Genetic Variation in IGF2 and HTRA1 and Breast Cancer Risk ... · as risk modifiers for breast...

Research Article

Genetic Variation in IGF2 and HTRA1 and Breast CancerRisk among BRCA1 and BRCA2 Carriers

Susan L. Neuhausen1, Sean Brummel2, Yuan Chun Ding1, Linda Steele1, Katherine L. Nathanson5,6,Susan Domchek5,6, Timothy R. Rebbeck5,7, Christian F. Singer9, Georg Pfeiler9, Henry T. Lynch10, Judy E. Garber3,Fergus Couch11, Jeffrey N. Weitzel1, Andrew Godwin12, Steven A. Narod13, Patricia A. Ganz14, Mary B. Daly8,Claudine Isaacs15, Olufunmilayo I. Olopade16, Gail E. Tomlinson17, Wendy S. Rubinstein18, Nadine Tung4,Joanne L. Blum19, and Daniel L. Gillen20

AbstractBackground: BRCA1 and BRCA2 mutation carriers have a lifetime breast cancer risk of 40% to 80%,

suggesting the presence of risk modifiers. We previously identified significant associations in genetic variants

in the insulin-like growth factor (IGF) signaling pathway. Here, we investigate additional IGF signaling genes

as risk modifiers for breast cancer development in BRCA carriers.

Methods: A cohort of 1,019 BRCA1 and 500 BRCA2 mutation carriers were genotyped for 99 single-

nucleotide polymorphisms (SNP) in 13 genes. Proportional hazards regression was used to model time from

birth to diagnosis of breast cancer for BRCA1 and BRCA2 carriers separately. For linkage disequilibrium (LD)

blocks with multiple SNPs, an additive genetic model was used. For an SNP analysis, no additivity

assumptions were made.

Results: Significant associations were found between risk of breast cancer and LD blocks in IGF2 for BRCA1

and BRCA2 mutation carriers (global P values of 0.009 for BRCA1 and 0.007 for BRCA2), HTRA1 for BRCA1

carriers (global P value of 0.005), and MMP3 for BRCA2 carriers (global P ¼ 0.0000007 for BRCA2).

Conclusions: We identified significant associations of genetic variants involved in IGF signaling. With the

known interaction of BRCA1 and IGF signaling and the loss of PTEN in a majority of BRCA1 tumors, this

suggests that signaling through AKT may modify breast cancer risk in BRCA1 carriers.

Impact: These results suggest potential avenues for future research targeting the IGF signaling pathway in

modifying risk in BRCA1and BRCA2 mutation carriers. Cancer Epidemiol Biomarkers Prev; 20(8); 1690–702.

�2011 AACR.

Introduction

Women who carry mutations in the BRCA1 or BRCA2(BRCA) genes have a substantially increased risk ofdeveloping breast and ovarian cancers as compared withthe general population. Estimates of the age-specific risk

attributable to mutations at these loci vary depending onthe ascertainment scheme. The cumulative risks of breastcancer by age 70 years have been estimated between 40%and 87% for BRCA1 and BRCA2 mutation carriers (1–5).Among BRCA mutation carriers, there is considerablevariability in both age at diagnosis and incidence of breast

Authors' Affiliations: 1Department of Population Sciences, BeckmanResearch Institute of the City of Hope, Duarte, California; 2Center forBiostatistics in AIDS Research, Harvard School of Public Health;3Department of Medicine, Harvard Medical School and Dana FarberCancer Institute; 4Beth Israel Deaconess Medical Center, Boston, Mas-sachusetts; 5Abramson Cancer Center, 6Department of Medicine, and7Center for Clinical Epidemiology and Biostatistics, University of Penn-sylvania School of Medicine; 8Fox Chase Cancer Center, Philadelphia,Pennsylvania; 9Division of Special Gynecology, Department of Obste-trics and Gynaecology, Medical University of Vienna, Vienna, Austria;10Departments of Medicine, and Preventive Medicine and Public Health,Creighton University, Omaha, Nebraska; 11Department of LaboratoryMedicine and Pathology, Mayo Clinic, Rochester, Minnesota; 12Depart-ment of Pathology and Laboratory Medicine, University of KansasMedical Center, Kansas City, Kansas; 13Women's College Hospital,Toronto, Ontario; 14Jonsson Comprehensive Cancer Center at theUniversity of California, Los Angeles, California; 15Lombardi CancerCenter, Georgetown University, Washington, District of Columbia;16Departments of Medicine and Human Genetics, University of Chicago,

Chicago, Illinois; 17Division of Pediatric Hematology Oncology, TheUniversity of Texas Health Science Center at San Antonio and Universityof Texas Southwestern Medical Center, Dallas, Texas; 18NorthShoreUniversity Health System, Center for Medical Genetics, Evanston, andUniversity of Chicago Pritzker School of Medicine, Chicago, Illinois;19Baylor-Charles A. Sammons Cancer Center, Dallas, Texas; and20Department of Statistics and Department of Epidemiology, The Uni-versity of California Irvine, Irvine, California

Note: Supplementary data for this article are available at Cancer Epide-miology, Biomarkers andPreventionOnline (http://cebp.aacrjournals.org/).

Corresponding Author: Susan L. Neuhausen, Department of PopulationSciences, the Beckman Research Institute of the City of Hope, 1500 E.Duarte, Duarte, CA 91010. Phone: 626-471-9261; Fax: 626-471-9269;E-mail: [email protected]

doi: 10.1158/1055-9965.EPI-10-1336

�2011 American Association for Cancer Research.

CancerEpidemiology,

Biomarkers& Prevention

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and ovarian cancers, even among women who carry thesame BRCA mutation (6–8). These observations of largevariation in risk are consistent with the hypothesis thatthe breast cancer risk in mutation carriers is modified byother genetic and/or environmental factors. To test thishypothesis, we have focused on genetic variation in theinsulin-like growth factor (IGF) signaling pathway, as itregulates both cellular proliferation and apoptosis(reviewed in refs. 9–11). We previously reported signifi-cant associations of single-nucleotide polymorphisms(SNP) in insulin receptor substrate (IRS) 1 and IGF1Rin BRCA1 mutation carriers and in IGF1R and IGFBP2 inBRCA2 mutation carriers (12).For this study, we investigated the association of var-

iants in additional genes involved in IGF signaling. Wefocused on 13 genes in this pathway, which were closelyrelated to genes with significant associations with breastcancer risk in our previous work (12). These genesincluded the IGF1 receptor (IGF1R) ligands IGF2 andinsulin (INS); the IGF binding proteins (IGBFP) IGFBP3(and its partners in binding IGF, IGFALS), IGFBP4, andIGFBP6; the IGFBP proteases kallikrein–related peptidase3 (KLK3, aka prostate-specific antigen; PSA), cathepsin D(CTSD), matrix metalloproteinases 3 and 7 (MMP3 andMMP7), HTRA serine peptidase 1 (HTRA1, aka PRSS11);the IGF1R docking protein IRS2; and its phosphorylationtarget phosphoinositide 3-kinase 110-kb catalytic subunitB (PIK3CB), as potential disease modifiers in deleteriousmutation carriers of BRCA1 and BRCA2.

Materials and Methods

ParticipantsFor the primary investigation, women with germline,

deleterious mutations in BRCA1 or BRCA2 were identi-fied in 14 centers in the United States, 1 center in Canada,and 1 center in Austria, including Baylor UniversityMedical Center-Dallas, Dallas, TX, Beth Israel in Boston,City of Hope, Creighton University, Omaha, NE, DanaFarber, Boston, MA, Fox Chase Cancer Center, Philadel-phia, PA, Georgetown University, Washington DC, theMayo Clinic, Scottsdale, AZ, Medical University ofVienna, Vienna, Austria, North Shore University Health-System, Chicago, IL University of California, LosAngeles, CA, University of California, Irvine, CA, Uni-versity of Chicago, Chicago, IL, University of Pennsylva-nia, Philadelphia, PA, and Women’s College Hospital,Toronto, Ontario. The majority of subjects were recruitedfrom the Medical University in Vienna, Creighton Uni-versity in Nebraska, the University of Pennsylvania, andthe University of California Irvine (previously at theUniversity of Utah and now at the Beckman ResearchInstitute of the City of Hope). All centers are part of theModifiers and Genetics in Cancer (MAGIC) Consortium.All participants were enrolled under Institutional ReviewBoards or ethics committee approval at each participatingsite. Women were identified through either clinical orresearch high-risk programs, generally because of a

family history of breast and/or ovarian cancer. Thecurrent study uses data on a total of 1,519 adult, femalenon-Hispanic Caucasian mutation carriers, including1,019 BRCA1 carriers (381 cases and 638 unaffected con-trols) and 500 BRCA2 carriers (219 cases and 281 unaf-fected controls). The BRCAmutation status of all subjectswas confirmed by direct mutation testing, with fullinformed consent under protocols approved by thehuman subjects review boards at each institution.Women were eligible for entry into the study cohort ifthey tested positive for a known deleterious mutation inBRCA1 or BRCA2. Women with deleterious mutations inboth BRCA1 and BRCA2 were excluded. Women wereexcluded if they were missing information on year ofbirth, parity, menopausal status, and oral contraceptiveuse or had a diagnosis of breast or ovarian cancer morethan 3 years prior to study entry. Information aboutbreast cancer, ovarian cancer, prophylactic mastectomy,and prophylactic oophorectomy was obtained frommed-ical records, and information on reproductive history andlifestyle habits was obtained by questionnaire.

SNP genotypingThe Genome Variation Server (GVS; ref. 13) at the

University of Washington was used to identify SNPs inthe genes and select haplotype tagging SNPs (htSNP)using the programLDSelect (14), which is integratedwiththe GVS. A total of 99 SNPswere selected from 13 genes tomark the common genetic variation in each gene andminimize the genotyping costs. However, because someof the genes had SNPs from the pooled HapMap race/ethnicity samples, we could not discern race and so werecalculated linkage disequilibrium (LD) blocks specifi-cally for the European (EU) population in this article asdescribed later.

Genotyping was done using the SNPlex assay fromApplied Biosystems, Inc. (ABI), for all but 3 SNPs inIGFBP3 for which alleles were genotyped byABI TaqManexonuclease assays. Genotyping by SNPlex was doneaccording to ABI’s protocols. The SNPlex assay is basedon an oligonucleotide ligation assay (OLA), followed bymultiplex PCR amplification using a universal primerpair, hybridization of reporter probes to amplicons, andcapillary electrophoresis to rapidly identify eluted repor-ter probes (ABI). On the basis of the list of SNPs sent toABI, 3 SNPlex pools were designed and ordered forgenotyping. We obtained genotype data for 99 SNPsfollowing the manufacturer’s protocol (ABI). Briefly,120 ng genomic DNA for each sample was fragmentedby denaturing at 99�C for 10 minutes. Phosphorylation ofprobes and allele-specific ligation between fragmentedDNA and probes were done by running an OLA programon a PTC225 thermal cycler. After purification of ligationproduct by exonuclease digestion, PCR was carried outusing universal primers with the reverse primer biotiny-lated. During hybridization, the captured biotinylatedPCR strands were hybridized with fluorescently labeledZipChute probes, with a unique sequence corresponding

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to the unique Zip code sequences at the 50 end of theallelic-specific probes used in OLA reactions. The Zip-Chute probes were separated by the ABI 3130xl capillarysequencer, and genotypes were called by ABI Genemap-per 4.0 program. The laboratory technician was blindedas to whether samples were duplicates, cases, or controls.Each 96-well plate contained 87 unique samples, 2 posi-tive controls, 1 negative control, and 6 ladders. Genotyp-ing call rates ranged from 67% to 99%. SNPs that weremonomorphic or with minor allele frequencies (MAF)less than 0.03 (n ¼ 10 SNPs) or with genotyping call ratesless than 80% (n ¼ 5 SNPs) were excluded from furtheranalysis. Because the duplicate concordance rates of the40 duplicated samples were higher than 99.9%, we feltconfident that the datawere accurate even for the 10 SNPswith 82% to 89% call rates.

Determination of LD blocksTo define LD blocks relative to the current study

population, all LD blocks were computed using thecurrent analytic data set. Because of the relatively smallproportion of non-EU subjects within the study sample,and the possibility that LD structure may differ betweenEU and non-EU ancestries, we restricted the analysis toonly non-Hispanic Caucasians. SNPs were groupedaccording to their adjacent pairwise LD coefficient, D0,which was computed between all adjacent marker pairswithin each candidate gene. To account for within-familycorrelation, multiple outputation (15) was used to esti-mate D0. In this case, a single member from each familywas randomly sampled to create a single bootstrap sam-ple, from which D0 was computed. This process wasrepeated to obtain 200 bootstrap samples, yielding anempirical distribution ofD0. An LDblockwas defined as aset of contiguous SNPs having D0 values exceeding 0.90between each contiguous pair of SNPs. The boundary ofan LD block would be defined by amarker pair withD0 �0.9. Given that individuals of Ashkenazi Jewish ancestrymake up approximately 24% of the analytic sample, wefurther explored differential LD structure between Ash-kenazi Jewish ancestry and non-Ashkenazi Jewish ances-try. No statistically significant differences were found (asdefined by nonoverlapping 95% CIs for D0 betweenancestry strata). However, to guard against groupingSNPs within an ancestry that may or may not be inlinkage, we used the minimum D0 between the non-Jewish and the Jewish groups when defining the LDblocks. The LD blocks for the SNPs within each geneare shown in Supplementary Table S1 along with theMAFs.

Statistical analysisFor all analyses, subjects were considered at risk for

breast cancer from birth until the first occurrence of breastcancer diagnosis, death, or loss to follow-up. Subjectswere censored in the event that they underwent a bilat-eral prophylactic surgery of the breasts more than 1 yearpreceding the diagnosis of breast cancer. Bilateral pro-

phylactic surgery of the breasts occurring within a year ofbreast cancer was considered an event to avoid potentialbiases resulting from informative censoring. Descriptivebreast cancer rates were calculated as the observed num-ber of breast cancers per total patient time at risk andstandardized to the age distribution of the study cohort atthe time of interview (16). Covariates that vary with time(ovarian cancer and prophylactic ovarian surgery) weretreated as time-dependent in the calculation of rates.Thus, a subject who had a diagnosis of ovarian cancercontributed time at risk in the nonovarian cancer groupprior to the diagnosis and then time at risk in the ovariancancer group following the diagnosis. Because subjectswere ascertained primarily from high-risk clinics, selec-tion bias is likely to result in an overrepresentation ofcases in the analysis sample relative to the general popu-lation. To account for potential bias in cumulative riskestimates due to nonrandom sampling from the generalpopulation, Kaplan–Meier estimates of the cumulativeprobability of breast cancer diagnosis were computedusing age-specific sampling weights for cases and con-trols as obtained from Antoniou and colleagues (17).

Cox proportional hazards regression was used to esti-mate the association between time from birth to diagnosisof breast cancer and haplotypes in genes within the IGFpathway. In this model, the hazard or instantaneous rateof breast cancer diagnosis is modeled as a function of thepredictor covariates. The relative risk or HR is theninterpreted for each covariate as the proportionatechange in the instantaneous rate of diagnosis for 2 indi-viduals differing by a single unit of that covariate. Whenanalyzing LD blocks with multiple SNPs, an additivehaplotype effect was assumed where the haplotype com-posed of the major allele for each individual SNP withinthe LD block was used as the referent group for compar-isons (i.e., 0000). However, when an LD block consisted ofan SNP, a general genetic model making no additivityassumption was used. To account for phase uncertaintyin haplotype analysis, we used a 2-step approximation tothe semiparametric maximum likelihood estimator of Linand Zeng (18). This method used the expectation–max-imization algorithm to compute posterior estimates of theprobability of all potential haplotypes for a subject giventheir known genotype, and these probabilities were usedto weight the individual’s contribution to the partiallikelihood. A similar approach has previously beenapplied to logistic regression models for analyzingcase–control data and shown to provide robust inferencefor relatively common haplotypes with little phase ambi-guity (19). To account for hierarchical clustering at theindividual level (multiple records per individual wereanalyzed according to the number of potential diplotypesconsistent with the individual’s genotype) and the familylevel (matched controls were often selected from thefamily of a case), the sandwich estimator of Lin andWei (20) was used in combination with multiple out-putation (15) to obtain robust inference about haplotypeassociations. All estimates were adjusted for birth cohort

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(to account for frequencymatching of cases and controls),ancestry, age at first pregnancy, and region of center[North American (US) vs. EU]. Ashkenazi Jewish indivi-duals were considered a separate group because thecarriers had only 1 of 3 founder mutations. Age at firstpregnancy, prophylactic oophorectomy, and ovarian can-cer status were treated as time-dependent covariates inthe analysis. To account for potential selection biasthrough recruitment from high-risk clinics, all regressionmodels employed age-specific sampling probabilityweights for cases and controls as obtained fromAntoniouand colleagues (17). For LD blocks exhibiting significantassociations with the time to breast cancer diagnosis,secondary analyses of individual SNPs making up theLD block were conducted. In addition, we consideredsensitivity analyses to assess the assumption of addi-tivity for haplotype models and found no quantifiabledifferences.In total, the current analysis involved testing of 83

SNPs in 41 LD blocks across the 13 genes, which is likelyto result in an inflation of the family-wise type I error ratefor the study if unadjusted critical values are used forassessing LD block significance. Noting that this analysisrepresents a first stage in identifying variants in the IGFpathway that are associated with time to breast cancerdiagnosis, we sought to control the family-wise type errorrate at 10% to minimize the type II error rate, limiting thepossibility of ruling out potentially important LD blocksfrom future investigation. Simulation was used to esti-mate the family-wise type I error rate, assuming a corre-lation of 0.75 across tests. On the basis of 100,000simulations, it was estimated that an adjusted P valueof 0.010 on any individual LD block test would result in afamily-wise type I error rate of 10% for the study. Thus,

an adjusted P value less than 0.010 was interpreted as asignificant association.

Results

The characteristics of study participants, study sites,and the observed incidence rate (per 1,000 women peryear) of breast cancer diagnosis stratified by BRCA statuswere previously described (12). Briefly, the age-standar-dized incidence rate of breast cancer diagnosis was esti-mated to be 26.94 per 1,000 per year in BRCA1 carriers(95% CI: 19.79, 34.10) compared with 25.03 per 1,000 peryear in BRCA2 carriers (95% CI: 18.71–31.36). The char-acteristics of the study participants, limited to non-His-panic Caucasians, are shown in Table 1. The majority ofstudy subjects in both strata were of non-Jewish ancestry(76%). Of the study subjects, 9% underwent bilateralprophylactic mastectomy and 41% underwent prophy-lactic bilateral salpingo-oophorectomy. Median age atdiagnosis was estimated to be 57.0 years (95% CI: 54.1–62.2) among BRCA1 carriers and was 70.5 years (95% CI:67.7–INF) among BRCA2 carriers. The results are pre-sented grouped by genes in components of the IGFsignaling pathway. As described in Materials and Meth-ods, only P values of less than 0.010 for individual LDblocks were considered significant.

IGFIR ligands: IGF2 and INSIn Figure 1, we present the estimated HR for time to

diagnosis by LD block and BRCA status after adjustmentfor covariates (described in Materials and Methods). Forboth BRCA1 and BRCA2 mutation carriers, significantassociations of LD blocks in IGF2were observed. AmongBRCA1 carriers, for IGF2 LD block 3 (defined by SNP

Table 1. Characteristics of study participants by BRCA gene

Characteristic BRCA1 carriers BRCA2 carriers

Total, n (%) Cases, n (%) Total, n (%) Cases, n (%)

Total 1,019 381 500 219Ethnicity

Caucasian (non-Jewish, non-Hispanic) 774 (76) 283 (74) 381 (76) 176 (80)Caucasian (Jewish, non-Hispanic) 245 (24) 98 (26) 119 (24) 43 (20)

Ovarian cancerYes 111 (11) 26 (7) 30 (6) 5 (2)No 908 (89) 407 (93) 513 (94) 233 (98)

Bilateral BPOYes, before breast cancer diagnosis 270 42 103 17Yes, after breast cancer diagnosis 154 154 94 94No BPO 594 184 303 108

Prophylactic bilateral mastectomyYes 99 37No 920 463

Abbreviation: BPO, prophylactic oophorectomy.






rs1065687), women with at least 1 variant allele wereestimated to experience a 76% higher relative risk ofdiagnosis than did women with no variant allele (per-allele HR 1.76; 95% CI: 1.15–2.70; P ¼ 0.009). AmongBRCA2 carriers, in LD block 5, composed of 4 SNPs, theglobal P value was significant for LD block 4 (P ¼ 0.003)and LD block 5 (P ¼ 0.0007). In LD block 4, women withhaplotype 10 had a more than 2-fold increased risk ofbreast cancer (HR ¼ 2.20; 95% CI: 1.4–3.5; P ¼ 0.0008). InLD block 5, womenwith haplotypes 0001 (HR¼ 0.48; 95%CI: 0.30–0.76; P ¼ 0.0017), 0100 (HR ¼ 0.40; 95% CI: 0.26–

0.61; P¼ 0.00002), and 0101 (HR¼ 0.39; 95% CI: 0.20–0.79;P ¼ 0.009) were estimated to experience a significantlydecreased risk of diagnosis when compared with thereference haplotype. Given the significant HRs for thehaplotypes in IGF2 LD blocks 4 and 5, we investigated theHRs for the 6 individual SNPs (rs3213232, rs3213229,rs3213223, rs3213221, rs3213217, and rs3213216) withinthe LDblocks to examinewhether the observedhaplotypeeffect could be attributed to any one SNP. Of the 6 SNPs,there was only an effect of carrying 1 copy of the variantallele of rs3213221 (HR ¼ 0.60; 95% CI: 0.40–0.92;

Figure 1. Estimated HRs associated with haplotype presence for IGF2 (A) and INS (B). Linkage blocks (C) were defined as pairwise D0 � 0.90. Estimateswere stratified by BRCA1/2 mutation status (BRCA1 in left column and BRCA2 in right column) and adjusted for birth cohort and ancestry (non-Jewishor Jewish) as well as first pregnancy, prophylactic oophorectomy, and diagnosis of ovarian cancer as time-dependent covariates. C, SNPs within eachof the LD blocks are shown for each gene.

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P ¼ 0.018). There was no significant association of INSand breast cancer risk among BRCA1 or BRCA2 carriersafter adjusting for multiple testing.

IGFBPs: IGFALS (in the complex with IGFBP3),IGFBP3, IGFBP4, and IGFBP6Estimated HRs for the haplotypes of the IGBFPs are

shown in Figure 2. No significant global tests of associa-

tions were observed for any haplotypes of the 3 IGFBPgenes. The SNP in IGFALS was also not associated withrisk (see Supplementary Table S1).

IGFBP proteases: HTRA1, MMP3, MMP7, KLK3,and CTSD

Estimated HRs for the haplotypes of the IGFBP pro-teases are shown in Figures 3 and 4. A highly significant

Figure 2. Estimated HRs associated with haplotype presence for IGFBP3 (A), IGFBP4 (B), and IGFBP6 (C). Linkage blocks (D) were defined as pairwiseD0 � 0.90. Estimates were stratified by BRCA1/2 mutation status (BRCA1 in left column and BRCA2 in right column) and adjusted for birth cohort andancestry as well as first pregnancy, prophylactic oophorectomy, and diagnosis of ovarian cancer as time-dependent covariates.






Figure 3. Estimated HRs associated with haplotype presence for HTRA1 (A), KLK3 (B), and CTSD (C). Linkage blocks (D) were defined as pairwiseD0 � 0.90. Estimates were stratified by BRCA1/2 mutation status (BRCA1 in left column and BRCA2 in right column) and adjusted for birth cohort andancestry as well as first pregnancy, prophylactic oophorectomy, and diagnosis of ovarian cancer as time-dependent covariates.

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association in HTRA1 LD block 3, composed of 3 SNPs,was observed in BRCA1 carriers (global P ¼ 0.005) withno association in BRCA2 carriers (global P ¼ 0.147).Within LD block 3, the rare haplotypes groupedtogether were significantly associated with a 2-fold risk

to develop breast cancer (HR¼ 2.12; 95% CI: 1.30–3.46; P¼ 0.0028). When looking at individual SNPs withinHTRA1, no SNP within LD block 3 was associated withrisk. There were no significant associations of LD blocksin HTRA1 and risk among BRCA2 carriers. However,

Figure 4. Estimated HRs associated with haplotype presence for MMP3 (A) and MMP7 (B). Linkage blocks (C) were defined as pairwise D0 � 0.90.Estimates were stratified by BRCA1/2 mutation status (BRCA1 in left column and BRCA2 in right column) and adjusted for birth cohort and ethnicity aswell as first pregnancy, prophylactic oophorectomy, and diagnosis of ovarian cancer as time-dependent covariates.






among BRCA2 carriers, carrying the variant allele inrs12571363 in LD block 1 conferred a 2-fold increasedrisk (per allele HR ¼ 2.03; 95% CI: 1.29–3.21; P ¼ 0.002).Haplotypes in KLK3 and CTSDwere not associated withany modification of risk for developing breast cancer.For MMP3 in BRCA2 carriers, a highly significant asso-ciation (global P ¼ 0.0000003) in LD block 3 wasobserved because of a combination of rare haplotypesassociated with a 5.1-fold higher risk (HR: 5.08; CI: 2.67–9.67; P ¼ 0.0000007; Fig. 4A). None of the 3 SNPsconstituting this haplotype, rs476762, rs679620, orrs3025058, could explain the association. For MMP7,after adjusting for multiple testing, there were no sig-nificant associations of any LD blocks with risk inBRCA1 or BRCA2 carriers.

IGF1R downstream docking protein andphosphorylation target: IRS2 and PIK3CB

There was no significant association of LD blocks ineither IRS2 or PIK3CB and breast cancer risk (Fig. 5).

Discussion

The IGF pathway signals cells to grow, differentiate,and survive through activation of the phosphoinositol-3-kinase/protein kinase AKT (PI3K/AKT) pathway andthe RAS/mitogen-activated protein kinase (RAS/MAPK)pathway. The role of the IGF pathway in breast cancerwas reviewed, and a figure of the IGF system and itsdownstream effectors was presented by Hamelers andSteenbergh (21). This study is a continuation of our

Figure 5. Estimated HRs associated with haplotype presence for IRS2 (A) and PIK3CB (B). Linkage blocks (C) were defined as pairwise D0 � 0.90.Estimates were stratified by BRCA1/2 mutation status (BRCA1 in left column and BRCA2 in right column) and adjusted for birth cohort and ancestryas well as first pregnancy, prophylactic oophorectomy, and diagnosis of ovarian cancer as time-dependent covariates.

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investigation of the role of genetic variants in IGF signal-ing asmodifiers of breast cancer risk in womenwho carrydeleterious mutations in BRCA1 and BRCA2. We pre-viously investigated only a small number of the genesinvolved in IGF signaling and reported significant HRsassociated with genetic variants in IGF1R and IRS1 inBRCA1 mutation carriers and in IGFBP2 and IGFBP5in BRCA2 mutation carriers (12). In this investigationof an additional 13 genes in the pathway, there weresignificant associations of variants in IGF2 in both BRCA1and BRCA2 mutation carriers and HTRA1 in BRCA1mutation carriers and MMP3 in BRCA2 carriers.There have been a limited number of epidemiologic

studiesof theassociationof sporadicbreast cancer riskandgenetic variation in the genes in the IGF pathway inves-tigated in this study. In a large study in theNCI breast andprostate cancer cohort consortium of 6,292 breast cancercases and 8,135 unaffected controls, they reported nosignificant associations (P < 0.00005) of SNPs in IGF2,IGFALS, IGFBP3, IGFBP4, IGFBP6, and IRS2 and breastcancer risk (22). Their results were inconsistent with ourobservation of significant associations with haplotypes inIGF2, which may reflect different SNPs and differentpopulation characteristics including ages at diagnosisand BRCA1 and BRCA2 carrier status. There have beenseveral studies of the �202 A>C SNP in the IGFBP3promoter and breast cancer risk,withmost being negative(reviewed in ref. 23). In association studies of SNPs andbreast cancer risk in theCancer Prevention Study II, 3 of 11SNPs in IRS2 were associated with breast cancer risk(haplotype OR ¼ 0.76; 95% CI: 0.63–0.92; ref. 24) andthe INS rs3842752 SNP was not associated with breastcancer risk (25). The INS SNPwas the same,whereas noneof the 11 IRS2 SNPs were the same as investigated in ourstudy. Two studies have reported significant associationsof SNPs in MMP7 and breast cancer survival, althoughwith different SNPs than investigated here (26, 27) As yet,there are no reported association studies in breast cancerinvestigating SNPs in HTRA1, PIK3CB, or MMP3.IGF1 and IGF2 are the primary ligands for binding to

the IGF1R, and IGF2 levels are higher than IGF1 levels incells. Interestingly, in a study of women of 43 womenwith localized breast cancer and 38 unaffected controls,there were significantly elevated circulating free IGF2and IGF1 levels yet significantly reduced total IGF2 levelsand reduced total IGF1 levels in the breast cancer cases ascompared with controls (28). They also found thatIGFBP2 levels were significantly reduced in the caseswith no differences in IGFBP1, 3, 4 or 6 levels andsuggested that the increase in free IGF levels was becausethere was less IGFBP2 to bind IGF2. IGFBP2 and IGFBP5preferentially bind IGF2 over IGF1. With higher amountsof free IGFs, there can be more signaling activity throughIGF1R. The significant association with variants inIGF2 fits with our previous results in which we hadobserved a significant association with variants at theIGFBP2_IGFBP5 locus in BRCA2 carriers and at IGF1R inBRCA1 carriers.

Proteolysis of IGFBPs occurs through the action ofIGFBP proteases that include serine proteases (KLKsand HTRA1), MMPs, and CTS (29). With proteolysis ofthe IGFBPs, there is then more bioavailability of the IGFsfor signaling through IGF1R. In BRCA1mutation carriers,an HTRA1 haplotype in LD block 3 was significantlyassociated with breast cancer (global P¼ 0.0005).HTRA1,located at 10q25.3-q26.2, was identified in 1996 as a serineprotease specific for IGFBPs (30). HTRA1 is also nowthought to function as a tumor suppressor gene (31),possibly through regulation of TGF-B signaling (32).None of the 4 SNPs in the LD block were significantlyassociated with breast cancer, suggesting that the asso-ciated haplotype only marks the causal variant in theregion. Further investigation of this region is needed tounderstand how it may be modifying risk of developingbreast cancer in BRCA1mutation carriers. A group of rarehaplotypes (combined frequency of 2%) in MMP3,another IGFBP protease, was significantly associatedwith breast cancer in BRCA2 carriers (HR ¼ 4.33). ForMMP3, many more carriers need to be investigated todetermine the actual associated haplotype within thegrouped haplotypes, as neither of the 2 SNPs in theLD block showed association.

PIK3CB is a 110-kDa catalytic subunit of PI3K and isactivated through the IGF1R as follows: Binding of IGFinduces receptor autophosphorylation of the b-subunit ofIGF1R, resulting in activation of the tyrosine kinaseactivity and subsequent tyrosine phosphorylation ofIRS1. The activated IRS1 binds the p85 a-subunit PI3K,which, in turn, activates PIK3CB for downstream signal-ing. PTEN regulates PI3K signaling by dephosphorylat-ing PI3K, so in the absence of PTEN, the pathway isactivated. In cells without PTEN, experiments haveshown that PIK3CB is necessary for continued PI3Ksignaling (33). PIK3CB may be particularly relevant tocancer in BRCA1 carriers because a majority of BRCA1and other basal-like breast cancers have loss of PTENexpression (34). Furthermore, this suggests a possibletherapeutic target in BRCA1 carriers. Clinical trials areongoing with agents targeting the inhibition of the IGF1Rand mTOR, although none are targeted to BRCA muta-tion carriers. In BRCA1 carriers, there was a marginalassociation of genetic variation in PIK3CB and breastcancer. The intronic SNP rs9878820 was associated withbreast cancer (per allele HR¼ 0.83, CI: 0.70–0.99, P¼ 0.04;homozygous recessive HR ¼ 0.69, P ¼ 0.04), and wasmore strongly associated in the larger data set includingHispanics, African Americans, and others (P ¼ 0.008).

Although this study provides an important continuedstep in identifying potential genetic modifiers of riskamong BRCA1 and BRCA2 mutation carriers, there aresome limitations. First, the sample size was limited,particularly for BRCA2 carriers, so that there may beassociations that we could not detect and the pointestimates for the associations we did detect may beimprecise, particularly for SNPs and haplotypes of lowfrequency. Second, the loci that we identified in this study






that had significant HRs for risk were not previouslyidentified as the top candidates in the genome-wideassociation study (GWAS) of BRCA1 (35) or BRCA2mutation carriers (36). However, even known associa-tions can be missed in GWAS, as only the top hits arefurther investigated through replication and imputationof additional SNPs in those regions. One example is theprevious finding that a promoter SNP in RAD51C (37) is amodifier of risk in BRCA2 carriers with an HR of 3.2among the rare homozygotes, yet it was not identified inthe GWAS (36). Therefore, it is possible that one or moreof the associations identified here were missed in theGWAS. Third, although the IGF pathway was a priorihypothesized as a source for potential modifiers, multipleLD blocks were considered for association testing andsuch testing could lead to inflation of the overall type Ierror rate for the study. With this being said, we studiedonly a relatively small number of the genes in IGFsignaling that we a priori deemed would potentially playa role in the time to diagnosis and considered significantonly those associations that decreased beyond a multiplecomparison-adjusted critical value. In addition, we viewthe goal of the current research as hypothesis refinementwhere, based upon the results from this well-defined setof genes, we will further validate the results using anindependent sample. As with all observational studies,there is the potential for selection bias and unmeasuredconfounding. However, we have adjusted for those fac-tors that are most likely to influence the risk of breastcancer diagnosis within this cohort, thus lowering thepotential for unadjusted confounding.

We and others have investigated putative risk factors,and a number of published studies have implicated locias modifiers of breast or ovarian cancer penetrance inwomen who carry germline BRCA1 or BRCA2 mutations(12, 35–42). The majority of modifiers of BRCA1 cancerrisk identified to date have been genetic variants inproteins that interact with BRCA1 in DNA repair. Ourresults suggest that IGF signaling also modifies breastcancer penetrance in BRCA1 and BRCA2 mutation car-riers. IGF signaling and BRCA1 directly interact withmultiple lines of evidence, including that IGF-1 enhancesBRCA1 activity (43), BRCA1 regulates IGF1R and IRS1activity (44, 45), and BRCA1 protein expression andlocalization are dependent on AKT activation (46).

In conclusion, this is the second study to investigate therole of genetic variation in IGF signaling and breastcancer risk in women carrying deleterious mutations inBRCA1 and BRCA2. In the previous study, we identifiedsignificant associations in variants in IGF1R and IRS1 forBRCA1 carriers and in IGF1R, IGFBP2, and IGFBP5 inBRCA2 carriers. On the basis of those results, and given

the known interaction of BRCA1 and IGF signaling, weinvestigated additional variants in genes in this pathwayand identified significant breast cancer risk modifierswith haplotypes in IGF2 for both BRCA1 and BRCA2mutation carriers and in HTRA1 and MMP3 for BRCA1and BRCA2 mutation carriers, respectively. The identifi-cation of causalmechanismswithin these loci is needed tovalidate and better understand these associations. Wehope that with further identification of genetic factorsthat modulate age at diagnosis and overall incidence ofbreast cancer, and better elucidation of the actualmechanisms of modifying risk, these data can be usedin the future to provide more precise risk estimates todevelop cancer and design targeted therapeutics forcarriers.

Disclosure of Potential Conflicts of Interest

T.R. Rebbeck is the Editor-in-Chief of Cancer Epidemiology, Biomarkers &Prevention. In keeping with the AACR’s Editorial policy, the manuscriptwas peer reviewed and a member of the AACR’s Publications Committeerendered the decision concerning acceptability. Its contents are solely theresponsibility of the authors and do not necessarily represent the officialviews of the State of Nebraska or the Nebraska Department of Health andHuman Services.

Acknowledgments

The MAGIC Consortium includes the following centers and indivi-duals: Baylor-Charles A. Sammons Cancer Center (J.L. Blum, MD, PhD;Estelle Brothers, RN; G. Ethington), Beckman Research Institute of theCity of Hope (formerly at the University of California, Irvine, S.L.Neuhausen, PhD; L. Steele; J.N. Weitzel, MD; S. Sand), Beth IsraelDeaconess Medical Center (N. Tung, MD), Creighton University (C.Snyder, BA; H.T. Lynch, MD; P. Watson, PhD), Dana Farber CancerInstitute (K. Stoeckert; J.E. Garber, MD MPH), Fox Chase Cancer Center(M.B. Daly, MD, PhD; A.K. Godwin, PhD), Georgetown University (C.Isaacs, MD), Jonsson Comprehensive Cancer Center at the University ofCalifornia, Los Angeles (J. Seldon, MSGC; P.A. Ganz, MD), Mayo Clinic(F. Couch, PhD), Northshore University HealthSystem Center for MedicalGenetics (C. Selkirk, S.M. Weissman, W.S. Rubinstein, MD, PhD), Uni-versity of Chicago (S. Cummings; O. Olopade, MD), University of Penn-sylvania Health System: (S. Domchek, MD; K. Nathanson, MD; T. Friebel,MPH; T. Rebbeck, PhD), University of Texas, San Antonio (G. Tomlinson,MD), University of Vienna (C. Singer, MD), Women’s College Hospital (S.A. Narod, MD).

Grant Support

Support was received from NIH grants 5UO1 CA86389 (to H.T. Lynch), R01-CA083855 and R01-CA74415 (to S.L. Neuhausen), R03-CA135691 (to D.L. Gillen),R01-CA102776 and R01-CA083855 (to T.R. Rebbeck), RC4-CA153828 (to J.N.Weitzel), R01CA140323 and 5U01CA113916 (to A. Godwin), R01-CA128978 andR01-CA116167 (to F. Couch), and U01CA69631 (to M.B. Daly) and a grant fromthe Breast Cancer Research Foundation (to F. Couch). This publication wassupported in part by revenue from Nebraska cigarette taxes awarded toCreighton University by the Nebraska Department of Health and HumanServices. S.L. Neuhausen is partially supported by the Morris and HorowitzFamilies Endowment.

Received December 23, 2010; revised April 22, 2011; accepted June 16,2011; published OnlineFirst June 27, 2011.

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2011;20:1690-1702. Published OnlineFirst June 27, 2011.Cancer Epidemiol Biomarkers Prev Susan L. Neuhausen, Sean Brummel, Yuan Chun Ding, et al.

CarriersBRCA2 and BRCA1among and Breast Cancer RiskHTRA1 and IGF2Genetic Variation in

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