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Correlated break at PARK2/FRA6E and loss of AF-6/Afadin protein expression are associated with poor outcome in breast cancer


Common fragile sites (CFSs) are regions of chromosomal break that may play a role in oncogenesis. The most frequent alteration occurs at FRA3B, within the FHIT gene, at chromosomal region 3p14. We studied a series of breast carcinomas for break of a CFS at 6q26, FRA6E, and its associated gene PARK2, using fluorescence in situ hybridization on tissue microarrays (TMA). We found break of PARK2 in 6% of cases. We studied the PARK2-encoded protein Parkin by using immunohistochemistry on the same TMA. Loss of Parkin was found in 13% of samples but was not correlated with PARK2 break. PARK2 break but not Parkin expression was correlated with prognosis. Alteration of PARK2/FRA6E may cause haplo-insufficiency of one or several telomeric potential tumor suppressor genes (TSG). The AF-6/MLLT4 gene, telomeric of PARK2, encodes the Afadin scaffold protein, which is essential for epithelial integrity. Loss of Afadin was found in 14.5% of cases, and 36% of these cases showed PARK2 break. Loss of Afadin had prognostic impact, suggesting that AF-6 may be a TSG. Loss of Afadin was correlated with loss of FHIT expression, suggesting fragility of FRA6E and FRA3B in a certain proportion of breast tumors.


The human chromosomes contain several regions called fragile sites that are particularly susceptible to break in response to environmental carcinogens (Richards, 2001). Breaks at common fragile sites (CFS) may play a role in tumor initiation and/or progression (Huebner and Croce, 2001; Dhillon et al., 2003; Popescu, 2003). Among them, the most frequently altered CFSs, FRA3B at 3p14.2 and FRA16D at 16q23.3, are encompassed by FHIT (Fragile Histidine Triad) and WWOX (WW domain-containing oxydoreductase) loci, respectively (Huebner et al., 1998; Bednarek et al., 2000). FHIT and WWOX are both considered as tumor suppressor genes (TSG) (Bednarek et al., 2001; Paige et al., 2001; Huebner and Croce, 2003; Fabbri et al., 2005). Their alterations are found in various types of cancer and lead to the loss or inactivation of their respective proteins (Paige et al., 2001; Huebner and Croce, 2003). We have previously reported that the loss of FHIT expression is a marker of adverse evolution in good prognosis localized breast cancer (Ginestier et al., 2003). FHIT and WWOX are coordinately inactivated in a subset of invasive breast cancers (Guler et al., 2005).

The third most frequent CFS, FRA6E, is located in chromosome region 6q26 within approximately 3.6 Mb. The PARK2 gene encompasses the distal half of the FRA6E locus. The most unstable region of FRA6E is localized between exons 2 and 8 of PARK2. The PARK2 gene encodes Parkin, a cytoplasmic E3 ubiquitin protein ligase, whose mutations cause autosomal-recessive juvenile Parkinsonism (Kitada et al., 1998; Marin et al., 2004). Frequent loss of heterozygosity (LOH) in introns 2 and 6 and downregulation of Parkin are found in ovarian tumors (Cesari et al., 2003; Denison et al., 2003b; Picchio et al., 2004; Wang et al., 2004), which suggests that PARK2 may be involved in oncogenesis as a TSG.

The long arm of chromosome 6 contains potential TSG involved in various types of cancer such as melanoma (Millikin et al., 1991), ovarian carcinoma (Saito et al., 1992; Tibiletti et al., 1996), breast carcinoma (Orphanos et al., 1995; Noviello et al., 1996), non-Hodgkin's lymphoma (Menasce et al., 1994a) and acute leukemia (Hayashi et al., 1990; Menasce et al., 1994b). Tumorigenicity of breast cell lines can be suppressed by microcell-mediated transfer of regions 6q21–q23 and/or 6q26–q27 suggesting that these regions may indeed contain TSG (Negrini et al., 1994). LOH and comparative genomic hybridization experiments have shown that the 6q26-qter region is frequently altered in breast cancer (Noviello et al., 1996; Kerangueven et al., 1997; Rodriguez et al., 2000; Teixeira et al., 2002).

The 6q26-qter region contains several genes including PARK2, FOP, TTLL2, AF-6/MLLT4, KIF25, THBS2 and TBP, potentially involved in cancer (Prasad et al., 1993; Taki et al., 1996; Whitcomb et al., 2003; Denison et al., 2003a; Guasch et al., 2004; Agirre et al., 2005). Among these genes, AF-6/MLLT4, located telomeric of PARK2, encodes the Afadin protein, which is crucial for epithelial physiology and development (Ikeda et al., 1999; Zhadanov et al., 1999). Afadin is a scaffold protein located at adherens and tight junctions (Mandai et al., 1997). It participates to the establishment and the maintenance of epithelial polarity, a process disrupted during oncogenesis.

We report here an analysis of PARK2/FRA6E, Parkin and Afadin in breast cancers. We first established the frequency of PARK2 break at FRA6E by using fluorescence in situ hybridization (FISH) on tissue microarrays (TMA). The break of PARK2, but not the loss of expression of Parkin, had an impact on disease outcome. We then showed indirectly that the PARK2 break could affect the telomeric gene AF-6, and the expression of its encoded protein Afadin. Loss of expression of Afadin measured by immunohistochemistry (IHC) was associated to poor outcome and seemed to be a good marker of metastasis appearance in the population of patients without axillary lymph node invasion. Finally, we showed that loss of Afadin expression after RNA silencing experiments affects cell–cell contacts. Our data suggest that AF-6 may be a TSG in breast cancer whose loss is a marker of adverse prognosis.


Characterization of break in the PARK2 gene in breast carcinoma

We searched for alteration of the PARK2 locus at FRA6E in 547 breast tumors by using FISH on TMA sections. Biotinylated and digoxigenin-labeled sequences used as probes in the 5′ and 3′ regions of PARK2 (Figure 1a) were seen as green or red fluorescent signals, respectively. Of the 547 cases, only 190 (35%) gave reliable results (Supplementary Table 1). Loss of data resulted either from the loss of the sample during stringent FISH pretreatment or from high background. Of these 190 samples, 177 (94%) showed integrity of the PARK2 locus revealed by clustered green/red signals (Figure 1Ba), two showed monosomy for this locus (Figure 1Bb), and 11 (6%) showed break of the locus (Figure 1Bc and Bd). Two types of PARK2 break were found. The first type, observed in 10 cases (nine ductal and one lobular carcinomas), displayed a wild-type locus and a chromosomal derivative detected by red signals without green signals. This indicated that the 5′ region of PARK2 (green signal) was lost (Figure 1Bc). The second type of alteration, observed in only one case (a ductal carcinoma), displayed a wild-type locus and a chromosomal derivative detected by green signals without red signal, indicating that the 3′ region of PARK2 was lost (Figure 1Bd).

Figure 1

Break of the PARK2 locus in breast cancer. (A) Map of the locus. (a) Ideogram of chromosome 6 showing the PARK2 locus at 6q26 (chr6:161 740 081–163 119 211) and the AF-6/MLLT4 locus at 6q27 (chr6:168 046 404–168 183 532). (b) The two pools of BAC clones used as probes in FISH experiments. To detect a break of PARK2, tumors present on a TMA were hybridized using biotinylated and dig-labeled sequences in the 5′ (green) and 3′ (red) regions of PARK2 revealed after detection in green and red, respectively. (c) Enlarged PARK2 locus showing exon–intron organization and the two overlapping BAC clones used as probes. (B) Examples of PARK2 status in breast cancer determined by FISH on TMA. (a) Tumor with intact PARK2 gene: two wild-type copies of PARK2 are seen as clusters of green and red signals (arrows). (b) Tumor with monosomy of PARK2 gene: only one wild-type copy is seen and revealed by clustered green and red signals (arrow). (c) Tumor with break of PARK2 gene seen as a split of the clustered signals and disappearance of one green signal (arrow), suggesting the loss of the 5′ region of the locus. (d) Tumor with break of PARK2 gene seen as a split of the clustered signals and disappearance of one red signal (arrow), suggesting the loss of the 3′ region of the locus.

Correlation of PARK2 break with histoclinical factors and clinical outcome

We next examined the relation between PARK2 break and histoclinical factors. We did not take into account the monosomy cases but only the cases with break. PARK2 break was not associated with any histoclinical factor, including age, histological type, pathological tumor size, SBR grade, peritumoral vascular invasion, axillary lymph node status, and ER, PR, ERBB2, P53 and Ki67 expression (Table 1).

Table 1 Correlation between the break of PARK2 determined by FISH and histoclinical factors

We examined if the PARK2 break had an impact on prognosis. When we considered the whole population of patients, the 5-year metastasis-free survival (MFS) was 61.4% (range 37.7–99.9) for patients with a tumor showing a break at PARK2, and 79.9% (73.9–86.5) for patients with a wild-type PARK2 tumor (P=0.0216) (Figure 2). PARK2 break was associated with decreased 5-year MFS in patients with breast cancer.

Figure 2

PARK2 status and associated survival in breast cancer. Impact of the break of PARK2 on MFS of the whole population analysed for PARK2 break (N=188). Kaplan–Meier curves illustrate MFS according to the status of PARK2.

Parkin expression in breast carcinomas

To determine if the break of the PARK2 gene affected Parkin expression, we studied expression of the protein by IHC on the same TMA. Parkin was strongly expressed in the cytoplasm of the epithelial cells of normal breast tissue (Figure 3Aa). Of the 547 tumors, 473 immunostained cases (86%) were available for quick score analysis (Supplementary Table 1). In 412 tumors (87%), Parkin was expressed with a level of expression from low to fully positive (Figure 3Ab). In 61 tumors (13%), no Parkin expression was found (Q=0) (Figure 3Ac). None of the tumors with break of PARK2 showed loss of Parkin expression. Other mechanisms, such as mutations, intragenic deletions and epigenetic modifications, may explain loss of expression in the tumors without PARK2 break.

Figure 3

Parkin and Afadin expression in breast cancer. (A) Parkin expression in normal breast and breast tumors determined by IHC on TMA. (a) Normal breast tissue with Parkin expression; (b) Tumor with preserved Parkin expression (arrow) and (c) Tumor showing loss of Parkin expression. (B) Afadin expression in normal breast and breast tumors determined by IHC on TMA: (a) Normal breast tissue with Afadin expression (arrow); (b) Tumor with Afadin expression (arrow) and (c) Tumor showing loss of Afadin expression in tumoral component (arrow) and Afadin expression in normal tissue.

We examined the impact of the loss of Parkin expression on the 5-year MFS. The 5-year MFS for patients with a Parkin-negative tumor was 75.7% (65.4–87.7), and 79.1% (75.1–83.3) for patients with a Parkin-positive tumor (P=0.994). Thus, in contrast to the PARK2 break, the loss of Parkin expression had no impact on prognosis.

Afadin expression in breast carcinomas

As there was no correlation between PARK2 gene status and Parkin expression, we studied the consequences of a PARK2 break on the expression of genes located in the 6q26-qter region telomeric of PARK2. Among the genes located in this region (FOP, TTLL2, AF-6, KIF25, THBS2, TBP), AF-6/MLLT4 is located in a region of frequent LOH and displays frequent deletions in breast cancers. Moreover, AF-6 encoded product, Afadin, is expressed in normal breast epithelium and is involved in epithelial cell architecture. We thus focused our attention on Afadin. We first validated the two different anti-Afadin antibodies (Table 2) on mammary cell lines by Western blot and IHC (data not shown).

Table 2 List of proteins tested by and characteristics of the corresponding antibodies

We investigated the expression of Afadin in breast tumors by IHC on TMA sections. Afadin was strongly expressed in the cytoplasm and at the cellular membrane of the epithelial cells of normal breast (Figure 3Ba). As measured by the quick score (QS), two distinct levels of Afadin expression were observed in the 352 tumors with reliable results (Supplementary Table 1). In 301 tumors (85.5%), the level of Afadin was similar to that of normal breast tissue (Figure 3Bb). In 51 tumors (14.5%), there was no Afadin expression (QS=0) (Figure 3Bc).

Loss of Afadin expression correlates with PARK2 break and prognosis

Loss of Afadin did not correlate with any of the studied histoclinical factors (Table 3). It tended to be associated with high pathological size (P=0.05389). Interestingly, 36% of Afadin-negative tumors (four cases) had break of PARK2, whereas only 5% of Afadin-positive tumors (seven cases) had break of PARK2 (P<0.001). Thus, loss of Afadin was associated with a PARK2 break. Other pathological mechanisms, such as mutations, intragenic deletions and epigenetic modifications, may explain loss of expression in the 64% of Afadin-negative tumors without break of PARK2.

Table 3 Correlation between Afadin expression determined by IHC and histoclinical factors

These results led us to examine the impact of Afadin expression on clinical outcome. When we considered the whole population of patients analysed for Afadin expression (N=352), the 5-year MFS was 67.8% (55.3–82.9) for patients with an Afadin-negative tumor, and 81.8% (77.4–86.5) for patients with an Afadin-positive tumor (P=0.046) (Figure 4a). When we considered the lymph node-negative population of patients (N=181), the 5-year MFS was 72.8% (56.1–94.5) for patients with an Afadin-negative tumor, and 89.5% (84.5–94.7) for patients with an Afadin-positive tumor (P=0.0496) (Figure 4b). Loss of Afadin was thus associated with poor outcome in this group of patients.

Figure 4

Afadin status and associated survival in breast cancer. (a) Impact of the loss of Afadin expression on MFS of the whole population analysed for Afadin expression (N=352). (b) Impact of the loss of Afadin expression on MFS of patients with absence of axillary lymph node invasion (N=181). Kaplan–Meier curves illustrate MFS according to Afadin expression.

We did a Cox multivariate analysis of MFS in which the values for Afadin, tumor size, age, grade, peritumoral vascular invasion, ER, PR and Ki67 were considered as categorical variables. Afadin expression remained significant as well as Ki67 status and grade according to the Akaike Information criterium when dichotomized negative vs positive, <20 vs 20 and I vs III, respectively (Table 4). The relative risk of recurrence was 2.96 for Afadin-negative disease compared to Afadin-positive disease (P=0.028).

Table 4 Cox multivariate analysis of metastasis-free survival for patients without axillary lymph node invasion

Loss of Afadin expression correlates with loss of FHIT expression

We next looked for variation of expression of FHIT on the same TMA (data not shown). We found a loss of expression of both FHIT and Afadin in 26% of cases (Table 3). The loss of these two proteins was correlated (P=0.01). Patients with an Afadin-negative/FHIT-negative tumor showed a poor prognosis as compared to patients with an Afadin-positive/FHIT-positive tumor (P=0.0148) (data not shown). This result suggests that the determination of Afadin expression in patients with a loss of FHIT protein expression, which is a marker of adverse evolution in good prognosis localized breast cancer (Ginestier et al., 2003), may help distinguish a subpopulation with a poorer outcome.

Loss of Afadin expression affects cell–cell junctions

To document the potential role of Afadin in breast cancer we analysed the effect of the loss of Afadin expression on cell behavior. We abolished Afadin expression in MDCK II epithelial cells using artificial microRNA (miRNA). We designed these miRNA to have 100% identity with a sequence of Afadin conserved between human, simian, canine and rodent. Cocistronic expression of emerald green fluorescence protein (EmGFP) and the miRNA in a pcDNA-based vector (pCDmiR-Afadin) allowed the correlation of GFP level and Afadin expression. EmGFP miR-Afadin was used in Cos cells and showed a marked reduction of endogenous Afadin expression (Figure 5a, top). This knockdown was specific. Irrelevant controls (EmGFP-miR-neg and EmGFP-miR-LacZ) did not change Afadin level and no miRNA affect the expression of unrelated protein p85 (Figure 5a, bottom). Analysis of confluent MDCKII cells stably transfected with the pCDmiRAF6-3481 vector showed a marked Afadin knockdown only in cells with high EmGFP levels (Figure 5b). The absence of Afadin expression was associated with a profound disorganization of epithelial cell–cell contacts confirming the fundamental role of Afadin in epithelial physiology previously suggested by the studies of knockout mouse models (Ikeda et al., 1999; Zhadanov et al., 1999).

Figure 5

Afadin knockdown in MDCKII cells leads to the destabilization of cell–cell junctions. (a) Different miRNA expression vectors were tested in Cos cells. Two different miRNA expression plasmids (EmGFP-miR-neg and EmGFP-miR-LacZ) were used as irrelevant controls to assess the specificity of the EmGFP-miR-Afadin plasmid. Cos lysates 10 μg were separated on SDS–PAGE then immunoblotted with Afadin mAb (top) and p85 to control loading (bottom). (b) MDCKII cells stably expressing the EmGFP-miR-Afadin plasmid. Afadin is localized at cell–cell junctions in confluent MDCKII cells as previously described (arrowheads). High EmGFP expression correlates with a marked knockdown of Afadin expression, the destabilization of cell–cell junctions and the extinction of Afadin signal at cell–cell junctions (arrows).


Breast cancer is an heterogeneous cancer with multiple forms and distinct entities (Sorlie et al., 2003; Charafe-Jauffret et al., 2005). A better understanding of the molecular basis of this heterogeneity should allow a better management of the disease. A possible molecular substratum for tumor development and heterogeneity is genetic instability. The identification of a distinct subclass of breast cancer with genomic fragility may help understand disease heterogeneity. This subclass could be recognized by alterations at CFS.

CFSs are highly unstable genomic regions. They could predispose chromosomes to break, generate chromosomal rearrangements in cancer cells and play a role in tumor initiation and/or progression (Huebner et al., 1998; Smith et al., 1998; Sutherland et al., 1998). The cloning and the characterization of FRA6E at 6q26 identified eight genes associated with this fragile site. Among them, PARK2 contains the most unstable region of FRA6E between its exons 2–8 (Denison et al., 2003a). PARK2 is a large gene that is mutated in patients with autosomal recessive juvenile Parkinsonism and spans the telomeric half of FRA6E. PARK2 shows similarities with the two most active CFS-associated genes, FHIT and WWOX. FHIT at FRA3B (3p14) and WWOX at FRA16D (16q23) are both large genes. They both suppress tumor cell growth in vitro and in vivo and have been classified as TSG (Bednarek et al., 2001; Paige et al., 2001; Roz et al., 2002; Huebner and Croce, 2003; Ishii et al., 2003; Fabbri et al., 2005).

PARK2 encodes the Parkin E3 ubiquitin ligase and is altered in various tumors. It is also considered a potential TSG (Cesari et al., 2003; Denison et al., 2003a; Wang et al., 2004). PARK2 alterations were initially reported in breast and ovarian cell lines and tumors (Cesari et al., 2003; Denison et al., 2003a, 2003b). The absence of normal PARK2 transcript and Parkin expression, and the presence of aberrant transcripts and occurrence of genomic deletions have been observed in malignant samples (Denison et al., 2003a). The same observations have been made in hepatocellular carcinomas (Wang et al., 2004) and non-small-cell lung cancer (Picchio et al., 2004).

We first determined the status of FRA6E breaks in breast tumors by using FISH on TMA. We measured the frequency of PARK2 break and its potential impact on clinical outcome. Break of one allele of PARK2 was observed in 6% of tumors. It correlated with decreased 5-year MFS. Loss of Parkin expression was observed in around 13% of cases. Similarly, Parkin expression is decreased in a large proportion of ovarian tumors (Cesari et al., 2003; Denison et al., 2003a). However, we found that loss of Parkin was not correlated with a break of PARK2. This was in sharp contrast to the good correlation observed between alterations at FRA3E and FRA16D and FHIT and WWOX protein levels, respectively (Ginestier et al., 2003; Park et al., 2004). The absence of correlation between FRA6E break and Parkin expression suggests that other mechanisms are responsible for abnormal expression of Parkin. Abnormal methylation may be one of these mechanisms (Agirre et al., 2005).

We hypothesized that the consequences of the PARK2 break on the clinical outcome may be due to a subsequent effect on a 6q gene, telomeric of PARK2. Genes located telomeric of FRA6E may be potential breast cancer genes. Frequent LOH are observed in this region in breast cancer (Orphanos et al., 1995; Noviello et al., 1996; Cesari et al., 2003). The tumorigenicity of breast cell lines can be suppressed by microcell-mediated transfer of a part of human chromosome 6 (Negrini et al., 1994). The 6q26–6q27 region contains several genes including FOP, TTLL2, AF-6/MLLT4, KIF25, THBS2, and TBP. FOP encodes a centrosomal protein that is fused to FGFR1 kinase in myeloproliferative disorders (Popovici et al., 1999; Delaval et al., 2005). It could be interesting to examine if this gene could play a role in oncogenesis out of its fusion with FGFR1. TTLL2 (Tubulin Tyrosine Ligase-like 2) encodes a member of the TTL homology domain protein family, which catalyses the ligation of glutamic acid to tubulin. In neuronal systems, tubulin polyglutamination could regulate the organization of microtubule network (Bonnet et al., 2001) thus controlling centriole stability and mitosis (Bobinnec et al., 1998a, 1998b). KIF25 encodes a protein of the kinesin superfamily, KIF25, which is involved in molecular transport away from the centrosome (Miki et al., 2005). No role in neoplasia has been reported yet for KIF25. The promoter of THBS2 (thrombospondin 2) gene is methylated (62.5%) in primary endometrial carcinoma (Whitcomb et al., 2003). High THBS2 expression may be associated with an angiogenic phenotype in endometrial cancer and THBS2 expression is a marker of poor prognosis in this disease (Seki et al., 2001). The TATA-binding protein encoded by TBP is associated with transcriptional cellular systems. Modulation of TBP concentration has an impact on gene expression that can mediate potential cell transformation (Johnson et al., 2003a, 2003b).

AF-6/MLLT4 encodes Afadin, which is involved in epithelial physiology. It is ubiquitously expressed in normal epithelial cells, where it localizes at adherens and tight junctions (Mandai et al., 1997). Afadin is a scaffold protein that links adhesion proteins, cellular receptors and signaling effectors to the actin cytoskeleton (Mandai et al., 1997; Buchert et al., 1999). Mice lacking the Af-6 gene die at 10 days post coitum of placenta failure (Ikeda et al., 1999; Zhadanov et al., 1999). AF-6 could play a key role in the development of carcinomas. AF-6 is fused to the MLL gene in the t(6;11)(q27;q23) chromosomal translocation, which is the most common translocation found in acute lymphoid leukemia (Prasad et al., 1993). We thus chose to study Afadin because of its role in epithelial physiology and potential involvement in cancer, but also for technical reasons. The two anti-Afadin antibodies work well in IHC on paraffin embedded tissues whereas no appropriate antibody is available for the other proteins encoded by the FRA6E-telomeric genes.

The Afadin status in breast tumors was addressed by using IHC on TMA. Complete loss of Afadin was observed in 14.5% of tumors. Loss was correlated with the break of PARK2 and with a bad outcome for patients without lymph node invasion. We propose that loss of Afadin expression can be due to a break of FRA6E/PARK2. The multivariate analysis showed that Afadin could be a good prognosis marker. In association with grade and Ki67 status, Afadin status may help in the detection of patients with poor prognosis in the lymph node-negative population. Moreover, in the FHIT-negative patient population, Afadin is a marker of poor prognosis. The combined analysis of FHIT and Afadin could be useful to discriminate patients with adverse outcome in the whole population. The coordinated loss of FHIT and WWOX expression has been found in breast cancers (Guler et al., 2005). We have similarly shown here that loss of break of PARK2 and loss of FHIT expression are concomitantly found in some samples. These cases are associated with a poor prognosis. We have not tested WWOX expression on our series.

Finally, we showed that loss of Afadin expression affects adherence of cells in culture. This is in perfect agreement with in vivo data; cell–cell adherens and tight junctions are improperly organized in the ectoderm of Af-6 (−/−) mice and embryoid bodies (Ikeda et al., 1999; Zhadanov et al., 1999). A thorough study has recently described the role of Afadin in the recruitment of E-cadherin and tight junction components at cell–cell junctions (Sato et al., 2006). Like E-cadherin, Afadin expression may be lost in a subgroup of breast cancers.

In conclusion, our data suggest that: (i) frequent breaks in tumors at a CFS should not automatically point to an intrasite gene as involved in cancer; breaks may induce loss of nearby TSG; (ii) Afadin may be a new marker of adverse evolution in patients with apparent good prognosis at diagnosis; (iii) breast tumors with concomitant loss of FRA6E break, Afadin loss and FHIT loss may constitute a subclass with increased genomic fragility; (iv) Afadin may have a role in mammary oncogenesis. It acts as a tumor suppressor whose loss of expression disrupts epithelial integrity and may favor metastasis.

Patients and methods

Patients and histological samples

A consecutive series of 547 unilateral localized invasive breast carcinomas from women treated at the Institut Paoli-Calmettes between October 1987 and December 1999 was studied. According to the WHO classification, this series comprised 386 ductal, 72 lobular, 37 tubular, 8 medullary carcinomas and 44 other histological types. The average age at diagnosis was 59 years (range 25–94 years). A total of 254 tumors were associated with lymph node invasion and 403 were positive for estrogen receptor. Of the 547 cases, 190 cases were available for FISH analysis, and 473 and 352 were available for Parkin and Afadin immunostaining, respectively (Supplementary Table 1).

The various histoclinical factors collected for this series included: patient age, invasive histological type, pathological tumor size, Scarff–Bloom–Richardson (SBR) grade (I–III), peritumoral vascular invasion, axillary lymph node status, estrogen receptor expression (ER), progesterone receptor expression (PR), P53, Parkin, Afadin, as evaluated by IHC with a positivity cutoff value of 1%, ERBB2 status, evaluated by IHC with the 0–3+ score as illustrated by the HercepTest kit scoring guidelines (DakoCytomation, Coppenhagen, Denmark), and Ki67 status as evaluated by IHC with a positive cutoff value at 20%.

TMA construction

TMA were prepared as described previously (Ginestier et al., 2002). For each tumor, three representative tumor areas were carefully selected from a hematoxylin-eosin-safran stained section of a donor block. Core cylinders with a diameter of 0.6 mm each were punched from each of these areas and deposited into three separate recipient paraffin blocks using a specific arraying device (Beecher Instruments, Silver Spring, MD, USA). In addition to tumor tissues, the recipient block also received normal breast tissues and cell lines pellets. Sections 5-μm of the resulting microarrays block were made and used for FISH and IHC analysis after transfer onto glass slides.

Fluorescence in situ hybridization analysis

FISH on TMA was carried out according to a published protocol (Chin et al., 2003; Huang et al., 2004). Based on the split-signal FISH approach (van der Burg et al., 2004), we used a combination of two differently labeled pools of BAC clones overlapping the PARK2 locus as probes (Figure 1a): from telomere to centromere, biotinylated RP11-157B17 (chr6: 163,481,350-163,680,324), RP11-117I16 (AC058815; chr6: 163,177,577- 163,342,875), RP11-153I8 (chr6: 162,898,135- 163,041,573) (revealed in green, FITC) and digoxigenin-labeled RP11-431E19 (chr6: 161,659,375- 161,837,993), RP11-479C23 (chr6: 161,442,754- 161,620,713), RP11-158E9 (chr6: 161,336,365-161,484,919) (revealed in red, TRITC). PARK2 is located on chromosome arm 6q, in the 161,740,081-163,119,211 genomic interval. RP11-153I8 and RP11-431E19 were the two overlapping BAC clones of PARK2 used in this combination. They overlap PARK2 on 221kb and 98kb, respectively (Figure 1a). Genomic information was taken from the UCSC Genome Browser on Human ( – May 2004 Assembly), which is based on NCBI Build 35 (National Center for Biotechnology Information, National Library of Medicine, Bethesda, USA).

DNA from BAC clones were purified, labeled and individually verified for their specificity for chromosome 6. All BAC clones were obtained from the BACPAC resource (Children's Hospital Oakland – BACPAC Resources, Oakland, CA, USA). After counterstaining with Vectashield containing 4,6-diamidino-2-phenylindole (DAPI) (Vector, Burlingame, CA, USA), images were analysed with a microscope (DMRXA, Leica Microsystems, Marseille, France), captured with a CCD camera, filtered and processed with ISIS software (In Situ Imaging Systems, Metasystems Hard- und Software GmbH, Altlussheim, Germany) (described in Fluorescence was scored on a minimum of 50 nuclei per tumor. The 50 nuclei of cancer cells were representative of the overall cell heterogeneity of the tumor. Two observers (AL and CG) read the TMA independently.

Immunohistochemical analysis

The characteristics of the antibodies used are listed in Table 1. IHC was carried out on five-μm sections of tissue fixed in alcohol formalin for 24 h and included in paraffin. Sections were deparaffinized in Histolemon (Carlo Erba Reagenti, Rodano, Italy) and rehydrated in graded alcohol solution. Antigen enhancement was carried out by incubating the sections in target retrieval solution (DakoCytomation, Coppenhagen, Denmark) as recommended. The reactions were carried out using an automatic stainer (Dako Autostainer, Copenhagen, Denmark). Staining was carried out at room temperature as follows: after washes in phosphate buffer, followed by quenching of endogenous peroxidase activity by treatment with 0.1% H2O2, slides were first incubated with blocking serum (DakoCytomation) for 30 min and then with the affinity-purified antibody for 1 h. After washes, slides were incubated with biotinylated antibody against rabbit immunoglobulin for 20 min followed by streptadivin-conjugated peroxidase (DakoCytomation LSABR2 kit). Diaminobenzidine or 3-amino-9-ethylcarbazole was used as the chromogen. Slides were counter-stained with hematoxylin, and coverslipped using Aquatex (Merck, Darmstadt, Germany) mounting solution. Results were evaluated under a light microscope by two pathologists (EC-J, JJ) and scored by the quick score (QS) as previously performed (Ginestier et al., 2002), except for Ki67 status which was expressed in terms of percentage of positive cells, and ERBB2 status, which was evaluated with the Dako scale (HercepTest kit scoring guidelines, DakoCytomation, Coppenhagen, Denmark). For each tumor, the mean of the score of a minimum of two core biopsies was calculated.

RNA silencing and cell transfection

RNA silencing was performed using the BLOCK-iTTM Pol II RNAi expression vector kit as recommended by the manufacturer (Invitrogen, Carlsbad, CA, USA). Artificial Afadin microRNA (miRNA) was cloned in the pcDNA 6.2-GW/EmGFP-miR leading to a cocistronic expression of Emerald GFP (EmGFP) with the miRNA of Afadin. Different sequences of Afadin miRNA were designed using an algorithm developed by Invitrogen. Sense and antisense DNA sequences were: AF6_3481S: TGCT GAGG ACTA GGAG GCTG ATTT GCGT TTTG GCCA CTGA CTGA CGCA AATC ACTC CTAG TCCT, and AF6_3481AS: CCTG AGGA CTAG GAGT GATT TGCG TCAG TCAG TGGC CAAA ACGC AAAT CAGC CTCC TAGT CCTC, respectively. This sequence is located at residue 3481 in AF-6 cDNA and is present in the different Afadin isoforms. MDCK II cells (50% confluent) were transfected with 10 μg of the indicated vectors and selection of transfected cells were selected by 5 μg/ml blasticidin (Invitrogen).

Western blot analysis

Cos cells were lyzed in ice-cold lysis buffer containing 50 mM Hepes, pH 7.5, 150 mM NaCl, 1.5 mM MgCl2, 1 mM EGTA, 1% Triton X-100 and 10% glycerol. A protease inhibitor mixture was added as recommended by the manufacturer (Roche Diagnostics, Meylan, France).

Ten μg of cell lysate was heated in sodium dodecyl sulfate (SDS) sample buffer (60 mM Tris-HCl, pH 6.7, 3% SDS, 2% (v/v) 2-mercaptoethanol, and 5% glycerol) separated by 7.5% SDS–polyacrylamide gel electrophoresis (PAGE), semidry transferred to polyvinylidene difluoride membranes (Immobilon-P, Millipore, Boston, MA, USA), probed with the indicated antibody and visualized with ECL (Amersham Pharmacia Biotech, Uppsala, Sweden).

Immunofluorescence studies

MDCK II cells were cultured on glass coverslips (VWR, West Chester, PA, USA) in Dulbecco's modified Eagle's medium supplemented with 10% fetal calf serum (FCS) until confluence. Cells were then fixed in 4% paraformaldehyde in phosphate-buffered saline (PBS) for 30 min, permeabilized in PBS 0.1% Triton X-100 for 2 × 5 min and blocked with PBS 1% bovine serum albumin (Euromedex, Souffelweyersheim, France) for 30 min. Then the cells were stained with anti-Afadin mAb. Between each incubation, coverslips were washed with PBS containing 0.1 mM CaCl2 and 1 mM MgCl2. Coverslips were mounted on slides with Prolong Gold (Invitrogen). Images were recorded with an Axio Zeiss LSM 510 Meta confocal microscope.

Statistical methods

Descriptive data were summarized by frequency and percentage for categorical variables and by means, median and range for continuous variables. Associations between molecular markers and other categorical variables were examined using χ2 analysis, or Fisher's exact test for small sample sizes. The metastasis-free interval was calculated from the date of diagnosis. The nonmetastatic patients are rightcensored at the last follow-up visit. MFS curves were estimated by the Kaplan–Meier method using the first metastatic recurrence as first event definition, and the curves were compared by the log rank test. All the tests where two-sided and a P-value of less than 0.05 was considered statistically significant. For graphical representation, follow-up was truncated at 120 months. Multivariate analyses for response were performed using Cox's proportional hazards regression model using a backward stepwise selection procedure to evaluate the effect of interaction between the different variables.


  1. Agirre X, Roman-Gomez J, Vazquez I, Jimenez-Velasco A, Garate L, Montiel-Duarte C et al. (2005). Int J Cancer 118: 1945–1953.

  2. Bednarek AK, Keck-Waggoner CL, Daniel RL, Laflin KJ, Bergsagel PL, Kiguchi K et al. (2001). Cancer Res 61: 8068–8073.

  3. Bednarek AK, Laflin KJ, Daniel RL, Liao Q, Hawkins KA, Aldaz CM . (2000). Cancer Res 60: 2140–2145.

  4. Bobinnec Y, Khodjakov A, Mir LM, Rieder CL, Edde B, Bornens M . (1998a). J Cell Biol 143: 1575–1589.

  5. Bobinnec Y, Moudjou M, Fouquet JP, Desbruyeres E, Edde B, Bornens M . (1998b). Cell Motil Cytoskeleton 39: 223–232.

  6. Bonnet C, Boucher D, Lazereg S, Pedrotti B, Islam K, Denoulet P et al. (2001). J Biol Chem 276: 12839–12848.

  7. Buchert M, Schneider S, Meskenaite V, Adams MT, Canaani E, Baechi T et al. (1999). J Cell Biol 144: 361–371.

  8. Cesari R, Martin ES, Calin GA, Pentimalli F, Bichi R, McAdams H et al. (2003). Proc Natl Acad Sci USA 100: 5956–5961.

  9. Charafe-Jauffret E, Ginestier C, Monville F, Fekairi S, Jacquemier J, Birnbaum D et al. (2005). Int J Oncol 27: 1307–1313.

  10. Chin SF, Daigo Y, Huang HE, Iyer NG, Callagy G, Kranjac T et al. (2003). Mol Pathol 56: 275–279.

  11. Delaval B, Letard S, Lelievre H, Chevrier V, Daviet L, Dubreuil P et al. (2005). Cancer Res 65: 7231–7240.

  12. Denison SR, Callahan G, Becker NA, Phillips LA, Smith DI . (2003a). Genes Chromosomes Cancer 38: 40–52.

  13. Denison SR, Wang F, Becker NA, Schule B, Kock N, Phillips LA et al. (2003b). Oncogene 22: 8370–8378.

  14. Dhillon VS, Husain SA, Ray GN . (2003). Teratog Carcinog Mutagen (Suppl 1): 35–45.

  15. Fabbri M, Iliopoulos D, Trapasso F, Aqeilan RI, Cimmino A, Zanesi N et al. (2005). Proc Natl Acad Sci USA 102: 15611–15616.

  16. Ginestier C, Bardou VJ, Popovici C, Charafe-Jauffret E, Bertucci F, Geneix J et al. (2003). Int J Cancer 107: 854–862.

  17. Ginestier C, Charafe-Jauffret E, Bertucci F, Eisinger F, Geneix J, Bechlian D et al. (2002). Am J Pathol 161: 1223–1233.

  18. Guasch G, Delaval B, Arnoulet C, Xie MJ, Xerri L, Sainty D et al. (2004). Blood 103: 309–312.

  19. Guler G, Uner A, Guler N, Han SY, Iliopoulos D, McCue P et al. (2005). Pathol Int 55: 471–478.

  20. Hayashi Y, Raimondi SC, Look AT, Behm FG, Kitchingman GR, Pui CH et al. (1990). Blood 76: 1626–1630.

  21. Huang TJ, Huang BJ, Liang QW, Huang CW, Fang Y . (2004). Hepatobiliary Pancreat Dis Int 3: 62–68.

  22. Huebner K, Croce CM . (2001). Nat Rev Cancer 1: 214–221.

  23. Huebner K, Croce CM . (2003). Br J Cancer 88: 1501–1506.

  24. Huebner K, Druck T, Siprashvili Z, Croce CM, Kovatich A, McCue PA . (1998). Recent Results Cancer Res 154: 200–215.

  25. Ikeda W, Nakanishi H, Miyoshi J, Mandai K, Ishizaki H, Tanaka M et al. (1999). J Cell Biol 146: 1117–1132.

  26. Ishii H, Zanesi N, Vecchione A, Trapasso F, Yendamuri S, Sarti M et al. (2003). FASEB J 17: 1768–1770.

  27. Johnson SA, Dubeau L, Kawalek M, Dervan A, Schonthal AH, Dang CV et al. (2003a). Mol Cell Biol 23: 3043–3051.

  28. Johnson SA, Dubeau L, White RJ, Johnson DL . (2003b). Cell Cycle 2: 442–444.

  29. Kerangueven F, Noguchi T, Coulier F, Allione F, Wargniez V, Simony-Lafontaine J et al. (1997). Cancer Res 57: 5469–5474.

  30. Kitada T, Asakawa S, Hattori N, Matsumine H, Yamamura Y, Minoshima S et al. (1998). Nature 392: 605–608.

  31. Mandai K, Nakanishi H, Satoh A, Obaishi H, Wada M, Nishioka H et al. (1997). J Cell Biol 139: 517–528.

  32. Marin I, Lucas JI, Gradilla AC, Ferrus A . (2004). Physiol Genom 17: 253–263.

  33. Menasce LP, Orphanos V, Santibanez-Koref M, Boyle JM, Harrison CJ . (1994a). Genes Chromosomes Cancer 10: 286–288.

  34. Menasce LP, Orphanos V, Santibanez-Koref M, Boyle JM, Harrison CJ . (1994b). Genes Chromosomes Cancer 10: 26–29.

  35. Miki H, Okada Y, Hirokawa N . (2005). Trends Cell Biol 15: 467–476.

  36. Millikin D, Meese E, Vogelstein B, Witkowski C, Trent J . (1991). Cancer Res 51: 5449–5453.

  37. Negrini M, Sabbioni S, Possati L, Rattan S, Corallini A, Barbanti-Brodano G et al. (1994). Cancer Res 54: 1331–1336.

  38. Noviello C, Courjal F, Theillet C . (1996). Clin Cancer Res 2: 1601–1606.

  39. Orphanos V, McGown G, Hey Y, Boyle JM, Santibanez-Koref M . (1995). Br J Cancer 71: 290–293.

  40. Paige AJ, Taylor KJ, Taylor C, Hillier SG, Farrington S, Scott D et al. (2001). Proc Natl Acad Sci USA 98: 11417–11422.

  41. Park SW, Ludes-Meyers J, Zimonjic DB, Durkin ME, Popescu NC, Aldaz CM . (2004). Br J Cancer 91: 753–759.

  42. Picchio MC, Martin ES, Cesari R, Calin GA, Yendamuri S, Kuroki T et al. (2004). Clin Cancer Res 10: 2720–2724.

  43. Popescu NC . (2003). Cancer Lett 192: 1–17.

  44. Popovici C, Zhang B, Gregoire MJ, Jonveaux P, Lafage-Pochitaloff M, Birnbaum D et al. (1999). Blood 93: 1381–1389.

  45. Prasad R, Gu Y, Alder H, Nakamura T, Canaani O, Saito H et al. (1993). Cancer Res 53: 5624–5628.

  46. Richards RI . (2001). Trends Genet 17: 339–345.

  47. Rodriguez C, Causse A, Ursule E, Theillet C . (2000). Genes Chromosomes Cancer 27: 76–84.

  48. Roz L, Gramegna M, Ishii H, Croce CM, Sozzi G . (2002). Proc Natl Acad Sci USA 99: 3615–3620.

  49. Saito S, Saito H, Koi S, Sagae S, Kudo R, Saito J et al. (1992). Cancer Res 52: 5815–5817.

  50. Sato T, Fujita N, Yamada A, Ooshio T, Okamoto R, Irie K et al. (2006). J Biol Chem 281: 5288–5299.

  51. Seki N, Kodama J, Hashimoto I, Hongo A, Yoshinouchi M, Kudo T . (2001). Int J Oncol 19: 305–310.

  52. Smith DI, Huang H, Wang L . (1998). Int J Oncol 12: 187–196.

  53. Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A et al. (2003). Proc Natl Acad Sci USA 100: 8418–8423.

  54. Sutherland GR, Baker E, Richards RI . (1998). Trends Genet 14: 501–506.

  55. Taki T, Hayashi Y, Taniwaki M, Seto M, Ueda R, Hanada R et al. (1996). Oncogene 13: 2121–2130.

  56. Teixeira MR, Pandis N, Heim S . (2002). Genes Chromosomes Cancer 33: 1–16.

  57. Tibiletti MG, Bernasconi B, Furlan D, Riva C, Trubia M, Buraggi G et al. (1996). Cancer Res 56: 4493–4498.

  58. van der Burg M, Poulsen TS, Hunger SP, Beverloo HB, Smit EM, Vang-Nielsen K et al. (2004). Leukemia 18: 895–908.

  59. Wang F, Denison S, Lai JP, Philips LA, Montoya D, Kock N et al. (2004). Genes Chromosomes Cancer 40: 85–96.

  60. Whitcomb BP, Mutch DG, Herzog TJ, Rader JS, Gibb RK, Goodfellow PJ . (2003). Clin Cancer Res 9: 2277–2287.

  61. Zhadanov AB, Provance Jr DW, Speer CA, Coffin JD, Goss D, Blixt JA et al. (1999). Curr Biol 9: 880–888.

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We thank F Birg and D Maraninchi for encouragements, C Chabannon for biobank sample management and JM Durey for his help with iconography. This work was supported by Institut Paoli-Calmettes, INSERM, and grants from Ligue Nationale Contre le Cancer (LNCC) (Label 2003-2006), the Association pour la Recherche contre le Cancer (ARC-3128) and Ministries of Health and Research (Cancéropôle PACA). SGU, CG and FM are supported by a fellowship from Ministry of Research and AL by a fellowship from LNCC.

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Correspondence to D Birnbaum.

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Letessier, A., Garrido-Urbani, S., Ginestier, C. et al. Correlated break at PARK2/FRA6E and loss of AF-6/Afadin protein expression are associated with poor outcome in breast cancer. Oncogene 26, 298–307 (2007).

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  • Afadin
  • AF-6 gene
  • breast cancer
  • FRA6E
  • Parkin
  • PARK2 gene
  • tissue microarrays

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