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Southey MC, Goldgar DE, Winqvist R, Pylkäs K, Couch F, Tischkowitz M, Foulkes WD, Dennis J, Michailidou K, van Rensburg EJ, Heikkinen T, Nevanlinna H, Hopper JL, Dörk T, Claes KB, Reis-Filho J, Teo ZL, Radice P, Catucci I, Peterlongo P, Tsimiklis H, Odefrey FA, Dowty JG, Schmidt MK, Broeks A, Hogervorst FB, Verhoef S, Carpenter J, Clarke C, Scott RJ, Fasching PA, Haeberle L, Ekici AB, Beckmann MW, Peto J, Dos-Santos-Silva I, Fletcher O, Johnson N, Bolla MK, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Marme F, Burwinkel B, Yang R, Guénel P, Truong T, Menegaux F, Sanchez M, Bojesen S, Nielsen SF, Flyger H, Benitez J, Zamora MP, Perez JIA, Menéndez P, Anton-Culver H, Neuhausen S, Ziogas A, Clarke CA, Brenner H, Arndt V, Stegmaier C, Brauch H, Brüning T, Ko YD, Muranen TA, Aittomäki K, Blomqvist C, Bogdanova NV, Antonenkova NN, Lindblom A, Margolin S, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Spurdle AB, Investigators KC, Wauters E, Smeets D, Beuselinck B, Floris G, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Olson JE, Vachon C, Pankratz VS, McLean C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Kristensen V, Alnæs GG, Zheng W, Hunter DJ, Lindstrom S, Hankinson SE, Kraft P, Andrulis I, Knight JA, Glendon G, Mulligan AM, Jukkola-Vuorinen A, Grip M, Kauppila S, Devilee P, Tollenaar RAEM, Seynaeve C, Hollestelle A, Garcia-Closas M, Figueroa J, Chanock SJ, Lissowska J, Czene K, Darabi H, Eriksson M, Eccles DM, Rafiq S, Tapper WJ, Gerty SM, Hooning MJ, Martens JWM, Collée JM, Tilanus-Linthorst M, Hall P, Li J, Brand JS, Humphreys K, Cox A, Reed MWR, Luccarini C, Baynes C, Dunning AM, Hamann U, Torres D, Ulmer HU, Rüdiger T, Jakubowska A, Lubinski J, Jaworska K, Durda K, Slager S, Toland AE, Ambrosone CB, Yannoukakos D, Swerdlow A, Ashworth A, Orr N, Jones M, González-Neira A, Pita G, Alonso MR, Álvarez N, Herrero D, Tessier DC, Vincent D, Bacot F, Simard J, Dumont M, Soucy P, Eeles R, Muir K, Wiklund F, Gronberg H, Schleutker J, Nordestgaard BG, Weischer M, Travis RC, Neal D, Donovan JL, Hamdy FC, Khaw KT, Stanford JL, Blot WJ, Thibodeau S, Schaid DJ, Kelley JL, Maier C, Kibel AS, Cybulski C, Cannon-Albright L, Butterbach K, Park J, Kaneva R, Batra J, Teixeira MR, Kote-Jarai Z, Olama AAA, Benlloch S, Renner SP, Hartmann A, Hein A, Ruebner M, Lambrechts D, Van Nieuwenhuysen E, Vergote I, Lambretchs S, Doherty JA, Rossing MA, Nickels S, Eilber U, Wang-Gohrke S, Odunsi K, Sucheston-Campbell LE, Friel G, Lurie G, Killeen JL, Wilkens LR, Goodman MT, Runnebaum I, Hillemanns PA, Pelttari LM, Butzow R, Modugno F, Edwards RP, Ness RB, Moysich KB, du Bois A, Heitz F, Harter P, Kommoss S, Karlan BY, Walsh C, Lester J, Jensen A, Kjaer SK, Høgdall E, Peissel B, Bonanni B, Bernard L, Goode EL, Fridley BL, Vierkant RA, Cunningham JM, Larson MC, Fogarty ZC, Kalli KR, Liang D, Lu KH, Hildebrandt MAT, Wu X, Levine DA, Dao F, Bisogna M, Berchuck A, Iversen ES, Marks JR, Akushevich L, Cramer DW, Schildkraut J, Terry KL, Poole EM, Stampfer M, Tworoger SS, Bandera EV, Orlow I, Olson SH, Bjorge L, Salvesen HB, van Altena AM, Aben KKH, Kiemeney LA, Massuger LFAG, Pejovic T, Bean Y, Brooks-Wilson A, Kelemen LE, Cook LS, Le ND, Górski B, Gronwald J, Menkiszak J, Høgdall CK, Lundvall L, Nedergaard L, Engelholm SA, Dicks E, Tyrer J, Campbell I, McNeish I, Paul J, Siddiqui N, Glasspool R, Whittemore AS, Rothstein JH, McGuire V, Sieh W, Cai H, Shu XO, Teten RT, Sutphen R, McLaughlin JR, Narod SA, Phelan CM, Monteiro AN, Fenstermacher D, Lin HY, Permuth JB, Sellers TA, Chen YA, Tsai YY, Chen Z, Gentry-Maharaj A, Gayther SA, Ramus SJ, Menon U, Wu AH, Pearce CL, Van Den Berg D, Pike MC, Dansonka-Mieszkowska A, Plisiecka-Halasa J, Moes-Sosnowska J, Kupryjanczyk J, Pharoah PD, Song H, Winship I, Chenevix-Trench G, Giles GG, Tavtigian SV, Easton DF, Milne RL. PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS. J Med Genet 2016; 53:800-811. [PMID: 27595995 PMCID: PMC5200636 DOI: 10.1136/jmedgenet-2016-103839] [Citation(s) in RCA: 148] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2016] [Revised: 06/01/2016] [Accepted: 06/21/2016] [Indexed: 12/21/2022]
Abstract
BACKGROUND The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. METHODS We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. RESULTS For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10-5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10-8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. CONCLUSIONS This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.
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Scott CM, Joo JE, O’Callaghan N, Buchanan DD, Clendenning M, Giles GG, Hopper JL, Wong EM, Southey MC. Methylation of Breast Cancer Predisposition Genes in Early-Onset Breast Cancer: Australian Breast Cancer Family Registry. PLoS One 2016; 11:e0165436. [PMID: 27902704 PMCID: PMC5130174 DOI: 10.1371/journal.pone.0165436] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Accepted: 10/11/2016] [Indexed: 12/31/2022] Open
Abstract
DNA methylation can mimic the effects of both germline and somatic mutations for cancer predisposition genes such as BRCA1 and p16INK4a. Constitutional DNA methylation of the BRCA1 promoter has been well described and is associated with an increased risk of early-onset breast cancers that have BRCA1-mutation associated histological features. The role of methylation in the context of other breast cancer predisposition genes has been less well studied and often with conflicting or ambiguous outcomes. We examined the role of methylation in known breast cancer susceptibility genes in breast cancer predisposition and tumor development. We applied the Infinium HumanMethylation450 Beadchip (HM450K) array to blood and tumor-derived DNA from 43 women diagnosed with breast cancer before the age of 40 years and measured the methylation profiles across promoter regions of BRCA1, BRCA2, ATM, PALB2, CDH1, TP53, FANCM, CHEK2, MLH1, MSH2, MSH6 and PMS2. Prior genetic testing had demonstrated that these women did not carry a germline mutation in BRCA1, ATM, CHEK2, PALB2, TP53, BRCA2, CDH1 or FANCM. In addition to the BRCA1 promoter region, this work identified regions with variable methylation at multiple breast cancer susceptibility genes including PALB2 and MLH1. Methylation at the region of MLH1 in these breast cancers was not associated with microsatellite instability. This work informs future studies of the role of methylation in breast cancer susceptibility gene silencing.
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Liu J, Lončar I, Collée JM, Bolla MK, Dennis J, Michailidou K, Wang Q, Andrulis IL, Barile M, Beckmann MW, Behrens S, Benitez J, Blomqvist C, Boeckx B, Bogdanova NV, Bojesen SE, Brauch H, Brennan P, Brenner H, Broeks A, Burwinkel B, Chang-Claude J, Chen ST, Chenevix-Trench G, Cheng CY, Choi JY, Couch FJ, Cox A, Cross SS, Cuk K, Czene K, Dörk T, dos-Santos-Silva I, Fasching PA, Figueroa J, Flyger H, García-Closas M, Giles GG, Glendon G, Goldberg MS, González-Neira A, Guénel P, Haiman CA, Hamann U, Hart SN, Hartman M, Hatse S, Hopper JL, Ito H, Jakubowska A, Kabisch M, Kang D, Kosma VM, Kristensen VN, Le Marchand L, Lee E, Li J, Lophatananon A, Jan Lubinski, Mannermaa A, Matsuo K, Milne RL, Neuhausen SL, Nevanlinna H, Orr N, Perez JIA, Peto J, Putti TC, Pylkäs K, Radice P, Sangrajrang S, Sawyer EJ, Schmidt MK, Schneeweiss A, Shen CY, Shrubsole MJ, Shu XO, Simard J, Southey MC, Swerdlow A, Teo SH, Tessier DC, Thanasitthichai S, Tomlinson I, Torres D, Truong T, Tseng CC, Vachon C, Winqvist R, Wu AH, Yannoukakos D, Zheng W, Hall P, Dunning AM, Easton DF, Hooning MJ, van den Ouweland AMW, Martens JWM, Hollestelle A. rs2735383, located at a microRNA binding site in the 3'UTR of NBS1, is not associated with breast cancer risk. Sci Rep 2016; 6:36874. [PMID: 27845421 PMCID: PMC5109293 DOI: 10.1038/srep36874] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Accepted: 10/21/2016] [Indexed: 02/08/2023] Open
Abstract
NBS1, also known as NBN, plays an important role in maintaining genomic stability. Interestingly, rs2735383 G > C, located in a microRNA binding site in the 3'-untranslated region (UTR) of NBS1, was shown to be associated with increased susceptibility to lung and colorectal cancer. However, the relation between rs2735383 and susceptibility to breast cancer is not yet clear. Therefore, we genotyped rs2735383 in 1,170 familial non-BRCA1/2 breast cancer cases and 1,077 controls using PCR-based restriction fragment length polymorphism (RFLP-PCR) analysis, but found no association between rs2735383CC and breast cancer risk (OR = 1.214, 95% CI = 0.936-1.574, P = 0.144). Because we could not exclude a small effect size due to a limited sample size, we further analyzed imputed rs2735383 genotypes (r2 > 0.999) of 47,640 breast cancer cases and 46,656 controls from the Breast Cancer Association Consortium (BCAC). However, rs2735383CC was not associated with overall breast cancer risk in European (OR = 1.014, 95% CI = 0.969-1.060, P = 0.556) nor in Asian women (OR = 0.998, 95% CI = 0.905-1.100, P = 0.961). Subgroup analyses by age, age at menarche, age at menopause, menopausal status, number of pregnancies, breast feeding, family history and receptor status also did not reveal a significant association. This study therefore does not support the involvement of the genotype at NBS1 rs2735383 in breast cancer susceptibility.
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Catucci I, Radice P, Milne RL, Couch FJ, Southey MC, Peterlongo P. The PALB2 p.Leu939Trp mutation is not associated with breast cancer risk. Breast Cancer Res 2016; 18:111. [PMID: 27829436 PMCID: PMC5101669 DOI: 10.1186/s13058-016-0762-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
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Hampras SS, Sucheston-Campbell LE, Cannioto R, Chang-Claude J, Modugno F, Dörk T, Hillemanns P, Preus L, Knutson KL, Wallace PK, Hong CC, Friel G, Davis W, Nesline M, Pearce CL, Kelemen LE, Goodman MT, Bandera EV, Terry KL, Schoof N, Eng KH, Clay A, Singh PK, Joseph JM, Aben KK, Anton-Culver H, Antonenkova N, Baker H, Bean Y, Beckmann MW, Bisogna M, Bjorge L, Bogdanova N, Brinton LA, Brooks-Wilson A, Bruinsma F, Butzow R, Campbell IG, Carty K, Cook LS, Cramer DW, Cybulski C, Dansonka-Mieszkowska A, Dennis J, Despierre E, Dicks E, Doherty JA, du Bois A, Dürst M, Easton D, Eccles D, Edwards RP, Ekici AB, Fasching PA, Fridley BL, Gao YT, Gentry-Maharaj A, Giles GG, Glasspool R, Gronwald J, Harrington P, Harter P, Hasmad HN, Hein A, Heitz F, Hildebrandt MA, Hogdall C, Hogdall E, Hosono S, Iversen ES, Jakubowska A, Jensen A, Ji BT, Karlan BY, Kellar M, Kelley JL, Kiemeney LA, Klapdor R, Kolomeyevskaya N, Krakstad C, Kjaer SK, Kruszka B, Kupryjanczyk J, Lambrechts D, Lambrechts S, Le ND, Lee AW, Lele S, Leminen A, Lester J, Levine DA, Liang D, Lissowska J, Liu S, Lu K, Lubinski J, Lundvall L, Massuger LF, Matsuo K, McGuire V, McLaughlin JR, McNeish I, Menon U, Moes-Sosnowska J, Narod SA, Nedergaard L, Nevanlinna H, Nickels S, Olson SH, Orlow I, Weber RP, Paul J, Pejovic T, Pelttari LM, Perkins B, Permuth-Wey J, Pike MC, Plisiecka-Halasa J, Poole EM, Risch HA, Rossing MA, Rothstein JH, Rudolph A, Runnebaum IB, Rzepecka IK, Salvesen HB, Schernhammer E, Schmitt K, Schwaab I, Shu XO, Shvetsov YB, Siddiqui N, Sieh W, Song H, Southey MC, Tangen IL, Teo SH, Thompson PJ, Timorek A, Tsai YY, Tworoger SS, Tyrer J, van Altena AM, Vergote I, Vierkant RA, Walsh C, Wang-Gohrke S, Wentzensen N, Whittemore AS, Wicklund KG, Wilkens LR, Wu AH, Wu X, Woo YL, Yang H, Zheng W, Ziogas A, Gayther SA, Ramus SJ, Sellers TA, Schildkraut JM, Phelan CM, Berchuck A, Chenevix-Trench G, Cunningham JM, Pharoah PP, Ness RB, Odunsi K, Goode EL, Moysich KB. Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer. Oncotarget 2016; 7:69097-69110. [PMID: 27533245 PMCID: PMC5340115 DOI: 10.18632/oncotarget.10215] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/1969] [Accepted: 12/31/1969] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer. METHODS In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients. RESULTS The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively). CONCLUSIONS Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.
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MESH Headings
- Adenocarcinoma, Clear Cell/genetics
- Adenocarcinoma, Clear Cell/immunology
- Adult
- Aged
- Carcinoma, Ovarian Epithelial
- Female
- Gene Expression Regulation, Neoplastic
- Gene Frequency
- Genetic Predisposition to Disease/genetics
- Genotype
- Humans
- Middle Aged
- Neoplasms, Glandular and Epithelial/genetics
- Neoplasms, Glandular and Epithelial/immunology
- Ovarian Neoplasms/genetics
- Ovarian Neoplasms/immunology
- Polymorphism, Single Nucleotide
- Protein Serine-Threonine Kinases/genetics
- Receptor, Transforming Growth Factor-beta Type II
- Receptors, Transforming Growth Factor beta/genetics
- Risk Factors
- T-Lymphocytes, Regulatory/immunology
- T-Lymphocytes, Regulatory/metabolism
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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 RAEM, 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 PDP, Kristensen V, Chenevix-Trench G, Easton DF, Dunning AM, Edwards SL. Evidence that the 5p12 Variant rs10941679 Confers Susceptibility to Estrogen-Receptor-Positive Breast Cancer through FGF10 and MRPS30 Regulation. Am J Hum Genet 2016; 99:903-911. [PMID: 27640304 PMCID: PMC5065698 DOI: 10.1016/j.ajhg.2016.07.017] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Accepted: 07/16/2016] [Indexed: 11/24/2022] Open
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.
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Win AK, Reece JC, Dowty JG, Buchanan DD, Clendenning M, Rosty C, Southey MC, Young JP, Cleary SP, Kim H, Cotterchio M, Macrae FA, Tucker KM, Baron JA, Burnett T, Le Marchand L, Casey G, Haile RW, Newcomb PA, Thibodeau SN, Hopper JL, Gallinger S, Winship IM, Lindor NM, Jenkins MA. Risk of extracolonic cancers for people with biallelic and monoallelic mutations in MUTYH. Int J Cancer 2016; 139:1557-63. [PMID: 27194394 PMCID: PMC5094810 DOI: 10.1002/ijc.30197] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Revised: 05/03/2016] [Accepted: 05/06/2016] [Indexed: 01/07/2023]
Abstract
Germline mutations in the DNA base excision repair gene MUTYH are known to increase a carrier's risk of colorectal cancer. However, the risks of other (extracolonic) cancers for MUTYH mutation carriers are not well defined. We identified 266 probands (91% Caucasians) with a MUTYH mutation (41 biallelic and 225 monoallelic) from the Colon Cancer Family Registry. Mutation status, sex, age and histories of cancer from their 1,903 first- and 3,255 second-degree relatives were analyzed using modified segregation analysis conditioned on the ascertainment criteria. Compared with incidences for the general population, hazard ratios (HRs) (95% confidence intervals [CIs]) for biallelic MUTYH mutation carriers were: urinary bladder cancer 19 (3.7-97) and ovarian cancer 17 (2.4-115). The HRs (95% CI) for monoallelic MUTYH mutation carriers were: gastric cancer 9.3 (6.7-13); hepatobiliary cancer 4.5 (2.7-7.5); endometrial cancer 2.1 (1.1-3.9) and breast cancer 1.4 (1.0-2.0). There was no evidence for an increased risk of cancers at the other sites examined (brain, pancreas, kidney or prostate). Based on the USA population incidences, the estimated cumulative risks (95% CI) to age 70 years for biallelic mutation carriers were: bladder cancer 25% (5-77%) for males and 8% (2-33%) for females and ovarian cancer 14% (2-65%). The cumulative risks (95% CI) for monoallelic mutation carriers were: gastric cancer 5% (4-7%) for males and 2.3% (1.7-3.3%) for females; hepatobiliary cancer 3% (2-5%) for males and 1.4% (0.8-2.3%) for females; endometrial cancer 3% (2%-6%) and breast cancer 11% (8-16%). These unbiased estimates of both relative and absolute risks of extracolonic cancers for people, mostly Caucasians, with MUTYH mutations will be important for their clinical management.
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Maas P, Barrdahl M, Joshi AD, Auer PL, Gaudet MM, Milne RL, Schumacher FR, Anderson WF, Check D, Chattopadhyay S, Baglietto L, Berg CD, Chanock SJ, Cox DG, Figueroa JD, Gail MH, Graubard BI, Haiman CA, Hankinson SE, Hoover RN, Isaacs C, Kolonel LN, Le Marchand L, Lee IM, Lindström S, Overvad K, Romieu I, Sanchez MJ, Southey MC, Stram DO, Tumino R, VanderWeele TJ, Willett WC, Zhang S, Buring JE, Canzian F, Gapstur SM, Henderson BE, Hunter DJ, Giles GG, Prentice RL, Ziegler RG, Kraft P, Garcia-Closas M, Chatterjee N. Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States. JAMA Oncol 2016; 2:1295-1302. [PMID: 27228256 PMCID: PMC5719876 DOI: 10.1001/jamaoncol.2016.1025] [Citation(s) in RCA: 225] [Impact Index Per Article: 28.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
IMPORTANCE An improved model for risk stratification can be useful for guiding public health strategies of breast cancer prevention. OBJECTIVE To evaluate combined risk stratification utility of common low penetrant single nucleotide polymorphisms (SNPs) and epidemiologic risk factors. DESIGN, SETTING, AND PARTICIPANTS Using a total of 17 171 cases and 19 862 controls sampled from the Breast and Prostate Cancer Cohort Consortium (BPC3) and 5879 women participating in the 2010 National Health Interview Survey, a model for predicting absolute risk of breast cancer was developed combining information on individual level data on epidemiologic risk factors and 24 genotyped SNPs from prospective cohort studies, published estimate of odds ratios for 68 additional SNPs, population incidence rate from the National Cancer Institute-Surveillance, Epidemiology, and End Results Program cancer registry and data on risk factor distribution from nationally representative health survey. The model is used to project the distribution of absolute risk for the population of white women in the United States after adjustment for competing cause of mortality. EXPOSURES Single nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive factors, and lifestyle factors. MAIN OUTCOMES AND MEASURES Degree of stratification of absolute risk owing to nonmodifiable (SNPs, family history, height, and some components of menstrual and/or reproductive history) and modifiable factors (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], menopausal hormone therapy [MHT], alcohol, and smoking). RESULTS The average absolute risk for a 30-year-old white woman in the United States developing invasive breast cancer by age 80 years is 11.3%. A model that includes all risk factors provided a range of average absolute risk from 4.4% to 23.5% for women in the bottom and top deciles of the risk distribution, respectively. For women who were at the lowest and highest deciles of nonmodifiable risks, the 5th and 95th percentile range of the risk distribution associated with 4 modifiable factors was 2.9% to 5.0% and 15.5% to 25.0%, respectively. For women in the highest decile of risk owing to nonmodifiable factors, those who had low BMI, did not drink or smoke, and did not use MHT had risks comparable to an average woman in the general population. CONCLUSIONS AND RELEVANCE This model for absolute risk of breast cancer including SNPs can provide stratification for the population of white women in the United States. The model can also identify subsets of the population at an elevated risk that would benefit most from risk-reduction strategies based on altering modifiable factors. The effectiveness of this model for individual risk communication needs further investigation.
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Shi J, Zhang Y, Zheng W, Michailidou K, Ghoussaini M, Bolla MK, Wang Q, Dennis J, Lush M, Milne RL, Shu XO, Beesley J, Kar S, Andrulis IL, Anton-Culver H, Arndt V, Beckmann MW, Zhao Z, Guo X, Benitez J, Beeghly-Fadiel A, Blot W, Bogdanova NV, Bojesen SE, Brauch H, Brenner H, Brinton L, Broeks A, Brüning T, Burwinkel B, Cai H, Canisius S, Chang-Claude J, Choi JY, Couch FJ, Cox A, Cross SS, Czene K, Darabi H, Devilee P, Droit A, Dork T, Fasching PA, Fletcher O, Flyger H, Fostira F, Gaborieau V, García-Closas M, Giles GG, Guenel P, Haiman CA, Hamann U, Hartman M, Miao H, Hollestelle A, Hopper JL, Hsiung CN, Ito H, Jakubowska A, Johnson N, Torres D, Kabisch M, Kang D, Khan S, Knight JA, Kosma VM, Lambrechts D, Li J, Lindblom A, Lophatananon A, Lubinski J, Mannermaa A, Manoukian S, Le Marchand L, Margolin S, Marme F, Matsuo K, McLean C, Meindl A, Muir K, Neuhausen SL, Nevanlinna H, Nord S, Børresen-Dale AL, Olson JE, Orr N, van den Ouweland AM, Peterlongo P, Putti TC, Rudolph A, Sangrajrang S, Sawyer EJ, Schmidt MK, Schmutzler RK, Shen CY, Hou MF, Shrubsole MJ, Southey MC, Swerdlow A, Teo SH, Thienpont B, Toland AE, Tollenaar RA, Tomlinson I, Truong T, Tseng CC, Wen W, Winqvist R, Wu AH, Yip CH, Zamora PM, Zheng Y, Floris G, Cheng CY, Hooning MJ, Martens JW, Seynaeve C, Kristensen VN, Hall P, Pharoah PD, Simard J, Chenevix-Trench G, Dunning AM, Antoniou AC, Easton DF, Cai Q, Long J. Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer. Int J Cancer 2016; 139:1303-1317. [PMID: 27087578 PMCID: PMC5110427 DOI: 10.1002/ijc.30150] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Revised: 01/11/2016] [Accepted: 01/19/2016] [Indexed: 02/03/2023]
Abstract
Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2) = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.
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Darabi H, Beesley J, Droit A, Kar S, Nord S, Moradi Marjaneh M, Soucy P, Michailidou K, Ghoussaini M, Fues Wahl H, Bolla MK, Wang Q, Dennis J, Alonso MR, Andrulis IL, Anton-Culver H, Arndt V, Beckmann MW, Benitez J, Bogdanova NV, Bojesen SE, Brauch H, Brenner H, Broeks A, Brüning T, Burwinkel B, Chang-Claude J, Choi JY, Conroy DM, Couch FJ, Cox A, Cross SS, Czene K, Devilee P, Dörk T, Easton DF, Fasching PA, Figueroa J, Fletcher O, Flyger H, Galle E, García-Closas M, Giles GG, Goldberg MS, González-Neira A, Guénel P, Haiman CA, Hallberg E, Hamann U, Hartman M, Hollestelle A, Hopper JL, Ito H, Jakubowska A, Johnson N, Kang D, Khan S, Kosma VM, Kriege M, Kristensen V, Lambrechts D, Le Marchand L, Lee SC, Lindblom A, Lophatananon A, Lubinski J, Mannermaa A, Manoukian S, Margolin S, Matsuo K, Mayes R, McKay J, Meindl A, Milne RL, Muir K, Neuhausen SL, Nevanlinna H, Olswold C, Orr N, Peterlongo P, Pita G, Pylkäs K, Rudolph A, Sangrajrang S, Sawyer EJ, Schmidt MK, Schmutzler RK, Seynaeve C, Shah M, Shen CY, Shu XO, Southey MC, Stram DO, Surowy H, Swerdlow A, Teo SH, Tessier DC, Tomlinson I, Torres D, Truong T, Vachon CM, Vincent D, Winqvist R, Wu AH, Wu PE, Yip CH, Zheng W, Pharoah PDP, Hall P, Edwards SL, Simard J, French JD, Chenevix-Trench G, Dunning AM. Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs). Sci Rep 2016; 6:32512. [PMID: 27600471 PMCID: PMC5013272 DOI: 10.1038/srep32512] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Accepted: 08/03/2016] [Indexed: 02/02/2023] Open
Abstract
Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 × 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10(-09), r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.
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Lawrenson K, Kar S, McCue K, Kuchenbaeker K, Michailidou K, Tyrer J, Beesley J, Ramus SJ, Li Q, Delgado MK, Lee JM, Aittomäki K, Andrulis IL, Anton-Culver H, Arndt V, Arun BK, Arver B, Bandera EV, Barile M, Barkardottir RB, Barrowdale D, Beckmann MW, Benitez J, Berchuck A, Bisogna M, Bjorge L, Blomqvist C, Blot W, Bogdanova N, Bojesen A, Bojesen SE, Bolla MK, Bonanni B, Børresen-Dale AL, Brauch H, Brennan P, Brenner H, Bruinsma F, Brunet J, Buhari SA, Burwinkel B, Butzow R, Buys SS, Cai Q, Caldes T, Campbell I, Canniotto R, Chang-Claude J, Chiquette J, Choi JY, Claes KBM, Cook LS, Cox A, Cramer DW, Cross SS, Cybulski C, Czene K, Daly MB, Damiola F, Dansonka-Mieszkowska A, Darabi H, Dennis J, Devilee P, Diez O, Doherty JA, Domchek SM, Dorfling CM, Dörk T, Dumont M, Ehrencrona H, Ejlertsen B, Ellis S, Engel C, Lee E, Evans DG, Fasching PA, Feliubadalo L, Figueroa J, Flesch-Janys D, Fletcher O, Flyger H, Foretova L, Fostira F, Foulkes WD, Fridley BL, Friedman E, Frost D, Gambino G, Ganz PA, Garber J, García-Closas M, Gentry-Maharaj A, Ghoussaini M, Giles GG, Glasspool R, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Goode EL, Goodman MT, Greene MH, Gronwald J, Guénel P, Haiman CA, Hall P, Hallberg E, Hamann U, Hansen TVO, Harrington PA, Hartman M, Hassan N, Healey S, Heitz F, Herzog J, Høgdall E, Høgdall CK, Hogervorst FBL, Hollestelle A, Hopper JL, Hulick PJ, Huzarski T, Imyanitov EN, Isaacs C, Ito H, Jakubowska A, Janavicius R, Jensen A, John EM, Johnson N, Kabisch M, Kang D, Kapuscinski M, Karlan BY, Khan S, Kiemeney LA, Kjaer SK, Knight JA, Konstantopoulou I, Kosma VM, Kristensen V, Kupryjanczyk J, Kwong A, de la Hoya M, Laitman Y, Lambrechts D, Le N, De Leeneer K, Lester J, Levine DA, Li J, Lindblom A, Long J, Lophatananon A, Loud JT, Lu K, Lubinski J, Mannermaa A, Manoukian S, Le Marchand L, Margolin S, Marme F, Massuger LFAG, Matsuo K, Mazoyer S, McGuffog L, McLean C, McNeish I, Meindl A, Menon U, Mensenkamp AR, Milne RL, Montagna M, Moysich KB, Muir K, Mulligan AM, Nathanson KL, Ness RB, Neuhausen SL, Nevanlinna H, Nord S, Nussbaum RL, Odunsi K, Offit K, Olah E, Olopade OI, Olson JE, Olswold C, O'Malley D, Orlow I, Orr N, Osorio A, Park SK, Pearce CL, Pejovic T, Peterlongo P, Pfeiler G, Phelan CM, Poole EM, Pylkäs K, Radice P, Rantala J, Rashid MU, Rennert G, Rhenius V, Rhiem K, Risch HA, Rodriguez G, Rossing MA, Rudolph A, Salvesen HB, Sangrajrang S, Sawyer EJ, Schildkraut JM, Schmidt MK, Schmutzler RK, Sellers TA, Seynaeve C, Shah M, Shen CY, Shu XO, Sieh W, Singer CF, Sinilnikova OM, Slager S, Song H, Soucy P, Southey MC, Stenmark-Askmalm M, Stoppa-Lyonnet D, Sutter C, Swerdlow A, Tchatchou S, Teixeira MR, Teo SH, Terry KL, Terry MB, Thomassen M, Tibiletti MG, Tihomirova L, Tognazzo S, Toland AE, Tomlinson I, Torres D, Truong T, Tseng CC, Tung N, Tworoger SS, Vachon C, van den Ouweland AMW, van Doorn HC, van Rensburg EJ, Van't Veer LJ, Vanderstichele A, Vergote I, Vijai J, Wang Q, Wang-Gohrke S, Weitzel JN, Wentzensen N, Whittemore AS, Wildiers H, Winqvist R, Wu AH, Yannoukakos D, Yoon SY, Yu JC, Zheng W, Zheng Y, Khanna KK, Simard J, Monteiro AN, French JD, Couch FJ, Freedman ML, Easton DF, Dunning AM, Pharoah PD, Edwards SL, Chenevix-Trench G, Antoniou AC, Gayther SA. Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus. Nat Commun 2016; 7:12675. [PMID: 27601076 PMCID: PMC5023955 DOI: 10.1038/ncomms12675] [Citation(s) in RCA: 68] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Accepted: 07/20/2016] [Indexed: 02/02/2023] Open
Abstract
A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P<2 × 10(-3)). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3'-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
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Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai ZS, Lawrenson K, Lindstrom S, Ramus SJ, Thompson DJ, Kibel AS, Dansonka-Mieszkowska A, Michael A, Dieffenbach AK, Gentry-Maharaj A, Whittemore AS, Wolk A, Monteiro A, Peixoto A, Kierzek A, Cox A, Rudolph A, Gonzalez-Neira A, Wu AH, Lindblom A, Swerdlow A, Ziogas A, Ekici AB, Burwinkel B, Karlan BY, Nordestgaard BG, Blomqvist C, Phelan C, McLean C, Pearce CL, Vachon C, Cybulski C, Slavov C, Stegmaier C, Maier C, Ambrosone CB, Høgdall CK, Teerlink CC, Kang D, Tessier DC, Schaid DJ, Stram DO, Cramer DW, Neal DE, Eccles D, Flesch-Janys D, Edwards DRV, Wokozorczyk D, Levine DA, Yannoukakos D, Sawyer EJ, Bandera EV, Poole EM, Goode EL, Khusnutdinova E, Høgdall E, Song F, Bruinsma F, Heitz F, Modugno F, Hamdy FC, Wiklund F, Giles GG, Olsson H, Wildiers H, Ulmer HU, Pandha H, Risch HA, Darabi H, Salvesen HB, Nevanlinna H, Gronberg H, Brenner H, Brauch H, Anton-Culver H, Song H, Lim HY, McNeish I, Campbell I, Vergote I, Gronwald J, Lubiński J, Stanford JL, Benítez J, Doherty JA, Permuth JB, Chang-Claude J, Donovan JL, Dennis J, Schildkraut JM, Schleutker J, Hopper JL, Kupryjanczyk J, Park JY, Figueroa J, Clements JA, Knight JA, Peto J, Cunningham JM, Pow-Sang J, Batra J, Czene K, Lu KH, Herkommer K, Khaw KT, Matsuo K, Muir K, Offitt K, Chen K, Moysich KB, Aittomäki K, Odunsi K, Kiemeney LA, Massuger LFAG, Fitzgerald LM, Cook LS, Cannon-Albright L, Hooning MJ, Pike MC, Bolla MK, Luedeke M, Teixeira MR, Goodman MT, Schmidt MK, Riggan M, Aly M, Rossing MA, Beckmann MW, Moisse M, Sanderson M, Southey MC, Jones M, Lush M, Hildebrandt MAT, Hou MF, Schoemaker MJ, Garcia-Closas M, Bogdanova N, Rahman N, Le ND, Orr N, Wentzensen N, Pashayan N, Peterlongo P, Guénel P, Brennan P, Paulo P, Webb PM, Broberg P, Fasching PA, Devilee P, Wang Q, Cai Q, Li Q, Kaneva R, Butzow R, Kopperud RK, Schmutzler RK, Stephenson RA, MacInnis RJ, Hoover RN, Winqvist R, Ness R, Milne RL, Travis RC, Benlloch S, Olson SH, McDonnell SK, Tworoger SS, Maia S, Berndt S, Lee SC, Teo SH, Thibodeau SN, Bojesen SE, Gapstur SM, Kjær SK, Pejovic T, Tammela TLJ, Dörk T, Brüning T, Wahlfors T, Key TJ, Edwards TL, Menon U, Hamann U, Mitev V, Kosma VM, Setiawan VW, Kristensen V, Arndt V, Vogel W, Zheng W, Sieh W, Blot WJ, Kluzniak W, Shu XO, Gao YT, Schumacher F, Freedman ML, Berchuck A, Dunning AM, Simard J, Haiman CA, Spurdle A, Sellers TA, Hunter DJ, Henderson BE, Kraft P, Chanock SJ, Couch FJ, Hall P, Gayther SA, Easton DF, Chenevix-Trench G, Eeles R, Pharoah PDP, Lambrechts D. Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types. Cancer Discov 2016; 6:1052-67. [PMID: 27432226 PMCID: PMC5010513 DOI: 10.1158/2159-8290.cd-15-1227] [Citation(s) in RCA: 139] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2015] [Accepted: 06/07/2016] [Indexed: 02/02/2023]
Abstract
UNLABELLED Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis. SIGNIFICANCE We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.
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Fehringer G, Kraft P, Pharoah PD, Eeles RA, Chatterjee N, Schumacher FR, Schildkraut JM, Lindström S, Brennan P, Bickeböller H, Houlston RS, Landi MT, Caporaso N, Risch A, Amin Al Olama A, Berndt SI, Giovannucci EL, Grönberg H, Kote-Jarai Z, Ma J, Muir K, Stampfer MJ, Stevens VL, Wiklund F, Willett WC, Goode EL, Permuth JB, Risch HA, Reid BM, Bezieau S, Brenner H, Chan AT, Chang-Claude J, Hudson TJ, Kocarnik JK, Newcomb PA, Schoen RE, Slattery ML, White E, Adank MA, Ahsan H, Aittomäki K, Baglietto L, Blomquist C, Canzian F, Czene K, Dos-Santos-Silva I, Eliassen AH, Figueroa JD, Flesch-Janys D, Fletcher O, Garcia-Closas M, Gaudet MM, Johnson N, Hall P, Hazra A, Hein R, Hofman A, Hopper JL, Irwanto A, Johansson M, Kaaks R, Kibriya MG, Lichtner P, Liu J, Lund E, Makalic E, Meindl A, Müller-Myhsok B, Muranen TA, Nevanlinna H, Peeters PH, Peto J, Prentice RL, Rahman N, Sanchez MJ, Schmidt DF, Schmutzler RK, Southey MC, Tamimi R, Travis RC, Turnbull C, Uitterlinden AG, Wang Z, Whittemore AS, Yang XR, Zheng W, Buchanan DD, Casey G, Conti DV, Edlund CK, Gallinger S, Haile RW, Jenkins M, Le Marchand L, Li L, Lindor NM, Schmit SL, Thibodeau SN, Woods MO, Rafnar T, Gudmundsson J, Stacey SN, Stefansson K, Sulem P, Chen YA, Tyrer JP, Christiani DC, Wei Y, Shen H, Hu Z, Shu XO, Shiraishi K, Takahashi A, Bossé Y, Obeidat M, Nickle D, Timens W, Freedman ML, Li Q, Seminara D, Chanock SJ, Gong J, Peters U, Gruber SB, Amos CI, Sellers TA, Easton DF, Hunter DJ, Haiman CA, Henderson BE, Hung RJ. Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations. Cancer Res 2016; 76:5103-14. [PMID: 27197191 PMCID: PMC5010493 DOI: 10.1158/0008-5472.can-15-2980] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 04/05/2016] [Indexed: 01/26/2023]
Abstract
Identifying genetic variants with pleiotropic associations can uncover common pathways influencing multiple cancers. We took a two-stage approach to conduct genome-wide association studies for lung, ovary, breast, prostate, and colorectal cancer from the GAME-ON/GECCO Network (61,851 cases, 61,820 controls) to identify pleiotropic loci. Findings were replicated in independent association studies (55,789 cases, 330,490 controls). We identified a novel pleiotropic association at 1q22 involving breast and lung squamous cell carcinoma, with eQTL analysis showing an association with ADAM15/THBS3 gene expression in lung. We also identified a known breast cancer locus CASP8/ALS2CR12 associated with prostate cancer, a known cancer locus at CDKN2B-AS1 with different variants associated with lung adenocarcinoma and prostate cancer, and confirmed the associations of a breast BRCA2 locus with lung and serous ovarian cancer. This is the largest study to date examining pleiotropy across multiple cancer-associated loci, identifying common mechanisms of cancer development and progression. Cancer Res; 76(17); 5103-14. ©2016 AACR.
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Wyszynski A, Hong CC, Lam K, Michailidou K, Lytle C, Yao S, Zhang Y, Bolla MK, Wang Q, Dennis J, Hopper JL, Southey MC, Schmidt MK, Broeks A, Muir K, Lophatananon A, Fasching PA, Beckmann MW, Peto J, Dos-Santos-Silva I, Sawyer EJ, Tomlinson I, Burwinkel B, Marme F, Guénel P, Truong T, Bojesen SE, Nordestgaard BG, González-Neira A, Benitez J, Neuhausen SL, Brenner H, Dieffenbach AK, Meindl A, Schmutzler RK, Brauch H, 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, Wildiers H, Chang-Claude J, Rudolph A, Radice P, Peterlongo P, Couch FJ, Olson JE, Giles GG, Milne RL, Haiman CA, Henderson BE, Dumont M, Teo SH, Wong TY, Kristensen V, Zheng W, Long J, Winqvist R, Pylkäs K, Andrulis IL, Knight JA, Devilee P, Seynaeve C, García-Closas M, Figueroa J, Klevebring D, Czene K, Hooning MJ, van den Ouweland AMW, Darabi H, Shu XO, Gao YT, Cox A, Blot W, Signorello LB, Shah M, Kang D, Choi JY, Hartman M, Miao H, Hamann U, Jakubowska A, Lubinski J, Sangrajrang S, McKay J, Toland AE, Yannoukakos D, Shen CY, Wu PE, Swerdlow A, Orr N, Simard J, Pharoah PDP, Dunning AM, Chenevix-Trench G, Hall P, Bandera E, Amos C, Ambrosone C, Easton DF, Cole MD. An intergenic risk locus containing an enhancer deletion in 2q35 modulates breast cancer risk by deregulating IGFBP5 expression. Hum Mol Genet 2016; 25:3863-3876. [PMID: 27402876 PMCID: PMC5216618 DOI: 10.1093/hmg/ddw223] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2016] [Revised: 06/11/2016] [Accepted: 07/04/2016] [Indexed: 12/20/2022] Open
Abstract
Breast cancer is the most diagnosed malignancy and the second leading cause of cancer mortality in females. Previous association studies have identified variants on 2q35 associated with the risk of breast cancer. To identify functional susceptibility loci for breast cancer, we interrogated the 2q35 gene desert for chromatin architecture and functional variation correlated with gene expression. We report a novel intergenic breast cancer risk locus containing an enhancer copy number variation (enCNV; deletion) located approximately 400Kb upstream to IGFBP5, which overlaps an intergenic ERα-bound enhancer that loops to the IGFBP5 promoter. The enCNV is correlated with modified ERα binding and monoallelic-repression of IGFBP5 following oestrogen treatment. We investigated the association of enCNV genotype with breast cancer in 1,182 cases and 1,362 controls, and replicate our findings in an independent set of 62,533 cases and 60,966 controls from 41 case control studies and 11 GWAS. We report a dose-dependent inverse association of 2q35 enCNV genotype (percopy OR = 0.68 95%CI 0.55-0.83, P = 0.0002; replication OR = 0.77 95% CI 0.73-0.82, P = 2.1 × 10-19) and identify 13 additional linked variants (r2 > 0.8) in the 20Kb linkage block containing the enCNV (P = 3.2 × 10-15 - 5.6 × 10-17). These associations were independent of previously reported 2q35 variants, rs13387042/rs4442975 and rs16857609, and were stronger for ER-positive than ER-negative disease. Together, these results suggest that 2q35 breast cancer risk loci may be mediating their effect through IGFBP5.
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Horne HN, Chung CC, Zhang H, Yu K, Prokunina-Olsson L, Michailidou K, Bolla MK, Wang Q, Dennis J, 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, Anton-Culver H, Neuhausen SL, Brenner H, Arndt V, Meindl A, Schmutzler RK, Brauch H, Hamann U, Nevanlinna H, Khan S, Matsuo K, Iwata H, Dörk T, Bogdanova NV, Lindblom A, Margolin S, Mannermaa A, Kosma VM, Chenevix-Trench G, Wu AH, ven den Berg D, Smeets A, Zhao H, Chang-Claude J, Rudolph A, Radice P, Barile M, Couch FJ, Vachon C, Giles GG, Milne RL, Haiman CA, Marchand LL, Goldberg MS, Teo SH, Taib NAM, Kristensen V, Borresen-Dale AL, Zheng W, Shrubsole M, Winqvist R, Jukkola-Vuorinen A, Andrulis IL, Knight JA, Devilee P, Seynaeve C, García-Closas M, Czene K, Darabi H, Hollestelle A, Martens JWM, Li J, Lu W, Shu XO, Cox A, Cross SS, Blot W, Cai Q, Shah M, Luccarini C, Baynes C, Harrington P, Kang D, Choi JY, Hartman M, Chia KS, Kabisch M, Torres D, Jakubowska A, Lubinski J, Sangrajrang S, Brennan P, Slager S, Yannoukakos D, Shen CY, Hou MF, Swerdlow A, Orr N, Simard J, Hall P, Pharoah PDP, Easton DF, Chanock SJ, Dunning AM, Figueroa JD. Fine-Mapping of the 1p11.2 Breast Cancer Susceptibility Locus. PLoS One 2016; 11:e0160316. [PMID: 27556229 PMCID: PMC4996485 DOI: 10.1371/journal.pone.0160316] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2016] [Accepted: 07/18/2016] [Indexed: 02/02/2023] Open
Abstract
The Cancer Genetic Markers of Susceptibility genome-wide association study (GWAS) originally identified a single nucleotide polymorphism (SNP) rs11249433 at 1p11.2 associated with breast cancer risk. To fine-map this locus, we genotyped 92 SNPs in a 900kb region (120,505,799-121,481,132) flanking rs11249433 in 45,276 breast cancer cases and 48,998 controls of European, Asian and African ancestry from 50 studies in the Breast Cancer Association Consortium. Genotyping was done using iCOGS, a custom-built array. Due to the complicated nature of the region on chr1p11.2: 120,300,000-120,505,798, that lies near the centromere and contains seven duplicated genomic segments, we restricted analyses to 429 SNPs excluding the duplicated regions (42 genotyped and 387 imputed). Per-allelic associations with breast cancer risk were estimated using logistic regression models adjusting for study and ancestry-specific principal components. The strongest association observed was with the original identified index SNP rs11249433 (minor allele frequency (MAF) 0.402; per-allele odds ratio (OR) = 1.10, 95% confidence interval (CI) 1.08-1.13, P = 1.49 x 10-21). The association for rs11249433 was limited to ER-positive breast cancers (test for heterogeneity P≤8.41 x 10-5). Additional analyses by other tumor characteristics showed stronger associations with moderately/well differentiated tumors and tumors of lobular histology. Although no significant eQTL associations were observed, in silico analyses showed that rs11249433 was located in a region that is likely a weak enhancer/promoter. Fine-mapping analysis of the 1p11.2 breast cancer susceptibility locus confirms this region to be limited to risk to cancers that are ER-positive.
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Schmidt MK, Hogervorst F, van Hien R, Cornelissen S, Broeks A, Adank MA, Meijers H, Waisfisz Q, Hollestelle A, Schutte M, van den Ouweland A, Hooning M, Andrulis IL, Anton-Culver H, Antonenkova NN, Antoniou AC, Arndt V, Bermisheva M, Bogdanova NV, Bolla MK, Brauch H, Brenner H, Brüning T, Burwinkel B, Chang-Claude J, Chenevix-Trench G, Couch FJ, Cox A, Cross SS, Czene K, Dunning AM, Fasching PA, Figueroa J, Fletcher O, Flyger H, Galle E, García-Closas M, Giles GG, Haeberle L, Hall P, Hillemanns P, Hopper JL, Jakubowska A, John EM, Jones M, Khusnutdinova E, Knight JA, Kosma VM, Kristensen V, Lee A, Lindblom A, Lubinski J, Mannermaa A, Margolin S, Meindl A, Milne RL, Muranen TA, Newcomb PA, Offit K, Park-Simon TW, Peto J, Pharoah PD, Robson M, Rudolph A, Sawyer EJ, Schmutzler RK, Seynaeve C, Soens J, Southey MC, Spurdle AB, Surowy H, Swerdlow A, Tollenaar RA, Tomlinson I, Trentham-Dietz A, Vachon C, Wang Q, Whittemore AS, Ziogas A, van der Kolk L, Nevanlinna H, Dörk T, Bojesen S, Easton DF. Age- and Tumor Subtype-Specific Breast Cancer Risk Estimates for CHEK2*1100delC Carriers. J Clin Oncol 2016; 34:2750-60. [PMID: 27269948 PMCID: PMC5019754 DOI: 10.1200/jco.2016.66.5844] [Citation(s) in RCA: 118] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
PURPOSE CHEK2*1100delC is a well-established breast cancer risk variant that is most prevalent in European populations; however, there are limited data on risk of breast cancer by age and tumor subtype, which limits its usefulness in breast cancer risk prediction. We aimed to generate tumor subtype- and age-specific risk estimates by using data from the Breast Cancer Association Consortium, including 44,777 patients with breast cancer and 42,997 controls from 33 studies genotyped for CHEK2*1100delC. PATIENTS AND METHODS CHEK2*1100delC genotyping was mostly done by a custom Taqman assay. Breast cancer odds ratios (ORs) for CHEK2*1100delC carriers versus noncarriers were estimated by using logistic regression and adjusted for study (categorical) and age. Main analyses included patients with invasive breast cancer from population- and hospital-based studies. RESULTS Proportions of heterozygous CHEK2*1100delC carriers in controls, in patients with breast cancer from population- and hospital-based studies, and in patients with breast cancer from familial- and clinical genetics center-based studies were 0.5%, 1.3%, and 3.0%, respectively. The estimated OR for invasive breast cancer was 2.26 (95%CI, 1.90 to 2.69; P = 2.3 × 10(-20)). The OR was higher for estrogen receptor (ER)-positive disease (2.55 [95%CI, 2.10 to 3.10; P = 4.9 × 10(-21)]) than it was for ER-negative disease (1.32 [95%CI, 0.93 to 1.88; P = .12]; P interaction = 9.9 × 10(-4)). The OR significantly declined with attained age for breast cancer overall (P = .001) and for ER-positive tumors (P = .001). Estimated cumulative risks for development of ER-positive and ER-negative tumors by age 80 in CHEK2*1100delC carriers were 20% and 3%, respectively, compared with 9% and 2%, respectively, in the general population of the United Kingdom. CONCLUSION These CHEK2*1100delC breast cancer risk estimates provide a basis for incorporating CHEK2*1100delC into breast cancer risk prediction models and into guidelines for intensified screening and follow-up.
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Guo Y, Warren Andersen S, Shu XO, Michailidou K, Bolla MK, Wang Q, Garcia-Closas M, Milne RL, Schmidt MK, Chang-Claude J, Dunning A, Bojesen SE, Ahsan H, Aittomäki K, Andrulis IL, Anton-Culver H, Arndt V, Beckmann MW, Beeghly-Fadiel A, Benitez J, Bogdanova NV, Bonanni B, Børresen-Dale AL, Brand J, Brauch H, Brenner H, Brüning T, Burwinkel B, Casey G, Chenevix-Trench G, Couch FJ, Cox A, Cross SS, Czene K, Devilee P, Dörk T, Dumont M, Fasching PA, Figueroa J, Flesch-Janys D, Fletcher O, Flyger H, Fostira F, Gammon M, Giles GG, Guénel P, Haiman CA, Hamann U, Hooning MJ, Hopper JL, Jakubowska A, Jasmine F, Jenkins M, John EM, Johnson N, Jones ME, Kabisch M, Kibriya M, Knight JA, Koppert LB, Kosma VM, Kristensen V, Le Marchand L, Lee E, Li J, Lindblom A, Luben R, Lubinski J, Malone KE, Mannermaa A, Margolin S, Marme F, McLean C, Meijers-Heijboer H, Meindl A, Neuhausen SL, Nevanlinna H, Neven P, Olson JE, Perez JIA, Perkins B, Peterlongo P, Phillips KA, Pylkäs K, Rudolph A, Santella R, Sawyer EJ, Schmutzler RK, Seynaeve C, Shah M, Shrubsole MJ, Southey MC, Swerdlow AJ, Toland AE, Tomlinson I, Torres D, Truong T, Ursin G, Van Der Luijt RB, Verhoef S, Whittemore AS, Winqvist R, Zhao H, Zhao S, Hall P, Simard J, Kraft P, Pharoah P, Hunter D, Easton DF, Zheng W. Genetically Predicted Body Mass Index and Breast Cancer Risk: Mendelian Randomization Analyses of Data from 145,000 Women of European Descent. PLoS Med 2016; 13:e1002105. [PMID: 27551723 PMCID: PMC4995025 DOI: 10.1371/journal.pmed.1002105] [Citation(s) in RCA: 93] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2015] [Accepted: 06/24/2016] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Observational epidemiological studies have shown that high body mass index (BMI) is associated with a reduced risk of breast cancer in premenopausal women but an increased risk in postmenopausal women. It is unclear whether this association is mediated through shared genetic or environmental factors. METHODS We applied Mendelian randomization to evaluate the association between BMI and risk of breast cancer occurrence using data from two large breast cancer consortia. We created a weighted BMI genetic score comprising 84 BMI-associated genetic variants to predicted BMI. We evaluated genetically predicted BMI in association with breast cancer risk using individual-level data from the Breast Cancer Association Consortium (BCAC) (cases = 46,325, controls = 42,482). We further evaluated the association between genetically predicted BMI and breast cancer risk using summary statistics from 16,003 cases and 41,335 controls from the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) Project. Because most studies measured BMI after cancer diagnosis, we could not conduct a parallel analysis to adequately evaluate the association of measured BMI with breast cancer risk prospectively. RESULTS In the BCAC data, genetically predicted BMI was found to be inversely associated with breast cancer risk (odds ratio [OR] = 0.65 per 5 kg/m2 increase, 95% confidence interval [CI]: 0.56-0.75, p = 3.32 × 10-10). The associations were similar for both premenopausal (OR = 0.44, 95% CI:0.31-0.62, p = 9.91 × 10-8) and postmenopausal breast cancer (OR = 0.57, 95% CI: 0.46-0.71, p = 1.88 × 10-8). This association was replicated in the data from the DRIVE consortium (OR = 0.72, 95% CI: 0.60-0.84, p = 1.64 × 10-7). Single marker analyses identified 17 of the 84 BMI-associated single nucleotide polymorphisms (SNPs) in association with breast cancer risk at p < 0.05; for 16 of them, the allele associated with elevated BMI was associated with reduced breast cancer risk. CONCLUSIONS BMI predicted by genome-wide association studies (GWAS)-identified variants is inversely associated with the risk of both pre- and postmenopausal breast cancer. The reduced risk of postmenopausal breast cancer associated with genetically predicted BMI observed in this study differs from the positive association reported from studies using measured adult BMI. Understanding the reasons for this discrepancy may reveal insights into the complex relationship of genetic determinants of body weight in the etiology of breast cancer.
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Teerlink CC, Leongamornlert D, Dadaev T, Thomas A, Farnham J, Stephenson RA, Riska S, McDonnell SK, Schaid DJ, Catalona WJ, Zheng SL, Cooney KA, Ray AM, Zuhlke KA, Lange EM, Giles GG, Southey MC, Fitzgerald LM, Rinckleb A, Luedeke M, Maier C, Stanford JL, Ostrander EA, Kaikkonen EM, Sipeky C, Tammela T, Schleutker J, Wiley KE, Isaacs SD, Walsh PC, Isaacs WB, Xu J, Cancel-Tassin G, Cussenot O, Mandal D, Laurie C, Laurie C, Thibodeau SN, Eeles RA, Kote-Jarai Z, Cannon-Albright L. Genome-wide association of familial prostate cancer cases identifies evidence for a rare segregating haplotype at 8q24.21. Hum Genet 2016; 135:923-38. [PMID: 27262462 PMCID: PMC5020907 DOI: 10.1007/s00439-016-1690-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2016] [Accepted: 05/26/2016] [Indexed: 10/21/2022]
Abstract
Previous genome-wide association studies (GWAS) of prostate cancer risk focused on cases unselected for family history and have reported over 100 significant associations. The International Consortium for Prostate Cancer Genetics (ICPCG) has now performed a GWAS of 2511 (unrelated) familial prostate cancer cases and 1382 unaffected controls from 12 member sites. All samples were genotyped on the Illumina 5M+exome single nucleotide polymorphism (SNP) platform. The GWAS identified a significant evidence for association for SNPs in six regions previously associated with prostate cancer in population-based cohorts, including 3q26.2, 6q25.3, 8q24.21, 10q11.23, 11q13.3, and 17q12. Of note, SNP rs138042437 (p = 1.7e(-8)) at 8q24.21 achieved a large estimated effect size in this cohort (odds ratio = 13.3). 116 previously sampled affected relatives of 62 risk-allele carriers from the GWAS cohort were genotyped for this SNP, identifying 78 additional affected carriers in 62 pedigrees. A test for an excess number of affected carriers among relatives exhibited strong evidence for co-segregation of the variant with disease (p = 8.5e(-11)). The majority (92 %) of risk-allele carriers at rs138042437 had a consistent estimated haplotype spanning approximately 100 kb of 8q24.21 that contained the minor alleles of three rare SNPs (dosage minor allele frequencies <1.7 %), rs183373024 (PRNCR1), previously associated SNP rs188140481, and rs138042437 (CASC19). Strong evidence for co-segregation of a SNP on the haplotype further characterizes the haplotype as a prostate cancer predisposition locus.
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Winship I, Southey MC. Gene panel testing for hereditary breast cancer. Med J Aust 2016; 204:188-90. [PMID: 26985847 DOI: 10.5694/mja15.01335] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Accepted: 01/28/2016] [Indexed: 11/17/2022]
Abstract
Inherited predisposition to breast cancer is explained only in part by mutations in the BRCA1 and BRCA2 genes. Most families with an apparent familial clustering of breast cancer who are investigated through Australia's network of genetic services and familial cancer centres do not have mutations in either of these genes. More recently, additional breast cancer predisposition genes, such as PALB2, have been identified. New genetic technology allows a panel of multiple genes to be tested for mutations in a single test. This enables more women and their families to have risk assessment and risk management, in a preventive approach to predictable breast cancer. Predictive testing for a known family-specific mutation in a breast cancer predisposition gene provides personalised risk assessment and evidence-based risk management. Breast cancer predisposition gene panel tests have a greater diagnostic yield than conventional testing of only the BRCA1 and BRCA2 genes. The clinical validity and utility of some of the putative breast cancer predisposition genes is not yet clear. Ethical issues warrant consideration, as multiple gene panel testing has the potential to identify secondary findings not originally sought by the test requested. Multiple gene panel tests may provide an affordable and effective way to investigate the heritability of breast cancer.
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Piscuoglio S, Ng CKY, Wen YH, Mannermaa A, Peterlongo P, Tondini C, Janatova M, Hwang TS, Ng PS, Looi LM, Foulkes W, Chenevix-Trench G, Weigelt B, Southey MC, Tischkowitz M, Reis-Filho JS. Abstract 134: Mutational landscape of breast cancers from PALB2 germline mutation carriers. Cancer Res 2016. [DOI: 10.1158/1538-7445.am2016-134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Introduction: The PALB2 gene encodes the partner and localizer of BRCA2 protein, which interacts with BRCA1/2 and is involved in homologous recombination DNA repair. Germline mutations in PALB2 are associated with an increased risk of breast cancer, with a cumulative risk of 35% by age 70 in female PALB2 mutation carriers. Whether the PALB2 wild-type allele is lost in the development of PALB2 breast cancers has yet to be defined. Further, the repertoire of somatic genetic alterations in these tumors is currently unknown. In this study we sought to characterize the genomic landscape of PALB2 breast cancers and to define the differences in the repertoire of somatic genetic alterations and mutational signatures between PALB2 and BRCA1 and BRCA2 breast cancers.
Material and Methods: Representative samples from nine breast cancers from patients with known PALB2 germline mutations were microdissected. DNA samples from microdissected tumors and matched normal counterparts were subjected to whole exome sequencing on an Illumina HiSeq2000. Somatic mutations were defined using MuTect and insertions and deletions using Strelka and Varscan2. Driver mutations were defined by state-of-the-art bioinformatics methods. Mutational signatures were defined using non-negative matrix factorization. Copy number alterations (CNAs) and regions with loss of heterozygosity were determined using FACETS. The mutational frequency of breast cancers from PALB2 germline mutation carriers was compared to that of breast cancers from BRCA1 (n = 11) and BRCA2 (n = 10) germline mutation carriers from The Cancer Genome Atlas study.
Results: Three patients harbored germline frame-shift PALB2 mutations (2 S1169fs, 1 T841fs), five displayed truncating mutations (3 W1038* and 2 Q775*) and 1 harbored a missense mutation (W1140G, of uncertain significance). Somatic loss of the PALB2 wild-type allele was found in 3 cases, in 2 of which the loss was caused by CNAs and in 1 case it was caused by a somatic PALB2 Q479* mutation. A median of 65 somatic mutations (range 45-223) and a median of 1 driver mutation (range 0-3) were identified per tumor. Cancer genes mutated in PALB2 breast cancers included TP53 (n = 2), PIK3CA (n = 2), NF1 (n = 1) and NCOR1 (n = 1). Six cases displayed mutational signatures consistent with the aging process; the BRCA signature was not found in any of the cases analyzed. Breast cancers from PALB2 mutation carriers had fewer somatic TP53 mutations than BRCA1 breast cancers (2/9, 22% vs 9/11, 82%, p = 0.02). No difference in the repertoire of somatic mutations between PALB2 and BRCA2 breast cancers was observed.
Conclusion: Unlike breast cancers from BRCA1 and BRCA2 mutation carriers, the majority of breast cancers from PALB2 mutation carriers lacked somatic loss of the wild-type allele and none displayed a BRCA mutational signature. No highly recurrently mutated gene was identified, but pathogenic mutations in driver genes (TP53, PIK3CA, NF1 and NCOR1) were found.
Citation Format: Salvatore Piscuoglio, Charlotte KY Ng, Y Hannah Wen, Arto Mannermaa, Paolo Peterlongo, Carlo Tondini, Marketa Janatova, Teo Soo Hwang, Pei-Sze Ng, Lai-Meng Looi, William Foulkes, Georgia Chenevix-Trench, Britta Weigelt, Melissa C. Southey, Marc Tischkowitz, Jorge S. Reis-Filho, PALB2 Interest Group. Mutational landscape of breast cancers from PALB2 germline mutation carriers. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 134.
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Krishnan K, Baglietto L, Apicella C, Stone J, Southey MC, English DR, Giles GG, Hopper JL. Mammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study. Breast Cancer Res 2016; 18:63. [PMID: 27316945 PMCID: PMC4912759 DOI: 10.1186/s13058-016-0722-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 05/28/2016] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Risk of screen-detected breast cancer mostly reflects inherent risk, while risk of interval cancer reflects inherent risk and risk of masking (risk of the tumor not being detected due to increased dense tissue). Therefore the predictors of whether a breast cancer is interval or screen-detected include those that predict masking. Our aim was to investigate the associations between mammographic measures and (1) inherent risk, and (2) masking. METHODS We conducted a case-control study nested within the Melbourne collaborative cohort study of 244 screen-detected cases (192 small tumors (<2 cm)) matched to 700 controls and 148 interval cases (76 small tumors) matched to 446 controls. Dense area (DA), percent dense area (PDA), and non-dense area (NDA) were measured using the Cumulus software. Conditional and unconditional logistic regression were applied as appropriate to estimate the odds per adjusted standard deviation (OPERA) adjusted for age and body mass index (BMI), allowing for the association with BMI to be a function of age at diagnosis. Tests of fit were performed using the Bayesian information criterion (BIC) and the area under the receiver operating characteristic curve. RESULTS For screen-detected cancer, the association with BMI had a marginally significant dependence on age at diagnosis, and after adjustment both DA and PDA were associated with risk (OPERA approximately 1.2) and gave a similar fit. NDA was not associated with risk. For interval cancer, the BMI risk association was not dependent on age at diagnosis and the best fitting model was PDA alone (OPERA = 2.24, 95 % confidence interval 1.75, 2.86). Prediction of interval versus screen-detected cancer was best achieved by PDA alone (OPERA = 1.76, 95 % confidence interval 1.39, 2.22) with no association with BMI. When the analysis was restricted to small tumors to reduce the influence of tumor growth, we obtained similar results. CONCLUSIONS Inherent breast cancer risk is predicted by BMI and DA or PDA, but not NDA. Masking is predicted by PDA, and not by BMI. Understanding risk and masking could help tailor mammographic screening.
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Kuroiwa-Trzmielina J, Wang F, Rapkins RW, Ward RL, Buchanan DD, Win AK, Clendenning M, Rosty C, Southey MC, Winship IM, Hopper JL, Jenkins MA, Olivier J, Hawkins NJ, Hitchins MP. SNP rs16906252C>T Is an Expression and Methylation Quantitative Trait Locus Associated with an Increased Risk of Developing MGMT-Methylated Colorectal Cancer. Clin Cancer Res 2016; 22:6266-6277. [PMID: 27267851 DOI: 10.1158/1078-0432.ccr-15-2765] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Revised: 05/20/2016] [Accepted: 06/01/2016] [Indexed: 01/15/2023]
Abstract
PURPOSE Methylation of the MGMT promoter is the major cause of O6-methylguanine methyltransferase deficiency in cancer and has been associated with the T variant of the promoter enhancer SNP rs16906252C>T. We sought evidence for an association between the rs16906252C>T genotype and increased risk of developing a subtype of colorectal cancer featuring MGMT methylation, mediated by genotype-dependent epigenetic silencing within normal tissues. EXPERIMENTAL DESIGN By applying a molecular pathologic epidemiology case-control study design, associations between rs16906252C>T and risk for colorectal cancer overall, and colorectal cancer stratified by MGMT methylation status, were estimated using multinomial logistic regression in two independent retrospective series of colorectal cancer cases and controls. The test sample comprised 1,054 colorectal cancer cases and 451 controls from Sydney, Australia. The validation sample comprised 612 colorectal cancer cases and 245 controls from the Australasian Colon Cancer Family Registry (ACCFR). To determine whether rs16906252C>T was linked to a constitutively altered epigenetic state, quantitative allelic expression and methylation analyses were performed in normal tissues. RESULTS An association between rs16906252C>T and increased risk of developing MGMT-methylated colorectal cancer in the Sydney sample was observed [OR, 3.3; 95% confidence interval (CI), 2.0-5.3; P < 0.0001], which was replicated in the ACCFR sample (OR, 4.0; 95% CI, 2.4-6.8; P < 0.0001). The T allele demonstrated about 2.5-fold reduced transcription in normal colorectal mucosa from cases and controls and was selectively methylated in a minority of normal cells, indicating that rs16906252C>T represents an expression and methylation quantitative trait locus. CONCLUSIONS We provide evidence that rs16906252C>T is associated with elevated risk for MGMT-methylated colorectal cancer, likely mediated by constitutive epigenetic repression of the T allele. Clin Cancer Res; 22(24); 6266-77. ©2016 AACR.
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Renault AL, Lesueur F, Coulombe Y, Gobeil S, Soucy P, Hamdi Y, Desjardins S, Le Calvez-Kelm F, Vallée M, Voegele C, Hopper JL, Andrulis IL, Southey MC, John EM, Masson JY, Tavtigian SV, Simard J. ABRAXAS (FAM175A) and Breast Cancer Susceptibility: No Evidence of Association in the Breast Cancer Family Registry. PLoS One 2016; 11:e0156820. [PMID: 27270457 PMCID: PMC4896418 DOI: 10.1371/journal.pone.0156820] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Accepted: 05/19/2016] [Indexed: 11/17/2022] Open
Abstract
Approximately half of the familial aggregation of breast cancer remains unexplained. This proportion is less for early-onset disease where familial aggregation is greater, suggesting that other susceptibility genes remain to be discovered. The majority of known breast cancer susceptibility genes are involved in the DNA double-strand break repair pathway. ABRAXAS is involved in this pathway and mutations in this gene impair BRCA1 recruitment to DNA damage foci and increase cell sensitivity to ionizing radiation. Moreover, a recurrent germline mutation was reported in Finnish high-risk breast cancer families. To determine if ABRAXAS could be a breast cancer susceptibility gene in other populations, we conducted a population-based case-control mutation screening study of the coding exons and exon/intron boundaries of ABRAXAS in the Breast Cancer Family Registry. In addition to the common variant p.Asp373Asn, sixteen distinct rare variants were identified. Although no significant difference in allele frequencies between cases and controls was observed for the identified variants, two variants, p.Gly39Val and p.Thr141Ile, were shown to diminish phosphorylation of gamma-H2AX in MCF7 human breast adenocarcinoma cells, an important biomarker of DNA double-strand breaks. Overall, likely damaging or neutral variants were evenly represented among cases and controls suggesting that rare variants in ABRAXAS may explain only a small proportion of hereditary breast cancer.
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274
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Young EL, Feng BJ, Stark AW, Damiola F, Durand G, Forey N, Francy TC, Gammon A, Kohlmann WK, Kaphingst KA, McKay-Chopin S, Nguyen-Dumont T, Oliver J, Paquette AM, Pertesi M, Robinot N, Rosenthal JS, Vallee M, Voegele C, Hopper JL, Southey MC, Andrulis IL, John EM, Hashibe M, Gertz J, Le Calvez-Kelm F, Lesueur F, Goldgar DE, Tavtigian SV. Multigene testing of moderate-risk genes: be mindful of the missense. J Med Genet 2016; 53:366-76. [PMID: 26787654 PMCID: PMC4893078 DOI: 10.1136/jmedgenet-2015-103398] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 12/18/2015] [Indexed: 12/13/2022]
Abstract
BACKGROUND Moderate-risk genes have not been extensively studied, and missense substitutions in them are generally returned to patients as variants of uncertain significance lacking clearly defined risk estimates. The fraction of early-onset breast cancer cases carrying moderate-risk genotypes and quantitative methods for flagging variants for further analysis have not been established. METHODS We evaluated rare missense substitutions identified from a mutation screen of ATM, CHEK2, MRE11A, RAD50, NBN, RAD51, RINT1, XRCC2 and BARD1 in 1297 cases of early-onset breast cancer and 1121 controls via scores from Align-Grantham Variation Grantham Deviation (GVGD), combined annotation dependent depletion (CADD), multivariate analysis of protein polymorphism (MAPP) and PolyPhen-2. We also evaluated subjects by polygenotype from 18 breast cancer risk SNPs. From these analyses, we estimated the fraction of cases and controls that reach a breast cancer OR≥2.5 threshold. RESULTS Analysis of mutation screening data from the nine genes revealed that 7.5% of cases and 2.4% of controls were carriers of at least one rare variant with an average OR≥2.5. 2.1% of cases and 1.2% of controls had a polygenotype with an average OR≥2.5. CONCLUSIONS Among early-onset breast cancer cases, 9.6% had a genotype associated with an increased risk sufficient to affect clinical management recommendations. Over two-thirds of variants conferring this level of risk were rare missense substitutions in moderate-risk genes. Placement in the estimated OR≥2.5 group by at least two of these missense analysis programs should be used to prioritise variants for further study. Panel testing often creates more heat than light; quantitative approaches to variant prioritisation and classification may facilitate more efficient clinical classification of variants.
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275
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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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