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Jennifer Permuth-Wey,
Kate Lawrenson,
Howard C Shen,
Aneliya Velkova,
Jonathan P Tyrer,
Zhihua Chen,
Hui-Yi Lin,
Y Ann Chen, Ya-Yu Tsai,
Xiaotao Qu, [......],
Catherine M Phelan,
Edwin Iversen,
Joellen M Schildkraut,
Andrew Berchuck,
Brooke L Fridley,
Ellen L Goode,
Paul D P Pharoah,
Alvaro N A Monteiro,
Thomas A Sellers,
Simon A Gayther
[show abstract]
[hide abstract]
ABSTRACT: Epithelial ovarian cancer (EOC) has a heritable component that remains to be fully characterized. Most identified common susceptibility variants lie in non-protein-coding sequences. We hypothesized that variants in the 3' untranslated region at putative microRNA (miRNA)-binding sites represent functional targets that influence EOC susceptibility. Here, we evaluate the association between 767 miRNA-related single-nucleotide polymorphisms (miRSNPs) and EOC risk in 18,174 EOC cases and 26,134 controls from 43 studies genotyped through the Collaborative Oncological Gene-environment Study. We identify several miRSNPs associated with invasive serous EOC risk (odds ratio=1.12, P=10(-8)) mapping to an inversion polymorphism at 17q21.31. Additional genotyping of non-miRSNPs at 17q21.31 reveals stronger signals outside the inversion (P=10(-10)). Variation at 17q21.31 is associated with neurological diseases, and our collaboration is the first to report an association with EOC susceptibility. An integrated molecular analysis in this region provides evidence for ARHGAP27 and PLEKHM1 as candidate EOC susceptibility genes.
Nature Communications 03/2013; 4:1627. · 7.40 Impact Factor
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Paul D P Pharoah, Ya-Yu Tsai,
Susan J Ramus,
Catherine M Phelan,
Ellen L Goode,
Kate Lawrenson,
Melissa Buckley,
Brooke L Fridley,
Jonathan P Tyrer,
Howard Shen, [......],
Per Hall,
Douglas F Easton,
Celeste L Pearce,
Andrew Berchuck,
Georgia Chenevix-Trench,
Edwin Iversen,
Alvaro N A Monteiro,
Simon A Gayther,
Joellen M Schildkraut,
Thomas A Sellers
[show abstract]
[hide abstract]
ABSTRACT: Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have associations close to genome-wide significance and identified three loci newly associated with risk: two loci associated with all EOC subtypes at 8q21 (rs11782652, P = 5.5 × 10(-9)) and 10p12 (rs1243180, P = 1.8 × 10(-8)) and another locus specific to the serous subtype at 17q12 (rs757210, P = 8.1 × 10(-10)). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility and implicated CHMP4C in the pathogenesis of ovarian cancer.
Nature Genetics 03/2013; 45(4):362-370. · 35.53 Impact Factor
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Elizabeth M Poole,
Margaret A Gates,
Brigit A High,
Stephen J Chanock,
Daniel W Cramer,
Julie M Cunningham,
Brooke L Fridley,
Simon A Gayther,
Ellen L Goode,
Edwin S Iversen, [......],
Susan J Ramus,
Joellen M Schildkraut,
Rebecca Sutphen, Ya-Yu Tsai,
Jonathan Tyrer,
Robert A Vierkant,
Nicolas Wentzensen,
Hannah P Yang,
Kathryn L Terry,
Shelley S Tworoger
[show abstract]
[hide abstract]
ABSTRACT: Previous studies have examined the association between ABO blood group and ovarian cancer risk, with inconclusive results.
In eight studies participating in the Ovarian Cancer Association Consortium, we determined ABO blood groups and diplotypes by genotyping 3 SNPs in the ABO locus. Odds ratios and 95 % confidence intervals were calculated in each study using logistic regression; individual study results were combined using random effects meta-analysis.
Compared to blood group O, the A blood group was associated with a modestly increased ovarian cancer risk: (OR: 1.09; 95 % CI: 1.01-1.18; p = 0.03). In diplotype analysis, the AO, but not the AA diplotype, was associated with increased risk (AO: OR: 1.11; 95 % CI: 1.01-1.22; p = 0.03; AA: OR: 1.03; 95 % CI: 0.87-1.21; p = 0.76). Neither AB nor the B blood groups were associated with risk. Results were similar across ovarian cancer histologic subtypes.
Consistent with most previous reports, the A blood type was associated modestly with increased ovarian cancer risk in this large analysis of multiple studies of ovarian cancer. Future studies investigating potential biologic mechanisms are warranted.
Cancer Causes and Control 09/2012; 23(11):1805-10. · 2.88 Impact Factor
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Kristen N Stevens,
Linda E Kelemen,
Xianshu Wang,
Brooke L Fridley,
Robert A Vierkant,
Zachary Fredericksen,
Sebastian M Armasu, Ya-Yu Tsai,
Andrew Berchuck,
Steven A Narod,
Catherine M Phelan,
Rebecca Sutphen,
Michael J Birrer,
Joellen M Schildkraut,
Thomas A Sellers,
Ellen L Goode,
Fergus J Couch
[show abstract]
[hide abstract]
ABSTRACT: Overexpression of mitotic kinases has been associated with prognosis, histologic grade, and clinical stage in ovarian cancer, but the relationship between inherited variation in these genes and ovarian cancer risk has not been well defined.
We measured associations between 397 single nucleotide polymorphisms (SNPs) from 67 mitotic kinases and invasive epithelial ovarian cancer risk in two case-control studies (n = 671 cases; n = 939 controls). Thirty-six candidate SNPs (P < 0.05) were assessed in a replication analysis consisting of three additional studies (n = 1,094 cases; n = 829 controls).
In initial analysis, thirty-six SNPs were suggestive of association with risk of serous ovarian cancer, all subtypes of ovarian cancer, or both (P < 0.05). Replication analyses suggested an association between rs2125846 in the Nemo-like kinase (NLK) gene and ovarian cancer (serous OR = 1.36, 95% CI: 1.11-1.67, P = 1.77 × 10(-3); all subtypes OR = 1.30, 95% CI: 1.08-1.56, P = 2.97 × 10(-3)). Furthermore, rs2125846 was associated with risk in the combined discovery and replication sets (serous OR = 1.33, 95% CI: 1.15-1.54; all subtypes OR = 1.27, 95% CI: 1.12-1.45).
Variation in NLK may be associated with risk of invasive epithelial ovarian cancer. Further studies are needed to confirm and understand the biologic relationship between this mitotic kinase and ovarian cancer risk.
An association between SNPs in NLK and ovarian cancer may provide biologic insight into the development of this disease.
Cancer Epidemiology Biomarkers & Prevention 03/2012; 21(3):523-8. · 4.12 Impact Factor
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Brooke L Fridley,
Gregory D Jenkins, Ya-Yu Tsai,
Honglin Song,
Kelly L Bolton,
David Fenstermacher,
Jonathan Tyrer,
Susan J Ramus,
Julie M Cunningham,
Robert A Vierkant, [......],
Ed Iversen,
Usha Menon,
Aleksandra Gentry-Maharaj,
Joellen Schildkraut,
Rebecca Sutphen,
Simon A Gayther,
Lynn C Hartmann,
Paul D P Pharoah,
Thomas A Sellers,
Ellen L Goode
[show abstract]
[hide abstract]
ABSTRACT: Genome-wide association studies (GWAS) for epithelial ovarian cancer (EOC), the most lethal gynecologic malignancy, have identified novel susceptibility loci. GWAS for survival after EOC have had more limited success. The association of each single-nucleotide polymorphism (SNP) individually may not be well suited to detect small effects of multiple SNPs, such as those operating within the same biologic pathway. Gene set analysis (GSA) overcomes this limitation by assessing overall evidence for association of a phenotype with all measured variation in a set of genes.
To determine gene sets associated with EOC overall survival, we conducted GSA using data from two large GWAS (N cases = 2,813, N deaths = 1,116), with a novel Principal Component-Gamma GSA method. Analysis was completed for all cases and then separately for high-grade serous histologic subtype.
Analysis of the high-grade serous subjects resulted in 43 gene sets with P < 0.005 (1.7%); of these, 21 gene sets had P < 0.10 in both GWAS, including intracellular signaling pathway (P = 7.3 × 10(-5)) and macrolide binding (P = 6.2 × 10(-4)) gene sets. The top gene sets in analysis of all cases were meiotic mismatch repair (P = 6.3 × 10(-4)) and macrolide binding (P = 1.0 × 10(-3)). Of 18 gene sets with P < 0.005 (0.7%), eight had P < 0.10 in both GWAS.
This research detected novel gene sets associated with EOC survival.
Novel gene sets associated with EOC survival might lead to new insights and avenues for development of novel therapies for EOC and pharmacogenomic studies.
Cancer Epidemiology Biomarkers & Prevention 03/2012; 21(3):529-36. · 4.12 Impact Factor
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Brooke L Fridley,
Prabhakar Chalise, Ya-Yu Tsai,
Zhifu Sun,
Robert A Vierkant,
Melissa C Larson,
Julie M Cunningham,
Edwin S Iversen,
David Fenstermacher,
Jill Barnholtz-Sloan,
Yan Asmann,
Harvey A Risch,
Joellen M Schildkraut,
Catherine M Phelan,
Rebecca Sutphen,
Thomas A Sellers,
Ellen L Goode
[show abstract]
[hide abstract]
ABSTRACT: Copy number variants (CNVs) have been implicated in many complex diseases. We examined whether inherited CNVs were associated with overall survival among women with invasive epithelial ovarian cancer. Germline DNA from 1,056 cases (494 deceased, average of 3.7 years follow-up) was interrogated with the Illumina 610 quad genome-wide array containing, after quality control exclusions, 581,903 single nucleotide polymorphisms (SNPs) and 17,917 CNV probes. Comprehensive analysis capitalized upon the strengths of three complementary approaches to CNV classification. First, to identify small CNVs, single markers were evaluated and, where associated with survival, consecutive markers were combined. Two chromosomal regions were associated with survival using this approach (14q31.3 rs2274736 p = 1.59 × 10(-6), p = 0.001; 22q13.31 rs2285164 p = 4.01 × 10(-5), p = 0.009), but were not significant after multiple testing correction. Second, to identify large CNVs, genome-wide segmentation was conducted to characterize chromosomal gains and losses, and association with survival was evaluated by segment. Four regions were associated with survival (1q21.3 loss p = 0.005, 5p14.1 loss p = 0.004, 9p23 loss p = 0.002, and 15q22.31 gain p = 0.002); however, again, after correcting for multiple testing, no regions were statistically significant, and none were in common with the single marker approach. Finally, to evaluate associations with general amounts of copy number changes across the genome, we estimated CNV burden based on genome-wide numbers of gains and losses; no associations with survival were observed (p > 0.40). Although CNVs that were not well-covered by the Illumina 610 quad array merit investigation, these data suggest no association between inherited CNVs and survival after ovarian cancer.
Frontiers in genetics. 01/2012; 3:142.
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Linda E Kelemen,
Qinggang Wang,
Irina Dinu,
Robert A Vierkant, Ya-Yu Tsai,
Julie M Cunningham,
Catherine M Phelan,
Brooke L Fridley,
Ernest K Amankwah,
Edwin S Iversen,
Andrew Berchuck,
Joellen M Schildkraut,
Ellen L Goode,
Thomas A Sellers
[show abstract]
[hide abstract]
ABSTRACT: ATIC, SHMT2, and SLC46A1 have essential roles in one-carbon (1-C) transfer. The authors examined whether associations between ovarian carcinoma and 15 variants in these genes are modified by regular multivitamin use, a source of 1-C donors, among Caucasian participants from two US case-control studies. Using a phased study design, variant-by-multivitamin interactions were tested, and associations between variants and ovarian carcinoma were reported stratified by multivitamin supplement use. Per-allele risk associations were modified by multivitamin use at six variants among 655 cases and 920 controls (Phase 1). In a larger sample of 968 cases and 1,265 controls (Phases 1 and 2), interactions were significant (P ≤ 0.03) for two variants, particularly among regular multivitamin users: ATIC rs7586969 [odds ratio (OR) = 0.7, 95% confidence interval (CI) = 0.6-0.9] and ATIC rs16853834 (OR = 1.5, 95% CI = 1.1-2.0). The two ATIC single nucleotide polymorphisms (SNPs) did not share the same haplotype; however, the haplotypes they comprised mirrored their SNP risk associations among regular multivitamin supplement users. A multi-variant analysis was also performed by comparing the observed likelihood ratio test statistic from adjusted models with and without the two ATIC variant-by-multivitamin interaction terms with a null distribution of test statistics generated by permuting case status 10,000 times. The corresponding observed P value of 0.001 was more extreme than the permutation-derived P value of 0.009, suggesting rejection of the null hypothesis of no association. In summary, there is little statistical evidence that the 15 variants are independently associated with risk of ovarian carcinoma. However, the statistical interaction of ATIC variants with regular multivitamin intake, when evaluated at both the SNP and gene level, may support these findings as relevant to ovarian health and disease processes.
Frontiers in genetics. 01/2012; 3:33.
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Paola Raska,
Edwin Iversen,
Ann Chen,
Zhihua Chen,
Brooke L Fridley,
Jennifer Permuth-Wey, Ya-Yu Tsai,
Robert A Vierkant,
Ellen L Goode,
Harvey Risch,
Joellen M Schildkraut,
Thomas A Sellers,
Jill Barnholtz-Sloan
[show abstract]
[hide abstract]
ABSTRACT: We investigated the ability of several principal components analysis (PCA)-based strategies to detect and control for population stratification using data from a multi-center study of epithelial ovarian cancer among women of European-American ethnicity. These include a correction based on an ancestry informative markers (AIMs) panel designed to capture European ancestral variation and corrections utilizing un-thinned genome-wide SNP data; case-control samples were drawn from four geographically distinct North-American sites. The AIMs-only and genome-wide first principal components (PC1) both corresponded to the previously described North or Northwest-Southeast axis of European variation. We found that the genome-wide PCA captured this primary dimension of variation more precisely and identified additional axes of genome-wide variation of relevance to epithelial ovarian cancer. Associations evident between the genome-wide PCs and study site corroborate North American immigration history and suggest that undiscovered dimensions of variation lie within Northern Europe. The structure captured by the genome-wide PCA was also found within control individuals and did not reflect the case-control variation present in the data. The genome-wide PCA highlighted three regions of local LD, corresponding to the lactase (LCT) gene on chromosome 2, the human leukocyte antigen system (HLA) on chromosome 6 and to a common inversion polymorphism on chromosome 8. These features did not compromise the efficacy of PCs from this analysis for ancestry control. This study concludes that although AIMs panels are a cost-effective way of capturing population structure, genome-wide data should preferably be used when available.
PLoS ONE 01/2012; 7(5):e35235. · 4.09 Impact Factor
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[show abstract]
[hide abstract]
ABSTRACT: Studies have shown that interactions of single nucleotide polymorphisms (SNPs) may play an important role in understanding the causes of complex disease. We have proposed an integrated machine learning method that combines two machine-learning methods-Random Forests (RF) and Multivariate Adaptive Regression Splines (MARS)-to identify a subset of important SNPs and detect interaction patterns more effectively and efficiently. In this two-stage RF-MARS (TRM) approach, RF is first applied to detect a predictive subset of SNPs, and then MARS is used to identify the interaction patterns. We evaluated the TRM performances in four models. RF variable selection was based on out-of-bag classification error rate (OOB) and variable important spectrum (IS). Our results support that RF(OOB) had better performance than MARS and RF(IS) in detecting important variables. This study demonstrates that TRM(OOB) , which is RF(OOB) plus MARS, has combined the strengths of RF and MARS in identifying SNP-SNP interactions in a scenario of 100 candidate SNPs. TRM(OOB) had greater true positive rate and lower false positive rate compared with MARS, particularly for searching interactions with a strong association with the outcome. Therefore, the use of TRM(OOB) is favored for exploring SNP-SNP interactions in a large-scale genetic variation study.
Annals of Human Genetics 12/2011; 76(1):53-62. · 2.57 Impact Factor
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Abra G Brisbin,
Yan W Asmann,
Honglin Song, Ya-Yu Tsai,
Jeremiah A Aakre,
Ping Yang,
Robert B Jenkins,
Paul Pharoah,
Fredrick Schumacher,
David V Conti,
David J Duggan,
Mark Jenkins,
John Hopper,
Steven Gallinger,
Polly Newcomb,
Graham Casey,
Thomas A Sellers,
Brooke L Fridley
[show abstract]
[hide abstract]
ABSTRACT: Human chromosomal region 8q24 contains several genes which could be functionally related to cancer, including the proto-oncogene c-MYC. However, the abundance of associations around 128 Mb on chromosome 8 could mask the appearance of a weaker, but important, association elsewhere on 8q24.
In this study, we completed a meta-analysis of results from nine genome-wide association studies for seven types of solid-tumor cancers (breast, prostate, pancreatic, lung, ovarian, colon, and glioma) to identify additional associations that were not apparent in any individual study.
Fifteen SNPs in the 8q24 region had meta-analysis p-values < 1E-04. In particular, the region consisting of 120,576,000-120,627,000 bp contained 7 SNPs with p-values < 1.0E-4, including rs6993464 (p = 1.25E-07). This association lies in the region between two genes, NOV and ENPP2, which have been shown to play a role in tumor development and motility. An additional region consisting of 5 markers from 128,478,000 bp - 128,524,000 (around gene POU5F1B) had p-values < 1E-04, including rs6983267, which had the smallest p-value (p = 6.34E-08). This result replicates previous reports of association between rs6983267 and prostate and colon cancer.
Further research in this area is warranted as these results demonstrate that the chromosomal region 8q24 may contain a locus that influences general cancer susceptibility between 120,576 and 120,630 kb.
BMC Medical Genetics 12/2011; 12:156. · 2.33 Impact Factor
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Ellen L Goode,
Georgia Chenevix-Trench,
Lynn C Hartmann,
Brooke L Fridley,
Kimberly R Kalli,
Robert A Vierkant,
Melissa C Larson,
Kristin L White,
Gary L Keeney,
Trynda N Oberg, [......],
David J Duggan, Ya-Yu Tsai,
Catherine M Phelan,
Linda E Kelemen,
Prema P Peethambaram,
Joellen M Schildkraut,
Vijayalakshmi Shridhar,
Rebecca Sutphen,
Fergus J Couch,
Thomas A Sellers
[show abstract]
[hide abstract]
ABSTRACT: Invasive ovarian cancer is a significant cause of gynecologic cancer mortality.
We examined whether this mortality was associated with inherited variation in approximately 170 candidate genes/regions [993 single-nucleotide polymorphisms (SNPs)] in a multistage analysis based initially on 312 Mayo Clinic cases (172 deaths). Additional analyses used The Cancer Genome Atlas (TCGA; 127 cases, 62 deaths). For the most compelling gene, we immunostained Mayo Clinic tissue microarrays (TMA, 326 cases) and conducted consortium-based SNP replication analysis (2,560 cases, 1,046 deaths).
The strongest initial mortality association was in HGF (hepatocyte growth factor) at rs1800793 (HR = 1.7, 95% CI = 1.3-2.2, P = 2.0 × 10(-5)) and with overall variation in HGF (gene-level test, P = 3.7 × 10(-4)). Analysis of TCGA data revealed consistent associations [e.g., rs5745709 (r(2) = 0.96 with rs1800793): TCGA HR = 2.4, CI = 1.4-4.1, P = 2.2 × 10(-3); Mayo Clinic + TCGA HR = 1.6, CI = 1.3-1.9, P = 7.0 × 10(-5)] and suggested genotype correlation with reduced HGF mRNA levels (P = 0.01). In Mayo Clinic TMAs, protein levels of HGF, its receptor MET (C-MET), and phospho-MET were not associated with genotype and did not serve as an intermediate phenotype; however, phospho-MET was associated with reduced mortality (P = 0.01) likely due to higher expression in early-stage disease. In eight additional ovarian cancer case series, HGF rs5745709 was not associated with mortality (HR = 1.0, CI = 0.9-1.1, P = 0.87).
We conclude that although HGF signaling is critical to migration, invasion, and apoptosis, it is unlikely that HGF genetic variation plays a major role in ovarian cancer mortality. Furthermore, any minor role is not related to genetically-determined expression.
Our study shows the utility of multiple data types and multiple data sets in observational studies.
Cancer Epidemiology Biomarkers & Prevention 07/2011; 20(8):1638-48. · 4.12 Impact Factor
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Jennifer Permuth-Wey,
Zhihua Chen, Ya-Yu Tsai,
Hui-Yi Lin,
Y Ann Chen,
Jill Barnholtz-Sloan,
Michael J Birrer,
Stephen J Chanock,
Daniel W Cramer,
Julie M Cunningham, [......],
Jonathan Tyrer,
Robert A Vierkant,
Nicolas Wentzensen,
Johnathan M Lancaster,
Jin Q Cheng,
Andrew Berchuck,
Paul D P Pharoah,
Joellen M Schildkraut,
Ellen L Goode,
Thomas A Sellers
[show abstract]
[hide abstract]
ABSTRACT: Single nucleotide polymorphisms (SNP) in microRNA-related genes have been associated with epithelial ovarian cancer (EOC) risk in two reports, yet associated alleles may be inconsistent across studies.
We conducted a pooled analysis of previously identified SNPs by combining genotype data from 3,973 invasive EOC cases and 3,276 controls from the Ovarian Cancer Association Consortium. We also conducted imputation to obtain dense coverage of genes and comparable genotype data for all studies. In total, 226 SNPs within 15 kb of 4 miRNA biogenesis genes (DDX20, DROSHA, GEMIN4, and XPO5) and 23 SNPs located within putative miRNA binding sites of 6 genes (CAV1, COL18A1, E2F2, IL1R1, KRAS, and UGT2A3) were genotyped or imputed and analyzed in the entire dataset.
After adjustment for European ancestry, no overall association was observed between any of the analyzed SNPs and EOC risk.
Common variants in these evaluated genes do not seem to be strongly associated with EOC risk.
This analysis suggests earlier associations between EOC risk and SNPs in these genes may have been chance findings, possibly confounded by population admixture. To more adequately evaluate the relationship between genetic variants and cancer risk, large sample sizes are needed, adjustment for population stratification should be carried out, and use of imputed SNP data should be considered.
Cancer Epidemiology Biomarkers & Prevention 06/2011; 20(8):1793-7. · 4.12 Impact Factor
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Jennifer Permuth-Wey,
Donghwa Kim, Ya-Yu Tsai,
Hui-Yi Lin,
Y Ann Chen,
Jill Barnholtz-Sloan,
Michael J Birrer,
Gregory Bloom,
Stephen J Chanock,
Zhihua Chen, [......],
Honglin Song,
Heather Stockwell,
Rebecca Sutphen,
Kathryn L Terry,
Jonathan Tyrer,
Robert A Vierkant,
Nicolas Wentzensen,
Johnathan M Lancaster,
Jin Q Cheng,
Thomas A Sellers
[show abstract]
[hide abstract]
ABSTRACT: Defective microRNA (miRNA) biogenesis contributes to the development and progression of epithelial ovarian cancer (EOC). In this study, we examined the hypothesis that single nucleotide polymorphisms (SNP) in miRNA biogenesis genes may influence EOC risk. In an initial investigation, 318 SNPs in 18 genes were evaluated among 1,815 EOC cases and 1,900 controls, followed up by a replicative joint meta-analysis of data from an additional 2,172 cases and 3,052 controls. Of 23 SNPs from 9 genes associated with risk (empirical P < 0.05) in the initial investigation, the meta-analysis replicated 6 SNPs from the DROSHA, FMR1, LIN28, and LIN28B genes, including rs12194974 (G>A), an SNP in a putative transcription factor binding site in the LIN28B promoter region (summary OR = 0.90, 95% CI: 0.82-0.98; P = 0.015) which has been recently implicated in age of menarche and other phenotypes. Consistent with reports that LIN28B overexpression in EOC contributes to tumorigenesis by repressing tumor suppressor let-7 expression, we provide data from luciferase reporter assays and quantitative RT-PCR to suggest that the inverse association among rs12194974 A allele carriers may be because of reduced LIN28B expression. Our findings suggest that variants in LIN28B and possibly other miRNA biogenesis genes may influence EOC susceptibility.
Cancer Research 06/2011; 71(11):3896-903. · 7.86 Impact Factor
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Paul D P Pharoah,
Rachel T Palmieri,
Susan J Ramus,
Simon A Gayther,
Irene L Andrulis,
Hoda Anton-Culver,
Natalia Antonenkova,
Antonis C Antoniou,
David Goldgar,
Mary S Beattie, [......],
Ignace Vergote,
Robert A Vierkant,
Allison F Vitonis,
Christine Walsh,
Shan Wang-Gohrke,
Barbara Wappenschmidt,
Anna H Wu,
Argyrios Ziogas,
Andrew Berchuck,
Harvey A Risch
[show abstract]
[hide abstract]
ABSTRACT: An assay for the single-nucleotide polymorphism (SNP), rs61764370, has recently been commercially marketed as a clinical test to aid ovarian cancer risk evaluation in women with family histories of the disease. rs67164370 is in a 3'-UTR miRNA binding site of the KRAS oncogene and is a candidate for epithelial ovarian cancer (EOC) susceptibility. However, only one published article, analyzing fewer than 1,000 subjects in total, has examined this association.
Risk association was evaluated in 8,669 cases of invasive EOC and 10,012 controls from 19 studies participating in the Ovarian Cancer Association Consortium, and in 683 cases and 2,044 controls carrying BRCA1 mutations from studies in the Consortium of Investigators of Modifiers of BRCA1/2. Prognosis association was also examined in a subset of five studies with progression-free survival (PFS) data and 18 studies with all-cause mortality data.
No evidence of association was observed between genotype and risk of unselected EOC (OR = 1.02, 95% CI: 0.95-1.10), serous EOC (OR = 1.08, 95% CI: 0.98-1.18), familial EOC (OR = 1.09, 95% CI: 0.78-1.54), or among women carrying deleterious mutations in BRCA1 (OR = 1.09, 95% CI: 0.88-1.36). There was little evidence for association with survival time among unselected cases (HR = 1.10, 95% CI: 0.99-1.22), among serous cases (HR = 1.12, 95% CI = 0.99-1.28), or with PFS in 540 cases treated with carboplatin and paclitaxel (HR = 1.18, 95% CI: 0.93-1.52).
These data exclude the possibility of an association between rs61764370 and a clinically significant risk of ovarian cancer or of familial ovarian cancer. Use of this SNP for ovarian cancer clinical risk prediction, therefore, seems unwarranted.
Clinical Cancer Research 03/2011; 17(11):3742-50. · 7.74 Impact Factor
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Jennifer Permuth-Wey,
Y Ann Chen, Ya-Yu Tsai,
Zhihua Chen,
Xiaotao Qu,
Johnathan M Lancaster,
Heather Stockwell,
Getachew Dagne,
Edwin Iversen,
Harvey Risch, [......],
Robert A Vierkant,
Brooke L Fridley,
Rebecca Sutphen,
John McLaughlin,
Steven A Narod,
Ellen L Goode,
Joellen M Schildkraut,
David Fenstermacher,
Catherine M Phelan,
Thomas A Sellers
[show abstract]
[hide abstract]
ABSTRACT: Mitochondria contribute to oxidative stress, a phenomenon implicated in ovarian carcinogenesis. We hypothesized that inherited variants in mitochondrial-related genes influence epithelial ovarian cancer (EOC) susceptibility.
Through a multicenter study of 1,815 Caucasian EOC cases and 1,900 controls, we investigated associations between EOC risk and 128 single nucleotide polymorphisms (SNPs) from 22 genes/regions within the mitochondrial genome (mtDNA) and 2,839 nuclear-encoded SNPs localized to 138 genes involved in mitochondrial biogenesis (BIO, n = 35), steroid hormone metabolism (HOR, n = 13), and oxidative phosphorylation (OXP, n = 90) pathways. Unconditional logistic regression was used to estimate OR and 95% CI between genotype and case status. Overall significance of each gene and pathway was evaluated by using Fisher's method to combine SNP-level evidence. At the SNP level, we investigated whether lifetime ovulation, hormone replacement therapy (HRT), and cigarette smoking were confounders or modifiers of associations.
Interindividual variation involving BIO was most strongly associated with EOC risk (empirical P = 0.050), especially for NRF1, MTERF, PPARGC1A, ESRRA, and CAMK2D. Several SNP-level associations strengthened after adjustment for nongenetic factors, particularly for MTERF. Statistical interactions with cigarette smoking and HRT use were observed with MTERF and CAMK2D SNPs, respectively. Overall variation within mtDNA, HOR, and OXP was not statistically significant (empirical P > 0.10).
We provide novel evidence to suggest that variants in mitochondrial biogenesis genes may influence EOC susceptibility.
A deeper understanding of the complex mechanisms implicated in mitochondrial biogenesis and oxidative stress may aid in developing strategies to reduce morbidity and mortality from EOC.
Cancer Epidemiology Biomarkers & Prevention 03/2011; 20(6):1131-45. · 4.12 Impact Factor
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Ernest K Amankwah,
Qinggang Wang,
Joellen M Schildkraut, Ya-Yu Tsai,
Susan J Ramus,
Brooke L Fridley,
Jonathan Beesley,
Sharon E Johnatty,
Penelope M Webb,
Georgia Chenevix-Trench, [......],
Linda S Cook,
Catherine M Phelan,
Julie M Cunningham,
Celine M Vachon,
Robert A Vierkant,
Edwin S Iversen,
Andrew Berchuck,
Ellen L Goode,
Thomas A Sellers,
Linda E Kelemen
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ABSTRACT: Alterations in stromal tissue components can inhibit or promote epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) show reduced stromal expression in serous epithelial ovarian cancer (sEOC). We hypothesized that common variants in these genes associate with risk. Associations with sEOC among Caucasians were estimated with odds ratios (OR) among 397 cases and 920 controls in two U.S.-based studies (discovery set), 436 cases and 1,098 controls in Australia (replication set 1) and a consortium of 15 studies comprising 1,668 cases and 4,249 controls (replication set 2). The discovery set and replication set 1 (833 cases and 2,013 controls) showed statistically homogeneous (P(heterogeneity)≥0.48) decreased risks of sEOC at four variants: DCN rs3138165, rs13312816 and rs516115, and LUM rs17018765 (OR = 0.6 to 0.9; P(trend) = 0.001 to 0.03). Results from replication set 2 were statistically homogeneous (P(heterogeneity)≥0.13) and associated with increased risks at DCN rs3138165 and rs13312816, and LUM rs17018765: all ORs = 1.2; P(trend)≤0.02. The ORs at the four variants were statistically heterogeneous across all 18 studies (P(heterogeneity)≤0.03), which precluded combining. In post-hoc analyses, interactions were observed between each variant and recruitment period (P(interaction)≤0.003), age at diagnosis (P(interaction) = 0.04), and year of diagnosis (P(interaction) = 0.05) in the five studies with available information (1,044 cases, 2,469 controls). We conclude that variants in DCN and LUM are not directly associated with sEOC, and that confirmation of possible effect modification of the variants by non-genetic factors is required.
PLoS ONE 01/2011; 6(5):e19642. · 4.09 Impact Factor
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ABSTRACT: One difficult question facing researchers is how to prioritize SNPs detected from genetic association studies for functional studies. Often a list of the top M SNPs is determined based on solely the p-value from an association analysis, where M is determined by financial/time constraints. For many studies of complex diseases, multiple analyses have been completed and integrating these multiple sets of results may be difficult. One may also wish to incorporate biological knowledge, such as whether the SNP is in the exon of a gene or a regulatory region, into the selection of markers to follow-up. In this manuscript, we propose a Bayesian latent variable model (BLVM) for incorporating "features" about a SNP to estimate a latent "quality score", with SNPs prioritized based on the posterior probability distribution of the rankings of these quality scores. We illustrate the method using data from an ovarian cancer genome-wide association study (GWAS). In addition to the application of the BLVM to the ovarian GWAS, we applied the BLVM to simulated data which mimics the setting involving the prioritization of markers across multiple GWAS for related diseases/traits. The top ranked SNP by BLVM for the ovarian GWAS, ranked 2(nd) and 7(th) based on p-values from analyses of all invasive and invasive serous cases. The top SNP based on serous case analysis p-value (which ranked 197(th) for invasive case analysis), was ranked 8(th) based on the posterior probability of being in the top 5 markers (0.13). In summary, the application of the BLVM allows for the systematic integration of multiple SNP "features" for the prioritization of loci for fine-mapping or functional studies, taking into account the uncertainty in ranking.
PLoS ONE 01/2011; 6(6):e20764. · 4.09 Impact Factor
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Ellen L Goode,
Georgia Chenevix-Trench,
Honglin Song,
Susan J Ramus,
Maria Notaridou,
Kate Lawrenson,
Martin Widschwendter,
Robert A Vierkant,
Melissa C Larson,
Susanne K Kjaer, [......],
Natalia Bogdanova,
Arto Leminen,
Ralf Butzow,
Tuomas Heikkinen,
Kari Stefansson,
Patrick Sulem,
Sören Besenbacher,
Thomas A Sellers,
Simon A Gayther,
Paul D P Pharoah
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ABSTRACT: Ovarian cancer accounts for more deaths than all other gynecological cancers combined. To identify common low-penetrance ovarian cancer susceptibility genes, we conducted a genome-wide association study of 507,094 SNPs in 1,768 individuals with ovarian cancer (cases) and 2,354 controls, with follow up of 21,955 SNPs in 4,162 cases and 4,810 controls, leading to the identification of a confirmed susceptibility locus at 9p22 (in BNC2). Here, we report on nine additional candidate loci (defined as having P ≤ 10⁻⁴) identified after stratifying cases by histology, which we genotyped in an additional 4,353 cases and 6,021 controls. We confirmed two new susceptibility loci with P ≤ 5 × 10⁻⁸ (8q24, P = 8.0 × 10⁻¹⁵ and 2q31, P = 3.8 × 10⁻¹⁴) and identified two additional loci that approached genome-wide significance (3q25, P = 7.1 × 10⁻⁸ and 17q21, P = 1.4 × 10⁻⁷). The associations of these loci with serous ovarian cancer were generally stronger than with other cancer subtypes. Analysis of HOXD1, MYC, TIPARP and SKAP1 at these loci and of BNC2 at 9p22 supports a functional role for these genes in ovarian cancer development.
Nature Genetics 10/2010; 42(10):874-9. · 35.53 Impact Factor
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Kelly L Bolton,
Jonathan Tyrer,
Honglin Song,
Susan J Ramus,
Maria Notaridou,
Chris Jones,
Tanya Sher,
Aleksandra Gentry-Maharaj,
Eva Wozniak, Ya-Yu Tsai, [......],
Penelope M Webb,
Jonathan Beesley,
Stephen Chanock,
Montserrat Garcia-Closas,
Tom Sellers,
Douglas F Easton,
Andrew Berchuck,
Georgia Chenevix-Trench,
Paul D P Pharoah,
Simon A Gayther
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ABSTRACT: Epithelial ovarian cancer (EOC) is the leading cause of death from gynecological malignancy in the developed world, accounting for 4% of the deaths from cancer in women. We performed a three-phase genome-wide association study of EOC survival in 8,951 individuals with EOC (cases) with available survival time data and a parallel association analysis of EOC susceptibility. Two SNPs at 19p13.11, rs8170 and rs2363956, showed evidence of association with survival (overall P = 5 × 10⁻⁴ and P = 6 × 10⁻⁴, respectively), but they did not replicate in phase 3. However, the same two SNPs demonstrated genome-wide significance for risk of serous EOC (P = 3 × 10⁻⁹ and P = 4 × 10⁻¹¹, respectively). Expression analysis of candidate genes at this locus in ovarian tumors supported a role for the BRCA1-interacting gene C19orf62, also known as MERIT40, which contains rs8170, in EOC development.
Nature Genetics 10/2010; 42(10):880-4. · 35.53 Impact Factor
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Catherine M Phelan, Ya-Yu Tsai,
Ellen L Goode,
Robert A Vierkant,
Brooke L Fridley,
Jonathan Beesley,
Xiao Qing Chen,
Penelope M Webb,
Stephen Chanock,
Daniel W Cramer, [......],
Edwin S Iversen,
Jeffrey R Marks,
Malcolm C Pike,
Simon A Gayther,
Julie M Cunningham,
Marc T Goodman,
Joellen M Schildkraut,
Georgia Chenevix-Trench,
Andrew Berchuck,
Thomas A Sellers
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ABSTRACT: Aberrant glycosylation is a well-described hallmark of cancer. In a previous ovarian cancer case control study that examined polymorphisms in 26 glycosylation-associated genes, we found strong statistical evidence (P = 0.00017) that women who inherited two copies of a single-nucleotide polymorphism in the UDP-N-acetylgalactosamine:polypeptide N-acetylgalactosaminyltransferase, GALNT1, had decreased ovarian cancer risk. The current study attempted to replicate this observation. The GALNT1 single-nucleotide polymorphism rs17647532 was genotyped in 6,965 cases and 8,377 controls from 14 studies forming the Ovarian Cancer Association Consortium. The fixed effects estimate per rs17647532 allele was null (odds ratio, 0.99; 95% confidence interval, 0.92-1.07). When a recessive model was fit, the results were unchanged. Test for heterogeneity of the odds ratios revealed consistency across the 14 replication sites but significant differences compared with the original study population (P = 0.03). This study underscores the need for replication of putative findings in genetic association studies.
Cancer Epidemiology Biomarkers & Prevention 02/2010; 19(2):600-4. · 4.12 Impact Factor
