Breast Cancer Association Consortium Research Articles

Associations of a Breast Cancer Polygenic Risk Score With Tumor Characteristics and Survival.

A polygenic risk score (PRS) consisting of 313 common genetic variants (PRS313) is associated with risk of breast cancer and contralateral breast cancer. This study aimed to evaluate the association of the PRS313 with clinicopathologic characteristics of, and survival following, breast cancer. Women with invasive breast cancer were included, 98,397 of European ancestry and 12,920 of Asian ancestry, from the Breast Cancer Association Consortium (BCAC), and 683 women from the European MINDACT trial. Associations between PRS313 and clinicopathologic characteristics, including the 70-gene signature for MINDACT, were evaluated using logistic regression analyses. Associations of PRS313 (continuous, per standard deviation) with overall survival (OS) and breast cancer-specific survival (BCSS) were evaluated with Cox regression, adjusted for clinicopathologic characteristics and treatment. The PRS313 was associated with more favorable tumor characteristics. In BCAC, increasing PRS313 was associated with lower grade, hormone receptor-positive status, and smaller tumor size. In MINDACT, PRS313 was associated with a low risk 70-gene signature. In European women from BCAC, higher PRS313 was associated with better OS and BCSS: hazard ratio (HR) 0.96 (95% CI, 0.94 to 0.97) and 0.96 (95% CI, 0.94 to 0.98), but the association disappeared after adjustment for clinicopathologic characteristics (and treatment): OS HR, 1.01 (95% CI, 0.98 to 1.05) and BCSS HR, 1.02 (95% CI, 0.98 to 1.07). The results in MINDACT and Asian women from BCAC were consistent. An increased PRS313 is associated with favorable tumor characteristics, but is not independently associated with prognosis. Thus, PRS313 has no role in the clinical management of primary breast cancer at the time of diagnosis. Nevertheless, breast cancer mortality rates will be higher for women with higher PRS313 as increasing PRS313 is associated with an increased risk of disease. This information is crucial for modeling effective stratified screening programs.

Identifying and ranking causal biochemical biomarkers for breast cancer: a Mendelian randomisation study

BackgroundOnly a few of the 34 biochemical biomarkers measured in the UK Biobank (UKB) have been associated with breast cancer, with many associations suffering from possible confounding and reverse causation. This study aimed to screen and rank all UKB biochemical biomarkers for possible causal relationships with breast cancer.MethodsWe conducted two-sample Mendelian randomisation (MR) analyses on ~420,000 women by leveraging summary-level genetic exposure associations from the UKB study (n = 194,174) and summary-level genetic outcome associations from the Breast Cancer Association Consortium (n = 228,951). Our exposures included all 34 biochemical biomarkers in the UKB, and our outcomes were overall, oestrogen-positive, and oestrogen-negative breast cancer. We performed inverse-variance weighted MR, weighted median MR, MR-Egger, and MR-PRESSO for 30 biomarkers for which we found multiple instrumental variables. We additionally performed multivariable MR to adjust for known risk factors, bidirectional MR to investigate reverse causation, and MR Bayesian model averaging to rank the significant biomarkers by their genetic evidence.ResultsIncreased genetic liability to overall breast cancer was robustly associated with the following biomarkers by decreasing importance: testosterone (odds ratio (OR): 1.12, 95% confidence interval (CI): 1.04–1.21), high-density lipoprotein (HDL) cholesterol (OR: 1.08, 95% CI: 1.04–1.13), insulin-like growth factor 1 (OR: 1.08, 95% CI: 1.02–1.13), and alkaline phosphatase (ALP) (OR: 0.93, 95% CI: 0.89–0.98).ConclusionsOur findings support a likely causal role of genetically predicted levels of testosterone, HDL cholesterol, and IGF-1, as well as a novel potential role of ALP in breast cancer aetiology. Further studies are needed to understand full disease pathways that may inform breast cancer prevention.

Association and performance of polygenic risk scores for breast cancer among French women presenting or not a familial predisposition to the disease

BackgroundThree partially overlapping breast cancer polygenic risk scores (PRS) comprising 77, 179 and 313 SNPs have been proposed for European-ancestry women by the Breast Cancer Association Consortium (BCAC) for improving risk prediction in the general population. However, the effect of these SNPs may vary from one country to another and within a country because of other factors. ObjectiveTo assess their associated risk and predictive performance in French women from (1) the CECILE population-based case-control study, (2) BRCA1 or BRCA2 (BRCA1/2) pathogenic variant (PV) carriers from the GEMO study, and (3) familial breast cancer cases with no BRCA1/2 PV and unrelated controls from the GENESIS study. ResultsAll three PRS were associated with breast cancer in all studies, with odds ratios per standard deviation varying from 1.7 to 2.0 in CECILE and GENESIS, and hazard ratios varying from 1.1 to 1.4 in GEMO. The predictive performance of PRS313 in CECILE was similar to that reported in BCAC but lower than that in GENESIS (area under the receiver operating characteristic curve (AUC) = 0.67 and 0.75, respectively). PRS were less performant in BRCA2 and BRCA1 PV carriers (AUC = 0.58 and 0.54 respectively). ConclusionOur results are in line with previous validation studies in the general population and in BRCA1/2 PV carriers. Additionally, we showed that PRS may be of clinical utility for women with a strong family history of breast cancer and no BRCA1/2 PV, and for those carrying a predicted PV in a moderate-risk gene like ATM, CHEK2 or PALB2.

Relationship between telomere length and the prognosis of breast cancer based on estrogen receptor status: A Mendelian randomization study.

To identify the relationship between telomere length and the prognosis of breast cancer with different status of estrogen receptor (ER). We collected single nucleotide polymorphisms (SNPs) associated with telomere length and breast cancer prognosis from the MRCIEU GWAS database and the dataset of a large meta-analysis conducted by the Breast Cancer Association Consortium (BCAC), respectively. The relationship was identified using inverse-variance weighted (IVW), MR-Egger, weighted median, penalized weighted median, and maximum likelihood methods. IVW, MR-Egger, and MR-PRESSO methods were used to perform sensitivity analysis to assess the accuracy of the results. Telomere length was negatively associated with the prognosis of total breast cancer (odds ratio [OR]=1.84, 95% confidence interval [CI]=1.08-3.14, IVW method), especially with ER- breast cancer (OR=1.89, 95% CI=1.11-3.22, IVW method). No similar relationship was found between telomere length and the prognosis of ER+ breast cancer (OR=0.99, 95% CI=0.62-1.58, IVW method). The findings from other methods were consistent with the results shown by the IVW method. The Mendelian randomization assumptions did not appear to be violated. Sensitivity analysis indicated that the result was robust, and no bias was observed in the study. Telomere length is associated with the prognosis of total breast cancer, especially with ER- breast cancer. There is no significant correlation between telomere length and the prognosis of ER+ breast cancer. These findings add to the evidence that long telomere could predict a poor prognosis of ER- breast cancer.

A Mendelian randomization study of the effect of tea intake on breast cancer.

The relationship between tea consumption and the risk of breast cancer is inconsistent in previous observational studies and is still in dispute. We intended to detect the causal association between tea consumption and breast cancer risk using two-sample Mendelian randomization (MR) analysis. The summary statistics of tea consumption was obtained from the UK Biobank Consortium with 349,376 individuals and breast cancer information was obtained from the Breast Cancer Association Consortium (BCAC) (122,977 cases and 105,974 non-cases). Sensitivity analyses of evaluating the influence of outliers and pleiotropy effects were performed by a variety of MR methods under different model assumptions. After potentially excluding pleiotropic single nucleotide polymorphisms (SNPs) using the MR Pleiotropy RESidual Sum and Outlier method, the odds ratio (OR) for per extra daily cup of tea intake for overall, estrogen receptor (ER)-positive, and ER-negative breast cancer risk was 1.029 [95% confidence interval (CI) = 0.983-1.077, P = 0.2086], 1.050 (95% CI = 0.994-1.109, P = 0.078), and 1.081 (95% CI = 0.990-1.103, P = 0.6513), respectively. The results were consistent with a sensitivity analysis that excluded SNPs associated with other phenotypes, manifesting that the findings were convincing and robust. Moreover, in the multivariable MR analysis, the null associations for breast cancer risk remained after adjusting for smoking and alcohol consumption separately or together. Our MR results based on genetic data did not support a causal relationship between tea consumption and breast cancer risk.

Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study

ObjectivesPhysical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups...

Incorporating progesterone receptor expression into the PREDICT breast prognostic model

BackgroundPredict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2). MethodThe prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance. ResultsHaving a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10−6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted. ConclusionThe inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.

Associations between circulating proteins and risk of breast cancer by intrinsic subtypes: a Mendelian randomisation analysis.

The aetiologic role of circulating proteins in the development of breast cancer subtypes is not clear. We aimed to examine the potential causal effects of circulating proteins on the risk of breast cancer by intrinsic-like subtypes within the Mendelian randomisation (MR) framework. MR was performed using summary statistics from two sources: the INTERVAL protein quantitative trait loci (pQTL) Study (1890 circulating proteins and 3301 healthy individuals) and the Breast Cancer Association Consortium (BCAC; 106,278 invasive cases and 91,477 controls). The inverse-variance (IVW)-weighted method was used as the main analysis to evaluate the associations between genetically predicted proteins and the risk of five different intrinsic-like breast cancer subtypes and the weighted median MR method, the Egger regression, the MR-PRESSO, and the MRLocus method were performed as secondary analysis. We identified 98 unique proteins significantly associated with the risk of one or more subtypes (Benjamini-Hochberg false discovery rate < 0.05). Among them, 51 were potentially specific to luminal A-like subtype, 14 to luminal B/Her2-negative-like, 11 to triple negative, 3 to luminal B-like, and 2 to Her2-enriched-like breast cancer (ntotal = 81). Associations for three proteins (ICAM1, PLA2R1 and TXNDC12) showed evident heterogeneity across the subtypes. For example, higher levels of genetically predicted ICAM1 (per unit of increase) were associated with an increased risk of luminal B/HER2-negative-like cancer (OR = 1.06, 95% CI = 1.03-1.08, BH-FDR = 2.43 × 10-4) while inversely associated with triple-negative breast cancer with borderline significance (OR = 0.97, 95% CI = 0.95-0.99, BH-FDR = 0.065, Pheterogeneity < 0.005). Our study found potential causal associations with the risk of subtypes of breast cancer for 98 proteins. Associations of ICAM1, PLA2R1 and TXNDC12 varied substantially across the subtypes. The identified proteins may partly explain the heterogeneity in the aetiology of distinct subtypes of breast cancer and facilitate the personalised risk assessment of the malignancy.

Major depression disorder may causally associate with the increased breast cancer risk: Evidence from two-sample mendelian randomization analyses.

Major depression disorder (MDD) has been associated with increased breast cancer risk in epidemiological studies; however, it is still unknown whether this association is causal or not. The aim of this study is to determine the causal relationship between MDD and breast cancer risk. Two-sample Mendelian randomization (MR) analyses with 92 single-nucleotide polymorphisms (SNPs) significantly associated with MDD as instrumental variables (IVs) were performed. Effects of these SNPs on breast cancer in women were estimated in the Breast Cancer Association Consortium (122,977 cases and 105,974 controls) using inverse variance weighted (IVW), weighted median and multivariable MR models. Heterogeneity and pleiotropy effects were assessed based on IVW and MR-Egger regression model, respectively. An 8.7% increased risk of overall breast cancer [odds ratio (OR)=1.087; 95% confidence interval (CI) 1.011-1.170; P=0.025] per log-odds ratio increment of MDD risk based on the IVW model was noticed. Similar results were obtained with the multivariable MR model (OR=1.118, 95% CI=1.010-1.237; P=0.031). An increment but not statistically significant causality association was noticed between MDD and risk of ER+ (OR=1.098, 95% CI=0.984-1.227; P=0.093) or ER- (OR=1.129, 95% CI=0.982-1.297; P=0.089) breast cancer under multivariable MR model. No significant pleiotropy effects were observed for the IVs in the two-sample MR studies. The results suggested that a genetic predisposition of MDD is causally associated with overall breast cancer risk; however, the underlying biological mechanisms are worthy of further study.

Association between dried fruit intake and pan-cancers incidence risk: A two-sample Mendelian randomization study.

BackgroundObservational studies have revealed that dried fruit intake may be associated with cancer incidence; however, confounding factors make the results prone to be disturbed. Therefore, we conducted a two-sample Mendelian randomization (MR) study to explore the causal relationship between dried fruit intake and 11 site-specific cancers.Materials and methodsForty-three single nucleoside polymers (SNPs) with robust genome-wide association study (GWAS) evidence, strongly correlated with dried fruit intake, were used as instrumental variables (IVs) in this study. The summary-level genetic datasets of site-specific cancers were obtained from the Oncoarray oral cavity and oropharyngeal cancer consortium, International Lung Cancer Consortium, Breast Cancer Association Consortium (BCAC), Ovarian Cancer Association Consortium, PanScan1, and GWAS of other scholars. We analyzed the causality between dried fruit intake and 11 site-specific cancers using the inverse-variance-weighted (IVW) and weighted median (WM) methods. For the results of the MR analysis, Cochran’s Q test was used to check for heterogeneity, and multiplicative random effects were used to evaluate the heterogeneity further. Gene pleiotropy was tested using MR-Egger regression and MR-PRESSO methods. In addition, the main results of this study were validated by using the summary statistical data from the FinnGen and UK Biobank databases, and adjusted body mass index (BMI), years of education, fresh fruit intake, and vitamin C using multivariable MR analysis to ensure the stability of the research results.ResultsThe evidence from IVW analyses showed that each increase of dried fruit intake by one standard deviation was statistically significantly associated with 82.68% decrease of oral cavity/pharyngeal cancer incidence risk (P = 0.0131), 67.01% decrease of lung cancer incidence risk (P = 0.0011), 77% decrease of squamous cell lung cancer incidence risk (P = 0.0026), 53.07% decrease of breast cancer incidence risk (P = 4.62 × 10–5), 39.72% decrease of ovarian cancer incidence risk (P = 0.0183), 97.26% decrease of pancreatic cancer incidence risk (P = 0.0280), 0.53% decrease of cervical cancer incidence risk (P = 0.0482); however, there was no significant effect on lung adenocarcinoma (P = 0.4343), endometrial cancer (P = 0.8742), thyroid cancer (P = 0.6352), prostate cancer (P = 0.5354), bladder cancer (P = 0.8996), and brain cancer (P = 0.8164). In the validation part of the study results, the causal relationship between dried fruit intake and lung cancer (P = 0.0043), squamous cell lung cancer (P = 0.0136), and breast cancer (P = 0.0192) was determined. After adjusting for the potential impact of confounders, the causal relationship between dried fruit intake and lung cancer (P = 0.0034), squamous cell lung cancer (P = 0.046), and breast cancer (P = 0.0001) remained. The sensitivity analysis showed that our results were stable and reliable.ConclusionThe intake of dried fruits may have a protective effect against some site-specific cancers. Therefore, health education and a reasonable adjustment of dietary proportions may help in the primary prevention of cancer.

Distinct Reproductive Risk Profiles for Intrinsic-Like Breast Cancer Subtypes: Pooled Analysis of Population-Based Studies.

Reproductive 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. Analyses 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. Compared 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. This 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 5900: Integrating prior knowledge of transcription factor occupied elements with transcriptome-wide association analysis identifies 153 breast cancer susceptibility genes

Abstract Transcriptome-wide association studies (TWAS) have been successful in uncovering large numbers of putative disease susceptibility genes. TWAS approaches such as S-PrediXcan, FUSION and TIGAR, show comparable overall performance for susceptibility gene discovery; however, integrating prior disease-specific regulatory information is lacking. To improve accuracy of gene expression prediction by integrating information on susceptible transcription factor (sTF) occupancy in target cells and tissues, we developed an analytical framework, called sTF-TWAS. We evaluated six sets of putative regulatory variants selected from sTF-occupied sites, and performed generalized Berk-Jones (GBJ) analysis to combine sets and quantify overall associations. We demonstrated that sTF-TWAS outperforms S-PrediXcan in both simulation and real data analyses. Using summary statistics data from the Breast Cancer Association Consortium (BCAC), we also incorporated alternative splicing (sp) data in TF-TWAS and identified 76 and 88 significant genes for breast cancer risk at a Bonferroni-corrected P &amp;lt;0.05 from sTF-TWAS and sp-sTF-TWAS, respectively. Of 153 putative susceptibility genes from both sTF-TWAS and sp-sTF-TWAS, 14 genes in 12 loci had novel associations with breast cancer risk and 90 genes were previously unreported by breast cancer GWAS. We also provide strong evidence for 15 previously unreported genes, including 11 essential for breast cell proliferation and five suggested cancer predisposition or driver genes: RAD50, IGHMBP2, ATXN3, KANSL1, and IL6ST. Overall, we demonstrated that our approach has significant advantages over regular TWAS and our findings provide additional insights into the genetic susceptibility of breast cancer. Citation Format: Xingyi Guo, Jingni He, Alicia Beeghly-Fadiel, Zhishan Chen, Chen Cao, Xiao-ou Shu, Wei Zheng, Quan Long. Integrating prior knowledge of transcription factor occupied elements with transcriptome-wide association analysis identifies 153 breast cancer susceptibility genes [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 5900.

Associations of a breast cancer polygenic risk score with tumor characteristics and survival.

563 Background: A polygenic risk score (PRS) consisting of 313 single nucleotide polymorphisms (PRS313) is associated with risk of breast cancer and contralateral breast cancer. One of the most promising clinical applications for the use of PRS is to provide a personalized risk assessment to individualize breast cancer screening programs. This study aimed to evaluate the association of the PRS313 with clinical-pathological characteristics and survival of breast cancer. Methods: Women of European ancestry with invasive breast cancer were included, 98,397 women from the Breast Cancer Association Consortium (BCAC) and 683 women from the MINDACT trial. Associations between PRS313 (continuous, per SD) and clinical-pathological characteristics, including the 70-gene signature for patients included in MINDACT, were evaluated with logistic regression analyses. Associations of PRS313 with overall survival (OS), breast cancer-specific survival (BCSS) and distant metastasis-free interval (DMFI) were evaluated with Cox regression analyses, adjusted for clinical-pathological characteristics and treatment. Results: The PRS313 was associated with favorable tumor characteristics. In BCAC, increasing PRS313 was mostly associated with lower grade, hormone receptor-positive tumors, and with smaller tumor size. In MINDACT, PRS313 was associated with a low risk 70-gene signature, but the association was attenuated after adjustment for clinical-pathological characteristics. In BCAC, univariable analyses showed an association of PRS313 with better survival, hazard ratio (HR) per unit SD increase of PRS313 for OS: 0.96 (95% confidence interval (CI): 0.94-0.97), for BCSS HR: 0.96 (95% CI: 0.94-0.98) and for DMFI HR: 0.98 (95% CI: 0.96-1.00). The association in the unadjusted analysis was explained by differences in clinical-pathological characteristics (and treatment) and disappeared after adjustment: OS HR: 1.01 (95% CI: 0.98-1.05), BCSS HR: 1.02 (95% CI: 0.98-1.07) and DMFI HR: 1.03 (95% CI: 0.99-1.07). Conclusions: An increased PRS313 is associated with favorable tumor characteristics but was not independently associated with prognosis. This information is crucial input for modelling effective stratified screening programs, especially in the current era of optimized (systemic) treatments. Given the significant increase in breast cancer risk associated with increasing PRS313, absolute breast cancer mortality will still be higher for women with higher PRS313.

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

BackgroundProtein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain.MethodsWe analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated.ResultsThe most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47–2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set.ConclusionsThese results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.

Mendelian randomization analyses of 23 known and suspected risk factors and biomarkers for breast cancer overall and by molecular subtypes.

Many risk factors have been identified for breast cancer. The potential causality for some of them remains uncertain, and few studies have comprehensively investigated these associations by molecular subtypes. We performed a two-sample Mendelian randomization (MR) study to evaluate potential causal associations of 23 known and suspected risk factors and biomarkers with breast cancer risk overall and by molecular subtypes using data from the Breast Cancer Association Consortium. The inverse-variance weighted method was used to estimate odds ratios (OR) and 95% confidence interval (CI) for association of each trait with breast cancer risk. Significant associations with breast cancer risk were found for 15 traits, including age at menarche, age at menopause, body mass index, waist-to-hip ratio, height, physical activity, cigarette smoking, sleep duration, and morning-preference chronotype, and six blood biomarkers (estrogens, insulin-like growth factor-1, sex hormone-binding globulin [SHBG], telomere length, HDL-cholesterol and fasting insulin). Noticeably, an increased circulating SHBG was associated with a reduced risk of estrogen receptor (ER)-positive cancer (OR=0.83, 95% CI: 0.73-0.94), but an elevated risk of ER-negative (OR=1.12, 95% CI: 0.93-1.36) and triple negative cancer (OR=1.19, 95% CI: 0.92-1.54) (Pheterogeneity =0.01). Fasting insulin was most strongly associated with an increased risk of HER2-negative cancer (OR=1.94, 95% CI: 1.18-3.20), but a reduced risk of HER2-enriched cancer (OR=0.46, 95% CI: 0.26-0.81) (Pheterogeneity =0.006). Results from sensitivity analyses using MR-Egger and MR-PRESSO were generally consistent. Our study provides strong evidence supporting potential causal associations of several risk factors for breast cancer and suggests potential heterogeneous associations of SHBG and fasting insulin levels with subtypes of breast cancer.

A genome-wide gene-based gene-environment interaction study of breast cancer in more than 90,000 women.

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.

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The number of new cancer diagnoses dropped by 13% to 23%, which the authors say necessitates a recovery plan to ensure that health centers can catch up with the backlog and meet the needs of patients whose healthcare access was disrupted.Englum BR… Lal BK. Cancer. 2022 Mar 1;128(5):1048-1056.

Effects of glutamate and aspartate on prostate cancer and breast cancer: a Mendelian randomization study

BackgroundRespectively, prostate cancer (PCa) and breast cancer (BC) are the second most and most commonly diagnosed cancer in men and women, and they account for a majority of cancer-related deaths world-wide. Cancer cells typically exhibit much-facilitated growth that necessitates upregulated glycolysis and augmented amino acid metabolism, that of glutamine and aspartate in particular, which is tightly coupled with an increased flux of the tricarboxylic acid (TCA) cycle. Epidemiological studies have exploited metabolomics to explore the etiology and found potentially effective biomarkers for early detection or progression of prostate and breast cancers. However, large randomized controlled trials (RCTs) to establish causal associations between amino acid metabolism and prostate and breast cancers have not been reported.ObjectiveUtilizing two-sample Mendelian randomization (MR), we aimed to estimate how genetically predicted glutamate and aspartate levels could impact upon prostate and breast cancers development.MethodsSingle nucleotide polymorphisms (SNPs) as instrumental variables (IVs), associated with the serum levels of glutamate and aspartate were extracted from the publicly available genome-wide association studies (GWASs), which were conducted to associate genetic variations with blood metabolite levels using comprehensive metabolite profiling in 1,960 adults; and the glutamate and aspartate we have chosen were two of 644 metabolites. The summary statistics for the largest and latest GWAS datasets for prostate cancer (61,106 controls and 79,148 cases) were from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium, and datasets for breast cancer (113,789 controls and 133,384 cases) were from Breast Cancer Association Consortium (BCAC). The study was performed through two-sample MR method.ResultsCausal estimates were expressed as odds ratios (OR) and 95% confidence interval (CI) per standard deviation increment in serum level of aspartate or glutamate. Aspartate was positively associated with prostate cancer (Effect = 1.043; 95% confidence interval, 1.003 to 1.084; P = 0.034) and breast cancer (Effect = 1.033; 95% confidence interval, 1.004 to 1.063; P = 0.028); however, glutamate was neither associated with prostate cancer nor with breast cancer. The potential causal associations were robust to the sensitivity analysis.ConclusionsOur study found that the level of serum aspartate could serve as a risk factor that contributed to the development of prostate and breast cancers. Efforts on a detailed description of the underlying biochemical mechanisms would be extremely valuable in early assessment and/or diagnosis, and strategizing clinical intervention, of both cancers.

Abstract P3-07-02: Identification of potential germline variants (GV) on tumor comprehensive genomic profiling (CGP) in patients with advanced breast cancer (BC): BRCA1/2 and beyond

Abstract Background Detection of pathogenic GVs in patients with BC has implications for both patients and their family members. Management options such as increased surveillance, chemoprevention, and surgical prophylaxis are available to GV carriers. Beyond BRCA1/2, GVs in the cancer susceptibility genes (CSGs) PALB2, ATM, and CHEK2 confer a 2-11-fold lifetime risk of BC. One opportunity CGP assays present is the potential to detect clinically-relevant GVs in addition to targetable somatic variants. While the Breast Cancer Association Consortium found that 5.2% of women with BC carried a GV in one of these five CSGs, we sought to describe the frequency of these potential GVs detected by CGP in a cohort of patients with advanced disease. Methods We reviewed an internal database of patients with advanced BC who underwent testing with a CGP panel using tissue (n= 20,109, FoundationOne® CDx) or plasma (n= 4,182, FoundationOne®Liquid CDx or FoundationOne®Liquid). Cases with a potential GV were identified by filtering base substitutions and short indels for inclusion in ClinVar as pathogenic or likely pathogenic and by variant allele frequency (VAF) based on an optimized assay-specific threshold, focusing on the select CSGs of BRCA1/2, PALB2, ATM and CHEK2. To enable follow-up of potential GVs, we implemented a new reporting “banner” to highlight select short variants in these CSGs. Predominant patient ancestry was inferred using a SNP-based classifier and Fisher’s exact test was utilized for comparison between groups. Results A total of 24,291 unique patients with primarily advanced BC had CGP results available for study, with common actionable findings including PIK3CA mutations (8,572, 35.3%), ESR1 mutations (3,289, 13.5%), and HER2 amplification (1,602, 6.6%). Focusing on the 5 CSGs, 16.4% of patients (3,986) had at least one pathogenic alteration detected in BRCA2 (1,153, 4.7%), ATM (969, 4.0%), CHEK2 (982, 4.0%) BRCA1 (849, 3.5%) or PALB2 (308, 1.3%); 1.1% of patients (263) harbored alterations in multiple CSGs. 50.7% (2,020/3,986) of patients with pathogenic alterations in these CSGs - 8.3% (2,020/24,291) of total patients with advanced BC - had an alteration meeting criterion as a potential GV. Variants in BRCA1 (511/919, 55.6%), BRCA2 (786/1,425, 55.2%), and PALB2 (201/376, 53.5%), more frequently met criteria as potential GVs than variants in CHEK2 (328/1,046, 31.4%) or ATM (265/1,100, 24.1%). In these five CSGs, 1,796/3,195 alterations detected on tissue CGP (56.2%) and 295/1,671 detected in plasma (17.7%) met criteria as a potential GVs. Ancestry analysis of 20,108 assessable BC patients tested using tissue CGP showed potential GVs in CHEK2 were more common in European vs non-European (1.7% vs 0.4%, p&amp;lt;0.01) and potential GVs in PALB2 were more common in African vs non-African (1.4% vs 0.7%, p&amp;lt;0.01) ancestries. Of 1,961 patients with BC tested over a 2-month period, 9.7% of reports (191) included a germline banner reporting a potential GV in one of these 5 CSGs and recommending consideration of referral for germline testing. Conclusion Potential pathogenic GVs in BRCA1/2, PALB2, ATM and CHEK2 were identified in 8.3% of patients with advanced BC tested utilizing CGP when filtering by VAF and ClinVar annotation. Highlighting these potential GVs with a report banner provides the opportunity for follow-up germline testing and genetic counseling for patients who otherwise may not have been referred for additional testing. These alterations were detected in both tissue and plasma CGP and in patients of varying ancestries. The potential for detection of potential GVs plus the detection of actionable driver and resistance mechanisms may add to the clinical value of CGP for patients with breast cancer. Citation Format: Marni B Tierno, Kali C Dougherty, Erica Gornstein, Dean C Pavlick, Alexa Schrock, Geoff R Oxnard. Identification of potential germline variants (GV) on tumor comprehensive genomic profiling (CGP) in patients with advanced breast cancer (BC): BRCA1/2 and beyond [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 P3-07-02.

Associations of genetically proxied inhibition of HMG-CoA reductase, NPC1L1, and PCSK9 with breast cancer and prostate cancer

BackgroundPreclinical and epidemiological studies indicate a potential chemopreventive role of low-density lipoprotein cholesterol (LDL-C) -lowering drugs in the risks of breast cancer and prostate cancer, but the causality remains unclear. We aimed to evaluate the association of genetically proxied inhibition of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, Niemann-Pick C1-Like 1 (NPC1L1), and proprotein convertase subtilisin/kexin type 9 (PCSK9) with risks of breast cancer and prostate cancer using a two-sample Mendelian randomization (MR) method.MethodsSingle-nucleotide polymorphisms (SNPs) in HMGCR, NPC1L1, and PCSK9 associated with LDL-C in a genome-wide association study (GWAS) meta-analysis from the Global Lipids Genetics Consortium (GLGC; up to 188,577 European individuals) were used to proxy inhibition of HMG-CoA reductase, NPC1L1, and PCSK9. Summary statistics with outcomes were obtained from a GWAS meta-analysis of the Breast Cancer Association Consortium (BCAC; 228,951 European females) and a Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL; 140,254 European males) consortium. SNPs were combined into multiallelic models and MR estimates representing lifelong inhibition of targets were generated using the inverse-variance weighted method.ResultsGenetically proxied inhibition of HMG-CoA reductase (OR: 0.84; 95% CI 0.74–0.95; P = 0.005) and NPC1L1 (OR: 0.72; 95% CI 0.58–0.90; P = 0.005) equivalent to a 1-mmol/L (38.7 mg/dL) reduction in LDL-C was associated with reduced breast cancer risk. There were no significant associations of genetically proxied inhibition of PCSK9 with breast cancer. In contrast, genetically proxied inhibition of PCSK9 (OR: 0.81; 95% CI 0.73–0.90; P < 0.001) but not HMG-CoA reductase and NPC1L1 was negatively associated with prostate cancer. In the secondary analysis, genetically proxied inhibition of HMG-CoA reductase (OR: 0.82; 95% CI 0.71–0.95; P = 0.008) and NPC1L1 (OR: 0.66; 95% CI 0.50–0.86; P = 0.002) was associated with estrogen receptor-positive breast cancer, whereas there was no association of HMG-CoA reductase and NPC1L1 with estrogen receptor-negative breast cancer.ConclusionsGenetically proxied inhibition of HMG-CoA reductase and NPC1L1 was significantly associated with lower odds of breast cancer, while genetically proxied inhibition of PCSK9 was associated with reduced risk of prostate cancer. Further randomized controlled trials are needed to confirm the respective roles of these LDL-C-lowering drugs in breast cancer and prostate cancer.