Skip to main content

Main menu

  • Home
  • Articles
    • Current
    • Special Feature Articles - Most Recent
    • Special Features
    • Colloquia
    • Collected Articles
    • PNAS Classics
    • List of Issues
  • Front Matter
    • Front Matter Portal
    • Journal Club
  • News
    • For the Press
    • This Week In PNAS
    • PNAS in the News
  • Podcasts
  • Authors
    • Information for Authors
    • Editorial and Journal Policies
    • Submission Procedures
    • Fees and Licenses
  • Submit
  • Submit
  • About
    • Editorial Board
    • PNAS Staff
    • FAQ
    • Accessibility Statement
    • Rights and Permissions
    • Site Map
  • Contact
  • Journal Club
  • Subscribe
    • Subscription Rates
    • Subscriptions FAQ
    • Open Access
    • Recommend PNAS to Your Librarian

User menu

  • Log in
  • My Cart

Search

  • Advanced search
Home
Home
  • Log in
  • My Cart

Advanced Search

  • Home
  • Articles
    • Current
    • Special Feature Articles - Most Recent
    • Special Features
    • Colloquia
    • Collected Articles
    • PNAS Classics
    • List of Issues
  • Front Matter
    • Front Matter Portal
    • Journal Club
  • News
    • For the Press
    • This Week In PNAS
    • PNAS in the News
  • Podcasts
  • Authors
    • Information for Authors
    • Editorial and Journal Policies
    • Submission Procedures
    • Fees and Licenses
  • Submit
Research Article

Evaluation of linkage of breast cancer to the putative BRCA3 locus on chromosome 13q21 in 128 multiple case families from the Breast Cancer Linkage Consortium

Deborah Thompson, Csilla I. Szabo, Jon Mangion, Rogier A. Oldenburg, Fabrice Odefrey, Sheila Seal, Rita Barfoot, Karin Kroeze-Jansema, Dawn Teare, Nazneen Rahman, Hélène Renard, KConFab Consortiumef, Graham Mann, John L. Hopper, Saundra S. Buys, Irene L. Andrulis, Ruby Senie, Mary B. Daly, Dee West, Elaine A. Ostrander, Ken Offit, Tamar Peretz, Ana Osorio, J. Benitez, Katherine L. Nathanson, Olga M. Sinilnikova, Edith Olàh, Yves-Jean Bignon, Pablo Ruiz, Michael D. Badzioch, Hans F. A. Vasen, Andrew P. Futreal, Catherine M. Phelan, Steven A. Narod, Henry T. Lynch, Bruce A. J. Ponder, Ros A. Eeles, Hanne Meijers-Heijboer, Dominique Stoppa-Lyonnet, Fergus J. Couch, Diana M. Eccles, D. Gareth Evans, Jenny Chang-Claude, Gilbert Lenoir, Barbara L. Weber, Peter Devilee, Douglas F. Easton, David E. Goldgar, and Michael R. Stratton
  1. aCRC Genetic Epidemiology Unit, Strangeways Research Laboratories, University of Cambridge, Cambridge CB1 4RN, United Kingdom; bUnit of Genetic Epidemiology, International Agency for Research on Cancer, 69008 Lyon, France; cSection of Cancer Genetics, Institute of Cancer Research, Sutton, Surrey SM2 5NG, United Kingdom; dDepartment of Human Genetics and Department of Pathology, Leiden University, NL-2333 AA, Leiden, The Netherlands; ewww.kconfab.org; gWestmead Institute for Cancer Research, University of Sydney at Westmead, Millennium Institute, Westmead NSW 2145, Australia; hCentre for Genetic Epidemiology, University of Melbourne, Melbourne 3002, Australia; iDepartment of Hematology–Oncology, University of Utah, Salt Lake City, UT 84132; jFred A Litwin Centre for Cancer Genetics, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, ON, Canada M5G 1X5; kMailman School of Public Health, Columbia University, New York, NY 10032; lFox Chase Cancer Center, Philadelphia, PA 19012; mNorthern California Cancer Center, Union City, CA 94587; nClinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109; oClinical Genetics Service, Department of Medicine, Memorial Sloan–Kettering Cancer Center, New York, NY 10021; pSharett Institute of Oncology, Hebrew University-Hadassah Medical Center, Jerusalem 91120, Israel; qDepartmento de Genetica Humana, Centro Nacional Investigaciones Oncologicas, 28220 Madrid, Spain; rAbramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, PA 19104; sDivision of Molecular Biology, National Cancer Institute, H-1122, Budapest, Hungary; tUnité d'Oncogénétique and Unité INSERM CRI 9502 & EA 2145, Centre Jean-Perrin, 63011 Clermont-Ferrand, France; uDepartamento de Bioquímica, Facultad de Medicina, Universidad Autónoma de Nuevo León, Monterrey, 64460, Mexico; vCancer Genome Project, Sanger Centre, Wellcome Trust Genome Campus, Cambridge CB10 1SA, United Kingdom; wCentre for Research in Women's Health, Women's College Hospital, Toronto, ON, Canada M5G 1N9; xDepartment of Preventive Medicine, Creighton University, Omaha, NE 68178; yCancer Research Campaign Department of Oncology, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 2XZ, United Kingdom; zCancer Genetics and Clinical Oncology, The Royal Marsden NHS Trust, Sutton, Surrey SM2 5PT, United Kingdom; aaDepartment of Clinical Genetics, Erasmus University, 3016 AH, Rotterdam, The Netherlands; bbUnité de Génétique Oncologique, Institut Curie and Unité INSERM U.434, 75248 Paris, France; ccDepartment of Laboratory Medicine and Pathology, Mayo Clinic and Foundation, Rochester, MN 55905; ddWessex Clinical Genetics Service, Princess Ann Hospital, Southampton S016 5YA, United Kingdom; eeRegional Genetic Service, St. Mary's Hospital, Manchester M13 0JH, United Kingdom; and ffDivision of Epidemiology, German Cancer Research Center DFKZ, D-69120 Heidelberg, Germany

See allHide authors and affiliations

PNAS January 22, 2002 99 (2) 827-831; https://doi.org/10.1073/pnas.012584499
Deborah Thompson
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Csilla I. Szabo
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jon Mangion
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rogier A. Oldenburg
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Fabrice Odefrey
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sheila Seal
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rita Barfoot
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Karin Kroeze-Jansema
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dawn Teare
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nazneen Rahman
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hélène Renard
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Graham Mann
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
John L. Hopper
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Saundra S. Buys
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Irene L. Andrulis
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ruby Senie
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mary B. Daly
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dee West
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Elaine A. Ostrander
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ken Offit
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tamar Peretz
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ana Osorio
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
J. Benitez
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Katherine L. Nathanson
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Olga M. Sinilnikova
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Edith Olàh
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yves-Jean Bignon
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Pablo Ruiz
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael D. Badzioch
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hans F. A. Vasen
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrew P. Futreal
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Catherine M. Phelan
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Steven A. Narod
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Henry T. Lynch
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bruce A. J. Ponder
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Ros A. Eeles
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hanne Meijers-Heijboer
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dominique Stoppa-Lyonnet
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Fergus J. Couch
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Diana M. Eccles
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
D. Gareth Evans
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jenny Chang-Claude
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gilbert Lenoir
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Barbara L. Weber
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter Devilee
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Douglas F. Easton
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
David E. Goldgar
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Michael R. Stratton
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  1. Communicated by Albert de la Chapelle, Ohio State University, Columbus, OH (received for review August 10, 2001)

  • Article
  • Figures & SI
  • Info & Metrics
  • PDF
Loading

Abstract

The known susceptibility genes for breast cancer, including BRCA1 and BRCA2, only account for a minority of the familial aggregation of the disease. A recent study of 77 multiple case breast cancer families from Scandinavia found evidence of linkage between the disease and polymorphic markers on chromosome 13q21. We have evaluated the contribution of this candidate “BRCA3” locus to breast cancer susceptibility in 128 high-risk breast cancer families of Western European ancestry with no identified BRCA1 or BRCA2 mutations. No evidence of linkage was found. The estimated proportion (α) of families linked to a susceptibility locus at D13S1308, the location estimated by Kainu et al. [(2000) Proc. Natl. Acad. Sci. USA 97, 9603–9608], was 0 (upper 95% confidence limit 0.13). Adjustment for possible bias due to selection of families on the basis of linkage evidence at BRCA2 did not materially alter this result (α = 0, upper 95% confidence limit 0.18). The proportion of linked families reported by Kainu et al. (0.65) is excluded with a high degree of confidence in our dataset [heterogeneity logarithm of odds (HLOD) at α = 0.65 was −11.0]. We conclude that, if a susceptibility gene does exist at this locus, it can only account for a small proportion of non-BRCA1/2 families with multiple cases of early-onset breast cancer.

Several genes are known to predispose to breast cancer. In the context of large multiple case families, the BRCA1 and BRCA2 genes are numerically the most important, accounting for most families segregating both early-onset breast cancer and ovarian cancer. However, as many as 60% of families with site-specific female breast cancer cannot be explained by BRCA1 and BRCA2 (1, 2). Moreover, population studies have demonstrated that these genes only account for ≈15% of the overall familial risk of breast cancer (3, 4). Even after allowing for other susceptibility genes that confer increased risk in the context of familial cancer syndromes, including TP53 (Li Fraumeni), PTEN (Cowden), and ATM (ataxia telangiectasia), at least 80% of familial breast cancer risk is not explained by known genes, suggesting that other important susceptibility genes remain to be mapped.

Outside the context of these specific syndromes, known genes other than BRCA1/BRCA2 do not appear to account for a substantial proportion of high-risk breast cancer families. Linkage analysis in a set of 56 families with 3 or more cases of breast cancer yielded no evidence for a significant role of PTEN, although an attributable fraction of up to 35% could not be ruled out in a family set of this size (5). However, direct mutation testing of the PTEN gene in a subset of these families has failed to identify any mutations, lending further support to the linkage results indicating that this locus is unlikely to account for a significant fraction of hereditary breast cancer.

To date, few additional candidate breast cancer susceptibility loci have been identified in families not attributable to any of the known genes. A potential susceptibility locus on chromosome 8p12–8p22 was identified through targeted linkage analysis of a region of frequent loss in breast tumors (6, 7). However, our analysis of a larger family series did not support the contribution of a putative gene at this locus to more than a small proportion [HLOD = 0.03, α = 0.03, upper 95% confidence limit (CL) 0.30] of high-risk families (8).

These findings illustrate the difficulties inherent in efforts to identify additional susceptibility genes for a disease with high population prevalence. First, breast cancer is a genetically heterogeneous disease, and it is likely that there are multiple genes remaining to be identified among non-BRCA1/BRCA2 families, with any one accounting only for a small proportion of such families. Second, in moderate-size families with a mixture of cases diagnosed at early and late ages, chance familial clustering of cases may confound linkage-based approaches. Finally, penetrances of additional breast cancer susceptibility genes are likely to be lower than those associated with BRCA1 and BRCA2 (9). Thus, analysis of a large family series with stringent selection criteria is required to achieve sufficient statistical power for unambiguous localization of novel susceptibility loci and meaningful evaluation of candidate genomic regions. To surmount these obstacles, our international collaborative group [Breast Cancer Linkage Consortium (BCLC)] has accrued, and continues to accrue, a collection of families appropriate to address the problem.

Recently, Kainu et al. (10) reported evidence for a novel breast cancer susceptibility locus on chromosome 13q21. They studied 77 families with multiple cases of breast cancer from Finland, Sweden, and Iceland in which no germline BRCA1 or BRCA2 mutations had been identified. Families were not specifically selected for early onset disease, nor were they excluded if one or more cases of ovarian cancer were present.

Initial analysis by comparative genomic hybridization (CGH) of tumors from 23 of these families and 14 others not analyzed further by linkage identified loss of 13q21–31 as a frequent and early event. Consistent loss of 13q21 in all five tumors from one family delineated a minimal region of haplotype sharing in these individuals as the target locus for a susceptibility gene. However, no evidence was presented for specific loss of the wild-type allele in these tumors, as would be expected for the underlying genetic model (inactivation of a tumor suppressor gene).

Genetic linkage analysis using 23 microsatellite markers from this region revealed supportive evidence of linkage to breast cancer. A maximum multipoint HLOD of 3.46 was found at marker D13S1308, with an estimated 65% of families linked. This marker lies ≈25 cM distal to BRCA2 on chromosome 13q. Simulation studies to account for the possible confounding of linkage results by the proximity of these loci indicated that the linkage was unlikely to be the result of unidentified BRCA2 mutations in a subset of families. However, the evidence for linkage was confined to a single pair of tightly linked markers (D13S1308/D13S1296) in this region, with linkage evidence dropping off quite rapidly surrounding this peak; indeed markers flanking a 2.1-cM region surrounding this peak yielded negative two-point LOD scores at recombination fractions up to 20%.

We present results from our attempt to confirm this linkage result through analysis of our series of 128 breast cancer families. In the remainder of this article, we refer to this locus as “BRCA3,” the quotation marks serving to emphasize the uncertainty regarding the existence and location of one or more such susceptibility loci.

Methods

Families.

Families were ascertained from cancer genetics or oncology centers in Europe (United Kingdom, Germany, Spain, Netherlands, France, and Israel), the United States, Australia, and Canada. One family was from Mexico. All families were Caucasian except the Mexican family that was of mixed European–Amerindian descent. Only families in which at least three women were diagnosed with breast cancer under age 60 years were eligible for the study. We excluded families in which cases of either ovarian cancer or male breast cancer were observed, because these phenotypes are strong predictors of BRCA1 or BRCA2 mutations (1). Within these 128 families a total of 650 women were affected with breast cancer (median 5 per family); 56% of these cases were diagnosed under age 50. Samples from 409 affected individuals and 293 unaffected relatives were available for genotyping. Table 1 shows the characteristics of the families in more detail.

View this table:
  • View inline
  • View popup
Table 1

Summary of the families used in the 13q21 analysis

Exclusion of BRCA1 and BRCA2.

At least one breast cancer case from each family was screened for mutations in BRCA1 and BRCA2, including all coding exons and splice junctions; in general, the sampled case with the youngest age at diagnosis was screened. This screening was performed using a variety of methods, including heteroduplex analysis (HDA), conformation sensitive gel electrophoresis (CSGE), and direct sequencing. Families from The Netherlands were also screened for the large genomic rearrangements that are known Dutch founder mutations, as these would not be detected by standard PCR-based screening methods. Other families were also tested for population-specific mutations, where appropriate. Overall, we estimate that, taken together, these methods have an average sensitivity of 0.70 (1, 11).

Genotyping.

Genotyping was carried out at the International Agency for Research on Cancer (62 families), Institute of Cancer Research (49 families), and University of Leiden (17 families). Genotypes were generated for 16 microsatellite markers within a 32-cM region of chromosome 13q21 spanning both BRCA2 and the putative “BRCA3” locus (see Table 2). Not all centers genotyped all markers; Table 2 gives details on which loci were genotyped at each center. Microsatellite repeats were amplified from peripheral blood lymphocyte genomic DNA by standard methods using published primer sequences (The Genome Database, http://gdbwww.gdb.org/). PCR conditions were specific to each genotyping center, as was fragment analysis. Internal consistency of allele sizing was achieved at each center by incorporating samples with known allele sizes on each gel. A common DNA sample (CEPH-1347-02) was typed to ensure consistency of allele sizing between centers. Allele frequencies were calculated separately for each center from the pedigree genotypes by using DOWNFREQ software, Version 1.1 (available through http://linkage.rockefeller.edu/soft/).

View this table:
  • View inline
  • View popup
Table 2

Summary of markers used in the analysis

Statistical Analysis.

We performed standard parametric linkage analyses, essentially identical to our previous analyses of linkage in breast cancer families (e.g., refs. 1, 5, and 8) and to the analysis conducted by Kainu et al. (10). These analyses assume the model of susceptibility to breast cancer based on the segregation analysis of Claus et al. (9). Under this model, susceptibility to breast cancer is conferred by a dominant allele with population frequency of 0.003. The risk of breast cancer by age 80 is assumed to be 0.80 in carriers and 0.08 in noncarriers. Risks are modeled in seven age categories (<30, 30–39, 40–49, 50–59, 60–69, 70–79, and 80+) as described in Easton et al. (12).

Multipoint linkage analyses were carried out using the programs GENEHUNTER (V. 2.0-B; ref. 13), VITESSE (14), and FASTLINK (15). GENEHUNTER was used where possible because it can analyze large numbers of polymorphic loci simultaneously and hence all of the markers we used could be incorporated into a single analysis. However, 33 families were too large to be accommodated by GENEHUNTER without discarding informative individuals. For these families we computed multipoint LOD scores by using either VITESSE (29 families) or FASTLINK (four families with multiple founders). The analyses assumed the intermarker distances as shown in Table 2.

We used the multipoint LOD scores for each family to compute heterogeneity LOD scores, using the standard admixture model, and hence estimated the proportion of families (α) linked to the putative “BRCA3” locus by maximizing the heterogeneity LOD score. A 95% confidence interval for α was derived by computing the values of the heterogeneity LOD score that were within 0.83 (corresponding to a Z value of 1.96) of its maximum value. Ninety-nine percent confidence intervals were also computed.

Because the putative “BRCA3” locus on 13q21 is linked to BRCA2, we performed a further analysis to allow for the possibility that preferential selection for families unlinked to BRCA2 may have biased the results against linkage at “BRCA3.” In this analysis, we computed multipoint heterogeneity LOD scores at the candidate “BRCA3” locus, conditional on the LOD scores at BRCA1 and BRCA2, according to the formula: Math In this formula α1, α2, and α3 are the proportions of families meeting the eligibility criteria that are linked to BRCA1, BRCA2 and “BRCA3,” respectively, and μ is the sensitivity of BRCA1/2 mutation screening. For the purposes of these analyses, α1 and α2 were set to 0.15 and μ to 0.7. LOD1(θ1) and LOD2(θ2) are the LOD scores at BRCA1 and BRCA2, respectively, whereas LOD2;3(θ2) and LOD2;3(θ3) are the LOD scores at BRCA2 and “BRCA3,” respectively, based on markers typed at both loci; LOD2(θ3) is the LOD score for “BRCA3” calculated using only markers at BRCA2. This calculated LOD score is the likelihood for the linkage data at “BRCA3” conditional on the existing linkage and mutation evidence at BRCA1 and BRCA2, and hence corrects (albeit conservatively) for any bias in the “BRCA3” evidence produced by exclusion of families linked to BRCA2.

Results

Total LOD scores were strongly negative throughout the 8-cM interval between D13S153 and D13S1291 (Table 2 and Fig. 1). At the location of “BRCA3” estimated by Kainu et al. (10), D13S1308, the total LOD score was −38.00. Based on the admixture model, the estimated proportion of linked families (α) was 0, with an upper 95% confidence limit of 0.13. The estimated α was also zero for all possible positions in the interval D13S153-D13S1291. Of the 128 families, only four had a multipoint LOD score of greater than 0.5 at D13S1308, the highest of which was 0.67 (one additional family achieved a LOD score of 1.55 at a more distal marker, D13S800). Twelve families achieved LOD scores less than −1 at D13S1308.

Figure 1
  • Download figure
  • Open in new tab
  • Download powerpoint
Figure 1

Multipoint LOD scores for the 128 families analyzed are shown graphically. The solid line represents scores obtained under the assumption of homogeneity; the dashed line assumes the proportion of linked families (α) to be 65%, as estimated by Kainu et al. (10); and the dotted line represents the 95% upper confidence interval (α = 0.13).

We reanalyzed the data conditioning on the genotyping data at BRCA1 and BRCA2. In this analysis the total LOD score was −25.08. In the heterogeneity analysis based on these conditional LOD scores, the estimated proportion of families linked to “BRCA3” was again 0, with an upper 95% confidence limit of 0.18.

In the 95 families that could be analyzed with GENEHUNTER, we also analyzed the data by using the nonparametric method (13) to evaluate haplotype sharing among affected women. Again, no significant evidence of linkage was found (data not shown).

Discussion

Our results clearly conflict with those reported by Kainu et al. (10). Using a set of multiple case female site-specific breast cancer families analyzed for a similar set of markers within the candidate region and subjected to comparable statistical analysis, we found no evidence of linkage to 13q21. The proportion of linked families (65%) reported by Kainu et al. (10) is excluded with a high degree of statistical significance (the heterogeneity LOD score at α = 0.65 was −11.03 in our dataset). This is true even after a conservative correction for possible bias due to potential exclusion of families linked at the BRCA2 locus (conditional LOD at α = 0.65 was −7.64). In addition, under both unconditional and conditional analyses, the estimated proportion of linked families was 0, with upper 95% confidence intervals of 13% and 18%, respectively, indicating that if there is a susceptibility locus on 13q, it is likely to account for only a minority of breast cancer families. The paper of Kainu et al. (10) did not provide confidence limits on their estimated proportion of linked families. However, based on their LOD scores given under homogeneity and 65% heterogeneity, and assuming confidence intervals that are symmetrical about the best estimate, we have estimate a lower 95% confidence limit for α of 0.31. Thus the 95% confidence limits for the two studies do not overlap. Moreover, even when using a more stringent criteria of 99%, the upper confidence limit for our estimated proportion of linked families is 0.19 for the unconditional analysis and 0.26 for the analysis conditioning on BRCA2 markers, further indicating a minor role, if any, for this locus.

There were some differences in selection criteria between the two studies. Our study was restricted to families in which at least three cases of breast cancer were diagnosed below age 60, whereas Kainu et al. (10) included families with three cases diagnosed at any age. Thus, our families may be more heavily selected for genes conferring high risk. It is perhaps noteworthy that the initial hypothesis-generating family analyzed by comparative genomic hybridization (CGH) in Kainu et al. (10) would not have qualified for our study because only two of the five cases were diagnosed under age 60. However, in the subset of 51 families with less than three cases diagnosed under age 50 (Table 1), there is also considerable evidence against linkage to this locus (multipoint LOD = −8.06; HLOD = 0; upper 95% CI for α = 24%; HLOD for α of 65% = −3.57). Thus it is unlikely that difference in age criteria can explain the differences in results between the two studies.

An additional difference in selection criteria was exclusion of families with any cases of ovarian cancer in our series, given the close association of this disease with BRCA1 and BRCA2. Although no BRCA2 mutations were identified in the family set of Kainu et al., the combination of detection methods applied to screening families have detection sensitivities of ≈0.70 (1, 11). Thus, although simulated linkage results allowing for up to 25% of the families in the dataset of Kainu et al. (10) being due to undetected BRCA2 mutations only exceeded the observed maximal lod score in 1 of 3,000 replicates, it is not known to what extent the seven families with ovarian cancer contributed to the observed overall LOD score.

The families in our study were drawn from Western Europe, or in descendent populations in North America and Australia, whereas the families studied by Kainu et al. (10) were from the Nordic countries. Although we have not specifically examined the ethnic origins of each family in our set, it is anticipated that the set of families from the United States and Canada (n = 43) are more ethnically heterogeneous, although most, if not all, are of Western European origin. Only a small minority of all of the families in our set are likely to be of Scandinavian origin, most notably the families ascertained in Minnesota, Seattle, and other parts of the Midwest, which have a high concentration of families descendent from emigrants of Sweden and Norway. One might speculate that the difference in the results observed is due to a population specific founder effect—i.e., an excess of some specific mutation in “BRCA3” in the Nordic populations.

We believe this to be unlikely. The different Nordic populations have different population histories and do not originate from a single small founder population. Although closely related, the Swedish, Icelandic, and (to a lesser extent) Finnish populations are also genetically similar to English and Dutch populations (17). If the observed linkage were due to a susceptibility allele that had reached a high frequency in the Swedish and Finnish populations, this allele would also be expected to occur at a detectable frequency in the British and Dutch families. On the other hand, if the linkage is the result of several different mutations in the candidate “BRCA3” gene, the expectation would be that (as in the case of BRCA1 and BRCA2) mutations would also occur in the British, Dutch, and other populations, albeit the set of mutations might be different. Under either model, we would have expected to observe similar evidence of linkage in our families. Indeed, even when the prevalence of a population specific founder mutation has led to a specific susceptibility gene accounting for the majority of families of a hereditary cancer syndrome [e.g., BRCA2 in the Icelandic population accounting for 61.4% of breast cancer families (18); >50% of hereditary non-polyposis colon cancer (HNPCC) families in the Finnish population attributable to two specific MLH1 mutations (19)], these same genes account for a substantial fraction of families with the same cancer syndrome in other populations [breast cancer reviewed in (20); HNPCC (19)].

We conclude therefore that any contribution of a locus at chromosome 13q21 to familial breast cancer is likely to be small in breast cancer families of European origin. Further linkage studies in large series of multiple case families, or targeted association studies in large series of breast cancer cases and controls, will be needed to identify remaining genes underlying familial aggregation of the disease.

Acknowledgments

We wish to acknowledge the database management support of C. Bonnardel (International Agency for Research on Cancer). We thank Prof. David Anderson (ret.) for having originally collected some of the families used in this study. This study is funded in part by the Cancer Research Campaign (CRC); the Association for International Cancer Research (AICR); the Dutch Cancer Society, The Swiss Bridge Foundation; KConFab is supported by the National Health and Medical Research Council (Australia) and the National Breast Cancer Foundation (Australia). National Institutes of Health Grants CA69446, CA69467, CA69417, CA69631, CA69398, and CA69638 support the Cooperative Family Resource for Breast Cancer Studies (CFRBCS), which is coordinated by Daniela Seminara, Epidemiology Branch, National Cancer Institute, Bethesda, MD. C.M.P. is supported by U.S. Army Grant DAMD17-00-1-0478.

Footnotes

    • ↵f The Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer (KConFab) Consortiom, Australia. Coordinators: Joseph Sambrook, Peter MacCallum Cancer Institute, Melbourne; Georgia Chenevix-Trench, Queensland Institute of Medical Research, Brisbane. Contributors: Ted Edkins, University of West Australia, Perth; John Hopper, Centre for Genetic Epidemiology, University of Melbourne, Melbourne; Graham Mann, Westmead Institute for Cancer Research, Sydney.

    • gg To whom reprint requests should be addressed at: Unit of Genetic Epidemiology, International Agency for Research on Cancer, 150 Cours Albert Thomas, 69008 Lyon, France. E-mail: goldgar{at}iarc.fr.

    Abbreviation

    HLOD,
    heterogeneity logarithm of odds
    • Received August 10, 2001.
    • Accepted November 1, 2001.
    • Copyright © 2002, The National Academy of Sciences

    References

    1. ↵
      1. Ford D,
      2. Easton D F,
      3. Stratton M,
      4. Narod S,
      5. Goldgar D,
      6. Devilee P,
      7. Bishop D T,
      8. Weber B,
      9. Lenoir G,
      10. Chang-Claude J,
      11. et al.
      (1998) Am J Hum Genet 62:334–345, pmid:9463314.
      OpenUrlCrossRefPubMed
    2. ↵
      1. Serova O,
      2. Mazoyer S,
      3. Puget N,
      4. Dubois V,
      5. Tonin P,
      6. Shugart Y,
      7. Goldgar D,
      8. Narod S A,
      9. Lynch H T,
      10. Lenoir G M
      (1997) Am J Hum Genet 60:486–495, pmid:9042907.
      OpenUrlPubMed
    3. ↵
      1. Peto J,
      2. Collins N,
      3. Barfoot R,
      4. Seal S,
      5. Warren W,
      6. Rahman N,
      7. Easton D F,
      8. Evans C,
      9. Deacon J,
      10. Stratton M R
      (1999) J Natl Cancer Inst 91:943–949, pmid:10359546.
      OpenUrlAbstract/FREE Full Text
    4. ↵
      1. Anglian Breast Cancer Study Group
      (2000) Br J Cancer 83:1301–1308, pmid:11044354.
      OpenUrlCrossRefPubMed
    5. ↵
      1. Shugart Y Y,
      2. Cour C,
      3. Renard H,
      4. Lenoir G,
      5. Goldgar D,
      6. Teare D,
      7. Easton D,
      8. Rahman N,
      9. Gusterton R,
      10. Seal S,
      11. et al.
      (1999) J Med Genet 36:720–721, pmid:10507734.
      OpenUrlFREE Full Text
    6. ↵
      1. Kerangueven F,
      2. Essioux L,
      3. Dib A,
      4. Noguchi T,
      5. Allione F,
      6. Geneix J,
      7. Longy M,
      8. Lidereau R,
      9. Eisinger F,
      10. Pebusque M J,
      11. et al.
      (1995) Oncogene 10:1023–1026, pmid:7898921.
      OpenUrlPubMed
    7. ↵
      1. Seitz S,
      2. Rohde K,
      3. Bender E,
      4. Nothanagel A,
      5. Kolble K,
      6. Schlag P M,
      7. Scherneck S
      (1997) Oncogene 14:741–743, pmid:9038382.
      OpenUrlCrossRefPubMed
    8. ↵
      1. Rahman N,
      2. Teare M D,
      3. Seal S,
      4. Renard H,
      5. Mangion J,
      6. Cour C,
      7. Thompson D,
      8. Shugart Y,
      9. Eccles D,
      10. Devilee P,
      11. et al.
      (2000) Oncogene 19:4170–4173, pmid:10962578.
      OpenUrlCrossRefPubMed
    9. ↵
      1. Claus E B,
      2. Risch N,
      3. Thompson W D
      (1991) Am J Hum Genet 48:232–242, pmid:1990835.
      OpenUrlPubMed
    10. ↵
      1. Kainu T,
      2. Jou S-H,
      3. Desper R,
      4. Schäffer A A,
      5. Gillanders E,
      6. Rozenblum E,
      7. Freas-Lutz D,
      8. Weaver D,
      9. Stephan D,
      10. Bailey-Wilson J,
      11. et al.
      (2000) Proc Natl Acad Sci USA 97:9603–9608, pmid:10944226.
      OpenUrlAbstract/FREE Full Text
    11. ↵
      1. Eng C,
      2. Brody L C,
      3. Wagner T M,
      4. Devilee P,
      5. Vijg J,
      6. Szabo C,
      7. Tavtigian S V,
      8. Nathanson K L,
      9. Ostrander E,
      10. Frank T S
      (2001) J Med Genet 38:824–833, pmid:11748305.
      OpenUrlAbstract/FREE Full Text
    12. ↵
      1. Easton D F,
      2. Bishop D T,
      3. Ford D,
      4. Crockford G P,
      5. the Breast Cancer Linkage Consortium
      (1993) Am J Hum Genet 52:678–701, pmid:8460634.
      OpenUrlPubMed
    13. ↵
      1. Kruglyak L,
      2. Daly M,
      3. Reeve-Daly M P,
      4. Lander E S
      (1995) Am J Hum Genet 58:1347–1363.
      OpenUrl
    14. ↵
      1. O'Connell J R,
      2. Weeks D E
      (1995) Nat Genet 11:402–408, pmid:7493020.
      OpenUrlCrossRefPubMed
    15. ↵
      1. Cottingham RW Jr,
      2. Idury R M,
      3. Schaffer A A
      (1993) Am J Hum Genet 53:252–263, pmid:8317490.
      OpenUrlPubMed
      1. Terwilliger J D,
      2. Shannon W D,
      3. Lathrop G M,
      4. Nolan J P,
      5. Goldin L R,
      6. Chase G A,
      7. Weeks D E
      (1997) Am J Hum Genet 61:430–438, pmid:9311749.
      OpenUrlPubMed
    16. ↵
      1. Cavalli-Sforza L L,
      2. Menozzi P,
      3. Piazza A
      (1994) The History and Geography of Human Genes (Princeton Univ. Press, Princeton, NJ).
    17. ↵
      1. Thorlacius S,
      2. Olafsdottir G,
      3. Tryggvadottir L,
      4. Neuhausen S,
      5. Jonasson J G,
      6. Tavtigian S V,
      7. Tulinius H,
      8. Ogmundsdotti r H M,
      9. Eyfjord J E
      (1996) Nat Genet 13:117–119, pmid:8673089.
      OpenUrlCrossRefPubMed
    18. ↵
      1. Holmberg M,
      2. Kristo P,
      3. Chadwicks R B,
      4. Mecklin J P,
      5. Jarvinen H,
      6. de la Chapelle A,
      7. Nystrom-Lahti M,
      8. Peltomaki P
      (1998) Hum Mut 11:482, pmid:10200055.
      OpenUrlPubMed
    19. ↵
      1. Szabo C I,
      2. King M C
      (1997) Am J Hum Genet 60:1013–1020, pmid:9150148.
      OpenUrlPubMed
    PreviousNext
    Back to top
    Article Alerts
    Email Article

    Thank you for your interest in spreading the word on PNAS.

    NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

    Enter multiple addresses on separate lines or separate them with commas.
    Evaluation of linkage of breast cancer to the putative BRCA3 locus on chromosome 13q21 in 128 multiple case families from the Breast Cancer Linkage Consortium
    (Your Name) has sent you a message from PNAS
    (Your Name) thought you would like to see the PNAS web site.
    CAPTCHA
    This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
    Citation Tools
    Evaluation of linkage of breast cancer to the putative BRCA3 locus on chromosome 13q21 in 128 multiple case families from the Breast Cancer Linkage Consortium
    Deborah Thompson, Csilla I. Szabo, Jon Mangion, Rogier A. Oldenburg, Fabrice Odefrey, Sheila Seal, Rita Barfoot, Karin Kroeze-Jansema, Dawn Teare, Nazneen Rahman, Hélène Renard, KConFab Consortiumef, Graham Mann, John L. Hopper, Saundra S. Buys, Irene L. Andrulis, Ruby Senie, Mary B. Daly, Dee West, Elaine A. Ostrander, Ken Offit, Tamar Peretz, Ana Osorio, J. Benitez, Katherine L. Nathanson, Olga M. Sinilnikova, Edith Olàh, Yves-Jean Bignon, Pablo Ruiz, Michael D. Badzioch, Hans F. A. Vasen, Andrew P. Futreal, Catherine M. Phelan, Steven A. Narod, Henry T. Lynch, Bruce A. J. Ponder, Ros A. Eeles, Hanne Meijers-Heijboer, Dominique Stoppa-Lyonnet, Fergus J. Couch, Diana M. Eccles, D. Gareth Evans, Jenny Chang-Claude, Gilbert Lenoir, Barbara L. Weber, Peter Devilee, Douglas F. Easton, David E. Goldgar, Michael R. Stratton
    Proceedings of the National Academy of Sciences Jan 2002, 99 (2) 827-831; DOI: 10.1073/pnas.012584499

    Citation Manager Formats

    • BibTeX
    • Bookends
    • EasyBib
    • EndNote (tagged)
    • EndNote 8 (xml)
    • Medlars
    • Mendeley
    • Papers
    • RefWorks Tagged
    • Ref Manager
    • RIS
    • Zotero
    Request Permissions
    Share
    Evaluation of linkage of breast cancer to the putative BRCA3 locus on chromosome 13q21 in 128 multiple case families from the Breast Cancer Linkage Consortium
    Deborah Thompson, Csilla I. Szabo, Jon Mangion, Rogier A. Oldenburg, Fabrice Odefrey, Sheila Seal, Rita Barfoot, Karin Kroeze-Jansema, Dawn Teare, Nazneen Rahman, Hélène Renard, KConFab Consortiumef, Graham Mann, John L. Hopper, Saundra S. Buys, Irene L. Andrulis, Ruby Senie, Mary B. Daly, Dee West, Elaine A. Ostrander, Ken Offit, Tamar Peretz, Ana Osorio, J. Benitez, Katherine L. Nathanson, Olga M. Sinilnikova, Edith Olàh, Yves-Jean Bignon, Pablo Ruiz, Michael D. Badzioch, Hans F. A. Vasen, Andrew P. Futreal, Catherine M. Phelan, Steven A. Narod, Henry T. Lynch, Bruce A. J. Ponder, Ros A. Eeles, Hanne Meijers-Heijboer, Dominique Stoppa-Lyonnet, Fergus J. Couch, Diana M. Eccles, D. Gareth Evans, Jenny Chang-Claude, Gilbert Lenoir, Barbara L. Weber, Peter Devilee, Douglas F. Easton, David E. Goldgar, Michael R. Stratton
    Proceedings of the National Academy of Sciences Jan 2002, 99 (2) 827-831; DOI: 10.1073/pnas.012584499
    del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
    • Tweet Widget
    • Facebook Like
    • Mendeley logo Mendeley
    Proceedings of the National Academy of Sciences: 99 (2)
    Table of Contents

    Submit

    Sign up for Article Alerts

    Jump to section

    • Article
      • Abstract
      • Methods
      • Results
      • Discussion
      • Acknowledgments
      • Footnotes
      • Abbreviation
      • References
    • Figures & SI
    • Info & Metrics
    • PDF

    You May Also be Interested in

    Water from a faucet fills a glass.
    News Feature: How “forever chemicals” might impair the immune system
    Researchers are exploring whether these ubiquitous fluorinated molecules might worsen infections or hamper vaccine effectiveness.
    Image credit: Shutterstock/Dmitry Naumov.
    Reflection of clouds in the still waters of Mono Lake in California.
    Inner Workings: Making headway with the mysteries of life’s origins
    Recent experiments and simulations are starting to answer some fundamental questions about how life came to be.
    Image credit: Shutterstock/Radoslaw Lecyk.
    Cave in coastal Kenya with tree growing in the middle.
    Journal Club: Small, sharp blades mark shift from Middle to Later Stone Age in coastal Kenya
    Archaeologists have long tried to define the transition between the two time periods.
    Image credit: Ceri Shipton.
    Illustration of groups of people chatting
    Exploring the length of human conversations
    Adam Mastroianni and Daniel Gilbert explore why conversations almost never end when people want them to.
    Listen
    Past PodcastsSubscribe
    Panda bear hanging in a tree
    How horse manure helps giant pandas tolerate cold
    A study finds that giant pandas roll in horse manure to increase their cold tolerance.
    Image credit: Fuwen Wei.

    Similar Articles

    Site Logo
    Powered by HighWire
    • Submit Manuscript
    • Twitter
    • Facebook
    • RSS Feeds
    • Email Alerts

    Articles

    • Current Issue
    • Special Feature Articles – Most Recent
    • List of Issues

    PNAS Portals

    • Anthropology
    • Chemistry
    • Classics
    • Front Matter
    • Physics
    • Sustainability Science
    • Teaching Resources

    Information

    • Authors
    • Editorial Board
    • Reviewers
    • Subscribers
    • Librarians
    • Press
    • Cozzarelli Prize
    • Site Map
    • PNAS Updates
    • FAQs
    • Accessibility Statement
    • Rights & Permissions
    • About
    • Contact

    Feedback    Privacy/Legal

    Copyright © 2021 National Academy of Sciences. Online ISSN 1091-6490