Tapper, William

Abstract Background Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. Methods Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) <0.2 was used to identify associations with strong statistical evidence. Results Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend<0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend<0.001 and <0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend<0.001 and <0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. Conclusion This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

Abstract Studies have identified genetic and epidemiologic factors associated with mammographic density (MD) phenotypes. However, MD-associated genetic variants only account for a small proportion of the total estimated heritability. Interrogating interactions between genetic and epidemiologic factors could potentially identify additional MD-associated loci, expand our understanding of the genetic basis of MD phenotypes, and clarify how epidemiologic factors modulate relationships between genetic variants and MD. We conducted six separate genome-wide, gene–environment (GxE) interaction analyses, applying 2 degrees of freedom (df) and 1df interaction tests, for each of three MD phenotypes (percent density, dense area (DA), and nondense area (NDA)). The six epidemiologic factors considered were height, ever parous, parity, ever menopausal hormone therapy, ever breastfeeding, and months of breastfeeding. We included European ancestry participants from multiple studies within the Markers of Density consortium and the Breast Cancer Association Consortium (n = 4895-16 218 depending on specific analyses). We identified 11 loci with genome-wide significant (P < 5 × 10−8) interaction tests including two novel common genetic signals interacting with parity (8p21.2) and ever breastfeeding (19p13.2) for NDA. Our results suggest that epidemiologic risk factors might influence relationships between common genetic variants and MD phenotypes at particular genomic loci.

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 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)

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 > 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 <20 years at first pregnancy [0.79 (0.72–0.86)]; >0–<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.

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 Familial studies were among the first to indicate that breast cancer prognosis has a heritable component. Subsequently many variants associated with prognosis have been identified using a range of techniques including genome-wide association studies (GWAs). Despite these advances, much of the heritability remains unexplained. In young women, breast cancer is characterised by a higher incidence of adverse pathological features, unique tumour gene expression profiles and worse survival. In addition, the association of risk with conventional epidemiological exposures is less clear in women with early onset. We hypothesise that some of these difference between early and late onset could be influenced by germline variation. To identify additional variants that influence breast cancer prognosis we conducted a two stage meta-analysis of four GWAs consisting of 6,042 patients from the UK (POSH), Finland (HEBCS), Germany (SUCCESS-A) and Australia (ABCFS). Cox-regression analyses were used to investigate overall survival (OS, n=1,101 events) and disease-free survival (DFS, n=1,316 events) with correction for oestrogen status (ER). These survival analyses were repeated in a subset of patients with early onset (aged ≤40 at diagnosis, n=2,315 patients, OS n=604 events, DFS n=716 events). Meta-analysis identified two intronic SNPs in ADAMTSL1 that were associated exclusively with early onset DFS, rs715212 (Pmeta=3.54x10-5) and rs10963755 (Pmeta=3.91x10-4) without heterogeneity between cohorts. Multivariable Cox-regression demonstrated that the effect of these SNPs were independent of the classical prognostic factors. Most importantly, rs715212 reached genome-wide significance (Pmultivariate=5.37x10-8) in the multivariate model. ADAMTSL1 encodes a glycoprotein that forms part of the extracellular matrix (ECM) and may function in cell-cell or cell-matrix interactions or may regulate other ADAMTS proteases. Previous studies have shown that ADAMTSL1 is hypermethylated in ER positive breast cancer tumours. Using GTEx to perform eQTL analysis, we found that rs715212 is associated with the expression of several biologically relevant genes AREG (P=0.035), TNF (P=0.015), FASLG (P=0.0031) and EGF (P=0.0018) in breast mammary tissue. Interestingly, separate studies have shown that AREG is overexpressed in ER-positive breast tumours from pre-menopausal women versus post-menopausal women. Furthermore, AREG is differentially expressed between parous and non-parous mammary glands and is persistently downregulated by parity, which suggests it may contribute to the susceptibility of the nulliparous gland to breast cancer. We conclude that rs715212 is associated with an increased risk of disease progression in patients with early onset and speculate that this could be due to an interaction with the expression of AREG. Note: This abstract was not presented at the meeting. Citation Format: Latha Kadalayil, Sofia Khan, Heli Nevanlinna, Peter A. Fasching, Fergus J. Couch, John Hopper, Jianjun Liu, Tom Maishman, Lorraine Durcan, Carl Bloomqvist, Andy Collins, Dianna Eccles, William Tapper. A meta-analysis of genome-wide association studies identifies novel loci that influence breast cancer prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1322. doi:10.1158/1538-7445.AM2017-1322

Background The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. Methods We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. Results For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. Conclusions This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.