Lissowska, Jolanta

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.

Abstract Purpose: Chemotherapy resistance remains a major challenge in the treatment of ovarian cancer. We hypothesize that germline polymorphisms might be associated with clinical outcome. Experimental Design: We analyzed approximately 2.8 million genotyped and imputed SNPs from the iCOGS experiment for progression-free survival (PFS) and overall survival (OS) in 2,901 European epithelial ovarian cancer (EOC) patients who underwent first-line treatment of cytoreductive surgery and chemotherapy regardless of regimen, and in a subset of 1,098 patients treated with ≥4 cycles of paclitaxel and carboplatin at standard doses. We evaluated the top SNPs in 4,434 EOC patients, including patients from The Cancer Genome Atlas. In addition, we conducted pathway analysis of all intragenic SNPs and tested their association with PFS and OS using gene set enrichment analysis. Results: Five SNPs were significantly associated (P ≤ 1.0 × 10−5) with poorer outcomes in at least one of the four analyses, three of which, rs4910232 (11p15.3), rs2549714 (16q23), and rs6674079 (1q22), were located in long noncoding RNAs (lncRNAs) RP11-179A10.1, RP11-314O13.1, and RP11-284F21.8, respectively (P ≤ 7.1 × 10−6). ENCODE ChIP-seq data at 1q22 for normal ovary show evidence of histone modification around RP11-284F21.8, and rs6674079 is perfectly correlated with another SNP within the super-enhancer MEF2D, expression levels of which were reportedly associated with prognosis in another solid tumor. YAP1- and WWTR1 (TAZ)-stimulated gene expression and high-density lipoprotein (HDL)-mediated lipid transport pathways were associated with PFS and OS, respectively, in the cohort who had standard chemotherapy (pGSEA ≤6 × 10−3). Conclusions: We have identified SNPs in three lncRNAs that might be important targets for novel EOC therapies. Clin Cancer Res; 21(23); 5264–76. ©2015 AACR.

Abstract Background: Nulliparity is an established endometrial cancer risk factor, but whether this association is related to infertility is unclear. Although there are many underlying causes of infertility, few studies have assessed risk relationships according to specific causes. Despite concerns that most treatments induce ovulation and that the endometrium is highly hormonally-responsive, previous studies have provided conflicting results on treatment associations. Methods: To address these issues, we conducted a pooled analysis of 8,151 cases and12,471 controls from 2 cohort and 12 case-control studies conducted in 1982 to 2009 (N. America, Europe, Australia, Asia). All studies provided self-reported infertility, causes and treatments, except for 1 study that relied on data from national registries. Study-specific exposures and covariate data were harmonized across studies. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI), adjusted for study, age, interview year, race, parity, oral contraceptive and menopausal hormone use, and body mass index. If data were not reported for a particular variable, that study was excluded from the variable-specific analysis. Results: Nulliparous women had an elevated endometrial cancer risk compared with parous women (adjusted OR=1.73; 95% CI: 1.58-1.90).Women with self-reported infertility also had an increased risk (adjusted OR=1.22; 95% CI: 1.13-1.32) compared with those without infertility issues, even after adjusting for parity; the strongest associations was seen among studies that defined infertility as unsuccessfully trying to conceive for 2+ years (adjusted OR=1.31; 95% CI: 1.07-1.60). Infertility was associated with similar risks among nulliparous (1.22; 1.10-1.48) and parous (1.22; 1.12-1.34) women, although there was no increased risk associated with infertility among those who had given birth to 3+ children. Two infertility causes associated with risk elevation were endometriosis (adjusted OR=2.08; 95% CI: 1.46-2.95 compared with women no infertility problems) and anovulation (adjusted OR=1.40; 95% CI: 1.16-1.70). Based on relatively small numbers, none of the individual treatments (in vitro fertilization, selective estrogen response modulators, gonatropins, progestins, estrogens) were substantially related to risk. Conclusion: Based on mainly self-reported infertility data, we found that parity and infertility independently contribute to endometrial cancer risk, with parity seemingly being the predominant risk predictor. Understanding residual endometrial cancer relationships related to causes of infertility and infertility treatment may benefit from documented medical information on causes of infertility and treatment parameters. Citation Format: Hannah P. Yang, Linda S. Cook, Elisabete Weiderpass, Hans-Olov Adami, Kristin E. Anderson, Hui Cai, James R. Cerhan, Tess Clendenen, Ashley S. Felix, Christine Friedenreich, Montserrat Garcia-Closas, Marc T. Goodman, Xiaolin Liang, Jolanta Lissowska, Lingeng Lu, Anthony M. Magliocco, Susan E. McCann, Kristen B. Moysich, Sara H. Olson, Malcolm C. Pike, Silvia Polidoro, Fulvio Ricceri, Harvey Risch, Carlotta Sacerdote, V. Wendy Setiawan, Xiao Ou Shu, Amanda B. Spurdle, Britton Trabert, Penelope M. Webb, Nicolas Wentzensen, Yong-Bing Xiang, Youming Xu, Herbert Yu, Anne Zeleniuch-Jacquotte, Louise A. Brinton. Infertility and risk of incident endometrial carcinoma: a pooled analysis from the Epidemiology of Endometrial Cancer Consortium. [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 2167. doi:10.1158/1538-7445.AM2014-2167

AbstractBreast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results.

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes‐type shrinkage estimator. Six SNPs showed interactions with associated p ‐values ( p int ) <1.1 × 10 −3 . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER‐negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER‐negative BC risk in women <160 cm (OR = 0.83, p = 0.039, p int = 1.9 × 10 −4 ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10 −4 ), and absent in women who had had just one (OR = 0.96, p = 0.19, p int = 6.1 × 10 −4 ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10 −5 ), but no association was observed in current smokers (OR = 1.07, p = 0.14, p int = 3.4 × 10 −4 ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies.