FREE NEJM E-TOC    HOME   |   SUBSCRIBE   |   CURRENT ISSUE   |   PAST ISSUES   |   COLLECTIONS   |   Search Term  Advanced Search

Sign in | Get NEJM's E-Mail Table of Contents — Free | Subscribe

Previous Volume 348:2339-2347 June 5, 2003 Number 23 Next

PDF PDA Full Text Letters Add to Personal Archive Add to Citation Manager Notify a Friend E-mail When Cited E-mail When Letters Appear PubMed Citation

Despite years of intensive study and substantial progress in understanding susceptibility to breast and ovarian cancer, these diseases remain important causes of death in women. However, several recent critical advances — sequencing of the human genome and the development of high-throughput techniques for identifying DNA-sequence variants, changes in copy numbers, and global expression profiles — have dramatically accelerated the pace of research aimed at preventing and curing these diseases. We review some of the important discoveries in the genetics of breast and ovarian cancer, ongoing studies to isolate additional susceptibility genes, and early work on molecular profiling involving microarrays.

Susceptibility to Breast and Ovarian Cancer

In the United States, 10 to 20 percent of patients with breast cancer and patients with ovarian cancer have a first- or second-degree relative with one of these diseases.¹ Two major genes associated with susceptibility to breast and ovarian cancer — breast cancer susceptibility gene 1 (BRCA1) and breast cancer susceptibility gene 2 (BRCA2) — have been identified to date.^2,3 Mutations in either of these genes confer a lifetime risk of breast cancer of between 60 and 85 percent and a lifetime risk of ovarian cancer of between 15 and 40 percent.^4,5 However, mutations in these genes account for only 2 to 3 percent of all breast cancers,^6,7 and susceptibility alleles in other genes, such as TP53, PTEN, and STK11/LKB1, are even less common causes of breast and ovarian cancer (Figure 1).

View larger version (4K): [in this window] [in a new window]   Figure 1. The Genetics of Breast Cancer. BRCA1 and BRCA2 mutations occur in approximately 20 percent of families with evidence of inherited susceptibility to breast cancer. Germ-line mutations in TP53 cause the Li–Fraumeni syndrome and account for no more than 1 percent of cases of familial breast cancer, but women who survive the childhood cancers associated with the Li–Fraumeni syndrome have as much as a 90 percent risk of breast cancer.8 Mutations in the cell-cycle–checkpoint kinase gene (CHEK2) account for about 5 percent of all cases of familial breast cancer (defined by the diagnosis of breast cancer in two or more family members before the age of 60 years), but the risk for individual mutation carriers is probably less than 20 percent.9 All other cases of breast cancer are presumed to be due to an undefined number of additional susceptibility genes with various degrees of penetrance, exposure to hormonal and environmental factors, and stochastic genetic events.

 
The prediction that there are common DNA-sequence variants that confer a small but appreciable enhanced risk of cancer has been validated with the recent discovery of the 1100delC mutation in the cell-cycle–checkpoint kinase gene (CHEK2).⁹ This mutation was found in 1.1 percent of women without breast cancer, 1.4 percent of women with a personal but no family history of breast cancer, and 4.2 percent of index patients from 718 families in which two or more members had been given a diagnosis of breast cancer before the age of 60 years but in which there was no detectable BRCA1 or BRCA2 mutation. This mutation doubles the risk of breast cancer among women and increases the risk among men by a factor of 10. CHEK2, an important component of the cellular machinery that recognizes and repairs damaged DNA, is activated after phosphorylation by the checkpoint gene ATM and in turn activates BRCA1. The role of ATM mutations in the predisposition to the early onset of breast cancer remains controversial, but some missense mutations do appear to increase susceptibility to breast cancer in humans¹⁰ and mice.¹¹

There is convincing evidence that additional high-penetrance genes that increase susceptibility to breast cancer exist. In contrast, it has been suggested that, other than BRCA1 and BRCA2, high-penetrance genes that confer susceptibility to ovarian cancer do not exist.¹² An ovarian-cancer–susceptibility locus on chromosome 3p22–25 has putatively been identified, but this finding has yet to be confirmed by an independent group.¹³

Many additional genetic variants in low-penetrance susceptibility alleles may moderately increase the risk of breast cancer, ovarian cancer, or both. These genetic variants are much more common in the population than are high-penetrance gene mutations and, thus, in aggregate may make a substantially greater contribution to breast and ovarian cancer in the population than mutations in high-risk genes.¹⁴ However, genetic heterogeneity and the rarity of high-penetrance genes make both high- and low-penetrance genes difficult to identify.

Identification of Genes That Increase Susceptibility to Breast and Ovarian Cancer

Identification of High-Penetrance Genes

Genetic linkage was used to identify the BRCA1 and BRCA2 loci on chromosomes 17q and 13q, respectively.^15,16 In both cases, no information was initially available on the location, structure, or function of the genes, and they were identified through positional cloning. Loss-of-heterozygosity mapping was of little assistance in either search; however, a homozygous deletion on chromosome 13 in a pancreatic adenocarcinoma helped identify the location of BRCA2.¹⁷ Finally, critical data in the search for BRCA2 came from studies of breast cancer in Iceland, whose population derives from a small group of settlers from Norway and Ireland.^18,19 Such populations share more genetic information than large, admixed populations and have been used successfully many times in gene mapping.²⁰ After the BRCA1 locus was identified, it took almost four years to isolate the gene and involved several labor-intensive strategies.² By contrast, the BRCA2 locus was one of the first genomic intervals to be systematically sequenced as part of the Human Genome Project. These data, together with other information about the genes in the region, reduced the time it took to isolate BRCA2 to two years.³ Thus, information from the human genome sequence greatly enhances the utility of linkage analysis for gene identification (Figure 2).

View larger version (21K): [in this window] [in a new window]   Figure 2. Effect of Sequencing the Human Genome on Gene-Discovery Strategies. The annotated DNA sequence of the human genome can be used to locate genes, repeat sequences, and other features and has revolutionized the identification of cancer genes. A sequence without annotation is of limited utility (Panel A). As shown in Panel B, an annotated sequence shows genetic markers such as CA and GT repeats along with other data, such as CpG islands, known genes, genes predicted to exist on the basis of computational models, and Basic Local Alignment Search Tool (BLAST) matches. Using publicly available data (http://www.ensembl.org, http://www.ncbi.nlm.nih.gov, and http://www.genome.ucsc.edu), it is possible to jump from a genetic region of interest to the identification of candidate genes in a matter of seconds and download the relevant data (Panel C). With these data in hand, experiments, such as those involving the polymerase chain reaction (PCR), can be designed to analyze the genes for mutations (Panel D). The final step in the identification of genes is to compare the sequence from patients with the disease of interest with the normal reference sequence to discover the mutations (Panel E).

 
BRCA3 and beyond

Several candidate regions for BRCA3 have been proposed, including chromosome 13q21²¹ and chromosome 8p12–22,²² but both have been strongly refuted by analysis of data from independent families.^23,24 The search for BRCA3 has been difficult for several reasons. First, ovarian cancer and male breast cancer were recognized as components of syndromes of breast-cancer susceptibility before either BRCA1 or BRCA2 was isolated, allowing targeted identification of affected families. Since no such phenotype has been associated with the putative BRCA3 gene or genes, families in current studies are selected only on the basis of a young age at the diagnosis of breast cancer and the absence of ovarian and male breast cancer. Ideally, these families should have multiple members with early-onset breast cancer and strong evidence against the involvement of either BRCA1 or BRCA2. However, the breast cancers in most such families are in fact due to germ-line mutations in BRCA1 or BRCA2,²⁵ and those that are not may represent the effects of multiple susceptibility alleles (genetic heterogeneity), reducing the power of linkage analysis. What is needed to further this effort are larger families to increase the statistical power of such studies, as well as novel means of clustering families into subgroups most likely to represent single-gene disorders.

One approach is to classify families with breast cancer according to the molecular profile of the associated tumors. These analyses could be based either on expression profiling or on array-based comparative genomic hybridization, both of which provide unique molecular signatures (Figure 3). Nonetheless, hundreds of small pedigrees may be needed to identify the BRCA3 locus.

View larger version (32K): [in this window] [in a new window]   Figure 3. Array-Based Comparative Genomic Hybridization. In Panel A, bacterial artificial chromosome clones or complementary DNAs are placed on glass slides at high density; tumor and normal DNA are labeled with CY3 and CY5, respectively; and the combined probe is hybridized to the array. The array is analyzed with use of a laser scanner that reads each color channel individually and then calculates an intensity ratio for each spot. In Panel B, spots with intensity ratios greater than 1.25 (green spots) represent increases in copy number (amplification), and those with intensity ratios of less than 0.75 (red spots) represent decreases in copy number (deletion). Each spot is a DNA segment that can be linked directly to the human genome sequence (Panel C), thus defining changes in the number of copies of a specific gene. In Panel D, the plotting of intensity ratios for the chromosome 9 bacterial artificial chromosome clones on the array in linear order identifies a homozygous loss of CDKN2A in a melanoma cell line.

 
Use of the Human Genome Sequence to Identify Low-Penetrance Genes

As noted, the susceptibility genes identified to date are not responsible for most breast and ovarian cancers, leaving a considerable potential contribution from less penetrant genes. One of the implicit problems in isolating low-penetrance genes is that such genes will rarely produce striking familial patterns involving multiple cases that can be used in traditional linkage studies. An additional concern is that very large studies, with statistical power to evaluate multiple interactions between genes, may be needed before genetic profiles involving this class of genes can be used for risk prediction.¹⁴ As the computational methods for finding coding sequences embedded in a sequence of genomic DNA become increasingly powerful, the value of the human genome sequence as a tool for identifying unknown genes also increases. These algorithms for finding genes have largely replaced laborious experimental techniques to identify potential coding sequences of unknown genes for mutation analysis within linkage regions. These methods are another illustration of the fact that it is the annotation of the genomic sequence (i.e., the identification of genes and their function) that brings the sequence to life. Annotation parses the sequence into genes and noncoding regions. By including genomic features such as CpG islands, which mark the promoter regions of many genes, annotations produce a complete rendering of each sequence. Annotated sequences are publicly available in several data bases (http://www.ensembl.org, http://www.ncbi.nlm.nih.gov, and http://www.genome.ucsc.edu) with associated genome browsers.

The depth and value of annotation have also grown through the addition of millions of single-nucleotide polymorphisms, which are invaluable in the search for susceptibility genes.²⁶ One such example is the recent demonstration that a silent single-nucleotide polymorphism in LIG4, a gene encoding a DNA ligase important in the repair of breaks in double-stranded DNA, is associated with survival among patients with breast cancer.²⁷ This effect was demonstrated in a British population-based study that included 2430 cases of breast cancer. DNA from these patients was genotyped for polymorphisms in 22 DNA-repair, hormone-metabolism, carcinogen-metabolism, and other genes, and the effect of each single-nucleotide polymorphism on the outcome was assessed by Cox regression analysis. The silent polymorphism D501D (t>c) in LIG4 had the largest effect. The estimated hazard ratio for death among patients homozygous for the polymorphism, as compared with those homozygous for the wild-type sequence, was 4.0 (95 percent confidence interval, 2.1 to 7.7; P=0.002), and this effect remained significant after stratification according to tumor stage, grade, and type (hazard ratio, 4.2; 95 percent confidence interval, 1.8 to 9.4; P=0.01). The inclusion of these single-nucleotide polymorphisms in the annotation of the human genome sequence greatly facilitated this analysis, which would otherwise have had to have been preceded by an extensive sequence-based effort to identify single-nucleotide polymorphisms.

Whole-Genome Approaches to the Analysis of Breast and Ovarian Cancer

Many genomic approaches to the identification of cancer genes are based on microarray techniques. For gene-expression profiling, each element usually represents one gene and is created with the use of a complementary DNA (cDNA) or oligonucleotide for the gene in question. Similar arrays have been produced with large genomic clones for array-based comparative genomic hybridization to identify changes in the number of copies of DNA. This approach replaced lower-resolution comparative genomic hybridization of cells in metaphase and provides a direct link to genes in the altered region (Figure 3).

A comparative genomic hybridization can be used to identify the loss of one or both copies of a given gene as well as regions of amplification. Arrays made with cDNAs can be used for expression profiling and comparative genomic hybridization simultaneously.²⁸ This approach allows a direct comparison between the number of copies of a gene and the level of expression of that gene, but the results of comparative genomic hybridization may be variable, presumably because the cDNA sequence and the genomic sequence are not collinear. However, the alternative approach of using large cloned segments of genomic DNA in the bacterial artificial chromosomes consistently provides excellent data.²⁹ The genomic clones can be spaced evenly across the genome, and the array set can be enriched with selected clones that contain candidate cancer genes to enhance resolution. The use of DNA microarrays has been suggested for other applications; however, epigenetic changes such as changes in DNA methylation, which are likely to be a critical component in the development of cancer, have been notoriously difficult to assay regardless of the format.

The power of a comparative genomic hybridization was recently demonstrated by Albertson and colleagues, who used this approach to map the recurrent breast-cancer amplicon at chromosome 20q12.3.³⁰ This approach clearly demonstrated that what had previously been described as a single amplicon was, in fact, two distinct amplicons, one containing the putative oncogene ZNF217³¹ and the other containing CYP24, which encodes vitamin D24-hydroxylase.³² The overexpression of this enzyme alters the control of growth mediated by vitamin D. There were two distinct peaks of high copy numbers within this 2-Mb region, with a gene at the peak of each amplicon. The ability of comparative genomic hybridization to show peaks in increases in copy numbers across regions of recurrent abnormality at high resolution is very useful for locating oncogenes in many human cancers.

Much less advanced, but critically important, are techniques involving proteomics, which examine the entire complement of proteins expressed in a specific tissue or cell. The information supplied complements that provided by a comparative genomic hybridization, expression profiling, and screening for mutations in cancer research,³³ since the genetic code does not indicate which proteins are expressed, in what quantity, and in what form. For example, post-translational modifications, such as phosphorylation or glycosylation, may determine the function or stability of a protein and are not detected by transcriptional analyses. Many differences between normal tissue and malignant tumors are due to post-translational modifications, and a complete analysis of the cancer phenotype will require a whole-proteome approach.

Diffuse large -cell lymphoma was the first human cancer to undergo gene-expression profiling, and a microarray containing 17,800 cDNAs was used.³⁴ Breast and ovarian cancer have now been subjected to molecular profiling as well. In the first such study, Perou and colleagues used a cDNA microarray containing 8000 genes to assay 65 breast-biopsy specimens, primarily invasive breast cancers.³⁵ Perhaps not surprisingly, estrogen-receptor status was a key predictor of the outcome and treatment response, with estrogen-receptor and coregulated genes being the primary elements needed for these tumors to cluster. In addition, a profile of tumors that overexpress ERBB2 was easily identifiable. Thus, the primary clusters recognized were tumors that expressed estrogen receptor and had a luminal-cell pattern of gene expression, tumors that did not express estrogen receptor and had a myoepithelial-cell pattern of expression, tumors that overexpressed ERBB2, and a fourth group of tumors that clustered with normal breast tissue. More recently, Hedenfalk and colleagues suggested that transcriptional profiling can also accurately differentiate breast cancers with underlying germ-line mutations in BRCA1 or BRCA2 from those without such mutations, an advance that could facilitate the identification of high-risk families on the basis of molecular phenotyping, as well as identify characteristic molecular differences that may be useful clinical targets for directed therapy.³⁶

Ovarian cancers have been subjected to transcriptional profiling with similar results. In one series, 27 serous papillary ovarian cancers and 3 samples of normal ovarian tissue underwent gene-expression profiling with oligonucleotide-based arrays representing more than 6000 human genes.³⁷ Normal ovarian tissue was clearly distinguishable from malignant tissues, and three types of tumors were identified. The first subtype clustered with normal tissue and was well differentiated on conventional histologic analyses. The second group was characterized by the expression of genes from admixed stromal cells and infiltrating lymphocytes. Although this profile could represent a random admixture of cell types, it could also represent an immune response to the tumor, as suggested recently by Zhang and colleagues.³⁸ The third group of tumors had a high level of expression of cell-cycle–associated genes, most likely reflecting a high proliferative rate. More than half the tumors in this cluster were poorly differentiated on histologic analysis. Which of the differentially expressed genes in this and other series represent the root causes of malignant transformation rather than markers of progression is not known but must be determined in order to distinguish diagnostic markers from therapeutic targets.

Microarrays have also been used to show how an expression profile can change as cancer cells develop resistance to doxorubicin-based therapy.³⁹ In these experiments, a set of genes that were transiently overexpressed after initial exposure to doxorubicin included a subgroup of genes that became constitutively overexpressed as resistance to doxorubicin developed. These experiments, although just the beginning of what will be a fundamental change in molecular oncology owing to the deciphering of the human genome sequence, demonstrate the power of this approach.

In perhaps the most extensive and informative study to date, the expression profiles of 117 primary breast cancers were compared with known prognostic markers and the clinical outcome at least five years after diagnosis.⁴⁰ Expression profiling with the use of 25,000 genes separated the tumors into two groups, one in which distant metastases developed in 34 percent at five years and one in which metastases developed in 70 percent at five years. From the original 25,000 genes in the array, 70 were identified as having the greatest accuracy in predicting recurrent disease. When the tumors were sorted on the basis of this smaller set of genes, fewer than 10 percent of the tumors in the poor-prognosis group were misclassified. A comparative multivariate analysis using clinical prognostic factors that included tumor grade, tumor size, the presence or absence of angiolymphatic invasion, patients' age, and tumor estrogen-receptor status demonstrated that as compared with the good-prognosis gene-expression signature, the poor-prognosis microarray profile was an independent predictor of recurrence, with an odds ratio of 18 (95 percent confidence interval, 3 to 94). This approach has now been tested in 295 consecutive patients with stage I or II breast cancer.⁴¹ Of these, 180 had the poor-prognosis profile and 115 had the good-prognosis profile. Ten years after the diagnosis of breast cancer, the probability of remaining free of metastases was 51 percent among women with a poor-prognosis profile and 85 percent among those with a good-prognosis profile. These data provide compelling evidence that the genetic program of a cancer cell at diagnosis defines its biologic behavior many years later, refuting a competing hypothesis that the genetic changes driving the development of metastatic disease are acquired in residual cells after adjuvant treatment.

Clinical Management of Inherited Susceptibility to Breast and Ovarian Cancer

Several computational models have been developed to predict an individual woman's risk of breast cancer, including one in which family history is the predominant risk factor. This model, developed by Claus and colleagues and published as a series of tables clinicians can use,⁴² is based on the number and degree of relatedness of family members with breast cancer and their age at diagnosis. However, this model does not provide estimates of the likelihood that an individual woman will have a germ-line mutation in BRCA1 or BRCA2. Several studies have identified factors that are associated with an increased likelihood that a BRCA1 or BRCA2 mutation will be identified, including early-onset breast cancer, the occurrence of breast and ovarian cancer in the same woman, a history of male family members with breast cancer, and Ashkenazi Jewish ancestry. These characteristics have also been included in predictive models designed for use by clinicians.^43,44,45

Testing for germ-line mutations in BRCA1 and BRCA2 is an important tool for predicting the risk of breast cancer and developing management strategies. Once such mutations are identified, we recommend that the woman choose between annual screening mammography and prophylactic mastectomy, which significantly reduced the risk of breast cancer in a small, retrospective study of mutation carriers.⁴⁶ We recommend that women who choose surveillance also investigate the possibility of participating in a clinical trial evaluating the utility of magnetic resonance imaging for screening high-risk women. Several studies have shown that in women with germ-line BRCA1 and BRCA2 mutations, breast cancers are likely to occur as interval cancers⁴⁷ and that standard mammograms are more likely to be negative than in women at low or moderate risk.^48,49,50

With respect to the risk of ovarian cancer among carriers of BRCA1 and BRCA2 mutations, we strongly recommend that such women undergo prophylactic oophorectomy as soon as they have completed childbearing, since no surveillance regimen to date has been shown to decrease the percentage of women who receive a diagnosis of advanced disease. Among mutation carriers, this procedure has been shown to reduce the risk of breast and ovarian cancer by more than 60 percent and 95 percent, respectively.^51,52 Again, although no prospective data are available, we recommend that these women receive hormone-replacement therapy until the age of 50 years, approximately the time of natural menopause. Although extending exposure to estrogens beyond the age of 50 years has been associated with a small increase in the risk of breast cancer, these younger women would be producing endogenous estrogens in the absence of prophylactic oophorectomy. The addition of hormone-replacement therapy makes this choice acceptable to women who would otherwise refuse it because of concern about premature menopause, and the risk–benefit ratio is strongly in favor of oophorectomy, with or without hormone-replacement therapy.

The use of tamoxifen to prevent breast cancer in carriers of BRCA1 and BRCA2 mutations remains controversial. One retrospective study suggested that adjuvant tamoxifen therapy in carriers of BRCA1 and BRCA2 mutations with estrogen-receptor–positive breast cancer reduced the risk of contralateral breast cancers by the same amount as that in unselected patients with breast cancer.⁵³ However, data showing that most BRCA1-associated breast cancers are negative for estrogen receptors⁵⁴ and recent data from the Breast Cancer Prevention Trial (BCPT) of the National Surgical Adjuvant Breast and Bowel Project have led to widespread speculation that tamoxifen will not prevent breast cancer in women with germ-line BRCA1 mutations.⁵⁵ It is important to consider that all available data suggest that endogenous exposure to hormones has a central role in defining the risk of cancer among carriers of BRCA1 mutations, that breast cancer developed in only eight carriers of BRCA1 mutations in the BCPT, and that the lack of a preventive effect of tamoxifen was statistically insignificant (odds ratio, 1.67; 95 percent confidence interval, 0.41 to 8.00). The length of treatment in the BCPT is also consistent with an early treatment effect, rather than true prevention, which, given the preponderance of estrogen-receptor–negative tumors among carriers of BRCA1 mutations, would produce the data seen in this study. Thus, we recommend that carriers of BRCA1 mutations consider taking tamoxifen once they discontinue hormone-replacement therapy at about the age of 50 years.

Summary

The past decade has been a period of unparalleled discovery in the field of the genetics and genomics of breast and ovarian cancer. Two major susceptibility genes have been isolated, and subsequent work provided sufficient management information to allow genetic testing for BRCA1 and BRCA2 mutations to become a part of routine practice in many clinical centers. In addition, work has begun on the characterization of genetic variants that, although associated with a lower risk of cancer than germ-line BRCA1 and BRCA2 mutations, are far more common in the population and thus may have a substantial role in defining the risk of cancer. Finally, gene-expression profiling, coupled with the sequencing of most or all of the genes in the human genome, is revolutionizing the study of the biology and the molecular classification of breast and ovarian cancer. Combined with data from projects conducting a genome-wide mutation analysis of all genes implicated in the development of cancer, the importance of which has just been illustrated with the discovery that more than 60 percent of melanomas have mutations in BRAF (v-raf murine sarcoma viral oncogene homologue B1),⁵⁶ and progress in developing effective preventive measures, a marked reduction in mortality from breast and ovarian cancer is a realistic goal for the next decade.

Source Information

From the Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom (R.W.); and the University of Pennsylvania, Philadelphia (B.L.W.).

References

1. Madigan MP, Ziegler RG, Benichou J, Byrne C, Hoover RN. Proportion of breast cancer cases in the United States explained by well-established risk factors. J Natl Cancer Inst 1995;87:1681-1685.
2. Miki Y, Swensen J, Shattuck-Eidens D, et al. A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science 1994;266:66-71.
3. Wooster R, Bignell G, Lancaster J, et al. Identification of the breast cancer susceptibility gene BRCA2. Nature 1995;378:789-792. [Erratum, Nature 1996;379:749.]
4. Brose MS, Rebbeck TR, Calzone KA, Stopfer JE, Nathanson KL, Weber BL. Cancer risk estimates for BRCA1 mutation carriers identified in a risk evaluation program. J Natl Cancer Inst 2002;94:1365-1372.
5. Thompson D, Easton DF. Cancer incidence in BRCA1 mutation carriers. J Natl Cancer Inst 2002;94:1358-1365.
6. Newman B, Millikan RC, King MC. Genetic epidemiology of breast and ovarian cancers. Epidemiol Rev 1997;19:69-79.
7. Ford D, Easton DF, Peto J. Estimates of the gene frequency of BRCA1 and its contribution to breast and ovarian cancer incidence. Am J Hum Genet 1995;57:1457-1462.
8. Garber JE, Goldstein AM, Kantor AF, Dreyfus MG, Fraumeni JF Jr, Li FP. Follow-up study of twenty-four families with Li-Fraumeni syndrome. Cancer Res 1991;51:6094-6097.
9. Meijers-Heijboer H, van den Ouweland A, Klijn J, et al. Low-penetrance susceptibility to breast cancer due to CHEK2(*) 1100delC in noncarriers of BRCA1 or BRCA2 mutations. Nat Genet 2002;31:55-59.
10. Chenevix-Trench G, Spurdle AB, Gatei M, et al. Dominant negative ATM mutations in breast cancer families. J Natl Cancer Inst 2002;94:205-215. [Erratum, J Natl Cancer Inst 2002;94:952.]
11. Spring K, Ahangari F, Scott SP, et al. Mice heterozygous for mutation in Atm, the gene involved in ataxia-telangiectasia, have heightened susceptibility to cancer. Nat Genet 2002;32:185-190.
12. Gayther SA, Russell P, Harrington P, Antoniou AC, Easton DF, Ponder BAJ. The contribution of germline BRCA1 and BRCA2 mutations to familial ovarian cancer: no evidence for other ovarian cancer-susceptibility genes. Am J Hum Genet 1999;65:1021-1029.
13. Sekine M, Nagata H, Tsuji S, et al. Localization of a novel susceptibility gene for familial ovarian cancer to chromosome 3p22-p25. Hum Mol Genet 2001;10:1421-1429.
14. Dunning AM, Healey CS, Pharoah PD, Teare MD, Ponder BA, Easton DF. A systematic review of genetic polymorphisms and breast cancer risk. Cancer Epidemiol Biomarkers Prev 1999;8:843-854.
15. Hall JM, Lee MK, Newman B, et al. Linkage of early-onset familial breast cancer to chromosome 17q21. Science 1990;250:1684-1689.
16. Wooster R, Neuhausen SL, Mangion J, et al. Localization of a breast cancer susceptibility gene, BRCA2, to chromosome 13q12-13. Science 1994;265:2088-2090.
17. Schutte M, da Costa LT, Hahn SA, et al. Identification by representational difference analysis of a homozygous deletion in pancreatic carcinoma that lies within the BRCA2 region. Proc Natl Acad Sci U S A 1995;92:5950-5954.
18. Barkardottir RB, Arason A, Egilsson V, Gudmundsson J, Jonasdottir A, Johannesdottir G. Chromosome 17q-linkage seems to be infrequent in Icelandic families at risk of breast cancer. Acta Oncol 1995;34:657-662.
19. Gudmundsson J, Johannesdottir G, Arason A, et al. Frequent occurrence of BRCA2 linkage in Icelandic breast cancer families and segregation of a common BRCA2 haplotype. Am J Hum Genet 1996;58:749-756.
20. Nyström-Lahti M, Peltomäki P, Aaltonen LA, de la Chapelle A. Genetic and genealogic study of 33 Finnish HNPCC kindreds. Am J Hum Genet 1994;55:Suppl:A365-A365. abstract.
21. Kainu T, Juo SH, Desper R, et al. Somatic deletions in hereditary breast cancers implicate 13q21 as a putative novel breast cancer susceptibility locus. Proc Natl Acad Sci U S A 2000;97:9603-9608.
22. Seitz S, Rohde K, Bender E, et al. Deletion mapping and linkage analysis provide strong indication for the involvement of the human chromosome region 8p12-p22 in breast carcinogenesis. Br J Cancer 1997;76:983-991.
23. Rahman N, Teare MD, Seal S, et al. Absence of evidence for a familial breast cancer susceptibility gene at chromosome 8p12-p22. Oncogene 2000;19:4170-4173.
24. Thompson D, Szabo CI, Mangion J, et al. 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. Proc Natl Acad Sci U S A 2002;99:827-831.
25. Ford D, Easton DF, Stratton M, et al. Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. Am J Hum Genet 1998;62:676-689.
26. Sachidanandam R, Weissman D, Schmidt SC, et al. A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature 2001;409:928-933.
27. Goode EL, Dunning AM, Kuschel B, et al. Effect of germ-line genetic variation on breast cancer survival in a population-based study. Cancer Res 2002;62:3052-3057.
28. Pollack JR, Sorlie T, Perou CM, et al. Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc Natl Acad Sci U S A 2002;99:12963-12968.
29. Snijders AM, Nowak N, Segraves R, et al. Assembly of microarrays for genome-wide measurement of DNA copy number. Nat Genet 2001;29:263-264.
30. Albertson DG, Ylstra B, Segraves R, et al. Quantitative mapping of amplicon structure by array CGH identifies CYP24 as a candidate oncogene. Nat Genet 2000;25:144-146.
31. Collins C, Rommens JM, Kowbel D, et al. Positional cloning of ZNF217 and NABC1: genes amplified at 20q13.2 and overexpressed in breast carcinoma. Proc Natl Acad Sci U S A 1998;95:8703-8708.
32. Walters MR. Newly identified actions of the vitamin D endocrine system. Endocr Rev 1992;13:719-764.
33. Figeys D, Gygi SP, Zhang Y, Watts J, Gu M, Aebersold R. Electrophoresis combined with novel mass spectrometry techniques: powerful tools for the analysis of proteins and proteomes. Electrophoresis 1998;19:1811-1818.
34. Alizadeh AA, Eisen MB, Davis RE, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000;403:503-511.
35. Perou CM, Jeffrey SS, van de Rijn M, et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci U S A 1999;96:9212-9217.
36. Hedenfalk I, Duggan D, Chen Y, et al. Gene-expression profiles in hereditary breast cancer. N Engl J Med 2001;344:539-548.
37. Welsh JB, Zarrinkar PP, Sapinoso LM, et al. Analysis of gene expression profiles in normal and neoplastic ovarian tissue samples identifies candidate molecular markers of epithelial ovarian cancer. Proc Natl Acad Sci U S A 2001;98:1176-1181.
38. Zhang L, Conejo-Garcia JR, Katsaros D, et al. Intratumoral T cells, recurrence, and survival in epithelial ovarian cancer. N Engl J Med 2003;348:203-213.
39. Kudoh K, Ramanna M, Ravatn R, et al. Monitoring the expression profiles of doxorubicin-induced and doxorubicin-resistant cancer cells by cDNA microarray. Cancer Res 2000;60:4161-4166.
40. van 't Veer LJ, Dai H, van de Vijver MJ, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002;415:530-536.
41. van de Vijver MJ, He YD, van 't Veer LJ, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002;347:1999-2009.
42. Claus EB, Risch N, Thompson WD. Genetic analysis of breast cancer in the cancer and steroid hormone study. Am J Hum Genet 1991;48:232-242.
43. Couch FJ, DeShano ML, Blackwood MA, et al. BRCA1 mutations in women attending clinics that evaluate the risk of breast cancer. N Engl J Med 1997;336:1409-1415.
44. Frank TS, Manley SA, Olopade OI, et al. Sequence analysis of BRCA1 and BRCA2: correlation of mutations with family history and ovarian cancer risk. J Clin Oncol 1998;16:2417-2425.
45. Parmigiani G, Berry D, Aguilar O. Determining carrier probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J Hum Genet 1998;62:145-158.
46. Meijers-Heijboer H, van Geel B, van Putten WLJ, et al. Breast cancer after prophylactic bilateral mastectomy in women with a BRCA1 or BRCA2 mutation. N Engl J Med 2001;345:159-164.
47. Brekelmans CT, Seynaeve C, Bartels CC, et al. Effectiveness of breast cancer surveillance in BRCA1/2 gene mutation carriers and women with high familial risk. J Clin Oncol 2001;19:924-930.
48. Warner E, Plewes DB, Shumak RS, et al. Comparison of breast magnetic resonance imaging, mammography, and ultrasound for surveillance of women at high risk for hereditary breast cancer. J Clin Oncol 2001;19:3524-3531.
49. Tilanus-Linthorst M, Verhoog L, Obdeijn IM, et al. A BRCA1/2 mutation, high breast density and prominent pushing margins of a tumor independently contribute to a frequent false-negative mammography. Int J Cancer 2002;102:91-95. [Erratum, Int J Cancer 2002;102:665.]
50. Stoutjesdijk MJ, Boetes C, Jager GJ, et al. Magnetic resonance imaging and mammography in women with a hereditary risk of breast cancer. J Natl Cancer Inst 2001;93:1095-1102.
51. Rebbeck TR, Levin AM, Eisen A, et al. Breast cancer risk after bilateral prophylactic oophorectomy in BRCA1 mutation carriers. J Natl Cancer Inst 1999;91:1475-1479.
52. Rebbeck TR, Lynch HT, Neuhausen SL, et al. Prophylactic oophorectomy in carriers of BRCA1 or BRCA2 mutations. N Engl J Med 2002;346:1616-1622.
53. Narod SA, Brunet JS, Ghadirian P, et al. Tamoxifen and risk of contralateral breast cancer in BRCA1 and BRCA2 mutation carriers: a case-control study. Lancet 2000;356:1876-1881.
54. Armes JE, Trute L, White D, et al. Distinct molecular pathogeneses of early-onset breast cancers in BRCA1 and BRCA2 mutation carriers: a population-based study. Cancer Res 1999;59:2011-2017.
55. King MC, Wieand S, Hale K, et al. Tamoxifen and breast cancer incidence among women with inherited mutations in BRCA1 and BRCA2: National Surgical Adjuvant Breast and Bowel Project (NSABP-P1) Breast Cancer Prevention Trial. JAMA 2001;286:2251-2256.
56. Davies H, Bignell GR, Cox C, et al. Mutations of the BRAF gene in human cancer. Nature 2002;417:949-954.

PDF PDA Full Text Letters Add to Personal Archive Add to Citation Manager Notify a Friend E-mail When Cited E-mail When Letters Appear PubMed Citation

Related Letters:

Breast-Cancer Genomics
Friedenson B., Piver M. S., Weber B. L., Wooster R.
Extract | Full Text | PDF  
N Engl J Med 2003; 349:910-911, Aug 28, 2003. Correspondence

This article has been cited by other articles:

• Shakya, R., Szabolcs, M., McCarthy, E., Ospina, E., Basso, K., Nandula, S., Murty, V., Baer, R., Ludwig, T. (2008). The basal-like mammary carcinomas induced by Brca1 or Bard1 inactivation implicate the BRCA1/BARD1 heterodimer in tumor suppression. Proc. Natl. Acad. Sci. USA 105: 7040-7045 [Abstract] [Full Text]  
• Kauff, N. D., Domchek, S. M., Friebel, T. M., Robson, M. E., Lee, J., Garber, J. E., Isaacs, C., Evans, D. G., Lynch, H., Eeles, R. A., Neuhausen, S. L., Daly, M. B., Matloff, E., Blum, J. L., Sabbatini, P., Barakat, R. R., Hudis, C., Norton, L., Offit, K., Rebbeck, T. R. (2008). Risk-Reducing Salpingo-Oophorectomy for the Prevention of BRCA1- and BRCA2-Associated Breast and Gynecologic Cancer: A Multicenter, Prospective Study. JCO 26: 1331-1337 [Abstract] [Full Text]  
• Gehlert, S., Sohmer, D., Sacks, T., Mininger, C., McClintock, M., Olopade, O. (2008). Targeting Health Disparities: A Model Linking Upstream Determinants To Downstream Interventions. Health Aff (Millwood) 27: 339-349 [Abstract] [Full Text]  
• Martin, L. P., Hamilton, T. C., Schilder, R. J. (2008). Platinum Resistance: The Role of DNA Repair Pathways. Clin. Cancer Res. 14: 1291-1295 [Abstract] [Full Text]  
• Fatouros, M., Baltoyiannis, G., Roukos, D. H. (2008). The Predominant Role of Surgery in the Prevention and New Trends in the Surgical Treatment of Women With BRCA1/2 Mutations. Ann. Surg. Oncol. 15: 21-33 [Abstract] [Full Text]  
• Laufer, M., Nandula, S. V., Modi, A. P., Wang, S., Jasin, M., Murty, V. V. V. S., Ludwig, T., Baer, R. (2007). Structural Requirements for the BARD1 Tumor Suppressor in Chromosomal Stability and Homology-directed DNA Repair. J. Biol. Chem. 282: 34325-34333 [Abstract] [Full Text]  
• Zhang, L., Huang, J., Yang, N., Greshock, J., Liang, S., Hasegawa, K., Giannakakis, A., Poulos, N., O'Brien-Jenkins, A., Katsaros, D., Butzow, R., Weber, B. L., Coukos, G. (2007). Integrative Genomic Analysis of Phosphatidylinositol 3'-Kinase Family Identifies PIK3R3 as a Potential Therapeutic Target in Epithelial Ovarian Cancer. Clin. Cancer Res. 13: 5314-5321 [Abstract] [Full Text]  
• Liu, X., Holstege, H., van der Gulden, H., Treur-Mulder, M., Zevenhoven, J., Velds, A., Kerkhoven, R. M., van Vliet, M. H., Wessels, L. F. A., Peterse, J. L., Berns, A., Jonkers, J. (2007). Somatic loss of BRCA1 and p53 in mice induces mammary tumors with features of human BRCA1-mutated basal-like breast cancer. Proc. Natl. Acad. Sci. USA 104: 12111-12116 [Abstract] [Full Text]  
• Tischkowitz, M., Xia, B., Sabbaghian, N., Reis-Filho, J. S., Hamel, N., Li, G., van Beers, E. H., Li, L., Khalil, T., Quenneville, L. A., Omeroglu, A., Poll, A., Lepage, P., Wong, N., Nederlof, P. M., Ashworth, A., Tonin, P. N., Narod, S. A., Livingston, D. M., Foulkes, W. D. (2007). Analysis of PALB2/FANCN-associated breast cancer families. Proc. Natl. Acad. Sci. USA 104: 6788-6793 [Abstract] [Full Text]  
• Behbakht, K., Qamar, L., Aldridge, C. S., Coletta, R. D., Davidson, S. A., Thorburn, A., Ford, H. L. (2007). Six1 Overexpression in Ovarian Carcinoma Causes Resistance to TRAIL-Mediated Apoptosis and Is Associated with Poor Survival. Cancer Res. 67: 3036-3042 [Abstract] [Full Text]  
• Kell, M. R, Burke, J. P (2007). Management of breast cancer in women with BRCA gene mutation. BMJ 334: 437-438 [Full Text]  
• Karppinen, S-M, Barkardottir, R B, Backenhorn, K, Sydenham, T, Syrjakoski, K, Schleutker, J, Ikonen, T, Pylkas, K, Rapakko, K, Erkko, H, Johannesdottir, G, Gerdes, A-M, Thomassen, M, Agnarsson, B A, Grip, M, Kallioniemi, A, Kere, J, Aaltonen, L A, Arason, A, Moller, P, Kruse, T A, Borg, A, Winqvist, R (2006). Nordic collaborative study of the BARD1 Cys557Ser allele in 3956 patients with cancer: enrichment in familial BRCA1/BRCA2 mutation-negative breast cancer but not in other malignancies. J. Med. Genet. 43: 856-862 [Abstract] [Full Text]  
• Seo, D., Ginsburg, G. S., Goldschmidt-Clermont, P. J. (2006). Gene Expression Analysis of Cardiovascular Diseases: Novel Insights Into Biology and Clinical Applications. J Am Coll Cardiol 48: 227-235 [Abstract] [Full Text]  
• Saeki, H., Siaud, N., Christ, N., Wiegant, W. W., van Buul, P. P. W., Han, M., Zdzienicka, M. Z., Stark, J. M., Jasin, M. (2006). Suppression of the DNA repair defects of BRCA2-deficient cells with heterologous protein fusions. Proc. Natl. Acad. Sci. USA 103: 8768-8773 [Abstract] [Full Text]  
• Zhang, L., Huang, J., Yang, N., Liang, S., Barchetti, A., Giannakakis, A., Cadungog, M. G., O'Brien-Jenkins, A., Massobrio, M., Roby, K. F., Katsaros, D., Gimotty, P., Butzow, R., Weber, B. L., Coukos, G. (2006). Integrative Genomic Analysis of Protein Kinase C (PKC) Family Identifies PKC{iota} as a Biomarker and Potential Oncogene in Ovarian Carcinoma.. Cancer Res. 66: 4627-4635 [Abstract] [Full Text]  
• Ashworth, A. (2006). Defective Double-Strand DNA Repair and Cancer Susceptibility in BRCA Mutation Carriers. aacredbook 2006: 303-306 [Full Text]  
• Wilkening, S., Bermejo, J. L., Burwinkel, B., Klaes, R., Bartram, C. R., Meindl, A., Bugert, P., Schmutzler, R. K., Wappenschmidt, B., Untch, M., Hemminki, K., Forsti, A. (2006). The Single Nucleotide Polymorphism IVS1+309 in Mouse Double Minute 2 Does Not Affect Risk of Familial Breast Cancer. Cancer Res. 66: 646-648 [Abstract] [Full Text]  
• Samuelson, D. J., Aperavich, B. A., Haag, J. D., Gould, M. N. (2005). Fine Mapping Reveals Multiple Loci and a Possible Epistatic Interaction within the Mammary Carcinoma Susceptibility Quantitative Trait Locus, Mcs5. Cancer Res. 65: 9637-9642 [Abstract] [Full Text]  
• Agata, S, Dalla Palma, M, Callegaro, M, Scaini, M C, Menin, C, Ghiotto, C, Nicoletto, O, Zavagno, G, Chieco-Bianchi, L, D'Andrea, E, Montagna, M (2005). Large genomic deletions inactivate the BRCA2 gene in breast cancer families. J. Med. Genet. 42: e64-e64 [Abstract] [Full Text]  
• Ferguson, D. A., Muenster, M. R., Zang, Q., Spencer, J. A., Schageman, J. J., Lian, Y., Garner, H. R., Gaynor, R. B., Huff, J. W., Pertsemlidis, A., Ashfaq, R., Schorge, J., Becerra, C., Williams, N. S., Graff, J. M. (2005). Selective Identification of Secreted and Transmembrane Breast Cancer Markers using Escherichia coli Ampicillin Secretion Trap. Cancer Res. 65: 8209-8217 [Abstract] [Full Text]  
• Nelson, H. D., Huffman, L. H., Fu, R., Harris, E. L. (2005). Genetic Risk Assessment and BRCA Mutation Testing for Breast and Ovarian Cancer Susceptibility: Systematic Evidence Review for the U.S. Preventive Services Task Force. ANN INTERN MED 143: 362-379 [Abstract] [Full Text]  
• Rau, K-M, Kang, H-Y, Cha, T-L, Miller, S A, Hung, M-C (2005). The mechanisms and managements of hormone-therapy resistance in breast and prostate cancers. Endocr Relat Cancer 12: 511-532 [Abstract] [Full Text]  
• Kim, M. Y., Zhang, T., Kraus, W. L. (2005). Poly(ADP-ribosyl)ation by PARP-1: `PAR-laying' NAD+ into a nuclear signal. Genes Dev. 19: 1951-1967 [Abstract] [Full Text]  
• Turner, S. S. (2005). Critical Junctures in Genetic Medicine: The Transformation of DNA Lab Science to Commercial Pharmacogenomics. Journal of Business and Technical Communication 19: 328-352 [Abstract]  
• Choudhury, A. D., Xu, H., Modi, A. P., Zhang, W., Ludwig, T., Baer, R. (2005). Hyperphosphorylation of the BARD1 Tumor Suppressor in Mitotic Cells. J. Biol. Chem. 280: 24669-24679 [Abstract] [Full Text]  
• Thompson, M. E., Robinson-Benion, C. L., Holt, J. T. (2005). An Amino-terminal Motif Functions as a Second Nuclear Export Sequence in BRCA1. J. Biol. Chem. 280: 21854-21857 [Abstract] [Full Text]  
• Brown, P. H., Rashid, A. (2005). Cancer Prevention: The Importance of Accurate Risk Assessment. Cancer Epidemiol. Biomarkers Prev. 14: 1357-1358 [Full Text]  
• Ishimori, T., Patel, P. V., Wahl, R. L. (2005). Detection of Unexpected Additional Primary Malignancies with PET/CT. JNM 46: 752-757 [Abstract] [Full Text]  
• Woodward, A M, Davis, T A, Silva, A G S, kConFab Investigators, , Kirk, J A, Leary, J A (2005). Large genomic rearrangements of both BRCA2 and BRCA1 are a feature of the inherited breast/ovarian cancer phenotype in selected families. J. Med. Genet. 42: e31-e31 [Abstract] [Full Text]  
• Shaag, A., Walsh, T., Renbaum, P., Kirchhoff, T., Nafa, K., Shiovitz, S., Mandell, J. B., Welcsh, P., Lee, M. K., Ellis, N., Offit, K., Levy-Lahad, E., King, M.-C. (2005). Functional and genomic approaches reveal an ancient CHEK2 allele associated with breast cancer in the Ashkenazi Jewish population. Hum Mol Genet 14: 555-563 [Abstract] [Full Text]  
• Zhang, L., Yang, N., Huang, J., Buckanovich, R. J., Liang, S., Barchetti, A., Vezzani, C., O'Brien-Jenkins, A., Wang, J., Ward, M. R., Courreges, M. C., Fracchioli, S., Medina, A., Katsaros, D., Weber, B. L., Coukos, G. (2005). Transcriptional Coactivator Drosophila Eyes Absent Homologue 2 Is Up-Regulated in Epithelial Ovarian Cancer and Promotes Tumor Growth. Cancer Res. 65: 925-932 [Abstract] [Full Text]  
• Wu, K., Hinson, S. R., Ohashi, A., Farrugia, D., Wendt, P., Tavtigian, S. V., Deffenbaugh, A., Goldgar, D., Couch, F. J. (2005). Functional Evaluation and Cancer Risk Assessment of BRCA2 Unclassified Variants. Cancer Res. 65: 417-426 [Abstract] [Full Text]  
• Powell, C. B., Kenley, E., Chen, L.-m., Crawford, B., McLennan, J., Zaloudek, C., Komaromy, M., Beattie, M., Ziegler, J. (2005). Risk-Reducing Salpingo-Oophorectomy in BRCA Mutation Carriers: Role of Serial Sectioning in the Detection of Occult Malignancy. JCO 23: 127-132 [Abstract] [Full Text]  
• Butch, A. W., Chun, H. H., Nahas, S. A., Gatti, R. A. (2004). Immunoassay to Measure Ataxia-Telangiectasia Mutated Protein in Cellular Lysates. Clin. Chem. 50: 2302-2308 [Abstract] [Full Text]  
• Sifri, R., Gangadharappa, S., Acheson, L. S. (2004). Identifying and Testing for Hereditary Susceptibility to Common Cancers. CA Cancer J Clin 54: 309-326 [Abstract] [Full Text]  
• Oh, H. S., Moharita, A., Potian, J. G., Whitehead, I. P., Livingston, J. C., Castro, T. A., Patel, P. S., Rameshwar, P. (2004). Bone Marrow Stroma Influences Transforming Growth Factor-{beta} Production in Breast Cancer Cells to Regulate c-myc Activation of the Preprotachykinin-I Gene in Breast Cancer Cells. Cancer Res. 64: 6327-6336 [Abstract] [Full Text]  
• Karppinen, S-M, Heikkinen, K, Rapakko, K, Winqvist, R (2004). Mutation screening of the BARD1 gene: evidence for involvement of the Cys557Ser allele in hereditary susceptibility to breast cancer. J. Med. Genet. 41: e114-e114 [Full Text]  
• Choudhury, A. D., Xu, H., Baer, R. (2004). Ubiquitination and Proteasomal Degradation of the BRCA1 Tumor Suppressor Is Regulated during Cell Cycle Progression. J. Biol. Chem. 279: 33909-33918 [Abstract] [Full Text]  
• Akahira, J.-i., Sugihashi, Y., Suzuki, T., Ito, K., Niikura, H., Moriya, T., Nitta, M., Okamura, H., Inoue, S., Sasano, H., Okamura, K., Yaegashi, N. (2004). Decreased Expression of 14-3-3{sigma} Is Associated with Advanced Disease in Human Epithelial Ovarian Cancer: Its Correlation with Aberrant DNA Methylation. Clin. Cancer Res. 10: 2687-2693 [Abstract] [Full Text]  
• Tan, W., Zheng, L., Lee, W.-H., Boyer, T. G. (2004). Functional Dissection of Transcription Factor ZBRK1 Reveals Zinc Fingers with Dual Roles in DNA-binding and BRCA1-dependent Transcriptional Repression. J. Biol. Chem. 279: 6576-6587 [Abstract] [Full Text]  
• Esteban-Cardenosa, E., Duran, M., Infante, M., Velasco, E., Miner, C. (2004). High-Throughput Mutation Detection Method to Scan BRCA1 and BRCA2 Based on Heteroduplex Analysis by Capillary Array Electrophoresis. Clin. Chem. 50: 313-320 [Abstract] [Full Text]  
• Simonds, W. F., Robbins, C. M., Agarwal, S. K., Hendy, G. N., Carpten, J. D., Marx, S. J. (2004). Familial Isolated Hyperparathyroidism Is Rarely Caused by Germline Mutation in HRPT2, the Gene for the Hyperparathyroidism-Jaw Tumor Syndrome. J. Clin. Endocrinol. Metab. 89: 96-102 [Abstract] [Full Text]  
• Brandt, B., Hermann, S., Straif, K., Tidow, N., Buerger, H., Chang-Claude, J. (2004). Modification of Breast Cancer Risk in Young Women by a Polymorphic Sequence in the egfr Gene. Cancer Res. 64: 7-12 [Abstract] [Full Text]  
• Macgregor, J. T. (2004). Biomarkers of Cancer Risk and Therapeutic Benefit: New Technologies, New Opportunities, and Some Challenges. Toxicol Pathol 32: 99-105 [Abstract]  
• Guttmacher, A. E., Collins, F. S. (2003). Welcome to the Genomic Era. NEJM 349: 996-998 [Full Text]  
• Friedenson, B., Piver, M. S., Weber, B. L., Wooster, R. (2003). Breast-Cancer Genomics. NEJM 349: 910-911 [Full Text]