Identification of Novel Genetic Markers of Breast Cancer Survival

Background: Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival. Methods: We conducted a large meta-analysis of studies in populations of European ancestry, including 37 954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200 000 and 900 000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23 059 ER-positive patients (1333 events). All statistical tests were two-sided. Results: We identified one new locus (rs2059614 at 11q24.2) associated with survival in ER-negative breast cancer cases (hazard ratio [HR] = 1.95, 95% confidence interval [CI] = 1.55 to 2.47, P = 1.91 x 10(-8)). Genotyping a subset of 2113 case patients, of which 300 were ER negative, provided supporting evidence for the quality of the imputation. The association in this set of case patients was stronger for the observed genotypes than for the imputed genotypes. A second locus (rs148760487 at 2q24.2) was associated at genome-wide statistical significance in initial analyses; the association was similar in ER-positive and ER-negative case patients. Here the results of genotyping suggested that the finding was less robust. Conclusions: This is currently the largest study investigating genetic variation associated with breast cancer survival. Our results have potential clinical implications, as they confirm that germline genotype can provide prognostic information in addition to standard tumor prognostic factors.Peer reviewe

PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS.

BackgroundThe 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.MethodsWe 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.ResultsFor 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.ConclusionsThis 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

A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46,450 cases and 42,461 controls from the breast cancer association consortium.

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome

Associations of common variants at 1p11.2 and 14q24.1 (RAD51L1) with breast cancer risk and heterogeneity by tumor subtype: findings from the Breast Cancer Association Consortium.

A genome-wide association study (GWAS) identified single-nucleotide polymorphisms (SNPs) at 1p11.2 and 14q24.1 (RAD51L1) as breast cancer susceptibility loci. The initial GWAS suggested stronger effects for both loci for estrogen receptor (ER)-positive tumors. Using data from the Breast Cancer Association Consortium (BCAC), we sought to determine whether risks differ by ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), grade, node status, tumor size, and ductal or lobular morphology. We genotyped rs11249433 at 1p.11.2, and two highly correlated SNPs rs999737 and rs10483813 (r(2)= 0.98) at 14q24.1 (RAD51L1), for up to 46 036 invasive breast cancer cases and 46 930 controls from 39 studies. Analyses by tumor characteristics focused on subjects reporting to be white women of European ancestry and were based on 25 458 cases, of which 87% had ER data. The SNP at 1p11.2 showed significantly stronger associations with ER-positive tumors [per-allele odds ratio (OR) for ER-positive tumors was 1.13, 95% CI = 1.10-1.16 and, for ER-negative tumors, OR was 1.03, 95% CI = 0.98-1.07, case-only P-heterogeneity = 7.6 × 10(-5)]. The association with ER-positive tumors was stronger for tumors of lower grade (case-only P= 6.7 × 10(-3)) and lobular histology (case-only P= 0.01). SNPs at 14q24.1 were associated with risk for most tumor subtypes evaluated, including triple-negative breast cancers, which has not been described previously. Our results underscore the need for large pooling efforts with tumor pathology data to help refine risk estimates for SNP associations with susceptibility to different subtypes of breast cancer

Body mass index and breast cancer survival:a Mendelian randomization analysis

Abstract Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival from breast cancer. Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER)-positive cases [hazard ratio (HR) = 1.11, per one-unit increment of GRS, 95% confidence interval (CI) 1.01–1.22, P = 0.03). We observed no association for ER-negative cases (HR = 1.00, per one-unit increment of GRS, 95% CI 0.89–1.13, P = 0.95). Conclusions: Our findings suggest a causal effect of increased BMI on reduced breast cancer survival for ER-positive breast cancer. There is no evidence of a causal effect of higher BMI on survival for ER-negative breast cancer cases