Kraft, Peter

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: Pathogenic variants detected in multi-gene cancer predisposition panels are increasingly used to counsel women regarding their risk for breast cancer. However, the clinical implications of moderate penetrance genes (e.g. CHEK2, ATM) remain unclear. Breast MRI is indicated for women with a lifetime risk of breast cancer of >20%, and polygenic risk scores (PRS) based on common variants discovered in recent genome-wide association studies (GWAS) may identify women with pathogenic variants in CHEK2 and ATM who are above or below this level of risk. PRS may also stratify carriers with substantially elevated lifetime risks of breast cancer. Previous work found that PRS modified breast cancer risk in carriers of pathogenic variant in BRCA1 or BRCA2, but the joint effects of pathogenic variants and PRS have not been studied in samples drawn from the general population. There is also no published study evaluating the effect of PRS among women with pathogenic variants in genes other than BRCA1/2 and CHEK2. Here, we evaluated the joint effects of PRS and pathogenic variants in ten established breast cancer predisposition genes in a population-based case-control sample. Method: We analyzed 43,144 non-Hispanic European-ancestry individuals (20,988 controls and 22,120 cases) drawn from 7 cohorts and 2 population-based case-control studies in the CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) consortium. Targeted sequencing was performed using a dual bar-coded QIAseq panel of breast cancer predisposition genes. Variant calling was conducted with Haplotype Caller and Vardict. The PRS was calculated based on 106 common variants using effect estimates from the largest published breast cancer GWAS. Genetic status was evaluated for 10 breast cancer predisposition genes: ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, NF1, PALB2 and TP53. Lasso Penalized regression was performed to assess the combined effect on overall breast cancer of pathogenic variants and common variants (including main and interaction effects between age, family history, carrier status and PRS). The fraction of women at >2-fold increased risk (which is associated with approximately 20% lifetime risk of breast cancer) was calculated for pathogenic variant carriers and non-carriers of different family history and age groups (<40, 40-50, 50-60, 60-70, >70yrs old). Results: Among non-carriers, one standard deviation change in the PRS was associated with a 1.63x change in odds of breast cancer. The best-fitting risk model did not include any PRS-by-carrier interaction terms, implying the relative risk gradient associated with PRS among women with pathogenic variants is similar to that among non-carriers. For carriers of pathogenic variants in moderate penetrance genes with no family history of breast cancer, the PRS can identify 60.6% of ATM pathogenic variant carriers and 30% of CHEK2 pathogenic variant carriers that have less than 2-fold risk of breast cancer; when carriers have a family history of breast cancer, the PRS can identify 30% of ATM pathogenic variant carriers and 11.8% of CHEK2 pathogenic variant carriers with less than 2-fold risk of breast cancer. Conclusion: In our large, population-based case-control study, the effect of the PRS among pathogenic variant carriers was not significantly different than among non-carriers. However, the PRS may be particularly important for estimating breast cancer risk among carriers of pathogenic variants in moderate penetrance genes such as CHEK2 and ATM, enabling a more precise approach for MRI screening strategy and breast cancer risk management. Citation Format: Chi Gao, Eric C. Polley, Chunling Hu, Steven N. Hart, Rohan Gnanaolivu, Kun Y. Lee, Jie Na, Nicholas J. Boddicker, Raed Samara, Paul Auer, Leslie Bernstein, Mia Gaudet, Amy Trentham-Dietz, Song Yao, Christopher Haiman, Janet E. Olson, Susan Neuhausen, Jeffrey N. Weitzel, David E. Goldgar, Susan Domchek, Katherine L. Nathanson, Fergus J. Couch, Peter Kraft, on behalf of the CARRIERS consortium. Polygenic risk scores provide clinically meaningful risk stratification among women carrying moderate penetrance pathogenic variants in breast cancer predisposition genes: Results from the CARRIERS study [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 PD3-02.

Abstract Germline mutations in several cancer predisposition genes included in hereditary multigene testing panels have been associated with increased breast cancer risk. However, estimates of breast cancer risks for each gene have in large part been derived from studies of high-risk populations enriched for family history of breast and ovarian cancer, young age of breast cancer diagnosis, or founder mutations. The breast cancer risks associated with mutations in many of these genes in the general population remain to be clearly defined. As clinical hereditary cancer genetic testing is already provided to many women at increased risk and may soon be offered to all breast cancer patients, population-based risk estimates associated with predisposition gene mutations will be needed for appropriate clinical management of mutation carriers. The “CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) consortium of 17 cohort-based case-control, population-based case-control, and family studies focused on estimation of population-based breast cancer risks and penetrance analysis for mutations in known and candidate breast cancer predisposition genes. Germline DNA from 39486 breast cancer cases and 35868 matched controls was subjected to dual bar-coded QIAseq multiplex amplification of 1733 target regions in 37 predisposition genes. Products from sets of 768 samples were pooled and sequenced in each lane of a HiSeq 4000 system. Mutations were called by GATK Haplotype Caller and Verdict. High quality sequence data was obtained for 99.3% of target regions. Here we report on results from 34741 population-based breast cancer cases and 32728 matched unaffected controls. The mean age of breast cancer diagnosis for cases was 61.2 years and mean age for controls was 61.1 years. Overall, 20.9% of cases and 14.3% of controls had a family history of breast cancer. Furthermore, 74.3% of cases and 75.8% of controls were non-Hispanic white, whereas 13.3% of cases and 15.3% of controls were African American. Among cases with tumor information available, 81.7% were ER-positive and 7.7% were triple negative breast cancers (TNBC). We assessed mutation frequencies in 24 genes including 12 established breast cancer predisposition genes (ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, NF1, PALB2, PTEN, RAD51C, RAD51D, andTP53). The overall mutation frequency was 6.2% in cases and 2.7% in controls. Case-control association analysis after adjusting for study, age, family history of breast cancer, and race/ethnicity showed that BRCA1(OR=7.45; 95%CI:5.24-10.95) and BRCA2(OR=5.31; 95%CI:4.15-6.88) were associated with high risks of breast cancer in the general population. However, PALB2mutations were only associated with moderate risks (OR=3.63; 95%CI:2.57-5.26). ATMmutations conferred attenuated risks (OR=1.83; 95%CI:1.47-2.28) relative to studies of high-risk families or young onset breast cancers. NBNmutations were not associated with increased breast cancer risk. Mutations in BARD1, RAD51C, RAD51Dand XRCC2were specifically significantly associated with moderate risks of ER-negative breast cancer and TNBC, whereas mutations in ATM, CDH1and CHEK2were specifically significantly associated with ER-positive disease. On the basis of these findings age-related absolute breast cancer risks for commonly mutated genes were estimated. Overall, results from the CARRIERS study establish that mutations in predisposition genes are associated with lower risks of breast cancer in the general population than in enriched populations including high-risk families and young onset, bilateral, or multiple primary cases. We anticipate that the results from this study will inform cancer screening and other risk management strategies for women in the general population with mutations in predisposition genes. Citation Format: Fergus J Couch, Chunling Hu, Steven N Hart, Rohan Gnanaolivu, Kun Y Lee, Jie Na, Chi Gao, Nicholas J Boddicker, Bruce Eckloff, Raed Samara, Josh Klebba, Christine B Ambrosone, Hoda Anton-Culver, Paul Auer, Leslie Bernstein, Mia M Gaudet, Christopher Haiman, Esther M John, Susan Neuhausen, Janet E Olson, Tuya Pal, Julie R Palmer, Dale P Sandler, Jack A Taylor, Amy Trentham-Dietz, Celine M Vachon, Clarice Weinberg, Song Yao, Jeffrey N Weitzel, David E Goldgar, Susan M Domchek, Katherine L Nathanson, Peter Kraft, Eric C Polley. Population-based breast cancer risk estimates for predisposition gene mutations: Results from the CARRIERS study [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 PD3-01.

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<0.05 all tumors). Alcohol drinkers had higher SCNV compared to non-drinkers (p<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 risks of breast cancer in African American (AA) women associated with inherited mutations in breast cancer predisposition genes are not well defined. Thus, whether multigene germline hereditary cancer testing panels are applicable to this population is unknown. We assessed associations between mutations in panel-based genes and breast cancer risk in 5054 AA women with breast cancer and 4993 unaffected AA women drawn from 10 epidemiologic studies. Methods Germline DNA samples were sequenced for mutations in 23 cancer predisposition genes using a QIAseq multiplex amplicon panel. Prevalence of mutations and odds ratios (ORs) for associations with breast cancer risk were estimated with adjustment for study design, age, and family history of breast cancer. Results Pathogenic mutations were identified in 10.3% of women with estrogen receptor (ER)-negative breast cancer, 5.2% of women with ER-positive breast cancer, and 2.3% of unaffected women. Mutations in BRCA1, BRCA2, and PALB2 were associated with high risks of breast cancer (OR = 47.55, 95% confidence interval [CI] = 10.43 to >100; OR = 7.25, 95% CI = 4.07 to 14.12; OR = 8.54, 95% CI = 3.67 to 24.95, respectively). RAD51D mutations were associated with high risk of ER-negative disease (OR = 7.82, 95% CI = 1.61 to 57.42). Moderate risks were observed for CHEK2, ATM, ERCC3, and FANCC mutations with ER-positive cancer, and RECQL mutations with all breast cancer. Conclusions The study identifies genes that predispose to breast cancer in the AA population, demonstrates the validity of current breast cancer testing panels for use in AA women, and provides a basis for increased referral of AA patients for cancer genetic testing.

AbstractPrevious transcriptome‐wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome‐wide association studies (GWAS), but analyses of breast cancer subtype‐specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta‐analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER−). We further compared associations with ER+ and ER− subtypes, using a case‐only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER– breast cancer. We further identified 30 TWAS‐significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast‐cancer gene in three of six regions harboring multiple TWAS‐significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER− breast cancer.

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 < 0.05 all women). Alcohol drinkers had higher SCNV versus nondrinkers (P < 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.

Abstract Background Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. Methods To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74–421 samples). Results We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction. Conclusions By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.

Abstract We previously identified five single nucleotide polymorphisms (SNPs) at four susceptibility loci for diffuse large B-cell lymphoma (DLBCL) in individuals of European ancestry through a large genome-wide association study (GWAS). To further elucidate genetic susceptibility to DLBCL, we sought to validate two loci at 3q13.33 and 3p24.1 that were suggestive in the original GWAS with additional genotyping. In the meta-analysis (5662 cases and 9237 controls) of the four original GWAS discovery scans and three replication studies, the 3q13.33 locus (rs9831894; minor allele frequency [MAF] = 0.40) was associated with DLBCL risk [odds ratio (OR) = 0.83, P = 3.62 × 10−13]. rs9831894 is in linkage disequilibrium (LD) with additional variants that are part of a super-enhancer that physically interacts with promoters of CD86 and ILDR1. In the meta-analysis (5510 cases and 12 817 controls) of the four GWAS discovery scans and four replication studies, the 3p24.1 locus (rs6773363; MAF = 0.45) was also associated with DLBCL risk (OR = 1.20, P = 2.31 × 10−12). This SNP is 29 426-bp upstream of the nearest gene EOMES and in LD with additional SNPs that are part of a highly lineage-specific and tumor-acquired super-enhancer that shows long-range interaction with AZI2 promoter. These loci provide additional evidence for the role of immune function in the etiology of DLBCL, the most common lymphoma subtype.