther M. John, John L. Hopper. External validation of the BOADICEA model for predicting ovarian cancer risk: The Breast Cancer Family Registry [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4623.

IntroductionNeighborhood socioeconomic (nSES) factors have been implicated in prostate cancer (PCa) disparities. In line with the Precision Medicine Initiative that suggests clinical and socioenvironmental factors can impact PCa outcomes, we determined whether nSES variables are associated with time to PCa diagnosis and could inform PCa clinical risk assessment.Materials and methodsThe study sample included 358 high risk men (PCa family history and/or Black race), aged 35-69 years, enrolled in an early detection program. Patient variables were linked to 78 nSES variables (employment, income, etc.) from previous literature via geocoding. Patient-level models, including baseline age, prostate specific antigen (PSA), digital rectal exam, as well as combined models (patient plus nSES variables) by race/PCa family history subgroups were built after variable reduction methods using Cox regression and LASSO machine-learning. Model fit of patient and combined models (AIC) were compared; p-valuesResultsIn combined models, nSES variables were significantly associated with time to PCa diagnosis. Workers mode of transportation and low income were significant in White men with a PCa family history. Homeownership (%owner-occupied houses with >3 bedrooms) and unemployment were significant in Black men with and without a PCa family history, respectively. The 5-year predicted probability of PCa was higher in men with a high neighborhood score (weighted combination of significant nSES variables) compared to a low score (e.g., Baseline PSA level of 4ng/mL for men with PCa family history: White-26.7% vs 7.7%; Black-56.2% vs 29.7%).DiscussionUtilizing neighborhood data during patient risk assessment may be useful for high risk men affected by disparities. However, future studies with larger samples and validation/replication steps are needed.

An earlier age at pubertal development is associated with increased breast cancer risk, and Westernized countries are observing earlier ages of pubertal timing in girls. While increased rates of childhood obesity are associated with earlier ages of pubertal development, earlier ages of puberty are also observed in countries that are not experiencing high rates of childhood obesity. Prior evidence from a birth cohort in Hong Kong suggests that early life infections, as measured by hospitalizations, is associated with pubertal onset. Emerging evidence suggests that early life and childhood exposures to infection may impact pubertal development. Therefore, we aimed to assess whether indirect measures of infections in infancy (birth-12 months) and early childhood (1-5 years) are associated with the age of onset of puberty (menarche and breast and pubic hair development). We used data from the Infection Questionnaire from the multisite prospective LEGACY Girls Study where mothers/guardians reported on daughters’ indirect exposure to infection (daycare attendance, antibiotic use, physician visit due to fever, hospitalization due to infection) and specific exposure to infections (e.g., tonsillitis, cold sores). Mothers/guardians reported on daughters’ age at first menses and the onset of breast and pubic hair development using Tanner Staging (as defined as Tanner Stage 2 or higher). We used Cox Proportional Hazard Ratio (HR) models to examine the prospective association between infection history and pubertal timing. We considered site, race/ethnicity, and maternal education as possible confounders. In 615 girls (average age (SD) 9.5 (2.4) years) whose mother/guardians completed the Infection Questionnaire, 65% were white non-Hispanic, 18% were Hispanic, 5% were Black non-Hispanic, and 9% were Asian. Sixty-nine percent of mothers/guardians had a college degree or higher. We assessed frequency of infectious exposures across infancy and early childhood where 73% of girls ever used antibiotics, 59% of girls ever had an ear infection, 59% of girls ever attended daycare over 10 hours per week, 29% of girls visited a physician due to fever (measured in childhood only), 36% of mothers reported girls having 2 or more infections, and 6% of girls were ever hospitalized due to infection. In multivariable models controlled for socioeconomic and maternal factors, earlier age of pubic hair development was associated with hospitalization due to infection compared to never hospitalized (HR=1.53, 95% CI=1.07-2.21) and ever antibiotic use compared to never antibiotic use (HR=1.31, 95% CI=1.03-1.68). Compared to never, multivariable models suggested that earlier age at menarche was associated with physician visit due to fever (HR=1.30, 95% CI=1.04-1.63). We observed no association between infectious exposures and earlier breast development. These results suggest that infancy and childhood infectious exposures may be related to earlier pubertal development, but more studies are needed to confirm these findings. Citation Format: Yun Huang, Irene L. Andrulis, Angela R. Bradbury, Saundra S. Buys, Mary B. Daly, Esther M. John, Lisa A. Schwartz, Mary Beth Terry, Jasmine A. McDonald. Infancy and childhood infections and pubertal timing in the LEGACY Girls’ Study [abstract]. In: Proceedings of the AACR Special Conference on Environmental Carcinogenesis: Potential Pathway to Cancer Prevention; 2019 Jun 22-24; Charlotte, NC. Philadelphia (PA): AACR; Can Prev Res 2020;13(7 Suppl): Abstract nr A14.

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.

This cohort study evaluates the association of prepubertal androgen concentrations with timing of breast development in girls with or without a family history of breast cancer., Key Points Question Are serum concentrations of androgens in prepubertal girls associated with a family history of breast cancer? Findings In this cohort study of 104 prepubertal girls, total testosterone concentrations were 10% higher, free testosterone concentrations were 92% higher, and androstenedione concentrations were 240% higher in girls with first-degree, but not second-degree, relatives with breast cancer compared with girls without a family history of breast cancer. Findings were statistically significant for androstenedione and total testosterone concentrations, but findings for free testosterone concentrations were not statistically significant. Meaning If replicated in larger studies, these results may support the finding that elevated androgen concentrations in adolescent girls whose mother has breast cancer may be another factor contributing to the familial clustering of breast cancer., Importance Early breast development is a risk factor for breast cancer, and girls with a breast cancer family history (BCFH) experience breast development earlier than girls without a BCFH. Objectives To assess whether prepubertal androgen concentrations are associated with timing of breast development (analysis 1) and to compare serum androgen concentrations in girls with and without a BCFH (analysis 2). Design, Setting, and Participants Prospective cohort study of 104 girls aged 6 to 13 years at baseline using data collected between August 16, 2011, and March 24, 2016, from the Lessons in Epidemiology and Genetics of Adult Cancer From Youth (LEGACY) Girls Study, New York site. Exposures Analysis 1 included serum concentrations of dehydroepiandrosterone sulfate, androstenedione, and testosterone (free and total) measured before breast development and divided at the median into high and low categories. Analysis 2 included the degree of BCFH: first-degree was defined as having a mother with breast cancer and second-degree was defined as having a grandmother or aunt with breast cancer. Main Outcomes and Measures Analysis 1 included age at onset of breast development measured using the Pubertal Development Scale (scores range from 1-4; scores ≥2 indicate breast development), and analysis 2 included serum androgen concentrations. We also assessed breast cancer–specific distress using the 8-item Child Impact of Events Scale. Results Our analyses included 36 girls for the prospective model, 92 girls for the cross-sectional model, and 104 girls for the longitudinal model. Of the 104 girls, the mean (SD) age at baseline was 10.3 (2.5) years, and 41 (39.4%) were non-Hispanic white, 41 (39.4%) were Hispanic, 13 (12.5%) were non-Hispanic black, and 9 (8.7%) were other race/ethnicity. Forty-two girls (40.4%) had a positive BCFH. Girls with prepubertal androstenedione concentrations above the median began breast development 1.5 years earlier than girls with concentrations below the median (Weibull survival model–estimated median age, 9.4 [95% CI, 9.0-9.8] years vs 10.9 [95% CI, 10.4-11.5] years; P = .001). Similar patterns were observed for dehydroepiandrosterone sulfate (1.1 years earlier: age, 9.6 [95% CI, 9.1-10.1] years vs 10.7 [95% CI, 10.2-11.3] years; P = .009), total testosterone (1.4 years earlier: age, 9.5 [95% CI, 9.1-9.9] years vs 10.9 [95% CI, 10.4-11.5] years; P = .001), and free testosterone (1.1 years earlier: age, 9.7 [95% CI, 9.2-10.1] years vs 10.8 [95% CI, 10.2-11.4] years; P = .01). Compared with girls without BCFH, girls with a first-degree BCFH, but not a second-degree BCFH, had 240% higher androstenedione concentrations (geometric means: no BCFH, 0.49 ng/mL vs first-degree BCFH, 1.8 ng/mL vs second-degree, 1.6 ng/mL; P = .01), 10% higher total testosterone concentrations (12.7 ng/dL vs 14.0 ng/dL vs 13.7 ng/dL; P = .01), and 92% higher free testosterone concentrations (1.3 pg/mL vs 2.5 pg/mL vs 0.3 pg/mL; P = .14). The dehydroepiandrosterone sulfate concentration did not differ between BCFH-positive and BCFH-negative girls but was elevated in girls with breast cancer–specific distress. Conclusions and Relevance Our findings suggest that androgen concentrations may differ between girls with and without a BCFH and that elevated hormone concentrations during adolescence may be another factor to help explain the familial clustering of breast cancer.

e13679 Background: The role of germline genetic testing (GGT) is rapidly changing for men with PCa. We describe the characteristics of men with PCa diagnosed with pathogenic (P) and likely pathogenic (LP) mutations on GGT. Methods: We conducted a retrospective single-institution study for all men with PCa who received single gene or multi-gene GGT from 1997-2019, unselected for disease stage, Gleason score, or age at diagnosis, and while most had a family history of cancer, some did not. All participants were from the Risk Assessment Program (RAP) database at FCCC and consented for research purposes at the time of GGT. Results: 160 men with PCa had GGT. 72/160 (45%) patients had no mutations. 41/160 (26%) patients had a variant of undetermined significance (VUS) (13 with 2 VUS, 1 with 3 VUS). 47/160 (29%) men were found to have a P or LP germline mutation. 26/47 (55%) with recurrent disease, and 1/47 (2%) unknown. 46 were Caucasian, and 1 was African American ( PALB2). 28/47 (60%) had Gleason Scores (GS) ≤7. 6/47 (13%) had a Prostate Specific Antigen (PSA) at diagnosis < 4.0 ng/mL. 23/47 (49%) were diagnosed < 60 years of age, and 8/47 (17%) at ≤ 50. 19/23 (83%) PCa cases with P/LP diagnosed below age 60 had DNA repair genes: BRCA2 (8), BRCA1 (4), CHEK2 (4), ATM (2), and PALB2 (1). 74/160 (46%) were tested after PCa NCCN genetics guidelines changed (October 2017), of which 19/74 (25%) had P/LP, and of those positive for P/LP, 6/19 (32%) had non-metastatic disease. Two patients had small cell neuroendocrine PCa ( CHEK2 and BRCA2), the remaining had adenocarcinoma PCa. Please see Table for full results. Conclusions: To our knowledge, this is the largest single-institution study reporting PCa characteristics and incidence of P/LP germline mutations. Rates of DNA-repair gene mutations were higher than previously reported, possibly reflecting our specialized cancer center’s population. While BRCA1/2 mutations were the most represented (55%), we describe PCa patients with mutations in ATM, CHEK2, NBN, PALB2, CFTR, and MUTYH, recognizing a few are not known to be linked to PCa. More than half of P/LP mutation carriers had GS ≤7. Additionally, 13% of the men with P/LP germline mutations had low PSA ( < 4.0 ng/mL) at diagnosis. Our findings highlight the importance of the new guidelines and GGT importance in some men with PCa, particularly if they could benefit from a different therapeutic approach, or be influenced into cascade GGT. [Table: see text]

e24179 Background: Many women with breast cancer (BC) lack the confidence to discuss sexual health with their clinicians. We evaluated, in a randomized controlled trial, a brief multimedia intervention designed to facilitate BC patients’ communication about sexual health. Methods: We randomly assigned BC patients to either a multimedia sexual/menopausal health communication skills intervention [ Starting the Conversation (STC), including a video, workbook, and pamphlet with local and web-based resources] or a control [resource guide only]. About 1-2 weeks after patients received materials, we audio recorded a clinic encounter with their BC provider, and subsequently coded the dialogue for patients raising the topic of sexual health or asking > 1 sexual health question. Self-report surveys administered at baseline, post-intervention, and 2-month follow-up assessed patients’ self-efficacy for discussing sexual health with their BC providers, sexual function, anxiety and depression, and quality of life. T-tests or mixed-effects logistic regression compared study arms; analyses of communication outcomes (patient raising the topic or asking a question during clinic encounter) were clustered by providers. Results: Study participants were 144 BC outpatients (82% acceptance rate; mean age = 56; 67% white; 15% metastatic; 31% active treatment). Women in the STC arm versus the control arm were more likely to raise the topic of sexual health [OR = 2.48 (1.11, 5.55), p= .03] and more likely to ask a sexual health question [OR = 2.93 (1.04, 8.26), p= .04]. Specifically, 51% of women in the STC arm raised the topic of sexual health versus 30% in the control arm and 40% of women in the STC arm asked a sexual health question versus 19% in the control arm. At 2-month follow-up, women in the STC arm showed greater improvements in self-efficacy ( p= .03) and anxiety, t(139) = 2.0, p= .04) compared to the control arm. Conclusions: STC, a brief multimedia intervention, was effective in facilitating BC patients’ communication about sexual health during routine clinic encounters and significantly reduced patients’ anxiety, possibly due to greater patient confidence in expressing their medical needs. Future studies should use longer-term follow-up and examine how sexual health communication can translate to improved patient sexual outcomes. Clinical trial information: NCT03624972 .

Publisher's version (útgefin grein)., Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis., The authors in this manuscript were working on behalf of BCAC, CCFR, CIMBA, CORECT, GECCO, OCAC, PRACTICAL, CRUK, BPC3, CAPS, PEGASUS, TRICL-ILCCO, ABCTB, APCB, BCFR, CONSIT TEAM, EMBRACE, GC-HBOC, GEMO, HEBON, kConFab/AOCS Mod SQuaD, and SWE-BRCA. The breast cancer genome-wide association analyses: BCAC is funded by Cancer Research UK [C1287/A16563, C1287/A10118], the European Union’s Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633784 for BRIDGES and B-CAST, respectively), and by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). The EU Horizon 2020 Research and Innovation Programme funding source had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Genotyping of the OncoArray was funded by the NIH Grant U19 CA148065, and Cancer UK Grant C1287/A16563 and the PERSPECTIVE project supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (grant GPH-129344) and, the Ministère de l’Économie, Science et Innovation du Québec through Genome Québec and the PSR-SIIRI-701 grant, and the Quebec Breast Cancer Foundation. Funding for the iCOGS infrastructure came from: the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978), and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112—the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, and Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The DRIVE Consortium was funded by U19 CA148065. The Australian Breast Cancer Family Study (ABCFS) was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia), and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellow. M.C.S. is a NHMRC Senior Research Fellow. The ABCS study was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009 4363]. The Australian Breast Cancer Tissue Bank (ABCTB) is generously supported by the National Health and Medical Research Council of Australia, The Cancer Institute NSW and the National Breast Cancer Foundation. The ACP study is funded by the Breast Cancer Research Trust, UK. The AHS study is supported by the intramural research program of the National Institutes of Health, the National Cancer Institute (grant number Z01-CP010119), and the National Institute of Environmental Health Sciences (grant number Z01-ES049030). The work of the BBCC was partly funded by ELAN-Fond of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breast Cancer Now and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). The BCEES was funded by the National Health and Medical Research Council, Australia and the Cancer Council Western Australia and acknowledges funding from the National Breast Cancer Foundation (JS). For the BCFR-NY, BCFR-PA, and BCFR-UT this work was supported by grant UM1 CA164920 from the National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. For BIGGS, ES is supported by NIHR Comprehensive Biomedical Research Centre, Guy’s & St. Thomas’ NHS Foundation Trust in partnership with King’s College London, United Kingdom. IT is supported by the Oxford Biomedical Research Centre. BOCS is supported by funds from Cancer Research UK (C8620/A8372/A15106) and the Institute of Cancer Research (UK). BOCS acknowledges NHS funding to the Royal Marsden/Institute of Cancer Research NIHR Specialist Cancer Biomedical Research Centre. The BREast Oncology GAlician Network (BREOGAN) is funded by Acción Estratégica de Salud del Instituto de Salud Carlos III FIS PI12/02125/Cofinanciado FEDER; Acción Estratégica de Salud del Instituto de Salud Carlos III FIS Intrasalud (PI13/01136); Programa Grupos Emergentes, Cancer Genetics Unit, Instituto de Investigacion Biomedica Galicia Sur. Xerencia de Xestion Integrada de Vigo-SERGAS, Instituto de Salud Carlos III, Spain; Grant 10CSA012E, Consellería de Industria Programa Sectorial de Investigación Aplicada, PEME I + D e I + D Suma del Plan Gallego de Investigación, Desarrollo e Innovación Tecnológica de la Consellería de Industria de la Xunta de Galicia, Spain; Grant EC11-192. Fomento de la Investigación Clínica Independiente, Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain; and Grant FEDER-Innterconecta. Ministerio de Economia y Competitividad, Xunta de Galicia, Spain. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). The CAMA study was funded by Consejo Nacional de Ciencia y Tecnología (CONACyT) (SALUD-2002-C01-7462). Sample collection and processing was funded in part by grants from the National Cancer Institute (NCI R01CA120120 and K24CA169004). CBCS is funded by the Canadian Cancer Society (grant # 313404) and the Canadian Institutes of Health Research. CCGP is supported by funding from the University of Crete. The CECILE study was supported by Fondation de France, Institut National du Cancer (INCa), Ligue Nationale contre le Cancer, Agence Nationale de Sécurité Sanitaire, de l’Alimentation, de l’Environnement et du Travail (ANSES), Agence Nationale de la Recherche (ANR). The CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council, and Herlev and Gentofte Hospital. The CNIO-BCS was supported by the Instituto de Salud Carlos III, the Red Temática de Investigación Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and the Fondo de Investigación Sanitario (PI11/00923 and PI12/00070). COLBCCC is supported by the German Cancer Research Center (DKFZ), Heidelberg, Germany. D.T. was in part supported by a postdoctoral fellowship from the Alexander von Humboldt Foundation. The American Cancer Society funds the creation, maintenance, and updating of the CPS-II cohort. The CTS was initially supported by the California Breast Cancer Act of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is currently funded through the National Institutes of Health (R01 CA77398, UM1 CA164917, and U01 CA199277). Collection of cancer incidence data was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. H.A.C eceives support from the Lon V Smith Foundation (LVS39420). The University of Westminster curates the DietCompLyf database funded by Against Breast Cancer Registered Charity No. 1121258 and the NCRN. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by: Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation, the Stavros Niarchos Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom). The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). FHRISK is funded from NIHR grant PGfAR 0707-10031. The GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer) is supported by the German Cancer Aid (grant no 110837, coordinator: Rita K. Schmutzler, Cologne). This work was also funded by the European Regional Development Fund and Free State of Saxony, Germany (LIFE - Leipzig Research Centre for Civilization Diseases, project numbers 713-241202, 713-241202, 14505/2470, and 14575/2470). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0, and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, the Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, as well as the Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany. The GEPARSIXTO study was conducted by the German Breast Group GmbH. The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and the German Cancer Research Center (DKFZ). GLACIER was supported by Breast Cancer Now, CRUK and Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The HABCS study was supported by the Claudia von Schilling Foundation for Breast Cancer Research, by the Lower Saxonian Cancer Society, and by the Rudolf-Bartling Foundation. The HEBCS was financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society, and the Sigrid Juselius Foundation. The HERPACC was supported by MEXT Kakenhi (No. 170150181 and 26253041) from the Ministry of Education, Science, Sports, Culture and Technology of Japan, by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from Ministry Health, Labour and Welfare of Japan, by Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan, by National Cancer Center Research and Development Fund, and “Practical Research for Innovative Cancer Control (15ck0106177h0001)” from Japan Agency for Medical Research and development, AMED, and Cancer Bio Bank Aichi. The HMBCS was supported by a grant from the Friends of Hannover Medical School and by the Rudolf Bartling Foundation. The HUBCS was supported by a grant from the German Federal Ministry of Research and Education (RUS08/017), and by the Russian Foundation for Basic Research and the Federal Agency for Scientific Organizations for support the Bioresource collections and RFBR grants 14-04-97088, 17-29-06014, and 17-44-020498. ICICLE was supported by Breast Cancer Now, CRUK, and Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (A.L.F.) between Stockholm County Council and Karolinska Institutet, the Swedish Cancer Society, The Gustav V Jubilee foundation and Bert von Kantzows foundation. The KARMA study was supported by Märit and Hans Rausings Initiative Against Breast Cancer. The KBCP was financially supported by the special Government Funding (E.V.O.) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, and by the strategic funding of the University of Eastern Finland. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. Financial support for the AOCS was provided by the United States Army Medical Research and Materiel Command [DAMD17-01-1-0729], Cancer Council Victoria, Queensland Cancer Fund, Cancer Council New South Wales, Cancer Council South Australia, The Cancer Foundation of Western Australia, Cancer Council Tasmania and the National Health and Medical Research Council of Australia (NHMRC; 400413, 400281, 199600). G.C.-T. and P.W. are supported by the NHMRC. RB was a Cancer Institute NSW Clinical Research Fellow. The KOHBRA study was partially supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 1020350; 1420190). LAABC is supported by grants (1RB-0287, 3PB-0102, 5PB-0018, 10PB-0098) from the California Breast Cancer Research Program. Incident breast cancer cases were collected by the USC Cancer Surveillance Program (CSP) which is supported under subcontract by the California Department of Health. The CSP is also part of the National Cancer Institute’s Division of Cancer Prevention and Control Surveillance, Epidemiology, and End Results Program, under contract number N01CN25403. L.M.B.C. is supported by the ‘Stichting tegen Kanker’. D.L. is supported by the FWO. The MABCS study is funded by the Research Centre for Genetic Engineering and Biotechnology “Georgi D. Efremov” and supported by the German Academic Exchange Program, DAAD. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419, 110826, 110828], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. MBCSG is supported by grants from the Italian Association for Cancer Research (AIRC) and by funds from the Italian citizens who allocated the 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects “5 × 1000”). The MCBCS was supported by the NIH grants CA192393, CA116167, CA176785 an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], and the Breast Cancer Research Foundation and a generous gift from the David F. and Margaret T. Grohne Family Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057 and 396414, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. The MEC was support by NIH grants CA63464, CA54281, CA098758, CA132839, and CA164973. The MISS study is supported by funding from ERC-2011-294576 Advanced grant, Swedish Cancer Society, Swedish Research Council, Local hospital funds, Berta Kamprad Foundation, Gunnar Nilsson. The MMHS study was supported by NIH grants CA97396, CA128931, CA116201, CA140286, and CA177150. MSKCC is supported by grants from the Breast Cancer Research Foundation and Robert and Kate Niehaus Clinical Cancer Genetics Initiative. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program – grant # CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade – grant # PSR-SIIRI-701. MYBRCA is funded by research grants from the Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Malaysia. MYMAMMO is supported by research grants from Yayasan Sime Darby LPGA Tournament and Malaysian Ministry of Higher Education (RP046B-15HTM). The NBCS has been supported by the Research Council of Norway grant 193387/V50 (to A.-L. Børresen-Dale and V.N. Kristensen) and grant 193387/H10 (to A.-L. Børresen-Dale and V.N. Kristensen), South Eastern Norway Health Authority (grant 39346 to A.-L. Børresen-Dale and 27208 to V.N. Kristensen) and the Norwegian Cancer Society (to A.-L. Børresen-Dale and 419616 - 71248 - PR-2006-0282 to V.N. Kristensen). It has received funding from the K.G. Jebsen Centre for Breast Cancer Research (2012-2015). The NBHS was supported by NIH grant R01CA100374. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The Northern California Breast Cancer Family Registry (NC-BCFR) and Ontario Familial Breast Cancer Registry (OFBCR) were supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The Carolina Breast Cancer Study was funded by Komen Foundation, the National Cancer Institute (P50 CA058223, U54 CA156733, and U01 CA179715), and the North Carolina University Cancer Research Fund. The NGOBCS was supported by Grants-in-Aid for the Third Term Comprehensive Ten-Year Strategy for Cancer Control from the Ministry of Health, Labor and Welfare of Japan, and for Scientific Research on Priority Areas, 17015049 and for Scientific Research on Innovative Areas, 221S0001, from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. The NHS was supported by NIH grants P01 CA87969, UM1 CA186107, and U19 CA148065. The NHS2 was supported by NIH grants UM1 CA176726 and U19 CA148065. The OBCS was supported by research grants from the Finnish Cancer Foundation, the Academy of Finland (grant number 250083, 122715 and Center of Excellence grant number 251314), the Finnish Cancer Foundation, the Sigrid Juselius Foundation, the University of Oulu, the University of Oulu Support Foundation, and the special Governmental EVO funds for Oulu University Hospital-based research activities. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. Genotyping for PLCO was supported by the Intramural Research Program of the National Institutes of Health, NCI, Division of Cancer Epidemiology and Genetics. The PLCO is supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, National Institutes of Health. The POSH study is funded by Cancer Research UK (grants C1275/A11699, C1275/C22524, C1275/A19187, C1275/A15956, and Breast Cancer Campaign 2010PR62, 2013PR044. PROCAS is funded from NIHR grant PGfAR 0707-10031. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). The SASBAC study was supported by funding from the Agency for Science, Technology and Research of Singapore (A*STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation. The SBCGS was supported primarily by NIH grants R01CA64277, R01CA148667, UMCA182910, and R37CA70867. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The scientific development and funding of this project were, in part, supported by the Genetic Associations and Mechanisms in Oncology (GAME-ON) Network U19 CA148065. The SBCS was supported by Sheffield Experimental Cancer Medicine Centre and Breast Cancer Now Tissue Bank. The SCCS is supported by a grant from the National Institutes of Health (R01 CA092447). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SEARCH is funded by Cancer Research UK [C490/A10124, C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academic Reserve. SEBCS was supported by the BRL (Basic Research Laboratory) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012-0000347). SGBCC is funded by the NUS start-up Grant, National University Cancer Institute Singapore (NCIS) Centre Grant and the NMRC Clinician Scientist Award. Additional controls were recruited by the Singapore Consortium of Cohort Studies-Multi-ethnic cohort (SCCS-MEC), which was funded by the Biomedical Research Council, grant number: 05/1/21/19/425. The Sister Study (SISTER) is supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES049033). The Two Sister Study (2SISTER) was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES102245), and, also by a grant from Susan G. Komen for the Cure, grant FAS0703856. SKKDKFZS is supported by the DKFZ. The SMC is funded by the Swedish Cancer Foundation. The SZBCS was supported by Grant PBZ_KBN_122/P05/2004. The TBCS was funded by The National Cancer Institute, Thailand. The TNBCC was supported by a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), a grant from the Breast Cancer Research Foundation, a generous gift from the David F. and Margaret T. Grohne Family Foundation. The TWBCS is supported by the Taiwan Biobank project of the Institute of Biomedical Sciences, Academia Sinica, Taiwan. The UCIBCS component of this research was supported by the NIH [CA58860, CA92044] and the Lon V Smith Foundation [LVS39420]. The UKBGS is funded by Breast Cancer Now and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The US3SS study was supported by Massachusetts (K.M.E., R01CA47305), Wisconsin (P.A.N., R01 CA47147) and New Hampshire (L.T.-E., R01CA69664) centers, and Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The USRT Study was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The WAABCS study was supported by grants from the National Cancer Institute of the National Institutes of Health (R01 CA89085 and P50 CA125183 and the D43 TW009112 grant), Susan G. Komen (SAC110026), the Dr. Ralph and Marian Falk Medical Research Trust, and the Avon Foundation for Women. The WHI program is funded by the National Heart, Lung, and Blood Institute, the US National Institutes of Health and the US Department of Health and Human Services (HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C). This work was also funded by NCI U19 CA148065-01. D.G.E. is supported by the all Manchester NIHR Biomedical research center Manchester (IS-BRC-1215-20007). HUNBOCS, Hungarian Breast and Ovarian Cancer Study was supported by Hungarian Research Grant KTIA-OTKA CK-80745, NKFI_OTKA K-112228. C.I. received support from the Nontherapeutic Subject Registry Shared Resource at Georgetown University (NIH/NCI P30-CA-51008) and the Jess and Mildred Fisher Center for Hereditary Cancer and Clinical Genomics Research. K.M. is supported by CRUK C18281/A19169. City of Hope Clinical Cancer Community Research Network and the Hereditary Cancer Research Registry, supported in part by Award Number RC4CA153828 (PI: J Weitzel) from the National Cancer Institute and the office of the Directory, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The colorectal cancer genome-wide association analyses: Colorectal Transdisciplinary Study (CORECT): The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CORECT Consortium, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government or the CORECT Consortium. We are incredibly grateful for the contributions of Dr. Brian Henderson and Dr. Roger Green over the course of this study and acknowledge them in memoriam. We are also grateful for support from Daniel and Maryann Fong. ColoCare: we thank the many investigators and staff who made this research possible in ColoCare Seattle and ColoCare Heidelberg. ColoCare was initiated and developed at the Fred Hutchinson Cancer Research Center by Drs. Ulrich and Grady. CCFR: the Colon CFR graciously thanks the generous contributions of their study participants, dedication of study staff, and financial support from the U.S. National Cancer Institute, without which this important registry would not exist. Galeon: GALEON wishes to thank the Department of Surgery of University Hospital of Santiago (CHUS), Sara Miranda Ponte, Carmen M Redondo, and the staff of the Department of Pathology and Biobank of CHUS, Instituto de Investigación Sanitaria de Santiago (IDIS), Instituto de Investigación Sanitaria Galicia Sur (IISGS), SERGAS, Vigo, Spain, and Programa Grupos Emergentes, Cancer Genetics Unit, CHUVI Vigo Hospital, Instituto de Salud Carlos III, Spain. MCCS: this study was made possible by the contribution of many people, including the original investigators and the diligent team who recruited participants and continue to work on follow-up. We would also like to express our gratitude to the many thousands of Melbourne residents who took part in the study and provided blood samples. SEARCH: We acknowledge the contributions of Mitul Shah, Val Rhenius, Sue Irvine, Craig Luccarini, Patricia Harrington, Don Conroy, Rebecca Mayes, and Caroline Baynes. The Swedish low-risk colorectal cancer study: we thank Berith Wejderot and the Swedish low-risk colorectal cancer study group. Genetics & Epidemiology of Colorectal Cancer Consortium (GECCO): we thank all those at the GECCO Coordinating Center for helping bring together the data and people that made this project possible. ASTERISK: we are very grateful to Dr. Bruno Buecher without whom this project would not have existed. We also thank all those who agreed to participate in this study, including the patients and the healthy control persons, as well as all the physicians, technicians and students. DACHS: we thank all participants and cooperating clinicians, and Ute Handte-Daub, Renate Hettler-Jensen, Utz Benscheid, Muhabbet Celik, and Ursula Eilber for excellent technical assistance. HPFS, NHS and PHS: we acknowledge Patrice Soule and Hardeep Ranu of the Dana-Farber Harvard Cancer Center High-Throughput Polymorphism Core who assisted in the genotyping for NHS, HPFS, and PHS under the supervision of Dr. Immaculata Devivo and Dr. David Hunter, Qin (Carolyn) Guo, and Lixue Zhu who assisted in programming for NHS and HPFS and Haiyan Zhang who assisted in programming for the PHS. We thank the participants and staff of the Nurses’ Health Study and the Health Professionals Follow-Up Study, for their valuable contributions as well as the following state cancer registries for their help: A.L., A.Z., A.R., C.A., C.O., C.T., D.E., F.L., G.A., I.D., I.L., I.N., I.A., K.Y., L.A., M.E., M.D., M.A., M.I., N.E., N.H., N.J., N.Y., N.C., N.D., O.H., O.K., O.R., P.A., R.I., S.C., T.N., T.X., V.A., W.A., W.Y. In addition, this study was approved by the Connecticut Department of Public Health (DPH) Human Investigations Committee. Certain data used in this publication were obtained from the DPH. We assume full responsibility for analyses and interpretation of these data. PLCO: we thank Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention, National Cancer Institute, the Screening Center investigators and staff or the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, Mr. Tom Riley and staff, Information Management Services Inc., Ms. Barbara O’Brien and staff, Westat Inc. and Drs. Bill Kopp, Wen Shao and staff, SAIC-Frederick. Most importantly, we acknowledge the study participants for their contributions for making this study possible. The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by NCI. PMH: we thank the study participants and staff of the Hormones and Colon Cancer study. WHI: we thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at https://cleo.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Short20List.pdf. CORECT: The CORECT Study was supported by the National Cancer Institute, National Institutes of Health (NCI/NIH), U.S. Department of Health and Human Services (grant numbers U19 CA148107, R01 CA81488, P30 CA014089, R01 CA197350; P01 CA196569; and R01 CA201407) and National Institutes of Environmental Health Sciences, National Institutes of Health (grant number T32 ES013678). The ATBC Study was supported by the US Public Health Service contracts (N01-CN-45165, N01-RC-45035, N01-RC-37004, and HHSN261201000006C) from the National Cancer Institute. The Cancer Prevention Study-II Nutrition Cohort is funded by the American Cancer Society. ColoCare: This work was supported by the National Institutes of Health (grant numbers R01 CA189184, U01 CA206110, 2P30CA015704-40 (Gilliland)), the Matthias Lackas-Foundation, the German Consortium for Translational Cancer Research, and the EU TRANSCAN initiative. Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO): funding for GECCO was provided by the National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services (grant numbers U01 CA137088, R01 CA059045, and U01 CA164930). This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA015704. The Colon Cancer Family Registry (CFR) Illumina GWAS was supported by funding from the National Cancer Institute, National Institutes of Health (grant numbers U01 CA122839, R01 CA143247). The Colon CFR/CORECT Affymetrix Axiom GWAS and OncoArray GWAS were supported by funding from National Cancer Institute, National Institutes of Health (grant number U19 CA148107 to S.G.). The Colon CFR participant recruitment and collection of data and biospecimens used in this study were supported by the National Cancer Institute, National Institutes of Health (grant number UM1 CA167551) and through cooperative agreements with the following Colon CFR centers: Australasian Colorectal Cancer Family Registry (NCI/NIH grant numbers U01 CA074778 and U01/U24 CA097735), USC Consortium Colorectal Cancer Family Registry (NCI/NIH grant numbers U01/U24 CA074799), Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (NCI/NIH grant number U01/U24 CA074800), Ontario Familial Colorectal Cancer Registry (NCI/NIH grant number U01/U24 CA074783), Seattle Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24 CA074794), and University of Hawaii Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24 CA074806), Additional support for case ascertainment was provided from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute to Fred Hutchinson Cancer Research Center (Control Nos. N01-CN-67009 and N01-PC-35142, and Contract No. HHSN2612013000121), the Hawai’i Department of Health (Control Nos. N01-PC-67001 and N01-PC-35137, and Contract No. HHSN26120100037C, and the California Department of Public Health (contracts HHSN261201000035C awarded to the University of Southern California, and the following state cancer registries: A.Z., C.O., M.N., N.C., N.H., and by the Victoria Cancer Registry and Ontario Cancer Registry. ESTHER/VERDI was supported by grants from the Baden–Württemberg Ministry of Science, Research and Arts and the German Cancer Aid. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. GALEON: FIS Intrasalud (PI13/01136). The MCCS was further supported by Australian NHMRC grants 509348, 209057, 251553, and 504711 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MSKCC: the work at Sloan Kettering in New York was supported by the Robert and Kate Niehaus Center for Inherited Cancer Genomics and the Romeo Milio Foundation. Moffitt: This work was supported by funding from the National Institutes of Health (grant numbers R01 CA189184, P30 CA076292), Florida Department of Health Bankhead-Coley Grant 09BN-13, and the University of South Florida Oehler Foundation. Moffitt contributions were supported in part by the Total Cancer Care Initiative, Collaborative Data Services Core, and Tissue Core at the H. Lee Moffitt Cancer Center & Research Institute, a National Cancer Institute-designated Comprehensive Cancer Center (grant number P30 CA076292). SEARCH: Cancer Research UK (C490/A16561). The Spanish study was supported by Instituto de Salud Carlos III, co-funded by FEDER funds –a way to build Europe– (grants PI14-613 and PI09-1286), Catalan Government DURSI (grant 2014SGR647), and Junta de Castilla y León (grant LE22A10-2). The Swedish Low-risk Colorectal Cancer Study: the study was supported by grants from the Swedish research council; K2015-55 × -22674-01-4, K2008-55 × -20157-03-3, K2006-72 × -20157-01-2 and the Stockholm County Council (ALF project). CIDR genotyping for the Oncoarray was conducted under contract 268201200008I (to K.D.), through grant 101HG007491-01 (to C.I.A.). The Norris Cotton Cancer Center - P30CA023108, The Quantitative Biology Research Institute - P20GM103534, and the Coordinating Center for Screen Detected Lesions - U01CA196386 also supported efforts of C.I.A. This work was also supported by the National Cancer Institute (grant numbers U01 CA1817700, R01 CA144040). ASTERISK: a Hospital Clinical Research Program (PHRC) and supported by the Regional Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue Régionale Contre le Cancer (LRCC). COLO2&3: National Institutes of Health (grant number R01 CA060987). DACHS: This work was supported by the German Research Council (BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, CH 117/1-1, HO 5117/2-1, HE 5998/2-1, KL 2354/3-1, RO 2270/8-1, and BR 1704/17-1), the Interdisciplinary Research Program of the National Center for Tumor Diseases (NCT), Germany, and the German Federal Ministry of Education and Research (01KH0404, 01ER0814, 01ER0815, 01ER1505A, and 01ER1505B). DALS: National Institutes of Health (grant number R01 CA048998 to M.L.S). HPFS is supported by National Institutes of Health (grant numbers P01 CA055075, UM1 CA167552, R01 137178, and P50 CA127003), NHS by the National Institutes of Health (grant numbers UM1 CA186107, R01 CA137178, P01 CA087969, and P50 CA127003), NHSII by the National Institutes of Health (grant numbers R01 050385CA and UM1 CA176726), and PHS by the National Institutes of Health (grant number R01 CA042182). MEC: National Institutes of Health (grant numbers R37 CA054281, P01 CA033619, and R01 CA063464). OFCCR: National Institutes of Health, through funding allocated to the Ontario Registry for Studies of Familial Colorectal Cancer (grant number U01 CA074783); see Colon CFR section above. As subset of ARCTIC, OFCCR is supported by a GL2 grant from the Ontario Research Fund, the Canadian Institutes of Health Research, and the Cancer Risk Evaluation (CaRE) Program grant from the Canadian Cancer Society Research Institute. T.J.H. and B.W.Z. are recipients of Senior Investigator Awards from the Ontario Institute for Cancer Research, through generous support from the Ontario Ministry of Research and Innovation. PLCO: Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. Additionally, a subset of control samples was genotyped as part of the Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer GWAS, Colon CGEMS pancreatic cancer scan (PanScan), and the Lung Cancer and Smoking study. The prostate and PanScan study datasets were accessed with appropriate approval through the dbGaP online resource (http://cgems.cancer.gov/data/) accession numbers phs000207.v1.p1 and phs000206.v3.p2, respectively, and the lung datasets were accessed from the dbGaP website (http://www.ncbi.nlm.nih.gov/gap) through accession number phs000093.v2.p2. Funding for the Lung Cancer and Smoking study was provided by National Institutes of Health (NIH), Genes, Environment and Health Initiative (GEI) Z01 CP 010200, NIH U01 HG004446, and NIH GEI U01 HG 004438. For the lung study, the GENEVA Coordinating Center provided assistance with genotype cleaning and general study coordination, 23 and the Johns Hopkins University Center for Inherited Disease Research conducted genotyping. PMH: National Institutes of Health (grant number R01 CA076366). VITAL: National Institutes of Health (grant number K05-CA154337). WHI: The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. The head and neck cancer genome-wide association analyses: The study was supported by NIH/NCI: P50 CA097190, and P30 CA047904, Canadian Cancer Society Research Institute (no. 020214) and Cancer Care Ontario Research Chair to R.H. The Princess Margaret Hospital Head and Neck Cancer Translational Research Program is funded by the Wharton family, Joe’s Team, Gordon Tozer, Bruce Galloway and the Elia family. Geoffrey Liu was supported by the Posluns Family Fund and the Lusi Wong Family Fund at the Princess Margaret Foundation, and the Alan B. Brown Chair in Molecular Genomics. This publication presents data from Head and Neck 5000 (H&N5000). H&N5000 was a component of independent research funded by the UK National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707-10034). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Human papillomavirus (HPV) in H&N5000 serology was supported by a Cancer Research UK Programme Grant, the Integrative Cancer Epidemiology Programme (grant number: C18281/A19169). National Cancer Institute (R01-CA90731); National Institute of Environmental Health Sciences (P30ES10126). The authors thank all the members of the GENCAPO team/The Head and Neck Genome Project (GENCAPO) was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/12054-9 and 10/51168-0). CPS-II recruitment and maintenance is supported with intramural research funding from the American Cancer Society. Genotyping performed at the Center for Inherited Disease Research (CIDR) was funded through the U.S. National Institute of Dental and Craniofacial Research (NIDCR) grant 1 × 01HG007780-0. The University of Pittsburgh head and neck cancer case-control study is supported by National Institutes of Health grants P50 CA097190 and P30 CA047904. The Carolina Head and Neck Cancer Study (CHANCE) was supported by the National Cancer Institute (R01-CA90731). The Head and Neck Genome Project (GENCAPO) was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/12054-9 and 10/51168-0). The authors thank all the members of the GENCAPO team. The HN5000 study was funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707-10034), the views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The Toronto study was funded by the Canadian Cancer Society Research Institute (020214) and the National Cancer Institute (U19-CA148127) and the Cancer Care Ontario Research Chair. The alcohol-related cancers and genetic susceptibility study in Europe (ARCAGE) was funded by the European Commission’s 5th Framework Program (QLK1-2001-00182), the Italian Association for Cancer Research, Compagnia di San Paolo/FIRMS, Region Piemonte, and Padova University (CPDA057222). The Rome Study was supported by the Associazione Italiana per la Ricerca sul Cancro (AIRC) IG 2011 10491 and IG2013 14220 to S.B., and Fondazione Veronesi to S.B. The IARC Latin American study was funded by the European Commission INCO-DC programme (IC18-CT97-0222), with additional funding from Fondo para la Investigacion Cientifica y Tecnologica (Argentina) and the Fundação de Amparo à Pesquisa do Estado de São Paulo (01/01768-2). We thank Leticia Fernandez, Instituto Nacional de Oncologia y Radiobiologia, La Habana, Cuba and Sergio and Rosalina Koifman, for their efforts with the IARC Latin America study São Paulo center. The IARC Central Europe study was supported by European Commission’s INCO-COPERNICUS Program (IC15- CT98-0332), NIH/National Cancer Institute grant CA92039, and the World Cancer Research Foundation grant WCRF 99A28. The IARC Oral Cancer Multicenter study was funded by grant S06 96 202489 05F02 from Europe against Cancer; grants FIS 97/0024, FIS 97/0662, and BAE 01/5013 from Fondo de Investigaciones Sanitarias, Spain; the UICC Yamagiwa-Yoshida Memorial International Cancer Study; the National Cancer Institute of Canada; Associazione Italiana per la Ricerca sul Cancro; and the Pan-American Health Organization. Coordination of the EPIC study is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The lung cancer genome-wide association analyses: Transdisciplinary Research for Cancer in Lung (TRICL) of the International Lung Cancer Consortium (ILCCO) was supported by (U19-CA148127, CA148127S1, U19CA203654, and Cancer Prevention Research Institute of Texas RR170048). The ILCCO data harmonization is supported by Cancer Care Ontario Research Chair of Population Studies to R. H. and Lunenfeld-Tanenbaum Research Institute, Sinai Health System. The TRICL-ILCCO OncoArray was supported by in-kind genotyping by the Centre for Inherited Disease Research (26820120008i-0-26800068-1). The CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiologia y Salud Pública. CIBERESP, SPAIN. The work performed in the CARET study was supported by the National Institute of Health/National Cancer Institute: UM1 CA167462 (PI: Goodman), National Institute of Health UO1-CA6367307 (PIs Omen, Goodman); National Institute of Health R01 CA111703 (PI Chen), National Institute of Health 5R01 CA151989-01A1(PI Doherty). The Liverpool Lung project is supported by the Roy Castle Lung Cancer Foundation. The Harvard Lung Cancer Study was supported by the NIH (National Cancer Institute) grants CA092824, CA090578, CA074386. The Multi-ethnic Cohort Study was partially supported by NIH Grants CA164973, CA033619, CA63464, and CA148127. The work performed in MSH-PMH study was supported by The Canadian Cancer Society Research Institute (020214), Ontario Institute of Cancer and Cancer Care Ontario Chair Award to R.J.H. and G.L. and the Alan Brown Chair and Lusi Wong Programs at the Princess Margaret Hospital Foundation. NJLCS was funded by the State Key Program of National Natural Science of China (81230067), the National Key Basic Research Program Grant (2011CB503805), the Major Program of the National Natural Science Foundation of China (81390543). The Norway study was supported by Norwegian Cancer Society, Norwegian Research Council. The Shanghai Cohort Study (SCS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The Singapore Chinese Health Study (SCHS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The work in TLC study has been supported in part the James & Esther King Biomedical Research Program (09KN-15), National Institutes of Health Specialized Programs of Research Excellence (SPORE) Grant (P50 CA119997), and by a Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and Research Institute, an NCI designated Comprehensive Cancer Center (grant number P30-CA76292). The Vanderbilt Lung Cancer Study—BioVU dataset used for the analyses described was obtained from Vanderbilt University Medical Center’s BioVU, which is supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by the Vanderbilt CTSA grant UL1TR000445 from NCATS/NIH. Dr. Aldrich was supported by NIH/National Cancer Institute K07CA172294 (PI: Aldrich) and Dr. Bush was supported by NHGRI/NIH U01HG004798 (PI: Crawford). The Copenhagen General Population Study (CGPS) was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The NELCS study: Grant Number P20RR018787 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). The Kentucky Lung Cancer Research Initiative was supported by the Department of Defense [Congressionally Directed Medical Research Program, U.S. Army Medical Research and Materiel Command Program] under award number: 10153006 (W81XWH-11-1-0781). Views and opinions of, and endorsements by the author(s) do not reflect those of the US Army or the Department of Defense. This research was also supported by unrestricted infrastructure funds from the UK Center for Clinical and Translational Science, NIH grant UL1TR000117 and Markey Cancer Center NCI Cancer Center Support Grant (P30 CA177558) Shared Resource Facilities: Cancer Research Informatics, Biospecimen and Tissue Procurement, and Biostatistics and Bioinformatics. The M.D. Anderson Cancer Center study was supported in part by grants from the NIH (P50 CA070907, R01 CA176568) (to X.W.), Cancer Prevention & Research Institute of Texas (RP130502) (to X.W.), and The University of Texas MD Anderson Cancer Center institutional support for the Center for Translational and Public Health Genomics. The deCODE study of smoking and nicotine dependence was funded in part by a grant from NIDA (R01- DA017932). The study in Lodz center was partially funded by Nofer Institute of Occupational Medicine, under task NIOM 10.13: Predictors of mortality from non-small cell lung cancer—field study. Genetic sharing analysis was funded by NIH grant CA194393. The research undertaken by M.D.T., L.V.W., and M.S.A. was partly funded by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. M.D.T. holds a Medical Research Council Senior Clinical Fellowship (G0902313). The work to assemble the FTND GWAS meta-analysis was supported by the National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA) grant number R01 DA035825 (Principal Investigator [PI]: DBH). The study populations included COGEND (dbGaP phs000092.v1.p1 and phs000404.v1.p1), COPDGene (dbGaP phs000179.v3.p2), deCODE Genetics, EAGLE (dbGaP phs000093.vs.p2), and SAGE. dbGaP phs000092.v1.p1). See Hancock et al. Transl Psychiatry 2015 (PMCID: PMC4930126) for the full listing of funding sources and other acknowledgments. The Resource for the Study of Lung Cancer Epidemiology in North Trent (ReSoLuCENT)study was funded by the Sheffield Hospitals Charity, Sheffield Experimental Cancer Medicine Centre and Weston Park Hospital Cancer Charity. The ovarian cancer genome-wide association analysis: The Ovarian Cancer Association Consortium (OCAC) is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME-ON Post-GWAS Initiative (U19-CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium that was funded by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The OCAC OncoArray genotyping project was funded through grants from the U.S. National Institutes of Health (CA1X01HG007491-01 (C.I.A.), U19-CA148112 (T.A.S.), R01-CA149429 (C.M.P.), and R01-CA058598 (M.T.G.); Canadian Institutes of Health Research (MOP-86727 (L.E.K.) and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission’s Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175) and through a grant from the U.S. National Institutes of Health (R01-CA122443 (E.L.G)). Funding for individual studies: AAS: National Institutes of Health (RO1-CA142081); AOV: The Canadian Institutes for Health Research (MOP-86727); AUS: The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command (DAMD17-01-1-0729), National Health & Medical Research Council of Australia (199600, 400413 and 400281), Cancer Councils of New South Wales, Victoria, Queensland, South Australia and Tasmania and Cancer Foundation of Western Australia (Multi-State Applications 191, 211, and 182). The Australian Ovarian Cancer Study gratefully acknowledges additional support from Ovarian Cancer Australia and the Peter MacCallum Foundation; BAV: ELAN Funds of the University of Erlangen-Nuremberg; BEL: National Kankerplan; BGS: Breast Cancer Now, Institute of Cancer Research; BVU: Vanderbilt CTSA grant from the National Institutes of Health (NIH)/National Center for Advancing Translational Sciences (NCATS) (ULTR000445); CAM: National Institutes of Health Research Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Cancer Centre; CHA: Innovative Research Team in University (PCSIRT) in China (IRT1076); CNI: Instituto de Salud Carlos III (PI12/01319); Ministerio de Economía y Competitividad (SAF2012); COE: Department of Defense (W81XWH-11-2-0131); CON: National Institutes of Health (R01-CA063678, R01-CA074850; and R01-CA080742); DKE: Ovarian Cancer Research Fund; DOV: National Institutes of Health R01-CA112523 and R01-CA87538; EMC: Dutch Cancer Society (EMC 2014-6699); EPC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC-2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom); GER: German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research (01 GB 9401) and the German Cancer Research Center (DKFZ); GRC: This research has been co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program of the General Secretariat for Research & Technology: SYN11_10_19 NBCA. Investing in knowledge society through the European Social Fund; GRR: Roswell Park Cancer Institute Alliance Foundation, P30 CA016056; HAW: U.S. National Institutes of Health (R01-CA58598, N01-CN-55424, and N01-PC-67001); HJO: Intramural funding; Rudolf-Bartling Foundation; HMO: Intramural funding; Rudolf-Bartling Foundation; HOC: Helsinki University Research Fund; HOP: Department of Defense (DAMD17-02-1-0669) and NCI (K07-CA080668, R01-CA95023, P50-CA159981 MO1-RR000056 R01-CA126841); HUO: Intramural funding; Rudolf-Bartling Foundation; JGO: JSPS KAKENHI grant; JPN: Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare; KRA: This study (Ko-EVE) was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 0920010); LAX: American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124; LUN: ERC-2011-AdG 294576-risk factors cancer, Swedish Cancer Society, Swedish Research Council, Beta Kamprad Foundation; MAC: National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; Fraternal Order of Eagles; MAL: Funding for this study was provided by research grant R01- CA61107 from the National Cancer Institute, Bethesda, MD, research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mermaid I project; MAS: Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation; MAY: National Institutes of Health (R01-CA122443, P30-CA15083, and P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; MCC: Cancer Council Victoria, National Health and Medical Research Council of Australia (NHMRC) grants number 209057, 251533, 396414, and 504715; MDA: DOD Ovarian Cancer Research Program (W81XWH-07-0449); MEC: NIH (CA54281, CA164973, CA63464); MOF: Moffitt Cancer Center, Merck Pharmaceuticals, the state of Florida, Hillsborough County, and the city of Tampa; NCO: National Institutes of Health (R01-CA76016) and the Department of Defense (DAMD17-02-1-0666); NEC: National Institutes of Health R01-CA54419 and P50-CA105009 and Department of Defense W81XWH-10-1-02802; NHS: UM1 CA186107, P01 CA87969, R01 CA49449, R01-CA67262, UM1 CA176726; NJO: National Cancer Institute (NIH-K07 CA095666, R01-CA83918, NIH-K22-CA138563, and P30-CA072720) and the Cancer Institute of New Jersey; If Sara Olson and/or Irene Orlow is a co-author, please add NCI CCSG award (P30-CA008748) to the funding sources; NOR: Helse Vest, The Norwegian Cancer Society, The Research Council of Norway; NTH: Radboud University Medical Centre; OPL: National Health and Medical Research Council (NHMRC) of Australia (APP1025142) and Brisbane Women’s Club; ORE: OHSU Foundation; OVA: This work was supported by Canadian Institutes of Health Research grant (MOP-86727) and by NIH/NCI 1 R01CA160669-01A1; PLC: Intramural Research Program of the National Cancer Institute; POC: Pomeranian Medical University; POL: Intramural Research Program of the National Cancer Institute; PVD: Canadian Cancer Society and Cancer Research Society GRePEC Program; RBH: National Health and Medical Research Council of Australia; RMH: Cancer Research UK, Royal Marsden Hospital; RPC: National Institute of Health (P50-CA159981, R01-CA126841); SEA: Cancer Research UK (C490/A10119 C490/A10124); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; SIS: NIH, National Institute of Environmental Health Sciences, Z01-ES044005 and Z01-ES049033; SMC: The bbSwedish Research Council-SIMPLER infrastructure; the Swedish Cancer Foundation; SON: National Health Research and Development Program, Health Canada, grant 6613-1415-53; SRO: Cancer Research UK (C536/A13086, C536/A6689) and Imperial Experimental Cancer Research Centre (C1312/A15589); STA: NIH grants U01 CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and VårKampMotCancer foundation; SWH: NIH (NCI) grant R37-CA070867; TBO: National Institutes of Health (R01-CA106414-A2), American Cancer Society (CRTG-00-196-01-CCE), Department of Defense (DAMD17-98-1-8659), Celma Mastery Ovarian Cancer Foundation; TOR: NIH grants R01-CA063678 and R01 CA063682; UCI: NIH R01-CA058860 and the Lon V Smith Foundation grant LVS39420; UHN: Princess Margaret Cancer Centre Foundation-Bridge for the Cure; UKO: The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre; UKR: Cancer Research UK (C490/A6187), UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; USC: P01CA17054, P30CA14089, R01CA61132, N01PC67010, R03CA113148, R03CA115195, N01CN025403, and California Cancer Research Program (00-01389V-20170, 2II0200); VAN: BC Cancer Foundation, VGH & UBC Hospital Foundation; VTL: NIH K05-CA154337; WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16; WOC: National Science Centren (N N301 5645 40). The Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academia Reserve. The prostate cancer genome-wide association analyses: we pay tribute to Brian Henderson, who was a driving force behind the OncoArray project, for his vision and leadership, and who sadly passed away before seeing its fruition. We also thank the individuals who participated in these studies enabling this work. The ELLIPSE/PRACTICAL (http//:practical.icr.ac.uk) prostate cancer consortium and his collaborating partners were supported by multiple funding mechanisms enabling this current work. ELLIPSE/PRACTICAL Genotyping of the OncoArray was funded by the US National Institutes of Health (NIH) (U19 CA148537 for ELucidating Loci Involved in Prostate Cancer SuscEptibility (ELLIPSE) project and X01HG007492 to the Center for Inherited Disease Research (CIDR) under contract number HHSN268201200008I). Additional analytical support was provided by NIH NCI U01 CA188392 (F.R.S.). Funding for the iCOGS infrastructure came from the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112; the GAME-ON initiative), the Department of Defense (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. This work was supported by the Canadian Institutes of Health Research, European Commission’s Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175), Cancer Research UK Grants C5047/A7357, C1287/A10118, C1287/A16563, C5047/A3354, C5047/A10692, C16913/A6135, C5047/A21332 and The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant: No. 1 U19 CA148537-01 (the GAME-ON initiative). We also thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, and The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. The Prostate Cancer Program of Cancer Council Victoria also acknowledge grant support from The National Health and Medical Research Council, Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204, 940394, and 614296), VicHealth, Cancer Council Victoria, The Prostate Cancer Foundation of Australia, The Whitten Foundation, PricewaterhouseCoopers, and Tattersall’s. E.A.O., D.M.K., and E.M.K. acknowledge the Intramural Program of the National Human Genome Research Institute for their support. The BPC3 was supported by the U.S. National Institutes of Health, National Cancer Institute (cooperative agreements U01-CA98233 to D.J.H., U01-CA98710 to S.M.G., U01-CA98216 to E.R., and U01-CA98758 to B.E.H., and Intramural Research Program of NIH/National Cancer Institute, Division of Cancer Epidemiology and Genetics). CAPS GWAS study was supported by the Swedish Cancer Foundation (grant no 09-0677, 11-484, 12-823), the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linneus Centre (Contract ID 70867902) financed by the Swedish Research Council, Swedish Research Council (grant no K2010-70 × -20430-04-3, 2014-2269). The Hannover Prostate Cancer Study was supported by the Lower Saxonian Cancer Society. PEGASUS was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health. RAPPER was supported by the NIHR Manchester Biomedical Research Center, Cancer Research UK (C147/A25254, C1094/A18504) and the EU’s 7th Framework Programme Grant/Agreement no 60186. Overall: this research has been conducted using the UK Biobank Resource (application number 16549). NHS is supported by UM1 CA186107 (NHS cohort infrastructure grant), P01 CA87969, and R01 CA49449. NHSII is supported by UM1 CA176726 (NHSII cohort infrastructure grant), and R01-CA67262. A.L.K. is supported by R01 MH107649. We would like to thank the participants and staff of the NHS and NHSII for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data.

BackgroundAlcohol consumption and cigarette smoking are associated with an increased risk of breast cancer (BC), but it is unclear whether these associations vary by a woman’s familial BC risk.MethodsUsing the Prospective Family Study Cohort, we evaluated associations between alcohol consumption, cigarette smoking, and BC risk. We used multivariable Cox proportional hazard models to estimate hazard ratios (HR) and 95% confidence intervals (CI). We examined whether associations were modified by familial risk profile (FRP), defined as the 1-year incidence of BC predicted by Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), a pedigree-based algorithm.ResultsWe observed 1009 incident BC cases in 17,435 women during a median follow-up of 10.4 years. We found no overall association of smoking or alcohol consumption with BC risk (current smokers compared with never smokers HR 1.02, 95% CI 0.85–1.23; consuming ≥ 7 drinks/week compared with non-regular drinkers HR 1.10, 95% CI 0.92–1.32), but we did observe differences in associations based on FRP and by estrogen receptor (ER) status. Women with lower FRP had an increased risk of ER-positive BC associated with consuming ≥ 7 drinks/week (compared to non-regular drinkers), whereas there was no association for women with higher FRP. For example, women at the 10th percentile of FRP (5-year BOADICEA = 0.15%) had an estimated HR of 1.46 (95% CI 1.07–1.99), whereas there was no association for women at the 90th percentile (5-year BOADICEA = 4.2%) (HR 1.07, 95% CI 0.80–1.44). While the associations with smoking were not modified by FRP, we observed a positive multiplicative interaction by FRP (pinteraction = 0.01) for smoking status in women who also consumed alcohol, but not in women who were non-regular drinkers.ConclusionsModerate alcohol intake was associated with increased BC risk, particularly for women with ER-positive BC, but only for those at lower predicted familial BC risk (5-year BOADICEA

The NCCN Guidelines for Breast Cancer Screening and Diagnosis have been developed to facilitate clinical decision making. This manuscript discusses the diagnostic evaluation of individuals with suspected breast cancer due to either abnormal imaging and/or physical findings. For breast cancer screening recommendations, please see the full guidelines on NCCN.org.

Background Full-term pregnancy (FTP) is associated with a reduced breast cancer (BC) risk over time, but women are at increased BC risk in the immediate years following an FTP. No large prospective studies, however, have examined whether the number and timing of pregnancies are associated with BC risk for BRCA1 and BRCA2 mutation carriers. Methods Using weighted and time-varying Cox proportional hazards models, we investigated whether reproductive events are associated with BC risk for mutation carriers using a retrospective cohort (5707 BRCA1 and 3525 BRCA2 mutation carriers) and a prospective cohort (2276 BRCA1 and 1610 BRCA2 mutation carriers), separately for each cohort and the combined prospective and retrospective cohort. Results For BRCA1 mutation carriers, there was no overall association with parity compared with nulliparity (combined hazard ratio [HRc] = 0.99, 95% confidence interval [CI] = 0.83 to 1.18). Relative to being uniparous, an increased number of FTPs was associated with decreased BC risk (HRc = 0.79, 95% CI = 0.69 to 0.91; HRc = 0.70, 95% CI = 0.59 to 0.82; HRc = 0.50, 95% CI = 0.40 to 0.63, for 2, 3, and ≥4 FTPs, respectively, Ptrend < .0001) and increasing duration of breastfeeding was associated with decreased BC risk (combined cohort Ptrend = .0003). Relative to being nulliparous, uniparous BRCA1 mutation carriers were at increased BC risk in the prospective analysis (prospective hazard ration [HRp] = 1.69, 95% CI = 1.09 to 2.62). For BRCA2 mutation carriers, being parous was associated with a 30% increase in BC risk (HRc = 1.33, 95% CI = 1.05 to 1.69), and there was no apparent decrease in risk associated with multiparity except for having at least 4 FTPs vs. 1 FTP (HRc = 0.72, 95% CI = 0.54 to 0.98). Conclusions These findings suggest differential associations with parity between BRCA1 and BRCA2 mutation carriers with higher risk for uniparous BRCA1 carriers and parous BRCA2 carriers.

Summary Background Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance. Methods In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20–70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and participants younger than 50 years at recruitment. We also assessed the effect that limited data input (eg, restriction of the amount of family history and non-genetic information included) had on the models' performance. Findings After median follow-up of 11·1 years (IQR 6·0–14·4), 619 (4%) of 15 732 women selected from the ProF-SC cohort study were prospectively diagnosed with breast cancer after recruitment, of whom 519 (84%) had histologically confirmed disease. BOADICEA and IBIS were well calibrated in the overall validation cohort, whereas BRCAPRO and BCRAT underpredicted risk (ratio of expected cases to observed cases 1·05 [95% CI 0·97–1·14] for BOADICEA, 1·03 [0·96–1·12] for IBIS, 0·59 [0·55–0·64] for BRCAPRO, and 0·79 [0·73–0·85] for BRCAT). The estimated C-statistics for the complete validation cohort were 0·70 (95% CI 0·68–0·72) for BOADICEA, 0·71 (0·69–0·73) for IBIS, 0·68 (0·65–0·70) for BRCAPRO, and 0·60 (0·58–0·62) for BCRAT. In subgroup analyses by BRCA mutation status, the ratio of expected to observed cases for BRCA-negative women was 1·02 (95% CI 0·93–1·12) for BOADICEA, 1·00 (0·92–1·10) for IBIS, 0·53 (0·49–0·58) for BRCAPRO, and 0·97 (0·89–1·06) for BCRAT. For BRCA-positive participants, BOADICEA and IBIS were well calibrated, but BRCAPRO underpredicted risk (ratio of expected to observed cases 1·17 [95% CI 0·99–1·38] for BOADICEA, 1·14 [0·96–1·35] for IBIS, and 0·80 [0·68–0·95] for BRCAPRO). We noted similar patterns of calibration for women younger than 50 years at recruitment. Finally, BOADICEA and IBIS predictive scores were not appreciably affected by limiting input data to family history for first-degree and second-degree relatives. Interpretation Our results suggest that models that include multigenerational family history, such as BOADICEA and IBIS, have better ability to predict breast cancer risk, even for women at average or below-average risk of breast cancer. Although BOADICEA and IBIS performed similarly, further improvements in the accuracy of predictions could be possible with hybrid models that incorporate the polygenic risk component of BOADICEA and the non-family-history risk factors included in IBIS. Funding US National Institutes of Health, National Cancer Institute, Breast Cancer Research Foundation, Australian National Health and Medical Research Council, Victorian Health Promotion Foundation, Victorian Breast Cancer Research Consortium, Cancer Australia, National Breast Cancer Foundation, Queensland Cancer Fund, Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and Cancer Foundation of Western Australia.

Returning genomic research results to family members raises complex questions. Genomic research on life-limiting conditions such as cancer, and research involving storage and reanalysis of data and specimens long into the future, makes these questions pressing. This author group, funded by an NIH grant, published consensus recommendations presenting a framework. This follow-up paper offers concrete guidance and tools for implementation. The group collected and analyzed relevant documents and guidance, including tools from the Clinical Sequencing Exploratory Research (CSER) Consortium. The authors then negotiated a consensus toolkit of processes and documents. That toolkit offers sample consent and notification documents plus decision flow-charts to address return of results to family of living and deceased participants, in adult and pediatric research. Core concerns are eliciting participant preferences on sharing results with family and on choice of a representative to make decisions about sharing after participant death.

Telephone disclosure of cancer genetic test results is noninferior to in-person disclosure. However, how patients who prefer in-person communication of results differ from those who agree to telephone disclosure is unclear but important when considering delivery models for genetic medicine. Patients undergoing cancer genetic testing were recruited to a multicenter, randomized, noninferiority trial (NCT01736345) comparing telephone to in-person disclosure of genetic test results. We evaluated preferences for in-person disclosure, factors associated with this preference and outcomes compared to those who agreed to randomization. Among 1178 enrolled patients, 208 (18%) declined randomization, largely given a preference for in-person disclosure. These patients were more likely to be older (P = 0.007) and to have had multigene panel testing (P < 0.001). General anxiety (P = 0.007), state anxiety (P = 0.008), depression (P = 0.011), cancer-specific distress (P = 0.021) and uncertainty (P = 0.03) were higher after pretest counseling. After disclosure of results, they also had higher general anxiety (P = 0.003), depression (P = 0.002) and cancer-specific distress (P = 0.043). While telephone disclosure is a reasonable alternative to in-person disclosure in most patients, some patients have a strong preference for in-person communication. Patient age, distress and complexity of testing are important factors to consider and requests for in-person disclosure should be honored when possible.

Background The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman’s familial risk. Methods We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline. Results The strength and direction of the BMI risk association depended on baseline menopausal status (P

Background Younger age at onset of breast development, which has been declining in recent decades, is associated with increased breast cancer risk independent of age at menarche. Given the need to study the drivers of these trends, it is essential to validate methods to assess breast onset that can be used in large-scale studies when direct clinical assessment of breast onset is not feasible. Methods Breast development is usually measured by Tanner stages (TSs), assessed either by physical examination or by mother’s report using a picture-based Sexual Maturation Scale (SMS). As an alternative, a mother-reported Pubertal Development Scale (PDS) without pictures has been used in some studies. We compared agreement of SMS and PDS with each other (n = 1022) and the accuracy of PDS with clinical TS as a gold standard for the subset of girls with this measure (n = 282) using the LEGACY cohort. We further compared prediction of breast onset using ROC curves and tested whether adding urinary estrone 1-glucuronide (E1G) improved the AUC. Results The agreement of PDS with SMS was high (kappa = 0.80). The sensitivity of PDS vs clinical TS was 86.6%. The AUCs for PDS alone and SMS alone were 0.88 and 0.79, respectively. Including E1G concentrations improved the AUC for both methods (0.91 and 0.86 for PDS and SMS, respectively). Conclusions The PDS without pictures is a highly accurate, sensitive, and specific method for assessing breast onset, especially in settings where clinical TS is not feasible. In addition, it is comparable to SMS methods with pictures and thus easier to implement in large-scale studies, particularly phone-based interviews where pictures may not be available. Urinary E1G can improve accuracy over than PDS or SMS alone. Electronic supplementary material The online version of this article (10.1186/s13058-018-0943-9) contains supplementary material, which is available to authorized users.

Background For BRCA1 and BRCA2 mutation carriers, the association between oral contraceptive preparation (OCP) use and breast cancer (BC) risk is still unclear. Methods Breast camcer risk associations were estimated from OCP data on 6030 BRCA1 and 3809 BRCA2 mutation carriers using age-dependent Cox regression, stratified by study and birth cohort. Prospective, left-truncated retrospective and full-cohort retrospective analyses were performed. Results For BRCA1 mutation carriers, OCP use was not associated with BC risk in prospective analyses (hazard ratio [HR] = 1.08, 95% confidence interval [CI] = 0.75 to 1.56), but in the left-truncated and full-cohort retrospective analyses, risks were increased by 26% (95% CI = 6% to 51%) and 39% (95% CI = 23% to 58%), respectively. For BRCA2 mutation carriers, OCP use was associated with BC risk in prospective analyses (HR = 1.75, 95% CI = 1.03 to 2.97), but retrospective analyses were inconsistent (left-truncated: HR = 1.06, 95% CI = 0.85 to 1.33; full cohort: HR = 1.52, 95% CI = 1.28 to 1.81). There was evidence of increasing risk with duration of use, especially before the first full-term pregnancy (BRCA1: both retrospective analyses, P < .001 and P = .001, respectively; BRCA2: full retrospective analysis, P = .002). Conclusions Prospective analyses did not show that past use of OCP is associated with an increased BC risk for BRCA1 mutation carriers in young middle-aged women (40–50 years). For BRCA2 mutation carriers, a causal association is also not likely at those ages. Findings between retrospective and prospective analyses were inconsistent and could be due to survival bias or a true association for younger women who were underrepresented in the prospective cohort. Given the uncertain safety of long-term OCP use for BRCA1/2 mutation carriers, indications other than contraception should be avoided and nonhormonal contraceptive methods should be discussed.

Concepts of disease risk and its management are central to processes of medicalisation and pharmaceuticalisation. Through a narrative perspective, this paper aims to understand how such macro-level developments may (or may not) be experienced individually, and how an algorithm that is used for recruitment into a clinical trial may structure individual notions of being ‘at risk’ and ‘in need of treatment’. We interviewed thirty-one women participating in the Study of Tamoxifen and Raloxifene (STAR), a chemoprevention trial conducted in the US between 1999 and 2006. Interviews were thematically analysed. Women in the study had experienced the threat of breast cancer and felt vulnerable to developing the disease prior to STAR participation. The diagnosis of ‘being at risk’ for cancer through an algorithm that determined risk-eligibility for STAR, opened up the possibility for the women to heal. The trial became a means to recognise and collectivise the women's experiences of vulnerability. Through medication intake, being cared for by study coordinators, and the sense of community with other STAR participants, trial participation worked to transform women's lives. Such transformative experiences may nevertheless have been temporary, enduring only as long as the close links to the medical institution through trial participation lasted.

Background: Decision-making experts emphasize that understanding and using probabilistic information are important for making informed decisions about medical treatments involving complex risk–benefit tradeoffs. Yet empirical research demonstrates that individuals may not use probabilities when making decisions. Objectives: To explore decision making and the use of probabilities for decision making from the perspective of women who were risk-eligible to enroll in the Study of Tamoxifen and Raloxifene (STAR). Methods: We conducted narrative interviews with 20 women who agreed to participate in STAR and 20 women who declined. The project was based on a narrative approach. Analysis included the development of summaries of each narrative, and thematic analysis with developing a coding scheme inductively to code all transcripts to identify emerging themes. Results: Interviewees explained and embedded their STAR decisions within experiences encountered throughout their lives. Such lived experiences included but were not limited to breast cancer family history, a personal history of breast biopsies, and experiences or assumptions about taking tamoxifen or medicines more generally. Conclusions: Women’s explanations of their decisions about participating in a breast cancer chemoprevention trial were more complex than decision strategies that rely solely on a quantitative risk–benefit analysis of probabilities derived from populations In addition to precise risk information, clinicians and risk communicators should recognize the importance and legitimacy of lived experience in individual decision making.

Breast cancer is the most frequently diagnosed malignancy in women in the United States and is second only to lung cancer as a cause of cancer death. To assist women who are at increased risk of developing breast cancer and their physicians in the application of individualized strategies to reduce breast cancer risk, NCCN has developed these guidelines for breast cancer risk reduction.

Multiplex genetic testing, including both moderate- and high-penetrance genes for cancer susceptibility, is associated with greater uncertainty than traditional testing, presenting challenges to informed consent and genetic counseling. We sought to develop a new model for informed consent and genetic counseling for four ongoing studies.Drawing from professional guidelines, literature, conceptual frameworks, and clinical experience, a multidisciplinary group developed a tiered-binned genetic counseling approach proposed to facilitate informed consent and improve outcomes of cancer susceptibility multiplex testing.In this model, tier 1 "indispensable" information is presented to all patients. More specific tier 2 information is provided to support variable informational needs among diverse patient populations. Clinically relevant information is "binned" into groups to minimize information overload, support informed decision making, and facilitate adaptive responses to testing. Seven essential elements of informed consent are provided to address the unique limitations, risks, and uncertainties of multiplex testing.A tiered-binned model for informed consent and genetic counseling has the potential to address the challenges of multiplex testing for cancer susceptibility and to support informed decision making and adaptive responses to testing. Future prospective studies including patient-reported outcomes are needed to inform how to best incorporate multiplex testing for cancer susceptibility into clinical practice.Genet Med 17 6, 485-492.

Background : Although epidemiologic studies have found evidence that aspirin use may be inversely associated with breast cancer (BC) risk, little is known about whether this applies to BRCA1 and BRCA2 mutation carriers. Methods : We compared aspirin use in 613 women with BRCA1 or BRCA2 mutations from the six centers of the Breast Cancer Family Registry (BCFR) who were recruited at baseline and completed a questionnaire at 10 year follow-up. We defined cases as carriers with BC (n = 215 with BRCA1 mutations and 137 with BRCA2 mutations) and controls as carriers unaffected with BC (n = 141 with BRCA1 mutations and 120 with BRCA2 mutations). We used logistic regression to estimate odds ratios and 95% confidence intervals separately by gene mutation type. Results : Three cases (1.4%) and 27 controls (19.1%) among the BRCA1 carriers and 3 cases (2.2%) and 25 controls (20.8%) among the BRCA2 carriers reported ever use of aspirin-based medications before diagnosis. Aspirin use before diagnosis was inversely associated with BC risk for both BRCA1 (OR, 0.13; 95% CI, 0.04-0.46 for ever vs. never use) and BRCA2 (OR, 0.12; 95% CI, 0.03-0.41 for ever vs. never use) carriers, after adjusting for age and center for BRCA1 carriers and age for BRCA2 carriers. Conclusion : If replicated by larger, prospective studies, aspirin use could become an inexpensive and acceptable risk-reducing measure for BRCA1 and BRCA2 mutation carriers. Citation Format: Naomi Kornhauser, Mary Beth Terry, Linda T Vahdat, Irene Andrulis, Saundra Buys, Mary Daly, Esther John, John L Hopper, Tessa Cigler. Aspirin and breast cancer risk for BRCA1 and BRCA2 mutation carriers [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P3-08-04.