Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: a combined case-control study.

INTRODUCTION: Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium. METHODS: We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects. RESULTS: These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar. CONCLUSIONS: The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.

Family history of breast cancer and all-cause mortality after breast cancer diagnosis in the Breast Cancer Family Registry.

Although having a family history of breast cancer is a well established breast cancer risk factor, it is not known whether it influences mortality after breast cancer diagnosis. We studied 4,153 women with first primary incident invasive breast cancer diagnosed between 1991 and 2000, and enrolled in the Breast Cancer Family Registry through population-based sampling in Northern California, USA; Ontario, Canada; and Melbourne and Sydney, Australia. Cases were oversampled for younger age at diagnosis and/or family history of breast cancer. Carriers of germline mutations in BRCA1 or BRCA2 were excluded. Cases and their relatives completed structured questionnaires assessing breast cancer risk factors and family history of cancer. Cases were followed for a median of 6.5 years, during which 725 deaths occurred. Cox proportional hazards regression was used to evaluate associations between family history of breast cancer at the time of diagnosis and risk of all-cause mortality after breast cancer diagnosis, adjusting for established prognostic factors. The hazard ratios for all-cause mortality were 0.98 (95% confidence interval [CI] = 0.84-1.15) for having at least one first- or second-degree relative with breast cancer, and 0.85 (95% CI = 0.70-1.02) for having at least one first-degree relative with breast cancer, compared with having no such family history. Estimates did not vary appreciably when stratified by case or tumor characteristics. In conclusion, family history of breast cancer is not associated with all-cause mortality after breast cancer diagnosis for women without a known germline mutation in BRCA1 or BRCA2. Therefore, clinical management should not depend on family history of breast cancer.

Assessment of PD-L1 expression across breast cancer molecular subtypes, in relation to mutation rate, BRCA1-like status, tumor-infiltrating immune cells and survival.

To better understand the expression pattern of programmed death-ligand 1 (PD-L1) expression in different breast cancer types, we characterized PD-L1 expression in tumor and tumor-infiltrating immune cells, in relation to mutation rate, BRCA1-like status and survival. We analyzed 410 primary treatment-naive breast tumors comprising 162 estrogen receptor-positive (ER+) and HER2-, 101 HER2+ and 147 triple-negative (TN) cancers. Pathologists quantified tumor-infiltrating lymphocytes (TILs) and PD-L1 expression in tumor cells and TILs using whole slides and tissue microarray. Mutation rate was assessed by DNA sequencing, BRCA1-like status using multiplex ligation-dependent probe amplification, and immune landscape by multiplex image analyses of CD4, CD68, CD8, FOXP3, cytokeratin, and PD-L1. Half of PD-L1 scores evaluated by tissue microarray were false negatives compared to whole slide evaluations. We observed at least 1% of PD-L1-positive (PD-L1+) cells in 53.1% of ER+HER2-, 73.3% of HER2+, and 84.4% of TN tumors. PD-L1 expression was higher in ductal compared to lobular carcinomas, also within ER+HER2- tumors (p = 0.04). High PD-L1+ TILs score (> 50%) was independently associated with better outcome in TN tumors (HR = 0.27; 95%CI = 0.10-0.69). Within TN tumors, PD-L1 and TIL scores showed a modest but significant positive association with the number of silent mutations, but no association with BRCA1-like status. Multiplex image analyses indicated that PD-L1 is expressed on multiple immune cells (CD68+ macrophages, CD4+, FOXP3+, and CD8+ T cells) in the breast tumor microenvironment, independent of the PD-L1 status of the tumor cells. We found no evidence that levels of PD-L1+ TILs in TN breast cancer are driven by high mutation rate or BRCA1-like status.

Accuracy of Self-Reported Breast Cancer Information among Women from the Ontario Site of the Breast Cancer Family Registry.

Obtaining complete medical record information can be challenging and expensive in breast cancer studies. The current literature is limited with respect to the accuracy of self-report and factors that may influence this. We assessed the agreement between self-reported and medical record breast cancer information among women from the Ontario site of the Breast Cancer Family Registry. Women aged 20-69 years diagnosed with incident breast cancer 1996-1998 were identified from the Ontario Cancer Registry, sampled on age and family history. We calculated kappa statistics, proportion correct, sensitivity, specificity, and positive and negative predictive values and conducted unconditional logistic regression to examine whether characteristics of the women influenced agreement. The proportions of women who correctly reported having received a broad category of therapy (hormone therapy, chemotherapy, radiation, or surgery) as well as sensitivity and specificity were above 90%, and the kappa statistics were above 0.80. The specific type of hormonal or chemotherapy was reported with low-to-moderate agreement. Aside from recurrence, no factors were consistently associated with agreement. Thus, most women were able to accurately report broad categories of treatment but not necessarily specific treatment types. The finding of this study can aid researchers in the use and design of self-administered treatment questionnaires.

Associations of breast cancer risk factors with tumor subtypes: a pooled analysis from the Breast Cancer Association Consortium studies.

BACKGROUND: Previous studies have suggested that breast cancer risk factors are associated with estrogen receptor (ER) and progesterone receptor (PR) expression status of the tumors. METHODS: We pooled tumor marker and epidemiological risk factor data from 35,568 invasive breast cancer case patients from 34 studies participating in the Breast Cancer Association Consortium. Logistic regression models were used in case-case analyses to estimate associations between epidemiological risk factors and tumor subtypes, and case-control analyses to estimate associations between epidemiological risk factors and the risk of developing specific tumor subtypes in 12 population-based studies. All statistical tests were two-sided. RESULTS: In case-case analyses, of the epidemiological risk factors examined, early age at menarche (≤12 years) was less frequent in case patients with PR(-) than PR(+) tumors (P = .001). Nulliparity (P = 3 × 10(-6)) and increasing age at first birth (P = 2 × 10(-9)) were less frequent in ER(-) than in ER(+) tumors. Obesity (body mass index [BMI] ≥ 30 kg/m(2)) in younger women (≤50 years) was more frequent in ER(-)/PR(-) than in ER(+)/PR(+) tumors (P = 1 × 10(-7)), whereas obesity in older women (>50 years) was less frequent in PR(-) than in PR(+) tumors (P = 6 × 10(-4)). The triple-negative (ER(-)/PR(-)/HER2(-)) or core basal phenotype (CBP; triple-negative and cytokeratins [CK]5/6(+) and/or epidermal growth factor receptor [EGFR](+)) accounted for much of the heterogeneity in parity-related variables and BMI in younger women. Case-control analyses showed that nulliparity, increasing age at first birth, and obesity in younger women showed the expected associations with the risk of ER(+) or PR(+) tumors but not triple-negative (nulliparity vs parity, odds ratio [OR] = 0.94, 95% confidence interval [CI] = 0.75 to 1.19, P = .61; 5-year increase in age at first full-term birth, OR = 0.95, 95% CI = 0.86 to 1.05, P = .34; obesity in younger women, OR = 1.36, 95% CI = 0.95 to 1.94, P = .09) or CBP tumors. CONCLUSIONS: This study shows that reproductive factors and BMI are most clearly associated with hormone receptor-positive tumors and suggest that triple-negative or CBP tumors may have distinct etiology.