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Start Over Author "Goldberg MS" Journal american journal of human genetics
7 results on '"Goldberg MS"'

1. Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element.

Author

Baxter JS, Johnson N, Tomczyk K, Gillespie A, Maguire S, Brough R, Fachal L, Michailidou K, Bolla MK, Wang Q, Dennis J, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Augustinsson A, Becher H, Beckmann MW, Behrens S, Benitez J, Bermisheva M, Bogdanova NV, Bojesen SE, Brenner H, Brucker SY, Cai Q, Campa D, Canzian F, Castelao JE, Chan TL, Chang-Claude J, Chanock SJ, Chenevix-Trench G, Choi JY, Clarke CL, Colonna S, Conroy DM, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dossus L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Engel C, Fasching PA, Figueroa J, Flyger H, Gago-Dominguez M, Gao C, García-Closas M, García-Sáenz JA, Ghoussaini M, Giles GG, Goldberg MS, González-Neira A, Guénel P, Gündert M, Haeberle L, Hahnen E, Haiman CA, Hall P, Hamann U, Hartman M, Hatse S, Hauke J, Hollestelle A, Hoppe R, Hopper JL, Hou MF, Ito H, Iwasaki M, Jager A, Jakubowska A, Janni W, John EM, Joseph V, Jung A, Kaaks R, Kang D, Keeman R, Khusnutdinova E, Kim SW, Kosma VM, Kraft P, Kristensen VN, Kubelka-Sabit K, Kurian AW, Kwong A, Lacey JV, Lambrechts D, Larson NL, Larsson SC, Le Marchand L, Lejbkowicz F, Li J, Long J, Lophatananon A, Lubiński J, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Matsuo K, Mavroudis D, Mayes R, Menon U, Milne RL, Mohd Taib NA, Muir K, Muranen TA, Murphy RA, Nevanlinna H, O'Brien KM, Offit K, Olson JE, Olsson H, Park SK, Park-Simon TW, Patel AV, Peterlongo P, Peto J, Plaseska-Karanfilska D, Presneau N, Pylkäs K, Rack B, Rennert G, Romero A, Ruebner M, Rüdiger T, Saloustros E, Sandler DP, Sawyer EJ, Schmidt MK, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Shah M, Shen CY, Shu XO, Simard J, Southey MC, Stone J, Surowy H, Swerdlow AJ, Tamimi RM, Tapper WJ, Taylor JA, Teo SH, Teras LR, Terry MB, Toland AE, Tomlinson I, Truong T, Tseng CC, Untch M, Vachon CM, van den Ouweland AMW, Wang SS, Weinberg CR, Wendt C, Winham SJ, Winqvist R, Wolk A, Wu AH, Yamaji T, Zheng W, Ziogas A, Pharoah PDP, Dunning AM, Easton DF, Pettitt SJ, Lord CJ, Haider S, Orr N, and Fletcher O

Subjects
Breast Neoplasms genetics, CRISPR-Cas Systems, Cell Line, Chromosome Mapping, Chromosomes, Human, Pair 2, Female, Genetic Association Studies, Genetic Variation, Humans, Risk Factors, Sequence Deletion, Insulin-Like Growth Factor Binding Protein 5 genetics, Molecular Sequence Annotation, Promoter Regions, Genetic
Abstract

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10 -31 )., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Published
2021
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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. Evidence that the 5p12 Variant rs10941679 Confers Susceptibility to Estrogen-Receptor-Positive Breast Cancer through FGF10 and MRPS30 Regulation.

Author

Ghoussaini M, French JD, Michailidou K, Nord S, Beesley J, Canisus S, Hillman KM, Kaufmann S, Sivakumaran H, Moradi Marjaneh M, Lee JS, Dennis J, Bolla MK, Wang Q, Dicks E, Milne RL, Hopper JL, Southey MC, Schmidt MK, Broeks A, Muir K, Lophatananon A, Fasching PA, Beckmann MW, Fletcher O, Johnson N, Sawyer EJ, Tomlinson I, Burwinkel B, Marme F, Guénel P, Truong T, Bojesen SE, Flyger H, Benitez J, González-Neira A, Alonso MR, Pita G, Neuhausen SL, Anton-Culver H, Brenner H, Arndt V, Meindl A, Schmutzler RK, Brauch H, Hamann U, Tessier DC, Vincent D, Nevanlinna H, Khan S, Matsuo K, Ito H, Dörk T, Bogdanova NV, Lindblom A, Margolin S, Mannermaa A, Kosma VM, Wu AH, Van Den Berg D, Lambrechts D, Floris G, Chang-Claude J, Rudolph A, Radice P, Barile M, Couch FJ, Hallberg E, Giles GG, Haiman CA, Le Marchand L, Goldberg MS, Teo SH, Yip CH, Borresen-Dale AL, Zheng W, Cai Q, Winqvist R, Pylkäs K, Andrulis IL, Devilee P, Tollenaar RA, García-Closas M, Figueroa J, Hall P, Czene K, Brand JS, Darabi H, Eriksson M, Hooning MJ, Koppert LB, Li J, Shu XO, Zheng Y, Cox A, Cross SS, Shah M, Rhenius V, Choi JY, Kang D, Hartman M, Chia KS, Kabisch M, Torres D, Luccarini C, Conroy DM, Jakubowska A, Lubinski J, Sangrajrang S, Brennan P, Olswold C, Slager S, Shen CY, Hou MF, Swerdlow A, Schoemaker MJ, Simard J, Pharoah PD, Kristensen V, Chenevix-Trench G, Easton DF, Dunning AM, and Edwards SL

Subjects
Alleles, Case-Control Studies, Cell Line, Tumor, Enhancer Elements, Genetic genetics, Fibroblast Growth Factor 10 metabolism, Haplotypes genetics, Humans, Promoter Regions, Genetic genetics, Quantitative Trait Loci genetics, Receptor, Fibroblast Growth Factor, Type 2 metabolism, Breast Neoplasms genetics, Breast Neoplasms metabolism, Chromosomes, Human, Pair 5 genetics, Fibroblast Growth Factor 10 genetics, Genetic Predisposition to Disease genetics, Polymorphism, Single Nucleotide genetics, Receptors, Estrogen metabolism
Abstract

Genome-wide association studies (GWASs) have revealed increased breast cancer risk associated with multiple genetic variants at 5p12. Here, we report the fine mapping of this locus using data from 104,660 subjects from 50 case-control studies in the Breast Cancer Association Consortium (BCAC). With data for 3,365 genotyped and imputed SNPs across a 1 Mb region (positions 44,394,495-45,364,167; NCBI build 37), we found evidence for at least three independent signals: the strongest signal, consisting of a single SNP rs10941679, was associated with risk of estrogen-receptor-positive (ER + ) breast cancer (per-g allele OR ER + = 1.15; 95% CI 1.13-1.18; p = 8.35 × 10 -30 ). After adjustment for rs10941679, we detected signal 2, consisting of 38 SNPs more strongly associated with ER-negative (ER - ) breast cancer (lead SNP rs6864776: per-a allele OR ER - = 1.10; 95% CI 1.05-1.14; p conditional = 1.44 × 10 -12 ), and a single signal 3 SNP (rs200229088: per-t allele OR ER + = 1.12; 95% CI 1.09-1.15; p conditional = 1.12 × 10 -05 ). Expression quantitative trait locus analysis in normal breast tissues and breast tumors showed that the g (risk) allele of rs10941679 was associated with increased expression of FGF10 and MRPS30. Functional assays demonstrated that SNP rs10941679 maps to an enhancer element that physically interacts with the FGF10 and MRPS30 promoter regions in breast cancer cell lines. FGF10 is an oncogene that binds to FGFR2 and is overexpressed in ∼10% of human breast cancers, whereas MRPS30 plays a key role in apoptosis. These data suggest that the strongest signal of association at 5p12 is mediated through coordinated activation of FGF10 and MRPS30, two candidate genes for breast cancer pathogenesis., (Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2016
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4. Polymorphisms in a Putative Enhancer at the 10q21.2 Breast Cancer Risk Locus Regulate NRBF2 Expression.

Author

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 RA, 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, and Chenevix-Trench G

Subjects
Age Factors, Asian People genetics, Autophagy-Related Proteins, Body Mass Index, Chromosome Mapping, Female, Genome-Wide Association Study, Genotype, Humans, Luciferases, Odds Ratio, Polymorphism, Single Nucleotide genetics, Quantitative Trait Loci genetics, Regression Analysis, Trans-Activators metabolism, White People genetics, Breast Neoplasms genetics, Chromosomes, Human, Pair 10 genetics, DNA-Binding Proteins genetics, Enhancer Elements, Genetic genetics, Gene Expression Regulation genetics, Trans-Activators genetics, Transcription Factors genetics
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., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2015
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5. Fine-scale mapping of the 5q11.2 breast cancer locus reveals at least three independent risk variants regulating MAP3K1.

Author

Glubb DM, Maranian MJ, Michailidou K, Pooley KA, Meyer KB, Kar S, Carlebur S, O'Reilly M, Betts JA, Hillman KM, Kaufmann S, Beesley J, Canisius S, Hopper JL, Southey MC, Tsimiklis H, Apicella C, Schmidt MK, Broeks A, Hogervorst FB, van der Schoot CE, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Fasching PA, Ruebner M, Ekici AB, Beckmann MW, Peto J, dos-Santos-Silva I, Fletcher O, Johnson N, Pharoah PD, Bolla MK, Wang Q, Dennis J, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Burwinkel B, Marme F, Yang R, Surowy H, Guénel P, Truong T, Menegaux F, Sanchez M, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, González-Neira A, Benitez J, Zamora MP, Arias Perez JI, Anton-Culver H, Neuhausen SL, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Meindl A, Schmutzler RK, Brauch H, Ko YD, Brüning T, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Matsuo K, Ito H, Iwata H, Tanaka H, Dörk T, Bogdanova NV, Helbig S, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Lambrechts D, Zhao H, Weltens C, van Limbergen E, Chang-Claude J, Flesch-Janys D, Rudolph A, Seibold P, Radice P, Peterlongo P, Barile M, Capra F, Couch FJ, Olson JE, Hallberg E, Vachon C, Giles GG, Milne RL, McLean C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Teo SH, Yip CH, See MH, Cornes B, Cheng CY, Ikram MK, Kristensen V, Zheng W, Halverson SL, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Kauppila S, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Devilee P, Tollenaar RA, Seynaeve C, Van Asperen CJ, García-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Klevebring D, Darabi H, Eriksson M, Hooning MJ, Hollestelle A, Martens JW, Collée JM, Hall P, Li J, Humphreys K, Shu XO, Lu W, Gao YT, Cai H, Cox A, Cross SS, Reed MW, Blot W, Signorello LB, Cai Q, Shah M, Ghoussaini M, Kang D, Choi JY, Park SK, Noh DY, Hartman M, Miao H, Lim WY, Tang A, Hamann U, Torres D, Jakubowska A, Lubinski J, Jaworska K, Durda K, Sangrajrang S, Gaborieau V, Brennan P, McKay J, Olswold C, Slager S, Toland AE, Yannoukakos D, Shen CY, Wu PE, Yu JC, Hou MF, Swerdlow A, Ashworth A, Orr N, Jones M, Pita G, Alonso MR, Álvarez N, Herrero D, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Ahmed S, Healey CS, Brown MA, Ponder BA, Chenevix-Trench G, Thompson DJ, Edwards SL, Easton DF, Dunning AM, and French JD

Subjects
Alleles, Case-Control Studies, Cell Line, Tumor, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotyping Techniques, Humans, MAP Kinase Kinase Kinase 1 metabolism, MCF-7 Cells, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Racial Groups genetics, Risk Factors, Breast Neoplasms genetics, Chromosome Mapping, Chromosomes, Human, Pair 5 genetics, MAP Kinase Kinase Kinase 1 genetics, Quantitative Trait Loci
Abstract

Genome-wide association studies (GWASs) have revealed SNP rs889312 on 5q11.2 to be associated with breast cancer risk in women of European ancestry. In an attempt to identify the biologically relevant variants, we analyzed 909 genetic variants across 5q11.2 in 103,991 breast cancer individuals and control individuals from 52 studies in the Breast Cancer Association Consortium. Multiple logistic regression analyses identified three independent risk signals: the strongest associations were with 15 correlated variants (iCHAV1), where the minor allele of the best candidate, rs62355902, associated with significantly increased risks of both estrogen-receptor-positive (ER(+): odds ratio [OR] = 1.24, 95% confidence interval [CI] = 1.21-1.27, ptrend = 5.7 × 10(-44)) and estrogen-receptor-negative (ER(-): OR = 1.10, 95% CI = 1.05-1.15, ptrend = 3.0 × 10(-4)) tumors. After adjustment for rs62355902, we found evidence of association of a further 173 variants (iCHAV2) containing three subsets with a range of effects (the strongest was rs113317823 [pcond = 1.61 × 10(-5)]) and five variants composing iCHAV3 (lead rs11949391; ER(+): OR = 0.90, 95% CI = 0.87-0.93, pcond = 1.4 × 10(-4)). Twenty-six percent of the prioritized candidate variants coincided with four putative regulatory elements that interact with the MAP3K1 promoter through chromatin looping and affect MAP3K1 promoter activity. Functional analysis indicated that the cancer risk alleles of four candidates (rs74345699 and rs62355900 [iCHAV1], rs16886397 [iCHAV2a], and rs17432750 [iCHAV3]) increased MAP3K1 transcriptional activity. Chromatin immunoprecipitation analysis revealed diminished GATA3 binding to the minor (cancer-protective) allele of rs17432750, indicating a mechanism for its action. We propose that the cancer risk alleles act to increase MAP3K1 expression in vivo and might promote breast cancer cell survival., (Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2015
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6. Fine-scale mapping of the FGFR2 breast cancer risk locus: putative functional variants differentially bind FOXA1 and E2F1.

Author

Meyer KB, O'Reilly M, Michailidou K, Carlebur S, Edwards SL, French JD, Prathalingham R, Dennis J, Bolla MK, Wang Q, de Santiago I, Hopper JL, Tsimiklis H, Apicella C, Southey MC, Schmidt MK, Broeks A, Van 't Veer LJ, Hogervorst FB, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Fasching PA, Lux MP, Ekici AB, Beckmann MW, Peto J, Dos Santos Silva I, Fletcher O, Johnson N, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Marme F, Schneeweiss A, Sohn C, Burwinkel B, Guénel P, Truong T, Laurent-Puig P, Menegaux F, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Milne RL, Zamora MP, Arias JI, Benitez J, Neuhausen S, Anton-Culver H, Ziogas A, Dur CC, Brenner H, Müller H, Arndt V, Stegmaier C, Meindl A, Schmutzler RK, Engel C, Ditsch N, Brauch H, Brüning T, Ko YD, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Matsuo K, Ito H, Iwata H, Yatabe Y, Dörk T, Helbig S, Bogdanova NV, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Chenevix-Trench G, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Lambrechts D, Thienpont B, Christiaens MR, Smeets A, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Radice P, Peterlongo P, Bonanni B, Bernard L, Couch FJ, Olson JE, Wang X, Purrington K, Giles GG, Severi G, Baglietto L, McLean C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Teo SH, Yip CH, Phuah SY, Kristensen V, Grenaker Alnæs G, Børresen-Dale AL, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Kauppila S, Andrulis IL, Knight JA, Glendon G, Tchatchou S, Devilee P, Tollenaar RA, Seynaeve CM, García-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Darabi H, Eriksson K, Hooning MJ, Martens JW, van den Ouweland AM, van Deurzen CH, Hall P, Li J, Liu J, Humphreys K, Shu XO, Lu W, Gao YT, Cai H, Cox A, Reed MW, Blot W, Signorello LB, Cai Q, Pharoah PD, Ghoussaini M, Harrington P, Tyrer J, Kang D, Choi JY, Park SK, Noh DY, Hartman M, Hui M, Lim WY, Buhari SA, Hamann U, Försti A, Rüdiger T, Ulmer HU, Jakubowska A, Lubinski J, Jaworska K, Durda K, Sangrajrang S, Gaborieau V, Brennan P, McKay J, Vachon C, Slager S, Fostira F, Pilarski R, Shen CY, Hsiung CN, Wu PE, Hou MF, Swerdlow A, Ashworth A, Orr N, Schoemaker MJ, Ponder BA, Dunning AM, and Easton DF

Subjects
Alleles, Asian People genetics, Binding Sites, Black People genetics, Case-Control Studies, Cell Line, Tumor, Chromatin Immunoprecipitation, E2F1 Transcription Factor genetics, E2F1 Transcription Factor metabolism, Female, Gene Expression Regulation, Neoplastic, Genetic Association Studies, Haplotypes, Hepatocyte Nuclear Factor 3-alpha genetics, Hepatocyte Nuclear Factor 3-alpha metabolism, Humans, Position-Specific Scoring Matrices, Promoter Regions, Genetic, Protein Binding, RNA Interference, Receptor, Fibroblast Growth Factor, Type 2 metabolism, White People genetics, Breast Neoplasms genetics, Breast Neoplasms metabolism, Chromosome Mapping, Genetic Loci, Receptor, Fibroblast Growth Factor, Type 2 genetics
Abstract

The 10q26 locus in the second intron of FGFR2 is the locus most strongly associated with estrogen-receptor-positive breast cancer in genome-wide association studies. We conducted fine-scale mapping in case-control studies genotyped with a custom chip (iCOGS), comprising 41 studies (n = 89,050) of European ancestry, 9 Asian ancestry studies (n = 13,983), and 2 African ancestry studies (n = 2,028) from the Breast Cancer Association Consortium. We identified three statistically independent risk signals within the locus. Within risk signals 1 and 3, genetic analysis identified five and two variants, respectively, highly correlated with the most strongly associated SNPs. By using a combination of genetic fine mapping, data on DNase hypersensitivity, and electrophoretic mobility shift assays to study protein-DNA binding, we identified rs35054928, rs2981578, and rs45631563 as putative functional SNPs. Chromatin immunoprecipitation showed that FOXA1 preferentially bound to the risk-associated allele (C) of rs2981578 and was able to recruit ERα to this site in an allele-specific manner, whereas E2F1 preferentially bound the risk variant of rs35054928. The risk alleles were preferentially found in open chromatin and bound by Ser5 phosphorylated RNA polymerase II, suggesting that the risk alleles are associated with changes in transcription. Chromatin conformation capture demonstrated that the risk region was able to interact with the promoter of FGFR2, the likely target gene of this risk region. A role for FOXA1 in mediating breast cancer susceptibility at this locus is consistent with the finding that the FGFR2 risk locus primarily predisposes to estrogen-receptor-positive disease., (Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2013
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7. Functional variants at the 11q13 risk locus for breast cancer regulate cyclin D1 expression through long-range enhancers.

Author

French JD, Ghoussaini M, Edwards SL, Meyer KB, Michailidou K, Ahmed S, Khan S, Maranian MJ, O'Reilly M, Hillman KM, Betts JA, Carroll T, Bailey PJ, Dicks E, Beesley J, Tyrer J, Maia AT, Beck A, Knoblauch NW, Chen C, Kraft P, Barnes D, González-Neira A, Alonso MR, Herrero D, Tessier DC, Vincent D, Bacot F, Luccarini C, Baynes C, Conroy D, Dennis J, Bolla MK, Wang Q, Hopper JL, Southey MC, Schmidt MK, Broeks A, Verhoef S, Cornelissen S, Muir K, Lophatananon A, Stewart-Brown S, Siriwanarangsan P, Fasching PA, Loehberg CR, Ekici AB, Beckmann MW, Peto J, dos Santos Silva I, Johnson N, Aitken Z, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Marme F, Schneeweiss A, Sohn C, Burwinkel B, Guénel P, Truong T, Laurent-Puig P, Menegaux F, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Milne RL, Zamora MP, Arias Perez JI, Benitez J, Anton-Culver H, Brenner H, Müller H, Arndt V, Stegmaier C, Meindl A, Lichtner P, Schmutzler RK, Engel C, Brauch H, Hamann U, Justenhoven C, Aaltonen K, Heikkilä P, Aittomäki K, Blomqvist C, Matsuo K, Ito H, Iwata H, Sueta A, Bogdanova NV, Antonenkova NN, Dörk T, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Wu AH, Tseng CC, Van Den Berg D, Stram DO, Lambrechts D, Peeters S, Smeets A, Floris G, Chang-Claude J, Rudolph A, Nickels S, Flesch-Janys D, Radice P, Peterlongo P, Bonanni B, Sardella D, Couch FJ, Wang X, Pankratz VS, Lee A, Giles GG, Severi G, Baglietto L, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Goldberg MS, Labrèche F, Dumont M, Teo SH, Yip CH, Ng CH, Vithana EN, Kristensen V, Zheng W, Deming-Halverson S, Shrubsole M, Long J, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Andrulis IL, Knight JA, Glendon G, Mulligan AM, Devilee P, Seynaeve C, García-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Klevebring D, Schoof N, Hooning MJ, Martens JW, Collée JM, Tilanus-Linthorst M, Hall P, Li J, Liu J, Humphreys K, Shu XO, Lu W, Gao YT, Cai H, Cox A, Balasubramanian SP, Blot W, Signorello LB, Cai Q, Pharoah PD, Healey CS, Shah M, Pooley KA, Kang D, Yoo KY, Noh DY, Hartman M, Miao H, Sng JH, Sim X, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Sangrajrang S, Gaborieau V, McKay J, Toland AE, Ambrosone CB, Yannoukakos D, Godwin AK, Shen CY, Hsiung CN, Wu PE, Chen ST, Swerdlow A, Ashworth A, Orr N, Schoemaker MJ, Ponder BA, Nevanlinna H, Brown MA, Chenevix-Trench G, Easton DF, and Dunning AM

Subjects
Binding Sites, Case-Control Studies, Cell Line, Tumor, Chromatin chemistry, Chromatin genetics, Chromatin Immunoprecipitation, Cyclin D1 metabolism, Electrophoretic Mobility Shift Assay, Female, GATA3 Transcription Factor antagonists & inhibitors, GATA3 Transcription Factor genetics, GATA3 Transcription Factor metabolism, Gene Expression Regulation, Neoplastic, Humans, Luciferases metabolism, Promoter Regions, Genetic genetics, RNA, Messenger genetics, RNA, Small Interfering genetics, Real-Time Polymerase Chain Reaction, Reverse Transcriptase Polymerase Chain Reaction, Silencer Elements, Transcriptional genetics, ets-Domain Protein Elk-4 antagonists & inhibitors, ets-Domain Protein Elk-4 genetics, ets-Domain Protein Elk-4 metabolism, Breast Neoplasms genetics, Chromosomes, Human, Pair 11 genetics, Cyclin D1 genetics, Enhancer Elements, Genetic genetics, Polymorphism, Single Nucleotide genetics
Abstract

Analysis of 4,405 variants in 89,050 European subjects from 41 case-control studies identified three independent association signals for estrogen-receptor-positive tumors at 11q13. The strongest signal maps to a transcriptional enhancer element in which the G allele of the best candidate causative variant rs554219 increases risk of breast cancer, reduces both binding of ELK4 transcription factor and luciferase activity in reporter assays, and may be associated with low cyclin D1 protein levels in tumors. Another candidate variant, rs78540526, lies in the same enhancer element. Risk association signal 2, rs75915166, creates a GATA3 binding site within a silencer element. Chromatin conformation studies demonstrate that these enhancer and silencer elements interact with each other and with their likely target gene, CCND1., (Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Published
2013
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