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Cuellar-Partida G, Lu Y, Dixon SC, Fasching PA, Hein A, Burghaus S, Beckmann MW, Lambrechts D, Van Nieuwenhuysen E, Vergote I, Vanderstichele A, Doherty JA, Rossing MA, Chang-Claude J, Rudolph A, Wang-Gohrke S, Goodman MT, Bogdanova N, Dörk T, Dürst M, Hillemanns P, Runnebaum IB, Antonenkova N, Butzow R, Leminen A, Nevanlinna H, Pelttari LM, Edwards RP, Kelley JL, Modugno F, Moysich KB, Ness RB, Cannioto R, Høgdall E, Høgdall C, Jensen A, Giles GG, Bruinsma F, Kjaer SK, Hildebrandt MAT, Liang D, Lu KH, Wu X, Bisogna M, Dao F, Levine DA, Cramer DW, Terry KL, Tworoger SS, Stampfer M, Missmer S, Bjorge L, Salvesen HB, Kopperud RK, Bischof K, Aben KKH, Kiemeney LA, Massuger LFAG, Brooks-Wilson A, Olson SH, McGuire V, Rothstein JH, Sieh W, Whittemore AS, Cook LS, Le ND, Blake Gilks C, Gronwald J, Jakubowska A, Lubiński J, Kluz T, Song H, Tyrer JP, Wentzensen N, Brinton L, Trabert B, Lissowska J, McLaughlin JR, Narod SA, Phelan C, Anton-Culver H, Ziogas A, Eccles D, Campbell I, Gayther SA, Gentry-Maharaj A, Menon U, Ramus SJ, Wu AH, Dansonka-Mieszkowska A, Kupryjanczyk J, Timorek A, Szafron L, Cunningham JM, Fridley BL, Winham SJ, Bandera EV, Poole EM, Morgan TK, Goode EL, Schildkraut JM, Pearce CL, Berchuck A, Pharoah PDP, Webb PM, Chenevix-Trench G, Risch HA, MacGregor S. Assessing the genetic architecture of epithelial ovarian cancer histological subtypes. Hum Genet 2016; 135:741-56. [PMID: 27075448 PMCID: PMC4976079 DOI: 10.1007/s00439-016-1663-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2016] [Accepted: 03/24/2016] [Indexed: 10/22/2022]
Abstract
Epithelial ovarian cancer (EOC) is one of the deadliest common cancers. The five most common types of disease are high-grade and low-grade serous, endometrioid, mucinous and clear cell carcinoma. Each of these subtypes present distinct molecular pathogeneses and sensitivities to treatments. Recent studies show that certain genetic variants confer susceptibility to all subtypes while other variants are subtype-specific. Here, we perform an extensive analysis of the genetic architecture of EOC subtypes. To this end, we used data of 10,014 invasive EOC patients and 21,233 controls from the Ovarian Cancer Association Consortium genotyped in the iCOGS array (211,155 SNPs). We estimate the array heritability (attributable to variants tagged on arrays) of each subtype and their genetic correlations. We also look for genetic overlaps with factors such as obesity, smoking behaviors, diabetes, age at menarche and height. We estimated the array heritabilities of high-grade serous disease ([Formula: see text] = 8.8 ± 1.1 %), endometrioid ([Formula: see text] = 3.2 ± 1.6 %), clear cell ([Formula: see text] = 6.7 ± 3.3 %) and all EOC ([Formula: see text] = 5.6 ± 0.6 %). Known associated loci contributed approximately 40 % of the total array heritability for each subtype. The contribution of each chromosome to the total heritability was not proportional to chromosome size. Through bivariate and cross-trait LD score regression, we found evidence of shared genetic backgrounds between the three high-grade subtypes: serous, endometrioid and undifferentiated. Finally, we found significant genetic correlations of all EOC with diabetes and obesity using a polygenic prediction approach.
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Dixon SC, Nagle CM, Thrift AP, Pharoah PD, Pearce CL, Zheng W, Painter JN, Chenevix-Trench G, Fasching PA, Beckmann MW, Lambrechts D, Vergote I, Lambrechts S, Van Nieuwenhuysen E, Rossing MA, Doherty JA, Wicklund KG, Chang-Claude J, Rudolph A, Moysich KB, Odunsi K, Goodman MT, Wilkens LR, Thompson PJ, Shvetsov YB, Dörk T, Park-Simon TW, Hillemanns P, Bogdanova N, Butzow R, Nevanlinna H, Pelttari LM, Leminen A, Modugno F, Ness RB, Edwards RP, Kelley JL, Heitz F, Karlan BY, Kjær SK, Høgdall E, Jensen A, Goode EL, Fridley BL, Cunningham JM, Winham SJ, Giles GG, Bruinsma F, Milne RL, Southey MC, Hildebrandt MAT, Wu X, Lu KH, Liang D, Levine DA, Bisogna M, Schildkraut JM, Berchuck A, Cramer DW, Terry KL, Bandera EV, Olson SH, Salvesen HB, Thomsen LC, Kopperud RK, Bjorge L, Kiemeney LA, Massuger LFAG, Pejovic T, Cook LS, Le ND, Swenerton KD, Brooks-Wilson A, Kelemen LE, Lubiński J, Huzarski T, Gronwald J, Menkiszak J, Wentzensen N, Brinton L, Yang H, Lissowska J, Høgdall CK, Lundvall L, Song H, Tyrer JP, Campbell I, Eccles D, Paul J, Glasspool R, Siddiqui N, Whittemore AS, Sieh W, McGuire V, Rothstein JH, Narod SA, Phelan C, Risch HA, McLaughlin JR, Anton-Culver H, Ziogas A, Menon U, Gayther SA, Ramus SJ, Gentry-Maharaj A, Wu AH, Pike MC, Tseng CC, Kupryjanczyk J, Dansonka-Mieszkowska A, Budzilowska A, Spiewankiewicz B, Webb PM. Adult body mass index and risk of ovarian cancer by subtype: a Mendelian randomization study. Int J Epidemiol 2016; 45:884-95. [PMID: 27401727 PMCID: PMC5644573 DOI: 10.1093/ije/dyw158] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/07/2016] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Observational studies have reported a positive association between body mass index (BMI) and ovarian cancer risk. However, questions remain as to whether this represents a causal effect, or holds for all histological subtypes. The lack of association observed for serous cancers may, for instance, be due to disease-associated weight loss. Mendelian randomization (MR) uses genetic markers as proxies for risk factors to overcome limitations of observational studies. We used MR to elucidate the relationship between BMI and ovarian cancer, hypothesizing that genetically predicted BMI would be associated with increased risk of non-high grade serous ovarian cancers (non-HGSC) but not HGSC. METHODS We pooled data from 39 studies (14 047 cases, 23 003 controls) in the Ovarian Cancer Association Consortium. We constructed a weighted genetic risk score (GRS, partial F-statistic = 172), summing alleles at 87 single nucleotide polymorphisms previously associated with BMI, weighting by their published strength of association with BMI. Applying two-stage predictor-substitution MR, we used logistic regression to estimate study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted BMI and risk, and pooled these using random-effects meta-analysis. RESULTS Higher genetically predicted BMI was associated with increased risk of non-HGSC (pooled OR = 1.29, 95% CI 1.03-1.61 per 5 units BMI) but not HGSC (pooled OR = 1.06, 95% CI 0.88-1.27). Secondary analyses stratified by behaviour/subtype suggested that, consistent with observational data, the association was strongest for low-grade/borderline serous cancers (OR = 1.93, 95% CI 1.33-2.81). CONCLUSIONS Our data suggest that higher BMI increases risk of non-HGSC, but not the more common and aggressive HGSC subtype, confirming the observational evidence.
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Hollestelle A, van der Baan FH, Berchuck A, Johnatty SE, Aben KK, Agnarsson BA, Aittomäki K, Alducci E, Andrulis IL, Anton-Culver H, Antonenkova NN, Antoniou AC, Apicella C, Arndt V, Arnold N, Arun BK, Arver B, Ashworth A, Baglietto L, Balleine R, Bandera EV, Barrowdale D, Bean YT, Beckmann L, Beckmann MW, Benitez J, Berger A, Berger R, Beuselinck B, Bisogna M, Bjorge L, Blomqvist C, Bogdanova NV, Bojesen A, Bojesen SE, Bolla MK, Bonanni B, Brand JS, Brauch H, Brenner H, Brinton L, Brooks-Wilson A, Bruinsma F, Brunet J, Brüning T, Budzilowska A, Bunker CH, Burwinkel B, Butzow R, Buys SS, Caligo MA, Campbell I, Carter J, Chang-Claude J, Chanock SJ, Claes KBM, Collée JM, Cook LS, Couch FJ, Cox A, Cramer D, Cross SS, Cunningham JM, Cybulski C, Czene K, Damiola F, Dansonka-Mieszkowska A, Darabi H, de la Hoya M, deFazio A, Dennis J, Devilee P, Dicks EM, Diez O, Doherty JA, Domchek SM, Dorfling CM, Dörk T, Silva IDS, du Bois A, Dumont M, Dunning AM, Duran M, Easton DF, Eccles D, Edwards RP, Ehrencrona H, Ejlertsen B, Ekici AB, Ellis SD, Engel C, Eriksson M, Fasching PA, Feliubadalo L, Figueroa J, Flesch-Janys D, Fletcher O, Fontaine A, Fortuzzi S, Fostira F, Fridley BL, Friebel T, Friedman E, Friel G, Frost D, Garber J, García-Closas M, Gayther SA, Gentry-Maharaj A, Gerdes AM, Giles GG, Glasspool R, Glendon G, Godwin AK, Goodman MT, Gore M, Greene MH, Grip M, Gronwald J, Gschwantler Kaulich D, Guénel P, Guzman SR, Haeberle L, Haiman CA, Hall P, Halverson SL, Hamann U, Hansen TVO, Harter P, Hartikainen JM, Healey S, Hein A, Heitz F, Henderson BE, Herzog J, T Hildebrandt MA, Høgdall CK, Høgdall E, Hogervorst FBL, Hopper JL, Humphreys K, Huzarski T, Imyanitov EN, Isaacs C, Jakubowska A, Janavicius R, Jaworska K, Jensen A, Jensen UB, Johnson N, Jukkola-Vuorinen A, Kabisch M, Karlan BY, Kataja V, Kauff N, Kelemen LE, Kerin MJ, Kiemeney LA, Kjaer SK, Knight JA, Knol-Bout JP, Konstantopoulou I, Kosma VM, Krakstad C, Kristensen V, Kuchenbaecker KB, Kupryjanczyk J, Laitman Y, Lambrechts D, Lambrechts S, Larson MC, Lasa A, Laurent-Puig P, Lazaro C, Le ND, Le Marchand L, Leminen A, Lester J, Levine DA, Li J, Liang D, Lindblom A, Lindor N, Lissowska J, Long J, Lu KH, Lubinski J, Lundvall L, Lurie G, Mai PL, Mannermaa A, Margolin S, Mariette F, Marme F, Martens JWM, Massuger LFAG, Maugard C, Mazoyer S, McGuffog L, McGuire V, McLean C, McNeish I, Meindl A, Menegaux F, Menéndez P, Menkiszak J, Menon U, Mensenkamp AR, Miller N, Milne RL, Modugno F, Montagna M, Moysich KB, Müller H, Mulligan AM, Muranen TA, Narod SA, Nathanson KL, Ness RB, Neuhausen SL, Nevanlinna H, Neven P, Nielsen FC, Nielsen SF, Nordestgaard BG, Nussbaum RL, Odunsi K, Offit K, Olah E, Olopade OI, Olson JE, Olson SH, Oosterwijk JC, Orlow I, Orr N, Orsulic S, Osorio A, Ottini L, Paul J, Pearce CL, Pedersen IS, Peissel B, Pejovic T, Pelttari LM, Perkins J, Permuth-Wey J, Peterlongo P, Peto J, Phelan CM, Phillips KA, Piedmonte M, Pike MC, Platte R, Plisiecka-Halasa J, Poole EM, Poppe B, Pylkäs K, Radice P, Ramus SJ, Rebbeck TR, Reed MWR, Rennert G, Risch HA, Robson M, Rodriguez GC, Romero A, Rossing MA, Rothstein JH, Rudolph A, Runnebaum I, Salani R, Salvesen HB, Sawyer EJ, Schildkraut JM, Schmidt MK, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schrauder MG, Schumacher F, Schwaab I, Scuvera G, Sellers TA, Severi G, Seynaeve CM, Shah M, Shrubsole M, Siddiqui N, Sieh W, Simard J, Singer CF, Sinilnikova OM, Smeets D, Sohn C, Soller M, Song H, Soucy P, Southey MC, Stegmaier C, Stoppa-Lyonnet D, Sucheston L, Swerdlow A, Tangen IL, Tea MK, Teixeira MR, Terry KL, Terry MB, Thomassen M, Thompson PJ, Tihomirova L, Tischkowitz M, Toland AE, Tollenaar RAEM, Tomlinson I, Torres D, Truong T, Tsimiklis H, Tung N, Tworoger SS, Tyrer JP, Vachon CM, Van 't Veer LJ, van Altena AM, Van Asperen CJ, van den Berg D, van den Ouweland AMW, van Doorn HC, Van Nieuwenhuysen E, van Rensburg EJ, Vergote I, Verhoef S, Vierkant RA, Vijai J, Vitonis AF, von Wachenfeldt A, Walsh C, Wang Q, Wang-Gohrke S, Wappenschmidt B, Weischer M, Weitzel JN, Weltens C, Wentzensen N, Whittemore AS, Wilkens LR, Winqvist R, Wu AH, Wu X, Yang HP, Zaffaroni D, Pilar Zamora M, Zheng W, Ziogas A, Chenevix-Trench G, Pharoah PDP, Rookus MA, Hooning MJ, Goode EL. No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer. Gynecol Oncol 2016; 141:386-401. [PMID: 25940428 PMCID: PMC4630206 DOI: 10.1016/j.ygyno.2015.04.034] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2015] [Accepted: 04/19/2015] [Indexed: 12/24/2022]
Abstract
OBJECTIVE Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3' UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370. METHODS Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers). RESULTS We found no association with risk of ovarian cancer (OR=0.99, 95% CI 0.94-1.04, p=0.74) or breast cancer (OR=0.98, 95% CI 0.94-1.01, p=0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR=1.09, 95% CI 0.97-1.23, p=0.14, breast cancer HR=1.04, 95% CI 0.97-1.12, p=0.27; BRCA2, ovarian cancer HR=0.89, 95% CI 0.71-1.13, p=0.34, breast cancer HR=1.06, 95% CI 0.94-1.19, p=0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR=0.94, 95% CI 0.83-1.07, p=0.38), breast cancer (HR=0.96, 95% CI 0.87-1.06, p=0.38), and all other previously-reported associations. CONCLUSIONS rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.
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Bolton KL, Tyrer J, Song H, Ramus SJ, Notaridou M, Jones C, Sher T, Gentry-Maharaj A, Wozniak E, Tsai YY, Weidhaas J, Paik D, Van Den Berg DJ, Stram DO, Pearce CL, Wu AH, Brewster W, Anton-Culver H, Ziogas A, Narod SA, Levine DA, Kaye SB, Brown R, Paul J, Flanagan J, Sieh W, McGuire V, Whittemore AS, Campbell I, Gore ME, Lissowska J, Yang HP, Medrek K, Gronwald J, Lubinski J, Jakubowska A, Le ND, Cook LS, Kelemen LE, Brooks-Wilson A, Massuger LFAG, Kiemeney LA, Aben KKH, van Altena AM, Houlston R, Tomlinson I, Palmieri RT, Moorman PG, Schildkraut J, Iversen ES, Phelan C, Vierkant RA, Cunningham JM, Goode EL, Fridley BL, Kruger-Kjaer S, Blaeker J, Hogdall E, Hogdall C, Gross J, Karlan BY, Ness RB, Edwards RP, Odunsi K, Moyisch KB, Baker JA, Modugno F, Heikkinenen T, Butzow R, Nevanlinna H, Leminen A, Bogdanova N, Antonenkova N, Doerk T, Hillemanns P, Dürst M, Runnebaum I, Thompson PJ, Carney ME, Goodman MT, Lurie G, Wang-Gohrke S, Hein R, Chang-Claude J, Rossing MA, Cushing-Haugen KL, Doherty J, Chen C, Rafnar T, Besenbacher S, Sulem P, Stefansson K, Birrer MJ, Terry KL, Hernandez D, Cramer DW, Vergote I, Amant F, Lambrechts D, Despierre E, Fasching PA, Beckmann MW, Thiel FC, Ekici AB, Chen X, Johnatty SE, Webb PM, Beesley J, Chanock S, Garcia-Closas M, Sellers T, Easton DF, Berchuck A, Chenevix-Trench G, Pharoah PDP, Gayther SA. Corrigendum: Common variants at 19p13 are associated with susceptibility to ovarian cancer. Nat Genet 2016; 48:101. [PMID: 26711112 DOI: 10.1038/ng0116-101b] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Moskowitz D, Chang J, Ziogas A, Anton-Culver H, Clayman RV. Treatment for T1a Renal Cancer Substratified by Size: "Less is More". J Urol 2016; 196:1000-7. [PMID: 27113965 DOI: 10.1016/j.juro.2016.04.063] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/12/2016] [Indexed: 01/20/2023]
Abstract
PURPOSE Due to the widespread use of computerized tomography, the diagnosis of small renal cancers (3 cm or less) within the T1a classification continues to increase. Current treatment of these tumors includes radical nephrectomy, partial nephrectomy and thermal ablation. We used the SEER (Surveillance, Epidemiology, and End Results) Program to compare treatment modalities for these cancers based on 1 cm increments in tumor size. We examined overall survival, cancer specific survival, survival from cardiovascular disease and race based treatment disparities. MATERIALS AND METHODS In the SEER database we identified 17,716 renal cancers 3 cm or less diagnosed from 2005 to 2010 treated with radical nephrectomy, partial nephrectomy or thermal ablation. Overall survival, cancer specific survival and cardiovascular survival were determined for each treatment group, and then substratified by size in centimeters, tumor grade, age, geographical location and ethnicity. Survival was analyzed using Kaplan-Meier methods, multivariate proportional hazards models and a propensity score weighted approach. RESULTS Overall survival, cancer specific survival and cardiovascular survival were better for partial nephrectomy than radical nephrectomy in all circumstances. Thermal ablation showed equivalent overall survival to partial nephrectomy for tumors 2 cm or less. Notably, radical nephrectomy for renal tumors 3 cm or less was applied in a disparately larger number of black patients (OR 1.63, 95% CI 1.47-1.81) and Hispanic patients (OR 1.28, 95% CI 1.14-1.44). CONCLUSIONS Radical nephrectomy should be avoided for all tumors 3 cm or less. For renal cancers 2 cm or less partial nephrectomy and thermal ablation are equally effective. For tumors 2.1 to 3 cm partial nephrectomy is better than thermal ablation. We identified significant racial treatment disparities that negatively impact survival in black and Hispanic patients.
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Præstegaard C, Kjaer SK, Nielsen TSS, Jensen SM, Webb PM, Nagle CM, Høgdall E, Risch HA, Rossing MA, Doherty JA, Wicklund KG, Goodman MT, Modugno F, Moysich K, Ness RB, Edwards RP, Goode EL, Winham SJ, Fridley BL, Cramer DW, Terry KL, Schildkraut JM, Berchuck A, Bandera EV, Paddock L, Kiemeney LA, Massuger LF, Wentzensen N, Pharoah P, Song H, Whittemore AS, McGuire V, Sieh W, Rothstein J, Anton-Culver H, Ziogas A, Menon U, Gayther SA, Ramus SJ, Gentry-Maharaj A, Wu AH, Pearce CL, Pike MC, Lee AW, Chang-Claude J, Jensen A. The association between socioeconomic status and tumour stage at diagnosis of ovarian cancer: A pooled analysis of 18 case-control studies. Cancer Epidemiol 2016; 41:71-9. [PMID: 26851750 PMCID: PMC4993452 DOI: 10.1016/j.canep.2016.01.012] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2015] [Revised: 01/15/2016] [Accepted: 01/20/2016] [Indexed: 11/17/2022]
Abstract
PURPOSE Socioeconomic status (SES) is a known predictor of survival for several cancers and it has been suggested that SES differences affecting tumour stage at diagnosis may be the most important explanatory factor for this. However, only a limited number of studies have investigated SES differences in tumour stage at diagnosis of ovarian cancer. In a pooled analysis, we investigated whether SES as represented by level of education is predictive for advanced tumour stage at diagnosis of ovarian cancer, overall and by histotype. The effect of cigarette smoking and body mass index (BMI) on the association was also evaluated. METHODS From 18 case-control studies, we obtained information on 10,601 women diagnosed with epithelial ovarian cancer. Study specific odds ratios (ORs) with corresponding 95% confidence intervals (CI) were obtained from logistic regression models and combined into a pooled odds ratio (pOR) using a random effects model. RESULTS Overall, women who completed ≤high school had an increased risk of advanced tumour stage at diagnosis compared with women who completed >high school (pOR 1.15; 95% CI 1.03-1.28). The risk estimates for the different histotypes of ovarian cancer resembled that observed for ovarian cancers combined but did not reach statistical significance. Our results were unchanged when we included BMI and cigarette smoking. CONCLUSION Lower level of education was associated with an increased risk of advanced tumour stage at diagnosis of ovarian cancer. The observed socioeconomic difference in stage at diagnosis of ovarian cancer calls for further studies on how to reduce this diagnostic delay.
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Winham SJ, Pirie A, Chen YA, Larson MC, Fogarty ZC, Earp MA, Anton-Culver H, Bandera EV, Cramer D, Doherty JA, Goodman MT, Gronwald J, Karlan BY, Kjaer SK, Levine DA, Menon U, Ness RB, Pearce CL, Pejovic T, Rossing MA, Wentzensen N, Bean YT, Bisogna M, Brinton LA, Carney ME, Cunningham JM, Cybulski C, deFazio A, Dicks EM, Edwards RP, Gayther SA, Gentry-Maharaj A, Gore M, Iversen ES, Jensen A, Johnatty SE, Lester J, Lin HY, Lissowska J, Lubinski J, Menkiszak J, Modugno F, Moysich KB, Orlow I, Pike MC, Ramus SJ, Song H, Terry KL, Thompson PJ, Tyrer JP, van den Berg DJ, Vierkant RA, Vitonis AF, Walsh C, Wilkens LR, Wu AH, Yang H, Ziogas A, Berchuck A, Chenevix-Trench G, Schildkraut JM, Permuth-Wey J, Phelan CM, Pharoah PDP, Fridley BL, Sellers TA, Goode EL. Investigation of Exomic Variants Associated with Overall Survival in Ovarian Cancer. Cancer Epidemiol Biomarkers Prev 2016; 25:446-54. [PMID: 26747452 PMCID: PMC4779669 DOI: 10.1158/1055-9965.epi-15-0240] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Accepted: 11/19/2015] [Indexed: 11/16/2022] Open
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.
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Park HL, Ziogas A, Chang J, Desai B, Bessonova L, Garner C, Lee E, Neuhausen SL, Wang SS, Ma H, Clague J, Reynolds P, Lacey JV, Bernstein L, Anton-Culver H. Novel polymorphisms in caspase-8 are associated with breast cancer risk in the California Teachers Study. BMC Cancer 2016; 16:14. [PMID: 26758508 PMCID: PMC4711015 DOI: 10.1186/s12885-015-2036-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2015] [Accepted: 12/20/2015] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND The ability of tamoxifen and raloxifene to decrease breast cancer risk varies among different breast cancer subtypes. It is important to determine one's subtype-specific breast cancer risk when considering chemoprevention. A number of single nucleotide polymorphisms (SNPs), including one in caspase-8 (CASP8), have been previously associated with risk of developing breast cancer. Because caspase-8 is an important protein involved in receptor-mediated apoptosis whose activity is affected by estrogen, we hypothesized that additional SNPs in CASP8 could be associated with breast cancer risk, perhaps in a subtype-specific manner. METHODS Twelve tagging SNPs of CASP8 were analyzed in a nested case control study (1,353 cases and 1,384 controls) of non-Hispanic white women participating in the California Teachers Study. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each SNP using all, estrogen receptor (ER)-positive, ER-negative, human epidermal growth factor receptor 2 (HER2)-positive, and HER2-negative breast cancers as separate outcomes. RESULTS Several SNPs were associated with all, ER-positive, and HER2-positive breast cancers; however, after correcting for multiple comparisons (i.e., p < 0.0008), only rs2293554 was statistically significantly associated with HER2-positive breast cancer (OR = 1.98, 95% CI 1.34-2.92, uncorrected p = 0.0005). CONCLUSIONS While our results for CASP8 SNPs should be validated in other cohorts with subtype-specific information, we conclude that some SNPs in CASP8 are associated with subtype-specific breast cancer risk. This study contributes to our understanding of CASP8 SNPs and breast cancer risk by subtype.
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Amankwah EK, Lin HY, Tyrer JP, Lawrenson K, Dennis J, Chornokur G, Aben KKH, Anton-Culver H, Antonenkova N, Bruinsma F, Bandera EV, Bean YT, Beckmann MW, Bisogna M, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bunker CH, Butzow R, Campbell IG, Carty K, Chen Z, Chen YA, Chang-Claude J, Cook LS, Cramer DW, Cunningham JM, Cybulski C, Dansonka-Mieszkowska A, du Bois A, Despierre E, Dicks E, Doherty JA, Dörk T, Dürst M, Easton DF, Eccles DM, Edwards RP, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Goodman MT, Gronwald J, Harrington P, Harter P, Hasmad HN, Hein A, Heitz F, Hildebrandt MAT, Hillemanns P, Hogdall CK, Hogdall E, Hosono S, Iversen ES, Jakubowska A, Jensen A, Ji BT, Karlan BY, Jim H, Kellar M, Kiemeney LA, Krakstad C, Kjaer SK, Kupryjanczyk J, Lambrechts D, Lambrechts S, Le ND, Lee AW, Lele S, Leminen A, Lester J, Levine DA, Liang D, Lim BK, Lissowska J, Lu K, Lubinski J, Lundvall L, Massuger LFAG, Matsuo K, McGuire V, McLaughlin JR, McNeish I, Menon U, Milne RL, Modugno F, Moysich KB, Ness RB, Nevanlinna H, Eilber U, Odunsi K, Olson SH, Orlow I, Orsulic S, Weber RP, Paul J, Pearce CL, Pejovic T, Pelttari LM, Permuth-Wey J, Pike MC, Poole EM, Risch HA, Rosen B, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Rzepecka IK, Salvesen HB, Schernhammer E, Schwaab I, Shu XO, Shvetsov YB, Siddiqui N, Sieh W, Song H, Southey MC, Spiewankiewicz B, Sucheston-Campbell L, Teo SH, Terry KL, Thompson PJ, Thomsen L, Tangen IL, Tworoger SS, van Altena AM, Vierkant RA, Vergote I, Walsh CS, Wang-Gohrke S, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Wu AH, Wu X, Woo YL, Yang H, Zheng W, Ziogas A, Kelemen LE, Berchuck A, Schildkraut JM, Ramus SJ, Goode EL, Monteiro ANA, Gayther SA, Narod SA, Pharoah PDP, Sellers TA, Phelan CM. Epithelial-Mesenchymal Transition (EMT) Gene Variants and Epithelial Ovarian Cancer (EOC) Risk. Genet Epidemiol 2015; 39:689-97. [PMID: 26399219 PMCID: PMC4721602 DOI: 10.1002/gepi.21921] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Revised: 07/17/2015] [Accepted: 07/20/2015] [Indexed: 01/24/2023]
Abstract
Epithelial-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.
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Johnatty SE, Tyrer JP, Kar S, Beesley J, Lu Y, Gao B, Fasching PA, Hein A, Ekici AB, Beckmann MW, Lambrechts D, Van Nieuwenhuysen E, Vergote I, Lambrechts S, Rossing MA, Doherty JA, Chang-Claude J, Modugno F, Ness RB, Moysich KB, Levine DA, Kiemeney LA, Massuger LFAG, Gronwald J, Lubiński J, Jakubowska A, Cybulski C, Brinton L, Lissowska J, Wentzensen N, Song H, Rhenius V, Campbell I, Eccles D, Sieh W, Whittemore AS, McGuire V, Rothstein JH, Sutphen R, Anton-Culver H, Ziogas A, Gayther SA, Gentry-Maharaj A, Menon U, Ramus SJ, Pearce CL, Pike MC, Stram DO, Wu AH, Kupryjanczyk J, Dansonka-Mieszkowska A, Rzepecka IK, Spiewankiewicz B, Goodman MT, Wilkens LR, Carney ME, Thompson PJ, Heitz F, du Bois A, Schwaab I, Harter P, Pisterer J, Hillemanns P, Karlan BY, Walsh C, Lester J, Orsulic S, Winham SJ, Earp M, Larson MC, Fogarty ZC, Høgdall E, Jensen A, Kjaer SK, Fridley BL, Cunningham JM, Vierkant RA, Schildkraut JM, Iversen ES, Terry KL, Cramer DW, Bandera EV, Orlow I, Pejovic T, Bean Y, Høgdall C, Lundvall L, McNeish I, Paul J, Carty K, Siddiqui N, Glasspool R, Sellers T, Kennedy C, Chiew YE, Berchuck A, MacGregor S, Pharoah PDP, Goode EL, deFazio A, Webb PM, Chenevix-Trench G. Genome-wide Analysis Identifies Novel Loci Associated with Ovarian Cancer Outcomes: Findings from the Ovarian Cancer Association Consortium. Clin Cancer Res 2015; 21:5264-76. [PMID: 26152742 PMCID: PMC4624261 DOI: 10.1158/1078-0432.ccr-15-0632] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2015] [Accepted: 05/20/2015] [Indexed: 11/16/2022]
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.
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Galvan-Turner VB, Chang J, Ziogas A, Bristow RE. Observed-to-expected ratio for adherence to treatment guidelines as a quality of care indicator for ovarian cancer. Gynecol Oncol 2015; 139:495-9. [PMID: 26387962 PMCID: PMC5145796 DOI: 10.1016/j.ygyno.2015.09.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2015] [Revised: 09/15/2015] [Accepted: 09/17/2015] [Indexed: 11/16/2022]
Abstract
OBJECTIVE To develop an observed-to-expected ratio (O/E) for adherence to National Comprehensive Cancer Network (NCCN) ovarian cancer treatment guidelines as a risk-adjusted hospital measure of quality care correlated with disease-specific survival. METHODS Consecutive patients with stages I-IV epithelial ovarian cancer were identified from the California Cancer Registry (1/1/96-12/31/06). Using a fit logistic regression model, O/E for guideline adherence was calculated for each hospital and distributed into quartiles stratified by hospital annual case volume: lowest O/E quartile or annual hospital case volume <5, middle two O/E quartiles and volume ≥5, and highest O/E quartile and volume ≥5. A multivariable logistic regression model was used to characterize the independent effect of hospital O/E on ovarian cancer-specific survival. RESULTS Overall, 18,491 patients were treated at 405 hospitals; 37.3% received guideline adherent care. Lowest O/E hospitals (n=285) treated 4661 patients (25.2%), mean O/E=0.77±0.55 and median survival 38.9months (95%CI=36.2-42.0months). Intermediate O/E hospitals (n=85) treated 8715 patients (47.1%), mean O/E=0.87±0.17 and median survival of 50.5months (95% CI=48.4-52.8months). Highest O/E hospitals (n=35) treated 5115 patients (27.7%), mean O/E=1.34±0.14 and median survival of 53.8months (95% CI=50.2-58.2months). After controlling for other variables, treatment at highest O/E hospitals was associated with independent and statistically significant improvement in ovarian cancer-specific survival compared to intermediate O/E (HR=1.06, 95% CI=1.01-1.11) and lowest O/E (1.16, 95% CI=1.10-1.23) hospitals. CONCLUSIONS Calculation of hospital-specific O/E for NCCN treatment guideline adherence, combined with minimum case volume criterion, as a measure of ovarian cancer quality of care is feasible and is an independent predictor of survival.
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Lawrenson K, Iversen ES, Tyrer J, Weber RP, Concannon P, Hazelett DJ, Li Q, Marks JR, Berchuck A, Lee JM, Aben KKH, Anton-Culver H, Antonenkova N, Bandera EV, Bean Y, Beckmann MW, Bisogna M, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bruinsma F, Butzow R, Campbell IG, Carty K, Chang-Claude J, Chenevix-Trench G, Chen A, Chen Z, Cook LS, Cramer DW, Cunningham JM, Cybulski C, Plisiecka-Halasa J, Dennis J, Dicks E, Doherty JA, Dörk T, du Bois A, Eccles D, Easton DT, Edwards RP, Eilber U, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Goode EL, Goodman MT, Gronwald J, Harter P, Hasmad HN, Hein A, Heitz F, Hildebrandt MAT, Hillemanns P, Hogdall E, Hogdall C, Hosono S, Jakubowska A, Paul J, Jensen A, Karlan BY, Kjaer SK, Kelemen LE, Kellar M, Kelley JL, Kiemeney LA, Krakstad C, Lambrechts D, Lambrechts S, Le ND, Lee AW, Cannioto R, Leminen A, Lester J, Levine DA, Liang D, Lissowska J, Lu K, Lubinski J, Lundvall L, Massuger LFAG, Matsuo K, McGuire V, McLaughlin JR, Nevanlinna H, McNeish I, Menon U, Modugno F, Moysich KB, Narod SA, Nedergaard L, Ness RB, Noor Azmi MA, Odunsi K, Olson SH, Orlow I, Orsulic S, Pearce CL, Pejovic T, Pelttari LM, Permuth-Wey J, Phelan CM, Pike MC, Poole EM, Ramus SJ, Risch HA, Rosen B, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Rzepecka IK, Salvesen HB, Budzilowska A, Sellers TA, Shu XO, Shvetsov YB, Siddiqui N, Sieh W, Song H, Southey MC, Sucheston L, Tangen IL, Teo SH, Terry KL, Thompson PJ, Timorek A, Tworoger SS, Van Nieuwenhuysen E, Vergote I, Vierkant RA, Wang-Gohrke S, Walsh C, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Woo YL, Wu X, Wu AH, Yang H, Zheng W, Ziogas A, Coetzee GA, Freedman ML, Monteiro ANA, Moes-Sosnowska J, Kupryjanczyk J, Pharoah PD, Gayther SA, Schildkraut JM. Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer. Carcinogenesis 2015; 36:1341-53. [PMID: 26424751 PMCID: PMC4635670 DOI: 10.1093/carcin/bgv138] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 09/14/2015] [Accepted: 09/16/2015] [Indexed: 12/15/2022] Open
Abstract
Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene.
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Lu Y, Cuellar-Partida G, Painter JN, Nyholt DR, Morris AP, Fasching PA, Hein A, Burghaus S, Beckmann MW, Lambrechts D, Van Nieuwenhuysen E, Vergote I, Vanderstichele A, Doherty JA, Rossing MA, Wicklund KG, Chang-Claude J, Eilber U, Rudolph A, Wang-Gohrke S, Goodman MT, Bogdanova N, Dörk T, Dürst M, Hillemanns P, Runnebaum IB, Antonenkova N, Butzow R, Leminen A, Nevanlinna H, Pelttari LM, Edwards RP, Kelley JL, Modugno F, Moysich KB, Ness RB, Cannioto R, Høgdall E, Jensen A, Giles GG, Bruinsma F, Kjaer SK, Hildebrandt MAT, Liang D, Lu KH, Wu X, Bisogna M, Dao F, Levine DA, Cramer DW, Terry KL, Tworoger SS, Missmer S, Bjorge L, Salvesen HB, Kopperud RK, Bischof K, Aben KKH, Kiemeney LA, Massuger LFAG, Brooks-Wilson A, Olson SH, McGuire V, Rothstein JH, Sieh W, Whittemore AS, Cook LS, Le ND, Gilks CB, Gronwald J, Jakubowska A, Lubiński J, Gawełko J, Song H, Tyrer JP, Wentzensen N, Brinton L, Trabert B, Lissowska J, Mclaughlin JR, Narod SA, Phelan C, Anton-Culver H, Ziogas A, Eccles D, Gayther SA, Gentry-Maharaj A, Menon U, Ramus SJ, Wu AH, Dansonka-Mieszkowska A, Kupryjanczyk J, Timorek A, Szafron L, Cunningham JM, Fridley BL, Winham SJ, Bandera EV, Poole EM, Morgan TK, Risch HA, Goode EL, Schildkraut JM, Webb PM, Pearce CL, Berchuck A, Pharoah PDP, Montgomery GW, Zondervan KT, Chenevix-Trench G, MacGregor S. Shared genetics underlying epidemiological association between endometriosis and ovarian cancer. Hum Mol Genet 2015; 24:5955-64. [PMID: 26231222 PMCID: PMC4581608 DOI: 10.1093/hmg/ddv306] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 07/16/2015] [Accepted: 07/24/2015] [Indexed: 12/13/2022] Open
Abstract
Epidemiological studies have demonstrated associations between endometriosis and certain histotypes of ovarian cancer, including clear cell, low-grade serous and endometrioid carcinomas. We aimed to determine whether the observed associations might be due to shared genetic aetiology. To address this, we used two endometriosis datasets genotyped on common arrays with full-genome coverage (3194 cases and 7060 controls) and a large ovarian cancer dataset genotyped on the customized Illumina Infinium iSelect (iCOGS) arrays (10 065 cases and 21 663 controls). Previous work has suggested that a large number of genetic variants contribute to endometriosis and ovarian cancer (all histotypes combined) susceptibility. Here, using the iCOGS data, we confirmed polygenic architecture for most histotypes of ovarian cancer. This led us to evaluate if the polygenic effects are shared across diseases. We found evidence for shared genetic risks between endometriosis and all histotypes of ovarian cancer, except for the intestinal mucinous type. Clear cell carcinoma showed the strongest genetic correlation with endometriosis (0.51, 95% CI = 0.18-0.84). Endometrioid and low-grade serous carcinomas had similar correlation coefficients (0.48, 95% CI = 0.07-0.89 and 0.40, 95% CI = 0.05-0.75, respectively). High-grade serous carcinoma, which often arises from the fallopian tubes, showed a weaker genetic correlation with endometriosis (0.25, 95% CI = 0.11-0.39), despite the absence of a known epidemiological association. These results suggest that the epidemiological association between endometriosis and ovarian adenocarcinoma may be attributable to shared genetic susceptibility loci.
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Kar SP, Tyrer JP, Li Q, Lawrenson K, Aben KKH, Anton-Culver H, Antonenkova N, Chenevix-Trench G, Baker H, Bandera EV, Bean YT, Beckmann MW, Berchuck A, Bisogna M, Bjørge L, Bogdanova N, Brinton L, Brooks-Wilson A, Butzow R, Campbell I, Carty K, Chang-Claude J, Chen YA, Chen Z, Cook LS, Cramer D, Cunningham JM, Cybulski C, Dansonka-Mieszkowska A, Dennis J, Dicks E, Doherty JA, Dörk T, du Bois A, Dürst M, Eccles D, Easton DF, Edwards RP, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Goode EL, Goodman MT, Grownwald J, Harrington P, Harter P, Hein A, Heitz F, Hildebrandt MAT, Hillemanns P, Hogdall E, Hogdall CK, Hosono S, Iversen ES, Jakubowska A, Paul J, Jensen A, Ji BT, Karlan BY, Kjaer SK, Kelemen LE, Kellar M, Kelley J, Kiemeney LA, Krakstad C, Kupryjanczyk J, Lambrechts D, Lambrechts S, Le ND, Lee AW, Lele S, Leminen A, Lester J, Levine DA, Liang D, Lissowska J, Lu K, Lubinski J, Lundvall L, Massuger L, Matsuo K, McGuire V, McLaughlin JR, McNeish IA, Menon U, Modugno F, Moysich KB, Narod SA, Nedergaard L, Ness RB, Nevanlinna H, Odunsi K, Olson SH, Orlow I, Orsulic S, Weber RP, Pearce CL, Pejovic T, Pelttari LM, Permuth-Wey J, Phelan CM, Pike MC, Poole EM, Ramus SJ, Risch HA, Rosen B, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Rzepecka IK, Salvesen HB, Schildkraut JM, Schwaab I, Shu XO, Shvetsov YB, Siddiqui N, Sieh W, Song H, Southey MC, Sucheston-Campbell LE, Tangen IL, Teo SH, Terry KL, Thompson PJ, Timorek A, Tsai YY, Tworoger SS, van Altena AM, Van Nieuwenhuysen E, Vergote I, Vierkant RA, Wang-Gohrke S, Walsh C, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Woo YL, Wu X, Wu A, Yang H, Zheng W, Ziogas A, Sellers TA, Monteiro ANA, Freedman ML, Gayther SA, Pharoah PDP. Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk. Cancer Epidemiol Biomarkers Prev 2015; 24:1574-84. [PMID: 26209509 PMCID: PMC4592449 DOI: 10.1158/1055-9965.epi-14-1270] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Accepted: 06/29/2015] [Indexed: 12/19/2022] Open
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 < 0.05 and FDR < 0.05). These results were replicated (P < 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.
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Lawrenson K, Li Q, Kar S, Seo JH, Tyrer J, Spindler TJ, Lee J, Chen Y, Karst A, Drapkin R, Aben KKH, Anton-Culver H, Antonenkova N, Baker H, Bandera EV, Bean Y, Beckmann MW, Berchuck A, Bisogna M, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bruinsma F, Butzow R, Campbell IG, Carty K, Chang-Claude J, Chenevix-Trench G, Chen A, Chen Z, Cook LS, Cramer DW, Cunningham JM, Cybulski C, Dansonka-Mieszkowska A, Dennis J, Dicks E, Doherty JA, Dörk T, du Bois A, Dürst M, Eccles D, Easton DT, Edwards RP, Eilber U, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Goode EL, Goodman MT, Grownwald J, Harrington P, Harter P, Hasmad HN, Hein A, Heitz F, Hildebrandt MAT, Hillemanns P, Hogdall E, Hogdall C, Hosono S, Iversen ES, Jakubowska A, James P, Jensen A, Ji BT, Karlan BY, Kruger Kjaer S, Kelemen LE, Kellar M, Kelley JL, Kiemeney LA, Krakstad C, Kupryjanczyk J, Lambrechts D, Lambrechts S, Le ND, Lee AW, Lele S, Leminen A, Lester J, Levine DA, Liang D, Lissowska J, Lu K, Lubinski J, Lundvall L, Massuger LFAG, Matsuo K, McGuire V, McLaughlin JR, Nevanlinna H, McNeish I, Menon U, Modugno F, Moysich KB, Narod SA, Nedergaard L, Ness RB, Azmi MAN, Odunsi K, Olson SH, Orlow I, Orsulic S, Weber RP, Pearce CL, Pejovic T, Pelttari LM, Permuth-Wey J, Phelan CM, Pike MC, Poole EM, Ramus SJ, Risch HA, Rosen B, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Rzepecka IK, Salvesen HB, Schildkraut JM, Schwaab I, Sellers TA, Shu XO, Shvetsov YB, Siddiqui N, Sieh W, Song H, Southey MC, Sucheston L, Tangen IL, Teo SH, Terry KL, Thompson PJ, Timorek A, Tsai YY, Tworoger SS, van Altena AM, Van Nieuwenhuysen E, Vergote I, Vierkant RA, Wang-Gohrke S, Walsh C, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Woo YL, Wu X, Wu AH, Yang H, Zheng W, Ziogas A, Monteiro A, Pharoah PD, Gayther SA, Freedman ML. Cis-eQTL analysis and functional validation of candidate susceptibility genes for high-grade serous ovarian cancer. Nat Commun 2015; 6:8234. [PMID: 26391404 PMCID: PMC4580986 DOI: 10.1038/ncomms9234] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Accepted: 07/31/2015] [Indexed: 12/23/2022] Open
Abstract
Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.
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Jim HSL, Lin HY, Tyrer JP, Lawrenson K, Dennis J, Chornokur G, Chen Z, Chen AY, Permuth-Wey J, Aben KK, Anton-Culver H, Antonenkova N, Bruinsma F, Bandera EV, Bean YT, Beckmann MW, Bisogna M, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bunker CH, Butzow R, Campbell IG, Carty K, Chang-Claude J, Cook LS, Cramer DW, Cunningham JM, Cybulski C, Dansonka-Mieszkowska A, du Bois A, Despierre E, Sieh W, Doherty JA, Dörk T, Dürst M, Easton DF, Eccles DM, Edwards RP, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Goodman MT, Gronwald J, Harter P, Hasmad HN, Hein A, Heitz F, Hildebrandt MAT, Hillemanns P, Hogdall CK, Hogdall E, Hosono S, Iversen ES, Jakubowska A, Jensen A, Ji BT, Karlan BY, Kellar M, Kiemeney LA, Krakstad C, Kjaer SK, Kupryjanczyk J, Vierkant RA, Lambrechts D, Lambrechts S, Le ND, Lee AW, Lele S, Leminen A, Lester J, Levine DA, Liang D, Lim BK, Lissowska J, Lu K, Lubinski J, Lundvall L, Massuger LFAG, Matsuo K, McGuire V, McLaughlin JR, McNeish I, Menon U, Milne RL, Modugno F, Thomsen L, Moysich KB, Ness RB, Nevanlinna H, Eilber U, Odunsi K, Olson SH, Orlow I, Orsulic S, Palmieri Weber R, Paul J, Pearce CL, Pejovic T, Pelttari LM, Pike MC, Poole EM, Schernhammer E, Risch HA, Rosen B, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Rzepecka IK, Salvesen HB, Schwaab I, Shu XO, Shvetsov YB, Siddiqui N, Song H, Southey MC, Spiewankiewicz B, Sucheston-Campbell L, Teo SH, Terry KL, Thompson PJ, Tangen IL, Tworoger SS, van Altena AM, Vergote I, Walsh CS, Wang-Gohrke S, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Wu AH, Wu X, Woo YL, Yang H, Zheng W, Ziogas A, Amankwah E, Berchuck A, Schildkraut JM, Kelemen LE, Ramus SJ, Monteiro ANA, Goode EL, Narod SA, Gayther SA, Pharoah PDP, Sellers TA, Phelan CM. Common Genetic Variation in Circadian Rhythm Genes and Risk of Epithelial Ovarian Cancer (EOC). ACTA ACUST UNITED AC 2015; 2. [PMID: 26807442 PMCID: PMC4722961 DOI: 10.23937/2378-3648/1410017] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Disruption in circadian gene expression, whether due to genetic variation or environmental factors (e.g., light at night, shiftwork), is associated with increased incidence of breast, prostate, gastrointestinal and hematologic cancers and gliomas. Circadian genes are highly expressed in the ovaries where they regulate ovulation; circadian disruption is associated with several ovarian cancer risk factors (e.g., endometriosis). However, no studies have examined variation in germline circadian genes as predictors of ovarian cancer risk and invasiveness. The goal of the current study was to examine single nucleotide polymorphisms (SNPs) in circadian genes BMAL1, CRY2, CSNK1E, NPAS2, PER3, REV1 and TIMELESS and downstream transcription factors KLF10 and SENP3 as predictors of risk of epithelial ovarian cancer (EOC) and histopathologic subtypes. The study included a test set of 3,761 EOC cases and 2,722 controls and a validation set of 44,308 samples including 18,174 (10,316 serous) cases and 26,134 controls from 43 studies participating in the Ovarian Cancer Association Consortium (OCAC). Analysis of genotype data from 36 genotyped SNPs and 4600 imputed SNPs indicated that the most significant association was rs117104877 in BMAL1 (OR = 0.79, 95% CI = 0.68-0.90, p = 5.59 × 10-4]. Functional analysis revealed a significant down regulation of BMAL1 expression following cMYC overexpression and increasing transformation in ovarian surface epithelial (OSE) cells as well as alternative splicing of BMAL1 exons in ovarian and granulosa cells. These results suggest that variation in circadian genes, and specifically BMAL1, may be associated with risk of ovarian cancer, likely through disruption of hormonal pathways.
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Park HL, Tran SM, Lee J, Goodman D, Ziogas A, Kelly R, Larsen KM, Alvarez A, Tannous C, Strope J, Lynch W, Anton-Culver H. Clinical Implementation of a Breast Cancer Risk Assessment Program in a Multiethnic Patient Population: Which Risk Model to Use? Breast J 2015; 21:562-4. [PMID: 26227105 DOI: 10.1111/tbj.12461] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Nagle CM, Dixon SC, Jensen A, Kjaer SK, Modugno F, deFazio A, Fereday S, Hung J, Johnatty SE, Fasching PA, Beckmann MW, Lambrechts D, Vergote I, Van Nieuwenhuysen E, Lambrechts S, Risch HA, Rossing MA, Doherty JA, Wicklund KG, Chang-Claude J, Goodman MT, Ness RB, Moysich K, Heitz F, du Bois A, Harter P, Schwaab I, Matsuo K, Hosono S, Goode EL, Vierkant RA, Larson MC, Fridley BL, Høgdall C, Schildkraut JM, Weber RP, Cramer DW, Terry KL, Bandera EV, Paddock L, Rodriguez-Rodriguez L, Wentzensen N, Yang HP, Brinton LA, Lissowska J, Høgdall E, Lundvall L, Whittemore A, McGuire V, Sieh W, Rothstein J, Sutphen R, Anton-Culver H, Ziogas A, Pearce CL, Wu AH, Webb PM. Obesity and survival among women with ovarian cancer: results from the Ovarian Cancer Association Consortium. Br J Cancer 2015; 113:817-26. [PMID: 26151456 PMCID: PMC4559823 DOI: 10.1038/bjc.2015.245] [Citation(s) in RCA: 97] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Revised: 06/01/2015] [Accepted: 06/10/2015] [Indexed: 12/15/2022] Open
Abstract
Background: Observational studies have reported a modest association between obesity and risk of ovarian cancer; however, whether it is also associated with survival and whether this association varies for the different histologic subtypes are not clear. We undertook an international collaborative analysis to assess the association between body mass index (BMI), assessed shortly before diagnosis, progression-free survival (PFS), ovarian cancer-specific survival and overall survival (OS) among women with invasive ovarian cancer. Methods: We used original data from 21 studies, which included 12 390 women with ovarian carcinoma. We combined study-specific adjusted hazard ratios (HRs) using random-effects models to estimate pooled HRs (pHR). We further explored associations by histologic subtype. Results: Overall, 6715 (54%) deaths occurred during follow-up. A significant OS disadvantage was observed for women who were obese (BMI: 30–34.9, pHR: 1.10 (95% confidence intervals (CIs): 0.99–1.23); BMI: ⩾35, pHR: 1.12 (95% CI: 1.01–1.25)). Results were similar for PFS and ovarian cancer-specific survival. In analyses stratified by histologic subtype, associations were strongest for women with low-grade serous (pHR: 1.12 per 5 kg m−2) and endometrioid subtypes (pHR: 1.08 per 5 kg m−2), and more modest for the high-grade serous (pHR: 1.04 per 5 kg m−2) subtype, but only the association with high-grade serous cancers was significant. Conclusions: Higher BMI is associated with adverse survival among the majority of women with ovarian cancer.
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Darabi H, McCue K, Beesley J, Michailidou K, Nord S, Kar S, Humphreys K, Thompson D, Ghoussaini M, Bolla MK, Dennis J, Wang Q, Canisius S, Scott CG, Apicella C, Hopper JL, Southey MC, Stone J, Broeks A, Schmidt MK, Scott RJ, Lophatananon A, Muir K, Beckmann MW, Ekici AB, Fasching PA, Heusinger K, Dos-Santos-Silva I, Peto J, Tomlinson I, Sawyer EJ, Burwinkel B, Marme F, Guénel P, Truong T, Bojesen SE, Flyger H, Benitez J, González-Neira A, Anton-Culver H, Neuhausen SL, Arndt V, Brenner H, Engel C, Meindl A, Schmutzler RK, Arnold N, Brauch H, Hamann U, Chang-Claude J, Khan S, Nevanlinna H, Ito H, Matsuo K, Bogdanova NV, Dörk T, Lindblom A, Margolin S, Kosma VM, Mannermaa A, Tseng CC, Wu AH, Floris G, Lambrechts D, Rudolph A, Peterlongo P, Radice P, Couch FJ, Vachon C, Giles GG, McLean C, Milne RL, Dugué PA, Haiman CA, Maskarinec G, Woolcott C, Henderson BE, Goldberg MS, Simard J, Teo SH, Mariapun S, Helland Å, Haakensen V, Zheng W, Beeghly-Fadiel A, Tamimi R, Jukkola-Vuorinen A, Winqvist R, Andrulis IL, Knight JA, Devilee P, Tollenaar RAEM, Figueroa J, García-Closas M, Czene K, Hooning MJ, Tilanus-Linthorst M, Li J, Gao YT, Shu XO, Cox A, Cross SS, Luben R, Khaw KT, Choi JY, Kang D, Hartman M, Lim WY, Kabisch M, Torres D, Jakubowska A, Lubinski J, McKay J, Sangrajrang S, Toland AE, Yannoukakos D, Shen CY, Yu JC, Ziogas A, Schoemaker MJ, Swerdlow A, Borresen-Dale AL, Kristensen V, French JD, Edwards SL, Dunning AM, Easton DF, Hall P, Chenevix-Trench G. Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression. Am J Hum Genet 2015; 97:22-34. [PMID: 26073781 PMCID: PMC4572510 DOI: 10.1016/j.ajhg.2015.05.002] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2015] [Accepted: 05/01/2015] [Indexed: 12/13/2022] Open
Abstract
Genome-wide association studies have identified SNPs near ZNF365 at 10q21.2 that are associated with both breast cancer risk and mammographic density. To identify the most likely causal SNPs, we fine mapped the association signal by genotyping 428 SNPs across the region in 89,050 European and 12,893 Asian case and control subjects from the Breast Cancer Association Consortium. We identified four independent sets of correlated, highly trait-associated variants (iCHAVs), three of which were located within ZNF365. The most strongly risk-associated SNP, rs10995201 in iCHAV1, showed clear evidence of association with both estrogen receptor (ER)-positive (OR = 0.85 [0.82-0.88]) and ER-negative (OR = 0.87 [0.82-0.91]) disease, and was also the SNP most strongly associated with percent mammographic density. iCHAV2 (lead SNP, chr10: 64,258,684:D) and iCHAV3 (lead SNP, rs7922449) were also associated with ER-positive (OR = 0.93 [0.91-0.95] and OR = 1.06 [1.03-1.09]) and ER-negative (OR = 0.95 [0.91-0.98] and OR = 1.08 [1.04-1.13]) disease. There was weaker evidence for iCHAV4, located 5' of ADO, associated only with ER-positive breast cancer (OR = 0.93 [0.90-0.96]). We found 12, 17, 18, and 2 candidate causal SNPs for breast cancer in iCHAVs 1-4, respectively. Chromosome conformation capture analysis showed that iCHAV2 interacts with the ZNF365 and NRBF2 (more than 600 kb away) promoters in normal and cancerous breast epithelial cells. Luciferase assays did not identify SNPs that affect transactivation of ZNF365, but identified a protective haplotype in iCHAV2, associated with silencing of the NRBF2 promoter, implicating this gene in the etiology of breast cancer.
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Bristow RE, Chang J, Ziogas A, Gillen DL, Bai L, Vieira VM. Spatial analysis of advanced-stage ovarian cancer mortality in California. Am J Obstet Gynecol 2015; 213:43.e1-43.e8. [PMID: 25644440 PMCID: PMC4485540 DOI: 10.1016/j.ajog.2015.01.045] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2014] [Revised: 11/10/2014] [Accepted: 01/28/2015] [Indexed: 01/22/2023]
Abstract
OBJECTIVE We sought to determine the impact of geographic location on advanced-stage ovarian cancer mortality in relation to adherence to National Comprehensive Cancer Network (NCCN) treatment guidelines and hospital case volume. STUDY DESIGN This was a retrospective observational cohort study of patients diagnosed with stage IIIC/IV epithelial ovarian cancer (Jan. 1, 1996, through Dec. 31, 2006) identified from the California Cancer Registry. Generalized additive models were created to assess the effect of spatial distributions of geographic location, demographic characteristics, disease-related variables, adherence to NCCN guidelines, and hospital case volume, with simultaneous smoothing of geographic location and adjustment for confounding variables. RESULTS A total of 11,765 patients were identified. Twelve of the 378 hospitals (3.2%) were high-volume hospitals (HVH) (≥20 cases/y) and cared for 2112 patients (17.9%). For all patients, the median distance to an HVH was 22.7 km/14.1 miles and 80% were located within 79.6 km/49.5 miles of an HVH. Overall, 45.4% of patients were treated according to NCCN guidelines. The global test for location revealed that geographic position within the state was significantly correlated with ovarian cancer mortality after adjusting for other variables (P < .001). Distance to receive care ≥32 km/20 miles was protective against mortality (hazard ratio [HR], 0.86; 95% confidence interval [CI], 0.79-0.93), while distance from an HVH ≥80 km/50 miles was associated with an increased risk of death (HR, 1.13; 95% CI, 1.03-1.23). The effects of geographic predictors were attenuated when nonadherence to NCCN guidelines (HR, 1.25; 95% CI, 1.18-1.32) and care at an HVH (HR, 0.87; 95% CI, 0.81-0.93) were introduced into the model. CONCLUSION Geographic location is a significant predictor of advanced-stage ovarian cancer mortality and the effect is primarily related to the likelihood of receiving NCCN guideline adherent care and treatment at an HVH.
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Chornokur G, Lin HY, Tyrer JP, Lawrenson K, Dennis J, Amankwah EK, Qu X, Tsai YY, Jim HSL, Chen Z, Chen AY, Permuth-Wey J, Aben KKH, Anton-Culver H, Antonenkova N, Bruinsma F, Bandera EV, Bean YT, Beckmann MW, Bisogna M, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bunker CH, Butzow R, Campbell IG, Carty K, Chang-Claude J, Cook LS, Cramer DW, Cunningham JM, Cybulski C, Dansonka-Mieszkowska A, du Bois A, Despierre E, Dicks E, Doherty JA, Dörk T, Dürst M, Easton DF, Eccles DM, Edwards RP, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Goodman MT, Gronwald J, Harrington P, Harter P, Hein A, Heitz F, Hildebrandt MAT, Hillemanns P, Hogdall CK, Hogdall E, Hosono S, Jakubowska A, Jensen A, Ji BT, Karlan BY, Kelemen LE, Kellar M, Kiemeney LA, Krakstad C, Kjaer SK, Kupryjanczyk J, Lambrechts D, Lambrechts S, Le ND, Lee AW, Lele S, Leminen A, Lester J, Levine DA, Liang D, Lim BK, Lissowska J, Lu K, Lubinski J, Lundvall L, Massuger LFAG, Matsuo K, McGuire V, McLaughlin JR, McNeish I, Menon U, Milne RL, Modugno F, Moysich KB, Ness RB, Nevanlinna H, Eilber U, Odunsi K, Olson SH, Orlow I, Orsulic S, Weber RP, Paul J, Pearce CL, Pejovic T, Pelttari LM, Pike MC, Poole EM, Risch HA, Rosen B, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Rzepecka IK, Salvesen HB, Schernhammer E, Schwaab I, Shu XO, Shvetsov YB, Siddiqui N, Sieh W, Song H, Southey MC, Spiewankiewicz B, Sucheston L, Teo SH, Terry KL, Thompson PJ, Thomsen L, Tangen IL, Tworoger SS, van Altena AM, Vierkant RA, Vergote I, Walsh CS, Wang-Gohrke S, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Wu AH, Wu X, Woo YL, Yang H, Zheng W, Ziogas A, Hasmad HN, Berchuck A, Iversen ES, Schildkraut JM, Ramus SJ, Goode EL, Monteiro ANA, Gayther SA, Narod SA, Pharoah PDP, Sellers TA, Phelan CM. Common Genetic Variation In Cellular Transport Genes and Epithelial Ovarian Cancer (EOC) Risk. PLoS One 2015; 10:e0128106. [PMID: 26091520 PMCID: PMC4474865 DOI: 10.1371/journal.pone.0128106] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2014] [Accepted: 04/22/2015] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Defective cellular transport processes can lead to aberrant accumulation of trace elements, iron, small molecules and hormones in the cell, which in turn may promote the formation of reactive oxygen species, promoting DNA damage and aberrant expression of key regulatory cancer genes. As DNA damage and uncontrolled proliferation are hallmarks of cancer, including epithelial ovarian cancer (EOC), we hypothesized that inherited variation in the cellular transport genes contributes to EOC risk. METHODS In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons. RESULTS The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4). CONCLUSION These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.
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Liu-Smith F, Farhat A, Arce A, Taylor TH, Ziogas A, Wang Z, Yourk V, Liu JI, McEligot A, Anton-Culver H, Meyskens FL. Gender difference in the association of melanoma etiology to solar UV exposure. J Clin Oncol 2015. [DOI: 10.1200/jco.2015.33.15_suppl.e20012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Eskander RH, Chang J, Ziogas A, Anton-Culver H, Bristow R. Evaluation of unanticipated 30-day readmission in patients with advanced stage epithelial ovarian cancer. J Clin Oncol 2015. [DOI: 10.1200/jco.2015.33.15_suppl.e17684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Bristow RE, Chang J, Ziogas A, Campos B, Chavez LR, Anton-Culver H. Impact of National Cancer Institute Comprehensive Cancer Centers on ovarian cancer treatment and survival. J Am Coll Surg 2015; 220:940-50. [PMID: 25840536 PMCID: PMC5145798 DOI: 10.1016/j.jamcollsurg.2015.01.056] [Citation(s) in RCA: 80] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2014] [Revised: 01/29/2015] [Accepted: 01/29/2015] [Indexed: 11/18/2022]
Abstract
BACKGROUND The regional impact of care at a National Cancer Institute Comprehensive Cancer Center (NCI-CCC) on adherence to National Comprehensive Cancer Network (NCCN) ovarian cancer treatment guidelines and survival is unclear. STUDY DESIGN We performed a retrospective population-based study of consecutive patients diagnosed with epithelial ovarian cancer between January 1, 1996 and December 31, 2006 in southern California. Patients were stratified according to care at an NCI-CCC (n = 5), non-NCI high-volume hospital (≥ 10 cases/year, HVH, n = 29), or low-volume hospital (<10 cases/year, LVH, n = 158). Multivariable logistic regression and Cox-proportional hazards models were used to examine the effect of NCI-CCC status on treatment guideline adherence and ovarian cancer-specific survival. RESULTS A total of 9,933 patients were identified (stage I, 22.8%; stage II, 7.9%; stage III, 45.1%; stage IV, 24.2%), and 8.1% of patients were treated at NCI-CCCs. Overall, 35.7% of patients received NCCN guideline adherent care, and NCI-CCC status (odds ratio [OR] 1.00) was an independent predictor of adherence to treatment guidelines compared with HVHs (OR 0.83, 95% CI 0.70 to 0.99) and LVHs (OR 0.56, 95% CI 0.47 to 0.67). The median ovarian cancer-specific survivals according to hospital type were: NCI-CCC 77.9 (95% CI 61.4 to 92.9) months, HVH 51.9 (95% CI 49.2 to 55.7) months, and LVH 43.4 (95% CI 39.9 to 47.2) months (p < 0.0001). National Cancer Institute Comprehensive Cancer Center status (hazard ratio [HR] 1.00) was a statistically significant and independent predictor of improved survival compared with HVH (HR 1.18, 95% CI 1.04 to 1.33) and LVH (HR 1.30, 95% CI 1.15 to 1.47). CONCLUSIONS National Cancer Institute Comprehensive Cancer Center status is an independent predictor of adherence to ovarian cancer treatment guidelines and improved ovarian cancer-specific survival. These data validate NCI-CCC status as a structural health care characteristic correlated with superior ovarian cancer quality measure performance. Increased access to NCI-CCCs through regional concentration of care may be a mechanism to improve clinical outcomes.
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Mavaddat N, Pharoah PDP, Michailidou K, Tyrer J, Brook MN, Bolla MK, Wang Q, Dennis J, Dunning AM, Shah M, Luben R, Brown J, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Czene K, Darabi H, Eriksson M, Peto J, Dos-Santos-Silva I, Dudbridge F, Johnson N, Schmidt MK, Broeks A, Verhoef S, Rutgers EJ, Swerdlow A, Ashworth A, Orr N, Schoemaker MJ, Figueroa J, Chanock SJ, Brinton L, Lissowska J, Couch FJ, Olson JE, Vachon C, Pankratz VS, Lambrechts D, Wildiers H, Van Ongeval C, van Limbergen E, Kristensen V, Grenaker Alnæs G, Nord S, Borresen-Dale AL, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Burwinkel B, Marme F, Schneeweiss A, Sohn C, Trentham-Dietz A, Newcomb P, Titus L, Egan KM, Hunter DJ, Lindstrom S, Tamimi RM, Kraft P, Rahman N, Turnbull C, Renwick A, Seal S, Li J, Liu J, Humphreys K, Benitez J, Pilar Zamora M, Arias Perez JI, Menéndez P, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Bogdanova NV, Antonenkova NN, Dörk T, Anton-Culver H, Neuhausen SL, Ziogas A, Bernstein L, Devilee P, Tollenaar RAEM, Seynaeve C, van Asperen CJ, Cox A, Cross SS, Reed MWR, Khusnutdinova E, Bermisheva M, Prokofyeva D, Takhirova Z, Meindl A, Schmutzler RK, Sutter C, Yang R, Schürmann P, Bremer M, Christiansen H, Park-Simon TW, Hillemanns P, Guénel P, Truong T, Menegaux F, Sanchez M, Radice P, Peterlongo P, Manoukian S, Pensotti V, Hopper JL, Tsimiklis H, Apicella C, Southey MC, Brauch H, Brüning T, Ko YD, Sigurdson AJ, Doody MM, Hamann U, Torres D, Ulmer HU, Försti A, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Andrulis IL, Knight JA, Glendon G, Marie Mulligan A, Chenevix-Trench G, Balleine R, Giles GG, Milne RL, McLean C, Lindblom A, Margolin S, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Eilber U, Wang-Gohrke S, Hooning MJ, Hollestelle A, van den Ouweland AMW, Koppert LB, Carpenter J, Clarke C, Scott R, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Brenner H, Arndt V, Stegmaier C, Karina Dieffenbach A, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Offit K, Vijai J, Robson M, Rau-Murthy R, Dwek M, Swann R, Annie Perkins K, Goldberg MS, Labrèche F, Dumont M, Eccles DM, Tapper WJ, Rafiq S, John EM, Whittemore AS, Slager S, Yannoukakos D, Toland AE, Yao S, Zheng W, Halverson SL, González-Neira A, Pita G, Rosario Alonso M, Álvarez N, Herrero D, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Ahmed S, Maranian M, Healey CS, Simard J, Hall P, Easton DF, Garcia-Closas M. Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst 2015; 107:djv036. [PMID: 25855707 PMCID: PMC4754625 DOI: 10.1093/jnci/djv036] [Citation(s) in RCA: 376] [Impact Index Per Article: 41.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Revised: 12/01/2014] [Accepted: 01/26/2015] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. METHODS We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. RESULTS There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. CONCLUSIONS The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.
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