Haiman, Christopher A.

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 Introduction: The risk of specific clinical subtype of breast cancer (defined by ER and HER2 status) among women in the general population who are carriers of germline pathogenic variants (PVs) in cancer predisposition genes is not well-defined. Methods: A total of 13,153 women with breast cancer (ER+/HER2-: 9381; ER+/HER2+: 1462; ER-/HER2+: 690; and ER-/HER2-: 1620) and 25,005 unaffected women (controls) from nine studies within the CAnceR RIsk Estimates Related to Susceptibility (CARRIERS) consortium that were not enriched for family history or early onset disease were included in the present analysis. A multiplex amplicon-based panel was used to perform germline sequencing for cancer predisposition genes. Case-control associations for each of the four clinical subtype of breast cancer was performed for PVs in 5 common breast cancer predisposition genes (ATM, BRCA1, BRCA2, CHEK2 and PALB2) utilizing a logistic regression model adjusting for study, age at diagnosis, race/ethnicity and family history of breast cancer. Results: The frequency of PVs in 5 genes was 3.8% for ER+/HER2-, 6.2% for ER+/HER2+, 4.2% for ER-/HER2+ and 9.3% for ER-/HER2- subtypes. PVs in BRCA1 and BRCA2 were associated with high risk (Odds Ratio (OR) >4) for all clinical subtypes of breast cancer, but the risk was highest (OR>8) for ER-/HER2- breast cancer. PVs in PALB2 were associated with high risk (OR>4) of ER-/HER2- and ER+/HER2+ subtypes and moderate risk (OR: 2-4) of ER+/HER2- breast cancer. Irrespective of the HER2 status, PVs in ATM were associated with a moderately increased risk (OR: 2-4) of ER+ breast cancer but the risk of ER- breast cancer was not elevated. In contrast, PVs in CHEK2 were associated with high risk (OR>4) of ER+/HER2+ breast cancer and moderate risk (OR: 2-4) of ER+/HER2- and ER-/HER2+ breast cancer, but the risk of ER-/HER2- breast cancer was not elevated. Conclusions: This study provides population-based estimates of risk of specific clinical subtypes of breast cancer which will be useful for genetic counseling and targeting appropriate screening strategies in PV carriers based on subtype specific risks of breast cancer. Citation Format: Siddhartha Yadav, Chunling Hu, Nicholas J. Boddicker, Eric Polley, Steven Hart, Rohan Gnanaolivu, Jie Na, Hongyan Huang, Song Yao, Celine M. Vachon, Lauren Teras, Jack A. Taylor, Dale P. Sandler, Julie R. Palmer, Janet E. Olson, Susan Neuhausen, Elena Martinez, Sara Lindstroem, Loic Le Marchand, Charles Kooperberg, Christopher Haiman, Mia M. Gaudet, James V. Lacey, Kimberly A. Bertrand, Leslie Bernstein, Paul W. Auer, Christine Ambrosone, Jeffrey N. Weitzel, Peter Kraft, David E. Goldgar, Katherine L. Nathanson, Susan M. Domchek, Fergus J. Couch, CARRIERS Consortium. Population-based risk estimates of clinical subtypes of breast cancer among carriers of germline pathogenic variants in cancer predisposition genes [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-09-01.

Abstract Introduction: Prostate Cancer (PCa) risk is influenced by both rare germline pathogenic variants (GPVs) in DNA damage repair genes and common variants as measured by polygenic risk scores (PRS) however, the combined effect of GPVs and PRS on PCa risk in men of African ancestry has not been investigated. Methods: We examined the combined effect of rare GPVs and PRS on PCa risk in 1,795 PCa cases and 1,424 controls of African ancestry men from the Multiethnic Cohort, the Los Angeles Study of Aggressive Prostate Cancer, and the Uganda Prostate Cancer Study. GPVs in 19 DNA genes were defined as clinically validated missense variants and variants that alter the protein sequence. The PRS was constructed as a weighted sum of 267 established PCa risk variants. The combined effect of the PRS and GPV status on PCa risk was evaluated using logistic regression models adjusting for age, study, and the first 10 principal components of ancestry to account for population stratification. Results: We identified 91 GPVs carried by 31 controls and 68 cases. Among GPV non-carriers, compared to those with average PRS (33.3-66.7%), odds ratios for PCa ranged from 0.56 (95% CI=0.45-0.70; P=1.2E-7) in low PRS men (0-33.3%) to 3.04 (95% CI=2.54-3.63; P=5.6E-35) in high PRS men (66.7-100%). Among GPV carriers, odds ratios for PCa ranged from 2.09 (95% CI=0.85-5.12; P=0.11) in low PRS men to 5.03 (95% CI=2.37-10.66; P=2.5E-5) in high PRS men, compared to GPV non-carriers with average PRS. Next, we restricted GPVs to ATM, BRCA2, PALB2, and NBN[BD2] (n=51 variants carried by 8 controls and 44 cases), which we previously reported as being the genes most strongly associated with advanced PCa in this population and study sample. Among GPV non-carriers, odds ratios for PCa ranged from 0.56 (95% CI=0.46-0.71; P=2.7E-7) in low PRS men to 5.03 (95% CI=0.85-5.12; P=0.11) in high PRS men, while among GPV carriers, odd ratios for PCa ranged from 2.08 (95% CI=0.58-7.49; P=0.26) in low PRS men to 18.06 (95% CI=4.24-76.84; P=9.0E-5) in high PRS men, compared to average PRS GPV non-carriers. When comparing aggressive cases to controls, considering the top four genes, GPV non-carrier odds ratios for PCa ranged from 0.52 (95% CI=0.40-0.70; P=6.2E-6) in low PRS men to 3.16 (95% CI=2.56-3.91; P=1.6E-26) in high PRS men, while among GPV carriers, odd ratios for PCa ranged from 2.97 (95% CI=073-12.16; P=0.13) in low PRS men to 23.58 (95% CI=5.39-103.20; P=2.7E-5) in high PRS men, compared to average PRS GPV non-carriers. Conclusion: We found that PCa risk in African ancestry men carrying GPVs in DNA damage repair and cancer predisposition genes, particularly ATM, BRCA2, PALB2, and NBN, varied depending on an individual's PRS. This implies that to comprehensively assess genetic risk of PCa, it is important to consider both rare and common variants. These findings could have implications for risk stratification in this high-risk population and emphasize the need for larger genetic studies of PCa in African ancestry men to identify and characterize genetic risk factors in this population. Citation Format: Raymond W. Hughley, Burcu F. Darst, Marco Matejcic, Yesha Patel, Jenna Lilyquist, Steven N. Hart, Eric C. Polley, Lucy Xia, Xin Sheng, Alexander Lubmawa, Sue A. Ingles, Lynne Wilkens, Loïc L. Marchand, Stephen Watya, Fergus J. Couch, David V. Conti, Christopher A. Haiman. Combined effect of a prostate cancer polygenic risk score and germline pathogenic variants in DNA damage repair genes on prostate cancer risk in men of African ancestry [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-197.

PURPOSE The prevalence of germline pathogenic variants (PVs) in established breast cancer predisposition genes in women in the general population over age 65 years is not well-defined. However, testing guidelines suggest that women diagnosed with breast cancer over age 65 years might have < 2.5% likelihood of a PV in a high-penetrance gene. This study aimed to establish the frequency of PVs and remaining risks of breast cancer for each gene in women over age 65 years. METHODS A total of 26,707 women over age 65 years from population-based studies (51.5% with breast cancer and 48.5% unaffected) were tested for PVs in germline predisposition gene. Frequencies of PVs and associations between PVs in each gene and breast cancer were assessed, and remaining lifetime breast cancer risks were estimated for non-Hispanic White women with PVs. RESULTS The frequency of PVs in predisposition genes was 3.18% for women with breast cancer and 1.48% for unaffected women over age 65 years. PVs in BRCA1, BRCA2, and PALB2 were found in 3.42% of women diagnosed with estrogen receptor (ER)–negative, 1.0% with ER-positive, and 3.01% with triple-negative breast cancer. Frequencies of PVs were lower among women with no first-degree relatives with breast cancer. PVs in CHEK2, PALB2, BRCA2, and BRCA1 were associated with increased risks (odds ratio = 2.9-4.0) of breast cancer. Remaining lifetime risks of breast cancer were ≥ 15% for those with PVs in BRCA1, BRCA2, and PALB2. CONCLUSION This study suggests that all women diagnosed with triple-negative breast cancer or ER-negative breast cancer should receive genetic testing and that women over age 65 years with BRCA1 and BRCA2 PVs and perhaps with PALB2 and CHEK2 PVs should be considered for magnetic resonance imaging screening.

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.

Abstract BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data.ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci.ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

PURPOSE This study assessed the joint association of pathogenic variants (PVs) in breast cancer (BC) predisposition genes and polygenic risk scores (PRS) with BC in the general population. METHODS A total of 26,798 non-Hispanic white BC cases and 26,127 controls from predominately population-based studies in the Cancer Risk Estimates Related to Susceptibility consortium were evaluated for PVs in BRCA1, BRCA2, ATM, CHEK2, PALB2, BARD1, BRIP1, CDH1, and NF1. PRS based on 105 common variants were created using effect estimates from BC genome-wide association studies; the performance of an overall BC PRS and estrogen receptor–specific PRS were evaluated. The odds of BC based on the PVs and PRS were estimated using penalized logistic regression. The results were combined with age-specific incidence rates to estimate 5-year and lifetime absolute risks of BC across percentiles of PRS by PV status and first-degree family history of BC. RESULTS The estimated lifetime risks of BC among general-population noncarriers, based on 10th and 90th percentiles of PRS, were 9.1%-23.9% and 6.7%-18.2% for women with or without first-degree relatives with BC, respectively. Taking PRS into account, more than 95% of BRCA1, BRCA2, and PALB2 carriers had > 20% lifetime risks of BC, whereas, respectively, 52.5% and 69.7% of ATM and CHEK2 carriers without first-degree relatives with BC, and 78.8% and 89.9% of those with a first-degree relative with BC had > 20% risk. CONCLUSION PRS facilitates personalization of BC risk among carriers of PVs in predisposition genes. Incorporating PRS into BC risk estimation may help identify > 30% of CHEK2 and nearly half of ATM carriers below the 20% lifetime risk threshold, suggesting the addition of PRS may prevent overscreening and enable more personalized risk management approaches.

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.

In this study we aim to examine gene–environment interactions (GxEs) between genes involved with estrogen metabolism and environmental factors related to estrogen exposure. GxE analyses were conducted with 1970 Korean breast cancer cases and 2052 controls in the case-control study, the Seoul Breast Cancer Study (SEBCS). A total of 11,555 SNPs from the 137 candidate genes were included in the GxE analyses with eight established environmental factors. A replication test was conducted by using an independent population from the Breast Cancer Association Consortium (BCAC), with 62,485 Europeans and 9047 Asians. The GxE tests were performed by using two-step methods in GxEScan software. Two interactions were found in the SEBCS. The first interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2 × 10−3). The age at menarche before 14 years old was associated with the high risk of breast cancer, and the risk was higher when subjects had homozygous minor allele G. The second GxE was shown between rs851998 near ESR1 and height in the GE|2df model (p-2df = 1.1 × 10−4). Height taller than 160 cm was associated with a high risk of breast cancer, and the risk increased when the minor allele was added. The findings were not replicated in the BCAC. These results would suggest specificity in Koreans for breast cancer risk.