Clinical Cancer Research CTRC-AACR San Antonio Breast Cancer Symposium Infection and Cancer: Biology, Therapeutics, and Prevention
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Silva, J.
Right arrow Articles by Bonilla, F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Silva, J.
Right arrow Articles by Bonilla, F.
Clinical Cancer Research Vol. 12, 6929-6936, December 1, 2006
© 2006 American Association for Cancer Research

Human Cancer Biology

Implication of Polycomb Members Bmi-1, Mel-18, and Hpc-2 in the Regulation of p16INK4a, p14ARF, h-TERT, and c-Myc Expression in Primary Breast Carcinomas

Javier Silva1, José M. García1, Cristina Peña1, Vanesa García1, Gemma Domínguez1, Dolores Suárez2, Francisca I. Camacho3, Ruth Espinosa1, Mariano Provencio1, Pilar España1 and Félix Bonilla1

Authors' Affiliations: Departments of 1 Medical Oncology and 2 Pathology, Hospital Universitario Puerta de Hierro, Madrid, Spain and 3 Department of Pathology, Hospital Virgen de la Salud, Toledo, Spain

Requests for reprints: Félix Bonilla, Department of Medical Oncology, Hospital Universitario Puerta de Hierro, C/ San Martín de Porres, 4, E-28035 Madrid, Spain. Phone: 34-91-386-6527; Fax: 34-91-373-7667; E-mail: felixbv{at}stnet.es.


   Abstract
Top
 Abstract
Materials and Methods
 Results
 Discussion
 References
 
Purpose: Deregulation of mammalian Polycomb group (PcG) members may contribute to human carcinogenesis. p16INK4a and p14ARF tumor suppressors, human telomerase reverse transcriptase (h-TERT), and oncoprotein c-Myc have been implicated in the regulation of the cell cycle and proliferation mediated by PcG proteins, mainly Bmi-1, in mice and in cell culture experiments. Here, we examine whether these in vitro findings can be extrapolated to the in vivo situation.

Experimental Design: We measure the expression of PcG members Bmi-1, Mel-18, and Hpc-2 and their potential targets by reverse transcription-PCR, immunostaining, and Western blotting in a series of 134 breast carcinomas and correlate the data with several clinical-pathologic variables of the tumors.

Results: Expression of PcG genes was variably detected, but overexpression of Bmi-1 was the most frequent PcG alteration observed. In addition, statistical direct correlation in expression level of the three PcG members was detected. A correlation between c-Myc and Bmi-1 expression levels was observed; however, there was no correlation between expression of Bmi-1 and p16INK4a, p14ARF, or h-TERT. However, expression of the other PcG members Mel-18 and Hpc-2 correlated with the cell cycle regulators. Moreover, PcG mRNA–altered expression correlated significantly with certain clinical-pathologic variables associated with poor prognosis.

Conclusions: Our data suggest that the oncogenic role of Bmi-1 in human primary breast carcinomas is not determined by its capacity to inhibit INK4a/ARF proteins or to induce telomerase activity.

The Polycomb group (PcG) consists of several proteins that form multiprotein complexes, 2 to 5 MDa in size, that regulate gene activity at the chromatin level. In the 1980s, the first components of Drosophila PcG were identified and several years later were recognized in mammalian cells, indicating strong evolutionary conservation (1). However, unlike the ubiquitous expression of Drosophila genes, the expression levels of mammalian PcG genes differ between tissues and cell types (2). PcG proteins, together with the counteracting Trithorax group (TrxG) proteins, were initially identified as part of the memory system that ensures the faithful transmission of cell identities throughout cell division (3). PcG genes were discovered as epigenetic silencers during embryo morphogenesis with a central role in the nervous system, heart, and skeleton development (4–8). Additionally, PcG members have been implicated in the regulation of such adult processes as the cell cycle, X-inactivation, and hematopoiesis (9–15). PcG protein expression seems tightly regulated in normal cell proliferation and differentiation. However, PcG expression is often deregulated in several types of human cancer (16). Moreover, several PcG genes seem to regulate the self-renewal of specific stem cell types, suggesting a link between the maintenance of cell homeostasis and carcinogenesis (17, 18).

Bmi-1 was initially identified as an oncogene that cooperated with c-Myc in the generation of mouse pre-B-cell lymphomas. It is also considered the first functional mammalian PcG proto-oncogene to be recognized, and it has been implicated in axial patterning, hematopoiesis, cell cycle regulation, and senescence (19–22). Data obtained in mice and in vitro studies have indicated that Bmi-1 protein regulates the INK4a/ARF locus, which encodes two unrelated tumor suppressors, p16INK4a and p19ARF (p14ARF in humans), which act in the two main cell cycle control pathways (pRb and p53, respectively). p16INK4a affects the retinoblastoma protein (pRb) by inhibiting the cyclin D/cyclin-dependent kinase 4/6 kinase complex. In the absence of Bmi-1, p16INK4a may be up-regulated and prevent binding of cyclin-dependent kinase 4/6 to cyclin D, thus inhibiting kinase activity. This fact results in hypophosphorylated pRb, which then binds E2F and inhibits E2F-mediated transcription of E2F target genes that are important for the G1-S transition. Thus, hypophosphorylated pRb ultimately leads to cell cycle arrest, senescence, or apoptosis depending on context. In contrast, deregulation of p16INK4a by Bmi-1 involves pRb hyperphosphorylation, which allows cell cycle progression. The INK4a/ARF locus also encodes p19ARF, which sequesters the p53 inhibitor MDM2 and thereby prevents the degradation of p53, resulting in p53-mediated cell cycle arrest and apoptosis. Thus, Bmi-1 overexpression inhibits p16INK4a and p19ARF activity and prevents activation of the INK4a/ARF failsafe mechanism (23–25). In addition, other targets of PcG proteins have been reported. Enhanced Bmi-1 expression in immortal mammary epithelial cells (MEC) led to transcription of human telomerase reverse transcriptase (h-TERT) and induction of telomerase. The activation of h-TERT extended the replicative life span and immortalized MECs, suggesting regulation of telomerase expression by Bmi-1 in the development of human breast cancer (26).

Unlike Bmi-1, the closely related Mel-18 was believed to have tumor-suppressive effects because Mel-18 inhibition enabled immortal NIH 3T3 to form tumors in nude mice (27). Subsequently, it was reported that Mel-18 regulates the cell cycle negatively through the Myc/cdc25 cascade (28). Human Hpc-2 was another PcG member identified as a repressor of c-Myc oncogene activity (29). Moreover, in contrast to Bmi-1, which induces S-phase entry by inhibiting Rb function via repression of the INK4a/ARF locus, Hpc-2 might arrest cells in G2-M by co-operating with Rb-E2F in repressing cyclin A and Cdc2 (30). These data suggest that PcG complexes have opposing roles, and that the eventual effect on the cell cycle depend on the relative concentration of a certain PcG protein (2). Thus, combined with the differential cell type–specific expression, it is likely that the balance of Bmi-1 and other PcG proteins, like Hpc-2 or Mel-18, is critical to target gene specificity. PcG complexes containing predominantly Bmi-1 may cooperate with c-Myc oncogenic activity and promote tumorigenesis by inhibiting INK4a/ARF proteins and by activating h-TERT, whereas complexes with higher concentrations of Mel-18 or Hpc-2 may act upstream of c-Myc, inhibiting cell proliferation.

In human tumors, several reports have described alterations in PcG expression, mainly in such human hematologic malignancies as nodal B-cell lymphomas (31, 32), mantle cell lymphomas (33, 34), and Hodgkin's lymphomas (14, 35, 36). Previous reports showed that solid tumors, such as lung cancers (37), medulloblastomas (4), liver (38), penis (39), breast (40, 41), colon (42), and prostate carcinomas (43), also display disturbed PcG gene expression, and some authors correlated these expression patterns with poor prognosis.

In spite of the foregoing, most data on PcG members come from observations in established tumor cell lines or from studies in mice. Thus, it is important to examine the relevance of these findings in human cancer. This implies a more comprehensive study of PcG expression in human cancers, including the known targets and related proteins. Here, we examine the mRNA and protein expression of Bmi-1, Mel-18, and Hpc-2 in a series of primary breast carcinomas. We also evaluate the correlations between PcG levels and the expression of the tumor suppressors p16INK4a and p14ARF and h-TERT. Expression of c-Myc was also analyzed to evaluate potential cooperation between c-Myc amplification and enhanced Bmi-1 expression in the development of breast cancer. Furthermore, a correlation study between expression levels of all the analyzed genes and several clinical pathologic variables of the tumors was designed, with the objective of appraising the prognostic value of these expression patterns.


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results
 Discussion
 References
 
Patients, tissue sampling, nucleic acid extraction, and clinical-pathologic variables. A prospective study that started in 2001 allowed us to identify and recruit 134 patients with breast cancer. The study was approved by the Research Ethics Board of our hospital, and participants gave their informed consent. Normal tissues and tumor tissues were obtained sequentially, immediately after mastectomy. These samples were then snap-frozen in liquid nitrogen and stored at –80°C until processing. All specimens were examined pathologically to confirm the diagnosis of breast carcinoma, to establish the pathologic stage, and to select the areas with least contamination of normal cells so that all tumor samples contained at least 75% tumor cells. No evidence of disseminated disease was observed at diagnosis in any patient. RNA was extracted from about 30 mg of tumor and of normal samples from the same breast in the 134 patients by RNeasy Mini kit (Qiagen, Inc., Hilden, Germany) and was quantified spectrophotometrically.

The following variables were obtained from the medical records of the 134 patients: age, tumor size, lymph node metastases, presence of steroid receptors (estrogen and progesterone), pathologic stage, histologic grade, proliferation index, erbB2 expression, vascular invasion, and p53 immunoassaying status. Pathologic stage was assessed using the tumor-node-metastases classification. The steroid receptor content was determined by an immunohistochemical procedure. The proliferation index was calculated by the Ki-67 antigen (Immunotech, Westbrook, ME) in immunohistochemistry analyses. ErbB2 expression was evaluated by a monoclonal mouse antibody (CB11; Novocastra Lab. Ltd., Newcastle, United Kingdom). Immunohistochemistry of p53 was analyzed with the cl 1801 mouse monoclonal antibody (Oncogene Science, Manhasset, NY) based on its ability to detect up to 89% of p53 point mutations (44).

Real-time PCR analysis. Bmi-1, Mel-18, Hpc-2, p16INK4a, p14ARF, c-Myc, and h-TERT expression levels were quantified in the tumor and in normal samples of the 134 breast cancer patients by real-time quantitative PCR. Ten of the 11 genes studied (six target and four housekeeping genes), except h-TERT, were detected in all tissue samples. mRNA levels were calculated in the tumor and normal tissues in a relative quantification approach, by which the amounts of the targets were expressed in relation to the geometric average of three reference housekeeping genes, TATA binding protein (TBP), succinate dehydrogenase complex subunit A (SDHA), and ubiquitin C (UBC), as a ratio target/geometric average of housekeeping gene in each sample. The relative concentration of the target and the reference genes was calculated by interpolation with a standard curve of each of the respective genes generated with a serial dilution of a cDNA from RNA extracted from normal tissue. We calculated the expression level of a target gene in a patient as the ratio: target in tumor tissue/target in normal tissue [R(T/N)]. A commercial kit (LightCycler TeloTAGGG hTERT, Roche Diagnostics, Mannheim, Germany) was used for the quantification of telomerase. This is a one-step reverse transcription-PCR kit for the quantitative detection of mRNA, encoding for human telomerase catalytic subunit h-TERT, and porphobilinogen deaminase (PBGD) is processed for use as housekeeping gene. h-TERT was detected in less of 25% of the healthy samples but in 93% of the tumors. Thus, telomerase activity was measured in tumor samples as a ratio of the concentration of h-TERT (copies per µL) to the concentration of PBGD (copies per µL). Finally, these values were normalized by using log10.

For the synthesis of the first-strand cDNA, 400 ng of total RNA was retro-transcribed using the Gold RNA PCR Core kit (PE Applied Biosystems, Foster City, CA), following the manufacturer's instructions. Random hexamers were the primers used for cDNA synthesis. Reverse transcription-PCR was done in a LightCycler apparatus with the LightCycler-FastStart DNA Master SYBR Green I kit (Roche Diagnostics). Each reaction was done in a final volume of 20 µL containing 2 µL of the cDNA product sample, 3 mmol/L MgCl2, 0.5 µmol/L of each primer, and 1x reaction mix, including FastStar DNA polymerase, reaction buffer, deoxynucleotide triphosphates, and SYBR green. Thermal cycling for all genes was initiated with a denaturation step of 95°C for 10 minutes followed by 30 to 35 cycles (denaturation at 94°C 2 seconds, specific annealing temperature for 5 seconds, and elongation at 72°C for 5 seconds, in which fluorescence was acquired). The primers and amplification conditions used are shown in Table 1 . At the end of the PCR cycles, melting curve analyses and electrophoresis of the products on nondenaturing 8% polyacrylamide gels, together with a molecular weight marker, were run to validate the generation of the expected specific PCR product. The allelic band intensity on the gels was detected by non-radioisotopic means, using commercially available silver staining method (45). The bands were sequenced in an ABI Prism 377 DNA sequencer apparatus (PE Applied Biosystems).


View this table:
[in this window]
[in a new window]

  		Table 1. Primer sequences for real-time quantification analysis

 
Immunohistochemistry assay. Immunophenotype analysis of 10 breast carcinomas showing differential mRNA expression of Bmi-1 was done according to standard procedures, with overnight incubation in the presence of BMI-1(c-20) polyclonal primary antibody raised against a peptide mapping near the COOH terminus of human Bmi-1 (sc8906, Santa Cruz Biotechnology, Santa Cruz, CA; diluted 1:10). Anti-goat biotin-SP-conjugated AffiniPure F(ab) fragment (705-066-147, Jackson ImmunoResearch Europe Ltd., Suffolk, United Kingdom) was used as secondary antibody. All immunostaining was done using the TechMate 500 (DAKO, Carpinteria, CA) automatic immunostaining device. Tonsil mantle cells were used as positive control. Positive cases exhibited cytoplasmic signal associated to nuclear staining, whereas negative cases exhibited an unspecific cytoplasmic staining. Bmi-1 protein was considered positive in tissue samples exhibiting nuclear staining in >20% of epithelial cells.

Western blotting assay. Mel-18 and Hpc-2 Western blottings were carried out in 10 breast carcinomas samples and normal counterparts. Total protein from frozen tumor and counterpart normal tissues was extracted by suspending in a lysing buffer [1% NP40, 25% glycerol, 420 mmol/L NaCl, 1.5 mmol/L MgCl2, 5 mmol/L EDTA, 200 mmol/L ß-glycerol, 0.5% sodium deoxycholate, 200 mmol/L Tris (pH 7.9)] containing a protease inhibitor mixture and homogenized in a potter. Lysates were centrifuged twice at 14,000 rpm for 15 minutes, and supernatants (30 µg protein) were loaded onto 10% SDS-PAGE gels, electrophoresed, and transferred to Optitran nitrocellulose membranes (Whatman). Membranes were immunoblotted with Hpc-2 (ab4189) and Mel-18 (ab5267) antibodies followed by washing and incubation with horseradish peroxidase–conjugated secondary antibodies. Antibody for ß-actin (ab8227) was used as internal control. Proteins were visualized using Lumi-LightPLUS Western Blotting Substrate (Roche Diagnostic).

Data analysis. The ratios of gene expression were not normally distributed (Kolmogorov-Smirnov test). The distribution was thus established by using log10, and geometric averages were compared. Correlation between expression levels was studied using the Pearson coefficient. Correlation between gene expression ratios and clinical pathologic variables in the tissue samples was analyzed by the ANOVA test. Two-tailed Ps ≤ 0.05 were considered statistically significant. Statistical analysis was done using version 11.0 of the SPSS package.


   Results
Top
 Abstract
 Materials and Methods
 Results
Discussion
 References
 
mRNA quantitative expression versus protein analysis. To validate mRNA expression data, we did immunohistochemical and Western blotting analysis. Thus, 10 breast carcinomas were analyzed for Bmi-1 protein expression by immunohistochemistry using Bmi-1-specific antibody (Fig. 1 ). Bmi-1 immunoreactivity was observed in 50% of the breast cancer cases, and protein expression correlated with mRNA quantification in 7 of the 10 breast samples (70%). Furthermore, other 10 breast carcinomas were analyzed for Mel-18 and Hpc-2 protein expression by Western blotting assay using specific antibodies (Fig. 2 ). Mel-18 and Hpc-2 were variably detected in 100% of the breast cancer cases analyzed, and protein expression correlated with mRNA quantification in 8 of the 10 breast samples (80%). Together, the elevated frequencies of concordance between mRNA expression data and protein expression suggest the absence of dramatic posttranscriptional events affecting protein level.


Figure 1
View larger version (101K):
[in this window]
[in a new window]

  		Fig. 1. Bmi-1 immunohistochemistry. Negative tumor case showing nonspecific cytoplasmic staining (A) and tonsil mantle cells used as positive control (B). Two positive examples from two different tumor cases: nonspecific cytoplasmic staining (C and D) and tonsil mantle cells (E and F).

 

Figure 2
View larger version (20K):
[in this window]
[in a new window]

  		Fig. 2. Western blotting of Mel-18 and Hpc-2. Tumors 1 and 2, decreased protein expression of Mel-18 and Hpc-2. Tumor 3, overexpression of Hpc-2. Tumor 5, overexpression of Mel-18. Tumor 4, with both proteins overexpressed.

 
Analysis and correlation of PcG mRNA expression levels. Statistically significant direct correlations were observed between mRNA expression of several genes in our series of primary breast carcinomas (Table 2 ). The highest Pearson coefficients were obtained for the correlation between Mel-18 and Hpc-2 (r = 0.599) and between Bmi-1 and Mel-18 (r = 0.501). Expression of Bmi-1 also correlated with Hpc-2, although the coefficient was lower (r = 0.363).


View this table:
[in this window]
[in a new window]

  		Table 2. Correlation among Bmi-1, Mel-18, Hpc-2, p16INK4a, p14ARF, h-TERT, and c-Myc expression in the 134 primary breast carcinomas

 
Analysis of correlation between p16INK4a, p14ARF, and PcG levels. The expected correlation between Bmi-1 oncogene overexpression and down-regulation of p16INK4 and p14ARF tumor suppressors was not found in our series (r = 0.209 and r = 0.016, respectively). However, there was a significant association between the other PcG members (Mel-18 and Hpc-2) and the expression of both tumor suppressors. The highest correlations were between Mel-18 and p16INK4a (r = 0.437) and between Hpc-2 and p14ARF (r = 0.449). We had previously reported concomitant expression of p16INK4a and p14ARF in a different series, which indicated that these proteins were co-altered in primary breast tumors.

Analysis of h-TERT activation by PcG genes. In our series human breast carcinomas, there was no evidence implicating Bmi-1 in the regulation of telomerase expression. There was no correlation between telomerase activation and Bmi-1 expression (r = 0.037). Similarly, expression of h-TERT was not correlated with expression of the other PcG genes (Mel-18 and Hpc-2: r = 0.077 and r = 0.004, respectively).

Analysis of the PcG genes and c-Myc cooperation. A weak correlation was found between Bmi-1 and c-Myc, but the Pearson coefficient was lower (r = 0.236) than for the other associations found. Stronger associations were observed between concomitant expression of c-Myc and the other PcG members (Mel-18 and Hpc-2: r = 0.370 and r = 0.332, respectively). Similarly, altered expression of c-Myc correlated with altered expression of the tumor suppressors genes (p16INK4a and p14ARF: r = 0.427 and r = 0.355, respectively).

Frequencies of altered expression of PcG members. To improve the statistical study, we included additional data analysis methods to check mRNA expression level of PcG genes. Thus, altered expression of Bmi-1, Mel-18, and Hpc2 was arbitrarily considered in tumor tissues when expression showed a 4-fold increase or decrease with respect to normal counterpart samples. We found altered expression of the three genes, but the strongest tendency was towards overexpression of Bmi-1 (20.9%) in comparison with the other genes analyzed (Mel-18 and Hpc-2). Increased Bmi-1 expression was similar to that shown in previous reports (Table 3 ).


View this table:
[in this window]
[in a new window]

  		Table 3. Frequencies of altered expression of Bmi-1, Mel-18, and Hpc-2 (4-fold expression analysis) in the 134 primary breast carcinomas

 
Correlation between mRNA expression and clinical-pathologic variables. Several of the analyzed variables showed significant associations with the mRNA expression levels (Table 4 ; Fig. 3 ). Thus, tumors with high expression of Bmi-1 correlated with negative p53 immunostaining and with positive progesterone receptors. Elevated values of expression of both p14ARF and c-Myc correlated with tumors with more than three lymph node metastases. Finally, positive Ki-67 proliferation index correlated with high levels of h-TERT. Moreover, we analyzed the possible association between the clinical-pathologic variables and different combinations of concomitant expression levels, but resulting subgroups of these different combinations did not contain sufficient samples to ensure statistically significant correlations. Nevertheless, we observed a trend between concomitant high expression of Mel-18/Hpc-2 or Mel-18/Bmi-1 and positive peripheral vascular invasion (data not shown). Tumors with concomitant expression of c-Myc and Bmi-1 were not correlated with variables of poor prognosis (data not shown).


View this table:
[in this window]
[in a new window]

  		Table 4. Correlations between expression levels and clinical-pathologic variables

 

Figure 3
View larger version (12K):
[in this window]
[in a new window]

  		Fig. 3. Association of Bmi-1 expression levels and clinical-pathologic features. Logarithm of Bmi-1 expression and p53 immunohistochemistry (A), logarithm of Bmi-1 expression and progesterone receptor immunohistochemistry (B), logarithm of c-Myc expression and lymph node metastases (C), logarithm of p14ARF expression and lymph node metastases (D), and logarithm of h-TERT expression and Ki-67 index (E).

 

   Discussion
Top
 Abstract
 Materials and Methods
 Results
 Discussion
References
 
PcG proteins modulate expression of key developmental regulators, such as homeotic genes, but they have also been implicated in the regulation of cell proliferation and therefore in tumorigenesis. The data obtained in established tumor cell lines or in mice suggest that Bmi-1 expression contributes to the development of tumors, and that the oncogenic activity proceeds from its capacity to down-regulate INK4a/ARF suppressor proteins, desensitizing cells to apoptosis and facilitating cell proliferation. However, the effect of Bmi-1 overexpression on the inactivation of the INK4a/ARF transcripts in human tumorigenesis is unclear. In the present study, we examined the mRNA levels of Bmi-1, p16INK4a, and p14ARF genes to assess the status of this pathway in primary breast tumors. Initially, we did two different protein expression assays to check potential posttranscriptional mechanisms that may affect protein levels of Bmi-1 and of the other two PcG members (Mel-18 and Hpc-2). Although high mRNA expression levels of Bmi-1 were frequently observed in our series of tumors (fact that is consistent with an oncogenic role for Bmi-1), they did not correlated with down-regulated p16INK4a or p14ARF expression, similarly to previous reports. Therefore, it seems that Bmi-1 may contribute to breast carcinogenesis but not by repressing p16INK4a or p14ARF proteins. In any case, this lack of correlation can not be interpreted as lack of regulation or relation between the proteins so that it may be possible that other inactivation mechanisms or other proteins regulating the INK4a/ARF locus can contribute to mask such regulation.

Previous studies reported that Bmi-1 induces telomerase activity and immortalizes human mammary epithelial cells (26). Thus, it has been suggested that activation of h-TERT by Bmi-1 may play a role in the development of human breast cancer. Expression of h-TERT in our series of primary breast carcinomas was extensive (93%), but it was generally absent in the normal tissue counterparts. However, telomerase levels in the tumors were not significantly correlated with high levels of Bmi-1 expression. Therefore, it seems that the oncogenic activity of Bmi-1 in human breast carcinogenesis cannot be explained by the induction of telomerase expression.

It has been proposed that PcG complexes containing predominantly Bmi-1 may cooperate with c-Myc oncogenic activity and promote tumorigenesis (2). Thus, expression of c-Myc was also analyzed in our series to evaluate the potential collaboration between c-Myc amplification and enhanced Bmi-1 expression in the development of breast cancer. Although a correlation between c-Myc and Bmi-1 expression levels was observed, tumors showing elevated expression of both genes were not associated to a worse prognosis.

Our results suggest that INK4a/ARF transcripts and PcG proteins Mel-18 and Hpc-2 are co-expressed. Furthermore, because Mel-18 and Hpc-2 are believed to be tumor suppressor genes, these PcG proteins may be regulated in the same way as other protective genes, like p16INK4a and p14ARF, in the tumor-suppressive cell response. In this respect, the induction of high levels of several tumor suppressors may then be a compensatory, albeit ineffective, cellular response to oncogenic stimuli, which would inhibit the oncogenic pathway. Thus, elevated expression of the c-Myc oncogene correlated with increased expression of these four tumor suppressor genes, which is consistent with our suggestion of multiple antitumor responses. Nevertheless, although these data are mainly descriptive, and although additional studies are required to clarify the mechanistic insights into the regulatory features, we suggest a new insight into the relation between PcG genes and cell proliferation regulators.

Bmi-1, Mel-18, and Hpc-2 are members of the same Polycomb repressive complex (PRC1), which is involved in the maintenance of a stable pattern of gene suppression, and their co-expression has been reported (35, 40). Nevertheless, several non-PcG proteins may contribute to the silencing activity of PcG complex, such as the transcription modulators CtBP, E2F6, nuclear factor-{kappa}B, KyoT2, RYBP, AF9, SSX, Cited2, and the mitogen-activated protein kinase–activated kinase 3pK (36, 46–53). Thus, in our primary breast carcinomas, Bmi-1, Mel-18, and Hpc-2 may be activated or repressed by some of these common regulating proteins. The concomitant expression of p16INK4a and p14ARF indicates that they were co-altered in primary breast tumors, as we previously reported (54).

Significant associations were found between mRNA levels of several genes and certain clinical-pathologic variables of the tumors. Increased expression of Bmi-1 correlated with positive progesterone receptors. A trend was also observed between high levels of Bmi-1 with positive estrogen receptors and between increased expression of Mel-18 and Hpc-2 with positive steroid receptors. The correlation between Bmi-1 and steroid receptors has recently been reported by others (41), but such a correlation for Mel-18 and Hpc-2 is new. This finding indicates that Polycomb genes may be appropriate markers to select cancer patients for treatment with hormonal therapy. A trend was observed between low expression levels of Hpc-2 and high tumor size, which supports the tumor suppressor role proposed for Hpc-2. In addition, high expression of Bmi-1 correlated with positive p53 immunostaining (p53 mutated). It was hypothesized that alterations in genes that act on the same pathway are functionally equivalent; therefore, these alterations may not be present in the same tumor. Furthermore, evidence supporting direct biochemical interactions between INK4a/ARF genes and p53 has been reported. If Bmi-1 protein contributes to cancer progression by repression of INK4a/ARF proteins, then concomitant p53 mutation may be an equivalent alteration and these two events might exclude each other. However, down-regulation of INK4a/ARF transcripts by Bmi-1 was not detected in our series of breast carcinomas. Thus, our data indicate that oncogenic activity of Bmi-1 is independent of the ARF/p53 pathway. In this respect, recent screenings of human cells using small interfering RNA constructs showed that Bmi-1 does not allow circumvention of the p53 pathway (55). We also found a significant correlation between tumors with decreased p14ARF or c-Myc expression and low number of lymph node metastases. The association is consistent with the oncogenic activity of c-Myc. Furthermore, p14ARF is known to be activated by c-Myc, and this fact may explain the correlation of this tumor suppressor gene and axillary lymph node metastasis.

In conclusion, our results suggest that Bmi-1 and its binding partners Mel-18 and Hpc-2 are coordinately deregulated. Interestingly, we observed a correlation between expression levels of Mel-18 and Hpc-2 with expression of p16INK4a and p14ARF. In contrast to the previous data observed in vivo or in vitro, p16INK4a and p14ARF expression were not down-regulated by Bmi-1 in our series of tumors, although other regulatory mechanisms may influence INK4a/ARF status. Likewise, telomerase levels were not altered by expression of Bmi-1. Thus, in human breast carcinogenesis, the role of Bmi-1 inhibiting INK4a/ARF proteins or inducting telomerase activity is not clear. Alternatively, these regulating mechanisms could play a transient role in the transformation process, which may not be evident in later tumor stages.


   Acknowledgments
 
We thank Robin Rycroft for English correction.


   Footnotes
 
Grant support: Fundación Científica de la Asociación Española Contra el Cáncer, Fundación Banco Santander Central Hispano, and grants SAF 2001-0004 and GEN 2001-4856.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Conflict of interest statement: The final text was reviewed and approved by all the listed co-authors. They all contributed to the intellectual content and to the experimental work in an honest manner. There are no conflicts of interest. The contents have not been published by or submitted to any other journal. No part of this text has been included in any other article.

Received 3/30/06; revised 7/11/06; accepted 8/24/06.


   References
Top
 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

  1. Satijn DPE, Hamer CM, Den Blaauwen J, Otte AP. The polycomb group protein EED interacts with YY1 and both proteins induce neural tissue in Xenopus embryos. Mol Cell Biol 2001;21:1360–9.[Abstract/Free Full Text]
  2. Jacobs JJ, van Lohuizen M. Polycomb repression: from cellular memory to cellular proliferation and cancer. Biochim Biophys Acta 2002;1602:151–61.[Medline]
  3. Francis NJ, Kingston RE. Mechanisms of transcriptional memory. Nat Rev Mol Cell Biol 2001;2:409–21.[CrossRef][Medline]
  4. Leung C, Lingbeek M, Shakhova O, et al. Bmi1 is essential for cerebellar development and is overexpressed in human medulloblastomas. Nature 2004;428:337–41.[CrossRef][Medline]
  5. van der Lugt NM, Domen J, Linders K, et al. Posterior transformation, neurological abnormalities and severe hematopoietic defects in mice with a targeted deletion of the bmi-1 proto-oncogene. Genes Dev 1994;8:757–69.[Abstract/Free Full Text]
  6. Koga H, Kaji Y, Nishii K, et al. Overexpression of Polycomb-group gene rae28 in cardiomyocytes does not complement abnormal cardiac morphogenesis in mice lacking rae28 but causes dilated cardiomyopathy. Lab Invest 2002;82:375–85.[Medline]
  7. Caretti G, Di Padova M, Micales B, Lyons GE, Sartorelli V. The Polycomb Ezh2 methyltransferase regulates muscle gene expression and skeletal muscle differentiation. Genes Dev 2004;18:2627–38.[Abstract/Free Full Text]
  8. Alkema MJ, van der Lugt NM, Bobeldijk RC, Berns A, Koseki H. Transformation of axial skeleton due to overexpression of bmi-1 in transgenic mice. Nature 1996;374:724–7.
  9. Heard E. Recent advances in X-chromosome inactivation. Curr Opin Cell Biol 2004;16:247–55.[CrossRef][Medline]
  10. Lessard J, Baban D, Sauvageau G. Stage-specific expression of polycomb group genes in human bone marrow cells. Blood 1998;91:1216–24.[Abstract/Free Full Text]
  11. Lessard J, Schumacher A, Thorsteinsdottir U, van Lohuizen M, Magnuson T, Sauvageau G. Functional antagonism of the Polycomb-group genes eed and Bmi1 in hemopoietic cell proliferation. Genes Dev 1999;13:2691–703.[Abstract/Free Full Text]
  12. Peytavi R, Hong SS, Gay B, et al. HEED, the product of the human homolog of the murine eed gene, binds to the matrix protein of HIV-1. J Biol Chem 1999;274:1635–45.[Abstract/Free Full Text]
  13. Fukuyama T, Otsuka T, Shigematsu N, et al. Proliferative involvement of ENX-1, a putative human polycomb group gene, in haematopoietic cells. Br J Haematol 2000;108:842–7.[CrossRef][Medline]
  14. Raaphorst FM, van Kemenade FJ, Blokzijl T, et al. Coexpression of BMI-1 and EZH2 polycomb group genes in Reed-Sternberg cells of Hodgkin's disease. Am J Pathol 2000;157:709–15.[Abstract/Free Full Text]
  15. Raaphorst FM, Otte AP, van Kemenade FJ, et al. Distinct BMI-1 and EZH2 expression patterns in thymocytes and mature T cells suggest a role for Polycomb genes in human T cell differentiation. J Immunol 2001;166:5925–34.[Abstract/Free Full Text]
  16. Raaphorst FM. Deregulated expression of polycomb-group oncogenes in human malignant lymphomas and epithelial tumours. Hum Mol Genet 2005;14:93–100.
  17. Valk-Lingbeek ME, Bruggeman SW, van Lohuizen M. Stem cells and cancer; the polycomb connection. Cell 2004;118:409–18.[CrossRef][Medline]
  18. Gil J, Bernard D, Peters G. Role of Polycomb group proteins in stem cell-renewal and cancer. DNA Cell Biol 2005;24:117–25.[CrossRef][Medline]
  19. Haupt Y, Alexander WS, Barri G, Klinken SP, Adams J. Novel zinc finger gene implicated as myc collaborator by retrovirally accelerated lymphomagenesis in E mu-myc transgenic mice. Cell 1991;65:753–63.[CrossRef][Medline]
  20. van Lohuizen M, Frasch M, Wientjens E, Berns A. Sequence similarity between the mammalian bmi-1 proto-oncogene and the Drosophila regulatory genes Psc and Su(z)2. Nature 1991;353:353–5.[CrossRef][Medline]
  21. Brunk BP, Martin EC, Adler PN. Drosophila genes Posterior Sex Combs and Suppressor two of zeste encode proteins with homology to the murine bmi-1 oncogene. Nature 1991;353:351–3.[CrossRef][Medline]
  22. Haupt Y, Bath ML, Harris AW, Adams J. Bmi-1 transgene induces lymphomas and collaborates with myc in tumourigenesis. Oncogene 1993;8:3161–4.[Medline]
  23. Jacobs JJ, Scheijen B, Voncken JW, Kieboom K, Berns A, van Lohuizen M. Bmi-1 collaborates with c-Myc in tumourigenesis by inhibiting c-Myc-induced apoptosis via INK4a/ARF. Genes Dev 1999;13:2678–90.[Abstract/Free Full Text]
  24. Jacobs JJ, Kieboom K, Marino S, DePinho RA, van Lohuizen M. The oncogene and Polycomb-group gene bmi-1 regulates cell proliferation and senescence through the ink4a locus. Nature 1999;397:164–8.[CrossRef][Medline]
  25. Sherr CJ. The INK4/ARF network in tumour suppression. Nat Rev 2001;2:731–7.[CrossRef]
  26. Dimri GP, Martinez JL, Jacobs JJ, et al. The Bmi-1 oncogene induces telomerase activity and immortalizes human mammary epithelial cells. Cancer Res 2002;62:4736–45.[Abstract/Free Full Text]
  27. Kanno M, Hasegawa M, Ishida A, Isono K, Taniguchi M. Mel-18, a Polycomb group-related mammalian gene, encodes a transcriptional negative regulator with tumour suppressive activity. EMBO J 1995;14:5672–8.[Medline]
  28. Tetsu O, Ishihara K, Kanno R, et al. Mel-18 negatively regulates cell cycle progression upon B cell antigen receptor stimulation through a cascade leading to c-myc/cdc25. Immunity 1998;9:439–48.[CrossRef][Medline]
  29. Satijn DPE, Hamer CM, Olson DJ, et al. Interference with the expression of a novel human polycomb protein, hPc2, results in cellular transformation and apoptosis. Mol Cell Biol 1997;17:6076–86.[Abstract]
  30. Dahiya A, Wong S, Gonzalo S, Gavin M, Dean DC. Linking the Rb and polycomb pathways. Mol Cell 2001;8:557–68.[CrossRef][Medline]
  31. van Kemenade FJ, Raaphorst FM, Blokzijl T, et al. Coexpression of BMI-1 and EZH2 polycomb-group proteins is associated with cycling cells and degree of malignancy in B-cell non-Hodgkin lymphoma. Blood 2001;97:3896–901.[Abstract/Free Full Text]
  32. Raaphorst FM, Vermeer M, Fieret E, et al. Site-specific expression of Polycomb-group genes encoding the HPC-HPH/PRC1 complex in clinically defined primary nodal and cutaneous large B-cell lymphomas. Am J Pathol 2004;164:533–42.[Abstract/Free Full Text]
  33. Viser HP, Gunster MJ, Kluin-Nelemans HC, et al. The Polycomb group protein EZH2 is upregulated in proliferating, cultured human mantle cell lymphoma. Br J Haematol 2001;112:950–8.[CrossRef][Medline]
  34. Bea S, Tort F, Pinyol M, et al. BMI-1 gene amplification and overexpression in hematological malignancies occur mainly in mantle cell lymphomas. Cancer Res 2001;61:2409–12.[Abstract/Free Full Text]
  35. Dukers D, van Galen JC, Giroth C, et al. Unique Polycomb gene expression pattern in Hodgkin's lymphoma and Hodgkin's lymphoma-derived cell lines. Am J Pathol 2004;164:873–81.[Abstract/Free Full Text]
  36. Sanchez-Beato M, Sanchez E, Garcia JF, et al. Abnormal PcG protein expression in Hodgkin's lymphoma. Relation with E2F6 and NfkappaB transcription factors. J Pathol 2004;204:528–37.[CrossRef][Medline]
  37. Vonlanthen S, Heighway J, Altermatt HJ, et al. The bmi-1 oncoprotein is differentially expressed in non-small cell lung cancer and correlates with INK4A-ARF locus expression. Br J Cancer 2001;84:1372–6.[CrossRef][Medline]
  38. Neo SY, Leow CK, Vega VB, et al. Identification of discriminators of hepatoma by gene expression profiling using a minimal dataset approach. Hepathology 2004;39:944–53.[CrossRef][Medline]
  39. Ferreux E, Lont AP, Horenblas S, et al. Evidence for at least three alternative mechanisms targeting the p16INK4A/cyclin D/Rb pathway in penile carcinoma, one of which is mediated by high-risk human papillomavirus. J Pathol 2003;201:109–18.[CrossRef][Medline]
  40. Raaphorst FM, Meijer CJLM, Fieret E, et al. Poorly differentiated breast carcinoma is associated with increased expression of the human polycomb group EZH2 gene. Neoplasia 2003;5:481–8.[Medline]
  41. Kim JH, Yoon SY, Jeong SH, et al. Overexpression of Bmi-1 oncoprotein correlates with axillary lymph node metastases in invasive ductal breast cancer. Breast 2004;13:383–8.[CrossRef][Medline]
  42. Kim JH, Yoon SY, Kim CN, et al. The Bmi-1 oncoprotein is overexpressed in human colorectal cancer and correlates with the reduced p16INK4a/p14ARF proteins. Cancer Lett 2004;203:217–24.[CrossRef][Medline]
  43. Varambally S, Dhanasekaram SM, Zhou M, et al. The Polycomb group protein EZH2 is involved in progression of prostate cancer. Nature 2002;419:624–9.[CrossRef][Medline]
  44. Sjögren S, Inganäs M, Torbjörn N. The p53 gene in breast cancer: prognostic value of complementary DNA sequencing versus immunohistochemistry. J Natl Cancer Inst 1996;88:173–82.[Medline]
  45. Oto M, Miyake S, Yuasa Y. Optimization of nonradioisotopic single strand conformation polymorphism analysis with a conventional minislab gel electrophoresis apparatus. Anal Biochem 1993;213:19–22.[CrossRef][Medline]
  46. Sewalt RG, Gunster MJ, van der Vlag J, Satijn DPE, Otte AP. C-Terminal binding protein is a transcriptional repressor that interacts with a specific class of vertebrate Polycomb proteins. Mol Cell Biol 1999;19:777–87.[Abstract/Free Full Text]
  47. Trimarchi JM, Fairchild B, Wen J, Lees JA. The E2F6 transcription factor is a component of the mammalian Bmi-1-containing polycomb complex. Proc Natl Acad Sci U S A 2001;98:1519–24.[Abstract/Free Full Text]
  48. Qin H, Wang J, Liang Y, Taniguchi K, Han H. RING1 inhibits transactivation of RBP-J by Notch through interaction with LIM protein KyoT2. Nucleic Acids Res 2004;32:1492–501.[Abstract/Free Full Text]
  49. Garcia E, Marcos-Gutierrez C, del Mar LM, Moreno JC, Vidal M. RYBP, a new repressor protein that interacts with components of the mammalian Polycomb complex and with transcription factor YY1. EMBO J 1999;18:3404–18.[CrossRef][Medline]
  50. Garcia-Cuellar MP, Zilles O, Schreiner SA, Birke M, Winkler TH, Slany RK. The ENL moiety of the childhood leukemia-associated MLL-ENL oncoprotein recruits human Polycomb 3. Oncogene 2001;20:411–9.[CrossRef][Medline]
  51. Soulez M, Saurin AJ, Freemont PS, Knight JC. SSX and the synovial-sarcoma-specific chimaeric protein SYT-SSX co-localize with the human polycomb group complex. Oncogene 1999;18:2739–46.[CrossRef][Medline]
  52. Voncken JW, Niessen H, Neufeld B, et al. MAPKAP kinase 3pK phosphorylates and regulates chromatin-association of the polycomb group protein Bmi1. J Biol Chem 2004;280:5178–87.[Medline]
  53. Kranc KR, Bamforth SD, Braganca J, Norbury C, van Lohuizen M, Bhattacharya S. Transcriptional coactivator Cited2 induces Bmi1 and Mel18 and controls fibroblast proliferation via Ink4a/ARF. Mol Cell Biol 2003;23:7658–66.[Abstract/Free Full Text]
  54. Silva J, Silva JM, Dominguez G, et al. Concomitant expression of p16INK4a and p14ARF in primary breast cancer and analysis of inactivation mechanisms. J Pathol 2003;199:289–97.[CrossRef][Medline]
  55. Bens K, Hijmans EM, Mullenders J, et al. A large-scale RNAi screen in human cells identifies new components of the p53 pathway. Nature 2004;428:431–7.[CrossRef][Medline]



This article has been cited by other articles:


Home page
 Mol. Cell. Biol.Home page
D. Wiederschain, L. Chen, B. Johnson, K. Bettano, D. Jackson, J. Taraszka, Y. K. Wang, M. D. Jones, M. Morrissey, J. Deeds, et al.
Contribution of Polycomb Homologues Bmi-1 and Mel-18 to Medulloblastoma Pathogenesis
Mol. Cell. Biol., July 1, 2007; 27(13): 4968 - 4979.
[Abstract] [Full Text] [PDF]

Home page
 Cancer Res.Home page
W.-J. Guo, M.-S. Zeng, A. Yadav, L.-B. Song, B.-H. Guo, V. Band, and G. P. Dimri
Mel-18 Acts as a Tumor Suppressor by Repressing Bmi-1 Expression and Down-regulating Akt Activity in Breast Cancer Cells
Cancer Res., June 1, 2007; 67(11): 5083 - 5089.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Silva, J.
Right arrow Articles by Bonilla, F.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Silva, J.
Right arrow Articles by Bonilla, F.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Cancer Research Clinical Cancer Research
Cancer Epidemiology Biomarkers & Prevention Molecular Cancer Therapeutics
Molecular Cancer Research Cancer Prevention Research
Cancer Prevention Journals Portal Cancer Reviews Online
Annual Meeting Education Book Meeting Abstracts Online