Mutational spectrum in a worldwide study of 29,700 families with BRCA1 or BRCA2 mutations

The prevalence and spectrum of germline mutations in BRCA1 and BRCA2 have been reported in single populations, with the majority of reports focused on White in Europe and North America. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has assembled data on 18,435 families with BRCA1 mutations and 11,351 families with BRCA2 mutations ascertained from 69 centers in 49 countries on six continents. This study comprehensively describes the characteristics of the 1,650 unique BRCA1 and 1,731 unique BRCA2 deleterious (disease-associated) mutations identified in the CIMBA database. We observed substantial variation in mutation type and frequency by geographical region and race/ethnicity. In addition to known founder mutations, mutations of relatively high frequency were identified in specific racial/ethnic or geographic groups that may reflect founder mutations and which could be used in targeted (panel) first pass genotyping for specific populations. Knowledge of the population-specific mutational spectrum in BRCA1 and BRCA2 could inform efficient strategies for genetic testing and may justify a more broad-based oncogenetic testing in some populations

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. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.Peer reviewe

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. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

Association of Type and Location of BRCA1 and BRCA2 Mutations With Risk of Breast and Ovarian Cancer (vol 313, pg 1347, 2015)

Heli Nevanlinna ja Kristiina Aittomäki ovat CIMBA Consortium -työryhmän jäseniä.IMPORTANCE Limited information about the relationship between specific mutations in BRCA1 or BRCA2 (BRCA1/2) and cancer risk exists. OBJECTIVE To identify mutation-specific cancer risks for carriers of BRCA1/2. DESIGN, SETTING, AND PARTICIPANTS Observational study of women who were ascertained between 1937 and 2011 (median, 1999) and found to carry disease-associated BRCA1 or BRCA2 mutations. The international sample comprised 19 581 carriers of BRCA1 mutations and 11 900 carriers of BRCA2 mutations from 55 centers in 33 countries on 6 continents. We estimated hazard ratios for breast and ovarian cancer based on mutation type, function, and nucleotide position. We also estimated RHR, the ratio of breast vs ovarian cancer hazard ratios. A value of RHR greater than 1 indicated elevated breast cancer risk; a value of RHR less than 1 indicated elevated ovarian cancer risk. EXPOSURES Mutations of BRCA1 or BRCA2. MAIN OUTCOMES AND MEASURES Breast and ovarian cancer risks. RESULTS Among BRCA1 mutation carriers, 9052 women (46%) were diagnosed with breast cancer, 2317(12%) with ovarian cancer, 1041 (5%) with breast and ovarian cancer, and 7171 (37%) without cancer. Among BRCA2 mutation carriers, 6180 women (52%) were diagnosed with breast cancer, 682(6%) with ovarian cancer, 272(2%) with breast and ovarian cancer, and 4766 (40%) without cancer. In BRCA1, we identified 3 breast cancer cluster regions (BCCRs) located at c.179 to c.505 (BCCR1; RHR = 1.46; 95% Cl, 1.22-1.74; P = 2 x 10(-6)), c.4328 to c.4945 (BCCR2; RH R = 1.34; 95% Cl, 1.01-1.78; P =.04), and c. 5261 to c.5563 (BCCR2', RHR = 1.38; 95% Cl, 1.22-1.55; P = 6 x 10(-9)). We also identified an ovarian cancer cluster region (OCCR) from c.1380 to c.4062 (approximately exon 11) with RHR = 0.62 (95% Cl, 0.56-0.70; P = 9 x 10(-17)). In BRCA2, we observed multiple BCCRs spanning c.1 to c.596 (BCCR1; RHR = 1.71; 95% Cl, 1.06-2.78; P =.03), c.772 to c.1806 (BCCRI; RHR = 1.63; 95% Cl, 1.10-2.40; P =.01), and c.7394 to c.8904 (BCCR2; RHR = 2.31; 95% Cl, 1.69-3.16; P =.00002). We also identified 3 OCCRs: the first (OCCR1) spanned c.3249 to c.5681 that was adjacent to c.5946delT (6174delT; RHR = 0.51; 95% Cl, 0.44-0.60; P = 6 x 10(-17)). The second OCCR spanned c.6645 to c.7471 (OCCR2; RHR = 0.57; 95% Cl, 0.41-0.80; P =.001). Mutations conferring nonsense-mediated decay were associated with differential breast or ovarian cancer risks and an earlier age of breast cancer diagnosis for both BRCA1 and BRCA2 mutation carriers. CONCLUSIONS AND RELEVANCE Breast and ovarian cancer risks varied by type and location of BRCA1/2 mutations. With appropriate validation, these data may have implications for risk assessment and cancer prevention decision making for carriers of BRCA1 and BRCA2 mutations.Peer reviewe

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. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

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. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for nonmucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.http://www.nature.com/ejhgam2023Genetic

Risks of breast and ovarian cancer for women harboring pathogenic missense variants in BRCA1 and BRCA2 compared with those harboring protein truncating variants

PurposeGermline genetic testing for BRCA1 and BRCA2 variants has been a part of clinical practice for >2 decades. However, no studies have compared the cancer risks associated with missense pathogenic variants (PVs) with those associated with protein truncating (PTC) variants.MethodsWe collected 582 informative pedigrees segregating 1 of 28 missense PVs in BRCA1 and 153 pedigrees segregating 1 of 12 missense PVs in BRCA2. We analyzed 324 pedigrees with PTC variants in BRCA1 and 214 pedigrees with PTC variants in BRCA2. Cancer risks were estimated using modified segregation analysis.ResultsEstimated breast cancer risks were markedly lower for women aged >50 years carrying BRCA1 missense PVs than for the women carrying BRCA1 PTC variants (hazard ratio [HR] = 3.9 [2.4-6.2] for PVs vs 12.8 [5.7-28.7] for PTC variants; P = .01), particularly for missense PVs in the BRCA1 C-terminal domain (HR = 2.8 [1.4-5.6]; P = .005). In case of BRCA2, for women aged >50 years, the HR was 3.9 (2.0-7.2) for those heterozygous for missense PVs compared with 7.0 (3.3-14.7) for those harboring PTC variants. BRCA1 p.[Cys64Arg] and BRCA2 p.[Trp2626Cys] were associated with particularly low risks of breast cancer compared with other PVs.ConclusionThese results have important implications for the counseling of at-risk women who harbor missense PVs in the BRCA1/2 genes

Metadata supporting data files of the related manuscript: The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer

In this study, the authors tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk. In vitro experiments were also carried out whereby these three variants were studied functionally by measuring survival and chromosome fragility in FANCM − / − patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib.Data access: A subset of the genotype data analysed in this study (that originated from the Oncoarray Consortium project) is publicly available from the dbGaP repository. A subset of the genotype data generated as part of the BCAC studies (and analysed in the present study) can be accessed at https://identifiers.org/dbgap:phs001265.v1.p1. A subset of the genotype data generated as part of the CIMBA studies (and analysed in the present study) can be accessed at https://identifiers.org/dbgap:phs001321.v1.p1. The remaining genotype data analysed in the present study (and generated in the BCAC and CIMBA studies listed in supplementary Tables 4 and 5 of the related article respectively) are not publicly available due to restraints imposed by the ethics committees of individual studies but can be accessed from the corresponding author on reasonable request; Dr. Paolo Peterlongo, Genome Diagnostics Program, IFOM, The FIRC Institute for Molecular Oncology, Via Adamello 16 - 20139 Milano (Italy), email address: [email protected]. Datasets survivals DEB e OLAPARIB.pzfx (supporting figure 1 and supplementary tables 2 and 3 in the published article) and chromatidics breaks distribution.xlsx (supporting figure 1 in the published article) generated during this study can be accessed from the corresponding author on reasonable request as described above.Participant consent: All participating studies were approved by their ethics review boards and followed national guidelines for informed consent. However, due to the retrospective nature of the majority of the studies, not all participant individuals have provided written informed consent to take part in the present analysis. The Milan Breast Cancer Study Group (MBCSG) was approved by ethics committee from Istituto Nazionale dei Tumori di Milano and Istituto Europeo di Oncologia, in Milan.Study aims and methodology: Previous studies identified several protein-truncating variants in the FANCM gene, which encodes for a DNA translocase, that were described as moderate breast cancer risk factors with a greater risk of triple negative breast cancer (TNBC). This study aimed to investigate the effect of FANCM further, by testing three recurrent truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931*, within the OncoArray Consortium, a collaboration of consortia established to discover germline genetic variants predisposing to different human cancers (e.g., breast, colon, lung, ovary, endometrium and prostate cancers). These three variants were tested for association with breast cancer risk in 67 112 breast cancer cases, 53 766 controls and 26 662 carriers of pathogenic variants of BRCA1 or BRCA2. The individuals included in this study were women of genetically confirmed European ancestry who were originally ascertained in 73 case-control studies from 19 countries participating in the Breast Cancer Association Consortium (BCAC) or in 59 studies enrolling BRCA1 or BRCA2 pathogenic variants carrier from 30 countries participating in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). The CIMBA studies contributed 15 679 carriers of a pathogenic BRCA1 variant and 10 983 carriers of a pathogenic BRCA2 variant to this analysis. The BCAC studies contributed 67 112 invasive breast cancer cases and 53 766 controls. Genotyping of FANCM:p.Arg658*, p.Gln1701* and p.Arg1931* truncating variants was conducted using a custom-designed Illumina genotyping array (the “OncoArray”, Illumina, Inc. San Diego, CA, USA) at six independent laboratories.Additionally, the authors studied the functional effect of these three variants after their lentiviral transduction into a FANCM−/− patient-derived cell line, EGF280, in which they measured survival and chromosome fragility after exposure to diepoxybutane (DEB) or the poly (ADP-ribose) polymerase inhibitor (PARPi) olaparib.Statistical analyses of the genotype data, western blot and mRNA experiments are described in detail in the published article.Dataset description:Data supporting table 1: Data SNP Genotypes from Illumina array and variables datasets include single variant and burden analyses of FANCM:p.Arg658*, p.Gln1701* and p.Arg1931 cases and controls, a subset of which can be accessed from the dbGaP repository at https://identifiers.org/dbgap:phs001265.v1.p1. Data supporting figure 1: The datasets survivals DEB e OLAPARIB.pzfx and chromatidics breaks distribution.xlsx are in .pzfx (Graphpad) and .xlsx file formats respectively and consist of results of functional studies of the FANCM:p.Arg658*, p.Gln1701* and p.Arg1931* truncating variants using the patient derived FANCM−/− EGF280 cell line. These data include western blot analysis showing the expression of FANCM in EGF280 cells after lentiviral transduction with the three FANCM variants, expression of the FANCM protein in EGF280+p.Arg658* cells, data on diepoxybutane (DEB) sensitivity on cell survival, chromosome fragility data in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane and data of the analysis of cellular sensitivity to olaparib.Data supporting supplementary table 1: The SNP Genotypes from Illumina array and variables dataset consist of FANCM:p.Arg658*, p.Gln1701* and p.Arg1931 truncating variants in carriers of pathogenic BRCA1 or BRCA2 variants. A subset of these genotype data from the CIMBA studies can be accessed from dbGaP at https://identifiers.org/dbgap:phs001321.v1.p1.Data supporting supplementary table 2: Dataset survivals DEB e OLAPARIB.pzfx is in a. pzfx (Graphpad) file format and reports on the sensitivity of different EGF280 cell lines to diepoxybutane (DEB) treatment.Data supporting supplementary table 3: Dataset survivals DEB e OLAPARIB.pzfx is in a. pzfx (Graphpad) file format and reports on the sensitivity of different EGF280 cell lines to olaparib treatment.Supplementary tables 4 and 5 provide descriptions of the BCAC and CIMBA studies respectively, included in the present analysis. A subset of the genotype data generated in the BCAC studies can be accessed from dbGaP at https://identifiers.org/dbgap:phs001265.v1.p1. A subset of the genotype data generated in the CIMBA studies can be accessed from dbGaP at https://identifiers.org/dbgap:phs001321.v1.p1.</div

Risks of breast and ovarian cancer for women harboring pathogenic missense variants in BRCA1 and BRCA2 compared with those harboring protein truncating variants

Purpose Germline genetic testing for BRCA1 and BRCA2 variants has been a part of clinical practice for >2 decades. However, no studies have compared the cancer risks associated with missense pathogenic variants (PVs) with those associated with protein truncating (PTC) variants. Methods We collected 582 informative pedigrees segregating 1 of 28 missense PVs in BRCA1 and 153 pedigrees segregating 1 of 12 missense PVs in BRCA2. We analyzed 324 pedigrees with PTC variants in BRCA1 and 214 pedigrees with PTC variants in BRCA2. Cancer risks were estimated using modified segregation analysis. Results Estimated breast cancer risks were markedly lower for women aged >50 years carrying BRCA1 missense PVs than for the women carrying BRCA1 PTC variants (hazard ratio [HR] = 3.9 [2.4-6.2] for PVs vs 12.8 [5.7-28.7] for PTC variants; P = .01), particularly for missense PVs in the BRCA1 C-terminal domain (HR = 2.8 [1.4-5.6]; P = .005). In case of BRCA2, for women aged >50 years, the HR was 3.9 (2.0-7.2) for those heterozygous for missense PVs compared with 7.0 (3.3-14.7) for those harboring PTC variants. BRCA1 p.[Cys64Arg] and BRCA2 p.[Trp2626Cys] were associated with particularly low risks of breast cancer compared with other PVs. Conclusion These results have important implications for the counseling of at-risk women who harbor missense PVs in the BRCA1/2 genes

Ovarian cancer susceptibility alleles and risk of ovarian cancer in BRCA1 and BRCA2 mutation carriers

Germline mutations in BRCA1 and BRCA2 are associated with increased risks of breast and ovarian cancer. A genome-wide association study (GWAS) identified six alleles associated with risk of ovarian cancer for women in the general population. We evaluated four of these loci as potential modifiers of ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Four single-nucleotide polymorphisms (SNPs), rs10088218 (at 8q24), rs2665390 (at 3q25), rs717852 (at 2q31), and rs9303542 (at 17q21), were genotyped in 12,599 BRCA1 and 7,132 BRCA2 carriers, including 2,678 ovarian cancer cases. Associations were evaluated within a retrospective cohort approach. All four loci were associated with ovarian cancer risk in BRCA2 carriers; rs10088218 per-allele hazard ratio (HR) = 0.81 (95% CI: 0.67-0.98) P-trend = 0.033, rs2665390 HR = 1.48 (95% CI: 1.21-1.83) P-trend = 1.8 x 10(-4), rs717852 HR = 1.25 (95% CI: 1.10-1.42) P-trend = 6.6 x 10(-4), rs9303542 HR = 1.16 (95% CI: 1.02-1.33) P-trend = 0.026. Two loci were associated with ovarian cancer risk in BRCA1 carriers; rs10088218 per-allele HR = 0.89 (95% CI: 0.81-0.99) P-trend = 0.029, rs2665390 HR = 1.25 (95% CI: 1.10-1.42) P-trend = 6.1 x 10(-4). The HR estimates for the remaining loci were consistent with odds ratio estimates for the general population. The identification of multiple loci modifying ovarian cancer risk may be useful for counseling women with BRCA1 and BRCA2 mutations regarding their risk of ovarian cancer