Yang, Hannah

Abstract Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two‐sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low‐density lipoprotein [LDL] and high‐density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels ( P < 5 × 10 −8 ) were identified as instrumental variables, and assessed using genome‐wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non‐endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non‐endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non‐endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non‐endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.

Abstract Black women in the United States are disproportionately affected by early-onset, triple-negative breast cancer. DNA methylation has shown differences by race in healthy and tumor breast tissues. We examined associations between genome-wide DNA methylation levels in breast milk and breast cancer risk factors, including race, to explain how this reproductive stage influences a woman's risk for, and potentially contributes to racial disparities in, breast cancer. Breast milk samples and demographic, behavioral, and reproductive data, were obtained from cancer-free, uniparous, and lactating U.S. black (n = 57) and white (n = 82) women, ages 19–44. Genome-wide DNA methylation analysis was performed on extracted breast milk DNA using the Infinium HumanMethylation450 BeadChip. Statistically significant associations between breast cancer risk factors and DNA methylation beta values, adjusting for potential confounders, were determined using linear regression followed by Bonferroni Correction (P &lt; 1.63 × 10−7). Epigenetic analysis in breast milk revealed statistically significant associations with race and lactation duration. Of the 284 CpG sites associated with race, 242 were hypermethylated in black women. All 227 CpG sites associated with lactation duration were hypomethylated in women who lactated longer. Ingenuity Pathway Analysis of differentially methylated promoter region CpGs by race and lactation duration revealed enrichment for networks implicated in carcinogenesis. Associations between DNA methylation and lactation duration may offer insight on its role in lowering breast cancer risk. Epigenetic associations with race may mediate social, behavioral, or other factors related to breast cancer and may provide insight into potential mechanisms underlying racial disparities in breast cancer incidence.

Abstract Background: Many epithelial ovarian cancer (EOC) risk factors relate to hormone exposure and elevated estrogen levels are associated with obesity in postmenopausal women. Therefore, we hypothesized that gene–environment interactions related to hormone-related risk factors could differ between obese and non-obese women. Methods: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy, and estrogen use) and assessed whether these interactions differed between obese and non-obese women. Interactions were assessed using logistic regression models and data from 14 case–control studies (6,247 cases; 10,379 controls). Histotype-specific analyses were also completed. Results: SNPs in the following candidate genes showed notable interaction: IGF1R (rs41497346, estrogen plus progesterone hormone therapy, histology = all, P = 4.9 × 10−6) and ESR1 (rs12661437, endometriosis, histology = all, P = 1.5 × 10−5). The most notable obesity–gene–hormone risk factor interaction was within INSR (rs113759408, parity, histology = endometrioid, P = 8.8 × 10−6). Conclusions: We have demonstrated the feasibility of assessing multifactor interactions in large genetic epidemiology studies. Follow-up studies are necessary to assess the robustness of our findings for ESR1, CYP11A1, IGF1R, CYP11B1, INSR, and IGFBP2. Future work is needed to develop powerful statistical methods able to detect these complex interactions. Impact: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC susceptibility. Cancer Epidemiol Biomarkers Prev; 25(5); 780–90. ©2016 AACR.

Abstract Background: While numerous susceptibility loci for epithelial ovarian cancer (EOC) have been identified, few associations have been reported with overall survival. In the absence of common prognostic genetic markers, we hypothesize that rare coding variants may be associated with overall EOC survival and assessed their contribution in two exome-based genotyping projects of the Ovarian Cancer Association Consortium (OCAC). Methods: The primary patient set (Set 1) included 14 independent EOC studies (4,293 patients) and 227,892 variants, and a secondary patient set (Set 2) included six additional EOC studies (1,744 patients) and 114,620 variants. Because power to detect rare variants individually is reduced, gene-level tests were conducted. Sets were analyzed separately at individual variants and by gene, and then combined with meta-analyses (73,203 variants and 13,163 genes overlapped). Results: No individual variant reached genome-wide statistical significance. A SNP previously implicated to be associated with EOC risk and, to a lesser extent, survival, rs8170, showed the strongest evidence of association with survival and similar effect size estimates across sets (Pmeta = 1.1E−6, HRSet1 = 1.17, HRSet2 = 1.14). Rare variants in ATG2B, an autophagy gene important for apoptosis, were significantly associated with survival after multiple testing correction (Pmeta = 1.1E−6; Pcorrected = 0.01). Conclusions: Common variant rs8170 and rare variants in ATG2B may be associated with EOC overall survival, although further study is needed. Impact: This study represents the first exome-wide association study of EOC survival to include rare variant analyses, and suggests that complementary single variant and gene-level analyses in large studies are needed to identify rare variants that warrant follow-up study. Cancer Epidemiol Biomarkers Prev; 25(3); 446–54. ©2016 AACR.

ABSTRACTEpithelial‐mesenchymal transition (EMT) is a process whereby epithelial cells assume mesenchymal characteristics to facilitate cancer metastasis. However, EMT also contributes to the initiation and development of primary tumors. Prior studies that explored the hypothesis that EMT gene variants contribute to epithelial ovarian carcinoma (EOC) risk have been based on small sample sizes and none have sought replication in an independent population. We screened 15,816 single‐nucleotide polymorphisms (SNPs) in 296 genes in a discovery phase using data from a genome‐wide association study of EOC among women of European ancestry (1,947 cases and 2,009 controls) and identified 793 variants in 278 EMT‐related genes that were nominally (P < 0.05) associated with invasive EOC. These SNPs were then genotyped in a larger study of 14,525 invasive‐cancer patients and 23,447 controls. A P‐value <0.05 and a false discovery rate (FDR) <0.2 were considered statistically significant. In the larger dataset, GPC6/GPC5 rs17702471 was associated with the endometrioid subtype among Caucasians (odds ratio (OR) = 1.16, 95% CI = 1.07–1.25, P = 0.0003, FDR = 0.19), whereas F8 rs7053448 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), F8 rs7058826 (OR = 1.69, 95% CI = 1.27–2.24, P = 0.0003, FDR = 0.12), and CAPN13 rs1983383 (OR = 0.79, 95% CI = 0.69–0.90, P = 0.0005, FDR = 0.12) were associated with combined invasive EOC among Asians. In silico functional analyses revealed that GPC6/GPC5 rs17702471 coincided with DNA regulatory elements. These results suggest that EMT gene variants do not appear to play a significant role in the susceptibility to EOC.

Abstract Introduction: Increased levels of circulating estrogens are associated with elevated risks of postmenopausal breast cancer. Previously, we showed that levels of sex steroid hormones in breast adipose tissue are positively correlated with circulating hormones. Further evaluation of hormone levels in breast tissues may help to explain the relationship between estrogens and breast cancer risk. Specifically, data suggest that focal breast lesions consisting of macrophages encircling dying adipocytes, referred to as “crown-like structures (CLS)”, are associated with increased aromatase activity, which could increase conversion of androgens to estrogens locally in the breast. Therefore, we assessed whether the presence of CLS affects the correlations between blood and breast adipose tissue hormone levels. Methods: Participants included 84 postmenopausal women with invasive breast cancer in the Polish Breast Cancer Study, a population based case-control study conducted from 2000 to 2003. We previously reported sex steroid hormone levels in cancer-free breast adipose tissue removed as part of breast excisions performed for cancer. Here, using immunohistochemical stains, we evaluated the number of CD68 positive macrophages and the presence of full CLS (i.e., complete adipocyte encirclement) in benign breast tissue sections prepared from surgical pathology specimens containing breast cancer. The relationship between the number of CD68 positive macrophages per unit area of fat and hormone levels was examined using Spearman rank correlations (rs). We assessed potential effect modification of the association between blood and tissue hormone levels by presence or absence of CLS by including an interaction term in linear regression models. Results: The number of CD68 positive macrophages per unit area of fat was not significantly correlated with levels of estrone, estradiol, androstenedione or testosterone measured in blood (rs = 0.001, -0.04, -0.07, and -0.09, respectively; p&gt;0.05) or breast adipose tissue (rs = -0.15, 0.06, -0.06, and -0.08, respectively; p&gt;0.05). Correlations between serum and adipose tissue hormones did not statistically significantly differ between women with CLS (n = 30) compared to those without CLS (n = 54). CLS were found more frequently in breast adipose tissue from overweight (i.e., women with a body mass index (BMI) between 25 and 29.9) (43%) and obese women (BMI &gt;30) (30%) versus normal weight women, with (BMI between 18.5 and 24.9), (27%); (p = 0.04, χ2 test). The number of CD68 positive macrophages per unit area of fat was not significantly related to BMI (p = 0.31). Conclusion: Among postmenopausal women with invasive breast cancer, the presence of CLS was more common among overweight and obese women, but CLS did not influence the correlation between circulating and breast adipose tissue sex steroid hormone levels. Citation Format: Maeve Mullooly, Hannah P. Yang, Roni T. Falk, Sarah Nyante, Renata Cora, Ruth M. Pfeiffer, Derek C. Radisky, Daniel W. Visscher, Lynn C. Hartmann, Amy C. Degnim, Frank Z. Stanczyk, Jonine F. Figueroa, Montserrat Garcia-Closas, Jolanta Lissowska, Melissa T. Troester, Louise A. Brinton, Mark E. Sherman, Gretchen L. Gierach. Investigation of the relationship between crown-like structures and adipose tissue hormone levels among postmenopausal women with breast cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2767. doi:10.1158/1538-7445.AM2015-2767

Abstract Background: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. Methods: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P &lt; 0.05 and FDR &lt; 0.05). These results were replicated (P &lt; 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. Cancer Epidemiol Biomarkers Prev; 24(10); 1574–84. ©2015 AACR.