Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk.

Background: Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers of (CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS).

Methods: We analyzed >22 million variants for 398,238 women.

Examination of fully automated mammographic density measures using LIBRA and breast cancer risk in a cohort of 21,000 non-Hispanic white women.

Background: Breast density is strongly associated with breast cancer risk. Fully automated quantitative density assessment methods have recently been developed that could facilitate large-scale studies, although data on associations with long-term breast cancer risk are limited. We examined LIBRA assessments and breast cancer risk and compared results to prior assessments using Cumulus, an established computer-assisted method requiring manual thresholding.

Ovarian cancer pathology characteristics as predictors of variant pathogenicity in BRCA1 and BRCA2.

Background: The distribution of ovarian tumour characteristics differs between germline BRCA1 and BRCA2 pathogenic variant carriers and non-carriers. In this study, we assessed the utility of ovarian tumour characteristics as predictors of BRCA1 and BRCA2 variant pathogenicity, for application using the American College of Medical Genetics and the Association for Molecular Pathology (ACMG/AMP) variant classification system.

Methods: Data for 10,373 ovarian cancer cases, including carriers and non-carriers of BRCA1 or BRCA2 pathogenic variants, were collected from unpublished international cohorts and consortia and published studies.

Lifetime ovulatory years and risk of epithelial ovarian cancer: a multinational pooled analysis.

Background: The role of ovulation in epithelial ovarian cancer (EOC) is supported by the consistent protective effects of parity and oral contraceptive use. Whether these factors protect through anovulation alone remains unclear. We explored the association between lifetime ovulatory years (LOY) and EOC.

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci.

Background: Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.

Methods: Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test.

Outdoor ambient air pollution and breast cancer survival among California participants of the Multiethnic Cohort Study.

Background: Within the Multiethnic Cohort (MEC), we examined the association between air pollution and mortality among African American, European American, Japanese American, and Latina American women diagnosed with breast cancer.

Methods: We used a land use regression (LUR) model and kriging interpolation to estimate nitrogen oxides (NO NO) and particulate matter (PM, PM) exposures for 3,089 breast cancer cases in the MEC, who were diagnosed from 1993 through 2013 and resided largely in Los Angeles County, California. Cox proportional hazards models were used to examine the association of time-varying air pollutants with all-cause, breast cancer, cardiovascular disease (CVD), and non-breast cancer/non-CVD mortality, accounting for key covariates.

Polygenic risk modeling for prediction of epithelial ovarian cancer risk.

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction.

Comparing 5-Year and Lifetime Risks of Breast Cancer using the Prospective Family Study Cohort.

Background: Clinical guidelines often use predicted lifetime risk from birth to define criteria for making decisions regarding breast cancer screening rather than thresholds based on absolute 5-year risk from current age.

Methods: We used the Prospective Family Cohort Study of 14 657 women without breast cancer at baseline in which, during a median follow-up of 10 years, 482 women were diagnosed with invasive breast cancer. We examined the performances of the International Breast Cancer Intervention Study (IBIS) and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk models when using the alternative thresholds by comparing predictions based on 5-year risk with those based on lifetime risk from birth and remaining lifetime risk.

Cross-Cancer Genome-Wide Association Study of Endometrial Cancer and Epithelial Ovarian Cancer Identifies Genetic Risk Regions Associated with Risk of Both Cancers.

Background: Accumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers.

Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk.

Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.

Two-stage Study of Familial Prostate Cancer by Whole-exome Sequencing and Custom Capture Identifies 10 Novel Genes Associated with the Risk of Prostate Cancer.

Background: Family history of prostate cancer (PCa) is a well-known risk factor, and both common and rare genetic variants are associated with the disease.

Objective: To detect new genetic variants associated with PCa, capitalizing on the role of family history and more aggressive PCa.

Design, Setting, And Participants: A two-stage design was used.

Expanding Our Understanding of Ovarian Cancer Risk: The Role of Incomplete Pregnancies.

Background: Parity is associated with decreased risk of invasive ovarian cancer; however, the relationship between incomplete pregnancies and invasive ovarian cancer risk is unclear. This relationship was examined using 15 case-control studies from the Ovarian Cancer Association Consortium (OCAC). Histotype-specific associations, which have not been examined previously with large sample sizes, were also evaluated.

Clinical and pathological associations of PTEN expression in ovarian cancer: a multicentre study from the Ovarian Tumour Tissue Analysis Consortium.

Background: PTEN loss is a putative driver in histotypes of ovarian cancer (high-grade serous (HGSOC), endometrioid (ENOC), clear cell (CCOC), mucinous (MOC), low-grade serous (LGSOC)). We aimed to characterise PTEN expression as a biomarker in epithelial ovarian cancer in a large population-based study.

Methods: Tumours from 5400 patients from a multicentre observational, prospective cohort study of the Ovarian Tumour Tissue Analysis Consortium were used to evaluate associations between immunohistochemical PTEN patterns and overall survival time, age, stage, grade, residual tumour, CD8+ tumour-infiltrating lymphocytes (TIL) counts, expression of oestrogen receptor (ER), progesterone receptor (PR) and androgen receptor (AR) by means of Cox proportional hazard models and generalised Cochran-Mantel-Haenszel tests.

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

Background: iPrevent is an online breast cancer (BC) risk management decision support tool. It uses an internal switching algorithm, based on a woman's risk factor data, to estimate her absolute BC risk using either the International Breast Cancer Intervention Study (IBIS) version 7.02, or Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm version 3 models, and then provides tailored risk management information.

Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results.

The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study).

Publisher Correction: Shared heritability and functional enrichment across six solid cancers.

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

Race/Ethnicity and Accuracy of Self-Reported Female First-Degree Family History of Breast and Other Cancers in the Northern California Breast Cancer Family Registry.

Background: Few studies have evaluated accuracy of self-reported family history of breast and other cancers in racial/ethnic minorities.

Methods: We assessed the accuracy of cancer family history reports by women with breast cancer (probands) from the Northern California Breast Cancer Family Registry compared with 2 reference standards: personal cancer history reports by female first-degree relatives and California Cancer Registry records.

Results: Probands reported breast cancer in first-degree relatives with high accuracy, but accuracy was lower for other cancers.