Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel.

BACKGROUND: Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women. METHODS: We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel. RESULTS: In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28). CONCLUSIONS: Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.

Estimating the Cost of 3 Risk Prediction Strategies for Potential Use in the United Kingdom National Breast Screening Program.

Background: Economic evaluations have suggested that risk-stratified breast cancer screening may be cost-effective but have used assumptions to estimate the cost of risk prediction. The aim of this study was to identify and quantify the resource use and associated costs required to introduce a breast cancer risk-stratification approach into the English national breast screening program. Methods: A micro-costing study, conducted alongside a cohort-based prospective trial (BC-PREDICT), identified the resource use and cost per individual (£; 2021 price year) of providing a risk-stratification strategy at a woman's first mammography. Costs were calculated for 3 risk-stratification approaches: Tyrer-Cuzick survey, Tyrer-Cuzick with Volpara breast-density measurement, and Tyrer-Cuzick with Volpara breast-density measurement and testing for 142 single nucleotide polymorphisms (SNP). Costs were determined for the intervention as implemented in the trial and in the health service. Results: The cost of providing the risk-stratification strategy was calculated to be £16.45 for the Tyrer-Cuzick survey approach, £21.82 for the Tyrer-Cuzick with Volpara breast-density measurement, and £102.22 for the Tyrer-Cuzick with Volpara breast-density measurement and SNP testing. Limitations: This study did not use formal expert elicitation methods to synthesize estimates. Conclusion: The costs of risk prediction using a survey and breast density measurement were low, but adding SNP testing substantially increases costs. Implementation issues present in the trial may also significantly increase the cost of risk prediction. Implications: This is the first study to robustly estimate the cost of risk-stratification for breast cancer screening. The cost of risk prediction using questionnaires and automated breast density measurement was low, but full economic evaluations including accurate costs are required to provide evidence of the cost-effectiveness of risk-stratified breast cancer screening. Highlights: Economic evaluations have suggested that risk-stratified breast cancer screening may be a cost-effective use of resources in the United Kingdom.Current estimates of the cost of risk stratification are based on pragmatic assumptions.This study provides estimates of the cost of risk stratification using 3 strategies and when these strategies are implemented perfectly and imperfectly in the health system.The cost of risk stratification is relatively low unless single nucleotide polymorphisms are included in the strategy.

Validation of lung cancer polygenic risk scores in a high-risk case-control cohort.

PURPOSE: Screening with low-dose computed tomography reduces lung cancer (LC) mortality. Risk prediction models used for screening selection do not include genetic variables. Here, we investigated the performance of previously published polygenic risk scores (PRSs) for LC, considering their potential to improve screening selection. METHODS: We validated 9 PRSs in a high-risk case-control cohort, comprising genotype data from 652 surgical patients with LC and 550 cancer-free, high-risk (PLCOM2012 score ≥ 1.51%) participants of the Manchester Lung Health Check, a community-based LC screening program (n = 550). Discrimination (area under the curve [AUC]) between cases and controls was assessed for each PRS independently and alongside clinical risk factors. RESULTS: Median age was 67 years, 53% were female, 46% were current smokers, and 76% were National Lung Screening Trial eligible. Median PLCOM2012 score among controls was 3.4%, 80% of cases were early stage. All PRSs significantly improved discrimination, AUC increased between +0.002 (P = .02) and +0.015 (P < .0001), compared with clinical risk factors alone. The best-performing PRS had an independent AUC of 0.59. Two novel loci, in the DAPK1 and MAGI2 genes, were significantly associated with LC risk. CONCLUSION: PRSs may improve LC risk prediction and screening selection. Further research, particularly examining clinical utility and cost-effectiveness, is required.

Breast cancer polygenic risk scores derived in White European populations are not calibrated for women of Ashkenazi Jewish descent.

PURPOSE: Polygenic risk scores (PRSs) are a major component of accurate breast cancer (BC) risk prediction but require ethnicity-specific calibration. Ashkenazi Jewish (AJ) population is assumed to be of White European (WE) origin in some commercially available PRSs despite differing effect allele frequencies (EAFs). We conducted a case-control study of WE and AJ women from the Predicting Risk of Cancer at Screening Study. The Breast Cancer in Northern Israel Study provided a separate AJ population-based case-control validation series. METHODS: All women underwent Illumina OncoArray single-nucleotide variation (SNV; formerly single-nucleotide polymorphism [SNP]) analysis. Two PRSs were assessed, SNV142 and SNV78. A total of 221 of 2243 WE women (discovery: cases = 111; controls = 110; validation: cases = 651; controls = 1772) and 221 AJ women (cases = 121; controls = 110) were included from the UK study; the Israeli series consisted of 2045 AJ women (cases = 1331; controls = 714). EAFs were obtained from the Genome Aggregation Database. RESULTS: In the UK study, the mean SNV142 PRS demonstrated good calibration and discrimination in WE population, with mean PRS of 1.33 (95% CI 1.18-1.48) in cases and 1.01 (95% CI 0.89-1.13) in controls. In AJ women from Manchester, the mean PRS of 1.54 (1.38-1.70) in cases and 1.20 (1.08-1.32) in controls demonstrated good discrimination but overestimation of BC relative risk. After adjusting for EAFs for the AJ population, mean risk was corrected (mean SNV142 PRS cases = 1.30 [95% CI 1.16-1.44] and controls = 1.02 [95% CI 0.92-1.12]). This was recapitulated in the larger Israeli data set with good discrimination (area under the curve = 0.632 [95% CI 0.607-0.657] for SNV142). CONCLUSION: AJ women should not be given BC relative risk predictions based on PRSs calibrated to EAFs from the WE population. PRSs need to be recalibrated using AJ-derived EAFs. A simple recalibration using the mean PRS adjustment ratio likely performs well.

Differential involvement of germline pathogenic variants in breast cancer genes between DCIS and low-grade invasive cancers.

PURPOSE: To investigate frequency of germline pathogenic variants (PVs) in women with ductal carcinoma in situ (DCIS) and grade 1 invasive breast cancer (G1BC). METHODS: We undertook BRCA1/2 analysis in 311 women with DCIS and 392 with G1BC and extended panel testing (non-BRCA1/2) in 176/311 with DCIS and 156/392 with G1BC. We investigated PV detection by age at diagnosis, Manchester Score (MS), DCIS grade and receptor status. RESULTS: 30/311 (9.6%) with DCIS and 16/392 with G1BC (4.1%) had a BRCA1/2 PV (p=0.003), and 24/176-(13.6%) and 7/156-(4.5%), respectively, a non-BRCA1/2 PV (p=0.004). Increasing MS was associated with increased likelihood of BRCA1/2 PV in both DCIS and G1BC, although the 10% threshold was not predictive for G1GB. 13/32 (40.6%) DCIS and 0/17 with G1BC <40 years had a non-BRCA1/2 PV (p<0.001). 0/16 DCIS G1 had a PV. For G2 and G3 DCIS, PV rates were 10/98 (BRCA1/2) and 9/90 (non-BRCA1/2), and 8/47 (BRCA1/2) and 8/45 (non-BRCA1/2), respectively. 6/9 BRCA1 and 3/26 BRCA2-associated DCIS were oestrogen receptor negative-(p=0.003). G1BC population testing showed no increased PV rate (OR=1.16, 95% CI 0.28 to 4.80). CONCLUSION: DCIS is more likely to be associated with both BRCA1/2 and non-BRCA1/2 PVs than G1BC. Extended panel testing ought to be offered in young-onset DCIS where PV detection rates are highest.

Breast cancer risk stratification in women of screening age: Incremental effects of adding mammographic density, polygenic risk, and a gene panel.

PURPOSE: There is great promise in breast cancer risk stratification to target screening and prevention. It is unclear whether adding gene panels to other risk tools improves breast cancer risk stratification and adds discriminatory benefit on a population basis. METHODS: In total, 10,025 of 57,902 women aged 46 to 73 years in the Predicting Risk of Cancer at Screening study provided DNA samples. A case-control study was used to evaluate breast cancer risk assessment using polygenic risk scores (PRSs), cancer gene panel (n = 33), mammographic density (density residual [DR]), and risk factors collected using a self-completed 2-page questionnaire (Tyrer-Cuzick [TC] model version 8). In total, 525 cases and 1410 controls underwent gene panel testing and PRS calculation (18, 143, and/or 313 single-nucleotide polymorphisms [SNPs]). RESULTS: Actionable pathogenic variants (PGVs) in BRCA1/2 were found in 1.7% of cases and 0.55% of controls, and overall PGVs were found in 6.1% of cases and 1.3% of controls. A combined assessment of TC8-DR-SNP313 and gene panel provided the best risk stratification with 26.1% of controls and 9.7% of cases identified at <1.4% 10-year risk and 9.01% of controls and 23.3% of cases at ≥8% 10-year risk. Because actionable PGVs were uncommon, discrimination was identical with/without gene panel (with/without: area under the curve = 0.67, 95% CI = 0.64-0.70). Only 7 of 17 PGVs in cases resulted in actionable risk category change. Extended case (n = 644)-control (n = 1779) series with TC8-DR-SNP143 identified 18.9% of controls and only 6.4% of stage 2+ cases at <1.4% 10-year risk and 20.7% of controls and 47.9% of stage 2+ cases at ≥5% 10-year risk. CONCLUSION: Further studies and economic analysis will determine whether adding panels to PRS is a cost-effective strategy for risk stratification.

The importance of ethnicity: Are breast cancer polygenic risk scores ready for women who are not of White European origin?

Polygenic risk scores (PRS) for disease risk stratification show great promise for application in general populations, but most are based on data from individuals of White European origin. We assessed two well validated PRS (SNP18, SNP143) in the Predicting-Risk-of-Cancer-At-Screening (PROCAS) study in North-West England for breast cancer prediction based on ethnicity. Overall, 9475 women without breast cancer at study entry, including 645 who subsequently developed invasive breast cancer or ductal carcinoma in situ provided DNA. All were genotyped for SNP18 and a subset of 1868 controls were genotyped for SNP143. For White Europeans both PRS discriminated well between individuals with and without cancer. For n = 395 Black (n = 112), Asian (n = 119), mixed (n = 44) or Jewish (n = 120) women without cancer both PRS overestimated breast cancer risk, being most marked for women of Black and Jewish origin (P < .001). SNP143 resulted in a potential mean 40% breast cancer risk overestimation in the combined group of non-White/non-European origin. SNP-PRS that has been normalized based on White European ethnicity for breast cancer should not be used to predict risk in women of other ethnicities. There is an urgent need to develop PRS specific for other ethnicities, in order to widen access of this technology.

High likelihood of actionable pathogenic variant detection in breast cancer genes in women with very early onset breast cancer.

BACKGROUND: While the likelihood of identifying constitutional breast cancer-associated BRCA1, BRCA2 and TP53 pathogenic variants (PVs) increases with earlier diagnosis age, little is known about the correlation with age at diagnosis in other predisposition genes. Here, we assessed the contribution of known breast cancer-associated genes to very early onset disease. METHODS: Sequencing of BRCA1, BRCA2, TP53 and CHEK2 c.1100delC was undertaken in women with breast cancer diagnosed ≤30 years. Those testing negative were screened for PVs in a minimum of eight additional breast cancer-associated genes. Rates of PVs were compared with cases ≤30 years from the Prospective study of Outcomes in Sporadic vs Hereditary breast cancer (POSH) study. RESULTS: Testing 379 women with breast cancer aged ≤30 years identified 75 PVs (19.7%) in BRCA1, 35 (9.2%) in BRCA2, 22 (5.8%) in TP53 and 2 (0.5%) CHEK2 c.1100delC. Extended screening of 184 PV negative women only identified eight additional actionable PVs. BRCA1/2 PVs were more common in women aged 26-30 years than in younger women (p=0.0083) although the younger age group had rates more similar to those in the POSH cohort. Out of 26 women with ductal carcinoma in situ (DCIS) alone, most were high-grade and 11/26 (42.3%) had a PV (TP53=6, BRCA2=2, BRCA1=2, PALB2=1). This PV yield is similar to the 61 (48.8%) BRCA1/2 PVs identified in 125 women with triple-negative breast cancer. The POSH cohort specifically excluded pure DCIS which may explain lower TP53 PV rates in this group (1.7%). CONCLUSION: The rates of BRCA1, BRCA2 and TP53 PVs are high in very early onset breast cancer, with limited benefit from testing of additional breast cancer-associated genes.

Extended gene panel testing in lobular breast cancer.

PURPOSE: Lobular breast cancer (LBC) accounts for ~ 15% of breast cancer. Here, we studied the frequency of pathogenic germline variants (PGVs) in an extended panel of genes in women affected with LBC. METHODS: 302 women with LBC and 1567 without breast cancer were tested for BRCA1/2 PGVs. A subset of 134 LBC affected women who tested negative for BRCA1/2 PGVs underwent extended screening, including: ATM, CDH1, CHEK2, NBN, PALB2, PTEN, RAD50, RAD51D, and TP53. RESULTS: 35 PGVs were identified in the group with LBC, of which 22 were in BRCA1/2. Ten actionable PGVs were identified in additional genes (ATM(4), CDH1(1), CHEK2(1), PALB2(2) and TP53(2)). Overall, PGVs in three genes conferred a significant increased risk for LBC. Odds ratios (ORs) were: BRCA1: OR = 13.17 (95%CI 2.83-66.38; P = 0.0017), BRCA2: OR = 10.33 (95%CI 4.58-23.95; P < 0.0001); and ATM: OR = 8.01 (95%CI 2.52-29.92; P = 0.0053). We did not detect an increased risk of LBC for PALB2, CDH1 or CHEK2. CONCLUSION: The overall PGV detection rate was 11.59%, with similar rates of BRCA1/2 (7.28%) PGVs as for other actionable PGVs (7.46%), indicating a benefit for extended panel genetic testing in LBC. We also report a previously unrecognised association of pathogenic variants in ATM with LBC.

Clinical utility of testing for PALB2 and CHEK2 c.1100delC in breast and ovarian cancer.

PURPOSE: To investigate the contribution of PALB2 pathogenic gene variants (PGVs, PALB2_PGV) and the CHEK2 c.1100delC (CHEK2_1100delC) PGV to familial breast and ovarian cancer, and PALB2_PGV associated breast cancer pathology. METHODS: Outcomes of germline PALB2_PGV and CHEK2_1100delC testing were recorded in 3,127 women with histologically confirmed diagnoses of invasive breast cancer, carcinoma in situ, or epithelial nonmucinous ovarian cancer, and 1,567 female controls. Breast cancer pathology was recorded in PALB2_PGV cases from extended families. RESULTS: Thirty-five PALB2 and 44 CHEK2_1100delC PGVs were detected in patients (odds ratio [OR] PALB2 breast-ovarian = 5.90 [95% CI: 1.92-18.36], CHEK2 breast-ovarian = 4.46 [95% CI: 1.86-10.46], PALB2 breast = 6.16 [95% CI: 1.98-19.21], CHEK2 breast = 4.89 [95% CI: 2.01-11.34]). Grade 3 ER-positive HER2-negative, grade 3 and triple negative (TN) tumors were enriched in cases with PALB2 PGVs compared with all breast cancers known to our service (respectively: 15/43, 254/1,843, P = 0.0005; 28/37, 562/1,381, P = 0.0001; 12/43, 204/1,639, P < 0.0001). PALB2_PGV likelihood increased with increasing Manchester score (MS) (MS < 15 = 17/1,763, MS 20-39 = 11/520, P = 0.04) but not for CHEK2_1100delC (MS < 15 = 29/1,762, MS 20-39 = 4/520). PALB2 PGVs showed perfect segregation in 20/20 first-degree relatives with breast cancer, compared with 7/13 for CHEK2_1100delC (P = 0.002). CONCLUSION: PALB2 PGVs and CHEK2_1100delC together account for ~2.5% of familial breast/ovarian cancer risk. PALB2 PGVs are associated with grade 3, TN, and grade 3 ER-positive HER2-negative breast tumors.

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study 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, progesterone receptor and human epidermal growth factor receptor 2 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 < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that 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 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

A case-control evaluation of 143 single nucleotide polymorphisms for breast cancer risk stratification with classical factors and mammographic density.

Panels of single nucleotide polymorphisms (SNPs) stratify risk for breast cancer in women from the general population, but studies are needed assess their use in a fully comprehensive model including classical risk factors, mammographic density and more than 100 SNPs associated with breast cancer. A case-control study was designed (1,668 controls, 405 cases) in women aged 47-73 years attending routine screening in Manchester UK, and enrolled in a wider study to assess methods for risk assessment. Risk from classical questionnaire risk factors was assessed using the Tyrer-Cuzick model; mean percentage visual mammographic density was scored by two independent readers. DNA extracted from saliva was genotyped at selected SNPs using the OncoArray. A predefined polygenic risk score based on 143 SNPs was calculated (SNP143). The odds ratio (OR, and 95% confidence interval, CI) per interquartile range (IQ-OR) of SNP143 was estimated unadjusted and adjusted for Tyrer-Cuzick and breast density. Secondary analysis assessed risk by oestrogen receptor (ER) status. The primary polygenic risk score was well calibrated (O/E OR 1.10, 95% CI 0.86-1.34) and accuracy was retained after adjustment for Tyrer-Cuzick risk and mammographic density (IQ-OR unadjusted 2.12, 95% CI% 1.75-2.42; adjusted 2.06, 95% CI 1.75-2.42). SNP143 was a risk factor for ER+ and ER- breast cancer (adjusted IQ-OR, ER+ 2.11, 95% CI 1.78-2.51; ER- 1.81, 95% CI 1.16-2.84). In conclusion, polygenic risk scores based on a large number of SNPs improve risk stratification in combination with classical risk factors and mammographic density, and SNP143 was similarly predictive for ER-positive and ER-negative disease.

Breast cancer pathology and stage are better predicted by risk stratification models that include mammographic density and common genetic variants.

PURPOSE: To improve breast cancer risk stratification to enable more targeted early detection/prevention strategies that will better balance risks and benefits of population screening programmes. METHODS: 9362 of 57,902 women in the Predicting-Risk-Of-Cancer-At-Screening (PROCAS) study who were unaffected by breast cancer at study entry and provided DNA for a polygenic risk score (PRS). The PRS was analysed alongside mammographic density (density-residual-DR) and standard risk factors (Tyrer-Cuzick-model) to assess future risk of breast cancer based on tumour stage receptor expression and pathology. RESULTS: 195 prospective incident breast cancers had a prediction based on TC/DR/PRS which was informative for subsequent breast cancer overall [IQ-OR 2.25 (95% CI 1.89-2.68)] with excellent calibration-(0.99). The model performed particularly well in predicting higher stage stage 2+ IQ-OR 2.69 (95% CI 2.02-3.60) and ER + BCs (IQ-OR 2.36 (95% CI 1.93-2.89)). DR was most predictive for HER2+ and stage 2+ cancers but did not discriminate as well between poor and extremely good prognosis BC as either Tyrer-Cuzick or PRS. In contrast, PRS gave the highest OR for incident stage 2+ cancers, [IQR-OR 1.79 (95% CI 1.30-2.46)]. CONCLUSIONS: A combined approach using Tyrer-Cuzick/DR/PRS provides accurate risk stratification, particularly for poor prognosis cancers. This provides support for reducing the screening interval in high-risk women and increasing the screening interval in low-risk women defined by this model.

A Dominantly Inherited 5' UTR Variant Causing Methylation-Associated Silencing of BRCA1 as a Cause of Breast and Ovarian Cancer.

Pathogenic variants in BRCA1 or BRCA2 are identified in ∼20% of families with multiple individuals affected by early-onset breast and/or ovarian cancer. Extensive searches for additional highly penetrant genes or alternative mutational mechanisms altering BRCA1 or BRCA2 have not explained the missing heritability. Here, we report a dominantly inherited 5' UTR variant associated with epigenetic BRCA1 silencing due to promoter hypermethylation in two families affected by breast and ovarian cancer. BRCA1 promoter methylation of ten CpG dinucleotides in families who are affected by breast and/or ovarian cancer but do not have germline BRCA1 or BRCA2 pathogenic variants was assessed by pyrosequencing and clonal bisulfite sequencing. RNA and DNA sequencing of BRCA1 from lymphocytes was undertaken to establish allelic expression and the presence of germline variants. BRCA1 promoter hypermethylation was identified in 2 of 49 families in which multiple women are affected by grade 3 breast cancer or high-grade serous ovarian cancer. Soma-wide BRCA1 promoter hypermethylation was confirmed in blood, buccal mucosa, and hair follicles. Pyrosequencing showed that DNA was ∼50% methylated, consistent with the silencing of one allele, which was confirmed by clonal bisulfite sequencing. RNA sequencing revealed the allelic loss of BRCA1 expression in both families and that this loss of expression segregated with the heterozygous variant c.-107A>T in the BRCA1 5' UTR. Our results establish a mechanism whereby familial breast and ovarian cancer is caused by an in cis 5' UTR variant associated with epigenetic silencing of the BRCA1 promoter in two independent families. We propose that methylation analyses be undertaken to establish the frequency of this mechanism in families affected by early-onset breast and/or ovarian cancer without a BRCA1 or BRCA2 pathogenic variant.

Use of Single-Nucleotide Polymorphisms and Mammographic Density Plus Classic Risk Factors for Breast Cancer Risk Prediction.

IMPORTANCE: Single-nucleotide polymorphisms (SNPs) have demonstrated an association with breast cancer susceptibility, but there is limited evidence on how to incorporate them into current breast cancer risk prediction models. OBJECTIVE: To determine whether a panel of 18 SNPs (SNP18) may be used to predict breast cancer in combination with classic risk factors and mammographic density. DESIGN, SETTING, AND PARTICIPANTS: This cohort study enrolled a subcohort of 9363 women, aged 46 to 73 years, without a previous breast cancer diagnosis from the larger prospective cohort of the PROCAS study (Predicting Risk of Cancer at Screening) specifically to evaluate breast cancer risk-assessment methods. Enrollment took place from October 2009 through June 2015 from multiple population-based screening centers in Greater Manchester, England. Follow-up continued through January 5, 2017. EXPOSURES: Genotyping of 18 SNPs, visual-assessment percentage mammographic density, and classic risk assessed by the Tyrer-Cuzick risk model from a self-completed questionnaire at cohort entry. MAIN OUTCOMES AND MEASURES: The predictive ability of SNP18 for breast cancer diagnosis (invasive and ductal carcinoma in situ) was assessed using logistic regression odds ratios per interquartile range of the predicted risk. RESULTS: A total of 9363 women were enrolled in this study (mean [range] age, 59 [46-73] years). Of these, 466 were found to have breast cancer (271 prevalent; 195 incident). SNP18 was similarly predictive when unadjusted or adjusted for mammographic density and classic factors (odds ratios per interquartile range, respectively, 1.56; 95% CI, 1.38-1.77 and 1.53; 95% CI, 1.35-1.74), with observed risks being very close to expected (adjusted observed-to-expected odds ratio, 0.98; 95% CI, 0.69-1.28). A combined risk assessment indicated 18% of the subcohort to be at 5% or greater 10-year risk, compared with 30% of all cancers, 35% of interval-detected cancers, and 42% of stage 2+ cancers. In contrast, 33% of the subcohort were at less than 2% risk but accounted for only 18%, 17%, and 15% of the total, interval, and stage 2+ breast cancers, respectively. CONCLUSIONS AND RELEVANCE: SNP18 added substantial information to risk assessment based on the Tyrer-Cuzick model and mammographic density. A combined risk is likely to aid risk-stratified screening and prevention strategies.

The impact of a panel of 18 SNPs on breast cancer risk in women attending a UK familial screening clinic: a case-control study.

BACKGROUND: Breast cancer familial risk clinics offer screening and preventive strategies. While BRCA1/BRCA2 genetic testing provides important risk information for some women, panels of more common breast cancer risk genetic variants may have relevance to greater numbers of women with familial risk. METHODS: Three polygenic risk scores (PRS) based on 18 SNPs were investigated in a case-control study of women attending a familial risk clinic. PRS were derived from published general European population allele ORs and frequencies (18-SNPs (SNP18)). In women with BRCA1/BRCA2 mutations, 3 SNPs/13 SNPs, respectively, generated the PRS estimates. In total, 364 incident breast cancer cases (112 with BRCA1/2 mutations) were matched with 1605 controls (691 BRCA1/2) by age last mammogram and BRCA1/2 genetic test result. 87 women with cancer before attendance were also considered. Logistic regression was used to measure PRS performance through ORs per IQR and calibration of the observed to expected (O/E) logarithm relative risk when unadjusted and adjusted for phenotypic risk factors assessed by the Tyrer-Cuzick (TC) model. RESULTS: SNP18 was predictive for non-carriers of BRCA1/2 mutations (IQR OR 1.55, 95% CI 1.29 to 1.87, O/E 96%). Findings were unaffected by adjustment from TC (IQR OR 1.56, 95% CI 1.29 to 1.89) or when prior cancers were included (IQR OR 1.55, 95% CI 1.30 to 1.87). There was some evidence to support polygenic scores with weights for individuals with BRCA1/2 mutations (BRCA1 IQR OR 1.44, 95% CI 1.17 to 1.76; BRCA2 IQ OR 1.44, 95% CI 0.90 to 2.31). CONCLUSIONS: PRS may be used to refine risk assessment for women at increased familial risk who test negative/have low likelihood of BRCA1/2 mutations. They may alter the recommended prevention strategy for many women attending family history clinics.

Impact of a Panel of 88 Single Nucleotide Polymorphisms on the Risk of Breast Cancer in High-Risk Women: Results From Two Randomized Tamoxifen Prevention Trials.

Purpose At least 94 common single nucleotide polymorphisms (SNPs) are associated with breast cancer. The extent to which an SNP panel can refine risk in women who receive preventive therapy has not been directly assessed previously. Materials and Methods A risk score on the basis of 88 SNPs (SNP88) was investigated in a nested case-control study of women enrolled in the International Breast Intervention Study (IBIS-I) or the Royal Marsden study. A total of 359 women who developed cancer were matched to 636 controls by age, trial, follow-up time, and treatment arm. Genotyping was done using the OncoArray. Conditional logistic regression and matched concordance indices (mC) were used to measure the performance of SNP88 alone and with other breast cancer risk factors assessed using the Tyrer-Cuzick (TC) model. Results SNP88 was predictive of breast cancer risk overall (interquartile range odds ratio [IQ-OR], 1.37; 95% CI, 1.14 to 1.66; mC, 0.55), but mainly for estrogen receptor-positive disease (IQ-OR, 1.44; 95% CI, 1.16 to 1.79; P for heterogeneity = .10) versus estrogen receptor-negative disease. However, the observed risk of SNP88 was only 46% (95% CI, 19% to 74%) of expected. No significant interaction was observed with treatment arm (placebo IQ-OR, 1.46; 95% CI, 1.13 to 1.87; tamoxifen IQ-OR, 1.25; 95% CI, 0.96 to 1.64; P for heterogeneity = .5). The predictive power was similar to the TC model (IQ-OR, 1.45; 95% CI, 1.21 to 1.73; mC, 0.55), but SNP88 was independent of TC (Spearman rank-order correlation, 0.012; P = .7), and when combined multiplicatively, a substantial improvement was seen (IQ-OR, 1.64; 95% CI, 1.36 to 1.97; mC, 0.60). Conclusion A polygenic risk score may be used to refine risk from the TC or similar models in women who are at an elevated risk of breast cancer and considering preventive therapy. Recalibration may be necessary for accurate risk assessment.

Relationship of ZNF423 and CTSO with breast cancer risk in two randomised tamoxifen prevention trials.

A case-control study from two randomised breast cancer prevention trials of tamoxifen and raloxifene (P-1 and P-2) identified single-nucleotide polymorphisms (SNPs) in or near genes ZNF423 and CTSO as factors which predict which women will derive most anti-cancer benefit from selective oestrogen receptor modulator (SERM) therapy. In this article, we further examine this question using blood samples from two randomised tamoxifen prevention trials: the International Breast Cancer Intervention Study I (IBIS-I) and the Royal Marsden trial (Marsden). A nested case-control study was designed with 2:1 matching in IBIS-I and 1:1 matching in Marsden. The OncoArray was used for genotyping and included two SNPs previously identified (rs8060157 in ZNF423 and rs10030044 near CTSO), and 102 further SNPs within the same regions. Overall, there were 369 cases and 662 controls, with 148 cases and 268 controls from the tamoxifen arms. Odds ratios were estimated by conditional logistic regression, with Wald 95 % confidence intervals. In the tamoxifen arms, the per-allele odds ratio for rs8060157 was 0.99 (95 %CI 0.73-1.34) and 1.00 (95 %CI 0.76-1.33) for rs10030044. In the placebo arm, the odds ratio was 1.10 (95 %CI 0.87-1.40) for rs8060157 and 1.01 (95 %CI 0.79-1.29) for rs10030044. There was no evidence to suggest that other SNPs in the surrounding regions of these SNPs might predict response to tamoxifen. Results from these two prevention trials do not support the earlier findings. rs8060157 in ZNF423 and rs10030044 near CTSO do not appear to predict response to tamoxifen.

Association of a promoter polymorphism in FSHR with ovarian reserve and response to ovarian stimulation in women undergoing assisted reproductive treatment.

Previous studies have suggested an association between a variant in the promoter region of the FSHR gene and diminished response to controlled ovarian hyperstimulation (COH) in women undergoing assisted reproduction. FSHR -29G>A was genotyped in 559 women undergoing their first cycle of COH for IVF/intracytoplasmic sperm injection (ICSI) using TaqMan allelic discrimination assay. Correlation and regression analysis was performed to assess the relationship between FSHR promoter genotypes and markers of ovarian reserve and measures of response to COH, including the number of oocytes retrieved, gonadotrophin dose used and the live-birth rate. There were no statistically significant differences between the genotype frequencies and the markers of ovarian reserve or the early measures of response to COH. However, the live-birth rate was higher for women carrying the variant A allele (odds ratio [OR] 1.37; 95% confidence interval [CI] 1.02-1.84 per allele). This relationship did not reach statistical significance after adjustment for the number of embryos transferred (OR 1.33; 95% CI 0.98-1.83 per allele). Results from this study do not provide evidence that the FSHR -29G>A variant can be used in the individualization of the treatment protocol for women undergoing IVF/ICSI.