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Burke KA, Berman S, Geyer FC, Piscuoglio S, Ng CK, Wen YH, Mannermaa A, Peterlongo P, Tondini C, Janatova M, Soo Hwang T, Ng PS, Looi LM, Chenevix-Trench G, Southey MC, Weigelt B, Foulkes W, Tischkowitz M, Reis-Filho JS. Abstract P2-03-01: Mutational landscape of breast cancers from PALB2 germline mutation carriers. Cancer Res 2017. [DOI: 10.1158/1538-7445.sabcs16-p2-03-01] [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
Background: The PALB2 gene encodes the partner and localizer of the BRCA2 protein, which participates in homologous recombination during DNA repair via an interaction with BRCA1 and BRCA2. 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 mutant carriers. The aims of this project were to characterize the genomic landscape of PALB2 breast cancers and define the differences in the repertoire of somatic genetic alterations and mutational signatures between PALB2, BRCA1 and BRCA2 breast cancers.
Methods: Representative samples from fourteen breast cancers from patients with known PALB2 germline mutations (seven frame-shift (2 H1170fs, 3 K346fs, 1 T841fs and 1 L531fs), five truncating (3 W1038* and 2 Q775*) and two missense (W1140G and L35P)) were microdissected to ensure a tumor cell content of >70%. DNA samples from microdissected tumors and their matched normal counterparts were subjected to whole exome sequencing on an Illumina HiSeq2000 to a median depth of 118x (range 33-193x). Somatic single nucleotide variations were detected using MuTect, and small insertions and deletions were identified using Strelka and Varscan2. Using ABSOLUTE and FACETS, we investigated the presence of loss of heterozygosity (LOH) of the PALB2 wild-type allele in these tumors. In addition, the mutational signatures and large scale state transitions (LSTs) were defined. The repertoire of somatic mutations identified in PALB2 breast cancers 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: PALB2 breast cancers were found to harbor a median of 80 somatic mutations (range 22-286) and one somatic mutation (range 0-13) affecting known cancer genes. Somatic loss of the PALB2 wild-type allele was found in five cases, and in three additional cases, a second PALB2 somatic mutation likely constituted the second 'hit' (two with truncating mutations, Q479* and Q61*, and one with a Q921fs frameshift mutation). Six PALB2 breast cancers displayed the BRCA mutations signature; of these, five had PALB2 bi-allelic inactivation (three LOH of the wild-type allele and two a second PALB2 somatic mutation). 71% of the samples were found to have LSTs, including all cases with a BRCA mutational signature. A significant association between PALB2 bi-allelic inactivation and concurrent BRCA signature and high LST was observed (p=0.015). Breast cancers from PALB2 mutation carriers had fewer somatic TP53 mutations than BRCA1 breast cancers (3/14, 21% vs 9/11, 82%, p=0.004), but no difference in the repertoire of somatic mutations compared to that of BRCA2 breast cancers.
Conclusions: PALB2 breast cancers were found to harbor pathogenic mutations in driver genes, including TP53, PIK3CA, NF1 and NCOR1, however lacked highly recurrent somatic mutations. Unlike BRCA1/2 breast cancers, the majority of breast cancers from PALB2 germline mutation carriers lacked LOH of the PALB2 wild-type allele. Importantly, however, an association between PALB2 bi-allelic inactivation and the BRCA mutational signature and LSTs was observed, providing additional evidence for a homologous recombination-deficient phenotype at least in a subset of PALB2 cancers.
Citation Format: Burke KA, Berman S, Geyer FC, Piscuoglio S, Ng CK, Wen YH, Mannermaa A, Peterlongo P, Tondini C, Janatova M, Soo Hwang T, Ng P-S, Looi LM, Chenevix-Trench G, Southey MC, Weigelt B, Foulkes W, Tischkowitz M, Reis-Filho JS, PALB2 Interest Group. Mutational landscape of breast cancers from PALB2 germline mutation carriers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-03-01.
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Law PJ, Berndt SI, Speedy HE, Camp NJ, Sava GP, Skibola CF, Holroyd A, Joseph V, Sunter NJ, Nieters A, Bea S, Monnereau A, Martin-Garcia D, Goldin LR, Clot G, Teras LR, Quintela I, Birmann BM, Jayne S, Cozen W, Majid A, Smedby KE, Lan Q, Dearden C, Brooks-Wilson AR, Hall AG, Purdue MP, Mainou-Fowler T, Vajdic CM, Jackson GH, Cocco P, Marr H, Zhang Y, Zheng T, Giles GG, Lawrence C, Call TG, Liebow M, Melbye M, Glimelius B, Mansouri L, Glenn M, Curtin K, Diver WR, Link BK, Conde L, Bracci PM, Holly EA, Jackson RD, Tinker LF, Benavente Y, Boffetta P, Brennan P, Maynadie M, McKay J, Albanes D, Weinstein S, Wang Z, Caporaso NE, Morton LM, Severson RK, Riboli E, Vineis P, Vermeulen RCH, Southey MC, Milne RL, Clavel J, Topka S, Spinelli JJ, Kraft P, Ennas MG, Summerfield G, Ferri GM, Harris RJ, Miligi L, Pettitt AR, North KE, Allsup DJ, Fraumeni JF, Bailey JR, Offit K, Pratt G, Hjalgrim H, Pepper C, Chanock SJ, Fegan C, Rosenquist R, de Sanjose S, Carracedo A, Dyer MJS, Catovsky D, Campo E, Cerhan JR, Allan JM, Rothman N, Houlston R, Slager S. Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia. Nat Commun 2017; 8:14175. [PMID: 28165464 PMCID: PMC5303820 DOI: 10.1038/ncomms14175] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2016] [Accepted: 12/06/2016] [Indexed: 02/07/2023] Open
Abstract
Several chronic lymphocytic leukaemia (CLL) susceptibility loci have been reported; however, much of the heritable risk remains unidentified. Here we perform a meta-analysis of six genome-wide association studies, imputed using a merged reference panel of 1,000 Genomes and UK10K data, totalling 6,200 cases and 17,598 controls after replication. We identify nine risk loci at 1p36.11 (rs34676223, P=5.04 × 10-13), 1q42.13 (rs41271473, P=1.06 × 10-10), 4q24 (rs71597109, P=1.37 × 10-10), 4q35.1 (rs57214277, P=3.69 × 10-8), 6p21.31 (rs3800461, P=1.97 × 10-8), 11q23.2 (rs61904987, P=2.64 × 10-11), 18q21.1 (rs1036935, P=3.27 × 10-8), 19p13.3 (rs7254272, P=4.67 × 10-8) and 22q13.33 (rs140522, P=2.70 × 10-9). These new and established risk loci map to areas of active chromatin and show an over-representation of transcription factor binding for the key determinants of B-cell development and immune response.
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Buchanan DD, Clendenning M, Rosty C, Eriksen SV, Walsh MD, Walters RJ, Thibodeau SN, Stewart J, Preston S, Win AK, Flander L, Ouakrim DA, Macrae FA, Boussioutas A, Winship IM, Giles GG, Hopper JL, Southey MC, English D, Jenkins MA. Tumor testing to identify lynch syndrome in two Australian colorectal cancer cohorts. J Gastroenterol Hepatol 2017; 32:427-438. [PMID: 27273229 PMCID: PMC5140773 DOI: 10.1111/jgh.13468] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/01/2016] [Indexed: 12/12/2022]
Abstract
BACKGROUND AND AIM Tumor testing of colorectal cancers (CRC) for mismatch repair (MMR) deficiency is an effective approach to identify carriers of germline MMR gene mutation (Lynch syndrome). The aim of this study was to identify MMR gene mutation carriers in two cohorts of population-based CRC utilizing a combination of tumor and germline testing approaches. METHODS Colorectal cancers from 813 patients diagnosed with CRC < 60 years of age from the Australasian Colorectal Cancer Family Registry (ACCFR) and from 826 patients from the Melbourne Collaborative Cohort Study (MCCS) were tested for MMR protein expression using immunohistochemistry, microsatellite instability (MSI), BRAFV600E somatic mutation, and for MLH1 methylation. MMR gene mutation testing (Sanger sequencing and Multiplex Ligation Dependent Probe Amplification) was performed on germline DNA of patients with MMR-deficient tumors and a subset of MMR-proficient CRCs. RESULTS Of the 813 ACCFR probands, 90 probands demonstrated tumor MMR deficiency (11.1%), and 42 had a MMR gene germline mutation (5.2%). For the MCCS, MMR deficiency was identified in the tumors of 103 probands (12.5%) and seven had a germline mutation (0.8%). All the mutation carriers were diagnosed prior to 70 years of age. Probands with a MMR-deficient CRC without MLH1 methylation and a gene mutation were considered Lynch-like and comprised 41.1% and 25.2% of the MMR-deficient CRCs for the ACCFR and MCCS, respectively. CONCLUSIONS Identification of MMR gene mutation carriers in Australian CRC-affected patients is optimized by immunohistochemistry screening of CRC diagnosed before 70 years of age. A significant proportion of MMR-deficient CRCs will have unknown etiology (Lynch-like) proving problematic for clinical management.
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Yow MA, Tabrizi SN, Severi G, Bolton DM, Pedersen J, Giles GG, Southey MC. Characterisation of microbial communities within aggressive prostate cancer tissues. Infect Agent Cancer 2017; 12:4. [PMID: 28101126 PMCID: PMC5237345 DOI: 10.1186/s13027-016-0112-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Accepted: 12/13/2016] [Indexed: 12/11/2022] Open
Abstract
Background An infectious aetiology for prostate cancer has been conjectured for decades but the evidence gained from questionnaire-based and sero-epidemiological studies is weak and inconsistent, and a causal association with any infectious agent is not established. We describe and evaluate the application of new technology to detect bacterial and viral agents in high-grade prostate cancer tissues. The potential of targeted 16S rRNA gene sequencing and total RNA sequencing was evaluated in terms of its utility to characterise microbial communities within high-grade prostate tumours. Methods Two different Massively Parallel Sequencing (MPS) approaches were applied. First, to capture and enrich for possible bacterial species, targeted-MPS of the V2-V3 hypervariable regions of the 16S rRNA gene was performed on DNA extracted from 20 snap-frozen prostate tissue cores from ten “aggressive” prostate cancer cases. Second, total RNA extracted from the same prostate tissue samples was also sequenced to capture the sequence profile of both bacterial and viral transcripts present. Results Overall, 16S rRNA sequencing identified Enterobacteriaceae species common to all samples and P. acnes in 95% of analyzed samples. Total RNA sequencing detected endogenous retroviruses providing proof of concept but there was no evidence of bacterial or viral transcripts suggesting active infection, although it does not rule out a previous ‘hit and run’ scenario. Conclusions As these new investigative methods and protocols become more refined, MPS approaches may be found to have significant utility in identifying potential pathogens involved in disease aetiology. Further studies, specifically designed to detect associations between the disease phenotype and aetiological agents, are required. Electronic supplementary material The online version of this article (doi:10.1186/s13027-016-0112-7) contains supplementary material, which is available to authorized users.
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Baglietto L, Ponzi E, Haycock P, Hodge A, Bianca Assumma M, Jung C, Chung J, Fasanelli F, Guida F, Campanella G, Chadeau‐Hyam M, Grankvist K, Johansson M, Ala U, Provero P, Wong EM, Joo J, English DR, Kazmi N, Lund E, Faltus C, Kaaks R, Risch A, Barrdahl M, Sandanger TM, Southey MC, Giles GG, Johansson M, Vineis P, Polidoro S, Relton CL, Severi G. DNA methylation changes measured in pre-diagnostic peripheral blood samples are associated with smoking and lung cancer risk. Int J Cancer 2017; 140:50-61. [PMID: 27632354 PMCID: PMC5731426 DOI: 10.1002/ijc.30431] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2016] [Accepted: 07/20/2016] [Indexed: 12/26/2022]
Abstract
DNA methylation changes are associated with cigarette smoking. We used the Illumina Infinium HumanMethylation450 array to determine whether methylation in DNA from pre-diagnostic, peripheral blood samples is associated with lung cancer risk. We used a case-control study nested within the EPIC-Italy cohort and a study within the MCCS cohort as discovery sets (a total of 552 case-control pairs). We validated the top signals in 429 case-control pairs from another 3 studies. We identified six CpGs for which hypomethylation was associated with lung cancer risk: cg05575921 in the AHRR gene (p-valuepooled = 4 × 10-17 ), cg03636183 in the F2RL3 gene (p-valuepooled = 2 × 10 - 13 ), cg21566642 and cg05951221 in 2q37.1 (p-valuepooled = 7 × 10-16 and 1 × 10-11 respectively), cg06126421 in 6p21.33 (p-valuepooled = 2 × 10-15 ) and cg23387569 in 12q14.1 (p-valuepooled = 5 × 10-7 ). For cg05951221 and cg23387569 the strength of association was virtually identical in never and current smokers. For all these CpGs except for cg23387569, the methylation levels were different across smoking categories in controls (p-valuesheterogeneity ≤ 1.8 x10 - 7 ), were lowest for current smokers and increased with time since quitting for former smokers. We observed a gain in discrimination between cases and controls measured by the area under the ROC curve of at least 8% (p-values ≥ 0.003) in former smokers by adding methylation at the 6 CpGs into risk prediction models including smoking status and number of pack-years. Our findings provide convincing evidence that smoking and possibly other factors lead to DNA methylation changes measurable in peripheral blood that may improve prediction of lung cancer risk.
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Jayasekara H, MacInnis RJ, Williamson EJ, Hodge AM, Clendenning M, Rosty C, Walters R, Room R, Southey MC, Jenkins MA, Milne RL, Hopper JL, Giles GG, Buchanan DD, English DR. Lifetime alcohol intake is associated with an increased risk of KRAS+ and BRAF-/KRAS- but not BRAF+ colorectal cancer. Int J Cancer 2016; 140:1485-1493. [PMID: 27943267 DOI: 10.1002/ijc.30568] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 10/14/2016] [Accepted: 11/24/2016] [Indexed: 12/16/2022]
Abstract
Ethanol in alcoholic beverages is a causative agent for colorectal cancer. Colorectal cancer is a biologically heterogeneous disease, and molecular subtypes defined by the presence of somatic mutations in BRAF and KRAS are known to exist. We examined associations between lifetime alcohol intake and molecular and anatomic subtypes of colorectal cancer. We calculated usual alcohol intake for 10-year periods from age 20 using recalled frequency and quantity of beverage-specific consumption for 38,149 participants aged 40-69 years from the Melbourne Collaborative Cohort Study. Cox regression was performed to derive hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between lifetime alcohol intake and colorectal cancer risk. Heterogeneity in the HRs across subtypes of colorectal cancer was assessed. A positive dose-dependent association between lifetime alcohol intake and overall colorectal cancer risk (mean follow-up = 14.6 years; n = 596 colon and n = 326 rectal cancer) was observed (HR = 1.08, 95% CI: 1.04-1.12 per 10 g/day increment). The risk was greater for rectal than colon cancer (phomogeneity = 0.02). Alcohol intake was associated with increased risks of KRAS+ (HR = 1.07, 95% CI: 1.00-1.15) and BRAF-/KRAS- (HR = 1.05, 95% CI: 1.00-1.11) but not BRAF+ tumors (HR = 0.89, 95% CI: 0.78-1.01; phomogeneity = 0.01). Alcohol intake is associated with an increased risk of KRAS+ and BRAF-/KRAS- tumors originating via specific molecular pathways including the traditional adenoma-carcinoma pathway but not with BRAF+ tumors originating via the serrated pathway. Therefore, limiting alcohol intake from a young age might reduce colorectal cancer originating via the traditional adenoma-carcinoma pathway.
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Hamdi Y, Soucy P, Adoue V, Michailidou K, Canisius S, Lemaçon A, Droit A, Andrulis IL, Anton-Culver H, Arndt V, Baynes C, Blomqvist C, Bogdanova NV, Bojesen SE, Bolla MK, Bonanni B, Borresen-Dale AL, Brand JS, Brauch H, Brenner H, Broeks A, Burwinkel B, Chang-Claude J, Couch FJ, Cox A, Cross SS, Czene K, Darabi H, Dennis J, Devilee P, Dörk T, Dos-Santos-Silva I, Eriksson M, Fasching PA, Figueroa J, Flyger H, García-Closas M, Giles GG, Goldberg MS, González-Neira A, Grenaker-Alnæs G, Guénel P, Haeberle L, Haiman CA, Hamann U, Hallberg E, Hooning MJ, Hopper JL, Jakubowska A, Jones M, Kabisch M, Kataja V, Lambrechts D, Marchand LL, Lindblom A, Lubinski J, Mannermaa A, Maranian M, Margolin S, Marme F, Milne RL, Neuhausen SL, Nevanlinna H, Neven P, Olswold C, Peto J, Plaseska-Karanfilska D, Pylkäs K, Radice P, Rudolph A, Sawyer EJ, Schmidt MK, Shu XO, Southey MC, Swerdlow A, Tollenaar RA, Tomlinson I, Torres D, Truong T, Vachon C, Van Den Ouweland AMW, Wang Q, Winqvist R, Investigators KC, Zheng W, Benitez J, Chenevix-Trench G, Dunning AM, Pharoah PDP, Kristensen V, Hall P, Easton DF, Pastinen T, Nord S, Simard J. Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21. Oncotarget 2016; 7:80140-80163. [PMID: 27792995 PMCID: PMC5340257 DOI: 10.18632/oncotarget.12818] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Accepted: 10/13/2016] [Indexed: 12/02/2022] Open
Abstract
There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas.
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MacInnis RJ, Schmidt DF, Makalic E, Severi G, FitzGerald LM, Reumann M, Kapuscinski MK, Kowalczyk A, Zhou Z, Goudey B, Qian G, Bui QM, Park DJ, Freeman A, Southey MC, Al Olama AA, Kote-Jarai Z, Eeles RA, Hopper JL, Giles GG. Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk. Cancer Epidemiol Biomarkers Prev 2016; 25:1619-1624. [PMID: 27539266 PMCID: PMC5232414 DOI: 10.1158/1055-9965.epi-16-0301] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 07/13/2016] [Accepted: 08/04/2016] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND We have developed a genome-wide association study analysis method called DEPTH (DEPendency of association on the number of Top Hits) to identify genomic regions potentially associated with disease by considering overlapping groups of contiguous markers (e.g., SNPs) across the genome. DEPTH is a machine learning algorithm for feature ranking of ultra-high dimensional datasets, built from well-established statistical tools such as bootstrapping, penalized regression, and decision trees. Unlike marginal regression, which considers each SNP individually, the key idea behind DEPTH is to rank groups of SNPs in terms of their joint strength of association with the outcome. Our aim was to compare the performance of DEPTH with that of standard logistic regression analysis. METHODS We selected 1,854 prostate cancer cases and 1,894 controls from the UK for whom 541,129 SNPs were measured using the Illumina Infinium HumanHap550 array. Confirmation was sought using 4,152 cases and 2,874 controls, ascertained from the UK and Australia, for whom 211,155 SNPs were measured using the iCOGS Illumina Infinium array. RESULTS From the DEPTH analysis, we identified 14 regions associated with prostate cancer risk that had been reported previously, five of which would not have been identified by conventional logistic regression. We also identified 112 novel putative susceptibility regions. CONCLUSIONS DEPTH can reveal new risk-associated regions that would not have been identified using a conventional logistic regression analysis of individual SNPs. IMPACT This study demonstrates that the DEPTH algorithm could identify additional genetic susceptibility regions that merit further investigation. Cancer Epidemiol Biomarkers Prev; 25(12); 1619-24. ©2016 AACR.
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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: 155] [Impact Index Per Article: 19.4] [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: 98] [Impact Index Per Article: 12.3] [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: 234] [Impact Index Per Article: 29.3] [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: 145] [Impact Index Per Article: 18.1] [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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