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11 results on '"Durcan, L"'

1. Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Author

Fachal L, Aschard H, Beesley J, Barnes DR, Allen J, Kar S, Pooley KA, Dennis J, Michailidou K, Turman C, Soucy P, Lemaçon A, Lush M, Tyrer JP, Ghoussaini M, Moradi Marjaneh M, Jiang X, Agata S, Aittomäki K, Alonso MR, Andrulis IL, Anton-Culver H, Antonenkova NN, Arason A, Arndt V, Aronson KJ, Arun BK, Auber B, Auer PL, Azzollini J, Balmaña J, Barkardottir RB, Barrowdale D, Beeghly-Fadiel A, Benitez J, Bermisheva M, Białkowska K, Blanco AM, Blomqvist C, Blot W, Bogdanova NV, Bojesen SE, Bolla MK, Bonanni B, Borg A, Bosse K, Brauch H, Brenner H, Briceno I, Brock IW, Brooks-Wilson A, Brüning T, Burwinkel B, Buys SS, Cai Q, Caldés T, Caligo MA, Camp NJ, Campbell I, Canzian F, Carroll JS, Carter BD, Castelao JE, Chiquette J, Christiansen H, Chung WK, Claes KBM, Clarke CL, Collée JM, Cornelissen S, Couch FJ, Cox A, Cross SS, Cybulski C, Czene K, Daly MB, de la Hoya M, Devilee P, Diez O, Ding YC, Dite GS, Domchek SM, Dörk T, Dos-Santos-Silva I, Droit A, Dubois S, Dumont M, Duran M, Durcan L, Dwek M, Eccles DM, Engel C, Eriksson M, Evans DG, Fasching PA, Fletcher O, Floris G, Flyger H, Foretova L, Foulkes WD, Friedman E, Fritschi L, Frost D, Gabrielson M, Gago-Dominguez M, Gambino G, Ganz PA, Gapstur SM, Garber J, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Glendon G, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Tibiletti MG, Greene MH, Grip M, Gronwald J, Grundy A, Guénel P, Hahnen E, Haiman CA, Håkansson N, Hall P, Hamann U, Harrington PA, Hartikainen JM, Hartman M, He W, Healey CS, Heemskerk-Gerritsen BAM, Heyworth J, Hillemanns P, Hogervorst FBL, Hollestelle A, Hooning MJ, Hopper JL, Howell A, Huang G, Hulick PJ, Imyanitov EN, Isaacs C, Iwasaki M, Jager A, Jakimovska M, Jakubowska A, James PA, Janavicius R, Jankowitz RC, John EM, Johnson N, Jones ME, Jukkola-Vuorinen A, Jung A, Kaaks R, Kang D, Kapoor PM, Karlan BY, Keeman R, Kerin MJ, Khusnutdinova E, Kiiski JI, Kirk J, Kitahara CM, Ko YD, Konstantopoulou I, Kosma VM, Koutros S, Kubelka-Sabit K, Kwong A, Kyriacou K, Laitman Y, Lambrechts D, Lee E, Leslie G, Lester J, Lesueur F, Lindblom A, Lo WY, Long J, Lophatananon A, Loud JT, Lubiński J, MacInnis RJ, Maishman T, Makalic E, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Martinez ME, Matsuo K, Maurer T, Mavroudis D, Mayes R, McGuffog L, McLean C, Mebirouk N, Meindl A, Miller A, Miller N, Montagna M, Moreno F, Muir K, Mulligan AM, Muñoz-Garzon VM, Muranen TA, Narod SA, Nassir R, Nathanson KL, Neuhausen SL, Nevanlinna H, Neven P, Nielsen FC, Nikitina-Zake L, Norman A, Offit K, Olah E, Olopade OI, Olsson H, Orr N, Osorio A, Pankratz VS, Papp J, Park SK, Park-Simon TW, Parsons MT, Paul J, Pedersen IS, Peissel B, Peshkin B, Peterlongo P, Peto J, Plaseska-Karanfilska D, Prajzendanc K, Prentice R, Presneau N, Prokofyeva D, Pujana MA, Pylkäs K, Radice P, Ramus SJ, Rantala J, Rau-Murthy R, Rennert G, Risch HA, Robson M, Romero A, Rossing M, Saloustros E, Sánchez-Herrero E, Sandler DP, Santamariña M, Saunders C, Sawyer EJ, Scheuner MT, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schöttker B, Schürmann P, Scott C, Scott RJ, Senter L, Seynaeve CM, Shah M, Sharma P, Shen CY, Shu XO, Singer CF, Slavin TP, Smichkoska S, Southey MC, Spinelli JJ, Spurdle AB, Stone J, Stoppa-Lyonnet D, Sutter C, Swerdlow AJ, Tamimi RM, Tan YY, Tapper WJ, Taylor JA, Teixeira MR, Tengström M, Teo SH, Terry MB, Teulé A, Thomassen M, Thull DL, Tischkowitz M, Toland AE, Tollenaar RAEM, Tomlinson I, Torres D, Torres-Mejía G, Troester MA, Truong T, Tung N, Tzardi M, Ulmer HU, Vachon CM, van Asperen CJ, van der Kolk LE, van Rensburg EJ, Vega A, Viel A, Vijai J, Vogel MJ, Wang Q, Wappenschmidt B, Weinberg CR, Weitzel JN, Wendt C, Wildiers H, Winqvist R, Wolk A, Wu AH, Yannoukakos D, Zhang Y, Zheng W, Hunter D, Pharoah PDP, Chang-Claude J, García-Closas M, Schmidt MK, Milne RL, Kristensen VN, French JD, Edwards SL, Antoniou AC, Chenevix-Trench G, Simard J, Easton DF, Kraft P, and Dunning AM

Subjects
Bayes Theorem, Female, Humans, Linkage Disequilibrium, Regulatory Sequences, Nucleic Acid, Risk Factors, Biomarkers, Tumor genetics, Breast Neoplasms genetics, Chromosome Mapping methods, Genetic Predisposition to Disease, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Quantitative Trait Loci
Abstract

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

Published
2020
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2. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Author

Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, Tyrer JP, Chen TH, Wang Q, Bolla MK, Yang X, Adank MA, Ahearn T, Aittomäki K, Allen J, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Auer PL, Auvinen P, Barrdahl M, Beane Freeman LE, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bernstein L, Blomqvist C, Bogdanova NV, Bojesen SE, Bonanni B, Børresen-Dale AL, Brauch H, Bremer M, Brenner H, Brentnall A, Brock IW, Brooks-Wilson A, Brucker SY, Brüning T, Burwinkel B, Campa D, Carter BD, Castelao JE, Chanock SJ, Chlebowski R, Christiansen H, Clarke CL, Collée JM, Cordina-Duverger E, Cornelissen S, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dos-Santos-Silva I, Dumont M, Durcan L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Ellberg C, Engel C, Eriksson M, Evans DG, Fasching PA, Figueroa J, Fletcher O, Flyger H, Försti A, Fritschi L, Gabrielson M, Gago-Dominguez M, Gapstur SM, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Gilyazova IR, Glendon G, Goldberg MS, Goldgar DE, González-Neira A, Grenaker Alnæs GI, Grip M, Gronwald J, Grundy A, Guénel P, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hankinson SE, Harkness EF, Hart SN, He W, Hein A, Heyworth J, Hillemanns P, Hollestelle A, Hooning MJ, Hoover RN, Hopper JL, Howell A, Huang G, Humphreys K, Hunter DJ, Jakimovska M, Jakubowska A, Janni W, John EM, Johnson N, Jones ME, Jukkola-Vuorinen A, Jung A, Kaaks R, Kaczmarek K, Kataja V, Keeman R, Kerin MJ, Khusnutdinova E, Kiiski JI, Knight JA, Ko YD, Kosma VM, Koutros S, Kristensen VN, Krüger U, Kühl T, Lambrechts D, Le Marchand L, Lee E, Lejbkowicz F, Lilyquist J, Lindblom A, Lindström S, Lissowska J, Lo WY, Loibl S, Long J, Lubiński J, Lux MP, MacInnis RJ, Maishman T, Makalic E, Maleva Kostovska I, Mannermaa A, Manoukian S, Margolin S, Martens JWM, Martinez ME, Mavroudis D, McLean C, Meindl A, Menon U, Middha P, Miller N, Moreno F, Mulligan AM, Mulot C, Muñoz-Garzon VM, Neuhausen SL, Nevanlinna H, Neven P, Newman WG, Nielsen SF, Nordestgaard BG, Norman A, Offit K, Olson JE, Olsson H, Orr N, Pankratz VS, Park-Simon TW, Perez JIA, Pérez-Barrios C, Peterlongo P, Peto J, Pinchev M, Plaseska-Karanfilska D, Polley EC, Prentice R, Presneau N, Prokofyeva D, Purrington K, Pylkäs K, Rack B, Radice P, Rau-Murthy R, Rennert G, Rennert HS, Rhenius V, Robson M, Romero A, Ruddy KJ, Ruebner M, Saloustros E, Sandler DP, Sawyer EJ, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schumacher F, Schürmann P, Schwentner L, Scott C, Scott RJ, Seynaeve C, Shah M, Sherman ME, Shrubsole MJ, Shu XO, Slager S, Smeets A, Sohn C, Soucy P, Southey MC, Spinelli JJ, Stegmaier C, Stone J, Swerdlow AJ, Tamimi RM, Tapper WJ, Taylor JA, Terry MB, Thöne K, Tollenaar RAEM, Tomlinson I, Truong T, Tzardi M, Ulmer HU, Untch M, Vachon CM, van Veen EM, Vijai J, Weinberg CR, Wendt C, Whittemore AS, Wildiers H, Willett W, Winqvist R, Wolk A, Yang XR, Yannoukakos D, Zhang Y, Zheng W, Ziogas A, Dunning AM, Thompson DJ, Chenevix-Trench G, Chang-Claude J, Schmidt MK, Hall P, Milne RL, Pharoah PDP, Antoniou AC, Chatterjee N, Kraft P, García-Closas M, Simard J, and Easton DF

Subjects
Adult, Age Factors, Aged, Aged, 80 and over, Breast Neoplasms diagnosis, Breast Neoplasms prevention & control, Female, Humans, Medical History Taking, Middle Aged, Polymorphism, Single Nucleotide genetics, Receptors, Estrogen metabolism, Reproducibility of Results, Risk Assessment, Breast Neoplasms classification, Breast Neoplasms genetics, Genetic Predisposition to Disease, Multifactorial Inheritance genetics
Abstract

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2019
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3. Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer.

Author

Milne RL, Kuchenbaecker KB, Michailidou K, Beesley J, Kar S, Lindström S, Hui S, Lemaçon A, Soucy P, Dennis J, Jiang X, Rostamianfar A, Finucane H, Bolla MK, McGuffog L, Wang Q, Aalfs CM, Adams M, Adlard J, Agata S, Ahmed S, Ahsan H, Aittomäki K, Al-Ejeh F, Allen J, Ambrosone CB, Amos CI, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Arnold N, Aronson KJ, Auber B, Auer PL, Ausems MGEM, Azzollini J, Bacot F, Balmaña J, Barile M, Barjhoux L, Barkardottir RB, Barrdahl M, Barnes D, Barrowdale D, Baynes C, Beckmann MW, Benitez J, Bermisheva M, Bernstein L, Bignon YJ, Blazer KR, Blok MJ, Blomqvist C, Blot W, Bobolis K, Boeckx B, Bogdanova NV, Bojesen A, Bojesen SE, Bonanni B, Børresen-Dale AL, Bozsik A, Bradbury AR, Brand JS, Brauch H, Brenner H, Bressac-de Paillerets B, Brewer C, Brinton L, Broberg P, Brooks-Wilson A, Brunet J, Brüning T, Burwinkel B, Buys SS, Byun J, Cai Q, Caldés T, Caligo MA, Campbell I, Canzian F, Caron O, Carracedo A, Carter BD, Castelao JE, Castera L, Caux-Moncoutier V, Chan SB, Chang-Claude J, Chanock SJ, Chen X, Cheng TD, Chiquette J, Christiansen H, Claes KBM, Clarke CL, Conner T, Conroy DM, Cook J, Cordina-Duverger E, Cornelissen S, Coupier I, Cox A, Cox DG, Cross SS, Cuk K, Cunningham JM, Czene K, Daly MB, Damiola F, Darabi H, Davidson R, De Leeneer K, Devilee P, Dicks E, Diez O, Ding YC, Ditsch N, Doheny KF, Domchek SM, Dorfling CM, Dörk T, Dos-Santos-Silva I, Dubois S, Dugué PA, Dumont M, Dunning AM, Durcan L, Dwek M, Dworniczak B, Eccles D, Eeles R, Ehrencrona H, Eilber U, Ejlertsen B, Ekici AB, Eliassen AH, Engel C, Eriksson M, Fachal L, Faivre L, Fasching PA, Faust U, Figueroa J, Flesch-Janys D, Fletcher O, Flyger H, Foulkes WD, Friedman E, Fritschi L, Frost D, Gabrielson M, Gaddam P, Gammon MD, Ganz PA, Gapstur SM, Garber J, Garcia-Barberan V, García-Sáenz JA, Gaudet MM, Gauthier-Villars M, Gehrig A, Georgoulias V, Gerdes AM, Giles GG, Glendon G, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Goodfellow P, Greene MH, Alnæs GIG, Grip M, Gronwald J, Grundy A, Gschwantler-Kaulich D, Guénel P, Guo Q, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hallberg E, Hamann U, Hamel N, Hankinson S, Hansen TVO, Harrington P, Hart SN, Hartikainen JM, Healey CS, Hein A, Helbig S, Henderson A, Heyworth J, Hicks B, Hillemanns P, Hodgson S, Hogervorst FB, Hollestelle A, Hooning MJ, Hoover B, Hopper JL, Hu C, Huang G, Hulick PJ, Humphreys K, Hunter DJ, Imyanitov EN, Isaacs C, Iwasaki M, Izatt L, Jakubowska A, James P, Janavicius R, Janni W, Jensen UB, John EM, Johnson N, Jones K, Jones M, Jukkola-Vuorinen A, Kaaks R, Kabisch M, Kaczmarek K, Kang D, Kast K, Keeman R, Kerin MJ, Kets CM, Keupers M, Khan S, Khusnutdinova E, Kiiski JI, Kim SW, Knight JA, Konstantopoulou I, Kosma VM, Kristensen VN, Kruse TA, Kwong A, Lænkholm AV, Laitman Y, Lalloo F, Lambrechts D, Landsman K, Lasset C, Lazaro C, Le Marchand L, Lecarpentier J, Lee A, Lee E, Lee JW, Lee MH, Lejbkowicz F, Lesueur F, Li J, Lilyquist J, Lincoln A, Lindblom A, Lissowska J, Lo WY, Loibl S, Long J, Loud JT, Lubinski J, Luccarini C, Lush M, MacInnis RJ, Maishman T, Makalic E, Kostovska IM, Malone KE, Manoukian S, Manson JE, Margolin S, Martens JWM, Martinez ME, Matsuo K, Mavroudis D, Mazoyer S, McLean C, Meijers-Heijboer H, Menéndez P, Meyer J, Miao H, Miller A, Miller N, Mitchell G, Montagna M, Muir K, Mulligan AM, Mulot C, Nadesan S, Nathanson KL, Neuhausen SL, Nevanlinna H, Nevelsteen I, Niederacher D, Nielsen SF, Nordestgaard BG, Norman A, Nussbaum RL, Olah E, Olopade OI, Olson JE, Olswold C, Ong KR, Oosterwijk JC, Orr N, Osorio A, Pankratz VS, Papi L, Park-Simon TW, Paulsson-Karlsson Y, Lloyd R, Pedersen IS, Peissel B, Peixoto A, Perez JIA, Peterlongo P, Peto J, Pfeiler G, Phelan CM, Pinchev M, Plaseska-Karanfilska D, Poppe B, Porteous ME, Prentice R, Presneau N, Prokofieva D, Pugh E, Pujana MA, Pylkäs K, Rack B, Radice P, Rahman N, Rantala J, Rappaport-Fuerhauser C, Rennert G, Rennert HS, Rhenius V, Rhiem K, Richardson A, Rodriguez GC, Romero A, Romm J, Rookus MA, Rudolph A, Ruediger T, Saloustros E, Sanders J, Sandler DP, Sangrajrang S, Sawyer EJ, Schmidt DF, Schoemaker MJ, Schumacher F, Schürmann P, Schwentner L, Scott C, Scott RJ, Seal S, Senter L, Seynaeve C, Shah M, Sharma P, Shen CY, Sheng X, Shimelis H, Shrubsole MJ, Shu XO, Side LE, Singer CF, Sohn C, Southey MC, Spinelli JJ, Spurdle AB, Stegmaier C, Stoppa-Lyonnet D, Sukiennicki G, Surowy H, Sutter C, Swerdlow A, Szabo CI, Tamimi RM, Tan YY, Taylor JA, Tejada MI, Tengström M, Teo SH, Terry MB, Tessier DC, Teulé A, Thöne K, Thull DL, Tibiletti MG, Tihomirova L, Tischkowitz M, Toland AE, Tollenaar RAEM, Tomlinson I, Tong L, Torres D, Tranchant M, Truong T, Tucker K, Tung N, Tyrer J, Ulmer HU, Vachon C, van Asperen CJ, Van Den Berg D, van den Ouweland AMW, van Rensburg EJ, Varesco L, Varon-Mateeva R, Vega A, Viel A, Vijai J, Vincent D, Vollenweider J, Walker L, Wang Z, Wang-Gohrke S, Wappenschmidt B, Weinberg CR, Weitzel JN, Wendt C, Wesseling J, Whittemore AS, Wijnen JT, Willett W, Winqvist R, Wolk A, Wu AH, Xia L, Yang XR, Yannoukakos D, Zaffaroni D, Zheng W, Zhu B, Ziogas A, Ziv E, Zorn KK, Gago-Dominguez M, Mannermaa A, Olsson H, Teixeira MR, Stone J, Offit K, Ottini L, Park SK, Thomassen M, Hall P, Meindl A, Schmutzler RK, Droit A, Bader GD, Pharoah PDP, Couch FJ, Easton DF, Kraft P, Chenevix-Trench G, García-Closas M, Schmidt MK, Antoniou AC, and Simard J

Subjects
Breast Neoplasms ethnology, Breast Neoplasms metabolism, Female, Genetic Predisposition to Disease ethnology, Genome-Wide Association Study methods, Heterozygote, Humans, Receptors, Estrogen metabolism, Risk Factors, White People genetics, BRCA1 Protein genetics, Breast Neoplasms genetics, Genetic Predisposition to Disease genetics, Mutation, Polymorphism, Single Nucleotide
Abstract

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10 -8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Published
2017
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4. Association analysis identifies 65 new breast cancer risk loci.

Author

Michailidou K, Lindström S, Dennis J, Beesley J, Hui S, Kar S, Lemaçon A, Soucy P, Glubb D, Rostamianfar A, Bolla MK, Wang Q, Tyrer J, Dicks E, Lee A, Wang Z, Allen J, Keeman R, Eilber U, French JD, Qing Chen X, Fachal L, McCue K, McCart Reed AE, Ghoussaini M, Carroll JS, Jiang X, Finucane H, Adams M, Adank MA, Ahsan H, Aittomäki K, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Arun B, Auer PL, Bacot F, Barrdahl M, Baynes C, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bernstein L, Blomqvist C, Bogdanova NV, Bojesen SE, Bonanni B, Børresen-Dale AL, Brand JS, Brauch H, Brennan P, Brenner H, Brinton L, Broberg P, Brock IW, Broeks A, Brooks-Wilson A, Brucker SY, Brüning T, Burwinkel B, Butterbach K, Cai Q, Cai H, Caldés T, Canzian F, Carracedo A, Carter BD, Castelao JE, Chan TL, David Cheng TY, Seng Chia K, Choi JY, Christiansen H, Clarke CL, Collée M, Conroy DM, Cordina-Duverger E, Cornelissen S, Cox DG, Cox A, Cross SS, Cunningham JM, Czene K, Daly MB, Devilee P, Doheny KF, Dörk T, Dos-Santos-Silva I, Dumont M, Durcan L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Ellberg C, Elvira M, Engel C, Eriksson M, Fasching PA, Figueroa J, Flesch-Janys D, Fletcher O, Flyger H, Fritschi L, Gaborieau V, Gabrielson M, Gago-Dominguez M, Gao YT, Gapstur SM, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Glendon G, Goldberg MS, Goldgar DE, González-Neira A, Grenaker Alnæs GI, Grip M, Gronwald J, Grundy A, Guénel P, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hamann U, Hamel N, Hankinson S, Harrington P, Hart SN, Hartikainen JM, Hartman M, Hein A, Heyworth J, Hicks B, Hillemanns P, Ho DN, Hollestelle A, Hooning MJ, Hoover RN, Hopper JL, Hou MF, Hsiung CN, Huang G, Humphreys K, Ishiguro J, Ito H, Iwasaki M, Iwata H, Jakubowska A, Janni W, John EM, Johnson N, Jones K, Jones M, Jukkola-Vuorinen A, Kaaks R, Kabisch M, Kaczmarek K, Kang D, Kasuga Y, Kerin MJ, Khan S, Khusnutdinova E, Kiiski JI, Kim SW, Knight JA, Kosma VM, Kristensen VN, Krüger U, Kwong A, Lambrechts D, Le Marchand L, Lee E, Lee MH, Lee JW, Neng Lee C, Lejbkowicz F, Li J, Lilyquist J, Lindblom A, Lissowska J, Lo WY, Loibl S, Long J, Lophatananon A, Lubinski J, Luccarini C, Lux MP, Ma ESK, MacInnis RJ, Maishman T, Makalic E, Malone KE, Kostovska IM, Mannermaa A, Manoukian S, Manson JE, Margolin S, Mariapun S, Martinez ME, Matsuo K, Mavroudis D, McKay J, McLean C, Meijers-Heijboer H, Meindl A, Menéndez P, Menon U, Meyer J, Miao H, Miller N, Taib NAM, Muir K, Mulligan AM, Mulot C, Neuhausen SL, Nevanlinna H, Neven P, Nielsen SF, Noh DY, Nordestgaard BG, Norman A, Olopade OI, Olson JE, Olsson H, Olswold C, Orr N, Pankratz VS, Park SK, Park-Simon TW, Lloyd R, Perez JIA, Peterlongo P, Peto J, Phillips KA, Pinchev M, Plaseska-Karanfilska D, Prentice R, Presneau N, Prokofyeva D, Pugh E, Pylkäs K, Rack B, Radice P, Rahman N, Rennert G, Rennert HS, Rhenius V, Romero A, Romm J, Ruddy KJ, Rüdiger T, Rudolph A, Ruebner M, Rutgers EJT, Saloustros E, Sandler DP, Sangrajrang S, Sawyer EJ, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schumacher F, Schürmann P, Scott RJ, Scott C, Seal S, Seynaeve C, Shah M, Sharma P, Shen CY, Sheng G, Sherman ME, Shrubsole MJ, Shu XO, Smeets A, Sohn C, Southey MC, Spinelli JJ, Stegmaier C, Stewart-Brown S, Stone J, Stram DO, Surowy H, Swerdlow A, Tamimi R, Taylor JA, Tengström M, Teo SH, Beth Terry M, Tessier DC, Thanasitthichai S, Thöne K, Tollenaar RAEM, Tomlinson I, Tong L, Torres D, Truong T, Tseng CC, Tsugane S, Ulmer HU, Ursin G, Untch M, Vachon C, van Asperen CJ, Van Den Berg D, van den Ouweland AMW, van der Kolk L, van der Luijt RB, Vincent D, Vollenweider J, Waisfisz Q, Wang-Gohrke S, Weinberg CR, Wendt C, Whittemore AS, Wildiers H, Willett W, Winqvist R, Wolk A, Wu AH, Xia L, Yamaji T, Yang XR, Har Yip C, Yoo KY, Yu JC, Zheng W, Zheng Y, Zhu B, Ziogas A, Ziv E, Lakhani SR, Antoniou AC, Droit A, Andrulis IL, Amos CI, Couch FJ, Pharoah PDP, Chang-Claude J, Hall P, Hunter DJ, Milne RL, García-Closas M, Schmidt MK, Chanock SJ, Dunning AM, Edwards SL, Bader GD, Chenevix-Trench G, Simard J, Kraft P, and Easton DF

Subjects
Asia ethnology, Asian People genetics, Binding Sites genetics, Breast Neoplasms diagnosis, Computer Simulation, Europe ethnology, Female, Humans, Multifactorial Inheritance genetics, Polymorphism, Single Nucleotide genetics, Regulatory Sequences, Nucleic Acid, Risk Assessment, Transcription Factors metabolism, White People genetics, Breast Neoplasms genetics, Genetic Loci, Genetic Predisposition to Disease genetics, Genome-Wide Association Study
Abstract

Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P < 5 × 10 -8 . The majority of credible risk single-nucleotide polymorphisms in these loci fall in distal regulatory elements, and by integrating in silico data to predict target genes in breast cells at each locus, we demonstrate a strong overlap between candidate target genes and somatic driver genes in breast tumours. We also find that heritability of breast cancer due to all single-nucleotide polymorphisms in regulatory features was 2-5-fold enriched relative to the genome-wide average, with strong enrichment for particular transcription factor binding sites. These results provide further insight into genetic susceptibility to breast cancer and will improve the use of genetic risk scores for individualized screening and prevention.

Published
2017
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5. Genetic testing in a cohort of young patients with HER2-amplified breast cancer.

Author

Eccles DM, Li N, Handwerker R, Maishman T, Copson ER, Durcan LT, Gerty SM, Jones L, Evans DG, Haywood L, and Campbell I

Subjects
Adult, Female, Humans, Prospective Studies, Young Adult, BRCA1 Protein genetics, BRCA2 Protein genetics, Breast Neoplasms genetics, Genetic Predisposition to Disease, Genetic Testing, Receptor, ErbB-2 genetics, Tumor Suppressor Protein p53 genetics
Abstract

Background: Young age at diagnosis for breast cancer raises the question of genetic susceptibility. We explored breast cancer susceptibility genes testing on ≤40-year-old patients with HER2-amplified invasive breast cancer., Patients and Methods: Patients were selected from a large UK cohort study. The inclusion criterion was age ≤40 at diagnosis with confirmed HER2-amplified breast cancer. The probability of finding a BRCA gene mutation was calculated based on family history. Genetic testing used was either clinical testing for BRCA1 and BRCA2, with a subset also tested for TP53 mutations, or research-based testing using a typical panel comprising 17 breast cancer susceptibility genes (CSGs) including BRCA1, BRCA2 and TP53., Results: Of the 591 eligible patients, clinical testing results were available for 133 cases and an additional 263 cases had panel testing results. BRCA testing across 396 cases found 8 BRCA2 (2%) and 6 BRCA1 (2%) pathogenic mutations. Of the 304 patients tested for TP53 mutations, overall 9 (3%) had deleterious TP53 mutations. Of the 396 patients, 101 (26%) met clinical criteria for BRCA testing (≥10% probability), among whom 11% had pathogenic BRCA mutations (6 BRCA2, 5 BRCA1). Where the probability was calculated to be <10%, only 4 of 295 (1%) patients had BRCA mutations. Among the 59 patients who had TP53 testing meeting the 10% threshold, 7 had mutations (12%). Likely functionally deleterious mutations in 14 lower penetrance CSGs were present in 12 of 263 (5%) panel-tested patients., Conclusion: Patients aged <41 at diagnosis with HER2+ breast cancer and no family history of breast cancer can be reassured that they have a low chance of being a high-risk gene carrier. If there is a strong family history, not only BRCA but also TP53 gene testing should be considered. The clinical utility of testing lower penetrance CSGs remains unclear., (© The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Published
2016
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6. Inherited mutations in 17 breast cancer susceptibility genes among a large triple-negative breast cancer cohort unselected for family history of breast cancer.

Author

Couch FJ, Hart SN, Sharma P, Toland AE, Wang X, Miron P, Olson JE, Godwin AK, Pankratz VS, Olswold C, Slettedahl S, Hallberg E, Guidugli L, Davila JI, Beckmann MW, Janni W, Rack B, Ekici AB, Slamon DJ, Konstantopoulou I, Fostira F, Vratimos A, Fountzilas G, Pelttari LM, Tapper WJ, Durcan L, Cross SS, Pilarski R, Shapiro CL, Klemp J, Yao S, Garber J, Cox A, Brauch H, Ambrosone C, Nevanlinna H, Yannoukakos D, Slager SL, Vachon CM, Eccles DM, and Fasching PA

Subjects
Adult, Aged, Aged, 80 and over, BRCA1 Protein genetics, BRCA2 Protein genetics, Cohort Studies, DNA Mutational Analysis, Family Health, Female, Humans, Middle Aged, Ovarian Neoplasms diagnosis, Ovarian Neoplasms genetics, Triple Negative Breast Neoplasms diagnosis, Young Adult, Genetic Predisposition to Disease genetics, Genetic Testing methods, Germ-Line Mutation, Triple Negative Breast Neoplasms genetics
Abstract

Purpose: Recent advances in DNA sequencing have led to the development of breast cancer susceptibility gene panels for germline genetic testing of patients. We assessed the frequency of mutations in 17 predisposition genes, including BRCA1 and BRCA2, in a large cohort of patients with triple-negative breast cancer (TNBC) unselected for family history of breast or ovarian cancer to determine the utility of germline genetic testing for those with TNBC., Patients and Methods: Patients with TNBC (N = 1,824) unselected for family history of breast or ovarian cancer were recruited through 12 studies, and germline DNA was sequenced to identify mutations., Results: Deleterious mutations were identified in 14.6% of all patients. Of these, 11.2% had mutations in the BRCA1 (8.5%) and BRCA2 (2.7%) genes. Deleterious mutations in 15 other predisposition genes were detected in 3.7% of patients, with the majority observed in genes involved in homologous recombination, including PALB2 (1.2%) and BARD1, RAD51D, RAD51C, and BRIP1 (0.3% to 0.5%). Patients with TNBC with mutations were diagnosed at an earlier age (P < .001) and had higher-grade tumors (P = .01) than those without mutations., Conclusion: Deleterious mutations in predisposition genes are present at high frequency in patients with TNBC unselected for family history of cancer. Mutation prevalence estimates suggest that patients with TNBC, regardless of age at diagnosis or family history of cancer, should be considered for germline genetic testing of BRCA1 and BRCA2. Although mutations in other predisposition genes are observed among patients with TNBC, better cancer risk estimates are needed before these mutations are used for clinical risk assessment in relatives., (© 2014 by American Society of Clinical Oncology.)

Published
2015
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7. Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer.

Author

Purrington KS, Slager S, Eccles D, Yannoukakos D, Fasching PA, Miron P, Carpenter J, Chang-Claude J, Martin NG, Montgomery GW, Kristensen V, Anton-Culver H, Goodfellow P, Tapper WJ, Rafiq S, Gerty SM, Durcan L, Konstantopoulou I, Fostira F, Vratimos A, Apostolou P, Konstanta I, Kotoula V, Lakis S, Dimopoulos MA, Skarlos D, Pectasides D, Fountzilas G, Beckmann MW, Hein A, Ruebner M, Ekici AB, Hartmann A, Schulz-Wendtland R, Renner SP, Janni W, Rack B, Scholz C, Neugebauer J, Andergassen U, Lux MP, Haeberle L, Clarke C, Pathmanathan N, Rudolph A, Flesch-Janys D, Nickels S, Olson JE, Ingle JN, Olswold C, Slettedahl S, Eckel-Passow JE, Anderson SK, Visscher DW, Cafourek VL, Sicotte H, Prodduturi N, Weiderpass E, Bernstein L, Ziogas A, Ivanovich J, Giles GG, Baglietto L, Southey M, Kosma VM, Fischer HP, Reed MW, Cross SS, Deming-Halverson S, Shrubsole M, Cai Q, Shu XO, Daly M, Weaver J, Ross E, Klemp J, Sharma P, Torres D, Rüdiger T, Wölfing H, Ulmer HU, Försti A, Khoury T, Kumar S, Pilarski R, Shapiro CL, Greco D, Heikkilä P, Aittomäki K, Blomqvist C, Irwanto A, Liu J, Pankratz VS, Wang X, Severi G, Mannermaa A, Easton D, Hall P, Brauch H, Cox A, Zheng W, Godwin AK, Hamann U, Ambrosone C, Toland AE, Nevanlinna H, Vachon CM, and Couch FJ

Subjects
Adult, Aged, Aged, 80 and over, Case-Control Studies, Chromosomes, Human, Pair 19, Estrogen Receptor alpha genetics, Female, Humans, Middle Aged, Polymorphism, Single Nucleotide, Young Adult, Genetic Predisposition to Disease, Genome-Wide Association Study, Quantitative Trait Loci, Triple Negative Breast Neoplasms genetics
Abstract

Triple-negative (TN) breast cancer is an aggressive subtype of breast cancer associated with a unique set of epidemiologic and genetic risk factors. We conducted a two-stage genome-wide association study of TN breast cancer (stage 1: 1529 TN cases, 3399 controls; stage 2: 2148 cases, 1309 controls) to identify loci that influence TN breast cancer risk. Variants in the 19p13.1 and PTHLH loci showed genome-wide significant associations (P < 5 × 10(-) (8)) in stage 1 and 2 combined. Results also suggested a substantial enrichment of significantly associated variants among the single nucleotide polymorphisms (SNPs) analyzed in stage 2. Variants from 25 of 74 known breast cancer susceptibility loci were also associated with risk of TN breast cancer (P < 0.05). Associations with TN breast cancer were confirmed for 10 loci (LGR6, MDM4, CASP8, 2q35, 2p24.1, TERT-rs10069690, ESR1, TOX3, 19p13.1, RALY), and we identified associations with TN breast cancer for 15 additional breast cancer loci (P < 0.05: PEX14, 2q24.1, 2q31.1, ADAM29, EBF1, TCF7L2, 11q13.1, 11q24.3, 12p13.1, PTHLH, NTN4, 12q24, BRCA2, RAD51L1-rs2588809, MKL1). Further, two SNPs independent of previously reported signals in ESR1 [rs12525163 odds ratio (OR) = 1.15, P = 4.9 × 10(-) (4)] and 19p13.1 (rs1864112 OR = 0.84, P = 1.8 × 10(-) (9)) were associated with TN breast cancer. A polygenic risk score (PRS) for TN breast cancer based on known breast cancer risk variants showed a 4-fold difference in risk between the highest and lowest PRS quintiles (OR = 4.03, 95% confidence interval 3.46-4.70, P = 4.8 × 10(-) (69)). This translates to an absolute risk for TN breast cancer ranging from 0.8% to 3.4%, suggesting that genetic variation may be used for TN breast cancer risk prediction.

Published
2014
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8. Genome-wide association studies identify four ER negative-specific breast cancer risk loci.

Author

Garcia-Closas M, Couch FJ, Lindstrom S, Michailidou K, Schmidt MK, Brook MN, Orr N, Rhie SK, Riboli E, Feigelson HS, Le Marchand L, Buring JE, Eccles D, Miron P, Fasching PA, Brauch H, Chang-Claude J, Carpenter J, Godwin AK, Nevanlinna H, Giles GG, Cox A, Hopper JL, Bolla MK, Wang Q, Dennis J, Dicks E, Howat WJ, Schoof N, Bojesen SE, Lambrechts D, Broeks A, Andrulis IL, Guénel P, Burwinkel B, Sawyer EJ, Hollestelle A, Fletcher O, Winqvist R, Brenner H, Mannermaa A, Hamann U, Meindl A, Lindblom A, Zheng W, Devillee P, Goldberg MS, Lubinski J, Kristensen V, Swerdlow A, Anton-Culver H, Dörk T, Muir K, Matsuo K, Wu AH, Radice P, Teo SH, Shu XO, Blot W, Kang D, Hartman M, Sangrajrang S, Shen CY, Southey MC, Park DJ, Hammet F, Stone J, Veer LJ, Rutgers EJ, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Peto J, Schrauder MG, Ekici AB, Beckmann MW, Dos Santos Silva I, Johnson N, Warren H, Tomlinson I, Kerin MJ, Miller N, Marme F, Schneeweiss A, Sohn C, Truong T, Laurent-Puig P, Kerbrat P, Nordestgaard BG, Nielsen SF, Flyger H, Milne RL, Perez JI, Menéndez P, Müller H, Arndt V, Stegmaier C, Lichtner P, Lochmann M, Justenhoven C, Ko YD, Muranen TA, Aittomäki K, Blomqvist C, Greco D, Heikkinen T, Ito H, Iwata H, Yatabe Y, Antonenkova NN, Margolin S, Kataja V, Kosma VM, Hartikainen JM, Balleine R, Tseng CC, Berg DV, Stram DO, Neven P, Dieudonné AS, Leunen K, Rudolph A, Nickels S, Flesch-Janys D, Peterlongo P, Peissel B, Bernard L, Olson JE, Wang X, Stevens K, Severi G, Baglietto L, McLean C, Coetzee GA, Feng Y, Henderson BE, Schumacher F, Bogdanova NV, Labrèche F, Dumont M, Yip CH, Taib NA, Cheng CY, Shrubsole M, Long J, Pylkäs K, Jukkola-Vuorinen A, Kauppila S, Knight JA, Glendon G, Mulligan AM, Tollenaar RA, Seynaeve CM, Kriege M, Hooning MJ, van den Ouweland AM, van Deurzen CH, Lu W, Gao YT, Cai H, Balasubramanian SP, Cross SS, Reed MW, Signorello L, Cai Q, Shah M, Miao H, Chan CW, Chia KS, Jakubowska A, Jaworska K, Durda K, Hsiung CN, Wu PE, Yu JC, Ashworth A, Jones M, Tessier DC, González-Neira A, Pita G, Alonso MR, Vincent D, Bacot F, Ambrosone CB, Bandera EV, John EM, Chen GK, Hu JJ, Rodriguez-Gil JL, Bernstein L, Press MF, Ziegler RG, Millikan RM, Deming-Halverson SL, Nyante S, Ingles SA, Waisfisz Q, Tsimiklis H, Makalic E, Schmidt D, Bui M, Gibson L, Müller-Myhsok B, Schmutzler RK, Hein R, Dahmen N, Beckmann L, Aaltonen K, Czene K, Irwanto A, Liu J, Turnbull C, Rahman N, Meijers-Heijboer H, Uitterlinden AG, Rivadeneira F, Olswold C, Slager S, Pilarski R, Ademuyiwa F, Konstantopoulou I, Martin NG, Montgomery GW, Slamon DJ, Rauh C, Lux MP, Jud SM, Bruning T, Weaver J, Sharma P, Pathak H, Tapper W, Gerty S, Durcan L, Trichopoulos D, Tumino R, Peeters PH, Kaaks R, Campa D, Canzian F, Weiderpass E, Johansson M, Khaw KT, Travis R, Clavel-Chapelon F, Kolonel LN, Chen C, Beck A, Hankinson SE, Berg CD, Hoover RN, Lissowska J, Figueroa JD, Chasman DI, Gaudet MM, Diver WR, Willett WC, Hunter DJ, Simard J, Benitez J, Dunning AM, Sherman ME, Chenevix-Trench G, Chanock SJ, Hall P, Pharoah PD, Vachon C, Easton DF, Haiman CA, and Kraft P

Subjects
Breast Neoplasms metabolism, Breast Neoplasms pathology, Case-Control Studies, Cooperative Behavior, Female, Genome-Wide Association Study, Genotype, Humans, Meta-Analysis as Topic, Oligonucleotide Array Sequence Analysis, Receptors, Estrogen genetics, Risk Factors, Breast Neoplasms etiology, Genetic Loci genetics, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide genetics, Receptors, Estrogen metabolism
Abstract

Estrogen receptor (ER)-negative tumors represent 20-30% of all breast cancers, with a higher proportion occurring in younger women and women of African ancestry. The etiology and clinical behavior of ER-negative tumors are different from those of tumors expressing ER (ER positive), including differences in genetic predisposition. To identify susceptibility loci specific to ER-negative disease, we combined in a meta-analysis 3 genome-wide association studies of 4,193 ER-negative breast cancer cases and 35,194 controls with a series of 40 follow-up studies (6,514 cases and 41,455 controls), genotyped using a custom Illumina array, iCOGS, developed by the Collaborative Oncological Gene-environment Study (COGS). SNPs at four loci, 1q32.1 (MDM4, P = 2.1 × 10(-12) and LGR6, P = 1.4 × 10(-8)), 2p24.1 (P = 4.6 × 10(-8)) and 16q12.2 (FTO, P = 4.0 × 10(-8)), were associated with ER-negative but not ER-positive breast cancer (P > 0.05). These findings provide further evidence for distinct etiological pathways associated with invasive ER-positive and ER-negative breast cancers.

Published
2013
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9. A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11.

Author

Siddiq A, Couch FJ, Chen GK, Lindström S, Eccles D, Millikan RC, Michailidou K, Stram DO, Beckmann L, Rhie SK, Ambrosone CB, Aittomäki K, Amiano P, Apicella C, Baglietto L, Bandera EV, Beckmann MW, Berg CD, Bernstein L, Blomqvist C, Brauch H, Brinton L, Bui QM, Buring JE, Buys SS, Campa D, Carpenter JE, Chasman DI, Chang-Claude J, Chen C, Clavel-Chapelon F, Cox A, Cross SS, Czene K, Deming SL, Diasio RB, Diver WR, Dunning AM, Durcan L, Ekici AB, Fasching PA, Feigelson HS, Fejerman L, Figueroa JD, Fletcher O, Flesch-Janys D, Gaudet MM, Gerty SM, Rodriguez-Gil JL, Giles GG, van Gils CH, Godwin AK, Graham N, Greco D, Hall P, Hankinson SE, Hartmann A, Hein R, Heinz J, Hoover RN, Hopper JL, Hu JJ, Huntsman S, Ingles SA, Irwanto A, Isaacs C, Jacobs KB, John EM, Justenhoven C, Kaaks R, Kolonel LN, Coetzee GA, Lathrop M, Le Marchand L, Lee AM, Lee IM, Lesnick T, Lichtner P, Liu J, Lund E, Makalic E, Martin NG, McLean CA, Meijers-Heijboer H, Meindl A, Miron P, Monroe KR, Montgomery GW, Müller-Myhsok B, Nickels S, Nyante SJ, Olswold C, Overvad K, Palli D, Park DJ, Palmer JR, Pathak H, Peto J, Pharoah P, Rahman N, Rivadeneira F, Schmidt DF, Schmutzler RK, Slager S, Southey MC, Stevens KN, Sinn HP, Press MF, Ross E, Riboli E, Ridker PM, Schumacher FR, Severi G, Dos Santos Silva I, Stone J, Sund M, Tapper WJ, Thun MJ, Travis RC, Turnbull C, Uitterlinden AG, Waisfisz Q, Wang X, Wang Z, Weaver J, Schulz-Wendtland R, Wilkens LR, Van Den Berg D, Zheng W, Ziegler RG, Ziv E, Nevanlinna H, Easton DF, Hunter DJ, Henderson BE, Chanock SJ, Garcia-Closas M, Kraft P, Haiman CA, and Vachon CM

Subjects
Female, Humans, Polymorphism, Single Nucleotide genetics, Receptors, Estrogen genetics, Breast Neoplasms genetics, Genetic Predisposition to Disease genetics, Genome-Wide Association Study
Abstract

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10(-5) in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10(-8)) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10(-6)) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10(-9)), and with both ER-positive (OR = 1.09; P = 1.5 × 10(-5)) and ER-negative (OR = 1.16, P = 2.5 × 10(-7)) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.

Published
2012
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10. Common breast cancer susceptibility loci are associated with triple-negative breast cancer.

Author

Stevens KN, Vachon CM, Lee AM, Slager S, Lesnick T, Olswold C, Fasching PA, Miron P, Eccles D, Carpenter JE, Godwin AK, Ambrosone C, Winqvist R, Brauch H, Schmidt MK, Cox A, Cross SS, Sawyer E, Hartmann A, Beckmann MW, Schulz-Wendtland R, Ekici AB, Tapper WJ, Gerty SM, Durcan L, Graham N, Hein R, Nickels S, Flesch-Janys D, Heinz J, Sinn HP, Konstantopoulou I, Fostira F, Pectasides D, Dimopoulos AM, Fountzilas G, Clarke CL, Balleine R, Olson JE, Fredericksen Z, Diasio RB, Pathak H, Ross E, Weaver J, Rüdiger T, Försti A, Dünnebier T, Ademuyiwa F, Kulkarni S, Pylkäs K, Jukkola-Vuorinen A, Ko YD, Van Limbergen E, Janssen H, Peto J, Fletcher O, Giles GG, Baglietto L, Verhoef S, Tomlinson I, Kosma VM, Beesley J, Greco D, Blomqvist C, Irwanto A, Liu J, Blows FM, Dawson SJ, Margolin S, Mannermaa A, Martin NG, Montgomery GW, Lambrechts D, dos Santos Silva I, Severi G, Hamann U, Pharoah P, Easton DF, Chang-Claude J, Yannoukakos D, Nevanlinna H, Wang X, and Couch FJ

Subjects
Adult, Aged, Breast Neoplasms etiology, Breast Neoplasms metabolism, Case-Control Studies, Chromosomes, Human, Pair 19 genetics, Female, Humans, Middle Aged, Receptors, Estrogen metabolism, Receptors, Progesterone metabolism, Risk, White People, Young Adult, Breast Neoplasms genetics, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Receptors, Estrogen genetics, Receptors, Progesterone genetics
Abstract

Triple-negative breast cancers are an aggressive subtype of breast cancer with poor survival, but there remains little known about the etiologic factors that promote its initiation and development. Commonly inherited breast cancer risk factors identified through genome-wide association studies display heterogeneity of effect among breast cancer subtypes as defined by the status of estrogen and progesterone receptors. In the Triple Negative Breast Cancer Consortium (TNBCC), 22 common breast cancer susceptibility variants were investigated in 2,980 Caucasian women with triple-negative breast cancer and 4,978 healthy controls. We identified six single-nucleotide polymorphisms, including rs2046210 (ESR1), rs12662670 (ESR1), rs3803662 (TOX3), rs999737 (RAD51L1), rs8170 (19p13.1), and rs8100241 (19p13.1), significantly associated with the risk of triple-negative breast cancer. Together, our results provide convincing evidence of genetic susceptibility for triple-negative breast cancer.

Published
2011
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11. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes

Author

Mavaddat, N., Michailidou, K., Dennis, J., Lush, M., Fachal, L., Lee, A., Tyrer, J. P., Chen, T. H., Wang, Q., Bolla, M. K., Yang, X., Adank, M. A., Ahearn, T., Aittomaki, K., Allen, J., Andrulis, I. L., Anton-Culver, H., Antonenkova, N. N., Arndt, V., Aronson, K. J., Auer, P. L., Auvinen, P., Barrdahl, M., Beane Freeman, L. E., Beckmann, M. W., Behrens, S., Benitez, J., Bermisheva, M., Bernstein, L., Blomqvist, C., Bogdanova, N. V., Bojesen, S. E., Bonanni, B., Borresen-Dale, A. L., Brauch, H., Bremer, M., Brenner, H., Brentnall, A., Brock, I. W., Brooks-Wilson, A., Brucker, S. Y., Bruning, T., Burwinkel, B., Campa, D., Carter, B. D., Castelao Fernández, José Esteban, Chanock, S. J., Chlebowski, R., Christiansen, H., Clarke, C. L., Collee, J. M., Cordina-Duverger, E., Cornelissen, S., Couch, F. J., Cox, A., Cross, S. S., Czene, K., Daly, M. B., Devilee, P., Dork, T., Dos-Santos-Silva, I., Dumont, M., Durcan, L., Dwek, M., Eccles, D. M., Ekici, A. B., Eliassen, A. H., Ellberg, C., Engel, C., Eriksson, M., Evans, D. G., Fasching, P. A., Figueroa, J., Fletcher, O., Flyger, H., Forsti, A., Fritschi, L., Gabrielson, M., Gago Dominguez, Manuela, Gapstur, S. M., Garcia-Saenz, J. A., Gaudet, M. M., Georgoulias, V., Giles, G. G., Gilyazova, I. R., Glendon, G., Goldberg, M. S., Goldgar, D. E., Gonzalez-Neira, A., Grenaker Alnaes, G. I., Grip, M., Gronwald, J., Grundy, A., Guenel, P., Haeberle, L., Hahnen, E., Haiman, C. A., Hakansson, N., Hamann, U., Hankinson, S. E., Muñoz Garzón, Victor, and others

Subjects
Adult, Aged, 80 and over, Multifactorial Inheritance, anciano, humanos, Age Factors, Reproducibility of Results, Breast Neoplasms, neoplasias de la mama, predisposición genética a la enfermedad, Middle Aged, adulto, Risk Assessment, Polymorphism, Single Nucleotide, herencia multifactorial, reproducibilidad de resultados, Receptors, Estrogen, evaluación de riesgos, Humans, Genetic Predisposition to Disease, anamnesis, Female, Medical History Taking, mediana edad, Aged
Abstract

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Published
2019

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