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Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk.
Yang Y, Wu L, Shu X, Lu Y, Shu XO, Cai Q, Beeghly-Fadiel A, Li B, Ye F, Berchuck A, Anton-Culver H, Banerjee S, Benitez J, Bjørge L, Brenton JD, Butzow R, Campbell IG, Chang-Claude J, Chen K, Cook LS, Cramer DW, deFazio A, Dennis J, Doherty JA, Dörk T, Eccles DM, Edwards DV, Fasching PA, Fortner RT, Gayther SA, Giles GG, Glasspool RM, Goode EL, Goodman MT, Gronwald J, Harris HR, Heitz F, Hildebrandt MA, Høgdall E, Høgdall CK, Huntsman DG, Kar SP, Karlan BY, Kelemen LE, Kiemeney LA, Kjaer SK, Koushik A, Lambrechts D, Le ND, Levine DA, Massuger LF, Matsuo K, May T, McNeish IA, Menon U, Modugno F, Monteiro AN, Moorman PG, Moysich KB, Ness RB, Nevanlinna H, Olsson H, Onland-Moret NC, Park SK, Paul J, Pearce CL, Pejovic T, Phelan CM, Pike MC, Ramus SJ, Riboli E, Rodriguez-Antona C, Romieu I, Sandler DP, Schildkraut JM, Setiawan VW, Shan K, Siddiqui N, Sieh W, Stampfer MJ, Sutphen R, Swerdlow AJ, Szafron LM, Teo SH, Tworoger SS, Tyrer JP, Webb PM, Wentzensen N, White E, Willett WC, Wolk A, Woo YL, Wu AH, Yan L, Yannoukakos D, Chenevix-Trench G, Sellers TA, Pharoah PDP, Zheng W, Long J
(2019) Cancer Res 79: 505-517
MeSH Terms: Biomarkers, Tumor, Carcinoma, Ovarian Epithelial, Cohort Studies, DNA Methylation, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Humans, Models, Genetic, Ovarian Neoplasms, Predictive Value of Tests, Risk, Women's Health
Show Abstract · Added March 26, 2019
DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study ( = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of < 7.94 × 10. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely , and . We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
©2018 American Association for Cancer Research.
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13 MeSH Terms
A Transcriptome-Wide Association Study Among 97,898 Women to Identify Candidate Susceptibility Genes for Epithelial Ovarian Cancer Risk.
Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, Im HK, Chen YA, Permuth JB, Reid BM, Teer JK, Moysich KB, Andrulis IL, Anton-Culver H, Arun BK, Bandera EV, Barkardottir RB, Barnes DR, Benitez J, Bjorge L, Brenton J, Butzow R, Caldes T, Caligo MA, Campbell I, Chang-Claude J, Claes KBM, Couch FJ, Cramer DW, Daly MB, deFazio A, Dennis J, Diez O, Domchek SM, Dörk T, Easton DF, Eccles DM, Fasching PA, Fortner RT, Fountzilas G, Friedman E, Ganz PA, Garber J, Giles GG, Godwin AK, Goldgar DE, Goodman MT, Greene MH, Gronwald J, Hamann U, Heitz F, Hildebrandt MAT, Høgdall CK, Hollestelle A, Hulick PJ, Huntsman DG, Imyanitov EN, Isaacs C, Jakubowska A, James P, Karlan BY, Kelemen LE, Kiemeney LA, Kjaer SK, Kwong A, Le ND, Leslie G, Lesueur F, Levine DA, Mattiello A, May T, McGuffog L, McNeish IA, Merritt MA, Modugno F, Montagna M, Neuhausen SL, Nevanlinna H, Nielsen FC, Nikitina-Zake L, Nussbaum RL, Offit K, Olah E, Olopade OI, Olson SH, Olsson H, Osorio A, Park SK, Parsons MT, Peeters PHM, Pejovic T, Peterlongo P, Phelan CM, Pujana MA, Ramus SJ, Rennert G, Risch H, Rodriguez GC, Rodríguez-Antona C, Romieu I, Rookus MA, Rossing MA, Rzepecka IK, Sandler DP, Schmutzler RK, Setiawan VW, Sharma P, Sieh W, Simard J, Singer CF, Song H, Southey MC, Spurdle AB, Sutphen R, Swerdlow AJ, Teixeira MR, Teo SH, Thomassen M, Tischkowitz M, Toland AE, Trichopoulou A, Tung N, Tworoger SS, van Rensburg EJ, Vanderstichele A, Vega A, Edwards DV, Webb PM, Weitzel JN, Wentzensen N, White E, Wolk A, Wu AH, Yannoukakos D, Zorn KK, Gayther SA, Antoniou AC, Berchuck A, Goode EL, Chenevix-Trench G, Sellers TA, Pharoah PDP, Zheng W, Long J
(2018) Cancer Res 78: 5419-5430
MeSH Terms: Carcinogenesis, Carcinoma, Ovarian Epithelial, Cohort Studies, Female, Gene Expression Profiling, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Prognosis, Quantitative Trait Loci, Risk Factors, Transcriptome
Show Abstract · Added December 6, 2018
Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their -predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of < 2.2 × 10, we identified 35 genes, including at 11q14.2 (Z = 5.08, = 3.83 × 10, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained ( < 1.47 × 10). These data identify one novel locus ) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis. Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. .
©2018 American Association for Cancer Research.
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15 MeSH Terms
Differential cyclooxygenase expression levels and survival associations in type I and type II ovarian tumors.
Beeghly-Fadiel A, Wilson AJ, Keene S, El Ramahi M, Xu S, Marnett LJ, Fadare O, Crispens MA, Khabele D
(2018) J Ovarian Res 11: 17
MeSH Terms: Aged, Biomarkers, Tumor, Cyclooxygenase 1, Cyclooxygenase 2, Female, Gene Expression Regulation, Neoplastic, Humans, Immunohistochemistry, Kaplan-Meier Estimate, Middle Aged, Neoplasm Grading, Neoplasm Staging, Ovarian Neoplasms, Prognosis, Proportional Hazards Models, Prostaglandin-Endoperoxide Synthases
Show Abstract · Added March 21, 2018
BACKGROUND - High cyclooxygenase (COX)-2 expression in ovarian tumors has been associated with poor prognosis, but the role of COX-1 expression and its relation to survival is less clear. Here, we evaluated COX expression and associations with survival outcomes between type I (clear cell, mucinous, low grade endometrioid and low grade serous) and type II (high grade serous and high grade endometrioid) ovarian tumors.
METHODS - We developed and validated a new COX-1 antibody, and conducted immunohistochemical (IHC) staining for COX-1 and COX-2 on a tissue microarray (TMA) of 190 primary ovarian tumors. In addition to standard IHC scoring and H-scores to combine the percentage of positive cells and staining intensity, we also measured COX-1 and COX-2 mRNA expression by QPCR. High expression was defined as greater than or equal to median values. Clinical characteristics and disease outcomes were ascertained from medical records. Associations with disease-free survival (DFS) and overall survival (OS) were quantified by hazard ratios (HRs) and confidence intervals (CIs) from proportional hazards regression.
RESULTS - Type I tumors had high COX-2 expression, while type II tumors had high COX-1 expression. In multivariable adjusted regression models, higher COX-1 mRNA expression was associated with shorter DFS (HR: 6.37, 95% CI: 1.84-22.01) and OS (HR: 2.26, 95% CI: 1.04-4.91), while higher H-scores for COX-2 expression were associated with shorter DFS (HR: 1.92, 95% CI: 1.06-3.49). Stratified analysis indicated that COX-2 was significantly associated with DFS among cases with Type II tumors (HR: 1.93, 95% CI: 1.06-3.53).
CONCLUSIONS - These findings suggest that ovarian tumor type contributes to differences in COX expression levels and associations with survival.
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16 MeSH Terms
Blood type, ABO genetic variants, and ovarian cancer survival.
Cozzi GD, Levinson RT, Toole H, Snyder MR, Deng A, Crispens MA, Khabele D, Beeghly-Fadiel A
(2017) PLoS One 12: e0175119
MeSH Terms: ABO Blood-Group System, Female, Genetic Variation, Genotype, Humans, Middle Aged, Ovarian Neoplasms, Phenotype, Prognosis, Retrospective Studies, Survival Analysis
Show Abstract · Added March 21, 2018
OBJECTIVE - Blood type A and the A1 allele have been associated with increased ovarian cancer risk. With only two small studies published to date, evidence for an association between ABO blood type and ovarian cancer survival is limited.
METHODS - We conducted a retrospective cohort study of Tumor Registry confirmed ovarian cancer cases from the Vanderbilt University Medical Center with blood type from linked laboratory reports and ABO variants from linked Illumina Exome BeadChip data. Associations with overall survival (OS) were quantified by hazard ratios (HR) and confidence intervals (CI) from proportional hazards regression models; covariates included age, race, stage, grade, histologic subtype, and year of diagnosis.
RESULTS - ABO phenotype (N = 694) and/or genotype (N = 154) data were available for 713 predominantly Caucasian (89.3%) cases. In multivariable models, blood type A had significantly better OS compared to either O (HR: 0.75, 95% CI: 0.60-0.93) or all non-A (HR: 0.77, 95% CI: 0.63-0.94) cases. Similarly, missense rs1053878 minor allele carriers (A2) had better OS (HR: 0.50, 95% CI: 0.25-0.99). Among Caucasians, this phenotype association was strengthened, but the genotype association was attenuated; instead, four variants sharing moderate linkage disequilibrium with the O variant were associated with better OS (HR: 0.62, 95% CI: 0.39-0.99) in unadjusted models.
CONCLUSIONS - Blood type A was significantly associated with longer ovarian cancer survival in the largest such study to date. This finding was supported by genetic analysis, which implicated the A2 allele, although O related variants also had suggestive associations. Further research on ABO and ovarian cancer survival is warranted.
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11 MeSH Terms
Use of common analgesic medications and ovarian cancer survival: results from a pooled analysis in the Ovarian Cancer Association Consortium.
Dixon SC, Nagle CM, Wentzensen N, Trabert B, Beeghly-Fadiel A, Schildkraut JM, Moysich KB, deFazio A, Australian Ovarian Cancer Study Group, Risch HA, Rossing MA, Doherty JA, Wicklund KG, Goodman MT, Modugno F, Ness RB, Edwards RP, Jensen A, Kjær SK, Høgdall E, Berchuck A, Cramer DW, Terry KL, Poole EM, Bandera EV, Paddock LE, Anton-Culver H, Ziogas A, Menon U, Gayther SA, Ramus SJ, Gentry-Maharaj A, Pearce CL, Wu AH, Pike MC, Webb PM
(2017) Br J Cancer 116: 1223-1228
MeSH Terms: Acetaminophen, Adult, Aged, Analgesics, Anti-Inflammatory Agents, Non-Steroidal, Anticarcinogenic Agents, Aspirin, Disease-Free Survival, Female, Humans, Middle Aged, Ovarian Neoplasms, Proportional Hazards Models, Risk Factors
Show Abstract · Added April 18, 2017
BACKGROUND - Nonsteroidal anti-inflammatory drugs (NSAIDs) have been associated with improved survival in some cancers, but evidence for ovarian cancer is limited.
METHODS - Pooling individual-level data from 12 Ovarian Cancer Association Consortium studies, we evaluated the association between self-reported, pre-diagnosis use of common analgesics and overall/progression-free/disease-specific survival among 7694 women with invasive epithelial ovarian cancer (4273 deaths).
RESULTS - Regular analgesic use (at least once per week) was not associated with overall survival (pooled hazard ratios, pHRs (95% confidence intervals): aspirin 0.96 (0.88-1.04); non-aspirin NSAIDs 0.97 (0.89-1.05); acetaminophen 1.01 (0.93-1.10)), nor with progression-free/disease-specific survival. There was however a survival advantage for users of any NSAIDs in studies clearly defining non-use as less than once per week (pHR=0.89 (0.82-0.98)).
CONCLUSIONS - Although this study did not show a clear association between analgesic use and ovarian cancer survival, further investigation with clearer definitions of use and information about post-diagnosis use is warranted.
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14 MeSH Terms
Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.
Phelan CM, Kuchenbaecker KB, Tyrer JP, Kar SP, Lawrenson K, Winham SJ, Dennis J, Pirie A, Riggan MJ, Chornokur G, Earp MA, Lyra PC, Lee JM, Coetzee S, Beesley J, McGuffog L, Soucy P, Dicks E, Lee A, Barrowdale D, Lecarpentier J, Leslie G, Aalfs CM, Aben KKH, Adams M, Adlard J, Andrulis IL, Anton-Culver H, Antonenkova N, AOCS study group, Aravantinos G, Arnold N, Arun BK, Arver B, Azzollini J, Balmaña J, Banerjee SN, Barjhoux L, Barkardottir RB, Bean Y, Beckmann MW, Beeghly-Fadiel A, Benitez J, Bermisheva M, Bernardini MQ, Birrer MJ, Bjorge L, Black A, Blankstein K, Blok MJ, Bodelon C, Bogdanova N, Bojesen A, Bonanni B, Borg Å, Bradbury AR, Brenton JD, Brewer C, Brinton L, Broberg P, Brooks-Wilson A, Bruinsma F, Brunet J, Buecher B, Butzow R, Buys SS, Caldes T, Caligo MA, Campbell I, Cannioto R, Carney ME, Cescon T, Chan SB, Chang-Claude J, Chanock S, Chen XQ, Chiew YE, Chiquette J, Chung WK, Claes KBM, Conner T, Cook LS, Cook J, Cramer DW, Cunningham JM, D'Aloisio AA, Daly MB, Damiola F, Damirovna SD, Dansonka-Mieszkowska A, Dao F, Davidson R, DeFazio A, Delnatte C, Doheny KF, Diez O, Ding YC, Doherty JA, Domchek SM, Dorfling CM, Dörk T, Dossus L, Duran M, Dürst M, Dworniczak B, Eccles D, Edwards T, Eeles R, Eilber U, Ejlertsen B, Ekici AB, Ellis S, Elvira M, EMBRACE Study, Eng KH, Engel C, Evans DG, Fasching PA, Ferguson S, Ferrer SF, Flanagan JM, Fogarty ZC, Fortner RT, Fostira F, Foulkes WD, Fountzilas G, Fridley BL, Friebel TM, Friedman E, Frost D, Ganz PA, Garber J, García MJ, Garcia-Barberan V, Gehrig A, GEMO Study Collaborators, Gentry-Maharaj A, Gerdes AM, Giles GG, Glasspool R, Glendon G, Godwin AK, Goldgar DE, Goranova T, Gore M, Greene MH, Gronwald J, Gruber S, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hansen TVO, Harrington PA, Harris HR, Hauke J, HEBON Study, Hein A, Henderson A, Hildebrandt MAT, Hillemanns P, Hodgson S, Høgdall CK, Høgdall E, Hogervorst FBL, Holland H, Hooning MJ, Hosking K, Huang RY, Hulick PJ, Hung J, Hunter DJ, Huntsman DG, Huzarski T, Imyanitov EN, Isaacs C, Iversen ES, Izatt L, Izquierdo A, Jakubowska A, James P, Janavicius R, Jernetz M, Jensen A, Jensen UB, John EM, Johnatty S, Jones ME, Kannisto P, Karlan BY, Karnezis A, Kast K, KConFab Investigators, Kennedy CJ, Khusnutdinova E, Kiemeney LA, Kiiski JI, Kim SW, Kjaer SK, Köbel M, Kopperud RK, Kruse TA, Kupryjanczyk J, Kwong A, Laitman Y, Lambrechts D, Larrañaga N, Larson MC, Lazaro C, Le ND, Le Marchand L, Lee JW, Lele SB, Leminen A, Leroux D, Lester J, Lesueur F, Levine DA, Liang D, Liebrich C, Lilyquist J, Lipworth L, Lissowska J, Lu KH, Lubinński J, Luccarini C, Lundvall L, Mai PL, Mendoza-Fandiño G, Manoukian S, Massuger LFAG, May T, Mazoyer S, McAlpine JN, McGuire V, McLaughlin JR, McNeish I, Meijers-Heijboer H, Meindl A, Menon U, Mensenkamp AR, Merritt MA, Milne RL, Mitchell G, Modugno F, Moes-Sosnowska J, Moffitt M, Montagna M, Moysich KB, Mulligan AM, Musinsky J, Nathanson KL, Nedergaard L, Ness RB, Neuhausen SL, Nevanlinna H, Niederacher D, Nussbaum RL, Odunsi K, Olah E, Olopade OI, Olsson H, Olswold C, O'Malley DM, Ong KR, Onland-Moret NC, OPAL study group, Orr N, Orsulic S, Osorio A, Palli D, Papi L, Park-Simon TW, Paul J, Pearce CL, Pedersen IS, Peeters PHM, Peissel B, Peixoto A, Pejovic T, Pelttari LM, Permuth JB, Peterlongo P, Pezzani L, Pfeiler G, Phillips KA, Piedmonte M, Pike MC, Piskorz AM, Poblete SR, Pocza T, Poole EM, Poppe B, Porteous ME, Prieur F, Prokofyeva D, Pugh E, Pujana MA, Pujol P, Radice P, Rantala J, Rappaport-Fuerhauser C, Rennert G, Rhiem K, Rice P, Richardson A, Robson M, Rodriguez GC, Rodríguez-Antona C, Romm J, Rookus MA, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Salvesen HB, Sandler DP, Schoemaker MJ, Senter L, Setiawan VW, Severi G, Sharma P, Shelford T, Siddiqui N, Side LE, Sieh W, Singer CF, Sobol H, Song H, Southey MC, Spurdle AB, Stadler Z, Steinemann D, Stoppa-Lyonnet D, Sucheston-Campbell LE, Sukiennicki G, Sutphen R, Sutter C, Swerdlow AJ, Szabo CI, Szafron L, Tan YY, Taylor JA, Tea MK, Teixeira MR, Teo SH, Terry KL, Thompson PJ, Thomsen LCV, Thull DL, Tihomirova L, Tinker AV, Tischkowitz M, Tognazzo S, Toland AE, Tone A, Trabert B, Travis RC, Trichopoulou A, Tung N, Tworoger SS, van Altena AM, Van Den Berg D, van der Hout AH, van der Luijt RB, Van Heetvelde M, Van Nieuwenhuysen E, van Rensburg EJ, Vanderstichele A, Varon-Mateeva R, Vega A, Edwards DV, Vergote I, Vierkant RA, Vijai J, Vratimos A, Walker L, Walsh C, Wand D, Wang-Gohrke S, Wappenschmidt B, Webb PM, Weinberg CR, Weitzel JN, Wentzensen N, Whittemore AS, Wijnen JT, Wilkens LR, Wolk A, Woo M, Wu X, Wu AH, Yang H, Yannoukakos D, Ziogas A, Zorn KK, Narod SA, Easton DF, Amos CI, Schildkraut JM, Ramus SJ, Ottini L, Goodman MT, Park SK, Kelemen LE, Risch HA, Thomassen M, Offit K, Simard J, Schmutzler RK, Hazelett D, Monteiro AN, Couch FJ, Berchuck A, Chenevix-Trench G, Goode EL, Sellers TA, Gayther SA, Antoniou AC, Pharoah PDP
(2017) Nat Genet 49: 680-691
MeSH Terms: Alleles, BRCA1 Protein, BRCA2 Protein, Carcinoma, Ovarian Epithelial, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Meta-Analysis as Topic, Mutation, Neoplasms, Glandular and Epithelial, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Risk Factors, Telomere-Binding Proteins
Show Abstract · Added April 18, 2017
To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.
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17 MeSH Terms
Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus.
Lawrenson K, Kar S, McCue K, Kuchenbaeker K, Michailidou K, Tyrer J, Beesley J, Ramus SJ, Li Q, Delgado MK, Lee JM, Aittomäki K, Andrulis IL, Anton-Culver H, Arndt V, Arun BK, Arver B, Bandera EV, Barile M, Barkardottir RB, Barrowdale D, Beckmann MW, Benitez J, Berchuck A, Bisogna M, Bjorge L, Blomqvist C, Blot W, Bogdanova N, Bojesen A, Bojesen SE, Bolla MK, Bonanni B, Børresen-Dale AL, Brauch H, Brennan P, Brenner H, Bruinsma F, Brunet J, Buhari SA, Burwinkel B, Butzow R, Buys SS, Cai Q, Caldes T, Campbell I, Canniotto R, Chang-Claude J, Chiquette J, Choi JY, Claes KB, GEMO Study Collaborators, Cook LS, Cox A, Cramer DW, Cross SS, Cybulski C, Czene K, Daly MB, Damiola F, Dansonka-Mieszkowska A, Darabi H, Dennis J, Devilee P, Diez O, Doherty JA, Domchek SM, Dorfling CM, Dörk T, Dumont M, Ehrencrona H, Ejlertsen B, Ellis S, EMBRACE, Engel C, Lee E, Evans DG, Fasching PA, Feliubadalo L, Figueroa J, Flesch-Janys D, Fletcher O, Flyger H, Foretova L, Fostira F, Foulkes WD, Fridley BL, Friedman E, Frost D, Gambino G, Ganz PA, Garber J, García-Closas M, Gentry-Maharaj A, Ghoussaini M, Giles GG, Glasspool R, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Goode EL, Goodman MT, Greene MH, Gronwald J, Guénel P, Haiman CA, Hall P, Hallberg E, Hamann U, Hansen TV, Harrington PA, Hartman M, Hassan N, Healey S, Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON), Heitz F, Herzog J, Høgdall E, Høgdall CK, Hogervorst FB, Hollestelle A, Hopper JL, Hulick PJ, Huzarski T, Imyanitov EN, KConFab Investigators, Australian Ovarian Cancer Study Group, Isaacs C, Ito H, Jakubowska A, Janavicius R, Jensen A, John EM, Johnson N, Kabisch M, Kang D, Kapuscinski M, Karlan BY, Khan S, Kiemeney LA, Kjaer SK, Knight JA, Konstantopoulou I, Kosma VM, Kristensen V, Kupryjanczyk J, Kwong A, de la Hoya M, Laitman Y, Lambrechts D, Le N, De Leeneer K, Lester J, Levine DA, Li J, Lindblom A, Long J, Lophatananon A, Loud JT, Lu K, Lubinski J, Mannermaa A, Manoukian S, Le Marchand L, Margolin S, Marme F, Massuger LF, Matsuo K, Mazoyer S, McGuffog L, McLean C, McNeish I, Meindl A, Menon U, Mensenkamp AR, Milne RL, Montagna M, Moysich KB, Muir K, Mulligan AM, Nathanson KL, Ness RB, Neuhausen SL, Nevanlinna H, Nord S, Nussbaum RL, Odunsi K, Offit K, Olah E, Olopade OI, Olson JE, Olswold C, O'Malley D, Orlow I, Orr N, Osorio A, Park SK, Pearce CL, Pejovic T, Peterlongo P, Pfeiler G, Phelan CM, Poole EM, Pylkäs K, Radice P, Rantala J, Rashid MU, Rennert G, Rhenius V, Rhiem K, Risch HA, Rodriguez G, Rossing MA, Rudolph A, Salvesen HB, Sangrajrang S, Sawyer EJ, Schildkraut JM, Schmidt MK, Schmutzler RK, Sellers TA, Seynaeve C, Shah M, Shen CY, Shu XO, Sieh W, Singer CF, Sinilnikova OM, Slager S, Song H, Soucy P, Southey MC, Stenmark-Askmalm M, Stoppa-Lyonnet D, Sutter C, Swerdlow A, Tchatchou S, Teixeira MR, Teo SH, Terry KL, Terry MB, Thomassen M, Tibiletti MG, Tihomirova L, Tognazzo S, Toland AE, Tomlinson I, Torres D, Truong T, Tseng CC, Tung N, Tworoger SS, Vachon C, van den Ouweland AM, van Doorn HC, van Rensburg EJ, Van't Veer LJ, Vanderstichele A, Vergote I, Vijai J, Wang Q, Wang-Gohrke S, Weitzel JN, Wentzensen N, Whittemore AS, Wildiers H, Winqvist R, Wu AH, Yannoukakos D, Yoon SY, Yu JC, Zheng W, Zheng Y, Khanna KK, Simard J, Monteiro AN, French JD, Couch FJ, Freedman ML, Easton DF, Dunning AM, Pharoah PD, Edwards SL, Chenevix-Trench G, Antoniou AC, Gayther SA
(2016) Nat Commun 7: 12675
MeSH Terms: African Continental Ancestry Group, Alleles, Asian Continental Ancestry Group, Breast Neoplasms, Chromosomes, Human, Pair 19, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Ovarian Neoplasms, Polymorphism, Single Nucleotide, RNA, Messenger
Show Abstract · Added April 3, 2018
A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P<2 × 10(-3)). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3'-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
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13 MeSH Terms
Thresholds and timing of pre-operative thrombocytosis and ovarian cancer survival: analysis of laboratory measures from electronic medical records.
Cozzi GD, Samuel JM, Fromal JT, Keene S, Crispens MA, Khabele D, Beeghly-Fadiel A
(2016) BMC Cancer 16: 612
MeSH Terms: Aged, Electronic Health Records, Fallopian Tube Neoplasms, Female, Humans, Middle Aged, Neoplasm Staging, Ovarian Neoplasms, Peritoneal Neoplasms, Platelet Count, Preoperative Period, Prevalence, Prognosis, Retrospective Studies, Survival Analysis, Thrombocytosis
Show Abstract · Added April 18, 2017
BACKGROUND - Thrombocytosis has been associated with poor ovarian cancer prognosis. However, comparisons of thresholds to define thrombocytosis and evaluation of relevant timing of platelet measurement has not been previously conducted.
METHODS - We selected Tumor Registry confirmed ovarian, primary peritoneal, and fallopian tube cancer cases diagnosed between 1995-2013 from the Vanderbilt University Medical Center. Laboratory measured platelet values from electronic medical records (EMR) were used to determine thrombocytosis at three thresholds: a platelet count greater than 350, 400, or 450 × 10(9)/liter. Timing was evaluated with 5 intervals: on the date of diagnosis, and up to 1, 2, 4, and 8 weeks prior to the date of diagnosis. Cox regression was used to calculate hazard ratios (HR) and confidence intervals (CI) for association with overall survival; adjustment included age, stage, grade, and histologic subtype of disease.
RESULTS - Pre-diagnosis platelet measures were available for 136, 241, 280, 297, and 304 cases in the five intervals. The prevalence of thrombocytosis decreased with increasing thresholds and was generally consistent across the five time intervals, ranging from 44.8-53.2 %, 31.6-39.4 %, and 19.9-26.1 % across the three thresholds. Associations with higher grade and stage of disease gained significance as the threshold increased. With the exception of the lowest threshold on the date of diagnosis (HR350: 1.55, 95 % CI: 0.97-2.47), all other survival associations were significant, with the highest reaching twice the risk of death for thrombocytosis on the date of diagnosis (HR400: 2.01, 95 % CI: 1.25-3.23).
CONCLUSIONS - Our EMR approach yielded associations comparable to published findings from medical record abstraction approaches. In addition, our results indicate that lower thrombocytosis thresholds and platelet measures up to 8 weeks before diagnosis may inform ovarian cancer characteristics and prognosis.
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16 MeSH Terms
Panobinostat sensitizes cyclin E high, homologous recombination-proficient ovarian cancer to olaparib.
Wilson AJ, Sarfo-Kantanka K, Barrack T, Steck A, Saskowski J, Crispens MA, Khabele D
(2016) Gynecol Oncol 143: 143-151
MeSH Terms: Antineoplastic Agents, Cyclin E, DNA Repair, Drug Synergism, Female, Homologous Recombination, Humans, Hydroxamic Acids, Indoles, Oncogene Proteins, Ovarian Neoplasms, Panobinostat, Phthalazines, Piperazines
Show Abstract · Added March 4, 2019
OBJECTIVE - Homologous recombination (HR) proficient ovarian cancers, including CCNE1 (cyclin E)-amplified tumors, are resistant to poly (ADP-ribose) polymerase inhibitors (PARPi). Histone deacetylase inhibitors (HDACi) are effective in overcoming tumor resistance to DNA damaging drugs. Our goal was to determine whether panobinostat, a newly FDA-approved HDACi, can sensitize cyclin E, HR-proficient ovarian cancer cells to the PARPi olaparib.
METHODS - Expression levels of CCNE1 (cyclin E), BRCA1, RAD51 and E2F1 in ovarian tumors and cell lines were extracted from The Cancer Genome Atlas (TCGA) and Broad-Novartis Cancer Cell Line Encyclopedia (CCLE). In HR-proficient ovarian cancer cell line models (OVCAR-3, OVCAR-4, SKOV-3, and UWB1.289+BRCA1 wild-type), cell growth and viability were assessed by sulforhodamine B and xenograft assays. DNA damage and repair (pH2AX and RAD51 co-localization and DRGFP reporter activity) and apoptosis (cleaved PARP and cleaved caspase-3) were assessed by immunofluorescence and Western blot assays.
RESULTS - TCGA and CCLE data revealed positive correlations (Spearman) between cyclin E E2F1, and E2F1 gene targets related to DNA repair (BRCA1 and RAD51). Panobinostat downregulated cyclin E and HR repair pathway genes, and reduced HR efficiency in cyclin E-amplified OVCAR-3 cells. Further, panobinostat synergized with olaparib in reducing cell growth and viability in HR-proficient cells. Similar co-operative effects were observed in xenografts, and on pharmacodynamic markers of HR repair, DNA damage and apoptosis.
CONCLUSIONS - These results provide preclinical rationale for using HDACi to reduce HR in cyclin E-overexpressing and other types of HR-proficient ovarian cancer as a means of enhancing PARPi activity.
Copyright © 2016 Elsevier Inc. All rights reserved.
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Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types.
Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z, Lawrenson K, Lindstrom S, Ramus SJ, Thompson DJ, ABCTB Investigators, Kibel AS, Dansonka-Mieszkowska A, Michael A, Dieffenbach AK, Gentry-Maharaj A, Whittemore AS, Wolk A, Monteiro A, Peixoto A, Kierzek A, Cox A, Rudolph A, Gonzalez-Neira A, Wu AH, Lindblom A, Swerdlow A, AOCS Study Group & Australian Cancer Study (Ovarian Cancer), APCB BioResource, Ziogas A, Ekici AB, Burwinkel B, Karlan BY, Nordestgaard BG, Blomqvist C, Phelan C, McLean C, Pearce CL, Vachon C, Cybulski C, Slavov C, Stegmaier C, Maier C, Ambrosone CB, Høgdall CK, Teerlink CC, Kang D, Tessier DC, Schaid DJ, Stram DO, Cramer DW, Neal DE, Eccles D, Flesch-Janys D, Edwards DR, Wokozorczyk D, Levine DA, Yannoukakos D, Sawyer EJ, Bandera EV, Poole EM, Goode EL, Khusnutdinova E, Høgdall E, Song F, Bruinsma F, Heitz F, Modugno F, Hamdy FC, Wiklund F, Giles GG, Olsson H, Wildiers H, Ulmer HU, Pandha H, Risch HA, Darabi H, Salvesen HB, Nevanlinna H, Gronberg H, Brenner H, Brauch H, Anton-Culver H, Song H, Lim HY, McNeish I, Campbell I, Vergote I, Gronwald J, Lubiński J, Stanford JL, Benítez J, Doherty JA, Permuth JB, Chang-Claude J, Donovan JL, Dennis J, Schildkraut JM, Schleutker J, Hopper JL, Kupryjanczyk J, Park JY, Figueroa J, Clements JA, Knight JA, Peto J, Cunningham JM, Pow-Sang J, Batra J, Czene K, Lu KH, Herkommer K, Khaw KT, kConFab Investigators, Matsuo K, Muir K, Offitt K, Chen K, Moysich KB, Aittomäki K, Odunsi K, Kiemeney LA, Massuger LF, Fitzgerald LM, Cook LS, Cannon-Albright L, Hooning MJ, Pike MC, Bolla MK, Luedeke M, Teixeira MR, Goodman MT, Schmidt MK, Riggan M, Aly M, Rossing MA, Beckmann MW, Moisse M, Sanderson M, Southey MC, Jones M, Lush M, Hildebrandt MA, Hou MF, Schoemaker MJ, Garcia-Closas M, Bogdanova N, Rahman N, NBCS Investigators, Le ND, Orr N, Wentzensen N, Pashayan N, Peterlongo P, Guénel P, Brennan P, Paulo P, Webb PM, Broberg P, Fasching PA, Devilee P, Wang Q, Cai Q, Li Q, Kaneva R, Butzow R, Kopperud RK, Schmutzler RK, Stephenson RA, MacInnis RJ, Hoover RN, Winqvist R, Ness R, Milne RL, Travis RC, Benlloch S, Olson SH, McDonnell SK, Tworoger SS, Maia S, Berndt S, Lee SC, Teo SH, Thibodeau SN, Bojesen SE, Gapstur SM, Kjær SK, Pejovic T, Tammela TL, GENICA Network, PRACTICAL consortium, Dörk T, Brüning T, Wahlfors T, Key TJ, Edwards TL, Menon U, Hamann U, Mitev V, Kosma VM, Setiawan VW, Kristensen V, Arndt V, Vogel W, Zheng W, Sieh W, Blot WJ, Kluzniak W, Shu XO, Gao YT, Schumacher F, Freedman ML, Berchuck A, Dunning AM, Simard J, Haiman CA, Spurdle A, Sellers TA, Hunter DJ, Henderson BE, Kraft P, Chanock SJ, Couch FJ, Hall P, Gayther SA, Easton DF, Chenevix-Trench G, Eeles R, Pharoah PD, Lambrechts D
(2016) Cancer Discov 6: 1052-67
MeSH Terms: Breast Neoplasms, Case-Control Studies, Chromosome Mapping, Datasets as Topic, Enhancer Elements, Genetic, Female, Gene Regulatory Networks, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Meta-Analysis as Topic, Organ Specificity, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Quantitative Trait Loci, Signal Transduction
Show Abstract · Added April 26, 2017
UNLABELLED - Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.
SIGNIFICANCE - We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
©2016 American Association for Cancer Research.
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