Seokang Chung

Prediction of Breast Cancer Survival Using Clinical and Genetic Markers by Tumor Subtypes

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 (P rs166870=2.88×10-7 and P rs10825036=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.

Tumor Subtype-Specific Associations of Hormone-Related Reproductive Factors on Breast Cancer Survival

Purpose 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. Methods 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. Results 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 (<5 vs. ≥20 years, HR for DFS=1.67, 95% CI=1.07-2.62) were associated with worse survival while longer duration of estrogen exposure with better survival (HR for DFS=0.97, 95% CI=0.96-0.99). In the stratified analyses by subtypes, those associations were more pronounced among women with hormone receptor and human epidermal growth factor 2 positive (HR+ HER2+) tumors. Conclusions It is suggested that reproductive factors, specifically age at menarche, number of children, time since last birth, and duration of estrogen exposure, could influence breast tumor progression, especially in the HR+ HER2+ subtype.

Heterogeneity of epidemiological factors by breast tumor subtypes in Korean women: A case-case study

Breast cancer is heterogeneous in clinical behavior by subtypes; however, it is unclear how this heterogeneity is related to epidemiological factors. To evaluate the differences in epidemiological factors by breast tumor subtypes, we investigated the associations of epidemiological factors between tumor subtypes in Korean women. From the Seoul Breast Cancer Study, a total of 3,058 patients with breast cancer were included in the analyses. Tumor subtypes were classified based on hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) statuses. The epidemiological factors of each subtype were compared through case–case analyses using multivariate a polytomous logistic regression model adjusted for age and recruiting centers. The distribution of the subtypes was as follows: 1,714 HR+ HER2− (56.0%), 414 HR+ HER2+ (13.5%), 423 HR− HER2+ (13.9%) and 507 HR− HER2− (16.6%) patients with breast cancer. There were significant differences in age, menopausal status, age at menarche, number of children, age at first full‐term pregnancy (FFTP), duration of breastfeeding and duration of endogenous estrogen exposure between tumor subtypes (p < 0.05). Compared to HR+ HER2− patients, the other subtype patients showed more frequency in having more numbers of children and less frequency in having earlier menarche, later FFTP and longer endogenous estrogen exposure. Although HR− HER2+ patients were less obese, HR− HER2− patients were younger and more obese. In conclusion, age, body mass index and reproductive factors were differentially associated with breast tumor subtypes suggesting a possible distinct etiology for tumor progression.

The associations between immunity-related genes and breast cancer prognosis in Korean women.

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<0.1). The IL-6R, IL-8, IL-10RB, IL-12A, and IL-12B was associated with the prognosis of cancer in data of both our study and a previous study. Therefore, our results suggest that genetic polymorphisms in immune-related genes have relevance to breast cancer prognosis among Korean women.

Genetic Predisposition of Polymorphisms in HMGB1-Related Genes to Breast Cancer Prognosis in Korean Women

Purpose The high mobility group box 1 (HMGB1) protein has roles in apoptosis and immune responses by acting as a ligand for receptor for advanced glycation end products (RAGE), Toll-like receptors (TLRs), and triggering receptor expressed on myeloid cells 1. In particular, HMGB1/RAGE is involved in tumor metastasis by inducing matrix metalloproteinase 2 (MMP2) and MMP9 expression. We investigated the associations between genetic variations in HMGB1-related genes and disease-free survival (DFS) and overall survival (OS) in Korean female breast cancer patients. Methods A total of 2,027 patients in the Seoul Breast Cancer Study were included in the analysis. One hundred sixteen single nucleotide polymorphisms (SNPs) were extracted from eight genes. A multivariate Cox proportional hazards model was used to estimate the hazard ratio and 95% confidence interval (CI) of each SNP. The effects of the SNPs on breast cancer prognosis were assessed at cumulative levels with polygenic risk scores. Results The SNPs significantly associated with DFS were rs243867 (hazard ratio, 1.26; 95% CI, 1.05–1.50) and rs243842 (hazard ratio, 1.24; 95% CI, 1.03–1.50); both SNPs were in MMP2. The SNPs significantly associated with OS were rs243842 in MMP2 (hazard ratio, 1.33; 95% CI 1.03–1.71), rs4145277 in HMGB1 (hazard ratio, 1.29; 95% CI, 1.00–1.66), rs7656411 in TLR2 (hazard ratio, 0.76; 95% CI, 0.60–0.98), and rs7045953 in TLR4 (hazard ratio, 0.50; 95% CI, 0.29–0.84). The polygenic risk score results for the DFS and OS patients showed third tertile hazard ratios of 1.72 (95% CI, 1.27–2.34) and 2.75 (95% CI, 1.79–4.23), respectively, over their first tertile references. Conclusion The results of the present study indicate that genetic polymorphisms in HMGB1-related genes are related to breast cancer prognosis in Korean women.

Associations between genetic polymorphisms of membrane transporter genes and prognosis after chemotherapy: meta-analysis and finding from Seoul Breast Cancer Study (SEBCS)

Membrane transporters can be major determinants of the pharmacokinetic profiles of anticancer drugs. The associations between genetic variations of ATP-binding cassette (ABC) and solute carrier (SLC) genes and cancer survival were investigated through a meta-analysis and an association study in the Seoul Breast Cancer Study (SEBCS). Including the SEBCS, the meta-analysis was conducted among 38 studies of genetic variations of transporters on various cancer survivors. The population of SEBCS consisted of 1338 breast cancer patients who had been treated with adjuvant chemotherapy. A total of 7750 SNPs were selected from 453 ABC and/or SLC genes typed by an Affymetrix 6.0 chip. ABCB1 rs1045642 was associated with poor progression-free survival in a meta-analysis (HR = 1.33, 95% CI: 1.07–1.64). ABCB1, SLC8A1, and SLC12A8 were associated with breast cancer survival in SEBCS (Pgene < 0.05). ABCB1 rs1202172 was differentially associated with survival depending on the chemotherapy (Pinteraction = 0.035). Our finding provides suggestive associations of membrane transporters on cancer survival.

Correction to: Age at menarche and age at natural menopause in East Asian women: a genome-wide association study

The original version of this article unfortunately contained a mistake.

Abstract 1276: Gene-environment interaction relevant to estrogen and risk of breast cancer

Introduction: Many established reproductive risk factors for breast cancer are mediated by hormonal mechanisms, and most parts are involved in estrogens. In addition, the estrogen level controlled by genetic factors might be a sort of determinants to breast cancer risk involving estrogen metabolism. This study aims to examine gene and environment interaction (GxE) between candidate genes which are involved in estrogen metabolism and environmental factors which are related to estrogen exposure. Methods: GxE analyses were conducted in the Korean 1,970 breast cancer cases and 2,052 controls which were recruited in the Seoul Breast Cancer Study (SEBCS), a multicenter case control study. 137 candidate genes involved in estrogen metabolism were searched from couple of databases and 11,555 SNPs (2,472 typed SNPs and 9,083 imputed SNPs) from the range of candidate genes were included in GxE analyses with 8 established environmental factors. Statistical analyses were performed by using GxEScan (ver. Beta 0.4.0; http://biostats.usc.edu/software) for GxE test. Results: There were three significant interaction between 11,555 SNPs and 8 environmental factors. Firstly, interaction rs851998 nearby ESR1 with height was shown in the GE|2df model (p-2df = 1.1x10 -4 ) This SNP had protective effect marginally (OR G = 0.82, 95% CI: 0.75-0.90) and further protective effect for women whose height is smaller than 160cm (OR G | height ≥ 160cm = 0.78, 95% CI: 0.70-0.87, p = 1.09x10 -5 ). Second interaction was shown between rs13035764 of NCOA1 and age at menarche in the GE|2df model (p-2df = 1.2x10 -3 ). This SNP also had protective effect marginally (OR G = 0.85, 95% CI: 0.77-0.97) and more protective effect when age at menarche is 14 years and over (OR G | age at menarche ≥ 14years = 0.82, 95% CI: 0.73-0.97, p=3.6x10 -4 ). Lastly, there was marginally significant interaction between rs4140979 of FSHR and age at first full term pregnancy (FFTP) in the EDGxE model. Although this SNP had no marginal effect, qualitative interaction was shown with FFTP (OR G | FFTP = 0.88, 95% CI: 0.78-1.00, p=0.0482; OR G | Nulliparity or FFTP ≥ 27 years = 1.30, 95% CI: 1.10-1.53, p=0.002). Conclusion: Three significant interactions were identified by focusing two step methods. Replication should be performed in the independent and larger population due to statistical limitation. Citation Format: JooYong Park, Ji-Yeob Choi, Seokang Chung, Nan Song, Sue K Park, Wonshik Han, Dong-Young Noh, Sei-Hyun Ahn, Mi-Kyung Kim, Keun-Young Yoo, Wei Zheng, Daehee Kang. Gene-environment interaction relevant to estrogen and risk of breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1276. doi:10.1158/1538-7445.AM2017-1276

Abstract 3273: Genetic variation in obesity-related genes and breast cancer risk in the Seoul Breast Cancer Study

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Many previous association studies have been addressed genetic variations in obesity related genes on breast cancer risk, however, limited consideration of genes and gene-environmental interaction was involved. We investigated the associations of known obesity-related genes on breast cancer risk by comprehensive assessment based on individual SNP analysis and gene-based pathway-analysis. This study was conducted in 1,786 cases and 1,789 controls from Seoul Breast Cancer Study (SEBCS), a multicenter case-control study. The selection of 1,561 candidate obesity-related gene for this study was involved based on GWAS catalog and previous published data associated with obesity. Associations of single-nucleotide polymorphism (SNP) with BMI were assessed by linear regression models under an additive genetic model adjusting for age and disease status to identify genetic loci for obesity. 2,366 BMI-related significant SNPs including additional significant 449 SNPs which independently associated with BMI in our data (p<10-4) were evaluated for the genetic effect on breast cancer risk. Per-allele odds ratio for breast cancer risk was assessed using logistic regression models adjusting for age and 1st family history of breast cancer. Gene-based pathway significance was assessed by the adaptive rank-truncated product (ARTP) method with 1,000 permutations for association between BMI-related genes and breast cancer risk. Among available 227,197 SNPs from candidate genes and additional significant SNPs in SEBCS data, 12,388 SNPs in 890 genes were found to be associated with BMI (p<0.05): 495 genes (55.7%) from GWAS catalog and 281 genes (48.4%) from published candidate genes for obesity were identified, respectively. Rs17804012 in RBFOX1 and rs2014791 in LINC00317 showed the most significant association with BMI (p<5E-6), which observed null association with breast cancer risk. In contrast, the gene-based pathway analysis including less significantly associated genes with BMI (N=644, p<0.05) showed significant association with breast cancer risk (the pathway p=0.003). Especially, the effect of THRB gene on breast cancer risk has highly significant value (p=9E-04) and the association was confined to premenopausal women with BMI above 23.2 (p<0.01). The group of BMI-related genes including THRB was significantly associated with breast cancer risk in pathway analysis and the associations were different depending on the menopausal status and/or BMI levels. Our results suggest that consideration of the complex genetic pathway related to environmental factors might reveal additional breast cancer susceptibility loci. Citation Format: Seokang Chung, Nan Song, Hyuna Sung, Sue K. Park, Wonshik Han, Dong-Young Noh, Sei-Hyun Ahn, Keun-Young Yoo, Daehee Kang, Ji-Yeob Choi. Genetic variation in obesity-related genes and breast cancer risk in the Seoul Breast Cancer Study. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3273. doi:10.1158/1538-7445.AM2014-3273