Laura C Hautala

Dario Greco

Riitta Koistinen

Tuomas Heikkinen

Päivi Heikkilä

Kristiina Aittomäki

Carl Blomqvist

Hannu Koistinen

Heli Nevanlinna
email: heli.nevanlinna@hus.fi

Glycodelin expression associates with differential tumour phenotype and outcome in sporadic and familial non-/ breast cancer patients

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Glycodelin (encoded by PAEP gene) is a secreted lipocalin protein mainly expressed in reproductive tissues [START_REF] Seppälä | Glycodelin: a major lipocalin protein of the reproductive axis with diverse actions in cell recognition and differentiation[END_REF]. It is also found in bone marrow and in many different glandular tissues of the human body. In the uterus, glycodelin is secreted in response to progesterone exposure from the endometrial glands during the secretory phase of the menstrual cycle [START_REF] Seppälä | Glycodelin: a major lipocalin protein of the reproductive axis with diverse actions in cell recognition and differentiation[END_REF]. In males, a differentially glycosylated form of glycodelin is expressed in the seminal vesicles [START_REF] Morris | Gender-specific glycosylation of human glycodelin affects its contraceptive activity[END_REF]. Different glycoforms of glycodelin play important roles in regulation of sperm function [START_REF] Yeung | Effects of glycodelins on functional competence of spermatozoa[END_REF]. Furthermore, glycodelin has immunosuppressive properties, which are thought to protect fetal semiallograft from maternal immune response [START_REF] Alok | The role of glycodelin as an immune-modulating agent at the feto-maternal interface[END_REF][START_REF] Seppälä | Glycodelin in reproductive endocrinology and hormone-related cancer[END_REF].

Several studies have shown that glycodelin is not only associated with differentiated epithelium, but it also induces cell differentiation in endometrial and breast cancer cells [START_REF] Seppälä | Glycodelin in reproductive endocrinology and hormone-related cancer[END_REF][START_REF] Kamäräinen | Expression of glycodelin in MCF-7 breast cancer cells induces differentiation into organized acinar epithelium[END_REF][START_REF] Hautala | Glycodelin reduces breast cancer xenograft growth in vivo[END_REF][START_REF] Koistinen | Glycodelin reduces carcinoma-associated gene expression in endometrial adenocarcinoma cells[END_REF][START_REF] Uchida | Histone deacetylase inhibitors induce differentiation of human endometrial adenocarcinoma cells through up-regulation of glycodelin[END_REF][START_REF] Ohta | Glycodelin blocks progression to S phase and inhibits cell growth: a possible progesterone-induced regulator for endometrial epithelial cell growth Gycodelin inhibits G1/S progression[END_REF][START_REF] Koistinen | The role of glycodelin in cell differentiation and tumor growth[END_REF]. Glycodelin differentiates MCF-7 breast cancer cells towards normal, less malignant direction [START_REF] Kamäräinen | Expression of glycodelin in MCF-7 breast cancer cells induces differentiation into organized acinar epithelium[END_REF][START_REF] Hautala | Glycodelin reduces breast cancer xenograft growth in vivo[END_REF]. When grown in Matrigel basement membrane matrix, the cells expressing glycodelin formed spheroids with acini, while the control cells formed more irregular structures. At the same time, glycodelin expression induced changes in the expression of genes, e.g., CAV1 and FGF2, that are associated with normal mammary epithelium and inhibition of tumour growth [START_REF] Hautala | Glycodelin reduces breast cancer xenograft growth in vivo[END_REF]. In pre-clinical xenograft mouse model, the glycodelintransfected MCF-7 cells formed significantly smaller tumours than the control cells. In addition, the glycodelin expressing tumours had lower proliferation rate (according to staining] than the control tumours [START_REF] Hautala | Glycodelin reduces breast cancer xenograft growth in vivo[END_REF]. Thus, in hormone-related cancers, glycodelin is considered to be a tumour growth suppressing factor. Glycodelin has been found to be expressed in several tumour types, but to date its clinical significance is unknown. In ovarian cancer, glycodelin staining has been found to be associated with favourable prognosis [START_REF] Mandelin | Glycodelin in ovarian serous carcinoma: association with differentiation and survival[END_REF]. In breast, glycodelin is expressed both in normal epithelial and cancerous tissue, where it is localized in the cytoplasm [START_REF] Kämäräinen | Expression of glycodelin in human breast and breast cancer[END_REF]. In mucinous breast cancer, an additional diffuse staining of the surrounding mucin may also exist. Previously, the expression of glycodelin has been reported to be associated with non-metastatic breast tumours in a series of 38 tumours as well as oestrogen and progesterone receptor positive tumours in 121 invasive breast cancers [START_REF] Jeschke | Expression of glycodelin protein and mRNA in human ductal breast cancer carcinoma in situ, invasive ductal carcinomas, their lymph node and distant metastases, and ductal carcinomas with recurrence[END_REF][START_REF] Scholz | Immunohistochemical expression of glycodelin in breast cancer correlates with estrogen-receptor alpha and progesterone-receptor A positivity[END_REF]. However, a more extensive study is needed to elucidate the role of glycodelin expression in breast cancer. Furthermore, glycodelin expression has not yet been investigated in familial breast cancer. In this study, we evaluated the expression of glycodelin in extensive series of sporadic and familial breast cancers in order to investigate the association of glycodelin with clinicopathological features of the tumours and the outcome in breast cancer, also with respect of the familial background of the patients. We further used gene expression analysis of breast tumours to investigate correlation of gene expression profiles with the PAEP expression in sporadic and familial breast tumours.

Materials and methods

Patients

A series of 884 unselected breast cancer patients was recruited at the Department of Oncology, Helsinki University Central Hospital, during the years 1997-1998 and 2000 [START_REF] Syrjäkoski | Population-based study of BRCA1 and BRCA2 mutations in 1035 unselected Finnish breast cancer patients[END_REF][START_REF] Kilpivaara | Correlation of CHEK2 protein expression and c.1100delC mutation status with tumor characteristics among unselected breast cancer patients[END_REF]. An additional familial breast cancer patient series (N = 546) was recruited at the Departments of Oncology and Clinical Genetics [START_REF] Eerola | Familial breast cancer in southern Finland: how prevalent are breast cancer families and can we trust the family history reported by patients?[END_REF]. For the tissue microarrays, altogether 1356 invasive breast cancer tumours were available. Of these tumours, 423 were derived from patients who did not have a familial background of breast cancer (i.e. sporadic), 818 were from patients with family history and 56 from BRCA1 and 59 from BRCA2 mutation positive families. Of the cases with family history, 481 tumours were from patients with strong family history of breast cancer (at least three first or second degree relatives with breast or ovarian cancer, including the proband) and 337 with two affected first degree relatives (including the proband). BRCA1 and BRCA2 mutations had been screened from the familial patient series as previously described [START_REF] Vehmanen | Low proportion of BRCA1 and BRCA2 mutations in Finnish breast cancer families: evidence for additional susceptibility genes[END_REF][START_REF] Vahteristo | A probability model for predicting BRCA1 and BRCA2 mutations in breast and breast-ovarian cancer families[END_REF][START_REF] Vahteristo | A CHEK2 genetic variant contributing to a substantial fraction of familial breast cancer[END_REF].

The clinicopathological data of the patients, including tumour diameter, nodal status, distant metastasis and oestrogen receptor (ER) and progesterone receptor (PR) status, were collected from the pathology reports. In addition, all the tumours were re-evaluated for histological diagnosis and graded by a pathologist (P.H.). The grading was performed using the Scarff-Bloom-Richardson method, modified by Elston and Ellis [START_REF] Elston | Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term followup[END_REF]. The tissue microarray sections were immunohistochemically stained for p53 expression [START_REF] Tommiska | Breast cancer patients with p53 Pro72 homozygous genotype have a poorer survival[END_REF] and considered as positive when 20% or more of the cancer cells were positively stained. HER2 protein expression was analyzed by immunohistochemical staining (samples with <10% of the cancer cells stained were considered as negative and >90% as positive) and gene amplification by using chromogenic in situ hybridization (6 or more copies in a single nucleus was considered as positive result) [START_REF] Aaltonen | Familial breast cancers without mutations in BRCA1 or BRCA2 have low cyclin E and high cyclin D1 in contrast to cancers in BRCA mutation carriers[END_REF]. The HER2 gene amplification was considered as the primary result and when not available, the result from the immunohistochemical staining was used. The expression of Ki-67 was evaluated using Ki-67 antibody and the tumour was considered as strong positive if 30% or more of the cancer cells were stained, moderate if 20-29% stained, weak positive if 5-19% stained and negative if less than 5% of the cancer cells were stained [START_REF] Ahlin | Ki67 and cyclin A as prognostic factors in early breast cancer. What are the optimal cut-off values?[END_REF]. Cyclin D1 and cyclin E expressions were detected by immunohistochemical staining and evaluated as described by Aaltonen et al. [START_REF] Aaltonen | Familial breast cancers without mutations in BRCA1 or BRCA2 have low cyclin E and high cyclin D1 in contrast to cancers in BRCA mutation carriers[END_REF]. The tumours expressing cyclins above mean expression of all tumours (9.1% for cyclin D1 and 6.8% for cyclin E) were considered as high-expressing and those below mean as low-expressing tumours.

The tumours were further divided into subgroups by hormone receptor and HER2 status with 1) positive ER or PR status and no HER2 over-expression, 2) positive ER or PR status and HER2 overexpression, 3) HER2-positive, ER-and PR-negative tumours and 4) triple-negative tumours (for ER, PR and HER2 status) as previously described [START_REF] Heikkinen | The breast cancer susceptibility mutation PALB2 1592delT is associated with an aggressive tumor phenotype[END_REF][START_REF] Blows | Subtyping of breast ca ncer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies[END_REF]. The patient and tumour characteristics are shown in Supplementary Table 1.

A total of 1356 invasive tumours were scored for glycodelin staining. The median age of the patients at diagnosis was 54 years (range 22-96 years). For survival analysis, the 10-year breast cancer-specific survival was defined as the time from the date of diagnosis to the date of death due to breast cancer and for the 5-year metastasis-free survival as the time from the date of diagnosis to the date of detection of distant metastasis. Information on death due to breast cancer was obtained from the Finnish Cancer Registry and on distant metastasis from the patient records. The median follow-up time was 109 months (range 1-540 months). Of all the 1098 patients in the survival analysis, 179 died from breast cancer and 193 relapsed with distant metastases during the follow-up time of 10 or 5 years, respectively.

This research was approved by the Ethics Committee of the Helsinki University Central

Hospital and the Ministry of Social Affairs and Health in Finland. The study was performed according to reporting recommendations for tumour marker prognostic study (REMARK) [START_REF] Mcshane | Reporting recommendations for tumor marker prognostic studies[END_REF].

Immunohistochemical analysis of glycodelin on tissue microarrays

Tissue microarrays were constructed as previously described [START_REF] Tommiska | Breast cancer patients with p53 Pro72 homozygous genotype have a poorer survival[END_REF][START_REF] Eerola | Relationship of patients' age to histopathological features of breast tumours in BRCA1 and BRCA2 and mutation-negative breast cancer families[END_REF]. Briefly, haematoxylin and eosin stained sections of the paraffin-embedded tumours were screened and the morphologically most representative sites of the tumours were selected by a pathologist (P.H.). Four tissue cores (0.6 mm in diameter) from these regions of each donor block were transferred into the recipient block. Five µm thick sections were cut from the tissue microarray blocks and placed onto glass slides. For immunohistochemical staining, the tissue microarray sections were deparaffinised. To enhance the antigen retrieval the sections were incubated in citrate buffer (pH 6.0) in a microwave oven for 10 minutes. Rabbit (#1) antiglycodelin IgG [START_REF] Mandelin | Glycodelin in ovarian serous carcinoma: association with differentiation and survival[END_REF] was used as the primary antibody (3.0 µg/ml) and the IgG fraction from proimmune serum of the same rabbit (3.0 µg/ml) was used as a negative control. Biotinylated swine anti-rabbit immunoglobulin E0353 (DAKOCytomation, Glostrup, Denmark) was used as the secondary antibody. Inactivation of the endogenous peroxidase was carried out using 2% H 2 O 2 in methanol. ABC complex (Vectastain ® ABC kit, Vectorlaboratories Inc., Burlingame, CA) detection system and AEC+ high sensitivity chromogen (DAKO, Carpinteria, CA) were used for antigen detection. Counterstaining was performed with Mayer's haematoxylin (Reagena, Kuopio, Finland). Glycodelin staining was scored either negative or positive by two observers (L.H. and R.K.).

Statistical analyses

The data was analyzed using SPSS for Windows v15.0 (SPSS Inc., Chicago, IL). The correlation of the glycodelin expression with different variables was done using Pearson's chi-square (χ 2 ) test. When one or more groups had less than five cases, the Fisher's exact test was used. Kaplan-Mayer survival analysis and log-rank test were used to estimate the effect of glycodelin expression on 10-year breast cancer-specific and 5-year metastasis-free survival rates of different patient series. Cox's proportional hazards regression model (backward stepwise, 95% CI) was used to estimate the association of glycodelin expressio n with survival and also to multivariate comparison of hazard ratios after adjusting for other prognostic factors (tumour diameter, nodal status, distant metastases, grade, and expression of oestrogen and progesterone receptors, Ki-67, p53, HER2). Glycodelin was considered as a categorical variable. To account for the multiple clinicopathological variables tested, P-values < 0.01 were considered significant. All P-values are two-sided.

Microarray data analysis

Total RNA was extracted from 64 familial non-BRCA1/2 and 106 sporadic primary breast cancer tumours (D. Greco et al, in preparation). The samples were labelled and hybridized to HumanHT-12 v3 Expression BeadChips (Illumina, San Diego, CA), containing 24660 Entrez Gene entities, according to the instructions provided by the manufacturer (http://www.illumina.com). After hybridization, the arrays were washed and scanned as recommended by the manufacturer.

Microarray raw data were imported into R (http://cran.r-project.org) and processed by the methods included in the BioConductor facilities [START_REF] Gentleman | Bioconductor: open software development for computational biology and bioinformatics[END_REF]. Briefly, after quality control [START_REF] Du | lumi: a pipeline for processing Illumina microarray[END_REF], the data was normalized using the quantile method [START_REF] Bolstad | A comparison of normalization methods for high density oligonucleotide array data based on variance and bias[END_REF] and the gene expression matrix was obtained by averaging the probes mapping to the same Entrez Gene IDs [START_REF] Tatusova | Genomic databases and resources at the national center for biotechnology information[END_REF]. The Pearson's correlation of each gene expression profile with the expression of glycodelin (PAEP) was calculated and the nominal P-values were estimated for the familial and the sporadic breast tumours separately. The genes with correlation P-value < 0.01 were further analyzed.

Functional annotation was performed on the PAEP-correlated gene lists using the DAVID annotation tools [START_REF] Huang Da | Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources[END_REF]. The categories with Fisher's exact test P-value < 0.05 were considered to be significantly enriched.

Results

Altogether, 1222 samples were scored for glycodelin staining. The remaining 10% (N = 134) of the samples were not analyzed due to either unrepresentative or missing tissue samples. Of the analyzed samples, 399 were from the sporadic series, 746 samples were from familial non-BRCA1/2 patients, of which 436 had strong family history and 310 had two affected first degree relatives, and 38 were BRCA1 and 39 BRCA2 mutation positive. Of all analyzed samples, 26% were positive for glycodelin expression. In sporadic and familial non-BRCA1/2 series with either two affected first degree relatives or strong family history the glycodelin staining was positive in 22%, 34% and 25% of the cases, respectively. The numbers of cases included in different analyses are shown in Supplementary Table 2.

In the sporadic series, the glycodelin expression was significantly associated with low proliferation rate (P < 0.001), with also a tendency towards low grade (grades 1 and 2) tumours (P = 0.012; Table 1) and high cyclin D1 (P = 0.034) expression. The expression of glycodelin was not significantly associated either with 10-year breast cancer-specific [cumulative survival (CS) = 80.6% vs. 80.6% for cases with glycodelin-positive vs. -negative tumours, P = 0.990] or 5-year metastasis-free survival of the patients (CS = 77.1% vs. 81.1% for cases with glycodelin-positive vs. -negative tumours, P = 0.478; Fig. 1a andb). Similarly, glycodelin expression had no significant effect on survival when the analysis was stratified by different systemic adjuvant therapy (Supplementary Table 3).

In the familial non-BRCA1/2 patient series with strong family history, the expression of glycodelin was associated with positive nodal status (P = 0.003) and positive HER2 status (P = 0.009; Table 1). Moreover, the expression of glycodelin was associated with the subgroup of HER2-positive, ER-and PR-negative tumours (P = 0.009). The expression of glycodelin was also associated with poor 10-year breast cancer-specific and 5-year metastasis-free survival rates of the patients (CS = 76.8% vs. 86.1% for cases with glycodelin-positive vs.negative tumours, P = 0.030 and CS = 73.0% vs. 86.3%, P = 0.001, respectively; Fig 1c andd). The survival effect by glycodelin expression was not influenced by different systemic adjuvant therapy (Supplementary Table 3).

In univariate analysis performed with Cox's regression model, glycodelin expression was associated with increased risk for death due to breast cancer (HR = 1.78, 95% CI = 1.05-3.02, P = 0,032) and distant metastasis (HR = 2.24, 95% CI = 1.37-3.66, P = 0.001) (Table 2a).

Furthermore, the multivariate analysis on 5-year metastasis-free survival showed that glycodelin was an independent predictor of distant metastasis (HR = 2.22, 95% CI = 1.22-4.03, P = 0.009). In addition to glycodelin, large tumour diameter, positive nodal status, negative ER status and high Ki-67 expression were independent prognostic factors in the analysis in the familial non-BRCA1/2 breast cancer patient series (Table 2b).

In the tumours from familial non-BRCA1/2 patients having only two affected first degree relatives, glycodelin expression was marginally associated with positive nodal status (P = 0.018) as was seen also in the familial patient series with strong family history. Glycodelin expression did not significantly associate with either the 10-year breast cancer-specific or the 5-year metastasis-free survival rates of the patients (CS = 83.7%, 95% CI = 0.74-0.86 vs. CS =80.3%, 95% CI = 0.74-0.93 for cases with glycodelin-positive vs. -negative tumours, P = 0.454 and CS = 85.3%, 95% CI = 0.75-0.87 vs. CS = 80.9%, 95% CI = 0.78-0.92, P = 0.378, respectively). No significant association of glycodelin expression with any clinico pathological features in patient series with BRCA1 or BRCA2 mutation (N = 38 and N = 39, respectively) was detected (data not shown).

In the gene expression analysis, a total of 267 and 109 gene expression profiles were found to be correlated with the PAEP expression with P-value < 0.01 in sporadic and familial non-BRCA1/2 tumours, respectively. Of these, 3 genes were found in both groups (PAEP, OR4F15 and ATP6V1B1; Supplementary Table 4 and Supplementary Table 5). The genes whose expression correlated with PAEP expression were enriched in 13 and 49 biological themes (i.e. terms, Table 3) in familial non-BRCA1/2 and sporadic tumours, respectively. None of these themes were present in both sporadic and familial non-BRCA1/2 groups.

Discussion

To date, this is the largest study evaluating the association of glycodelin expression with tumour phenotype and outcome in breast cancer patients, as well as the first to specifically investigate the glycodelin expression on familial non-BRCA1/2 breast tumours. We found that, in sporadic breast cancer patients, glycodelin expression was associated with a nonaggressive tumour phenotype with low proliferation rate and a tendency towards welldifferentiated tumours. This is in keeping with previous studies showing that glycodelin is associated with well-differentiated tumours having negative lymph node status [START_REF] Jeschke | Expression of glycodelin protein and mRNA in human ductal breast cancer carcinoma in situ, invasive ductal carcinomas, their lymph node and distant metastases, and ductal carcinomas with recurrence[END_REF].

However, in the breast cancers of patients with strong family history glycodelin expression was associated with a less favourable phenotype of positive lymph node and HER2 status. Furthermore, glycodelin expression was also an independent prognostic factor with over twofold increased risk of distant metastasis for breast cancer patients in BRCA1/2-mutation negative breast cancer families.

In the sporadic series, the association of glycodelin with low proliferation rate and tendency towards well-differentiated tumours is in keeping with our previous pre-clinical mouse model study showing that the glycodelin-transfected MCF-7 human breast carcinoma cells form significantly smaller tumours and express less Ki-67 than the control tumours and that glycodelin induces cancer cell differentiation towards non-malignant direction [START_REF] Hautala | Glycodelin reduces breast cancer xenograft growth in vivo[END_REF].

Furthermore, the expression of glycodelin in ER-positive MCF-7 breast cancer xenograft tumours decreased cyclin D1 levels [START_REF] Hautala | Glycodelin reduces breast cancer xenograft growth in vivo[END_REF]. In human breast cancer, we have previously shown that high cyclin D1 expression associates with high proliferation rate in ER-positive, but with low proliferation rate in ER-negative breast cancer [START_REF] Aaltonen | Cyclin D1 expression is associated with poor prognostic features in estrogen receptor positive breast cancer[END_REF]. In this study, positive glycodelin expression associated marginally with high cyclin D1 expression and the association was seen only in ER-positive tumours (P = 0.048; data not shown). The number of ER-negative tumours was relatively small, which might make it more difficult to reach statistical significance.

However, in familial non-BRCA1/2 tumours of the patients with strong family history, glycodelin expression was associated with a less favourable phenotype, i.e. lymph node positive tumours, and ER-or PR-positive and HER2-positive tumours which phenotype has been shown to associate with worst long term survival in breast cancer [START_REF] Blows | Subtyping of breast ca ncer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies[END_REF]. Furthermore, patients with glycodelin-positive tumours had reduced 5-year metastasis-free survival also when adjusted for other conventional prognostic factors. Inte restingly, contrary to breast cancer cells in vitro, in melanoma cells glycodelin transfection has been found to cause more aggressive phenotype [START_REF] Ren | Functional characterization of the progestagenassociated endometrial protein gene in human melanoma[END_REF]. The association of glycodelin expression with the less favourable tumour phenotype and poor survival in familial non-BRCA1/2 cases with a strong family history is intriguing and suggests that in breast cancer families the tumour phenotype and survival may be affected by genetic factors underlying the genetic predisposition to breast cancer. Such effects may lead to different, still unknown, molecular mechanisms, which regulate glycodelin expression or alter its effects and may lead to differential progression pathway(s) with effect also on survival. This hypothesis is supported by the gene expression analysis which revealed different gene expression profiles correlating with the PAEP expression in the sporadic and familial non-BRCA1/2 breast cancers. Furthermore, these genes were enriched in different biological themes based on their functions. We have previously found also differential expression of cyclin E and D1 in sporadic and familial breast tumours and shown that cyclin E and D1 expression distinguishes familial non-BRCA1/2 tumours both from sporadic, and BRCA1-and BRCA2-associated tumours [START_REF] Aaltonen | Familial breast cancers without mutations in BRCA1 or BRCA2 have low cyclin E and high cyclin D1 in contrast to cancers in BRCA mutation carriers[END_REF].

Tumours from especially BRCA1 but to some extent also BRCA2 mutation carriers display distinct tumour characteristics and gene expression or genomic copy number patterns and associate predominantly with the basal or luminal A or B subtypes, respectively. Some studies have also shown phenotypic and genomic characteristics for non-BRCA1/2 breast tumours although this group of tumours is heterogeneous at large and fall in similar intrinsic subtypes as also the sporadic breast tumours [START_REF] Palacios | The molecular pathology of hereditary breast cancer[END_REF][START_REF] Melchor | An integrative hypothesis about the origin and development of sporadic and familial breast cancer subtypes[END_REF][START_REF] Waddell | Subtypes of familial breast tumours revealed by expression and copy number profiling[END_REF]. This is consistent with the heterogeneous genetic background in the non-BRCA1/2 familial breast cancer which may result from joint effects of multiple low penetrance alleles or a large number of rare mutations with moderate or even high penetrance [START_REF] Fletcher | Architecture of inherited susceptibility to common cancer[END_REF][START_REF] Meindl | Germline mutations in breast and ovarian cancer pedigrees establish RAD51C as a human cancer susceptibility gene[END_REF]. However, the results derived from defined breast cancer families, like the different gene expression profiles correlating with the PAEP expression in the sporadic and familial non-BRCA1/2 breast cancers in the present study may reflect the different predisposition and pathogenesis in the familial breast tumours, suggesting also distinct genetic background and progression pathways in familial, non-BRCA1/2 breast cancer.

In conclusion, we have shown that glycodelin expression is associated with a less aggressive tumour phenotype in sporadic breast cancer patients, while in familial non-BRCA1/2 breast cancer patients glycodelin associated with a less favo urable tumour phenotype and was an independent predictor of distant metastasis for breast cancer patients in BRCA1/2-mutation negative breast cancer families. Gene expression analysis further revealed different gene expression profiles correlating with the PAEP expression in the sporadic and familial non-BRCA1/2 breast cancers. These findings suggest differential progression pathways in the sporadic and familial non-BRCA1/2 breast tumours expressing glycodelin and provide insight into the genes and biological themes associated with PAEP expression in the sporadic and familial breast cancer.

Fig. 1

 1 Fig. 1 Kaplan-Meier cumulative survival curves of (a, b) sporadic and (c, d) familial non-

Table 1

 1 Association of glycodelin expression with the clinicopathological features in the tumours of sporadic and familial non-BRCA1/2 patient series T, tumour size; N, nodal sta tus; M, pri ma ry metastasis; Gd, gl ycodelin; OR, odds ra tio.

			Sporadic series			Familial non-BRCA1/2 series
		Gd neg	Gd pos			Gd neg	Gd pos
	Category	N (%)	N (%)	P	OR (95% CI)	N (%)	N (%)	P	OR (95% CI)
	T
	1	167 (54.6) 56 (62.9) 0.162 0.71 (0.44-1.15)	209 (65.3) 64 (59.3) 0.258 1.29 (0.83-2.03)
	2	121 (39.5) 27 (30.3) 1 vs. 2, 3, and 4	93 (29.1) 37 (34.3) 1 vs. 2, 3, and 4
	3	6 (2.0)	3 (3.4)			8 (2.5)	5 (4.6)
	4	12 (3.9)	3 (3.4)			10 (3.1)	2 (1.9)
	N
	neg	160 (52.3) 45 (50.6) 0.774 1.07 (0.67-1.72)	203 (63.4) 50 (47.2) 0.003 1.94 (1.25-3.03)
	pos	146 (47.7) 44 (49.4)			117 (36.6) 56 (52.8)
	M
	neg	299 (96.5) 85 (95.5) 0.752 1.28 (0.40-4.12)	315 (98.4) 106 (98.1) 1.000 1.19 (0.23-6.22)
	pos	11 (3.5)	4 (4.5)			5 (1.6)	2 (1.9)
	ER
	neg	59 (19.4) 12 (13.6) 0.216 0.66 (0.33-1.28)	71 (23.7) 18 (17.6) 0.201 0.69 (0.39-1.22)
	pos	245 (80.6) 76 (86.4)			228 (76.3) 84 (82.4)
	PR
	neg	99 (32.5) 22 (25.0) 0.182 0.69 (0.40-1.19)	98 (32.9) 37 (37.0) 0.452 1.20 (0.75-1.92)
	pos	206 (67.5) 66 (75.0)			200 (67.1) 63 (63.0)
	Grade
	1	70 (22.8) 28 (31.8) 0.012 0.48 (0.27-0.86)	75 (23.7) 27 (25.2) 0.689 0.90 (0.55-1.49)
	2	135 (44.0) 43 (48.9) 1 and 2 vs. 3	155 (49.1) 53 (49.5) 1 and 2 vs. 3
	3	102 (33.2) 17 (19.3)			86 (27.2) 27 (25.2)
	Histology
	Ductal	216 (69.7) 67 (75.3) 0.305 1.33 (0.77-2.27)	230 (70.3) 79 (72.5) 0.670 1.11 (0.69-1.80)
	Lobular	52 (16.8) 11 (12.4) Ductal vs. non-ductal	66 (20.2) 20 (18.3) Ductal vs. non-ductal
	M edullar	2 (0.6)	0 (0.0)	0.314 0.70 (0.35-1.41)	7 (2.1)	0 (0.0) 0.677 0.89 (0.51-1.55)
	Other	40 (12.9) 11 (12.4) Lobular vs. non-lobular	24 (7.3)	10 (9.2) Lobular vs. non-lobular
	p53
	neg	231 (80.2) 71 (86.6) 0.188 0.63 (0.31-1.26)	252 (80.0) 84 (77.8) 0.622 1.14 (0.67-1.94)
	pos	57 (19.8) 11 (13.4)			63 (20.0) 24 (22.2)
	HER2
	neg	261 (87.6) 74 (85.1) 0.537 1.24 (0.63-2.45)	284 (91.0) 84 (81.6) 0.009 2.29 (1.22-4.31)
	pos	37 (12.4) 13 (14.9)			28 (9.0)	19 (18.4)
	Ki-67
	0 (<5%)	57 (18.9) 23 (25.8) <0.001 0.37 (0.21-0.64)	96 (29.8) 33 (30.6) 0.102 1.48 (0.92-2.36)
	1 (5-19%)	123 (40.3) 48 (53.9) 0 and 1 vs. 2 and 3	142 (44.1) 38 (35.2) 0 and 1 vs. 2 and 3
	2 (20-29%)	64 (21.0) 11 (12.4)			41 (12.7) 22 (20.4)
	3 (≥30%)	61 (20.0) 7 (7.9)			43 (13.4) 15 (13.9)
	Type
	ER/PR pos,
	HER2 neg	218 (74.7) 68 (79.1) 0.946 0.97 (0.38-2.48)	210 (73.9) 70 (72.2) 0.009 2.65 (1.25-5.60)
	ER/PR pos,			ER/PR pos, HER2 pos vs.			ER/PR pos, HER2 pos vs,
	HER2 pos	21 (7.2)	6 (7.0) other		17 (6.0)	14 (14.4) other
	ER/PR neg,
	HER2 pos	16 (5.5)	7 (8.1)	0.075 0.43 (0.16-1.12)	10 (3.5)	5 (5.2) 0.044 0.45 (0.21-1.00)
	Triple-neg	37 (12.7) 5 (5.8) Triple-neg vs. other	47 (16.5)	8 (8.2) Triple-neg vs. other
	Cyclin E
	high	63 (21.5) 14 (16.9) 0.356 0.74 (0.39-1.40)	34 (12.1) 10 (11.8) 0.934 0.97 (0.46-2.05)
	low	230 (78.5) 69 (83.1)			247 (87.9) 75 (88.2)
	Cyclin D1
	high	141 (48.0) 53 (60.9) 0.034 0.59 (0.36-0.96)	153 (54.3) 50 (60.2) 0.335 0.78 (0.48-1.29)
	low	153 (52.0) 34 (39.1)			129 (45.7) 33 (39.8)

Table 3

 3 Functional terms over-represented among the PAEP-correlated genes

	Familial non-BRCA1/2 tumours
	Category	Term

Acknowledge ments

We thank Drs. Kirsimari Aaltonen and Karl von Smitten and RN Hanna Jäntti for their help with the patient data and specimens. The Finnish Cancer Registry is gratefully acknowledged for the cancer data. This work was supported by Helsinki University Central Hospital Research Fund, Academy of Finland (132473, 135937), the Finnish Cancer Society, the Sigrid Juselius Foundation and Magnus Ehrnrooth Foundation.

Conflict of interest

The author declare no conflict of interest.


Mads Thomassen

Inge Søkilde Pedersen

Ida Vogel

Thomas V O Hansen

Charlotte Brasch-Andersen

Claus L Brasen

Dorthe Crüger

Lone Sunde

Finn C Nielsen

Uffe B Jensen

Charlotte Brasch- Andersen

Marie Luise Bisgaard

Åke Borg

Anne-Marie Gerdes

Torben A Kruse

A BRCA2 mutation incorrectly mapped in the original BRCA2

Keywords: hereditary breast cancer, BRCA2, 7845+1G>A, founder mutation, mutation age, SNP array, RT-PCR

établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Breast cancer is the most common female cancer in the western world affecting more than 10% of women. Approximately 5-10% of cases are believed to be inherited [1]. Germline mutations in the BRCA1 and BRCA2 genes predispose to breast and ovarian cancer and to a lesser extend to other cancers. The two genes have been used increasingly for clinical diagnostics and prognosis during the last 10-15 years. In Denmark, mutations in the two genes are identified in 28% of high risk families which is comparable to other western populations [2]. The relatively low frequency of mutations in the high risk families indicates the influence of other genes or insufficient analysis of BRCA1 and BRCA2. For example promoters and the majority of intron sequences are usually not analyzed and interpretation of variants in these regions is difficult. Even for variations located near the consensus AG and GT acceptor and donor splice sites, functional analyses are necessary to reveal splice defects. Furthermore, the applied techniques do not have 100% sensitivity, resulting in missed mutations. High quality cDNA and genomic reference sequences are essential to ensure correct interpretation of gene structure and clinical significance of identified variations. The mutational spectrum for BRCA1 and BRCA2 is wide and analysis of entire coding regions and flanking sequences is necessary in most populations. However, founder mutations are evident in isolated genetic populations like the inhabitants in Iceland [START_REF] Thorlacius | Study of a single BRCA2 mutation with high carrier frequency in a small population[END_REF], Norway [START_REF] Dorum | Three per cent of Norwegian ovarian cancers are caused by BRCA1 1675delA or 1135insA[END_REF], Greenland [START_REF] Hansen | A common Greenlandic Inuit BRCA1 RING domain founder mutation[END_REF] and among Ashkenazi Jews [START_REF] Abeliovich | The founder mutations 185delAG and 5382insC in BRCA1 and 6174delT in BRCA2 appear in 60% of ovarian cancer and 30% of early-onset breast cancer patients among Ashkenazi women[END_REF]. We have previously reported the mutational spectrum in BRCA1 and BRCA2 and only found weak indications of local founder mutations in Denmark [START_REF] Thomassen | BRCA1 and BRCA2 mutations in Danish families with hereditary breast and/or ovarian cancer[END_REF]. However, at that time a mutation in BRCA2 intron 15, was interpreted as likely non deleterious in most Danish laboratories because of an error in the mapping of the splice junction in the reference sequence. Here we have performed functional analysis of the mutation, and we have analyzed the prevalence and the geographical distribution of the mutation in Denmark and Southern Sweden in samples forwarded for mutation screening from departments of clinical genetics. Moreover, the genetic origin and the age of the mutation were addressed by haplotype analysis using dense SNP arrays.

Materials and methods

Mutation analysis BRCA1 and BRCA2 testing was requested after genetic risk assessment and counseling at the departments of clinical genetics. Blood samples were preferably collected from affected index persons. In some families no affected persons were alive and indirect testing was performed on a number of healthy relatives [START_REF] Cruger | Indirect' BRCA1/2 testing: a useful approach in hereditary breast and ovarian cancer families without a living affected relative[END_REF]. Mutation analysis of Danish samples was performed in 4 separate laboratories (Aalborg, Odense, Copenhagen, and Lund). Analysis of Swedish samples was performed in Lund. Mutation screening was performed by slightly different techniques, but most laboratories performed prescreening by DHPLC (denaturing high-performance liquid chromatography) and in some laboratories TGCE (Temperature Gradient Capillary Electrophoresis [START_REF] Li | Integrated platform for detection of DNA sequence variants using capillary array electrophoresis[END_REF]) and PTT (Protein Truncation Test [10]) followed by sequencing of relevant regions. MLPA (Multiplex Ligation dependent Probe Amplification) was used to identify large genomic rearrangements. As part of these screenings, the exon 15 region of BRCA2 was analyzed by MLPA, TGCE, DHPLC and/or sequencing.

Reverse transcriptase PCR Total RNA was extracted from blood from a carrier of 7845+1G>A using TRI reagent (Sigma) according to manufacturer's instructions. Random hexamer primed reverse transcription was carried out using SuperScriptIII (Invitrogen) at 50ºC for 60 min, according to manufacturer's instructions. Primers (c2EX14F: 5' GGA GGA AAA CAG ACA AAA GC 3' and c2EX16R: 5' CAT CCA CCA TCA GCC AAC 3') encompassing exon 15 of BRCA2 were designed. PCR was carried out using AmpliTaq DNA polymerase with GeneAmp10XPCR buffer II (Applied Biosystems) in the presence of 2 mM MgCl 2 under the following conditions: 95ºC for 2 min followed by 38 cycles of 95ºC for 30 s, 58ºC for 30 s and 72ºC for 60 s, and finally 72ºC for 2 min. The PCR products were sequenced in both directions using a 3130XL Genetic Analyzer (Applied Biosystems). To estimate the frequency of exon 15 skipping from the mutated allele, we used peak heights in positions in the sequence with dual base calls corresponding to exon 15 and 16 in the forward sequence and exon 14 and 15 in the reverse sequence. The fraction of loss was calculated as F = h2/(h2+(h1-h2)/2) were h1 and h2 are the heights of the two peaks in one position; h1 representing the base of the wild type allele and h2 representing the base of the mutated allele. This formula assumes equal expression of both alleles. The percentage of loss was calculated as the mean value of F for 10 dual base positions in each sequence multiplied with 100%.

SNP array analysis

Genome-Wide Human SNP 5.0 Arrays (Affymetrix) were used according to manufacturer's instructions. Briefly, two aliquots of 250 ng DNA were digested with Sty1 and Nsp1, respectively. Adaptors containing universal primer sites were ligated to the fragment ends and fragments were amplified in multiplex PCR. Purified PCR products were hybridized to 5.0 chips that were subsequently washed and scanned and cel files were generated. Genotypes were called from cel files using BRLMM-P algorithm. All chips had present call rates above the QC limit of 86%, except one chip with 83%, which is allowed according to Affymetrix analysis guidelines. One chip was excluded because of lower present call rate resulting in 18 informative arrays representing 18 families. A common haplotype was estimated as the most common allele for each SNP on chromosome 13. The length of the haplotype was estimated in each individual as the longest fragment including BRCA2 without a homozygous SNP discordant with the common haplotype. The genetic lengths of the haplotypes measured in cM were calculated using recombination rates from UCSC (http://genome.ucsc.edu). The age of the mutation was calculated by assuming 100 generations to generate haplotypes of 1 cM and an average generation time of 25 years.

Pedigree analysis

Pedigrees from all families were constructed by the clinical genetic departments. Genetic testing of affected and healthy family members allowed co-segregation analysis of the mutation with the breast and ovarian cancer phenotypes. We calculated a likelihood ratio as proposed by Mohammadi et al [START_REF] Mohammadi | A simple method for co-segregation analysis to evaluate the pathogenicity of unclassified variants; BRCA1 and BRCA2 as an example[END_REF]. This method use penetrance as a function of age of onset, thereby avoiding the use of discrete liability classes used in LOD score methods. Furthermore, we applied their method to calculate the combined likelihood score across families as the product of individual likelihood ratios.

Results

As part of the routine screening for mutations in BRCA1 and BRCA2 we identified a G>A substitution in intron 15 of BRCA2. According to the genomic sequence originally reported [START_REF] Wooster | Micklem G Identification of the breast cancer susceptibility gene BRCA2[END_REF], X95165, the identified variation was mapped 16 bases within intron 15. This reference sequence was also recommended by BIC (Breast Cancer Information Core) at that time. Furthermore, the entries in BIC still refer to exon/intron boundary at position 7829 in the cDNA in agreement with X95165. There are four entries for 7829+1G>A, 3 from Myriad and one of Danish origin reported by Bergthorsson et al [START_REF] Bergthorsson | BRCA1 and BRCA2 mutation status and cancer family history of Danish women affected with multifocal or bilateral breast cancer at a young age[END_REF]. However, Bergthorsson named it 7845+1G>A in their publication. Furthermore, the mutation has been reported in one Spanish family [START_REF] Gutierrez-Enriquez | The variants BRCA1 IVS6-1G>A and BRCA2 IVS15+1G>A lead to aberrant splicing of the transcripts[END_REF]. We observed misalignment to X95165 when sequencing the region. We therefore consulted more recent reference sequences that concurrently mapped the exon/intron boundary to position 7845, resulting in reclassification of the mutation as interrupting the consensus G in first position of the splice donor site in intron 15. In general we interpret a mutation in this position as deleterious. However, disruption of the consensus donor site may lead to an in-frame transcript that may not be deleterious. Furthermore, because of the disagreement of the reference sequences, we decided to perform functional splice analysis of the mutation. We isolated RNA from lymphocytes sampled from a carrier of the mutation for RT-PCR analysis. By using PCR primers located in exon 14 and 16 and sequencing the product, we obtained a mixed sequence in agreement with loss of exon 15 on one allele (figure 1). To estimate the fraction of loss of the mutated allele we calculated the percentage of mRNA missing exon 15 compared to the expected total amount of mutated allele. The values were 94% for exon 15 compared to exon 16 in the forward sequence and 90% for exon 15 compared to exon 16 in the reverse sequence, respectively. In conclusion the mutation causes almost complete loss (approximately 92%) of exon 15 in RNA from the mutated allele. Loss of the 192 bases will result in frame shift and stop codon 7 amino acids after exon 14.

Of the 19 identified families, pedigrees were available from 18. This information is summarized in table 1. To confirm that the mutation is deleterious, we calculated likelihood ratio for co-segregation of the mutation and breast and ovarian cancer. A significant exception for the segregation pattern was observed in family 1, where a female non-carrier developed bilateral breast cancer (54 and 60 years), resulting in a likelihood ratio of 0.0095. However, the likelihood ratios were near 1 or higher in the remaining families and the overall ratio across all families was 1,662,078 (table 1). The patients included in the study were from 5 regions. The peninsula Jutland in West Denmark contains Aalborg in the north, Aarhus in the upper middle, Vejle in the lower middle and South Jutland. The island Funen is in the southern middle part of Denmark and East Denmark containing half of the Danish population is composed of Zealand and smaller islands (Figure 2). Our analysis revealed a skewed distribution of the mutation: more than half of the 7845+1G>A families were located in Vejle area; whereas only 13% of families undergoing genetic screening of BRCA1 and BRCA2 were from this area (466/3690, table 2). Compared to East Denmark where the 7845+1G>A mutation was identified only once in 1300 mutation screenings, higher frequencies were observed in Jutland. When these frequencies were compared to the number of mutation screenings, significantly higher frequencies were found for Aarhus (p=0.03) and Vejle (p=0.00001) whereas it was borderline significant for Aalborg (p=0.07). Similarly, when the number of families with 7845+1G>A mutations was compared to the number of families with identified pathogenic mutations in BRCA1 and BRCA2, increased frequencies for Vejle (p=0.000005), Aarhus (p=0.016) and Aalborg (p=0.049) were found compared to East Denmark (Figure 2). An insignificantly higher frequency of 7845+1G>A was found in South Jutland and Funen compared to East Denmark. The mutation was not identified in South Sweden supporting its skewed distribution.

To clarify if the 7845+1G>A mutation had one common founder, we analyzed DNA from index persons from 18 of the 19 families using SNP arrays. Of the 500K SNPs, approximately 17K was located on chromosome 13. The longest shared haplotype was estimated from the most common allele for each SNP. The ends of the haplotypes were limited by SNPs that were homozygous and different from the common type (red in figure 3). The results are in agreement with one common founder haplotype. The length of the shared haplotype ranged from 0.2 Mb to 3.3 Mb corresponding to 415 and 23 generations respectively. The mean number of generations across all chips was 63.8 and assuming 25 years for each generation the mutation was founded 1500 years ago in the Danish Iron Age.

Discussion

We have identified a mutation that may be misinterpreted because of an error in the previously used reference sequence. Many laboratories tend to use a fixed reference sequence to ensure consistency in nomenclature. However, our results highlight the importance of using updated reference sequences. We have confirmed that the identified mutation is most likely to be deleterious by calculating likelihood ratios for co-segregation and by RT-PCR analysis. For one family a disagreement with cosegregation was observed, because a woman with bilateral breast cancer turned out to be a non-carrier. However, no deleterious BRCA1 and BRCA2 mutations were identified in 84.7% of the women with bilateral breast cancer diagnosed at a mean age of 46 years in the WECARE study [START_REF] Borg | Characterization of BRCA1 and BRCA2 deleterious mutations and variants of unknown clinical significance in unilateral and bilateral breast cancer: the WECARE study[END_REF] supporting that our case is a phenocopy. Another potential phenocopy, a non carrier from family 4 developed breast cancer 39 years old. However, 5 other affected women in that family were all mutation positive and the resulting LR was 57.35 supporting co-segregation of disease and breast and ovarian cancer. The overall likelihood ratio for all families was 1,662,078, strongly supporting co-segregation of the mutation with the disease. RT-PCR analysis demonstrated skipping of exon 15. Quantification of the mutated and the wildtype alleles indicated that exon 15 is lost in approximately 92% of mRNAs produced by the mutated allele, suggesting slightly reduced penetrance of this mutation. However, correct splicing using a nonconsensus donor site is highly unlikely and the result may reflect uncertainty in the measurement. The most likely explanation for the observation that the RNA lacking exon 15 did not constitute 50% of mRNA, is nonsense mediated decay of mRNA because of premature termination of transcripts. The results are in agreement with Gutierrez-Enriquez et al. [START_REF] Gutierrez-Enriquez | The variants BRCA1 IVS6-1G>A and BRCA2 IVS15+1G>A lead to aberrant splicing of the transcripts[END_REF], although they did not quantify the the fraction of exon 15 loss. The age of the mutation may seem relatively high (1500 years) taking its skewed location into account i.e. the strong over-representation in central Jutland compared to the rest of Denmark. This may be surprising because the Danish population is regarded genetically homogeneous with no genetically isolated sub-regions. The most obvious explanation may be that the mutation was founded in the Vejle area, and that individuals carrying this mutation have not tended to move to Funen and East Denmark. Another potential explanation could be that the mutation was missed in some laboratories. However, this is highly unlikely because all Danish laboratories identified the mutation at least once and the mutation was confirmed in the Swedish laboratory in a positive control sample from Denmark. In conclusion, the 7845+1G>A mutation is perceived a deleterious founder mutation located mostly in central Jutland. We have not examined the presence of the mutation in other countries than Denmark and Sweden and draw the attention of other laboratories to the incorrect annotation in the X95165 sequence to avoid clinically important errors.

Figure 1

 1 Figure 1 Sequence of the exon 15 region Upper panel: electropherograms for forward sequences of cDNA obtained from a control sample and a patient carrying the 7845+1G>A mutation. Lower panel: Reverse sequences for control and patient sample.

Figure 2

 2 Figure 2 Map of Denmark and South SwedenThe fraction of 7845+1G>A mutation compared to the total number of pathogenic BRCA1 and BRCA2 mutations are indicated. The intensity of the gray coloring corresponds to the mutation frequency.

Figure 3

 3 Figure 3 Haplotypes in the BRCA2 region among carriers of the 7845+1G>A mutation The blue regions indicate the longest fragment of the common haplotype in 18 index cases. Red lines indicate SNPs where the genotype breaks the haplotype. The y-axis indicates position on chromosome 13 in base pairs.

Table 1

 1 Clinical characteristics of families carrying BRCA2 7845+1G>A BC: female breast cancer, MBC: male breast cancer, OC: ovarian cancer, PC: prostate cancer, TES: testicular cancer, VEN: gastric cancer; AB: abdominal cancer; LEU: leukemia, CER: cervical cancer; AST: astrocytoma, GLI: glioblastoma; HN: head and neck cancer; KI: kidney cancer; BL: bladder cancer; RC: rectum cancer; BOC: bone cancer. F: father, M: mother, N: niece, PU: paternal uncle, MU: maternal uncle, PA: paternal aunt, MA: maternal aunt, PGM: paternal grandmother, MGM: maternal grandmother, MGF: maternal grandfather, FFC: Father's female cousin, PGMS: paternal grandmothers sister (+): mutation carriers and obligate carriers, (-): individuals tested negative for the mutation. Individuals labeled with red are potentially in conflict with 7845+1G>A being deleterious. LR: likelihood ratio

	Family Screened	Family history of breast and ovarian	Other cancers	LR
		individual (index	cancer
		person)
	1	BC 61(+)	M BC 51; S BC 54 + 60(-); MA BC; MA BC	B PC 63	0.0095
	2	BC 54 71(+)		F PC+VEN 64; B PC + BOC 66	1.13
	3	BC 54(+)	M BC 49; S BC 58 (+)		4.38
	4	OC(+)	MA BC 41+53(+); MA BC 39(+); MA OC 64; MA BC; FC BC39(+);	M AB(+); MU KI 78 + BL 81;	57.35
			FC OC 51; FC BC 62(+); FC BC 39(-)	MU TES 20
	5	BC 36(+)	PA BC 45	F PC 77; M LU 53; MGF PC 83; PGM VEN	1.00
				54
	6	BC 58 + OC 58(+)	MC MBC 62(+)	F LEU(+); MC CER+VEN	11.39
	7	BC 44(+)	M OC 50(+); FC OC 36 (+)	MU AST + GLI 51	11.10
	8	BC 38(+)	M OC 59; FC BC	F PC; S LEU 6; PU LU 48; PU VEN 84	1.00
	9	BC 44(+)	S BC 49(+); PA BC 45; PA BC 36 +37(+); PA BC 38; PA BC 42+50;		31.39
			PA BC 47 + OC 60(+); PA BC 35
			FC BC 49; FC BC 30(+);
	10	BC 46(+)	MA OC 64+BC 64	M HN 77(+); MU VEN 53; MU VEN	1.08
	11	BC 50(+)	M BC 43	MU PC; MU LU	0.87
	12	BC 41+ OC 59(+)	M OC?; S BC 45(+); S BC 48(+); N BC 37(+); D BC 45; MGM BC 40(+)	B SKIN; ♀	12.04
	13	BC 37(+)	M BC 49; MGM OC 72	FC HN; MU PAN 54	1.00
	14	♂HN(+)	M BC 70; S OC 68; S OC 65		1.97
	15	BC 56(+)	S BC 51; S BC 29+42(+)		1.19
	16	BC 48+53(+)	D BC 25	F SKIN 75; S RC	1.00
	17	BC 27(+)	PGM OC 50; PGMS BC 70; FFC BC 50; FFC BC		4.82
	18	BC 47 + OC 63	S BC 56(+)		1.21
				Over all LR	1,662,078

Table 2

 2 Geographical distribution of BRCA2 7845+1G>A mutation are calculated by comparing the geographical regions to East Denmark. Collaborativ group (2002) Breast cancer and breastfeeding: collaborative reanalysis of individual data from 47 epidemiological studies in 30 countries, including 50302 women with breast cancer and 96973 women without the disease. Lancet 360: 187-195.

		# mutation	#mutations	7845+1G>A p-value	p-value
		screenings	BRCA1/2		(analyses)	(mutations)
	Aalborg	259	28 (10.8 %)	2 (7 %)	0.07	0.049
	Aarhus	806	89 (11.0 %)	5 (5.6 %)	0.03	0.016
	Vejle	466	55 (11.8 %)	10 (18 %)	0.00001	0.000005
	South	859	85 (9.9 %)	1 (1.1 %)	1	0.52
	Jutland/Funen
	East Denmark	1300	190 (14.6 %) 1 (0.005 %)
	Total	3690	447	19
	p-values Reference List
	1

Gerdes AM, Cruger DG, Thomassen M, and Kruse TA (2006) Evaluation of two different models to predict BRCA1 and BRCA2 mutations in a cohort of Danish hereditary breast and/or ovarian cancer families. Clin.Genet. 69: 171-178.

Acknowledgements

Susan N Rasmussen, Dorte F Jensen, Jette Thinggaard and Flemming H Bergholdt are thanked for excellent technical assistance. This study was supported by the Neye Foundation.

Conflicts of interest

All authors declare no conflicts of interest.