Inherited variants in the inner centromere protein (INCENP) gene of the chromosomal passenger complex contribute to the susceptibility of ER-negative breast cancer.

The chromosomal passenger complex (CPC) plays a pivotal role in the regulation of cell division. Therefore, inherited CPC variability could influence tumor development. The present candidate gene approach investigates the relationship between single nucleotide polymorphisms (SNPs) in genes encoding key CPC components and breast cancer risk. Fifteen SNPs in four CPC genes (INCENP, AURKB, BIRC5 and CDCA8) were genotyped in 88 911 European women from 39 case-control studies of the Breast Cancer Association Consortium. Possible associations were investigated in fixed-effects meta-analyses. The synonymous SNP rs1675126 in exon 7 of INCENP was associated with overall breast cancer risk [per A allele odds ratio (OR) 0.95, 95% confidence interval (CI) 0.92-0.98, P = 0.007] and particularly with estrogen receptor (ER)-negative breast tumors (per A allele OR 0.89, 95% CI 0.83-0.95, P = 0.0005). SNPs not directly genotyped were imputed based on 1000 Genomes. The SNPs rs1047739 in the 3' untranslated region and rs144045115 downstream of INCENP showed the strongest association signals for overall (per T allele OR 1.03, 95% CI 1.00-1.06, P = 0.0009) and ER-negative breast cancer risk (per A allele OR 1.06, 95% CI 1.02-1.10, P = 0.0002). Two genotyped SNPs in BIRC5 were associated with familial breast cancer risk (top SNP rs2071214: per G allele OR 1.12, 95% CI 1.04-1.21, P = 0.002). The data suggest that INCENP in the CPC pathway contributes to ER-negative breast cancer susceptibility in the European population. In spite of a modest contribution of CPC-inherited variants to the total burden of sporadic and familial breast cancer, their potential as novel targets for breast cancer treatment should be further investigated.

Height and Breast Cancer Risk: Evidence From Prospective Studies and Mendelian Randomization.

BACKGROUND: Epidemiological studies have linked adult height with breast cancer risk in women. However, the magnitude of the association, particularly by subtypes of breast cancer, has not been established. Furthermore, the mechanisms of the association remain unclear. METHODS: We performed a meta-analysis to investigate associations between height and breast cancer risk using data from 159 prospective cohorts totaling 5216302 women, including 113178 events. In a consortium with individual-level data from 46325 case patients and 42482 control patients, we conducted a Mendelian randomization analysis using a genetic score that comprised 168 height-associated variants as an instrument. This association was further evaluated in a second consortium using summary statistics data from 16003 case patients and 41335 control patients. RESULTS: The pooled relative risk of breast cancer was 1.17 (95% confidence interval [CI] = 1.15 to 1.19) per 10cm increase in height in the meta-analysis of prospective studies. In Mendelian randomization analysis, the odds ratio of breast cancer per 10cm increase in genetically predicted height was 1.22 (95% CI = 1.13 to 1.32) in the first consortium and 1.21 (95% CI = 1.05 to 1.39) in the second consortium. The association was found in both premenopausal and postmenopausal women but restricted to hormone receptor-positive breast cancer. Analyses of height-associated variants identified eight new loci associated with breast cancer risk after adjusting for multiple comparisons, including three loci at 1q21.2, DNAJC27, and CCDC91 at genome-wide significance level P < 5×10(-8). CONCLUSIONS: Our study provides strong evidence that adult height is a risk factor for breast cancer in women and certain genetic factors and biological pathways affecting adult height have an important role in the etiology of breast cancer.

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.

The SNP rs6500843 in 16p13.3 is associated with survival specifically among chemotherapy-treated breast cancer patients.

We have utilized a two-stage study design to search for SNPs associated with the survival of breast cancer patients treated with adjuvant chemotherapy. Our initial GWS data set consisted of 805 Finnish breast cancer cases (360 treated with adjuvant chemotherapy). The top 39 SNPs from this stage were analyzed in three independent data sets: iCOGS (n=6720 chemotherapy-treated cases), SUCCESS-A (n=3596), and POSH (n=518). Two SNPs were successfully validated: rs6500843 (any chemotherapy; per-allele HR 1.16, 95% C.I. 1.08-1.26, p=0.0001, p(adjusted)=0.0091), and rs11155012 (anthracycline therapy; per-allele HR 1.21, 95% C.I. 1.08-1.35, p=0.0010, p(adjusted)=0.0270). The SNP rs6500843 was found to specifically interact with adjuvant chemotherapy, independently of standard prognostic markers (p(interaction)=0.0009), with the rs6500843-GG genotype corresponding to the highest hazard among chemotherapy-treated cases (HR 1.47, 95% C.I. 1.20-1.80). Upon trans-eQTL analysis of public microarray data, the rs6500843 locus was found to associate with the expression of a group of genes involved in cell cycle control, notably AURKA, the expression of which also exhibited differential prognostic value between chemotherapy-treated and untreated cases in our analysis of microarray data. Based on previously published information, we propose that the eQTL genes may be connected to the rs6500843 locus via a RBFOX1-FOXM1 -mediated regulatory pathway.