Inherited Genetic Susceptibility to Breast Cancer

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    Accepted for publicationJuly 22, 2013.



    accounting for 23% of all malignancies in women world-1

    ronmental, factors account for most of the familial aggrega-

    cancer is complex, and is the result of germ-line variation atmany different loci. The susceptibility alleles at these loci havewidely different frequencies, and confer different disease risks


    breast cancer of >50%, sufcient to warrant intervention to

    used to identify high-penetrance alleles in BRCA1 and

    lative frequency, approximately 1 in 800 for BRCA1 muta-tions and 1 in 500 for BRCA2mutations9) and confer a 10- to

    Supported by the European Communitys Seventh Framework Programmegrant 223175 (HEALTH-F2-2009-223175) and Cancer Research UK Q14.

    The American Journal of Pathology, Vol. -, No. -,- 2013


    63646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123(Figure 1). Genetic variants for breast cancer can be broadlytion. Molecular genetic studies during the past 20 years havedemonstrated that the genetic basis of susceptibility to breast

    BRCA2, two tumor-suppressor genes involved in DNArepair.7,8 Deleterious alleles of these genes are rare (cumu-wide. In the United States, the lifetime risk of breast canceris approximately one in eight.2 It is also the most commoncause of cancer-related deaths worldwide (nearly 400,000a year).1

    The incidence of breast cancer is approximately twofoldhigher in rst-degree relatives of breast cancer patients. Thisrisk increases with the number of affected relatives and ismuch greater for women with relatives affected at a youngage.3e6 The higher prevalence of breast cancer amongmonozygotic twins of patients compared with dizygotic twinsor siblings suggests strongly that genetic, rather than envi-

    reduce risk (eg, prophylactic surgery or magnetic resonanceimaging screening), even in the absence of any other factors.Moderate-penetrance alleles confer risks of greater thantwofold, corresponding to lifetime risks of 20% in Westernpopulations, whereas low-penetrance alleles confer smallerincreases in risk (ie, 10% to 20% lifetime risk).

    Rare High-Penetrance Alleles

    Family-based linkage analysis and positional cloning wereBreast cancer is the most common cancer among women inboth developing and developed regions in the world,

    categorized into high-, moderate-, and low-penetrance alleles.The high-penetrance alleles typically confer lifetime risks ofC


    hAddress correspondence toMaya Ghoussaini, Departmentof Oncology, Centre for CancerGenetic Epidemiology, Univer-sity of Cambridge, WortsCauseway, Cambridge CB18RN, United Kingdom.E-mail: 2013 American Society for Inveublished by Elsevier Inc. All rights reserved


    RGenome-wide association studies have identied 72 loci associated with breast cancer susceptibility.Seventeen of these are known to predispose to other cancers. High-penetrance susceptibility loci forbreast cancer usually result from coding alterations, principally in genes involved in DNA repair,whereas almost all of the associations identied through genome-wide association studies are found innoncoding regions of the genome and are likely to involve regulation of genes in multiple pathways.However, the genes underlying most associations are not yet known. In this review, we summarize thendings from genome-wide association studies in breast cancer and describe the genes and mechanismsthat are likely to be involved in the tumorigenesis process. We also discuss approaches to ne-scalemapping of susceptibility regions used to identify the likely causal variant(s) underlying the associa-tions, a major challenge in genetic epidemiology. Finally, we discuss the potential impact of suchndings on personalized medicine and future avenues for screening, prediction, and preventionprograms. (Am J Pathol 2013, -: 1e14; Breast Cancer Theme Issue

    REVIEWInherited Genetic Susceptibi

    The Beginning of the End or tMaya Ghoussaini,* Paul D.P. Pharoah,*y and Douglas F. East

    From the Departments of Oncology* and Public Health and Primary Care,y

    United Kingdomstigative Pathology.


    EV 5.2.0 DTD AJPA1459_proof y to Breast Cancer

    End of the Beginning?

    re for Cancer Genetic Epidemiology, University of Cambridge, Cambridge,


    22 August 2013 11:15 pm EO: AJP13_0146

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    (TOX3), 12p11 (PTHLH ), and 10q21 (ZNF365), are asso-ciated with both disease types.26,30,31,38e41 Seven loci withcommon susceptibility alleles for ER breast cancer havebeen identied: 6q25 (near ESR1) was rst identied ina GWAS conducted in Chinese women33; 19p13 was initiallyidentied as a modier of the BRCA1 breast cancer,25 and5p12 was identied through a GWAS in ER and triple-negative (ER/progesterone receptor/HER Q3) breast can-cer.28 Four loci (1q32, MDM4; 1q32, LGR6; 2p24, gene Q4

    desert; 16q12, FTO) were recently identied after combiningthree GWASs comprising 4193 ER-negative breast cancercases and 35,194 controls.34 Most GWAS loci also modifythe penetrance of breast cancer in BRCA2 carriers, to a similarrelative extent, but only the subset of SNPs associated withER disease appear to modify the risk in BRCA1 carriers,consistent with the distinct pathological characteristics of thedisease in BRCA1 carriers.

    Ghoussaini et al


    18718818919019119219319419519619719819920020120220320420520620720820921021121221321421521621721821922022122222322422522622722822923023123223323423523623723823924024124224324424524624724830-fold increase in the risk of breast cancer in carrierscompared with noncarriers.10 These alleles also predispose toother cancer types, including ovarian and prostate cancers.11

    Deleterious alleles in other genes conferring a similar riskto BRCA1 and BRCA2 may exist, but they are likely to berare, because approximately 84% of families with four ormore cases of breast cancer diagnosed at younger than 60years can be accounted for by mutations in BRCA1 orBRCA2.10 A few high-penetrance alleles have been identi-ed as part of inherited cancer symptoms, such as TP53mutations found in Li-Fraumeni cancer syndrome12 andSTK11/LKB1 mutations found in Peutz-Jegher syndrome.13

    Rare Moderate-Penetrance Alleles

    Moderate-penetrance variants have been found by rese-quencing candidate genes, such as those interacting withBRCA1 and BRCA2, or acting in the same DNA repairpathway. Protein truncating variants in ATM,14 CHEK2,15,16

    PALB2,17 and BRIP118 genes have been shown to confera twofold to fourfold risk of breast cancer. Other moderate-penetrance genes have been identied through linkagestudies in families with rare syndromes involving breast andother malignancies. Deleterious alleles of PTEN (Cowdendisease)19 and CDH1 (hereditary diffuse gastric cancer)20

    confer relative risks of two to eight. It is likely that othergenetic variations in this category exist, but their identica-tion will require resequencing in large case-control studies.The susceptibility alleles previously mentioned are rare

    and do not reach a frequency of >1% even when combined,suggesting a selective disadvantage, possibly as a result ofhomozygotes being nonviable or seriously disadvantaged.Altogether, they account for 5%) are associated witha modest increase in breast cancer risk (relative risk of

  • F2F2


    Genetic Susceptibility to Breast Cancer


    311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343344345346347348349350351352353354355356357358359360361362363364365366367368369370371372With the exception of the FGFR2 locus, which alsoshows the strongest association with breast cancer, themechanisms and the genes behind these associations arelargely unknown. However, knowledge about gene functionwithin the regions suggests that a complex and diverse rangeof biological pathways are involved in the commonsusceptibility to breast carcinogenesis. Almost all of the lociare in regions that contain genes that could be involved inbreast cancer development (Figure 2), and it is notable thatseveral of these genes have been shown to be somaticallymutated in breast tumors (MAP3K1, TBX3, NOTCH2, MYC,CASP8, CCND1, and TET2).42 However, in almost allcases, there is no direct evidence that these genes arecausally related to the observed susceptibility.

    From Association to Causation and Function

    A Major Challenge for Molecular Genetics

    There are two key steps to understanding the functional mech-anisms bywhich the risk-associated variant causes breast cancerat a susceptibility locus. The rst is to identify the true causalvariant at the locus, and the second is to identify the molecularmechanism by which the risk allele could cause cancer.

    Fine-Scale Mapping

    Fine-scale mapping aims to identify the causal variant(s) ata susceptibility locus. The set of SNPs genotyped in a GWASare designed to tag common variation across the genome.Thus, most variants found to be associated with disease will becorrelated with multiple other variants in the surroundingregion [called linkage disequilibrium (LD) block or haplotypeblock], for which the boundaries are delimited by recombi-nation hot spots. Haplotype blocks vary substantially in size,the number of SNPs, and the LD structure of those SNPs.Several steps are required to narrow down a locus of

    interest and pinpoint the causal variant(s). The rst step is toobtain a complete list of all variants in the LD block ofinterest. The availability of the 1000 Genomes project(, last accessed July 29, 2013)has accelerated this process, and resequencing of the regionis usually no longer needed to search for common variants.Ideally, all of the SNPs correlated with the associatedmarker are then genotyped in a large case-control set, andthe strength of association is compared. The variant with thestrongest statistical evidence for association is the strongestcandidate for being the causal variant. However, because ofthe high correlation among SNPs within a block, multipleSNPs may have equally strong evidence and the true causalvariant may not be denitively identied. Because thepattern of LD often differs among populations, case-controlstudies from multiple populations (notably populations ofEast Asian or African ancestries, in addition to Europeanancestry) can assist with the ne mapping, provided that thesame causal variant segregates in each populationThe American Journal of Pathology - ajp.amjpathol.orgREV 5.2.0 DTD AJPA1459_proof (Figure 3). However, complementary approaches are stilllikely to be required to identify a single causal variant.Because the causative variant is expected to be more

    strongly associated with breast cancer risk than other SNPs,nding the causal variant in each of the GWAS loci will alsoimprove the accuracy of disease risk prediction. Bio-informatic analysis SNPs may have a variety of functionaleffects, by either directly altering protein structure (missensevariants or splice site variants) or altering the transcriptionalregulation of nearby genes. In silico bioinformatics analysiscan help identify SNPs more or less likely to have a func-tional effect.43 For example, SNPs in genomic regions thatare highly conserved between species are more likely to befunctionally important, particularly those in noncodingregions. Genome data on many species, including 28vertebrate species, are publicly available to enable suchanalyses to be routine. The ENCyclopedia Of DNA Elements(National Human Genome Research Institute, NIH,, last accessed July 29, 2013)project has recently provided functional annotation across thehuman genome [histone modication and regulatoryelements, DNA methylation, DNase-hypersensitive sites andfootprints, chromosome-interacting regions, transcriptionfactor (TF) binding sites, regulatory elements, and codingand noncoding RNAs], showing that 80% of the noncodinggenome could be functional.44 Putative causal SNPs can bemapped to see if they lie in specic functional elements, suchas enhancers, silencers, or TF binding sites.When the LD block of interest contains several genes, it

    may be difcult to predict what gene is being targeted by theassociated variant. Because most associations are thought tobe regulatory, the target gene may be identied by evalu-ating whether the SNP genotype is associated with geneexpression. For example, a gene expression database, GENeExpression VARiation, in which the expression of geneswas quantied in immortalized B lymphocytes extractedfrom the 270 HapMap individuals of European, Asian, andAfrican ancestries, has been made publicly available. Thisapproach may be limited by the size of the association withexpression levels, which may be modest. More important,expression may be tissue specic, in which case availabledata in, for example, blood will be of limited value.Emerging data on expression in tumors, through projectssuch as The Cancer Genome Atlas (National Cancer Insti-tute,, last accessed July29, 2013) and the International Cancer Genome ConsortiumCancer Genome Projects (, last accessedJuly 29, 2013), may be more valuable for analysis of genesexpressed in the breast, but ultimately studies in normalbreast tissue may be required.

    Functional Experiments

    Experiments to determine the functional effect of candidatecausal variants are beyond the scope of this review. Briey,if an SNP falls in the noncoding region of the genome322 August 2013 11:15 pm EO: AJP13_0146

  • Table 1 List of the 72 Breast Cancer Susceptibility Loci Identied to Date.

    Region SNP Nearest plausible genes Year Per-allele OR P value MAF

    1p11 rs11249433 NOTCH2/FCGR1B 2009 1.16 (1.09e1.24) 7 1010 0.391p13 rs11552449 TPN22/BCL2L15 2013 1.07 (1.04e1.09) 1.8 108 0.171p36 rs616488 PEX14 2013 0.94 (0.92e0.96) 2.0 1010 0.331q32 rs4245739 MDM4 2013 1.14 (1.10e1.18) 2.1 1012 0.261q32 rs6678914 LGR6 2013 1.10 (1.06e1.13) 1.4 108 0.592p24 rs12710696 desert 2013 1.10 (1.06e1.13) 0.362q14 rs4849887 None 2013 0.91 (0.88e0.94) 3.7 1011 0.102q31 rs2016394 METAP1D 2013 0.95 (0.93e0.97) 1.2 108 0.482q31 rs1550623 CDCA7 2013 0.94 (0.92e0.97) 3.0 108 0.162q33 rs1045485 CASP8 2007 0.88 (0.84e0.92) 1.1 107 0.13

    rs10931936 0.88 (0.82e0.94) 0.262q35 rs13387042 IGFBP2, IGFBP5, TPN2 2007 1.20 (1.14e1.26) 1 1013 0.492q35 rs16857609 DIRC3 2013 1.08 (1.06e1.10) 1.1 1015 0.263p24 rs4973768 SLC4A7/NEK10 2009 1.11 (1.08e1.13) 4.1 1023 0.463p24 rs12493607 TGFBR2 2013 1.06 (1.03e1.08) 2.3 108 0.353p26 rs6762644 ITPR1/EGOT 2013 1.07 (1.04e1.09) 2.2 1012 0.404q24 rs9790517 TET2 2013 1.05 (1.03e1.08) 4.2 108 0.234q34 rs6828523 ADAM29 2013 0.90 (0.87e0.92) 3.5 1016 0.135p12 rs10941679 MRPS30/HCN1 2008 1.19 (1.13e1.26) 1 1011 0.25

    rs9790879 1.10 (1.03e1.17) 0.405p15* rs10069690 TERT/CLPTM1L 2011 1.18 (1.13e1.25) 1.0 1010 0.305q11 rs889312 MAP3K1/MEIR3 2007 1.13 (1.10e1.16) 1 1015 0.285q11 rs10472076 RAB3C 2013 1.05 (1.03e1.07) 2.9 108 0.385q11 rs1353747 PDE4D 0.92 (0.89e0.95) 2.5 108 0.105q33 rs1432679 EBF1 2013 1.07 (1.05e1.09) 2.0 1014 0.436p23 rs204247 RANBP9 2013 1.05 (1.03e1.07) 8.3 109 0.436p25 rs11242675 FOXQ1 2013 0.94 (0.92e0.96) 7.1 109 0.396q14 rs17530068 None 2012 1.12 (1.08e1.16) 1.1 10-9 0.226q25 rs3757318 ESR1 2009 1.21 (1.13e1.31) 2 1015 0.076q25 rs2046210 ESR1 2009 1.11 (1.07e1.16) 3.7 109 0.347q35 rs720475 ARHGEF5/NOBOX 2013 0.94 (0.92e0.96) 7.0 1011 0.258p12 rs9693444 None 2013 1.07 (1.05e1.09) 9.2 1014 0.328q21 rs6472903 None 2013 0.91 (0.89e0.93) 1.7 1017 0.188q21 rs2943559 HNF4G 2013 1.13 (1.09e1.17) 5.7 1015 0.078q24 rs13281615 MYC 2007 1.08 (1.05e1.11) 5 1012 0.408q24 rs1562430 MYC 2010 1.17 (1.10e1.25) 5 1012 0.408q24 rs11780156 MIR1208 2013 1.07 (1.04e1.10) 3.4 1011 0.169p21 rs1011970 CDKN2A/B 2010 1.09 (1.04e1.14) 2.5 108 0.179q31 rs865686 KLF4/RAD23B 2011 0.89 (0.85 0.92) 1.7 1010 0.399q31 rs10759243 None 2013 1.06 (1.03e1.08) 1.2 108 0.3910p12 rs7072776 MLLT10/DNAJC1 2013 1.07 (1.05e1.09) 4.3 1014 0.2910p12 rs11814448 DNAJC1 2013 1.26 (1.18e1.35) 9.3 1016 0.0210p15 rs2380205 ANKRD16 2010 0.94 (0.91e0.98) 4.6 107 0.4310q21 rs10995190 ZNF365 2010 0.86 (0.82e0.91) 5.1 1015 0.1510q22 rs704010 ZMIZ1 2010 1.07 (1.03e1.11) 3 108 0.3910q25 rs7904519 TCF7L2 2013 1.06 (1.04e1.08) 3.1 108 0.4610q26 rs2981582 FGFR2 2007 1.26 (1.23e1.30) 2 1076 0.3810q26 rs2981579 FGFR2 2010 1.43 (1.35e1.53) 2 1076 0.4210q26 rs11199914 None 2013 0.95 (0.93e0.97) 1.9 108 0.3211p15 rs3817198 LSP1/H19 2007 1.07 (1.04e1.11) 1 109 0.3011p15 rs909116 LSP1/H19 2007 1.17 (1.10e1.24) 1 109 0.3011q13* rs614367 CCND1/FGFs 2010 1.15 (1.10e1.20) 3.2 1015 0.1511q13 rs3903072 OVOL1 2013 0.95 (0.93e0.96) 8.6 1012 0.4711q24 rs11820646 None 2013 0.95 (0.93e0.97) 1.1 109 0.4112p11 rs10771399 PTHLH 2011 0.79 (0.71e0.87) 4.3 1035 0.1012p13 rs12422552 None 2013 1.05 (1.03e1.07) 3.7 108 0.2612q22 rs17356907 NTN4 2013 0.91 (0.89e0.93) 1.8 1022 0.30

    (table continues)

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    14q13 rs2236007 PAX9/SLC25A21 201314q24 rs999737 RAD51B 2009



    Genetic Susceptibility to Breast Cancer


    559560561562563564565566567568569570571572573574575576577578579580581582583584585586587588589590(promoter, enhancer, or intron) and is predicted to affect thebinding of a TF, experiments such as electrophoretic

    14q24 rs8009944 RAD51B 214q24 rs2588809 RAD51L1 214q32 rs941764 CCDC88C 216q12 rs12443621 TOX3/LOC643714 216q12 rs3803662 TOX3/LOC643714 216q12 rs17817449 MIR1972-2-FTO 216q23 rs13329835 CDYL2 216q22 rs11075995 FTO 217q23 rs6504950 STXBP4/COX11 218q11 rs527616 None 218q11 rs1436904 CHST9 219p13 rs8170 MERIT40 219p13 rs2363956 MERIT40 219p13 rs4808801 SSBP4/ISYNA1/ELL 219q13 rs3760982 KCNN4/ZNF283 220q11 rs2284378 RALY 221q21 rs2823093 NRIP1 222q12 rs132390 EMID1/RHBDD3 222q13 rs6001930 MKL1 2

    MAF, minor allele frequency.*For each of the 5p15/TERT locus and 11q13/CCND1 locus, three indepenTable 1 (continued )

    Region SNP Nearest plausible genes Y

    12q24 rs1292011 TBX3/MAPKAP5 213q13 rs11571833 BRCA2 2mobility shift assays can be used to test for a differentialprotein binding pattern. Luciferase transfection assays canbe used to measure the activity of a promoter or theexpression of target genes. Chromatin immunoprecipitationcan be used to establish whether the site of a candidatecausal variant is occupied by a TF in vivo. This approachwas recently used to determine the SNPs that are likely tohave a functional effect in FGFR2.45 Chromosome confor-mation capture can be used to test long-range interactionsthat inuence gene expression (eg, between a regulatoryelement containing the causal SNP and the promoter of thesuspected targeted gene). This technique was used for thene mapping of the 11q13 locus, where the enhancer andsilencer in which the causal variants lie were found tointeract with the promoter and terminator of the CCND1gene.46

    In summary, a combination of genetic epidemiologicalcharacteristics, in silico bioinformatics, and functionalexperiments may enable the causal variant (or variants) to beidentied with some certainty.

    Fine Mapping in Breast Cancer

    To date, only four of the 72 known breast cancer suscepti-bility loci have been thoroughly ne mapped in European,Asian, and African American populations.26,45e49 In

    The American Journal of Pathology - ajp.amjpathol.orgREV 5.2.0 DTD AJPA1459_proof addition, 19 of the breast cancer susceptibility loci havebeen ne mapped in African Americans.50

    Per-allele OR P value MAF

    0.92 (0.91e0.94) 5.9 1019 0.411.26 (1.14e1.39) 4.9 108 0.010.93 (0.91e0.95) 1.7 1013 0.210.94 (0.88e0.99) 2 107 0.240.88 (0.82e0.95) 2 107 0.241.08 (1.05e1.11) 1.4 1010 0.161.06 (1.04e1.09) 3.7 1010 0.341.11 (1.08e1.14) 1 1036 0.461.20 (1.16e1.24) 1 1036 0.260.93 (0.91e0.95) 6.4 1014 0.401.08 (1.05e1.10) 2.1 1016 0.221.07 (1.11e1.15) 4.0 108 0.240.95 (0.92e0.97) 1.4 108 0.270.95 (0.93e0.97) 1.6 1010 0.380.96 (0.94e0.98) 3.2 108 0.401.26 (1.17e1.35) 2.3 109 0.180.84 (0.80e0.89) 5.5 09 0.500.93 (0.91e0.95) 4.6 1015 0.351.06 (1.04e1.08) 2.1 1010 0.461.16 (1.01e1.10) 1.1 108 0.350.94 (0.92e0.96) 1.1 1010 0.271.12 (1.07e1.18) 3.1 109 0.041.12 (1.09e1.16) 8.8 1019 0.11

    SNPs are associated with breast cancer.FGFR2 Locus

    Two variants in intron 2 of FGFR2 on the 10q26 locus werefound to be associated with breast cancer in two differentstudies.26,29 Fine-scale mapping in Europeans, Asians, andAfrican Americans identied eight SNPs as the most likelycandidates for being the causal variant.26,47 The moststrongly associated SNP, rs2981578, lies in an open chro-matin conformation region, where DNA is highly conservedamong mammalian species and was found to mediatedifferential TF binding, leading to an increase in FGFR2expression levels.47 The same SNP was associated withincreased FGFR2 signaling activity in stromal broblasts.51

    These data altogether suggest that rs2981578 is likely to befunctional. Another correlated SNP, rs7895676, was alsofound to increase FGFR2 expression.47 With the availabilityof a more complete catalog of common variants released bythe 1000 Genome project and ne mapping in larger case-control studies, it is possible that additional causal vari-ant(s) may be identied.

    TOX3 Locus

    The second strongest GWAS locus lies in a region onchromosome 16q12 containing TOX3 (formerly calledTNRC9) and LOC643714.26,52 The number of candidate



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    683684685686687688689690691692693694695696697698699700701702703704705706707708709710711712713714causal variants was reduced to 13 using data from Europeanand Asian studies, with eight clustering in a highly

    Figure 2 Mechanisms that are potentially involved in breast cancer suscein blue are cancer candidates found in/near common breast cancer susceptthose genes are the ones driving the association. Follow-up of the associatgenes.conserved region of open chromatin conformation located inthe intergenic region.26,52 Based on these data, it wasimpossible to discriminate which one of the 13 was thecausal variant. In African American studies, these variantshad completely opposite effects, suggesting the existence ofan additional risk variant, not present in Europeans andAsians, although this hypothesis requires conrmation.52

    The expression of TOX3 did not vary by the genotypes ofthe original risk variant, rs3803662, in normal and tumorbreast samples.52 Long et al53 found the strongest associa-tion with one of the 13 variants, rs4784227, in Asian andEuropean case-control studies, and demonstrated that thisvariant is functional in luciferase and electrophoreticmobility shift assays. However, unlike the variants previ-ously mentioned, it lies in a region of closed chromatin,emphasizing the difculty in interpreting functional exper-iments in this context.53 More recently, rs478227 wasassociated with increased FOXA1 binding and a repressiveeffect on TOX3.54

    CCND1 Locus (11q13)

    The 11q13 locus (rs614367) was among the loci with thestrongest association with breast cancer.32 An extensivene-scale mapping of this locus using 4405 genotyped andimputed variants was performed in 89,050 Europeansubjects from the Breast Cancer Association Consortium

    6REV 5.2.0 DTD AJPA1459_proof(BCAC).46 Three independent association signals weredetected and were strictly conned to ER tumors;

    ity. Genes in red represent high- and moderate-penetrance mutations. Genesloci. With the exception of FGFR2, MYC, CASP8, and CCND1, it is unclear if

    ci and functional analysis will conrm or exclude the involvement of thesers554219, in the strongest peak, lies in an enhancer element,increases breast cancer risk, induces differential binding ofa TF, reduces the enhancer activity, and is associated witha decrease in cyclin D1 (CCND1) levels in breast tumors. Asecond, independent SNP in the same peak, rs78540526,lies in the same enhancer element and also appears to befunctional. A third SNP, rs75915166, generates a GATA3

    Causative SNP Tag SNP

    Haplotype 1

    Hap 1 Hap 2 Hap 3Population 2

    Population 1

    Figure 3 Schematic diagram of the LD pattern in a different pop-ulation. This diagram illustrates the value of using populations from otherethnicities to rene the signal of association. Haplotype 1 in population 1is split into three haplotypes in population 2. In population 1, the causalvariant and the tag SNPs are both in the same haplotype block, in highcorrelation with each other, and are hence both associated with thedisease. In population 2, the causal variant is no longer on the samehaplotype as the tag SNP because they were separated by a recombinationevent. Therefore, if we were to genotype both SNPs in population 2, thecausal variant will remain associated with the disease but not the tag SNP.Assuming that the LD structure is different between populations for thelocus of interest, ne mapping in other ethnicities can help to reduce thenumber of candidate causal variants. - The American Journal of Pathology


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  • 5Genetic Susceptibility to Breast Cancer


    807808809810811812813814815816817818819820821822823824825826827828829830831832833834835836837838839840841842843844845846847848849850851852853854855856857858859860861862863864865866867868binding site within a silencer element. A long-range inter-action conned to ER breast cancer cells was identiedbetween the enhancer and silencer elements and withCCND1. These associations were replicated in Asian pop-ulations despite their low frequency (

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    931932933934935936937938939940941942943944945946947948949950951952953954955956957958959960961962963964965966967968969970971972973974975976977978979980981982983984985986987988989990991992dramatically induced by transforming growth factor-b,suggesting its involvement in transforming growth factor-beinduced growth inhibition.69,70 MAP3K1 encodes acomponent of the mitogen-activated protein kinase (MAPK)signaling pathway, known for its key role in cell differen-tiation, proliferation, and apoptosis.71 MAP3K1 regulatescell migration and survival, as well as immune systemfunction. MAP3K1-decient retinas exhibit increased pro-liferation and apoptosis in mice.72 MRPS30 (programed celldeath protein 9/PDCP9) is a key component of the apoptoticsignals in cells.73 MYC is a proto-oncogene that drivesseveral mitogenic signals through activation of the MAPK/ERK pathway.74 MYC is overexpressed in different tumors,including breast and prostate cancers,74 and reducing itsexpression levels using RNA interference inhibits tumorgrowth both in vivo and in vitro.75 The TCF7L2 is a proto-oncogene, an important component of the WNT pathway,and well known for its association with type 2 diabetes.76

    The MAPKAPKs have a pivotal role in the cell mitogenicprocesses and survival and are directly regulated byMAPKs.77 MK5/MAPKAP5 was found to regulate thetranslation of MYC and vice versa by a negative feedbackloop.78 NOTCH2 belongs to a family of transmembranereceptors and plays a key role in cell differentiation, pro-liferation, and apoptosis.79 Decreases in NOTCH2 expres-sion are associated with increasing grade of human breastcancer,80 and its signaling is required for anti-tumor im-munity in vivo.81 CCND1 is a key cell cycle regulator, andits amplication and overexpression were documented ina variety of tumors.82 FGFs have diverse roles in regulatingcell proliferation, migration, and differentiation, and theyplay a role in cancer pathogenesis.83 KREMEN1 suppressesthe WNT/b-catenin pathway, and its expression is low orabsent in tumor cells compared with normal tissues. Lack ofKREMEN1 and therefore activation of the WNT/b-cateninpathway is likely to be one of the mechanisms by whichtumorigenesis is enhanced.84

    Of these regions, only 8q24 has been the focus ofmultiple functional experiments. Several independent loci,clustered in a gene desert a few hundred kb upstream anddownstream of MYC, have been found to be associated withan increased risk of prostate, breast, colorectal, ovarian,glioblastoma, and bladder cancers, as well as lymphocyticleukemia (National Humane Genome Research Institute,NIH,, last accessed July29, 2013). Functional assessment both in vivo and in vitroidentied enhancer elements in each of the loci, includingmammary and prostate enhancers that interact physicallywith the MYC and PVT-1 promoters through a long-rangechromatin loop and regulate its expression levels.85e87

    Growth Factors and Tumor Aggressiveness

    Although departure from tissue homeostasis and initiation ofcancer are mainly initiated by oncogenic mutations, growthfactors play a major role in the subsequent steps of tumor8REV 5.2.0 DTD AJPA1459_proofprogression, particularly clonal expansion, invasiveness,and colonization of distant organs. Several genes near themost recently identied loci encode a growth factor (NTN4at 12q22) or are involved in tumor aggressiveness andmetastasis (PTH1R at 3p21), FOXQ1 at 6p25, ARHGEF5 at7q35, PAX9 at 14q13, and MKL1 at 22q13. NTN4 encodesa growth factor crucial for the regulation of tumor growth.High expression levels of NTN4 were detected in ER

    breast cancer but not in ER, and its use was suggested asa prognosis marker.88 PTH1R is the receptor of PTHLH(also identied in a GWAS). Up-regulation of PTH1R wasfound in patients with invasive breast ductal carcinoma.Silencing PTH1R induced suppression of cell prolifera-tion.89 Forkhead TF (FOXQ1) plays a key role in regulatingepithelial-mesenchymal transition (EMT; crucial formetastasis) in breast cancer cells. Its expression is correlatedwith high-grade breast cancers and is associated with poorprognosis. Silencing FOXQ1 reversed EMT in invasivehuman breast cancer cell lines and decreased their inva-siveness. Conversely, overexpression of FOXQ1 in humanmammary epithelial cells induced an EMT and the acqui-sition of resistance to apoptosis after chemotherapy.90

    ARHGEF5 is an oncogene and plays a pivotal role incancer development and breast metastasis through activationof the ARHGEF5/TIM pathway.91 PAX9 encodes a TF thatregulates cell proliferation, invasion, and resistance toapoptosis.92 MLK1 is also important in cell invasion andmetastasis, particularly in breast carcinomas.93

    ER Pathway

    Estrogen plays a key role in growth and in the maintenanceof reproductive functions. Two breast cancer susceptibilityloci are near genes with pivotal roles in this pathway. One at6q25 is close to ESR1 and the other, at 21q21, is close toNRIP1/RIP140. ESR1 encodes the ERa protein, which isactivated by bound estrogen. NRIP1 is a cofactor of ERaand can inhibit its mitogenic effects. This gene plays animportant role in the regulation of breast cancer cell growth,notably in ER-positive breast tumors.94

    Telomere Length

    Telomeres are regions of repetitive nucleotides at the end ofchromosomes. They are crucial in maintaining genomicstability by protecting chromosomes from degradation,recombination, and end-to-end fusion.95 Human telomerestend to progressively shorten with each cell division, andthis shortening process is associated with ageing andincreased risk of cancer.96 One of the identied breastcancer susceptibility loci lies at 5p15 and is near TERT,which encodes telomerase reverse transcriptase, the catalyticsubunit of telomerase.28 Abnormal expression of TERT hasbeen reported in several types of cancer, and the region isfrequently amplied in many types of cancer, such as lungand cervical cancers.97, - The American Journal of Pathology 22 August 2013 11:16 pm EO: AJP13_0146

  • Other Biological Pathways

    Many genes near the known susceptibility loci are either ofunknown function or have functions that do not have a clearconnection to breast cancer development (a notable examplebeing the TOX3 locus). These genes could simply not be theones being targeted, but alternatively might be involved insusceptibility through a previously unsuspected mechanism.Future functional analysis should shed some light on thecausal variants within each of these loci and the mechanismsby which they are driving the association.

    Common Pathways for Multiple Phenotypes

    Although most breast cancer susceptibility loci are diseasespecic, at least 17 loci (at 1q32, 2p24, 2q31, 4q24, 5p12,5p15, 6q25, 8q24, 9p21, 9q31, 10p12, 19p13, 10q26,11p15, 11q13, 12q24, and 14q24) occur in regions associ-ated with other cancers and complex diseases/phenotypes,suggesting a shared mechanism in disease development(Figure 4F4F4 ). Four of these have been intensively discussed.The 5p15 region containing TERT is also associated withglioma, basal cell carcinoma, and lung and pancreaticcancers ( The 8q24region is associated with at least six cancers and one of theloci, rs6983267, has a pleiotropic effect on prostate, colo-

    associated with at least six cancers (breast and pancreaticcancers, lymphoblastic leukemia, melanoma, glioma, basalcell carcinoma, and nasopharyngeal carcinoma), myocardialinfarction, type 2 diabetes, intracranial aneurysm, cutaneousnevi, and sporadic amyotrophic lateral sclerosis ( The 11q13 region containsCCND1 and several FGFs and is associated with breast,prostate, and renal cancers ( The nearest genes to the 12q24 region areTBX3, important for mammary gland development, andMAPKAP, a component of the MAPK pathway that inter-acts with MYC. SNPs in this region are associated withbreast cancer, squamous esophageal carcinoma, liveradenoma, renal cell carcinoma, heart diseases, type 1 dia-betes, blood pressure, and PSA Q9levels (

    Clinical Implications

    Although the clinical utility of testing for high-penetrancemutations such as BRCA1 and BRCA2, is well established,the potential clinical use of polygenic prediction for breastcancer is extensively debated.99e102 Taken separately, theSNP associations are too weak to be useful on an individualbasis. However, because their effects seem to combinemultiplicatively, there is potential for the predictive power


    ther, 12q

    Genetic Susceptibility to Breast Cancer


    10551056105710581059106010611062106310641065106610671068106910701071107210731074107510761077107810791080108110821083108410851086108710881089109010911092109310941095109610971098109911001101110211031104110511061107110811091110111111121113111411151116Figure 4 Location of the common breast cancer susceptibility loci toge4q24, 5p12, 5p15, 6q25, 8q24, 9p21, 9q31, 10p12, 10q26, 11p15, 11q13cancers.rectal, and possibly ovarian cancers ( The 9p21 region containing the twotumor-suppressor genes, CDKN2A and CDKN2B, isThe American Journal of Pathology - ajp.amjpathol.orgREV 5.2.0 DTD AJPA1459_proof to improve substantially as more variants are found.101 Ithas been argued that polygenic risk proles have limiteddiscrimination for breast cancer, but because the clinical

    with the most plausible nearby genes. At least 17 loci (1q32, 2p24, 2q31,24, 14q24, and 19q13) are associated with breast, prostate, and ovarian922 August 2013 11:16 pm EO: AJP13_0146

  • Q10

    these loci will need further work, but their characterization

    Ghoussaini et al


    11791180118111821183118411851186118711881189119011911192119311941195119611971198119912001201120212031204120512061207120812091210121112121213121412151216121712181219122012211222122312241225122612271228122912301231123212331234123512361237123812391240utility of a risk prediction model is not restricted todiscrimination, these should be further evaluated in thecontext of risk stratication after combining other riskfactors, such as lifestyle elements and family history.In a recent study, Pashayan et al103 showed that person-

    alized screening based on age and polygenic risk factors (18common low-penetrance loci) is more efcient than a stan-dard approach based solely on age. Personalized screeningcould reduce the number of people eligible for screening by24% while detecting most cancers (86%) compared witha program based on age alone.103 Individual risk stratica-tion would increase the efciency of the screening program,by intensifying screening in high-risk individuals andsparing unnecessary and even potentially harmful screeningin those with lower risk levels. This increase in efciencywould be even greater for risk stratication based on the 72loci identied.104

    Future Directions

    Whole Genome Resequencing

    The emerging results from GWASs suggest that a substan-tial fraction, perhaps the majority, of the familial risk ofbreast cancer can be explained by common variants, most ofwhich are yet to be identied. It is highly likely that rarer,higher-risk alleles (such as risk alleles of PALB2) alsoremain to be identied. Unraveling the full architecture ofbreast cancer susceptibility will therefore require a compre-hensive search for rarer variants. Technological advancesover the past few years have rendered whole-exome orwhole-genome resequencing of large cohorts of cases andcontrols increasingly more practical.

    Consortia and Collaborations

    Studies with large sample sizes are critical to enhancepower, achieve genome-wide signicance levels, and yieldadditional insights in terms of replication of the results, newgenetic discoveries, and key biological ndings.The past few years witnessed the formation of multiple

    international consortia and substantial widespread collabo-rations of many multidisciplinary investigators, includingepidemiologists, clinicians, statisticians, bioinformaticians,and biologists. Groups with their individual case-control setsjoined efforts to increase sample size through meta-analysis,and these collaborations resulted in an explosion of newassociations. One of the most successful examples in canceris the Collaborative Oncological Gene-Environment Study,a collaborative project funded by the European Commission,which combined data from four different consortia: BCAC,Prostate Cancer Association Group to Investigate CancerAssociated Alterations in the Genome, the Ovarian CancerAssociation Consortium, and the Consortium of Investigatorsof Modiers of BRCA1/2. This collaboration has developeda genotyping array (Collaborative Oncological Gene-10REV 5.2.0 DTD AJPA1459_proofmight reveal unexpected and important insights into cancerbiology. Loci that are associated with breast cancer and othercancers and traits will be important in revealing biologicalmechanisms that connect pathways and diseases. In additionto the common variants, rare genetic variations identiedthrough whole-exome and whole-genome sequencing strat-egies will likely expand the catalog of breast cancersusceptibility variations. Further studies to examine struc-tural variation and epigenomics may also uncover moresusceptibility loci. Integration of the germ-line susceptibilitydata with emerging somatic sequence data may be importantto both provide a more comprehensive analysis of suscepti-bility by disease subtype and interpret better the underlyingbiological characteristics. Finally, large-scale populationstudies (preferably prospective) will be required to dene thecombined effects of common and rare variants, and lifestyleConclusions

    In the future, more breast cancer susceptibility alleles arelikely to be identied, and these should, in turn, lead tofurther functional studies and expand our understanding ofthe underlying biological characteristics of breast cancer. Thecandidate genes in susceptibility regions identied thus farappear to cluster into a few biological pathways: mammarygland development, DNA repair, cell cycle control, andestrogen receptor signaling. Genes with unknown function atEnvironment Study) of approximately 200,000 SNPs thathas been genotyped in approximately 200,000 cases withbreast, prostate, and ovarian cancers and approximately200,000 controls from around the world. Results from thisproject identied 74 novel breast, prostate, and ovariancancer loci (41 of which are for breast cancer), nearlydoubling the number of the previously established ones. Inaddition, those results provided an accurate assessment of therisk related to each locus and will offer a comprehensive nemapping of the known loci. It will also be possible to evaluategenetic associations with disease survival, clinical outcome,and tumor subsets and to evaluate the combined effect ofgenetic variants and lifestyle risk factors on disease risk.More ndings emerging from this project should add greatlyto our understanding of the genetic architecture of breast andother cancers.

    GWASs in Other Populations

    Breast cancer GWASs have primarily been conducted inwomen of European descent, with the exception of one studyperformed in Chinese women, which indicated importantdifferences in the pattern of genetic loci between ethnicities.These may result from differences in allele frequencies,patterns of LD, or interactions with genetic background orlifestyle risk factors. Further GWASs in non-Europeanpopulations should therefore be extremely - The American Journal of Pathology 22 August 2013 11:16 pm EO: AJP13_0146

  • Q11



    Genetic Susceptibility to Breast Cancer


    13031304130513061307130813091310131113121313131413151316131713181319132013211322132313241325132613271328132913301331133213331334133513361337133813391340134113421343134413451346134713481349135013511352135313541355135613571358135913601361136213631364and other risk factors, on disease risk. This should lead tomore rational strategies of disease prevention, while theknowledge of breast cancer etiology gained through thefunctional understanding of disease susceptibility may leadto novel therapeutic approaches for breast cancer patients.


    We thank Dr. David Meyre and Mel Maranian for com-menting on an early draft of the manuscript and RogerMilne for generating Figure 4.


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    Ghoussaini et al


    16281629163016311632163316341635163616371638163916401641164214REV 5.2.0 DTD - The American Journal of Pathology 22 August 2013 11:16 pm EO: AJP13_0146

    Inherited Genetic Susceptibility to Breast CancerRare High-Penetrance AllelesRare Moderate-Penetrance AllelesCommon Low-Penetrance VariationAssociation of GWAS Loci by Tumor SubtypesFrom Association to Causation and FunctionA Major Challenge for Molecular GeneticsFine-Scale MappingFunctional Experiments

    Fine Mapping in Breast CancerFGFR2 LocusTOX3 LocusCCND1 Locus (11q13)TERT Locus (5p15)

    Biological Characteristics of Known Low-Penetrance Breast Cancer LociInsights into Genes and PathwaysMammary Gland DevelopmentDNA Repair PathwayCell Cycle, Differentiation, and ApoptosisGrowth Factors and Tumor AggressivenessER PathwayTelomere LengthOther Biological PathwaysCommon Pathways for Multiple Phenotypes

    Clinical ImplicationsFuture DirectionsWhole Genome ResequencingConsortia and CollaborationsGWASs in Other Populations



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