Background Many cases of hereditary breast cancer are due tomutations in either the BRCA1 or the BRCA2 gene. The histopathologicalchanges in these cancers are often characteristic of the mutantgene. We hypothesized that the genes expressed by these twotypes of tumors are also distinctive, perhaps allowing us toidentify cases of hereditary breast cancer on the basis of gene-expressionprofiles.
Methods RNA from samples of primary tumors from seven carriersof the BRCA1 mutation, seven carriers of the BRCA2 mutation,and seven patients with sporadic cases of breast cancer wascompared with a microarray of 6512 complementary DNA clonesof 5361 genes. Statistical analyses were used to identify aset of genes that could distinguish the BRCA1 genotype fromthe BRCA2 genotype.
Results Permutation analysis of multivariate classificationfunctions established that the gene-expression profiles of tumorswith BRCA1 mutations, tumors with BRCA2 mutations, and sporadictumors differed significantly from each other. An analysis ofvariance between the levels of gene expression and the genotypeof the samples identified 176 genes that were differentiallyexpressed in tumors with BRCA1 mutations and tumors with BRCA2mutations. Given the known properties of some of the genes inthis panel, our findings indicate that there are functionaldifferences between breast tumors with BRCA1 mutations and thosewith BRCA2 mutations.
Conclusions Significantly different groups of genes are expressedby breast cancers with BRCA1 mutations and breast cancers withBRCA2 mutations. Our results suggest that a heritable mutationinfluences the gene-expression profile of the cancer.
Inheritance of a mutant BRCA1 or BRCA2 gene (numbers 113705and 600185, respectively, in Online Mendelian Inheritance inMan, a catalogue of inherited diseases) confers a lifetime riskof breast cancer of 50 to 85 percent and a lifetime risk ofovarian cancer of 15 to 45 percent.1,2,3,4,5,6 These germ-linemutations account for a substantial proportion of inheritedbreast and ovarian cancers,7 but it is likely that additionalsusceptibility genes will be discovered.8,9
Certain pathological features can help to distinguish breasttumors with BRCA1 mutations from those with BRCA2 mutations.Tumors with BRCA1 mutations are high-grade cancers with a highmitotic index, "pushing" tumor margins (i.e., noninfiltrating,smooth edges), and a lymphocytic infiltrate, whereas tumorswith BRCA2 mutations are heterogeneous, are often relativelyhigh grade, and display substantially less tubule formation.The proportion of the perimeter with continuous pushing marginscan distinguish both types of tumors from sporadic cases ofbreast cancer.10 Tumors with BRCA1 mutations are generally negativefor both estrogen and progesterone receptors, whereas most tumorswith BRCA2 mutations are positive for these hormone receptors.11,12,13,14These differences imply that the mutant BRCA1 and BRCA2 genesinduce the formation of breast tumors through separate pathways.
The BRCA1 and BRCA2 proteins participate in DNA repair and homologousrecombination and probably other cellular processes.15 A cellwith a mutant BRCA1 or BRCA2 gene, which therefore lacks functionalBRCA1 or BRCA2 protein, has a decreased ability to repair damagedDNA. In animal models, this defect causes genomic instability.16In humans, breast tumors in carriers of mutant BRCA1 or BRCA2genes are characterized by a large number of chromosomal changes,some of which differ depending on the genotype.17
In this study, we examined breast-cancer tissues from patientswith BRCA1-related cancer, patients with BRCA2-related cancer,and patients with sporadic cases of breast cancer to determinewhether there are distinctive patterns of global gene expressionin these three kinds of tumors.
Methods
Patients and Biopsy Specimens
Patients with primary breast cancer and who had a family historyof breast or ovarian cancer, or both, that was compatible witha dominant mode of inheritance were referred for genetic counselingto the Oncogenetic Clinic of Lund University Hospital. Thesepatients were asked to provide a blood sample and to sign aninformed-consent form authorizing an analysis for BRCA1 andBRCA2 mutations. Mutation analysis was performed as describedpreviously.18 Biopsy specimens of primary breast tumors frompatients with germ-line mutations of BRCA1 (seven patients)or BRCA2 (eight tumors from seven patients) were selected foranalysis. In addition, seven patients with sporadic cases ofprimary breast cancer whose family history was unknown werealso identified. These patients had either estrogen-receptor–negative,aggressive tumors (characterized by aneuploidy and a high fractionof cells in S phase) or estrogen-receptor–positive, lessaggressive tumors. Total RNA was extracted from flash-frozentumor specimens, which had been stored at –80°C, withthe use of the RNeasy Maxi Kit (Qiagen) and Trizol reagent (GIBCOBRL) according to the manufacturers' recommendations.19
The studies were approved by the institutional review boardsof both Lund University and the National Human Genome ResearchInstitute of the National Institutes of Health.
Microarrays of Complementary DNA
We obtained samples of complementary DNA (cDNA) with verifiedsequences20 under a Cooperative Research and Development Agreementwith Research Genetics. Gene names are listed according to build110 of the UniGene human-sequence collection (available at theUniGene Web site: http://www.ncbi.nlm.nih.gov/UniGene/build.html).The 6512 cDNAs we used represent 5361 unique genes: 2905 areknown and 2456 are unknown genes.
Microarrays were hybridized and scanned, and image analysiswas performed as described previously (Figure 1).20,21,22 Thereference cell line, MCF-10A (American Type Culture Collection,CRL-10317), a nontumorigenic breast-cell line, was an internalstandard against which each tumor was compared (not a biologiccontrol). RNA from normal breast epithelial cells was includedfor comparison (Figure 2B).
Figure 1. Overview of Procedures for Preparing and Analyzing Microarrays of Complementary DNA (cDNA) and Breast-Tumor Tissue.
As shown in Panel A, reference RNA and tumor RNA are labeled by reverse transcription with different fluorescent dyes (green for the reference cells and red for the tumor cells) and hybridized to a cDNA microarray containing robotically printed cDNA clones. As shown in Panel B, the slides are scanned with a confocal laser scanning microscope, and color images are generated for each hybridization with RNA from the tumor and reference cells. Genes up-regulated in the tumors appear red, whereas those with decreased expression appear green. Genes with similar levels of expression in the two samples appear yellow. Genes of interest are selected on the basis of the differences in the level of expression by known tumor classes (e.g., BRCA1-mutation–positive and BRCA2-mutation–positive). Statistical analysis determines whether these differences in the gene-expression profiles are greater than would be expected by chance. As shown in Panel C, the differences in the patterns of gene expression between tumor classes can be portrayed in the form of a color-coded plot, and the relations between tumors can be portrayed in the form of a multidimensional-scaling plot. Tumors with similar gene-expression profiles cluster close to one another in the multidimensional-scaling plot. As shown in Panel D, particular genes of interest can be further studied through the use of a large number of arrayed, paraffin-embedded tumor specimens, referred to as tissue microarrays. As shown in Panel E, immunohistochemical analyses of hundreds or thousands of these arrayed biopsy specimens can be performed in order to extend the microarray findings.
Figure 2. Identification of Genes That Can Be Used to Differentiate BRCA1-Mutation–Positive, BRCA2-Mutation–Positive, and Sporadic Cases of Primary Breast Cancer.
Panel A shows the 51 genes that best differentiated among the three types of tumors, as determined by a modified F test (=0.001). Panel B shows the multidimensional-scaling plot of the seven samples from patients with BRCA1-mutation–positive breast tumors (blue circles), eight samples from patients with BRCA2-mutation–positive tumors (tan circles), seven samples from patients with sporadic tumors (gray circles), and two samples of normal mammary epithelial cells (pink circles) that included all 3226 genes that met the criteria for inclusion in the analysis. Panel C shows the multidimensional-scaling plot of the 22 primary-tumor samples that included the 51 genes that best differentiated the three types of tumors, as evidenced by the clustering of the BRCA2-mutation–positive samples and the BRCA1-mutation–positive samples.
Tissue Microarrays
A microarray of breast-cancer tissue (Figure 1), constructedas previously described,23 consisted of samples of 113 primarybreast tumors, in duplicate, derived from a population-basedseries of patients from southern Sweden in whom the diseasehad been diagnosed before the age of 40 years. The patientsconsisted of 23 with BRCA1 mutations, 17 with BRCA2 mutations,20 with familial breast cancer (defined as a history of breastor ovarian cancer in at least one first-degree relative) butno BRCA1 or BRCA2 mutations, 19 with possibly familial breastcancer (defined as a history of breast or ovarian cancer inat least one second-degree relative) but no BRCA1 or BRCA2 mutations,and 34 with sporadic breast cancer. The duplicate core-tissue–biopsyspecimens (diameter, 0.6 mm) were obtained from the least differentiatedregions of individual paraffin-embedded tumors.
Analysis of DNA Methylation
Patterns of DNA methylation in the CpG island of the BRCA1 genewere determined by a methylation-specific polymerase chain reaction.24
Statistical Analysis
Tests for associations between each type of mutation (BRCA1or BRCA2) and clinical variables were performed with Fisher'sexact test for categorical variables and the Wilcoxon–Mann–Whitneytest for continuous and ordered variables. Reported P valuesare exact and have not been corrected for multiple comparisons(30 variables were tested). All P values are two-sided.
In the analyses involving cDNA microarrays, a total of 3226genes with an average intensity (level of expression) of morethan 2500 pixels among all samples, an average spot area ofmore than 40 pixels, and no more than one sample in which thesize of the spot area was 0 pixels were included.22 A conservativeestimate of experimental variance (involving hybridization ofpairs of cDNAs on different days) indicated that our observationsfell within the 95 percent confidence interval of 0.61 to 1.65for a mean value of 1.0.
We used a class-prediction method to determine whether the patternsof gene expression could be used to classify tumor samples intotwo classes according to the presence or absence of BRCA1 andBRCA2 mutations (positive or negative for BRCA1 mutations andpositive or negative for BRCA2 mutations), with use of a compoundcovariate predictor.25 We estimated the misclassification rateusing leave-one-out cross-validation and used random permutationsof the class-membership indicators to determine the significanceof the results.
We used three methods to generate lists of genes with differentlevels of expression among the groups of patients with breastcancer: modified F tests and t-tests, a weighted gene analysis,and mutual-information scoring (InfoScore). InfoScore uses aranking-based scoring system and combinatorial permutation ofsample labels to produce a rigorous statistical benchmarkingof the overabundance of genes whose differential expressionpattern correlates with sample type (information available athttp://www.labs.agilent.com/resources/techreports.html). Anagglomerative hierarchical clustering algorithm was used toinvestigate any relation among the statistically significantdiscriminator genes.19,20 We also used multidimensional scalingto show the correlation of expression of given subgroups ofgenes among various tumor samples.20 In this three-dimensionalrendering of the data, samples with similar expression profileslie closer to each other than those with dissimilar profiles.
Mutations in seven carriers of BRCA1 mutations and seven carriersof BRCA2 mutations were confirmed by direct sequencing (Table 1).Specimens were also obtained from seven patients with sporadicprimary breast cancer. Tumors were classified pathologicallyaccording to criteria of the Breast Cancer Linkage Consortium10,26,27;all slides were read by a single pathologist. Grading was performedaccording to a previously described method.28 The pathologicalresults for our cohort were similar to those of earlier studies.10,12,26,29,30,31All tumors with BRCA1 mutations were grade 3, most had lymphocyticinfiltration and extensive pushing margins, most tended to growin sheets, and several had confluent necrosis; there was oneatypical medullary carcinoma. These features as a whole werenot as common among patients with BRCA2 mutations.30,31 As expected,estrogen and progesterone receptors were absent in tumors fromall the patients with BRCA1 mutations and also from one patientwith a BRCA2 mutation.11,12
Table 1. Characteristics of Breast-Cancer Tissue from Patients with BRCA1-Mutation–Positive, BRCA2-Mutation–Positive, or Sporadic Cases of Primary Breast Cancer.
Use of Gene-Expression Profiles to Identify Hereditary Breast Cancers
Fluorescence-intensity ratios were calculated and gene-expressionprofiles were generated for each sample. The gene-expressionprofiles were used to determine which of the genes expressedby the tumors correlated with the BRCA1-mutation–positivetumors, the BRCA2-mutation–positive tumors, and the sporadictumors. Figure 2A shows the results of a modified F test, whichyielded 51 genes (=0.001) whose variation in expression amongall experiments best differentiated among these types of cancers.The multidimensional-scaling plot of the 22 samples from patientswith primary breast cancer and 2 samples of normal mammary epithelialcells that included all 3226 genes that met the criteria forinclusion is shown in Figure 2B. The multidimensional-scalingplot of the 22 samples from patients with primary breast cancerthat included the 51 genes that best differentiated among thethree types of tumors is shown in Figure 2C.
We used a class-prediction method to determine whether the gene-expressionprofiles of the 22 breast-tumor samples accurately identifiedthem as positive or negative for BRCA1 mutations or as positiveor negative for BRCA2 mutations. For the analysis of all 22tumor samples, 9 genes were differentially expressed betweenBRCA1-mutation–positive tumors and BRCA1-mutation–negativetumors, and 11 genes were differentially expressed between BRCA2-mutation–positivetumors and BRCA2-mutation–negative tumors (=0.0001) (Table 2).All 7 tumors with BRCA1 mutations and 14 of 15 tumors withoutBRCA1 mutations were correctly identified in the BRCA1 classification.Five of 8 tumors with BRCA2 mutations and 13 of 14 tumors withoutBRCA2 mutations were correctly identified in the BRCA2 classification.The accuracy of these classifications was significant as comparedwith randomized data. Only 0.3 percent of data sets in whichBRCA1 classifications were permuted resulted in the misclassificationof one or fewer samples, and only 4.0 percent of data sets inwhich BRCA2 classifications were permuted resulted in the misclassificationof four or fewer samples. Similar results were obtained whenwe applied naive Bayesian classifiers.32
Table 2. Classification of Hereditary Breast Cancers According to the Gene-Expression Profile.
Taken together, these results suggest that the gene-expressionprofiles of BRCA1-mutation–positive and BRCA2-mutation–positivetumors are generally distinctive and differ from each otheras well as from those of sporadic tumors. However, identificationof the BRCA2-mutation–positive and BRCA2-mutation–negativetumors was less accurate than the identification of BRCA1-mutation–positiveand BRCA1-mutation–negative tumors. Of the three samplesthat were misclassified in the BRCA2 classification, two hadthe earliest truncating mutation among the eight BRCA2 mutationsidentified in the study (Table 1), and the other came from aman with breast cancer. The gene-expression profile of his BRCA2-mutation–positivetumor was very similar to the profiles of the other such tumors,but the expression of a small subgroup of genes could have causedthe misclassification.
Figure 3 shows the way in which we identified the genes thatare most important in distinguishing a BRCA1-mutation–positivebreast cancer from a BRCA2-mutation–positive breast cancer.A total of 176 such genes were identified by all three statisticalmethods (modified t-test, weighted gene analysis, and mutual-informationscoring). This list shows that BRCA1 and BRCA2 tumors differsignificantly in their gene-expression profiles. Within thislist is a large block of genes (shown in red in Figure 3A) thatare up-regulated in BRCA1-mutation–positive samples butnot in BRCA2-mutation–positive samples. Examination ofindividual genes in this block suggests the coordinated transcriptionalactivation of two major cellular processes in BRCA1-mutation–positivesamples: DNA repair and apoptosis. DNA-repair pathways are reflectedby genes (e.g., MSH2)33 that participate in the activation ofcellular responses to stress. In addition, BRCA1-mutation–positivetumors display increased expression of genes associated withinducing apoptosis (e.g., PDCD5)34 and decreased expressionof genes involved in suppressing apoptosis (e.g., CTGF ).35
Figure 3. Analysis of Genes Discriminating Breast Cancers with BRCA1 Mutations from Those with BRCA2 Mutations.
Three statistical methods were used to generate lists of genes that discriminate between the BRCA1-mutation–positive and BRCA2-mutation–positive breast tumors; the three lists were then combined into a consensus list consisting of 176 genes. Panel A shows the BRCA1-mutation–positive and BRCA2-mutation–positive samples of breast-cancer tissue with regard to the level of expression of the 176 genes on the consensus list. Panel B shows the resulting multidimensional-scaling plot; it illustrates the ability of these 176 genes to separate BRCA1-mutation–positive tumors (blue circles) from BRCA2-mutation–positive tumors (tan circles). Panel C shows the results of staining of tissue microarrays with antibodies against cyclin D1 and MEK-1. The average nuclear intensity is considered to be 0 in the absence of staining, 1 in the presence of weak staining, 2 in the presence of moderate staining, and 3 in the presence of strong staining. Each analysis included 23 BRCA1-mutation–positive samples and 17 BRCA2-mutation–positive samples. Each tumor was represented on the array by two cores; the agreement in scores between each pair was high as measured by a weighted kappa statistic. The Wilcoxon–Mann–Whitney test was used to test for differences between BRCA1-mutation–positive and BRCA2-mutation–positive tissues (with use of the mean score for both cores). P values are two-sided and exact. The specimens used in the analysis of cDNA microarrays and the tumor-microarray analyses differed but were from the same institution (Lund University Hospital).
This finding suggests that the mutation of BRCA1 leads to aconstitutive stress-type state. The cellular response to damagedDNA is complex and includes the activation of "checkpoints"in the cell cycle, DNA repair, and changes in gene transcription— all these functions involve the proteins encoded byBRCA1 and BRCA2.15 The finding that BRCA1-mutation–positivetumors have increased expression of genes involved in a responseto stress should provide further insight into the differentfunctions of the two genes.
High-Density Tissue Microarrays
A high-density microarray of breast-cancer tissue (Figure 1Dand Figure 1E)23 was used to determine whether levels of proteinsencoded by selected genes (as measured by immunohistochemicalanalysis) correlate with the cDNA microarray results. Figure 3Cillustrates the results for two genes (encoding cyclin D1and mitogen-activated protein kinase kinase 1 [MEK-1]) againsta microarray containing 113 breast-cancer specimens obtainedfrom the same referring hospital that provided all the samplesused in cDNA-microarray analyses.
The intensity of staining for cyclin D1 differed significantly(P<0.001): BRCA2-mutation–positive tumors displayedmore intense staining than BRCA1-mutation–positive tumors,a finding that is consistent with the expression of cyclin D1in cDNA-microarray experiments (P<0.001 by the t-test) (Figure 3C).As expected, the negative control MEK-1, the gene for whichwas not on the consensus gene list, had similar levels of expressionin the two types of tumors (P=0.23) (Figure 3C and http://www.nhgri.nih.gov/DIR/Microarray).
Effect of DNA Methylation on Gene Expression
In our analysis, only one tumor (from Patient 20, who had sporadicbreast cancer) was misclassified as positive for a BRCA1 mutation(Table 2 and Figure 2C). As compared with the specimens fromthe other six patients with sporadic breast cancer, this specimenhad a markedly reduced level of expression of BRCA1, perhapsbecause of an unrecognized mutation of BRCA1 in this patient.On further investigation, the tumor was found to have phenotypiccharacteristics (e.g., negativity for estrogen receptors, ahigh grade, and a ductal location) that were consistent withthe common clinical and pathological profiles of a BRCA1-mutation–positivebreast cancer.
On approval by the institutional review board, the patient wascontacted and agreed to be tested for a germ-line mutation inBRCA1. Using sequence-based mutation analysis and a chip-basedsystem of mutation detection,36 we found no mutation in theBRCA1 gene. We then analyzed the BRCA1 promoter region for aberrantmethylation, which is known to silence BRCA1 in sporadic cancerswith no mutations in the gene.24,37 Testing (in a blinded fashion)of all specimens of sporadic tumors from our study indicatedthat the misclassified tumor (from Patient 20) was the onlyone with hypermethylation of the BRCA1 promoter region, indicativeof the inactivation of BRCA1 (Figure 4). This result was corroboratedby the finding that this tumor exhibited by far the lowest levelof BRCA1 messenger RNA of all the samples in the study.
Figure 4. Methylation Analysis of the BRCA1 Promoter Region in Tumor Samples from Seven Patients with Sporadic Breast Cancer.
A methylation-specific polymerase-chain-reaction assay was used to distinguish unmethylated alleles (U) from methylated alleles (M) of BRCA1 on the basis of sequence changes produced by treating DNA with bisulfite, which converts unmethylated (but not methylated) cytosines to uracil, followed by a polymerase-chain-reaction assay involving primers designed for either methylated or unmethylated DNA.24 The methylated product is 75 bp long, and the unmethylated product is 86 bp. DNA from normal lymphocytes was used as a negative control, and in vitro methylated DNA was used as a positive control.
Discussion
Studies of the pathological features of breast cancer suggestthat cancers with underlying germ-line mutations in BRCA1 andBRCA2 differ from each other and from cancers that do not carrythese mutations.10,26 However, methods to classify these cancerson the basis of such features have been prone to error and subjectiveinterpretation. Our study, although limited in terms of thenumber of specimens, indicates that gene-expression technologycan increase the specificity of the molecular classificationof breast cancer.
Early reports suggested that there is a loss of estrogen andprogesterone receptors in tumors with BRCA1 mutations,11,12,13,14whereas tumors with BRCA2 mutations are more variable in thisrespect but often have such receptors.11 For this reason, someof the differences we found in the levels of expression of variousgenes between BRCA1-mutation–positive and BRCA2-mutation–positivebreast cancers are probably due to differences in the geneswhose expression is associated with these receptors. Nevertheless,these differences cannot explain all the findings. For example,one breast-cancer sample with a BRCA2 mutation lacked estrogenand progesterone receptors, yet its gene-expression profilewas very similar to those of the receptor-positive cancer specimenswith BRCA2 mutations. Also, many of the genes that were differentiallyexpressed in receptor-positive and receptor-negative sporadictumors did not distinguish between BRCA1-mutation–positiveor BRCA2-mutation–positive tumors. Conversely, many ofthe genes that identified hereditary breast cancers were unableto separate receptor-positive from receptor-negative sporadicbreast cancers. These results, together with those of a recentlypublished study by Perou et al.,38 indicate that cDNA microarrayscan readily distinguish estrogen-receptor–positive fromestrogen-receptor–negative sporadic breast tumors.
We used several statistical approaches to evaluate the patternsof gene expression in the breast-cancer specimens. Of the 22specimens that we studied, the class-prediction method misclassifiedone sporadic tumor as positive for a BRCA1 mutation, three BRCA2-mutation–positivesamples as negative for a BRCA2 mutation, and one tumor sampleas positive for a BRCA2 mutation. The different patterns ofgene expression among the three types of breast cancer on microarrayanalyses therefore represent useful ways of distinguishing thesetypes, but the method is clearly imprecise in determining thepresence or absence of BRCA2 mutations. The use of microarrayscovering a larger proportion of the genome and the analysisof larger numbers of tumors may make possible a more precisemolecular classification of breast cancer.
Our finding that a case of sporadic breast cancer appeared toarise from a BRCA1 mutation prompted us to investigate the mechanismof the inactivation of this gene in this specimen. We foundthat the down-regulation of the expression of BRCA1 in thistumor was associated with hypermethylation of the promoter region.This suggests that cDNA microarrays may be of use in identifyingsporadic breast tumors with a phenotype resembling that of aBRCA1-mutation–positive breast cancer.37 This unexpectedfinding prompted consideration of whether to contact the patientto request that she undergo testing for BRCA1 mutations.
The institutional review boards of the participating centersinitially waived the requirement to obtain the patients' consentto use these specimens, with the stipulation that the investigatorswould not contact subjects with the results. This approach wasimplemented to avoid providing results to subjects without theirprior consent to receive results. The investigators and theinstitutional review boards evaluated this unanticipated finding,noting that patients with breast cancer who have a BRCA1 mutationare at greater risk for ovarian cancer and breast cancer inthe contralateral breast than patients with breast cancer whodo not have a BRCA1 mutation39 and that preventive surgery (oophorectomyand mastectomy) might increase the life expectancy of such patients.40In addition, further research to determine why this sporadicbreast tumor had a gene-expression profile similar to that ofthe BRCA1-mutation–positive samples might improve ourunderstanding of breast cancer.
The institutional review boards agreed that the patient couldbe contacted to disclose the finding and request that she undergofurther evaluation but asked that her primary physician makethe final decision and be the initial conveyor of the information.The primary physician's established relationship with the patientplaced him in the best position to weigh the clinical benefitsand the harm of conveying this information. To avoid similarproblems in future studies in which personal identifiers areretained, obtaining subjects' consent to be contacted in theevent of a relevant finding should be strongly considered. Oneapproach would be to incorporate such explicit consent in thesurgical consent process. Whenever there appears to be a compellingneed to contact a subject for clinical reasons, this decisionshould involve both the institutional review boards and thesubject's physician.
Perhaps the most striking finding of our study is that tumorsamples from patients with germ-line mutations in BRCA1 andthose from patients with such mutations in BRCA2 differ significantlyin their global patterns of gene expression, even though bothmutant genes lead to breast and ovarian cancer. Study of themolecular differences between these cancers may improve ourunderstanding of the way in which pathologically different breastcancers arise in carriers of BRCA1 or BRCA2 mutations. Our resultsindicate that a heritable mutation influences the gene-expressionprofile of a tumor.
Supported by grants from the Swedish Cancer Society, the NordicCancer Union, Mrs. Berta Kamprad's Foundation, the G.A.E. NilssonFoundation, the Hospital of Lund Foundations, the F.M. BergquistFoundation, the King Gustav V Jubilee Foundation, and BreakthroughBreast Cancer.
We are indebted to Dr. Joseph Hacia for technical assistancewith the chip-based mutation analysis.
Source Information
From the Cancer Genetics Branch (I.H., D.D., Y.C., M.B., P.M., O.-P.K., J.T.) and the Medical Genetics Branch (B.W.), National Human Genome Research Institute, and the Division of Cancer Treatment and Diagnosis, National Cancer Institute (M.R., R.S.), National Institutes of Health, Bethesda, Md.; the Department of Oncology, University of Lund, Lund, Sweden (I.H., Å.B.); the Department of Pathology, Western Infirmary, University of Glasgow, Glasgow, Scotland (B.G.); and the Division of Tumor Biology, Johns Hopkins Oncology Center, Baltimore (M.E.).
Address reprint requests to Dr. Trent at the National Human Genome Research Institute, National Institutes of Health, Bldg. 49, Rm. 4A22, Bethesda, MD 20892-4470, or at jtrent{at}nih.gov.
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=0.001) whose variation in expression among all experiments best differentiated among these types of cancers. The multidimensional-scaling plot of the 22 samples from patients with primary breast cancer and 2 samples of normal mammary epithelial cells that included all 3226 genes that met the criteria for inclusion is shown in Figure 2B. The multidimensional-scaling plot of the 22 samples from patients with primary breast cancer that included the 51 genes that best differentiated among the three types of tumors is shown in Figure 2C. 
