Eliassen, A. Heather

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.

Abstract Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer–specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (Padj &gt; 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5–25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06–1.34)]; current versus never smoking [1.37 (1.27–1.47)], high versus low physical activity [0.43 (0.21–0.86)], age ≥30 years versus &lt;20 years at first pregnancy [0.79 (0.72–0.86)]; &gt;0–&lt;5 years versus ≥10 years since last full-term birth [1.31 (1.11–1.55)]; ever versus never use of oral contraceptives [0.91 (0.87–0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen–progestin therapy [0.61 (0.54–0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02–1.21) for current versus never smoking. Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.

Abstract We evaluated the joint associations between a new 313-variant PRS (PRS313) and questionnaire-based breast cancer risk factors for women of European ancestry, using 72 284 cases and 80 354 controls from the Breast Cancer Association Consortium. Interactions were evaluated using standard logistic regression and a newly developed case-only method for breast cancer risk overall and by estrogen receptor status. After accounting for multiple testing, we did not find evidence that per-standard deviation PRS313 odds ratio differed across strata defined by individual risk factors. Goodness-of-fit tests did not reject the assumption of a multiplicative model between PRS313 and each risk factor. Variation in projected absolute lifetime risk of breast cancer associated with classical risk factors was greater for women with higher genetic risk (PRS313 and family history) and, on average, 17.5% higher in the highest vs lowest deciles of genetic risk. These findings have implications for risk prevention for women at increased risk of breast cancer.

Abstract Background: Understanding the molecular influence of epidemiological risk factors can provide insights into breast cancer etiology and progression, and lead to better prevention efforts and treatment guidelines. The link between modifiable breast cancer risk factors and tumor genomic alterations remains unexplored. This study evaluated the association of tobacco use and alcohol consumption with somatic copy number variation (SCNV), total somatic mutation burden (TSMB), seven single base substitution (SBS) signatures (SBS1, SBS2, SBS3, SBS5, SBS13, SBS29, and SBS30) (1-3), and nine breast cancer driver mutations (CDH1, GATA3, KMT2C, MAP2K4, MAP3K1, NCOR1, PIK3CA, RUNX1, and TP53) (4,5), in a subset of The Cancer Genome Atlas (TCGA). Method: Clinical and genomic data were retrieved from the TCGA database, and breast cancer risk factor information was collected from four TCGA sites; in all, 219 female breast cancer cases were included. Pre-diagnostic tobacco use was defined as never or ever; alcohol consumption was defined as drinkers or non-drinkers. Total SCNV was obtained by summing all segments with ≥|0.2|. TSMB was calculated by summing all significant mutations for each case. SBS signatures were computed using whole exome sequencing data. Analyses were conducted in all tumors (i.e., pooled) and by stratifying according to estrogen receptor (ER) status using multivariate regression, adjusting for co-variables. Results: Tobacco users had higher TSMB compared to non-users (p&lt;0.05 all tumors). Alcohol drinkers had higher SCNV compared to non-drinkers (p&lt;0.05 all tumors and among ER+ tumors). Tobacco use was not associated with any SBS signature. SBS3 signature (defective homologous recombination-based repair) was exclusively found in alcohol drinkers with ER- disease. No breast cancer driver mutation was associated with tobacco use or alcohol consumption. Conclusion: This study provides preliminary evidence that tobacco use and alcohol consumption can influence breast tumor biology, in particular, DNA alterations. Future larger epidemiological studies are required to confirm these findings. References 1. Vineis P, et al. Mutational signatures associated with tobacco smoking in human cancer. Science. 2016;354(6312):618-22. 2. Alexandrov LB, et al. Clock-like mutational processes in human somatic cells. Nat Genet. 2015;47(12):1402-7. 3. Petljak M, Alexandrov LB. Understanding mutagenesis through delineation of mutational signatures in human cancer. Carcinogenesis. 2016;37(6):531-40. 4. Heng YJ, et al. The molecular basis of breast cancer pathologic phenotypes. J Pathol. 2017 Nov;241(3):375-91. 5. Ciriello G, et al. Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer. Cell. 2015 Oct 10;163(2):506-19. Citation Format: Yujing J Heng, Susan E Hankinson, Jun Wang, Ludmil B Alexandrov, Christine B Ambrosone, Victor Piana de Andrade, Adam M Brufsky, Fergus J Couch, Tari A King, Francesmary Modugno, Celine M Vachon, A. Heather Eliassen, Rulla M Tamimi, Peter Kraft. Tobacco use, alcohol consumption, and breast cancer somatic genomic alterations [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-08-07.

Abstract Background: The link between modifiable breast cancer risk factors and tumor genomic alterations remains largely unexplored. We evaluated the association of prediagnostic body mass index (BMI), cigarette smoking, and alcohol consumption with somatic copy number variation (SCNV), total somatic mutation burden (TSMB), seven single base substitution (SBS) signatures (SBS1, SBS2, SBS3, SBS5, SBS13, SBS29, and SBS30), and nine driver mutations (CDH1, GATA3, KMT2C, MAP2K4, MAP3K1, NCOR1, PIK3CA, RUNX1, and TP53) in a subset of The Cancer Genome Atlas (TCGA). Methods: Clinical and genomic data were retrieved from the TCGA database. Risk factor information was collected from four TCGA sites (n = 219 women), including BMI (1 year before diagnosis), cigarette smoking (smokers/nonsmokers), and alcohol consumption (current drinkers/nondrinkers). Multivariable regression analyses were conducted in all tumors and stratified according to estrogen receptor (ER) status. Results: Increasing BMI was associated with increasing SCNV in all women (P = 0.039) and among women with ER− tumors (P = 0.031). Smokers had higher SCNV and TSMB versus nonsmokers (P &lt; 0.05 all women). Alcohol drinkers had higher SCNV versus nondrinkers (P &lt; 0.05 all women and among women with ER+ tumors). SBS3 (defective homologous recombination-based repair) was exclusively found in alcohol drinkers with ER− disease. GATA3 mutation was more likely to occur in women with higher BMI. No association was significant after multiple testing correction. Conclusions: This study provides preliminary evidence that BMI, cigarette smoking, and alcohol consumption can influence breast tumor biology, in particular, DNA alterations. Impact: This study demonstrates a link between modifiable breast cancer risk factors and tumor genomic alterations.