García‐Closas, Montserrat

Abstract Background Most breast biopsies are diagnosed as benign breast disease, with 1.5- to 4-fold increased breast cancer risk. Apart from pathologic diagnoses of atypical hyperplasia, few factors aid in breast cancer risk assessment of these patients. We assessed whether a 313–single nucleotide variation (formerly single-nucleotide polymorphism) polygenic risk score stratifies risk of benign breast disease patients. Methods We pooled data from 5 Breast Cancer Association Consortium case-control studies (mean age = 59.9 years), including 6706 participants with breast cancer and 8488 participants without breast cancer. Using logistic regression, we estimated breast cancer risk associations by self-reported benign breast disease history and strata of polygenic risk score, with median polygenic risk score category among women without benign breast disease as the referent. We assessed interactions and mediation of benign breast disease and polygenic risk score with breast cancer risk. Results Benign breast disease history was associated with increased breast cancer risk (odds ratio [OR] = 1.48, 95% confidence interval [CI] = 1.37 to 1.60; P < .001). Polygenic risk score increased breast cancer risk, irrespective of benign breast disease history (Pinteraction = .48), with minimal evidence of mediation of either factor by the other. Women with benign breast disease and polygenic risk score in the highest tertile had more than twofold increased odds of breast cancer (OR = 2.73, 95% CI = 2.41 to 3.09), and those with benign breast disease and polygenic risk score in the lowest tertile experienced reduced breast cancer risk (OR = 0.79, 95% CI = 0.70 to 0.91) compared with the referent group. Women with benign breast disease and polygenic risk score in the highest decile had a 3.7-fold increase (95% CI = 3.00 to 4.61) compared with those with median polygenic risk score without benign breast disease. Conclusion Breast cancer risks are elevated among women with benign breast disease and increase progressively with polygenic risk score, suggesting that optimal combinations of these factors may improve risk stratification.

A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity—findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.

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.

Abstract Background Breast cancer (BC) patients with a germline CHEK2 c.1100delC variant have an increased risk of contralateral BC (CBC) and worse BC‐specific survival (BCSS) compared to non‐carriers. Aim To assessed the associations of CHEK2 c.1100delC, radiotherapy, and systemic treatment with CBC risk and BCSS. Methods Analyses were based on 82,701 women diagnosed with a first primary invasive BC including 963 CHEK2 c.1100delC carriers; median follow‐up was 9.1 years. Differential associations with treatment by CHEK2 c.1100delC status were tested by including interaction terms in a multivariable Cox regression model. A multi‐state model was used for further insight into the relation between CHEK2 c.1100delC status, treatment, CBC risk and death. Results There was no evidence for differential associations of therapy with CBC risk by CHEK2 c.1100delC status. The strongest association with reduced CBC risk was observed for the combination of chemotherapy and endocrine therapy [HR (95% CI): 0.66 (0.55–0.78)]. No association was observed with radiotherapy. Results from the multi‐state model showed shorter BCSS for CHEK2 c.1100delC carriers versus non‐carriers also after accounting for CBC occurrence [HR (95% CI): 1.30 (1.09–1.56)]. Conclusion Systemic therapy was associated with reduced CBC risk irrespective of CHEK2 c.1100delC status. Moreover, CHEK2 c.1100delC carriers had shorter BCSS, which appears not to be fully explained by their CBC risk.

Abstract Over one million biopsies are performed annually in the U.S. to evaluate suspicious breast lesions. Most biopsies lead to a diagnosis of benign breast disease (BBD) and these women have a 1.5- to fourfold increase in subsequent breast cancer (BC) risk compared with the general population. A polygenic risk score (PRS) including 313 common variants was developed to predict BC risk in the general population and has improved performance when added to existing BC prediction models. However, the value of PRS in risk prediction models among women with BBD has not been evaluated. To evaluate the role of the established PRS, BBD, and BC risk, we pooled data from 15,194 white women (6,706 BC cases and 8,488 controls) participating in five Breast Cancer Association Consortium case-control studies. BC risk associations were evaluated by self-reported BBD history and combinations of PRS expressed in tertiles using odds ratios (OR), considering the lowest category of PRS among women without BBD as the referent. Associations were also assessed in an independent case-cohort study (831 BC cases and 1,845 controls) using hazard ratios (HR). Among the case-control studies, the PRS was strongly associated with BC risk (OR=2.50 per standard deviation increase), and associations were similar in women with (OR=2.60) and without a history of BBD (OR=2.44, p-interaction=0.23). Women with BBD have a higher risk of BC than those without BBD within each level of PRS. Compared to women without BBD and in the lowest PRS category, those with BBD and PRS in the highest tertile had 5-fold increased odds of BC (OR = 5.38; 95% CI 4.73-6.13). Associations were similar in an independent case-cohort study. These findings indicate that BBD history and PRS are independent contributors to BC risk, and consideration of both simultaneously could improve breast cancer risk prediction. Future studies are needed to integrate PRS with other risk measures to refine absolute BC risk prediction among BBD patients. Associations of BC risk with combinations of PRS (tertiles) and history of BBD in five case-control studies and a case-cohort study from the Breast Cancer Association Consortium. Case-control studies Case-cohort study PRS score range History of BBD n BC cases n controls OR (95% CI)1 n BC cases n controls HR (95% CI)2 Tertile 1 (≤ -0.57) No 1009 2692 1.00 (Ref) 117 584 1.00 (Ref) Yes 508 902 1.54 (1.35-1.76) 69 163 2.05 (1.45-2.89) Tertile 2 (-0.58, -0.03) No 1469 2001 1.97 (1.78-2.17) 181 475 1.93 (1.48-2.51) Yes 760 798 2.65 (2.34-3.01) 108 170 2.99 (2.18-4.09) Tertile 3 (≥ -0.02) No 1910 1551 3.32 (3.01-3.67) 214 336 3.28 (2.52-4.26) Yes 1050 544 5.38 (4.73-6.13) 142 117 4.83 4.25-8.02) 1.Logistic regression analysis, adjusted for study site/genomic platform and age at enrollment. OR, odds ratio; CI, confidence interval.2.Cox proportional hazards regression analysis, accounting for the case-cohort study design and adjusted for age at enrollment. HR, hazard ratio; CI, confidence interval. Citation Format: Stacey J. Winham, Mark Sherman, Robert Vierkant, Bryan McCauley, Christopher Scott, Mia Gaudet, Melissa Troester, Sandhya Pruthi, Derek Radisky, Amy Degnim, Kristan Aronson, Rachel Murphy, Pascal Guenel, Therese Truong, Jenny Chang-Claude, Heiko Becher, Montserrat Garcia-Closas, Stephen Chanock, Thomas Ahearn, Xiaohong Yang, Doug Easton, Manjeet Bolla, Celine Vachon, Breast Cancer Association Consortium. Association of polygenic risk scores with breast cancer risk among women with benign breast disease. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5241.

Abstract Breast cancer (BC) patients with a germline CHEK2 c.1100delC variant have an increased risk of contralateral BC (CBC) and worse BC-specific survival (BCSS) compared to non-carriers. We aimed to assess the associations of CHEK2 c.1100delC, radiotherapy, and systemic treatment with CBC risk and BCSS. Analyses were based on 82,701 women diagnosed with invasive BC including 963 CHEK2 c.1100delC carriers; median follow-up was 9.1 years. Differential associations of treatment by CHEK2 c.1100delC status were tested by including interaction terms in a multivariable Cox regression model. A multi-state model was used for further insight into the relation between CHEK2 c.1100delC status, treatment, CBC risk and death. There was no evidence for differential associations of therapy with CBC risk by CHEK2 c.1100delC status The strongest association with reduced CBC risk was observed for the combination of chemotherapy and endocrine therapy [HR(95%CI): 0.66 (0.55–0.78)]. No association was observed with radiotherapy. Results from the multi-state model showed shorter BCSS for CHEK2 c.1100delC carriers versus non-carriers also after accounting for CBC occurrence [HR(95%CI) :1.30 (1.09–1.56)]. In conclusion, systemic therapy was associated with reduced CBC risk irrespective of CHEK2 c.1100delC status. Moreover, CHEK2 c.1100delC carriers had shorter BCSS, which appears not to be fully explained by their CBC risk. (Main MS: 3201 words)

AbstractBackgroundReproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear.MethodsAnalyses included up to 23 353 cases and 71 072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2–like, HER2-enriched–like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided.ResultsCompared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2–like, and HER2-enriched–like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like.ConclusionsThis large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction.

Abstract Introduction: Incorporation of mammographic density to breast cancer risk models could improve risk stratification to tailor screening and prevention strategies according to risk. However, robust validation of such models in prospective cohort studies is needed to determine their accuracy in identifying women at different risk levels. Methods: We incorporated Breast Imaging and Reporting Data System (BI-RADS) breast density to a literature-based model with questionnaire-based risk factors and a 313-variant polygenic risk score (PRS). The Individualized Coherent Absolute Risk Estimator (iCARE) tool was used to build and validate a 5-year absolute risk model for breast cancer. The model was evaluated for calibration and discrimination in three prospective cohorts of women of European ancestry (1,468 cases, 19,104 controls): US-based Nurses’ Health Study (NHS I and II) and Mayo Mammography Health Study (MMHS); and Sweden-based Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Analyses were done separately for women younger (NHS II, KARMA) and older than 50 years (NHS I, MMHS, KARMA). Improvements in risk stratification were assessed among US non-Hispanic White women aged 50-70 years. Results: For women younger than 50 years, the model with questionnaire-based risk factors, PRS and BI-RADS was well calibrated across risk deciles in NHS II, but overestimated risk at the highest risk decile in KARMA. For women 50 years or older, the model showed good calibration in all studies, with evidence of slight overestimation at the highest risk decile and underestimation at the lowest risk decile. The model with PRS and BI-RADS was well calibrated for women at high-risk in both age groups. Incorporation of BI-RADS to questionnaire-based risk factors and PRS improved risk discrimination: area under the curves (AUC) 67.0% (95% CI: 63.5-70.6%) vs. 65.6% (95% CI: 61.9-69.3%) for models with and without BI-RADS for younger women and 66.1% (95% CI 64.4-67.8%) vs. 65.5% (95% CI: 63.8-67.2%) for older women. The model with BI-RADS identified 18.4% population of non-Hispanic US women 50-70 years old above 3% 5-year risk (used for recommending risk-reducing medication in the US), with 42.4% of future cases expected to occur in this group. Addition of BI-RADS led to the reclassification of ~8.0% of US non-Hispanic White women aged 50-70 years at the high-risk threshold (3% 5-year risk), resulting in identification of 4.2% of additional future cases. Conclusion: Integrating BI-RADS with questionnaire-based risk factors and PRS resulted in improved risk stratification among women of European ancestry, with evidence of slight overestimation of risk for women at elevated risk. Additional validation of the integrated model in diverse populations is needed prior to considering clinical applications. Citation Format: Charlotta V. Mulder, Yon Ho Jee, Xin Yang, Christopher G. Scott, Chi Gao, Amber N. Hurson, Mikael Eriksson, Per Hall, Peter Kraft, Celine M. Vachon, Antonis C. Antoniou, Gretchen Gierach, Montserrat Garcia-Closas, Parichoy Pal Choudhury. Validation of an integrated breast cancer risk model with mammographic density in three prospective cohort studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2256.

Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P < 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk.

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values<5x10-8 as genome-wide significant, and p-values<1x10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values<1x105. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. Conclusions: In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.