Citations

Abstract Prostate cancer is the second most common malignancy among men worldwide. Genome-wide association studies have identified 100 risk variants for prostate cancer, which can explain approximately 33% of the familial risk of the disease. We hypothesized that a comprehensive analysis of genetic variations found within the 3′ untranslated region of genes predicted to affect miRNA binding (miRSNP) can identify additional prostate cancer risk variants. We investigated the association between 2,169 miRSNPs and prostate cancer risk in a large-scale analysis of 22,301 cases and 22,320 controls of European ancestry from 23 participating studies. Twenty-two miRSNPs were associated (P < 2.3 × 10−5) with risk of prostate cancer, 10 of which were within 7 genes previously not mapped by GWAS studies. Further, using miRNA mimics and reporter gene assays, we showed that miR-3162-5p has specific affinity for the KLK3 rs1058205 miRSNP T-allele, whereas miR-370 has greater affinity for the VAMP8 rs1010 miRSNP A-allele, validating their functional role. Significance: Findings from this large association study suggest that a focus on miRSNPs, including functional evaluation, can identify candidate risk loci below currently accepted statistical levels of genome-wide significance. Studies of miRNAs and their interactions with SNPs could provide further insights into the mechanisms of prostate cancer risk. Cancer Discov; 5(4); 368–79. ©2015 AACR. See related commentary by Yousef, p. 351 This article is highlighted in the In This Issue feature, p. 333

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.

Abstract Purpose: To analyze the effect of germline mutations in BRCA1 and BRCA2 on mortality in patients with ovarian cancer up to 10 years after diagnosis. Experimental Design: We used unpublished survival time data for 2,242 patients from two case–control studies and extended survival time data for 4,314 patients from previously reported studies. All participants had been screened for deleterious germline mutations in BRCA1 and BRCA2. Survival time was analyzed for the combined data using Cox proportional hazard models with BRCA1 and BRCA2 as time-varying covariates. Competing risks were analyzed using Fine and Gray model. Results: The combined 10-year overall survival rate was 30% [95% confidence interval (CI), 28%–31%] for non-carriers, 25% (95% CI, 22%–28%) for BRCA1 carriers, and 35% (95% CI, 30%–41%) for BRCA2 carriers. The HR for BRCA1 was 0.53 at time zero and increased over time becoming greater than one at 4.8 years. For BRCA2, the HR was 0.42 at time zero and increased over time (predicted to become greater than 1 at 10.5 years). The results were similar when restricted to 3,202 patients with high-grade serous tumors and to ovarian cancer–specific mortality. Conclusions: BRCA1/2 mutations are associated with better short-term survival, but this advantage decreases over time and in BRCA1 carriers is eventually reversed. This may have important implications for therapy of both primary and relapsed disease and for analysis of long-term survival in clinical trials of new agents, particularly those that are effective in BRCA1/2 mutation carriers. Clin Cancer Res; 21(3); 652–7. ©2014 AACR.

Abstract Background:BRCA1 and BRCA2 mutation carriers are at substantially increased risk for developing breast and ovarian cancer. The incomplete penetrance coupled with the variable age at diagnosis in carriers of the same mutation suggests the existence of genetic and nongenetic modifying factors. In this study, we evaluated the putative role of variants in many candidate modifier genes. Methods: Genotyping data from 15,252 BRCA1 and 8,211 BRCA2 mutation carriers, for known variants (n = 3,248) located within or around 445 candidate genes, were available through the iCOGS custom-designed array. Breast and ovarian cancer association analysis was performed within a retrospective cohort approach. Results: The observed P values of association ranged between 0.005 and 1.000. None of the variants was significantly associated with breast or ovarian cancer risk in either BRCA1 or BRCA2 mutation carriers, after multiple testing adjustments. Conclusion: There is little evidence that any of the evaluated candidate variants act as modifiers of breast and/or ovarian cancer risk in BRCA1 or BRCA2 mutation carriers. Impact: Genome-wide association studies have been more successful at identifying genetic modifiers of BRCA1/2 penetrance than candidate gene studies. Cancer Epidemiol Biomarkers Prev; 24(1); 308–16. ©2014 AACR.

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.

Abstract Tumor infiltrating regulatory T cells (Tregs) appear to play a role in survival in a number of solid tumors, including ovarian cancer. We assessed genetic variation via tag SNPs (N=749) in 25 Treg associated genes (CD28, CTLA4, FOXP3, IDO1, IL10, IL10RA, IL15, 1L17RA, IL23A, IL23R, IL2RA, IL6, IL6R, IL8, LGALS1, LGALS9, MAP3K8, STAT5A, STAT5B, TGFB1, TGFB2, TGFB3, TGFBR1, TGRBR2, and TGFBR3) in relation to ovarian cancer survival. SNPs were selected based on r2 ≥ 0.8, MAF ≥ 0.05, 5 kb upstream and downstream from the gene. We had SNP and outcome data for ovarian cancer from 10,084 combined ovarian cancer cases, including 5,248 high grade serous, 1,452 endometrioid, 661 mucinous, and 795 clear cell cases of European descent across multiple studies from the Ovarian Cancer Association Consortium (OCAC). Cox proportional hazards regression modeling was used to estimate per-allele hazard ratios (HRs) and 95% confidence intervals (CIs) for associations with overall survival, adjusting for age at diagnosis, population substructure PCs, study site, histology (for the all case analysis), tumor stage, tumor grade and oral contraceptive use. The strongest associations were found for endometrioid histologic subtype and IL2RA SNPs (maximum r2=0.67) rs11256497 [HR=1.42, 95% CI: 1.22-1.64; p=5.7 x 10−6], rs791587 [HR=1.36, 95% CI: 1.17-1.57; p=6.2 x 10−5], rs2476491 [HR=1.40, 95% CI: 1.19-1.64; p=5.6 x 10−5], and rs10795763 [HR=1.35, 95% CI: 1.17-1.57; p=7.9 x 10−5], as well as clear cell ovarian cancer and CTLA4 SNP rs231775 [HR=0.67, 95% CI: 0.54-0.82; p=9.3 x 10−5]. No other associations were observed at p&lt;1 x 10−4. Overall, this study provided evidence that variation in genes related to Tregs, particularly IL2RA and CTLA4, influence ovarian cancer survival. Citation Format: Bridget Charbonneau, Keith Knutson, Robert A. Vierkant, Julie M. Cunningham, Zachary C. Fogarty, Kimberly R. Kalli, Matthew J. Maurer, Ann L. Oberg, Brooke L. Fridley, Claudia C. Preston, Paul D.P. Pharoah, Susan J. Ramus, Catherine M. Phelan, Kunle Odunsi, Kirsten Moysich, Ellen L. Goode. Polymorphisms in regulatory T cell related genes and ovarian cancer survival. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4844. doi:10.1158/1538-7445.AM2013-4844

Abstract Since most GWAS hits fall in non-coding regions of the genome and long non-coding RNAs (lncRNAs) are emerging as drivers of carcinogenesis, we hypothesized that SNPs in lncRNAs influence epithelial ovarian cancer (EOC) risk. A comprehensive lncRNA database (lncRNA db) that contained 104 human lncRNAs when downloaded in November 2011 was used to identify 1,737 variants in 63 unique lncRNAs that were represented in three genome-wide association studies from North America, the United Kingdom, and Poland (3,995 EOC cases and 3,277 controls of European background). SNPs with MAF &lt;5% were excluded, and missing genotypes were inferred with Mach using the HapMap CEU population. Unconditional logistic regression treating alternate alleles as an ordinal variable was used to evaluate individual SNP-EOC risk associations. Subgroup analysis was conducted for serous adenocarcinomas (N= 2,066), the main histologic subtype of EOC. Models were adjusted for study and European ancestry using the first two principal components (PCs). We reduced correlated signals (r2 ≥ 0.8) within each lncRNA and kept the most statistically significant variants based on Wald tests, resulting in 651 SNPs for further analyses. Fisher's product method was used to aggregate evidence of multiple variants within each lncRNA using 10,000 permutations. To adjust for multiple comparisons, a false discovery rate (FDR) of 10% was used. A replication phase was carried out for top-ranked SNPs from an additional 9,854 EOC cases (5,802 serous) and 17,633 controls genotyped through an international effort known as the Collaborative Oncological Gene-Environment study (COGS). Four lncRNAs, WT1-AS (p = 0.005, n = 2 SNPs), Hoxa11as (p = 0.013, n = 2), AK082072 (p = 0.016, n = 4) and H19 (p = 0.020, n = 2), were significantly associated with EOC risk among all histologies (FDR ≤ 10%). The SNP in WT1-AS most significantly associated with EOC risk was rs3809061 (T&gt;C) (minor allele frequency= 36%, odds ratio (OR) = 0.91, CI: 0.84-0.97, p = 0.008). Among serous cases, rs3809061 was also protective (OR = 0.92, p = 0.04). These findings were replicated by a correlated SNP rs2301250 (r2 = 0.84) evaluated in COGS among serous cases (OR = 0.94, CI: 0.90-0.99, p = 0.009) and less significant among all histologies (OR = 0.96, CI: 0.93-1.00, p = 0.054). We further interrogated its functional role by performing an expression quantitative trait locus analysis on WTI-AS mRNA expression using the Cancer Genome Atlas (TCGA) data (N = 462 serous cases). WT1-AS expression was significantly higher among carriers of the variant allele (compared to TT homozygotes) using the Mann-Whitney U test (p = 0.001). WT1-AS is the antisense and possible regulator of WT1, a tumor suppressor gene reported to be prognostic in advanced EOC. These findings implicate germline lncRNA variants associated with EOC risk that merit further investigation. Citation Format: Yian Ann Chen, Zhihua Chen, Jennifer Permuth-Wey, Ya-Yu Tsai, Hui-Yi Lin, Xiaotao Qu, Kate Lawrenson, David Fenstermacher, Catherine M. Phelan, Alvaro Monteiro, Simon A. Gayther, Steven A. Narod, Rebecca Sutphen, Michael J. Birrer, Nicolas Wentzensen, Joellen M. Schildkraut, Ellen L. Goode, Paul Pharoah, Thomas Sellers. Variants in long non-coding RNAs are associated with epithelial ovarian cancer risk in a pooled analysis of three genome-wide association studies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4579. doi:10.1158/1538-7445.AM2013-4579