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PURPOSE:To identify the genetic variants associated with breast cancer survival, a genome-wide association study (GWAS) was conducted of Korean breast cancer patients. METHODS:From the Seoul Breast Cancer Study (SEBCS), 3,226 patients with breast cancer (1,732 in the discovery and 1,494 in the replication set) were included in a two-stage GWAS on disease-free survival (DFS) by tumor subtypes based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2). The associations of the re-classified combined prognostic markers through recursive partitioning analysis (RPA) of DFS for breast cancer were assessed with the Cox proportional hazard model. The prognostic predictive values of the clinical and genetic models were evaluated by Harrell's C. RESULTS:In the two-stage GWAS stratified by tumor subtypes, rs166870 and rs10825036 were consistently associated with DFS in the HR+ HER2- and HR- HER2- breast cancer subtypes, respectively (Prs166870 = 2.88 × 10(-7) and Prs10825036 = 3.54 × 10(-7) in the combined set). When patients were classified by the RPA in each subtype, genetic factors contributed significantly to differentiating the high risk group associated with DFS inbreast cancer, specifically the HR+ HER2- (P discovery=1.18 × 10(-8) and P replication = 2.08 × 10(-5)) and HR- HRE2- subtypes (P discovery = 2.35 × 10(-4) and P replication = 2.60 × 10(-2)). The inclusion of the SNPs tended to improve the performance of the prognostic models consisting of age, TNM stage and tumor subtypes based on ER, PR, and HER2 status. CONCLUSION:Combined prognostic markers that include clinical and genetic factors by tumor subtypes could improve the prediction of survival in breast cancer.

It is inconclusive whether reproductive factors, which are known as risk factors of breast cancer, also influence survival. We investigated overall and subtype-specific associations between reproductive factors and breast cancer survival.Among 3,430 incident breast cancer patients who enrolled in the Seoul Breast Cancer Study, 269 patients (7.8%) died and 528 patients (15.4%) recurred. The overall and subtype-specific associations of reproductive factors including age at menarche and menopause, duration of estrogen exposure, menstrual cycle, parity, age at first full-term pregnancy, number of children, age at last birth, time since the last birth, and duration of breastfeeding, on overall and disease-free survival (OS and DFS) were estimated by hazard ratios (HRs) and 95% confidence intervals (95% CIs) using a multivariate Cox proportional hazard model.An older age at menarche (HR for OS=1.10, 95% CI=1.03-1.19), a greater number of children (≥ 4 vs. 2, HR for DFS=1.58, 95% CI=1.11-2.26), and a shorter time since last birth (

We investigated the role of common genetic variation in immune-related genes on breast cancer disease-free survival (DFS) in Korean women. 107 breast cancer patients of the Seoul Breast Cancer Study (SEBCS) were selected for this study. A total of 2,432 tag single nucleotide polymorphisms (SNPs) in 283 immune-related genes were genotyped with the GoldenGate Oligonucleotide pool assay (OPA). A multivariate Cox-proportional hazard model and polygenic risk score model were used to estimate the effects of SNPs on breast cancer prognosis. Harrell's C index was calculated to estimate the predictive accuracy of polygenic risk score model. Subsequently, an extended gene set enrichment analysis (GSEA-SNP) was conducted to approximate the biological pathway. In addition, to confirm our results with current evidence, previous studies were systematically reviewed. Sixty-two SNPs were statistically significant at p-value less than 0.05. The most significant SNPs were rs1952438 in SOCS4 gene (hazard ratio (HR) = 11.99, 95% CI = 3.62-39.72, P = 4.84E-05), rs2289278 in TSLP gene (HR = 4.25, 95% CI = 2.10-8.62, P = 5.99E-05) and rs2074724 in HGF gene (HR = 4.63, 95% CI = 2.18-9.87, P = 7.04E-05). In the polygenic risk score model, the HR of women in the 3rd tertile was 6.78 (95% CI = 1.48-31.06) compared to patients in the 1st tertile of polygenic risk score. Harrell's C index was 0.813 with total patients and 0.924 in 4-fold cross validation. In the pathway analysis, 18 pathways were significantly associated with breast cancer prognosis (P