Background: BRCA mutation-associated (BRCAmut) breast cancer represents a heterogeneous group displaying certain molecular features. Claudin-low breast cancers (CLBC) overlap with characteristics of BRCAmut tumors; therefore, we have investigated whether these are identical subtypes. Methods: Using public gene expression data, CLDN, CDH1, 9-cell line claudin-low predictor (9CLCLP) and PAM50 expression was evaluated in BRCAmut and BRCA wild-type (BRCAwt) breast cancer cases focusing on their possible overlap with the CLBC subtype. A separate formalin-fixed, paraffin-embedded (FFPE) cohort of 22 BRCAmut and 19 BRCAwt tumor tissues was used for immunohistochemical examination of AR, CD24, CD44, CK5/6, claudin-1, -3, -4 and -7, E-cadherin, EGFR, estrogen receptor (ER), EZH2, HER2, Ki67, p53, progesterone receptor (PgR) and vimentin expression. Results: In the data sets, CLDN1 (ROC = 0.785, p < 0.001), CDH1 (ROC = 0.785, p < 0.001), CLDN7 (ROC = 0.723, p < 0.001), CLDN3 (ROC = 0.696, p = 0.020) and CLDN4 (ROC = 0.685, p = 0.027) were expressed at higher level in BRCAmut than BRCAwt tumor tissue. The PAM50 subtype differed from the assigned immunohistochemistry (IHC)-based subtype in 30%. Based on accessible 9CLCLP predictor genes, BRCAmut breast cancer does not display the claudin-low phenotype. Utilizing FFPE samples, claudins were evidently expressed in both BRCAmut and BRCAwt cases. However, at the protein level, only claudin-3 expression was higher in BRCAmut tumors, while claudin-1, -4 and -7 and E-cadherin expression was lower compared to BRCAwt cases. A CD24low/CD44high phenotype was found in BRCAmut tumors upon comparison with BRCAwt cases (p < 0.001 and p = 0.001, respectively). Conclusions: There is a prominent correlation between the genes under focus herein and BRCA mutation status. BRCAmut tumors bear stem cell characteristics displaying a distinct cell adhesion molecule profile characterized by high expression of CDH1 and CLDN4 according to public gene expression data set analysis, and higher claudin-3 expression as detected by IHC; thus, BRCAmut breast carcinomas are not identical with the previously identified claudin-low subtype of breast cancer.

Breast cancer (BC) is the most common (non-skin) malignancy affecting women and it is expected that over a million women will develop the disease yearly [1]. Familial BC represents about 7% of all cases. Paul Broca, a French surgeon, anatomist and anthropologist, was the first to describe a family of four generations with high prevalence of BC [2]. About 130 years later, the tumor suppressor genes BRCA1 and BRCA2, which were associated with a high risk of BC and ovarian cancer, were discovered [3,4]. Mutations in these two genes are present in 1/400 to 1/40 women. BRCA1 germline mutation-associated tumors are usually high-grade invasive carcinomas (NOS), which present more frequently with a medullary-like morphology [5,6]. About 70-75% of these tumors are negative for estrogen receptor (ER), progesterone receptor (PgR) and Her2 (triple-negative BC - TNBC), but they commonly express basal cytokeratins (CK5/6 and CK14) and/or EGFR. BRCA1-associated BC and sporadic TNBC commonly express stem cell phenotype (CD24low/CD44high) [7]. The majority of BRCA1-associated tumors cluster within the basal-like intrinsic subtype of BC (BLBC) by gene expression profiling [8]. The development of the two-layered breast epithelium and derived corresponding BC subtypes (fig. 1) have previously been described by Böcker et al. [9], and the concept was further utilized by Prat and Perou [10]. About 5-20% of BRCA1-associated tumors are ER+ though, especially if arising in older patients [11].

Fig. 1

Mammary development and the derived intrinsic BC subtypes and their suggested biomarker expression.

Fig. 1

Mammary development and the derived intrinsic BC subtypes and their suggested biomarker expression.

Close modal

BRCA2-associated BC represents a heterogeneous group. The large majority of these tumors are ER+ and PgR+ and Her2- invasive carcinomas (NOS), but there is a significant decrease in the proportion of ER+ tumors with age, and according to the CIMBA study 16% of BRCA2-associated BC cases are TNBC [11]. High-grade tumors are slightly less frequent in BRCA2 mutation carriers and invasive lobular cancers also occur more commonly among them as compared to BRCA1 mutation carriers.

Genetic profiling of human BC has identified 6 subtypes: luminal A, luminal B, HER2-enriched (HER2-E), molecular apocrine, BLBC and claudin-low BC (CLBC; fig. 1). For diagnostic purposes, the PAM50 gene expression-based classifier was developed, which is available for formalin-fixed tissue [12]. It is using NanoString assay technology and evaluates the expression of 50 genes reproducibly assigning the molecular subtype category to the samples; it also provides prognostic information in endocrine-treated patients with ER+, node-negative disease [13].

CLBC was described in 2007 and characterized by the loss of genes involved in cell-cell adhesion, primarily low expression of claudin-3, -4 and -7 and E-cadherin [14]. Further characterization of these tumors resulted in the identification of the 9-cell line claudin-low predictor (9CLCLP) based on the Agilent gene expression platform [15]; thus, its marker genes are not fully accessible on Affymetrix arrays. Based on gene expression studies, the original CLBC was identified among the tumors with invasive (ductal) carcinoma histology, which was subsequently shown to be closely related to metaplastic BC suggesting a common cellular origin [16]. Gerhard et al. [17] identified the CLBC using immunohistochemistry (IHC) outlining the metaplastic carcinomas of the breast as well. ALDH1+ mammary stem cells and aberrant luminal progenitors alike have been candidate cell populations for BLBC development in BRCA1 mutation carriers [18].

It appears that BRCA mutation-associated (BRCAmut) BC represent certain gene expression subtypes, claudin profiles and stem cell characteristics. Therefore, we have investigated these parameters, i.e. selected cell adhesion and tight junction molecular expression; the gene expression profile reflecting PAM50; the accessible genes and their expression of the previously identified 9CLCLP, in public data sets, and protein expression, i.e. markers known as proteins suitable to classify BC into categories reflecting intrinsic molecular subtypes (ER, PgR, Her2, Ki67, p53 and AR), basal cell markers (CK5/6 and EGFR), their adhesion or tight junction molecular profiles (E-cadherin and claudin-1, -3, -4 and -7) and stem cell characteristics (CD24/44, EZH2 and vimentin) by IHC in tumor samples of a consecutive cohort of BC patients with known BRCA mutation status.

The study comprised two independent cohorts both containing largely equal numbers of BRCAmut and BRCA wild-type (BRCAwt) patients' data and samples (fig. 2). First, bioinformatic analysis of mRNA expression profiles of data sets (n = 33) was performed, which was followed by investigation of protein expression in samples collected from BC patients (n = 41).

Fig. 2

Study design and overview of the intended methods for the in silico and tumor tissue-based examinations.

Fig. 2

Study design and overview of the intended methods for the in silico and tumor tissue-based examinations.

Close modal

For the first part, gene expression data from three previously published BC data sets were retrieved from GEO consisting of 16 BRCAmut carriers (12 from GSE50567 [19], 2 from GSE18864 [20] and 2 from GSE3744 [21]) and 17 BRCAwt carriers as controls (10 from GSE18864 [20] and 7 from GSE50567 [19]). The study had quasi a case-control design with the available parameters for all samples: ER status and age. Some of the patients received neoadjuvant chemotherapy. Clinicopathological characteristics of the patients from the data sets are presented in table 1. Following the selection, we have downloaded publicly available unprocessed .CEL files which were normalized using MAS5 in the R statistical environment (R, version 2.10.1; R Foundation for Statistical Computing, Vienna, Austria) by employing the Affymetrix Bioconductor library [22].

Table 1

Clinicopathological properties of the patients whose gene expression data were retrieved from three data sets

Clinicopathological properties of the patients whose gene expression data were retrieved from three data sets
Clinicopathological properties of the patients whose gene expression data were retrieved from three data sets

Then, a separate cohort of 22 BRCA mutation carrier women with available BC tissue was selected (table 2). The BRCA mutation was identified previously by Sanger sequencing and the maternal and paternal loci were also analyzed to assess the origin of the inherited mutation (table 3). Data on a control cohort for IHC studies (19 women) were retrieved from the archives of the Second Department of Pathology, Semmelweis University. These patients underwent BC operation at the Semmelweis University and also had BRCA mutation analysis at the First Department of Pathology and Experimental Cancer Research, Semmelweis University (table 2). Ethical approval (according to the Helsinki Declaration of 1964) was granted by the Institutional Review Board of the Chaim Sheba Medical Center filed under the identification No. 0144-13-SMC and by the Semmelweis University filed as IKEB-17/2006, IKEB-139/2009 and IKEB-141/2009.

Table 2

Clinicopathological data on the patients who were enrolled in the IHC study

Clinicopathological data on the patients who were enrolled in the IHC study
Clinicopathological data on the patients who were enrolled in the IHC study
Table 3

BRCA mutation spectrum and inheritance in the patients enrolled at the Chaim Sheba Medical Center

BRCA mutation spectrum and inheritance in the patients enrolled at the Chaim Sheba Medical Center
BRCA mutation spectrum and inheritance in the patients enrolled at the Chaim Sheba Medical Center

Formalin-fixed, paraffin-embedded (FFPE) blocks and slides were reviewed for tumor content by two investigators (L.M. and N.B.) and tissue microarrays (TMA) were composed using 2 cores of 2 mm per case, which were placed consecutively in 2 blocks with a TMA builder instrument (MTA-1; Beecher Instruments, Inc., Sun Prairie, Wis., USA).

TMA sections were cut at 4 μm thickness and IHC reactions were performed for the following proteins using an automated Ventana Benchmark XT immunostainer (Ventana, Tucson, Ariz., USA) with the respective protocols provided by the manufacturer: AR, CD24, CD44, CK5/6, claudin-1, claudin-3, claudin-4, claudin-7, E-cadherin, EGFR, ER, EZH2, HER2, Ki67, p53, PgR and vimentin (see online suppl. table S1; for all online suppl. material, see www.karger.com/doi/10.1159/000439135). The IHC slides were scanned using a Pannoramic 250β scanner (3DHistech Ltd., Budapest, Hungary). The expression differences between the cores were minimal and were therefore averaged for the values for each case. For each antibody, one slide was stained with appropriate positive control tissue. Depending on the protein examined, internal controls were also assessed during evaluation of the reactions. The evaluation was based on the combined assessment of staining intensity (0-3) and frequency (0-5) of positive tumor cells in the core regions [23]. The raw data were then added resulting in an Allred-like number (0, 2-8), and the average of scores from each core was assigned to the given case. Ki67 was evaluated on a scale from 0 to 100%. ER and PgR were considered according to the Allred system [23]. Her2 was assessed on a scale from 0 to 3+ and supported by FISH for those resulting in a score of 2+ with IHC. For other reactions, a value <3 was considered negative, 3-4 was low, and >4 was considered high.

Analysis of data on the tumor subtypes in the data sets was performed in R statistical environment using the PAM50 predictor described previously [24]. The χ2 test and the Kruskal-Wallis test were applied to test significant differences in nominal and numeric ordinal variables. Numeric scale variables were compared with Student's t test using SPSS 15.0 (SPSS Inc., Chicago, Ill., USA). Two-sided tests were used and we set a significance level of 0.05.

Based on published gene expression data, we have investigated the expression of CLDN1 (ROC = 0.785, p = 2.6e-4), CDH1 (ROC = 0.785, p = 2.2e-4), CLDN7 (ROC = 0.723, p = 8.8e-3), CLDN3 (ROC = 0.696, p = 0.020) and CLDN4 (ROC = 0.685, p = 0.027) for the purpose of distinguishing between the BRCAmut versus BRCAwt BC. When comparing the expression of claudins between the groups, it was noted that CLDN1, CLDN3, CLDN4, CLDN7 and CLDN10 are expressed at higher mRNA levels in the BRCAmut than in the BRCAwt tumors (p = 0.339, 0.062, 0.126, 0.082 and 0.784, respectively). We noted that ESR1 and ERBB2 were lower (p = 0.770 and 0.477, respectively), while EGFR, TP53, VIM and MKI67 showed a tendency towards higher expression (p = 0.179, 0.064, 0.002 and 0.347, respectively) in BRCAmut versus BRCAwt cases (online suppl. fig. S2).

The ‘PAM50' predictor was applied (modeled in silico) to classify the tumors according to the gene expression-derived intrinsic subtype, which did not always reflect the subtype of samples previously assigned (table 1): 4 of the BRCAmut BLBC turned out to be luminal BC, while 1 of the BRCAwt BLBC was HER2-E and 1 of the BRCAwt luminal BC was BLBC according to our reclassification.

The genes as positive and negative predictors, published as the 9CLCLP previously [25], were identified in the tumors of the downloaded data set. Out of the 437 positive predictor and 370 negative predictor genes, 161 and 354 were available for analysis, respectively. The positive predictors tended to have a higher expression in BRCAwt tumors [2,258.73 ± 716.39 (mean ± SD)] than in the BRCAmut cancers (1,904.40 ± 544.27; p = 0.114), while the negative genes were more likely to be expressed at lower levels in the BRCAwt tumors (1,553.60 ± 490.40) than in the BRCAmut cancers (1,621.82 ± 360.62; p = 0.647). We have found that the group of BRCAmut tumors does not display the claudin-low phenotype, and that BRCAmut tumors do not display a uniform group as compared to BRCAwt tumors based on either the positive or negative predictor genes (online suppl. fig. S3 and S4), and they do not form a uniform cluster (fig. 3).

Fig. 3

Heat map displaying the BRCAwt tumors (lower 17 cases) and the BRCAmut tumors (upper 17 cases) with the positive and negative predictor genes arranged according to their scores for distinction of the claudin-low phenotype in a left-to-right fashion. The lower expression is towards green and higher expression towards red coloration. Colors refer to the online version only.

Fig. 3

Heat map displaying the BRCAwt tumors (lower 17 cases) and the BRCAmut tumors (upper 17 cases) with the positive and negative predictor genes arranged according to their scores for distinction of the claudin-low phenotype in a left-to-right fashion. The lower expression is towards green and higher expression towards red coloration. Colors refer to the online version only.

Close modal

In the patient cohort with FFPE samples, we have performed immunophenotypical characterization. One Her2+ tumor was found among both BRCA1 and BRCA2 mutation carriers. All other BRCA2 tumors were luminal, and the majority of BRCA1 tumors were TNBC (fig. 4).

Fig. 4

Immunophenotypes displayed in the FFPE samples of the BRCAmut tumors. a Cases possessing BRCA1 mutation. b BRCA2 mutation. c The tumor with both BRCA1 and BRCA2 mutations. LUM = Luminal; LUMB = luminal B.

Fig. 4

Immunophenotypes displayed in the FFPE samples of the BRCAmut tumors. a Cases possessing BRCA1 mutation. b BRCA2 mutation. c The tumor with both BRCA1 and BRCA2 mutations. LUM = Luminal; LUMB = luminal B.

Close modal

Claudin-1, -3 and -7 were barely expressed in any BRCAmut tumor, while claudin-4 was expressed in 45.5% (10/22) of the tumors and E-cadherin was in 68.5% (15/22) positive (table 4; fig. 5). None of these markers differed significantly across BRCA1 and BRCA2 tumors (p = 1.000, 1.000, 0.344, 0.200 and 0.501, respectively).

Table 4

IHC expression of the investigated proteins in the FFPE samples (resulting comparisons are displayed in the last column supported by the Kruskal-Wallis approach)

IHC expression of the investigated proteins in the FFPE samples (resulting comparisons are displayed in the last column supported by the Kruskal-Wallis approach)
IHC expression of the investigated proteins in the FFPE samples (resulting comparisons are displayed in the last column supported by the Kruskal-Wallis approach)
Fig. 5

a-e The distribution of claudins and E-cadherin expression. f Heat map of the protein expression and the assigned immunophenotypes of BRCAmut tumors; cases are shown in rows and markers in columns.

Fig. 5

a-e The distribution of claudins and E-cadherin expression. f Heat map of the protein expression and the assigned immunophenotypes of BRCAmut tumors; cases are shown in rows and markers in columns.

Close modal

The majority of BRCAmut cases did not express CD24 (81.8%, 18/22) with high expression of CD44 (77.3%, 17/22). EZH2 was negative in 5 (22.7%), low in 8 (36.4%) and positive in 9 (40.9%) cases, respectively. Vimentin was mostly negative (10, 45.5%) or low (5, 22.7%) and positive in 7 cases (31.8%). EGFR was negative in 8 (36.4%), low in 5 (22.7%) and positive in 7 (31.8%) cases (fig. 5). Additionally, p53 nuclear positivity was found in 76.2% (16/21) of tumors. (For this latter IHC reaction, 1 BRCAmut case was not evaluable.)

Regarding the paternal and maternal alleles, ER and PgR were both lower in the paternally inherited BRCAmut tumors than in the maternal ones (p = 0.038 and 0.050, respectively).

Upon comparing BRCAmut and BRCAwt tissue samples (table 4), we have found that BRCAmut tumors display a lower expression of ER and PgR, and a higher level of EGFR, Her2 and p53. Also, CD24 and CD44 were lower, while EZH2 and vimentin were expressed at a higher level in BRCAmut cases, and the ratio of CD24/CD44 was characteristically low/high for these tumors as compared to high/high in BRCAwt. Regarding tight junction and adhesion molecules, claudin-1, -4 and -7 and E-cadherin expression was lower and claudin-3 expression was higher in BRCAmut samples. All markers but claudin-3 were expressed in both wild-type and mutant tumors: claudin-3 was not detected in BRCAwt carcinomas (online suppl. fig. S4).

Significant positive and negative correlations were detected between the markers with modest coefficients: the strongest positive correlation was noted for CD24 with CD44 and claudin-1; claudin-1 with claudin-4 and Ki67; the strongest negative correlations were found for E-cadherin with vimentin, and EGFR with ER (online suppl. table S2).

We have investigated claudin expression and stem cell markers in BRCAmut BC. In public data sets, claudins performed with an AUC of 0.685-0.785, which suggests that BRCAmut tumors also present a special claudin expression profile. We have noted that claudins are expressed at higher levels in the BRCAmut than BRCAwt cancers. Also, ESR1 and ERBB2 displayed a lower, and EGFR, TP53, VIM and MKI67 showed a tendency towards a higher expression in these cases, but a limitation of our study is the low number of cases available.

The surrogate of PAM50 predictor applied to establish the intrinsic BC subtype reclassified the tumors in 4/13 BRCAmut (basal-like into luminal B) cases and 2/7 BRCAwt (1 basal-like into HER2-E and 1 luminal into basal-like) cases. This altogether 33% discordance with the distribution of ER- cases turning out as luminal and HER2-E, while a low number of ER+ cases showing basal-like features corresponds with other findings [26]. In our FFPE cohort, we identified 2 Her2+ tumors, most BRCA2 tumors were luminal, and the majority of BRCA1 tumors were TNBC; however, we were unable to access the PAM50 classifier for confirmation.

The genes of the original 9CLCLP were identified in the downloaded gene expression set of 34 tumors [25]. However, due to the fact that 9CLCLP utilized Agilent arrays and the public data set of BRCAmut tumors resulted from the Affymetrix platform, we could test 161 out of 437 positive and 354 out of 370 negative predictor genes. The positive predictors showed a higher expression tendency in the BRCAwt than in the BRCAmut cancers, while the negative genes were more likely to be expressed at lower levels in the BRCAwt tumors; thus, we conclude that the group of BRCAmut tumors does not present the claudin-low phenotype, and that BRCAmut tumors do not display a uniform group as compared to BRCAwt. Again, a limitation of the study is that for the data sets there are no publicly available gene expression data of CLBC for the Affymetrix U133 or U133plus2 platform rendering large comparative studies and a training set for bioinformatic analysis challenging.

Claudin-1, -3 and -7 were barely expressed in any BRCAmut tumors in our FFPE cohort, while claudin-4 was expressed in 10 of 22 tumors and E-cadherin in 15 of 22 cases. None of these markers differed significantly across BRCA1- and BRCA2-mutant carcinomas. Heerma van Voss et al. [27] have concluded that claudin-1 and -6 may help in the distinction of BRCAmut and BRCAwt tumors. They found a higher expression of claudin-1 in BRCAmut cancer. This confirms that BRCAmut tumors do display a distinct cell adhesion molecule profile, which is in line with our study at protein level. Among them, the higher expression of E-cadherin and claudin-4 suggests imparity with the CLBC.

Decreased expression of tight junction molecules has been identified in BC studies [28,29,30], while claudin-1 was found to be expressed at higher level in BLBC [31], especially in older patients [32]. Claudin-3 and -4 are expressed at higher level in high-grade and ER- tumors, especially in BLBC [31,33]. Claudin-4, in line with E-cadherin, was found to be a biomarker predicting poor prognosis in BC [34,35]. At mRNA (derived from in silico data) and protein expression (derived from our IHC investigations) level, we have noted a discrepancy, which we suggest is the result of the following: (i) the sample number was still low, although we used all available public gene expression data sets and all available BRCAmut and BRCAwt cases from both our archives; (ii) correspondingly, the FFPE cohort could not be matched for age and hormone receptor/subtype status to the data set analyzed by bioinformatics, and (iii) epigenetic regulation may alter the translation process of the proteins investigated.

The majority of BRCAmut tumors did not express CD24, with high expression of CD44 with negativity and low expression of EZH2 in two thirds of all cases. Vimentin expression was mostly lacking or low. EGFR was positive in one third of the cases. In our FFPE cohort (with 1 case excluded for equivocal p53 IHC result), p53 was expressed in 76.2% of tumors, which confirms the study highlighting p53 as a hallmark of BRCAness in BRCAmut BLBC [36]. As compared to wild-type tumors, BRCAmut cases have shown more frequently p53 mutations, higher EGFR and HER2 expression but lower hormone receptor levels. The ratio of CD24 and CD44 was more characteristic for a stem cell phenotype in BRCAmut tumors, which was also supplemented by a higher vimentin and EZH2 expression of these carcinomas.

We have further found that ER and PgR levels are both lower in the paternally inherited BRCAmut tumors due to the relatively higher frequency of BRCA1 mutation inheritance (11/14, 78.5%) than in the maternal ones (4/7, 57.1%).

The strongest positive correlation was noted for CD24 with CD44, all claudins and E-cadherin expression. Claudin-1 displayed similar expression levels to claudin-4/-7, EZH2 and Ki67, in contrast to ER expression. Claudin-4 correlated with E-cadherin, EGFR and EZH2 expression positively and negatively with ER. E-cadherin negatively correlated with vimentin and EGFR with ER staining.

In accessible public data sets of BRCAmut tumors and a matched control group, we have noted that there is a prominent correlation between the expression of claudins and the BRCAmut status, which suggests that BRCAmut BC also present a special claudin expression profile. BRCAmut tumors might bear stem cell characteristics and do display a distinct claudin profile which is characterized by a higher expression of E-cadherin and claudin-4, and thus are not identical with the previously identified claudin-low subtype of BC. The PAM50 predictor may reclassify BC into different subtypes than IHC.

The research study was supported by the European Union and the State of Hungary, cofinanced by the European Social Fund in the framework of TÁMOP 4.2.4.A/2-11-1-2012-0001 ‘National Excellence Program'. This paper was also supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences. We thank Erzsebet Azumah and Gyorgy Szekeres for their faithful support in the IHC reactions and we also express our special thanks to Jason I. Herschkowitz for sharing his critical comments. The publication charges were covered by the KTIA_NAP_13-2-2014-0021 grant.

The authors declare that they have no competing interests.

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