Combined profile of the tandem repeats CAG, TA and CA of the androgen and estrogen receptor genes in breast cancer

Purpose Case–control studies have reported inconsistent results concerning the association between polymorphisms in the androgen and estrogen receptor (ER) genes and breast cancer. While several studies investigated the association between the androgen receptor (AR) gene, CAG repeat and breast cancer, for the CA and TA repeats in the ER genes there are considerably fewer studies (one for CA and none for TA).

We have investigated the potential link between three tandem repeats (CAG, TA, and CA) in the AR, ERs α and β genes, respectively, and breast cancer. DNA was isolated from 153 invasive breast tumors and 318 controls, and the three tandem repeats were sized by polyacrylamide electrophoresis. Number of repeats in each allele and the total repeats of both alleles were taken as variables for classification into dichotomous groups using the median of each variable in the control group as cut-off point. Relationship between polymorphic tandem repeats and breast cancer was assessed by multivariate logistic regression models.

Three variables combined, longer CAGsum (≥28), shorter TA (<23) and CA (<23) repeats could constitute a possible genetic profile associated with breast cancer.

Our results confirm previous reports regarding an association between longer CAG repeats and breast cancer. In addition to that, we found that the combination of long CAG, short TA and CA repeats are strongly associated with breast cancer.

Androgen receptor gene, Breast cancer, Estrogen receptor genes, Polymorphic tandem repeats

In spite of the extensive research efforts of the last two decades to elucidate the etiology of breast cancer, only about 30% of cases due to heredity and only a small percent can be explained by the high-penetrance breast cancer genes (Lichtenstein et al. 2000). In this respect, other low-penetrance polymorphisms of breast cancer related genes, such as sexual hormones receptor genes, may be important predisposing factors (Antoniou et al. 2001). Many studies analyzing sexual receptor genes polymorphisms focused on short tandem repeats (microsatellites); such polymorphisms are being described till date only for the estrogen and androgen receptor (AR) genes (del Senno et al. 1992; Tsukamoto et al. 1998; Jenster et al. 1995). Estrogen receptors (ERs) are members of the nuclear receptor superfamily and mediate the pleiotropic effects of estrogen in certain developmental and physiological processes (Mangelsdorf et al. 1995). For example, the cellular growth regulating effects of estradiol are mediated through ERα and ERβ which act also as transcription factors for many genes involved in cell proliferation control (White and Parker 1998). Although estrogens are important physiological regulators, they have also been associated pathologically with an increased risk for breast cancer in women (Sommer and Fuqua 2001; Beato et al. 1995; Jensen and Jacobson 1962). The ERα gene is located on chromosome 6q25–27 and its promoter region contains a polymorphic dinucleotide TA tandem repeat (del Senno et al. 1992), while the ERβ gene is located on chromosome 14q23–24 and contains a polymorphic dinucleotide CA tandem repeat in its 3′-untranslated region (Tsukamoto et al. 1998). The functional role of these polymorphisms has not yet been clarified although it is believed that such tandem repeats may influence the expression of genes (Comings 1998). The AR is expressed in the majority of breast cancers and binds specifically to androgen mediating its action by activating the transcription of androgen-regulated genes (Bryan et al. 1984; Lea et al. 1989; Kuenen-Boumeester et al. 1992; Soreide et al. 1992; Hall et al. 1996; Bayer-Garner and Smoller 2000; Brys et al. 2002). The mechanism of testosterone action in the female breast is still unclear as well as whether the effects are predominantly proliferative or anti-proliferative on breast cells at physiologic levels. In contrast to the epidemiologic observation of a consistent association between serum testosterone levels and increasing breast cancer risk (Wysowski et al. 1987; Garland et al. 1992; Dorgan et al. 1996; Berrino et al. 1996; Thomas et al. 1997; Zeleniuch-Jacquotte et al. 1997; Hankinson et al. 1998; Cauley et al. 1999), in vivo studies reported an anti-proliferative effect (Zava and McGuire 1977), and in vitro studies reported both proliferative (Poulin et al. 1988; Ortmann et al. 2002) and anti-proliferative effects (Hackenberg et al. 1988; Marugo et al. 1992). The AR gene is located on chromosome Xq11–12 and contains a trinucleotide CAG polymorphic repeat in its first exon translated into a polyglutamine stretch in the amino-terminal domain of the AR protein (Jenster et al. 1995). This polyglutamine region seems to influence the function of the AR as a transcription factor, long fragments being associated with a low function of the receptor by inhibiting the interaction with certain coactivators (Chamberlain et al. 1994; Irvine et al. 2000). The immunohistochemical expression of AR in breast cancer has been correlated with ER and progesterone receptor (PR) expression, their presence in breast cancer cells being associated with well differentiated cancer tissue (Soreide et al. 1992; Kuenen-Boumeester et al. 1992). In order to further investigate the role of AR, ERα, and ERβ in breast cancer, we analyzed the CAG, TA, and CA polymorphic repeats, respectively, in 153 invasive breast cancer tumors and 318 blood specimens as controls.

One hundred and fifty-three patients with histological confirmed invasive ductal carcinoma who underwent surgery were taken into this study. Paraffin embedded cancer tissue was obtained from hospitals as well as clinical and follow-up information for these patients. All patients gave their consent for the use of their paraffin embedded tissue, and the study was approved by the Ethics Committee of the University of Medicine and Pharmacy “Victor Babes” from Timisoara, Romania. The median follow-up time was 40.5 months. The mean age at diagnosis in the patient group was 57 (range 23–88) years. Clinical stage distribution, according to WHO classification (Rosai 2004), was as follows: 15% of the patients had stage I disease, 63.4% had stage II, 20.3% had stage III, and 1.3% had stage IV. About one third (36.6%) of patients had positive immunohistochemical ER status, 27.5% had positive PR status, and 19% had both ER and PR positive status. Three hundred and eighteen blood samples from Romanian Caucasian female volunteer donors were analyzed as controls. Mean age in controls was 51, ranging between 35 and 66. Laboratory analysis Genomic DNA from blood samples was isolated using the QIAamp DNA Blood Mini Kit (QIAGEN, Valencia, CA, USA) following manufacturer’s instructions. A simple protocol for DNA extraction from paraffin blocks was used, available online at http://www.bioon.com/experiment/nua/. Briefly, 20 μm × 10 μm sections were deparaffinated by incubating with xylene at 55°C followed by 100% ethanol precipitation. After overnight incubation with 0.5 mg/ml proteinase K, DNA was extracted using the organic extraction method with phenol:cloroform:isoamyl alcohol followed by ethanol precipitation. DNA was recovered in 25 μl of TE buffer by overnight incubation at room temperature. Three different regions were amplified by PCR, one region containing the CAG repeat in the AR gene, one region containing the TA repeat in the ERα gene, and another region containing the CA repeat in the ERβ gene. Primers and PCR conditions were the same as those described by Westberg et al. (2001), the only difference being that we used HotStar Taq Polymerase (QIAGEN, Valencia, CA, USA) and nonlabeled primers. PCR products were separated by 6% high-resolution denaturing polyacrylamide gel electrophoresis in a PROTEAN II xi CELL (BIO-RAD, Hercules, CA, USA) electrophoresis system, followed by silver staining. In order to determine allele sizes, pGEM DNA Markers (Promega, Madison, WI, USA) were run together with PCR products. Allele determination was performed by scanning the gels with a GS-710 Calibrated Imaging Densitometer (BIO-RAD, Hercules, CA, USA) followed by sizing with the aid of the Quantity One-The Discovery Series v.4.0.1. (BIO-RAD, Hercules, CA, USA) software, taking the pGEM DNA Markers (Promega) as size standards. Electrophoresis and alleles determinations were performed at least twice to ensure consistency of results. HE-stained histological slides were prepared from all paraffin embedded blocks in order to confirm the cancer type described in patient’s records. Immunohistochemical quantification was performed for ER and PR in a DakoCytomation Autostainer Instrument (DakoCytomation, Glostrup, Denmark) using monoclonal mouse anti-human ERα antibody and monoclonal mouse anti-human PR clone PgR 636 for ER and PR (DakoCytomation, Glostrup, Denmark), respectively, according to the manufacturer’s instructions. Statistical analysis The CAG repeat data were analyzed in three categories: the number of CAG repeats in allele 1, the number of CAG repeats in allele 2, and the total of CAG repeats in both alleles. For heterozygous samples, allele 1 was the allele with the fewer number of CAG repeats. The three numerical CAG variables were classified into dichotomous groups using the median of each variable in the control group as cut-off point. A similar procedure was applied for TA and CA repeats variables. Associations between CAG, TA, and CA variables and breast cancer were assessed using univariate logistic regression. Odds ratios (OR) and their 95% confidence intervals (CI) were calculated. The independent variables that were statistically significant were entered into multivariate logistic regression models. Using backward elimination procedures, the most parsimonious multivariate logistic model was produced for predicting breast cancer. Crude ORs were then adjusted for age as a potential confounder. All P values were calculated based on two-sided statistical tests. Statistical analyses were performed using Epi Info v. 3.2.2 or SPSS v.10 software.

The AR gene CAG repeat, along with the ERα and ERβ genes TA and CA repeats, respectively, were amplified by PCR from 153 breast cancer tumor samples and sized by high-resolution denaturing polyacrylamide gel electrophoresis. Polymorphic tandem repeats lengths were compared with those obtained by genotyping the control group (Table 1). Table 1. | Mean | Median | SD | Range | | |---|---|---|---|---| | Cancer | |||| | CAG1 | 18.2 | 18 | 4.6 | 8–28 | | CAG2 | 20.2 | 22 | 4.3 | 11–29 | | CAGsum | 38.4 | 41 | 8.8 | 19–57 | | TA1 | 16.1 | 16 | 3.1 | 11–26 | | TA2 | 18.8 | 19 | 4.1 | 12–27 | | TAsum | 35.0 | 35 | 6.5 | 24–52 | | CA1 | 21.5 | 22 | 2.5 | 13–27 | | CA2 | 22.8 | 23 | 2.0 | 15–28 | | CAsum | 44.3 | 44 | 4.0 | 30–54 | | Controls | |||| | CAG1 | 15.3 | 12 | 6.3 | 9–28 | | CAG2 | 17.2 | 16 | 5.3 | 11–28 | | CAGsum | 32.5 | 28 | 11.5 | 21–56 | | TA1 | 16.9 | 16 | 3.1 | 13–24 | | TA2 | 21.5 | 23 | 4.5 | 15–30 | | TAsum | 38.5 | 38 | 6.8 | 29–51 | | CA1 | 21.2 | 21 | 2.8 | 15–28 | | CA2 | 23.3 | 23 | 1.5 | 19–28 | | CAsum | 44.6 | 45 | 3.7 | 37–56 | Each polymorphic repeat length was dichotomized into two allele categories taking the control group medians as cut-off points (12 for CAG1, 16 for CAG2, 28 for CAGsum, 16 for TA1, 23 for TA2, 38 for TAsum, 21 for CA1, 23 for CA2, 45 for CAsum). Comparison of the short/long allele frequency in the breast cancer group versus control by univariate logistic regression is presented in Table 2. The independent variables that were statistically significant (P < 0.25) were entered into multivariate logistic regression models for predicting breast cancer. Multivariate logistic regression data are presented in Table 3. Nagelkerke’s R 2 value, an estimate of variations in outcome variables explained by a logistic regression model, was calculated. Its value is 0.32, indicating that 32% of the variance in breast cancer was explained by the logistic regression model. Model chi-squared test value was 39.45 with 3 degrees of freedom (P<0.001). Interactions between covariates were not significant and were not included in the final model. The overall success of the model in predicting breast cancer (classification table) was 74.1% (for a cut value of 0.5). Table 2. | Variables | OR (95% CI) | P value | Variables | OR (95% CI) | P value | |---|---|---|---|---|---| | CAG1 | TAsum | |||| | <13 | 1.0 (ref.) | <0.001 | <38 | 2.13 (1.11–4.08) | 0.023 | | ≥13 | 6.08 (2.83–13.05) | ≥38 | 1.0 (ref.) | || | CAG2 | CA1 | |||| | <16 | 1.0 (ref.) | <0.001 | <22 | 1.0 (ref.) | 0.29 | | ≥16 | 4.53 (2.16–9.49) | ≥22 | 1.43 (0.79–2.57) | || | CAGsum | CA2 | |||| | <28 | 1.0 (ref.) | <0.001 | <23 | 3.03 (1.50–6.14) | <0.002 | | ≥28 | 7.23 (3.19–16.42) | ≥23 | 1.0 (ref.) | || | TA1 | CAsum | |||| | <16 | 1.28 (0.67–2.45) | 0.55 | <45 | 1.34 (0.74–2.40) | 0.41 | | ≥16 | 1.0 (ref.) | ≥45 | 1.0 (ref.) | || | TA2 | ||||| | <23 | 3.45 (1.76–6.76) | <0.001 | ||| | ≥23 | 1.0 (ref.) | Table 3. | Variable | Coefficient (SE) | Crude OR | 95% CI | P value | |---|---|---|---|---| | CAGsum | 2.226 (0.485) | 9.262 | 3.583–23.945 | <00.001 | | TA2 | 1.434 (0.401) | 4.195 | 1.912–9.206 | <0.001 | | CA2 | 1.157 (0.528) | 3.180 | 1.131–8.943 | 0.028 | In order to assess if age is a possible confounder, crude ORs were adjusted for age in the regression model (Table 4). The overall success of the model in predicting breast cancer dropped to 73.4%. Given the fact that the CA2 variable presents a marginal statistic value (P=0.62, adjusted OR 2.759), we analyzed the model without taking this variable into account. The overall success of the model in predicting breast cancer dropped to 67.1% in this case. Table 4. | Variable | Coefficient (SE) | Adjusted OR | 95% CI | P value | |---|---|---|---|---| | Age | 0.054 (0.021) | 1.056 | 1.012–1.101 | 0.012 | | CAGsum | 2.135 (0.508) | 8.455 | 3.121–22.903 | <0.001 | | TA2 | 1.425 (0.412) | 4.159 | 1.855–9.327 | 0.001 | | CA2 | 1.015 (0.544) | 2.759 | 0.950–8.010 | 0.062 |

We investigated the potential link between breast cancer and three tandem repeats (CAG, TA, and CA) in the AR, ERα, and ERβ genes, respectively, in a group of 153 patients. Several studies investigated these polymorphic repeats separately in different pathologies including breast cancer, but to our knowledge, no one investigated them together till date. Association studies between AR CAG repeat length and breast cancer displayed inconsistent results, some reporting a strong association between long CAG repeats and breast cancer (Rebbeck et al. 1999; Haiman et al. 2002; Elhaji et al. 2001; Giguere et al. 2001; Yu et al. 2000) while other studies showing no association (Spurdle et al. 1999; Kadouri et al. 2001; Menin et al. 2001; Given et al. 2000; Dagan et al. 2002), although in vitro studies demonstrated that long fragments of CAG repeats are associated with a low function of the AR (Chamberlain et al. 1994; Irvine et al. 2000). Investigating the potential role of CAG repeats in female breast cancer is difficult because of the presence of two alleles and the random chromosome X inactivation. Moreover, in breast tissue, estrogens appear to be the predominant hormonal regulator, although ERβ CA repeats seem to influence serum androgen levels in women (Westberg et al. 2001). CA polymorphic repeats in the ERβ gene were also associated with bone mineral density in women (Ogawa et al. 2000) while others found no association between this tandem repeat and risk of breast cancer (Forsti et al. 2003). The polymorphic TA repeat in the promoter region of ERα gene has been associated with coronary heart disease (Kunnas et al. 2000) and anxiety (Comings et al. 1999) in men, and with bone mineral density (Becherini et al. 2000; Langdahl et al. 2000), familiar premature ovarian dysfunction (Syrrou et al. 1999), and endometriosis (Georgiou et al. 1999) in women. To our knowledge, till date, no studies were conducted to investigate the potential role of ERα gene TA repeats in breast cancer. All three sexual hormone receptors (AR, ERα, ERβ) mediate the hormone response at breast tissue level, having possible pathological implications in breast cancer development. Although the functional role of the three tandem repeats investigated here (CAG for AR, TA for ERα, and CA for ERβ) is not clearly understood, they may influence the expression of these genes. In order to overcome the difficulties of having two alleles per polymorphic repeat, we analyzed each allele as a separate variant, as well as the CAG, TA, and CA repeats sum of alleles, in a regression model composed of the most relevant variables for each tandem repeat. In our logistic regression model, CAGsum (≥28), TA2 (<23) and CA2 (<23) repeats were independently associated with breast cancer. According to the Nagelkerke’s R 2 value, 32% of the variance in breast cancer was explained by the three covariates mentioned above. The overall success of this model in predicting breast cancer cases, based on the classification table, was 74.1% for a cut value of 0.5. After adjusting for age as a potential confounder, CA2 variable presented a marginal statistic significance (P=0.62) and was rejected from the model. Thus, age is a confounder for CA2 repeats by changing the OR of this covariate by 13%. We believe that a limitation of our study is the number of cases that may have influenced the exclusion of some of the covariates in multivariate logistic regression modeling. Further investigation using a larger sample of cases will probably enlarge the number of covariates associated with better prediction values. Our results lead to the possible conclusion that the combination of longer CAGsum repeats (≥28), shorter TA2 (<23) and shorter CA2 (<23) repeats may represent a characteristic genetic profile for breast cancer. This supports the idea of an associative action of sexual hormones in breast cancer. Acknowledgment This work was supported by VIASAN Program grant no. 159/2002 from the Romanian Academy of Medical Sciences. Footnotes This paper was initially submitted with an additional co-author who withdrew the co-authorship during the review process. All listed authors have now signed that they agree with the content of the current paper.

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