The estrogen receptor (ER) status of breast tumors is used to identify patients who may respond to endocrine agents such as tamoxifen. However, ER status alone is not perfectly predictive, and there is a pressing need for more reliable markers of endocrine responsiveness.

Here, we identified the well-known CGA gene (coding for the α subunit of glycoprotein hormones) as a new ERα-responsive gene in human breast cancer cells. We used a real-time quantitative reverse transcription-PCR assay to quantify CGA mRNA copy numbers in a large series of breast tumors. CGAoverexpression (>10 SD above the mean for normal breast tissues) was observed in 44 of 131 (33.6%) breast tumor RNAs, ranging from 20 to 16,500 times the level in normal breast tissues; the highest levels of CGA gene expression were close to those observed in placenta.

Significant links were observed between CGA gene overexpression and Scarff-Bloom-Richardson histopathological grade I+II(P = 0.015), and progesterone(P = 0.0009) and estrogen(P < 10-7) receptor positivity, which suggested that CGA is a marker of low tumor aggressiveness. We observed CGA mRNA overexpression in 44 of 90 (48.9%) ERα-positive tumors and in none of the 41 ERα-negative tumors. Immunohistochemical studies demonstrated that human chorionic gonadotropin α protein was strictly limited to ERα-positive tumor cells. Overexpression of the CGA gene was not accompanied by overexpression of the CGB gene.

Our results also suggest that CGA could be a more reliable marker than PS2 and PR for ERαfunctionality and, thus, for endocrine responsiveness. Moreover, the CGA marker has the added value of dichotomizing ERα-positive patients into two subgroups of similar size. Specific antibodies directed to secreted human chorionic gonadotropin αprotein are commercially available, thus facilitating the future application of this marker to the clinical management of breast cancer.

Breast cancer growth is regulated by estrogen, whose effect is mediated by binding to the ER.3The presence of ER in breast tumors has thus been used to identify those patients who may respond to endocrine agents such as tamoxifen. However, one-half of the patients with ER-positive tumors fail to respond favorably to antiestrogen treatment (1). Several mechanisms have been put forward to explain the lack of response in ER-positive patients; one postulates a mutated, nonfunctional ER that is unable to mediate the inhibitory cellular actions of endocrine treatments (2). It has been postulated that coassessment of ER- and estrogen-inducible genes or protein products (as markers of functional ER-mediated cellular growth mechanisms) might give better predictive results. Measurement of tumor PR and PS2 contents have been shown to partly improve patient selection(3). However, expression of PR and PS2 correlate strongly with ER expression, meaning that the PS2 and PR markers provide little further information on hormone dependence relative to ER. There is a pressing need for more reliable markers of endocrine responsiveness, but few ER-responsive genes have been identified.

We fortuitously identified the well-known CGA gene (coding for the α subunit of glycoprotein hormones) as a new ERα-responsive gene in human breast cancer cells. Indeed, the initial purpose of this study was to determine whether the emergence of “trophoblastic” CGB genes, which we have previously shown to be associated with malignant breast transformation (4), was accompanied by cooverexpression of the CGA gene and the production of ectopic hCG heterodimeric hormone in breast tumor cells. We thus quantified CGA and CGB gene expression in the large series of unilateral invasive primary breast tumor RNAs by means of real-time quantitative RT-PCR assays based on TaqMan methodology. We unexpectedly found marked differences in the total amount of CGA mRNA molecules that were clearly independent of CGB expression status but fully associated with the ERα-positive phenotype in our breast tumor series. Indeed, CGA gene overexpression was observed in one-half of the ERα-positive tumors and in none of the ERα-negative tumors. Immunohistochemical studies confirmed the hCGα protein overexpression and showed that it was strictly limited to ERα-positive tumor cells.

To further examine the unexpected link between CGA gene overexpression and ERα positivity, we analyzed the expression of the estrogen-responsive genes PR and PS2. Our results suggest that CGA could be a more reliable marker than PR and PS2 for ERα functionality and, thus, for endocrine responsiveness.

Patients and Samples

We analyzed tissue from primary breast tumors excised from 131 women treated at the Center René Huguenin from 1977 to 1989. The samples were examined histologically for the presence of tumor cells. A tumor sample was considered suitable for this study if the proportion of tumor cells was more than 60%. Immediately after surgery, the tumor samples were stored in liquid nitrogen until RNA extraction.

Immunohistochemical study was performed on fixed, paraffin-embedded tissue sections from 20 of the 131 breast tumor specimen.

The patients (mean age, 58.2 years; range, 34–91) met the following criteria: primary unilateral nonmetastatic breast carcinoma on which complete clinical, histological, and biological data were available;and no radiotherapy or chemotherapy before surgery. The main prognostic factors are presented in Table 1. The median follow-up was 8.1 years (range, 1.0–15.9). Forty-seven patients relapsed (the distribution of first relapse events was as follows: 13 local and/or regional recurrences, 30 metastases, and 4 both).

Specimens of adjacent normal breast tissue from nine of the breast cancer patients, and normal breast tissue from six women undergoing cosmetic breast surgery, were used as sources of normal RNA.

Evaluation of “Classical” Prognostic Factors

The histological type and steroid-hormone receptor status of each tumor, and the number of positive axillary nodes, were established at the time of surgery. The malignancy of infiltrating carcinomas was scored according to Bloom and Richardson’s histoprognostic system(5). ER and PR status was assayed by biochemical method(EIA) as described by the European Organization for Research and Treatment of Cancer (6), with a detection limit of 10 fmol/mg cytosolic protein.

Real-Time RT-PCR

Theoretical Basis.

Quantitative values are obtained from the threshold cycle number at which the increase in the signal associated with exponential growth of PCR products begins to be detected using PE Biosystems analysis software, according to the manufacturer’s manuals.

The precise amount of total RNA added to each reaction mix (based on absorbance) and its quality (i.e., lack of extensive degradation) are both difficult to assess. We, therefore, also quantified transcripts of the RPLP0 gene (also known as 36B4) encoding human acidic ribosomal phosphoprotein P0 as the endogenous RNA control, and each sample was normalized on the basis of its RPLP0 content.

The relative target gene expression level was also normalized to a calibrator, or 1× sample, consisting of a normal breast tissue sample(quantitation of CGA, CGB, and RPLP0genes) or of the breast tumor tissue sample that contained the smallest amount of target gene mRNA (quantitation of other target genes).

Final results, expressed as N-fold differences in target gene expression relative to the RPLP0 gene and the calibrator, termed Ntarget, were determined as follows:

\[\mathrm{N}\mathit{target{=}2}^{\mathit{({\Delta}Ct}_{\mathrm{sample}}{-}{\Delta}Ct_{\mathrm{calibrator}})}\]

where ΔCt values of the sample and calibrator are determined by subtracting the average Ctvalue of the target gene from the average Ct value of the RPLP0 gene.

Primers, Probes, and PCR Consumables.

Primers and probes for the RPLP0 and target genes were chosen with the assistance of the computer programs Oligo 4.0 (National Biosciences, Plymouth, MN) and Primer Express (Perkin-Elmer Applied Biosystems, Foster City, CA). We conducted BLASTN searches against dbEST, htgs, and nr (the nonredundant set of the GenBank, European Molecular Biology Laboratory, and DNA Data Bank of Japan database sequences) to confirm the total gene specificity of the nucleotide sequences chosen for the primers and probes, and the absence of DNA polymorphisms. The nucleotide sequences of the oligonucleotide hybridization probes and primers are shown in Table 2. To avoid amplification of contaminating genomic DNA, one of the two primers was placed in a different exon. For example, the upper primer and the probe of CGA were placed in exon 3, and the lower primer was placed at the junction between exons 3 and 4.

RNA Extraction.

Total RNA was extracted from breast specimens by using the acid-phenol guanidium method. The quality of the RNA samples was determined by electrophoresis through agarose gels and staining with ethidium bromide, and the 18S and 28S RNA bands were visualized under UV light.

cDNA Synthesis.

RNA was reverse transcribed in a final volume of 20 μl containing 1×RT buffer [500 mm each dNTP, 3 mm MgCl2, 75 mm KCl, and 50 mm Tris-HCl (pH 8.3)], 10 units of RNasinTM RNase inhibitor (Promega, Madison, WI), 10 mmDTT, 50 units of Superscript II RNase H-reverse transcriptase (Life Technologies, Inc., Gaithersburg, MD), 1.5 mm random hexamers (Pharmacia, Uppsala, Sweden), and 1 μg of total RNA. The samples were incubated at 20°C for 10 min and 42°C for 30 min, and reverse transcriptase was inactivated by heating at 99°C for 5 min and cooling at 5°C for 5 min.

PCR Amplification.

All of the PCR reactions were performed using an ABI Prism 7700 Sequence Detection system (Perkin-Elmer Applied Biosystems). PCR was performed using either the TaqMan PCR Core Reagents kit or the SYBR Green PCR Core Reagents kit (Perkin-Elmer Applied Biosystems). The thermal cycling conditions comprised an initial denaturation step at 95°C for 10 min and 50 cycles at 95°C for 15 s and 65°C for 1 min. Experiments were performed with duplicates for each data point.

Indirect immunoperoxidase staining of fixed tissues was performed using monoclonal antibody HT13 directed against the αsubunit of glycoprotein hormones [a kind gift from Dr Jean-Michel Bidart (Service de Biologie Oncologique, Institut Gustave Roussy, 94805 Villejuif Cedex, France); Ref. 7] and monoclonal antibody ID5 raised against human ER (Dako SA, Trappes, France).

The immunohistochemical procedure was performed on paraffin-embedded tissue sections. A microwave antigen-retrieval technique was used in all of the cases. Sections were mounted on precoated slides(triethylenethiophosphoramide-coated slides) and allowed to dry at 50°C overnight. The sections were then dewaxed in xylene and hydrated through graded concentrations of alcohol. Endogenous activity was blocked with 1% hydrogen peroxide for 15 min. Sections were then immersed in a thermoresistant plastic box containing 10 ml of citrate buffer (pH 6.0) and processed in the microwave oven four times for 5 min each at 750 W. Sections were then allowed to cool at room temperature for 30 min before rinsing in TRIS-buffered saline. The blocking reagent was topped off, and the primary antibodies were left for 1 h. A standard avidin-biotin-peroxidase complex was used to reveal the antibody-antigen reaction.

Localization and intensity of staining were assessed by two pathologists, blinded to the real-time RT-PCR results.

Relapse-free survival was determined as the interval between diagnosis and detection of the first relapse (local and/or regional recurrences, and/or metastases).

Clinical, histological, and biological parameters were compared using the χ2 test. Differences between the two populations were judged significant at confidence levels greater than 95% (P < 0.05). Survival distributions were estimated by the Kaplan-Meier method (8), and the significance of differences between survival rates was determined using the log-rank test.

CGA mRNA Level in Normal Breast Tissues.

To determine the cutoff point for altered CGA gene expression at the RNA level in breast cancer tissue, the NCGA value, calculated as described in “Materials and Methods,” was determined for 15 normal breast tissue RNAs. As this value consistently fell between 0.4 and 6.6 (mean, 1.83 ± 1.78 SD), values of 20 (mean + 10 SD)or more were considered to represent CGA gene overexpression in tumor RNA samples.

CGA mRNA Level in Tumor Breast Tissues.

Among the 131 breast tumor RNA samples tested, 44 (33.6%) showed CGA gene overexpression. Very large differences in the amount of CGA mRNA were observed (NCGA, from 20.6 to 16500): 10 tumors had an expression level of 20–40 times; 11 tumors 41–100 times; 13 tumors 101–1000 times; and 10 tumors >1000 times that of normal breast tissue RNA. The highest levels of CGAgene expression in breast tumors were close to those observed in placenta (data not shown). CGA gene expression was also investigated in nine patients from whom both primary breast tumors and matched normal breast tissue were available: four tumors showed clearly higher CGA expression in the tumor (NCGA: 2260.1,70.4, 66.9, and 36.9, respectively) than in the normal tissue(NCGA: 0.9, 3.4, 2.2, and 1.3, respectively).

Correlation between CGA mRNA Levels and Clinical and Pathological Parameters.

We then sought links between quantitative CGA mRNA status and standard clinical, pathological, and biological factors in breast cancer (Table 3).

Statistically significant links were found between CGA gene overexpression and SBR histopathological grade I+II(P = 0.015), and positive progesterone(P = 0.0009) and estrogen(P < 10−7) receptor status, as determined by biochemical method (EIA). Importantly, we observed an absolute link between CGA gene overexpression and ER status, 44 of 90 (48.9%) ER-positive tumors and none of the 41 ER-negative tumors showed CGA gene overexpression.

Patients with tumors overexpressing CGA did not relapse more(or less) frequently (Table 3) and did not have significantly shorter(or longer) disease-free survival after surgery compared with patients whose tumors normally expressed CGA (log-rank test, not shown).

Localization of hCGα Subunit in Tumor Cell Cytoplasm.

Of the 20 tumors studied by immunohistochemistry, we detected specific immunoreactivity in the 10 tumors that overexpressed CGA mRNA and in none of the tumors that showed no CGA overexpression. We thus observed a perfect match between CGA mRNA overexpression and immunohistochemical positivity (Fig. 1). hCGα immunoreactivity was exclusively found inside ER-positive tumor cells; infiltrating lymphocytes and normal glandular cells in the tumor were negative. Tumor cell staining was found exclusively in the cytoplasm, and the staining pattern consisted mainly of isolated positive cells (Fig. 1). The positive cells were chromogranin A-negative (data not shown).

Relationship between CGA mRNA Levels and CGB mRNA Levels.

Major differences in the amount of CGB mRNA molecules were observed (range, 0.3–192). However, the highest levels of CGB gene expression in breast tumors were>103-fold lower than those observed in placenta(data not shown). To study the relationship between CGA mRNA levels and CGB mRNA levels, we subdivided tumors into those with very low (NCGB, 0.3–2.9), low (3–5.9), intermediate(6–9.9) and high 10–192(10–192) CGB mRNA levels. No correlation was observed between CGA mRNA and CGB mRNA levels(Table 3). Neither were links observed between CGB gene overexpression and PR and ER status (data not shown).

Relationship between CGA mRNA Levels and CCND1, MYC, and ERBB2Expression Status.

The 131 tumors studied for CGA expression had previously been tested for mRNA expression of the CCND1, MYC, and ERBB2 genes (9, 10).4We found a significant link between CGA overexpression and CCND1 overexpression (P = 0.00003)but no link between CGA overexpression and altered mRNA expression of the other two genes (Table 3).

Relationship between CGA mRNA Levels and PS2 and ERβ Expression Status.

To study the link between CGA gene overexpression and ER positivity, we also quantified, by means of a real-time quantitative RT-PCR assay, the expression of the ERα-responsive gene PS2, as well as the ER β (ERβ) gene. We also analyzed mRNA levels of the PR and ERα genes to confirm PR and ER protein status determined by a biochemical (EIA)method, to obtain quantitative PR and ERαvalues and to avoid a possible discrepancy due to tumor heterogeneity.

As regards the ERα, PS2, ERβ, and PR markers, patients were subdivided into three equal groups of tumors with low (n = 43), intermediate(n = 44), and high (n = 44) mRNA levels. A total correlation was observed between ERα gene status determined with biochemical and real-time RT-PCR. Indeed, all of the 41 ER-negative tumors in the biochemical(EIA) method had low ERα mRNA levels. Then, breast tumors were subdivided into ERα-negative tumors (low ERα mRNA; n = 43) and ERα-positive tumors (intermediate/high ERαmRNA; n = 88).

The results (summarized in Tables 4 and 5) showed a stronger association between ERα gene status and CGA gene status (total link) than between ERαgene status and PS2, PR or ERβ gene status (subtotal links). Indeed, several ERα-negative (low ERα mRNA expressed) tumors overexpressed PS2and/or PR, whereas none of the“ ERα-negative” tumors overexpressed the CGAgene. Interestingly, we observed a negative correlation between ERα and ERβ mRNA expression levels(P = 0.0013).

Finally, in the ERα-positive subgroup(n = 88), we found a significant link between CGA overexpression and CCND1 overexpression(P = 0.0024), but no link between CGA mRNA expression status and PS2, PR, or ERβ mRNA expression levels (Table 6).

In this report, we have developed a real-time quantitative RT-PCR assay to quantify CGA mRNA copy numbers in homogeneous total RNA solutions prepared from tumor samples. This recently developed approach to nucleic acid quantification in homogeneous solutions may become a reference, given its performance, accuracy, sensitivity, and high throughput capacity, and also the fact that it eliminates the need for tedious post-PCR processing (11). Above all, this method is suited to the development of new target gene assays with a high level of interlaboratory standardization and yields statistical confidence values. A major advantage of this method is that the system has a large linear dynamic range (at least six orders of magnitude)suitable for analyzing the expression of genes, such as CGA,that show large differences in the amount of mRNA molecules(CGA gene expression ranged from 0.3 to 16,500 times the level in normal breast tissues). Overexpression (>10 SD above the mean for normal breast tissues) of the CGA gene was observed in 44 (33.6%) of the 131 breast tumor RNA samples. Immunohistochemical studies confirmed hCGα protein overexpression and showed that it was strictly limited to breast tumor cells. Our results are in keeping with a report of hCGα protein production by breast tumor cells, as shown by immunohistochemistry analysis (12).

We sought to determine whether the observed overexpression of hCGαprotein in breast cancer has to aim to associate with the hCGβsubunit to produce the heterodimeric hormone hCG, which could mediate biological activities through the luteinizing hormone/hCG receptor, which was recently shown to be expressed in breast cancer(13, 14). Although we observed large differences in the amount of CGB mRNA molecules (as high as 192 times the level in normal breast tissues), we found no link between CGA mRNA overexpression and CGB mRNA overexpression in our series of breast tumors (Table 3). We also observed no link between CGA overexpression and mRNA expression of the LHB, FSHB, and TSHB genes, which code for the other three β subunits capable of associating with the hCGαsubunit to produce glycoprotein hormones (data not shown). The highest levels of CGA gene expression in our breast tumor series,which were close to those observed in placenta and were much higher than the amount of CGB mRNA in breast tumors(>103-fold lower that placental levels) suggest that different genetic (or epigenetic) mechanisms are responsible for CGA and CGB gene overexpression in breast tumors. Taken together, these results suggest that if the free hCGα subunit(and not the heterodimeric hormone hCG) is involved in breast tumorigenesis, it would act via a novel pathway not involving the luteinizing hormone/hCG receptor.

Little is known of the involvement of the hCGα subunit itself in carcinogenic processes. Rivera et al.(15)showed that an antisense sequence to the CGA gene inhibited the growth and reversed the transformed phenotype of human lung tumor cells. One possibility, in breast tissue, is that the hCGα subunit controls PRL (prolactin) gene expression, as in myometrial,decidual, and pituitary gland cells (16, 17, 18). Because PRL (prolactin) gene expression is altered in breast cancer(19), we tested this hypothesis. We found no link between CGA mRNA overexpression and PRL mRNA overexpression, ruling out a role of the CGA gene in PRL pathway dysregulation in breast tumors (data not shown).

The most important result of our study is that CGA gene overexpression is perfectly linked to ER positivity in breast tumors. Indeed, CGA gene overexpression was observed in one-half of the ERα-positive tumors and in none of the ERα-negative tumors. We also found a weaker association between CGA gene overexpression and PR positivity and SBR histopathological grade I+II,which suggests that CGA is a marker of tumors with low aggressiveness. No relationship between ER positivity and CGB overexpression was observed in the same series. Our immunohistochemical data confirm that hCGα protein overexpression is strictly limited to ER-positive tumor cells. This makes CGAstatus an attractive candidate as a molecular marker, and one that may prove far more reliable than ER status alone, to predict endocrine responsiveness. Indeed, only one-half of all of the ER-positive patients respond favorably to antiestrogen treatment (1),and we observed CGA gene overexpression in one-half of the ERα-positive tumors in our breast tumor series. Moreover,we observed no link between CGA mRNA expression status and PS2 or PR mRNA expression levels in the ERα-positive subgroup, which suggests that CGA activation requires ERα but involves a mechanism different from that of PS2 and PR. Moreover, our results (summarized in Tables 4 and 5) suggest that the CGA gene may be a more reliable marker than PS2 and PR for ERαfunctionality and, thus, for endocrine responsiveness. Indeed, several“ ERα-negative” (low ERα mRNA expressed)tumors overexpressed PS2 and/or PR, whereas none of the ERα-negative tumors overexpressed the CGA gene. Taken together, these findings suggest that the CGA marker provides new, independent information that, in conjunction with ERα status, may help to determine the likelihood that a given tumor will respond to endocrine therapy. We infer that the subpopulation of CGA-positive, ERα-positive tumors would correspond to those responsive to hormone therapy. Because endocrine therapy was rarely used 20 years ago, which is when our samples were obtained, we were unable to study the relationship between CGA gene overexpression and the response to endocrine therapy. However, among the 44 ERα-positive patients who received postoperative hormone therapy, 71.4% (15 of 21)of those who had CGA overexpression are relapse-free,compared with 43.5% (10 of 23) of those who had normal CGAexpression (P = 0.06).

In addition to their clinical application, our results raise an important question concerning the mechanisms that lead to CGA overexpression in ERα-positive breast tumors. The structure of the CGA promoter has been extensively studied(reviewed in Ref. 20). Most studies have focused on CGA gene expression in placenta and pituitary tissues and suggest that the tissue-specific expression of the CGA gene is determined by combinations of several elements, some of which are common to all of the tissues, whereas others are specific to a given tissue. These studies identified a remarkable series of composite regulatory elements that interact with families of transcription factors that are still being characterized. These elements include a trophoblast-specific element (TSE) that binds TSEB and two CREs that bind CREBs. However, no consensus ERE was found in the 1638 bp of the cloned promoter region of the human CGA gene (GenBank accession no. AF109152). It is noteworthy that we observed no link between overexpression of the CGA gene and the PS2 or PR genes, two ERα-inducible genes with ERE elements, which suggests that ERα activates CGA gene expression in breast tumors via a mechanism that does not involve an ERE element.

The most plausible hypothesis is that CGA gene activation by ERα protein occurs via the CRE element. Indeed, estrogen activates its receptor by inducing a conformational change in the hormone-binding domain (21), thereby creating a structural motif that binds to a number of transcriptional coactivators such as SRC-1(steroid receptor coactivator), p300/CBP (CREB-binding protein), and P/CAF (p300/CBP-associated factor). Interestingly, p300/CBP can bind to CREB, which is known to bind to the CRE element, whereas P/CAF is an enzyme known to promote transcription by acetylating histones, thereby modifying the chromatin structure and facilitating gene expression.

In this respect it is noteworthy that the CCND1 gene, the overexpression of which is also strongly linked to ER positivity in breast tumors, contains a CRE element but not an ERE element in its promoter. Sabbah et al.(22) recently showed that it is this CRE element that is involved in the activation of the CCND1 gene by ERα. Interestingly, we observed a strong link between CGA mRNA overexpression and CCND1mRNA overexpression in our breast tumor series (Table 3) and especially in the ERα-positive subgroup (Table 6).

Keri et al.(23), using 1500 bp of the proximal 5′ flanking sequence of the human CGA gene in in vitro(cultured cells) or in vivo (transgenic mice) models, did not observe up-regulation by estrogen (or ERα) of reporter gene expression. We observed no CGA overexpression in the ERα-positive breast cell lines tested (MCF7, T-47D, ZR-75–1) either before or after estradiol treatment. Taken together, these results suggest that the mechanism that leads in vivo to CGA overexpression in human ERα-positive breast tumors involves several factors, including ERαand several uncharacterized transcriptional coactivators that are not all present in the classical in vitro and in vivomodels used to date.

In conclusion, we have identified CGA as a major new ERα-responsive gene that should greatly contribute to our understanding of the role of the ER in breast cancer. Our results also make the CGA gene an attractive alternative molecular marker to PR and PS2 as a refined predictor of endocrine responsiveness in breast cancer patients. We are currently conducting a large study of specific breast cancer patient phenotypes to test the practical value of CGA as a predictor of the response to hormone therapy. The CGA gene encodes a well-characterized secreted protein for which specific antibodies are already commercially available, thus facilitating the future application of this marker to the clinical management of breast cancer.

Fig. 1.

Immunohistochemistry staining of hCGα (A, B, and D) and ERα (C) proteins in breast cancer tissues. A and B, intense expression of hCGα protein was found mainly in isolated breast tumor cells (A) or in cribriform areas (B).×20. B and C, serial sections show hCGα immunoreactivity (B) exclusively found inside ERα-positive tumor cells (C). Note a negative staining of hCGα protein in some ERα-positive tumor cells. ×20. D, hCGα immunoreactivity was localized in the cytoplasm of the cancer cells; ×100.

Fig. 1.

Immunohistochemistry staining of hCGα (A, B, and D) and ERα (C) proteins in breast cancer tissues. A and B, intense expression of hCGα protein was found mainly in isolated breast tumor cells (A) or in cribriform areas (B).×20. B and C, serial sections show hCGα immunoreactivity (B) exclusively found inside ERα-positive tumor cells (C). Note a negative staining of hCGα protein in some ERα-positive tumor cells. ×20. D, hCGα immunoreactivity was localized in the cytoplasm of the cancer cells; ×100.

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1

This work was supported by the Association pour la Recherche sur le Cancer and the Ministère de l’Enseignement Supérieur et de la Recherche.

3

The abbreviations used are: ER, estrogen receptor; PR, progesterone receptor; hCG, human chorionic gonadotropin;RT-PCR, reverse transcription-PCR; EIA, enzyme immunoassay;SBR, Scarff-Bloom-Richardson; ERE, estrogen-response element; CRE, cAMP response element; CREB, CRE binding protein; CBP, CREB binding protein.

4

I. Bièche, M. Olivi, C. Noguès, M. Vidaud, and R. Lidereau. Prognostic value of CCND1 gene status in sporadic breast tumors, as determined by real-time quantitative PCR assays, manuscript in preparation.

Table 1

Characteristics of the 131 patients and relation to disease-free survival

No. of patients (%)Disease-free survival
No. of eventsaP              b
Age   NSc 
≤50 39 (29.8) 12  
>50 92 (70.2) 35  
Menopausal status   NS 
Premenopausal 45 (34.3) 16  
Postmenopausal 86 (65.7) 31  
Histological graded   NS 
I+II 76 (62.3) 30  
III 46 (37.7) 16  
Lymph node status   0.026 
Node-negative 49 (37.4) 10  
Node-positive 82 (62.6) 37  
ER status   NS 
+ (≥10 fm/mg) 90 (68.7) 36  
− (<10 fm/mg) 41 (31.3) 11  
PR status   NS 
+ (≥10 fm/mg) 78 (59.5) 28  
− (<10 fm/mg) 53 (40.5) 19  
Macroscopic tumor sizee   NS 
≤30 mm 90 (72.6) 32  
>30 mm 34 (27.4) 13  
No. of patients (%)Disease-free survival
No. of eventsaP              b
Age   NSc 
≤50 39 (29.8) 12  
>50 92 (70.2) 35  
Menopausal status   NS 
Premenopausal 45 (34.3) 16  
Postmenopausal 86 (65.7) 31  
Histological graded   NS 
I+II 76 (62.3) 30  
III 46 (37.7) 16  
Lymph node status   0.026 
Node-negative 49 (37.4) 10  
Node-positive 82 (62.6) 37  
ER status   NS 
+ (≥10 fm/mg) 90 (68.7) 36  
− (<10 fm/mg) 41 (31.3) 11  
PR status   NS 
+ (≥10 fm/mg) 78 (59.5) 28  
− (<10 fm/mg) 53 (40.5) 19  
Macroscopic tumor sizee   NS 
≤30 mm 90 (72.6) 32  
>30 mm 34 (27.4) 13  
a

First relapses (local and/or regional recurrences, and/or metastases).

b

Log-rank test.

c

NS, not significant.

d

SBR classification; information available for 122 patients.

e

Information available for 124 patients.

Table 2

Oligonucleotide primer and probe sequences used

GenesOligonucleotideSequencePCR product size (pb)
RPLP0 Upper primer 5′-GGC GAC CTG GAA GTC CAA CT-3′ 149 
 Lower primer 5′-CCA TCA GCA CCA CAG CCT TC-3′  
 Probe 5′-ATC TGC TGC ATC TGC TTG GAG CCC A-3′  
CGA Upper primer 5′-TCC CAC TCC ACT AAG GTC CAA-3′ 106 
 Lower primer 5′-CCC CAT TAC TGT GAC CCT GTT-3′  
 Probe 5′-CAC AGC AAG TGG ACT CTG AGG TGA CG-3′  
CGB Upper primer 5′-GCT ACT GCC CCA CCA TGA CC-3′ 94 
 Lower primer 5′-ATG GAC TCG AAG CGC ACA TC-3′  
 Probe 5′-CCT GCC TCA GGT GGT GTG CAA CTA CC-3′  
ERαa Upper primer 5′-CCA CCA ACC AGT GCA CCA TT-3′ 108 
 Lower primer 5′-GGT CTT TTC GTA TCC CAC CTT TC-3′  
PRa Upper primer 5′-CGC GCT CTA CCC TGC ACT C-3′ 121 
 Lower primer 5′-TGA ATC CGG CCT CAG GTA GTT-3′  
PS2a Upper primer 5′-CAT CGA CGT CCC TCC AGA AGA G-3′ 105 
 Lower primer 5′-CTC TGG GAC TAA TCA CCG TGC TG-3′  
ERβa Upper primer 5′-AGA GTC CCT GGT GTG AAG CAA G-3′ 143 
 Lower primer 5′-GAC AGC GCA GAA GTG AGC ATC-3′  
GenesOligonucleotideSequencePCR product size (pb)
RPLP0 Upper primer 5′-GGC GAC CTG GAA GTC CAA CT-3′ 149 
 Lower primer 5′-CCA TCA GCA CCA CAG CCT TC-3′  
 Probe 5′-ATC TGC TGC ATC TGC TTG GAG CCC A-3′  
CGA Upper primer 5′-TCC CAC TCC ACT AAG GTC CAA-3′ 106 
 Lower primer 5′-CCC CAT TAC TGT GAC CCT GTT-3′  
 Probe 5′-CAC AGC AAG TGG ACT CTG AGG TGA CG-3′  
CGB Upper primer 5′-GCT ACT GCC CCA CCA TGA CC-3′ 94 
 Lower primer 5′-ATG GAC TCG AAG CGC ACA TC-3′  
 Probe 5′-CCT GCC TCA GGT GGT GTG CAA CTA CC-3′  
ERαa Upper primer 5′-CCA CCA ACC AGT GCA CCA TT-3′ 108 
 Lower primer 5′-GGT CTT TTC GTA TCC CAC CTT TC-3′  
PRa Upper primer 5′-CGC GCT CTA CCC TGC ACT C-3′ 121 
 Lower primer 5′-TGA ATC CGG CCT CAG GTA GTT-3′  
PS2a Upper primer 5′-CAT CGA CGT CCC TCC AGA AGA G-3′ 105 
 Lower primer 5′-CTC TGG GAC TAA TCA CCG TGC TG-3′  
ERβa Upper primer 5′-AGA GTC CCT GGT GTG AAG CAA G-3′ 143 
 Lower primer 5′-GAC AGC GCA GAA GTG AGC ATC-3′  
a

The genes ERα, PR,PS2, and ERβ were analyzed by using the fluorescent SYBR green methodology (without use of a TaqMan fluorogenic probe).

Table 3

Relationship between mRNA CGA status (normal/overexpression) and the standard clinical, pathological, and biological factors

Total population (%)Normal CGA mRNAOverexpressed CGA mRNA
No. of patients (%)No. of patients (%)P              a
Total 131 (100.0) 87 (66.4) 44 (33.6)  
Age    NSb 
≤50 39 (29.8) 29 (33.3) 10 (20.7)  
>50 92 (70.2) 58 (66.7) 34 (77.3)  
Menopausal status    NS 
Premenopausal 45 (34.3) 33 (37.9) 12 (27.3)  
Postmenopausal 86 (65.7) 54 (62.1) 32 (72.7)  
Histological gradec    0.015 
I+II 76 (62.3) 43 (54.4) 33 (76.7)  
III 46 (37.7) 36 (45.6) 10 (23.3)  
Lymph node status    NS 
Node-negative 49 (37.4) 33 (37.9) 16 (36.4)  
Node-positive 82 (62.6) 54 (62.1) 28 (63.6)  
ER status    <10−7 
+ (≥10 fm/mg) 90 (68.7) 46 (52.9) 44 (100.0)  
− (<10 fm/mg) 41 (31.3) 41 (47.1)  
PR status    0.0009 
+ (≥10 fm/mg) 78 (59.5) 43 (49.4) 35 (79.5)  
− (<10 fm/mg) 53 (40.5) 44 (50.6) 9 (20.5)  
Macroscopic tumor sized    NS 
≤30 mm 90 (72.6) 62 (73.8) 28 (70.0)  
>30 mm 34 (27.4) 22 (26.2) 12 (30.0)  
Relapses    NS 
47 (35.9) 32 (36.8) 15 (34.1)  
− 84 (64.1) 55 (63.2) 29 (65.9)  
RNA CGB status    NS 
NCGB (0.3–2.9) 33 (25.2) 25 (28.7) 8 (18.2)  
NCGB (3.0–5.9) 31 (23.7) 20 (23.0) 11 (25.0)  
NCGB (6.0–9.9) 35 (26.7) 23 (26.4) 12 (27.3)  
NCGB (10.0–192) 32 (24.4) 19 (21.9) 13 (29.5)  
RNA CCND1 statuse    0.00003 
Overexpressed 43 (32.8) 18 (20.7) 25 (56.8)  
Normal 88 (67.2) 69 (79.3) 19 (43.2)  
RNA MYC statusf    NS 
Overexpressed 28 (21.4) 17 (19.5) 11 (25.0)  
Normal 103 (78.6) 70 (80.5) 33 (75.0)  
RNA ERBB2 statusg    NS 
Overexpressed 22 (16.8) 16 (18.3) 6 (13.6)  
Normal 109 (83.2) 71 (81.7) 38 (86.4)  
Total population (%)Normal CGA mRNAOverexpressed CGA mRNA
No. of patients (%)No. of patients (%)P              a
Total 131 (100.0) 87 (66.4) 44 (33.6)  
Age    NSb 
≤50 39 (29.8) 29 (33.3) 10 (20.7)  
>50 92 (70.2) 58 (66.7) 34 (77.3)  
Menopausal status    NS 
Premenopausal 45 (34.3) 33 (37.9) 12 (27.3)  
Postmenopausal 86 (65.7) 54 (62.1) 32 (72.7)  
Histological gradec    0.015 
I+II 76 (62.3) 43 (54.4) 33 (76.7)  
III 46 (37.7) 36 (45.6) 10 (23.3)  
Lymph node status    NS 
Node-negative 49 (37.4) 33 (37.9) 16 (36.4)  
Node-positive 82 (62.6) 54 (62.1) 28 (63.6)  
ER status    <10−7 
+ (≥10 fm/mg) 90 (68.7) 46 (52.9) 44 (100.0)  
− (<10 fm/mg) 41 (31.3) 41 (47.1)  
PR status    0.0009 
+ (≥10 fm/mg) 78 (59.5) 43 (49.4) 35 (79.5)  
− (<10 fm/mg) 53 (40.5) 44 (50.6) 9 (20.5)  
Macroscopic tumor sized    NS 
≤30 mm 90 (72.6) 62 (73.8) 28 (70.0)  
>30 mm 34 (27.4) 22 (26.2) 12 (30.0)  
Relapses    NS 
47 (35.9) 32 (36.8) 15 (34.1)  
− 84 (64.1) 55 (63.2) 29 (65.9)  
RNA CGB status    NS 
NCGB (0.3–2.9) 33 (25.2) 25 (28.7) 8 (18.2)  
NCGB (3.0–5.9) 31 (23.7) 20 (23.0) 11 (25.0)  
NCGB (6.0–9.9) 35 (26.7) 23 (26.4) 12 (27.3)  
NCGB (10.0–192) 32 (24.4) 19 (21.9) 13 (29.5)  
RNA CCND1 statuse    0.00003 
Overexpressed 43 (32.8) 18 (20.7) 25 (56.8)  
Normal 88 (67.2) 69 (79.3) 19 (43.2)  
RNA MYC statusf    NS 
Overexpressed 28 (21.4) 17 (19.5) 11 (25.0)  
Normal 103 (78.6) 70 (80.5) 33 (75.0)  
RNA ERBB2 statusg    NS 
Overexpressed 22 (16.8) 16 (18.3) 6 (13.6)  
Normal 109 (83.2) 71 (81.7) 38 (86.4)  
a

χ2 test.

b

NS, not significant.

c

SBR classification; information available for 122 patients.

d

Information available for 124 patients.

e

I. Bièche, M. Olivi, C. Noguès, M. Vidaud, and R. Lidereau. Prognostic value of CCND1 gene status in sporadic breast tumors, as determined by real-time quantitative PCR assays, manuscript in preparation.

f

I. Bièche et al.,(9).

g

I. Bièche et al.(10).

Table 4

Relationship between mRNA ERα status and other molecular marker status

Total populationERα-negative tumors Low ERα mRNA expressed tumors (NERα: 1–40)aERα-moderately positive tumors Intermediate ERα mRNA expressed tumors (NERα: 41–300)ERα-highly positive tumors High ERα mRNA expressed tumors (NERα: 301–50,000)P              b
Total 131 (100.0)c 43 (32.8) 44 (33.6) 44 (33.6)  
CGA gene mRNA     <10−7 
Normal 87 (66.4) 43 (100.0) 22 (50.0) 22 (50.0)  
Overexpressed 44 (33.6) 22 (50.0) 22 (50.0)  
PS2 gene mRNA     <10−7 
Low (NPS2: 1–70) 43 (32.8) 32 (74.4) 5 (11.4) 6 (13.6)  
Intermediate (NPS2: 71–3,000) 44 (33.6) 9 (20.9) 19 (43.2) 16 (36.4)  
High (NPS2: 3,001–140,000) 44 (33.6) 2 (4.7) 20 (45.4) 22 (50.0)  
PR gene mRNA     <10−7 
Low (NPR: 1–17) 43 (32.8) 32 (74.4) 6 (13.6) 5 (11.4)  
Intermediate (NPR: 18–300) 44 (33.6) 10 (23.3) 23 (52.3) 11 (25.0)  
High (NPR: 301–12,000) 44 (33.6) 1 (2.3) 15 (34.1) 28 (63.6)  
ERβ gene mRNA     0.0013 
Low (NERβ: 1–16) 43 (32.8) 6 (14.0) 21 (47.7) 16 (36.4)  
Intermediate (NERβ: 17–53) 44 (33.6) 13 (30.2) 13 (29.6) 18 (40.9)  
High (NERβ: 54–550) 44 (33.6) 24 (55.8) 10 (22.7) 10 (22.7)  
Total populationERα-negative tumors Low ERα mRNA expressed tumors (NERα: 1–40)aERα-moderately positive tumors Intermediate ERα mRNA expressed tumors (NERα: 41–300)ERα-highly positive tumors High ERα mRNA expressed tumors (NERα: 301–50,000)P              b
Total 131 (100.0)c 43 (32.8) 44 (33.6) 44 (33.6)  
CGA gene mRNA     <10−7 
Normal 87 (66.4) 43 (100.0) 22 (50.0) 22 (50.0)  
Overexpressed 44 (33.6) 22 (50.0) 22 (50.0)  
PS2 gene mRNA     <10−7 
Low (NPS2: 1–70) 43 (32.8) 32 (74.4) 5 (11.4) 6 (13.6)  
Intermediate (NPS2: 71–3,000) 44 (33.6) 9 (20.9) 19 (43.2) 16 (36.4)  
High (NPS2: 3,001–140,000) 44 (33.6) 2 (4.7) 20 (45.4) 22 (50.0)  
PR gene mRNA     <10−7 
Low (NPR: 1–17) 43 (32.8) 32 (74.4) 6 (13.6) 5 (11.4)  
Intermediate (NPR: 18–300) 44 (33.6) 10 (23.3) 23 (52.3) 11 (25.0)  
High (NPR: 301–12,000) 44 (33.6) 1 (2.3) 15 (34.1) 28 (63.6)  
ERβ gene mRNA     0.0013 
Low (NERβ: 1–16) 43 (32.8) 6 (14.0) 21 (47.7) 16 (36.4)  
Intermediate (NERβ: 17–53) 44 (33.6) 13 (30.2) 13 (29.6) 18 (40.9)  
High (NERβ: 54–550) 44 (33.6) 24 (55.8) 10 (22.7) 10 (22.7)  
a

Relative gene target expression value, normalized both to an endogenous RNA control(RPLP0 gene) and to a calibrator (breast tumor tissue sample that contained the smallest amount of target gene mRNA).

b

χ2 test(ERα-negative versusERα-positive tumors; low versus intermediate/high gene mRNA expressed tumors).

c

Number of patients (%).

Table 5

Subdivision of the 131 tumors according to mRNA CGA, ERα, PR, and PS2 status

CGA statusERα statusPR statusPS2 statusNo. of patients (%)
 +a 35 (26.7) 
− 6 (4.6) 
− 2 (1.5) 
− − 1 (0.8) 
− 
− − 
− − 
− − − 
− 33 (25.2) 
− − 3 (2.3) 
− − 7 (5.3) 
− − − 1 (0.8) 
− − 8 (6.1) 
− − − 3 (2.3) 
− − − 3 (2.3) 
− − − − 29 (22.1) 
CGA statusERα statusPR statusPS2 statusNo. of patients (%)
 +a 35 (26.7) 
− 6 (4.6) 
− 2 (1.5) 
− − 1 (0.8) 
− 
− − 
− − 
− − − 
− 33 (25.2) 
− − 3 (2.3) 
− − 7 (5.3) 
− − − 1 (0.8) 
− − 8 (6.1) 
− − − 3 (2.3) 
− − − 3 (2.3) 
− − − − 29 (22.1) 
a

+, intermediate or high gene mRNA expression level; −, low gene mRNA expression level.

Table 6

Relationship between mRNA CGA status and other molecular marker status in the 88 ERα-positive tumors

Total populationCGA normal expressed-ERα-positive tumorsCGA overexpressed-ERα-positive tumorsP              a
Total 88 (100.0) 44 (50.0) 44 (50.0)  
PS2 gene mRNA    NSb 
Low 11 (12.5)c 4 (9.1) 7 (15.9)  
Intermediate 35 (39.8) 19 (43.2) 16 (36.4)  
High 42 (47.7) 21 (44.7) 21 (47.7)  
PR gene mRNA    NS 
Low 11 (12.5) 8 (18.2) 3 (6.8)  
Intermediate 34 (38.6) 12 (27.3) 22 (50.0)  
High 43 (48.9) 24 (54.5) 19 (43.2)  
ERβ gene mRNA    NS 
Low 37 (42.1) 15 (34.1) 22 (50.0)  
Intermediate 31 (35.2) 17 (38.6) 14 (31.8)  
High 20 (22.7) 12 (27.3) 8 (18.2)  
CCND1 gene mRNA    0.0024 
Normal 52 (59.1) 33 (75.0) 19 (43.2)  
Overexpressed 36 (40.9) 11 (25.0) 25 (56.8)  
Total populationCGA normal expressed-ERα-positive tumorsCGA overexpressed-ERα-positive tumorsP              a
Total 88 (100.0) 44 (50.0) 44 (50.0)  
PS2 gene mRNA    NSb 
Low 11 (12.5)c 4 (9.1) 7 (15.9)  
Intermediate 35 (39.8) 19 (43.2) 16 (36.4)  
High 42 (47.7) 21 (44.7) 21 (47.7)  
PR gene mRNA    NS 
Low 11 (12.5) 8 (18.2) 3 (6.8)  
Intermediate 34 (38.6) 12 (27.3) 22 (50.0)  
High 43 (48.9) 24 (54.5) 19 (43.2)  
ERβ gene mRNA    NS 
Low 37 (42.1) 15 (34.1) 22 (50.0)  
Intermediate 31 (35.2) 17 (38.6) 14 (31.8)  
High 20 (22.7) 12 (27.3) 8 (18.2)  
CCND1 gene mRNA    0.0024 
Normal 52 (59.1) 33 (75.0) 19 (43.2)  
Overexpressed 36 (40.9) 11 (25.0) 25 (56.8)  
a

χ2 test.

b

NS, not significant.

c

Number of patients (%).

We thank the staff of the Center René Huguenin for assistance in specimen collection and patient care. We also thank Dr. Martine Trassard (Laboratoire d’Anatomo-Cytopathologie, Centre Reńe Huguenin, 92211 St-Cloud, France) for helpful contributions. We are also indebted to Drs. Marie-France Pichon (Service de Médecine Nucléaire, Centre Reńe Huguenin, 92211 St-Cloud, France) and Jean-Michel Bidart (Service de Biologie Oncologique, Institut Gustave Roussy, 94805 Villejuif Cedex, France)for kindly providing a number of tissue specimens and the monoclonal antibody HT13, respectively. We thank Odile Champy for excellent technical assistance.

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