Cyclin D1 (CCND1) is a key cell cycle regulatory protein that governs cell cycle progression from the G1 to S phase. A common polymorphism (A870G) in exon 4 of the CCND1 gene produces an alternate transcript (transcript-b) that preferentially encodes a protein with enhanced cell transformation activity and possible prolonged half-life. We evaluated the association of CCND1 A870G polymorphism with breast cancer risk and survival in 1,130 breast cancer cases and 1,196 controls who participated in the Shanghai Breast Cancer Study. Approximately 81% of cases and 79% of controls carried the A allele at A870G of the CCND1 gene [odds ratio, 1.1; 95% confidence interval (95% CI), 0.9-1.4]. As lightly stronger but nonsignificant association was found for the A allele among younger women (odds ratio, 1.3; 95% CI, 0.9-1.8). However, this polymorphism seems to modify the effect of hormonal exposures on postmenopausal breast cancer, as the positive associations of postmenopausal breast cancer with body mass index (Pfor interaction = 0.02) and waist-to-hip ratios (P for interaction < 0.03; all Ps are two sided) were only observed among women who carry the A allele at A870G of the CCND1 gene. Following up with this cohort of patients for an average of 4.84 years, we found that the CCND1 A870G polymorphism was inversely associated with overall and disease-free survival, particularly among women with late stage or estrogen/progesterone receptor-negative breast cancer. The adjusted hazard ratios for disease-free survival associated with GA and AA genotypes were 0.94 (95% CI, 0.49-1.82) and 0.41 (95% CI, 0.19-0.91) for tumor-node-metastasis stage III to IV breast cancer, and 0.35 (95% CI, 0.15-0.80) and 0.32 (95% CI, 0.13-0.79) for estrogen/progesterone receptor-negative breast cancer. This study suggests that CCND1 A870G polymorphism may modify the postmenopausal breast cancer risk associated with hormonal exposure and predict survival after breast cancer diagnosis.

Cyclin D1 (CCND1), a member of the D-type cyclin family, is an essential regulator of cell cycle progression. Overexpression of CCND1 disrupts normal cell cycle control, possibly promoting the development and progression of cancers, including breast cancer (1-3). Overexpression of CCND1 in breast cancer tissue has been described in several studies (4-9) and was related to better prognosis (10, 11) and estrogen/progesterone receptor (ER/PR) positivity (6, 11, 12), whereas low levels of CCND1 was related to early recurrence of ipsilateral breast cancer (13).

A single nucleotide adenine-to-guanine substitution (A870G) in exon 4 of the CCND1 gene produces an alternate transcript (transcript-b) that does not splice at the exon 4-intron 4 boundary (14). Transcript-b does not contain a PEST-rich region, a domain implicated in destabilizing CCND1, which may lead to an increase in the half-life of the alternate protein (14). A number of studies have linked the CCND1 A allele to increased cancer risk (15-21), but the evidence has not been entirely consistent (22-24). A few studies have investigated the effect of CCND1 A870G polymorphism on cancer prognosis with mixed results (14, 25-28). To our knowledge, the relation of CCND1 A870G polymorphism with breast cancer has only been evaluated in two small-scale case-control studies with a null association reported (26, 29). Both of these studies were hospital based, and no information on traditional breast cancer risk factors was available. Using data collected from the Shanghai Breast Cancer Study, we systematically evaluated the association of CCND1 A870G polymorphism with breast cancer risk and survival, particularly in conjunction with estrogenexposure.

Study Participants

The Shanghai Breast Cancer Study is a population-based case-control study. Details of the study design have been described elsewhere (30). Briefly, cases consisted of permanent Shanghai residents between the ages of 25 and 64 years who were newly diagnosed with breast cancer between August 1996 and March 1998. Through a rapid case ascertainment system supplemented by the Shanghai Cancer Registry, 1,602 eligible cases were identified during the study period. Of these, 1,459 (91.1%) participated in the study. The major reasons for nonparticipation were refusal (109 cases, 6.8%), death before interview (17 cases, 1.1%), or inability to locate the subject (17 cases, 1.1%). The initial cancer diagnoses were confirmed by an independent review of pathologic slides by two senior pathologists. Information on cancer diagnosis, disease stage [tumor-node-metastasis (TNM) stage], cancer treatments, and ER/PR status was abstracted from medical charts using a standard protocol.

Controls were randomly selected from the Shanghai Resident Registry, which keeps names and addresses for all permanent residents of urban Shanghai. Controls were frequency matched to cases by age (5-year interval). The number of controls for each age strata was predetermined using the age distribution of breast cancer cases reported to the Shanghai Cancer Registry from 1990 to 1993. Of the 1,734 eligible controls, 1,556 (90.3%) were interviewed. The major reasons for nonparticipation were refusal (166 controls, 9.6%) or death or a prior cancer diagnosis (2 controls, 0.1%). Consent was obtained from all participants, and the study was approved by the institutional review boards of all participating institutes.

Data Collection

All participating cases and controls completed a face-to-face interview using a structured questionnaire. The questionnaire included demographic factors, reproductive factors, hormone use, dietary factors, physical activity, tobacco and alcohol use, prior disease history, family history of cancer, and a quantitative food-frequency questionnaire. Women were measured for current weight, circumference of waist and hips, and sitting and standing heights. All measurements were taken twice by trained interviewers using a standard protocol. A third measurement was taken if any difference between the two measurements was greater than the tolerance limit (1 kg for weight and 1cm for heights and circumferences). The averages of the two closest measurements were used in this analysis.

In addition to the in-person interviews, 10-mL blood samples were obtained from 1,193 cases (82%) and 1,310 controls (84%). The samples were collected in vacutainer tubes containing EDTA or heparin and processed the same day, typically with 6 hours of blood draw, at the Shanghai Cancer Institute and were stored at −70°C.

All 1,459 cancer patients were followed through January 2003 with a combination of active follow-up and record linkage to the death certificates kept by the Vital Statistics Unit of the Shanghai Center for Disease Control and Prevention (31). Of these, 1,290 (88.4%) were successfully contacted either in-person (n = 1,241, 85.0%) or by telephone (n = 49, 3.4%) between March 2000 and December 2002. Among them, 200 patients were deceased. Survival status for the remaining 169 participants who could not be contacted in person or by telephone was established in June 2003 by linkage to the death registry. Through the linkage, 40 deaths were identified and information on the date of death and cause of death was obtained. One hundred twenty-six subjects had no match in the death registry and were assumed to be still living on December 30, 2002, 6months before our search to allow for a possible delay of entry of the death certificates into the registry. Four subjects had insufficient information for the record linkage and were excluded from the survival study. The current report of survival analysis was based on 1,127 breast cancer patients whose genotype information was available.

DNA Extraction and Genotyping

Genomic DNA was extracted from buffy coats (WBC) using Puregene DNA Purification Kits (Gentra Systems, Minneapolis, MN) following the manufacturer's protocol. Genotyping for CCND1 A870G polymorphisms was done using PCR-RFLP method reported previously (32) with modification. The primers for analysis were 5′-GTGAAGTTCATTTCCAATCCGC-3′ and 5′-GGGACATCACCCTCACTTAC-3′. The PCR was done in a Biometra T Gradient Thermocycler. Each 25 μL of PCR mixture contained 10 ng DNA, 1× PCR buffer [50mmol/L KCl, 10 mmol/L Tris-HCl (pH 9.0)], 1.5 mmol/L MgCl2, 0.16 mmol/L each of deoxynucleotide triphosphate, 0.4 μmol/L of each primer, and 1unit of Taq DNA polymerase. The reaction mixture was initially denatured at 94°C for 3 minutes, followed by 35 cycles of 94°C for 45 seconds, 55°C for 45 seconds, and 72°C for 45 seconds. The PCR was completed by a final extension cycle at 72°C for 7 minutes. Each PCR product (10 μL) was digested with 15 units of NciI (New England BioLabs, Beverly, MA) at 37°C for 3hours. The DNA fragments are then separated and visualized by electrophoresis on 3% agarose gel containing ethidium bromide. The A → G substitution at nucleotide 870 in exon 4 creates a NciI cleavage site. The PCR product (167 bp) with the G allele was digested to two fragments (145 and 22 bp), whereas the PCR product with the A allele was not cut by NciI. Genotype for CCND1 was successfully determined for 1,130 cases and 1,196 controls.

The laboratory staff was blind to the identity of the subjects. Quality control samples were included in genotyping assays. Each 96-well plate contained one water, two CEPH 1347-02 DNA, two blinded quality control DNA, and two unblinded quality control DNA samples. The blinded and unblinded quality control samples were taken from the second tube of study samples included in the study. The genotype consistency rate for the 56 study quality control samples was98.2%.

In an ancillary study of the Shanghai Breast Cancer Study, pretreatment plasma from all postmenopausal breast cancer patients (n = 190) and plasma from all postmenopausal controls (n = 407) were measured for levels of steroid hormones and sex hormone-binding globulin (SHBG; ref. 31). These data were included in the current analysis to evaluate the interaction between hormone levels and CCND1 genotype. The hormonal measurements were conducted by Diagnostic Systems Laboratories, Inc. (DSL, Webster, TX), a reference lab certified by Clinical Laboratory Improvement Amendments and the International Standard ISO 9001. Data from premenopausal women were not included in the analysis due to concerns that a single measurement was not sufficient to capture the large hormonal variation that occurs during the menstrual cycle.

Statistical Methods

We used χ2 statistics to analyze the distribution of the CCND1 genotypes in cases and controls, and unconditional logistic regression to derive odds ratio (OR) and 95% confidence interval (95% CI; ref. 33) to measure the strength of the association between CCND1 genotypes and risk of breast cancer. Stratified analyses were conducted to evaluate the modifying effect of CCND1 A870G polymorphism on hormone-related conditions and measurements (the latter was done only for postmenopausal women). Survival time for cases was calculated as the time from cancer diagnosis to the study's end points, censoring at the date of last contact or noncancer death (for disease-free survival only). The Cox regression model was applied to evaluate the effect of the CCND1 genotype on overall survival and disease-free survival with adjustments for age and the known prognostic factors for breast cancer, including TNM cancer treatments and ER/PR status. The proportional hazard assumption of the Cox regression model was examined by graphic evaluation of Schoenfeld's residual plot. Analyses were also conducted by stratifying the data by traditional breast cancer prognostic factors to examine the potential interactive effects. A test for multiplicative interactions was conducted by introducing a product of two relevant variables into the regression models. All Ps are two sided.

Table 1 presents the case-control comparisons on demographic and traditional breast cancer risk factors for subjects who had genotype information. Cases and controls were comparable in age distribution and education attainment. Compared with controls, cases were more likely to have had a breast fibroadenoma, earlier age at menarche, later age at menopause, later age at first live birth, longer total years of menstruation, higher body mass index (BMI), larger waist-to-hip ratio (WHR), and were less likely to regularly engage in exercise in the past 10 years (Table 1). There was no case-control difference in hormone replacement therapy, oral contraceptive use, or alcohol consumption. Subjects included in the current analyses (i.e., those with the genotype data) did not differ in any noticeable way from the participants of the parent Shanghai Breast Cancer Study, and nongenetic risk factors were similar for the substudies and parent studies (data not shown).

Table 1.

Comparison of cases and controls for demographic and selected breast cancer risk factors among subjects with genotype information, the Shanghai Breast Cancer Study

Subject characteristics*Cases(n=1,130)Controls(n=1,196)P
Demographic factors    
    Age(y) 47.6±8.0 47.2±8.7 0.20 
    Education(%high school or more) 43.6 43.1 0.81 
Reproductive risk factors    
    Age at menarche 14.5±1.6 14.7±1.7 <0.01 
    Age at menopause 48.2±4.7 47.4±5.0 0.03 
    Age at first live birth 26.8±4.1 26.2±3.8 <0.01 
    Total years of menstruation 29.8±5.1 28.5±5.5 <0.01 
    No. live births 1.48±0.81 1.52±0.86 0.24 
Other risk factors    
    Breast cancer among first degree relatives(%) 3.4 2.4 0.14 
    Ever had breast fibroadenoma(%) 9.7 5.3 <0.01 
    Ever used hormone replacement therapy(%) 2.5 2.5 0.97 
    BMI (kg/m223.5 ± 3.4 23.2 ± 3.4 0.01 
    WHR 0.81 ± 0.06 0.80 ± 0.06 <0.01 
    Alcohol consumption(% ever) 3.6 3.9 0.70 
    Physically active during past 10 years(%) 19.4 26.1 <0.01 
    Ever used oral contraceptive(%) 21.4 21.5 0.97 
Subject characteristics*Cases(n=1,130)Controls(n=1,196)P
Demographic factors    
    Age(y) 47.6±8.0 47.2±8.7 0.20 
    Education(%high school or more) 43.6 43.1 0.81 
Reproductive risk factors    
    Age at menarche 14.5±1.6 14.7±1.7 <0.01 
    Age at menopause 48.2±4.7 47.4±5.0 0.03 
    Age at first live birth 26.8±4.1 26.2±3.8 <0.01 
    Total years of menstruation 29.8±5.1 28.5±5.5 <0.01 
    No. live births 1.48±0.81 1.52±0.86 0.24 
Other risk factors    
    Breast cancer among first degree relatives(%) 3.4 2.4 0.14 
    Ever had breast fibroadenoma(%) 9.7 5.3 <0.01 
    Ever used hormone replacement therapy(%) 2.5 2.5 0.97 
    BMI (kg/m223.5 ± 3.4 23.2 ± 3.4 0.01 
    WHR 0.81 ± 0.06 0.80 ± 0.06 <0.01 
    Alcohol consumption(% ever) 3.6 3.9 0.70 
    Physically active during past 10 years(%) 19.4 26.1 <0.01 
    Ever used oral contraceptive(%) 21.4 21.5 0.97 
*

Values are presented in means ± SD among cases and controls unless noted otherwise.

Among postmenopausal women.

Among parous women.

The distribution of the CCND1 A870G genotype is consistent with Hardy-Weinberg equilibrium for both cases and controls. Approximately the same proportion of cases (56.3%) and controls (56.5%) possess the A allele of the CCND1 A870G polymorphism, with an OR of 1.1 (95% CI, 0.9-1.4). Overall, the homozygous AA genotype was not related to the risk of breast cancer (OR, 1.0; 95% CI, 0.8-1.3), whereas the heterozygous genotype (GA) was associated with a slightly elevated and borderline significant risk of breast cancer (OR, 1.2; 95% CI, 1.0-1.5; Table 2). The elevated risk was mainly seen in younger women (<45 years old at time of diagnosis), with ORs being 1.4 (95% CI, 1.0-2.0) and 1.2 (95% CI, 0.8-1.8), respectively, for the GA and AA genotypes. The genotype association did not vary by menopausal status (data not shown).

Table 2.

Association of CCND1 A870G polymorphism with breast cancer risk, the Shanghai Breast Cancer Study

Cyclin D1 genotypeCases*
Controls
Age-adjusted OR(95% CI)MultiadjustedOR(95% CI)
No.(%)No.(%)
All participants     
    GG 213(18.8) 250(20.9) 1.00 (reference) 1.0 (reference) 
    GA/AA 917 (81.2) 946 (79.1) 1.1 (0.9-1.4) 1.1 (0.9-1.4) 
    GA 561 (49.7) 540 (45.2) 1.2 (1.0-1.5) 1.2 (1.0-1.5) 
    AA 356 (31.5) 406 (34.0) 1.0 (0.8-1.3) 1.0 (0.8-1.3) 
Women ages <45 y     
    GG 77 (16.9) 103 (20.5) 1.0 (reference) 1.0(reference) 
    GA/AA 380 (83.1) 399 (79.5) 1.3 (0.9-1.8) 1.3 (0.9-1.8) 
    GA 229 (50.1) 231 (46.0) 1.4 (1.0-1.9) 1.4 (1.0-2.0) 
    AA 151 (33.0) 168 (33.5) 1.2 (0.8-1.8) 1.2 (0.8-1.8) 
Women ages ≥45 y     
    GG 136 (20.2) 147 (21.2) 1.0 (reference) 1.0 (reference) 
    GA/AA 537 (79.8) 547 (78.8) 1.0 (0.8-1.4) 1.0 (0.8-1.4) 
    GA 332 (49.3) 309 (44.5) 1.1 (0.9-1.5) 1.1 (0.8-1.5) 
    AA 205 (30.5) 238 (34.3) 0.9 (0.7-1.2) 0.9 (0.7-1.2) 
Cyclin D1 genotypeCases*
Controls
Age-adjusted OR(95% CI)MultiadjustedOR(95% CI)
No.(%)No.(%)
All participants     
    GG 213(18.8) 250(20.9) 1.00 (reference) 1.0 (reference) 
    GA/AA 917 (81.2) 946 (79.1) 1.1 (0.9-1.4) 1.1 (0.9-1.4) 
    GA 561 (49.7) 540 (45.2) 1.2 (1.0-1.5) 1.2 (1.0-1.5) 
    AA 356 (31.5) 406 (34.0) 1.0 (0.8-1.3) 1.0 (0.8-1.3) 
Women ages <45 y     
    GG 77 (16.9) 103 (20.5) 1.0 (reference) 1.0(reference) 
    GA/AA 380 (83.1) 399 (79.5) 1.3 (0.9-1.8) 1.3 (0.9-1.8) 
    GA 229 (50.1) 231 (46.0) 1.4 (1.0-1.9) 1.4 (1.0-2.0) 
    AA 151 (33.0) 168 (33.5) 1.2 (0.8-1.8) 1.2 (0.8-1.8) 
Women ages ≥45 y     
    GG 136 (20.2) 147 (21.2) 1.0 (reference) 1.0 (reference) 
    GA/AA 537 (79.8) 547 (78.8) 1.0 (0.8-1.4) 1.0 (0.8-1.4) 
    GA 332 (49.3) 309 (44.5) 1.1 (0.9-1.5) 1.1 (0.8-1.5) 
    AA 205 (30.5) 238 (34.3) 0.9 (0.7-1.2) 0.9 (0.7-1.2) 
*

Allele frequency among cases:G, 43.7%;A, 56.3%.

Allele frequency among controls:G, 43.5%;A, 56.5%.

Adjusted for age, education, ever had breast fibroadenoma, age at first live birth, age at menopause, and physical activity in the past 10 years.

The associations of hormone-related conditions and measured endogenous hormone levels with breast cancer risk by the CCND1 genotypes are presented in Tables 3 and 4. The associations of BMI and WHR with postmenopausal breast cancer were found to be modified by the CCND1 genotypes (multiplicative interaction test P = 0.02 and 0.03). Among women with the GA or AA genotype, higher BMI (P for trend test = 0.002) and WHR (P for trend test = 0.006) were associated with an increased risk of postmenopausal breast cancer, whereas for women with the GG genotype BMI (P for trend test=0.10) and WHR (P for trend test = 0.023) were inversely associated with risk. Similarly, higher levels of measured estrogens, especially estrone, and testosterone were associated with increased postmenopausal breast cancer among women carrying the GA or AA genotype (P for trend test < 0.01), but was associated with nonsignificantly reduced risk among women with the GG genotype. None of the tests for multiplicative interaction were significant, which is probably due to the small sample size. The inverse association of the plasma SHBG level with breast cancer was also restricted to women with the GA or AA genotype. The CCND1 A870G polymorphism did not seem to modify the effect of BMI on premenopausal breast cancer, which is as expected, because BMI is not related to risk of premenopausal breast cancer. We only found a significant positive association between WHR and premenopausal breast cancer risk among women carrying the GA or AA genotype. The association between years of menstruation and breast cancer risk did not vary by the CCND1 A870G polymorphism for either premenopausal or postmenopausal women (Table 3). We did not find that CCND1 A870G polymorphism modifies the effect of oral contraceptive use (data not shown). Only 2.5% of cases and controls reported ever using hormone replacement therapy in our study, which precluded analyses by this exposure.

Table 4.

Associations of hormonal measurement with postmenopausal breast cancer by CCND1 genotype, the Shanghai Women's Breast Cancer Study

Quartile Levels
Q1
Q2
Q3
Q4
P for trend
Case/controlOR (reference)Case/controlOR (95% CI)Case/controlOR (95% CI)Case/controlOR (95% CI)
Estradiol          
GG 8/18 1.0 6/14 1.1 (0.3-3.9) 19/26 1.8 (0.6-5.3) 8/31 0.6 (0.2-2.0) 0.62 
GA/AA 46/92 1.0 16/71 0.4 (0.1-0.9) 48/87 1.1 (0.7-1.8) 41/74 1.2 (0.7-2.0) 0.24 
    P for interaction = 0.17      
Estrone          
GG 11/15 1.0 4/20 0.2 (0.1-0.9) 10/27 0.6 (0.2-1.6) 16/26 0.8 (0.3-2.2) 0.82 
GA/AA 26/77 1.0 31/75 1.2 (0.7-2.3) 23/86 0.8 (0.4-1.5) 70/83 2.6 (1.5-4.5) <0.001 
    P for interaction = 0.12      
Estrone sulfa          
GG 10/21 1.0 7/22 0.7 (0.2-2.3) 18/26 1.4 (0.5-3.7) 6/20 0.7 (0.2-2.3) 0.95 
GA/AA 33/81 1.0 27/80 0.8 (0.5-1.5) 58/95 1.5 (0.9-2.5) 32/68 1.2 (0.7-2.2) 0.16 
    P for interaction = 0.81      
SHBG          
GG 13/27 1.0 10/24 0.8 (0.3-2.2) 10/22 0.9 (0.3-2.4) 9/16 1.2 (0.4-3.3) 0.44 
GA/AA 47/75 1.0 40/79 0.8 (0.5-1.4) 39/82 0.8 (0.5-1.3) 26/88 0.5 (0.3-0.9) <0.001 
    P for interaction = 0.48      
Testosterone          
GG 7/16 1.0 9/17 1.3 (0.4-4.4) 8/27 0.8 (0.2-2.5) 17/29 1.5 (0.5-4.6) 0.53 
GA/AA 28/80 1.0 23/86 0.8 (0.4-1.4) 33/81 1.2 (0.7-2.2) 67/77 2.5 (1.5-4.3) <0.001 
    P for interaction = 0.29      
Quartile Levels
Q1
Q2
Q3
Q4
P for trend
Case/controlOR (reference)Case/controlOR (95% CI)Case/controlOR (95% CI)Case/controlOR (95% CI)
Estradiol          
GG 8/18 1.0 6/14 1.1 (0.3-3.9) 19/26 1.8 (0.6-5.3) 8/31 0.6 (0.2-2.0) 0.62 
GA/AA 46/92 1.0 16/71 0.4 (0.1-0.9) 48/87 1.1 (0.7-1.8) 41/74 1.2 (0.7-2.0) 0.24 
    P for interaction = 0.17      
Estrone          
GG 11/15 1.0 4/20 0.2 (0.1-0.9) 10/27 0.6 (0.2-1.6) 16/26 0.8 (0.3-2.2) 0.82 
GA/AA 26/77 1.0 31/75 1.2 (0.7-2.3) 23/86 0.8 (0.4-1.5) 70/83 2.6 (1.5-4.5) <0.001 
    P for interaction = 0.12      
Estrone sulfa          
GG 10/21 1.0 7/22 0.7 (0.2-2.3) 18/26 1.4 (0.5-3.7) 6/20 0.7 (0.2-2.3) 0.95 
GA/AA 33/81 1.0 27/80 0.8 (0.5-1.5) 58/95 1.5 (0.9-2.5) 32/68 1.2 (0.7-2.2) 0.16 
    P for interaction = 0.81      
SHBG          
GG 13/27 1.0 10/24 0.8 (0.3-2.2) 10/22 0.9 (0.3-2.4) 9/16 1.2 (0.4-3.3) 0.44 
GA/AA 47/75 1.0 40/79 0.8 (0.5-1.4) 39/82 0.8 (0.5-1.3) 26/88 0.5 (0.3-0.9) <0.001 
    P for interaction = 0.48      
Testosterone          
GG 7/16 1.0 9/17 1.3 (0.4-4.4) 8/27 0.8 (0.2-2.5) 17/29 1.5 (0.5-4.6) 0.53 
GA/AA 28/80 1.0 23/86 0.8 (0.4-1.4) 33/81 1.2 (0.7-2.2) 67/77 2.5 (1.5-4.3) <0.001 
    P for interaction = 0.29      

NOTE: Adjusted for age.

Table 3.

Associations of hormone-related conditions with breast cancer by CCND1 genotype, the Shanghai Women's Breast Cancer Study*

Quartile levels
Q1
Q2
Q3
Q4
P for trend
Case/controlOR (reference)Case/controlOR (95% CI)Case/controlOR(95% CI)Case/controlOR (95% CI)
All subjects          
    BMI          
        GG 42/61 1.0 62/63 1.4 (0.8-2.3) 59/59 1.3 (0.8-2.3) 50/67 1.0 (0.6-1.8) 0.20 
        GA/AA 195/237 1.0 207/236 1.0 (0.8-1.3) 236/240 1.2 (0.9-1.5) 277/232 1.4 (1.1-1.9) 0.002 
    P for interaction = 0.26      
    WHR          
        GG 51/58 1.0 53/55 1.1 (0.6-1.9) 51/57 1.0 (0.6-1.7) 58/80 0.8 (0.5-1.3) 0.08 
        GA/AA 173/242 1.0 220/252 1.2(0.9-1.6) 247/234 1.5(1.1-1.9) 275/217 1.8(1.4-2.4) <0.001 
    P for interaction = 0.03      
    Years of menstruation          
        GG 25/61 1.0 57/67 2.2 (1.1-4.3) 51/48 3.0 (1.4-6.5) 80/74 3.3 (1.5-7.2) 0.002 
        GA/AA 135/217 1.0 211/233 1.5 (1.0-2.1) 228/207 2.1 (1.4-3.2) 337/284 2.7 (1.8-4.1) <0.001 
    P for interaction = 0.62      
Premenopausal women          
    BMI          
        GG 27/39 1.0 30/40 1.0 (0.5-2.0) 45/42 1.4 (0.7-2.7) 35/36 1.2 (0.6-2.5) 0.93 
        GA/AA 134/151 1.0 135/148 1.0 (0.7-1.4) 164/150 1.1 (0.8-1.6) 185/155 1.2 (0.9-1.7) 0.12 
    P for interaction = 0.91      
    WHR          
        GG 32/35 1.0 30/41 0.8 (0.4-1.5) 37/38 1.1 (0.6-2.1) 38/43 0.9 (0.4-1.7) 0.61 
        GA/AA 108/161 1.0 149/141 1.6 (1.1-2.2) 169/154 1.6 (1.1-2.2) 192/148 1.9 (1.3-2.6) <0.001 
    P for interaction = 0.20      
    Years of menstruation          
    GG 16/31 1.0 26/41 1.2 (0.5-3.1) 41/42 2.1 (0.7-6.7) 54/43 3.2 (0.8-12.0) 0.10 
    GA/AA 86/139 1.0 97/123 1.4(0.9-2.2) 199/162 2.7 (1.6-4.6) 237/180 3.9 (2.1-7.3) <0.001 
    P for interaction = 0.92      
Postmenopausal women          
    BMI          
        GG 23/16 1.0 21/28 0.5 (0.2-1.2) 10/18 0.3 (0.1-1.0) 22/31 0.5 (0.2-1.2) 0.10 
        GA/AA 56/92 1.0 67/79 1.4 (0.9-2.2) 74/89 1.4 (0.9-2.2) 95/77 2.1 (1.3-3.2) 0.002 
    P for interaction = 0.02      
 WHR          
        GG 18/18 1.0 23/20 1.0 (0.4-2.6) 16/22 0.6 (0.2-1.6) 19/33 0.5 (0.2-1.3) 0.023 
        GA/AA 61/95 1.0 63/81 1.2 (0.8-2.0) 74/88 1.3 (0.9-2.1) 94/73 2.1 (1.3-3.3) 0.006 
    P for interaction = 0.03      
    Years of menstruation          
        GG 10/23 1.0 27/27 2.5 (1.0-6.7) 14/19 2.2 (0.8-6.7) 25/24 3.2 (1.2-8.8) 0.01 
        GA/AA 34/76 1.0 75/79 2.2(1.3-3.8) 75/81 2.2(1.3-3.8) 108/101 2.7(1.6-4.5) <0.001 
    P for interaction = 0.97      
Quartile levels
Q1
Q2
Q3
Q4
P for trend
Case/controlOR (reference)Case/controlOR (95% CI)Case/controlOR(95% CI)Case/controlOR (95% CI)
All subjects          
    BMI          
        GG 42/61 1.0 62/63 1.4 (0.8-2.3) 59/59 1.3 (0.8-2.3) 50/67 1.0 (0.6-1.8) 0.20 
        GA/AA 195/237 1.0 207/236 1.0 (0.8-1.3) 236/240 1.2 (0.9-1.5) 277/232 1.4 (1.1-1.9) 0.002 
    P for interaction = 0.26      
    WHR          
        GG 51/58 1.0 53/55 1.1 (0.6-1.9) 51/57 1.0 (0.6-1.7) 58/80 0.8 (0.5-1.3) 0.08 
        GA/AA 173/242 1.0 220/252 1.2(0.9-1.6) 247/234 1.5(1.1-1.9) 275/217 1.8(1.4-2.4) <0.001 
    P for interaction = 0.03      
    Years of menstruation          
        GG 25/61 1.0 57/67 2.2 (1.1-4.3) 51/48 3.0 (1.4-6.5) 80/74 3.3 (1.5-7.2) 0.002 
        GA/AA 135/217 1.0 211/233 1.5 (1.0-2.1) 228/207 2.1 (1.4-3.2) 337/284 2.7 (1.8-4.1) <0.001 
    P for interaction = 0.62      
Premenopausal women          
    BMI          
        GG 27/39 1.0 30/40 1.0 (0.5-2.0) 45/42 1.4 (0.7-2.7) 35/36 1.2 (0.6-2.5) 0.93 
        GA/AA 134/151 1.0 135/148 1.0 (0.7-1.4) 164/150 1.1 (0.8-1.6) 185/155 1.2 (0.9-1.7) 0.12 
    P for interaction = 0.91      
    WHR          
        GG 32/35 1.0 30/41 0.8 (0.4-1.5) 37/38 1.1 (0.6-2.1) 38/43 0.9 (0.4-1.7) 0.61 
        GA/AA 108/161 1.0 149/141 1.6 (1.1-2.2) 169/154 1.6 (1.1-2.2) 192/148 1.9 (1.3-2.6) <0.001 
    P for interaction = 0.20      
    Years of menstruation          
    GG 16/31 1.0 26/41 1.2 (0.5-3.1) 41/42 2.1 (0.7-6.7) 54/43 3.2 (0.8-12.0) 0.10 
    GA/AA 86/139 1.0 97/123 1.4(0.9-2.2) 199/162 2.7 (1.6-4.6) 237/180 3.9 (2.1-7.3) <0.001 
    P for interaction = 0.92      
Postmenopausal women          
    BMI          
        GG 23/16 1.0 21/28 0.5 (0.2-1.2) 10/18 0.3 (0.1-1.0) 22/31 0.5 (0.2-1.2) 0.10 
        GA/AA 56/92 1.0 67/79 1.4 (0.9-2.2) 74/89 1.4 (0.9-2.2) 95/77 2.1 (1.3-3.2) 0.002 
    P for interaction = 0.02      
 WHR          
        GG 18/18 1.0 23/20 1.0 (0.4-2.6) 16/22 0.6 (0.2-1.6) 19/33 0.5 (0.2-1.3) 0.023 
        GA/AA 61/95 1.0 63/81 1.2 (0.8-2.0) 74/88 1.3 (0.9-2.1) 94/73 2.1 (1.3-3.3) 0.006 
    P for interaction = 0.03      
    Years of menstruation          
        GG 10/23 1.0 27/27 2.5 (1.0-6.7) 14/19 2.2 (0.8-6.7) 25/24 3.2 (1.2-8.8) 0.01 
        GA/AA 34/76 1.0 75/79 2.2(1.3-3.8) 75/81 2.2(1.3-3.8) 108/101 2.7(1.6-4.5) <0.001 
    P for interaction = 0.97      
*

Adjusted for age.

The average follow-up time for the 1,127 breast cancer patients was 4.84 years, whereas the median was 5.17 years. CCND1 A870G polymorphism was unrelated to the TNM stage or the ER/PR status of the breast cancer in the study population (data not shown). This polymorphism, however, was related to a reduced risk of death and/or disease progression, particularly among women with stage III to IV or ER/PR-negative breast cancer (Table 5). The adjusted hazard ratios for disease-free survival associated with the GA and AA genotypes were 0.94(95% CI, 0.49-1.82) and 0.41(95% CI, 0.19-0.91) for TNM stage III to IV breast cancer and 0.35 (95% CI, 0.15-0.80) and 0.32(0.13-0.79) for ER/PR-negative breast cancer. The corresponding hazard ratios were 0.94 (95% CI, 0.61-1.45), 0.84 (95% CI, 0.52-1.34) for stage 0 to III cancer, and 0.96 (95% CI, 0.55-1.68) and 0.66(95% CI, 0.36-1.23) for ER/PR-positive cancer. A similar pattern was observed for overall survival.

Table 5.

Association of CCND1 A870G polymorphism with survival among breast cancer patients, the Shanghai Breast Cancer Study

CCND1 genotypeDeath/subjectsHazard ratio*(95% CI)Hazard ratio(95% CI)
Overall survival    
        GG 40/212 1.0 1.0 
        GA 91/560 0.85 (0.56-1.23) 0.83 (0.57-1.21) 
        AA 53/355 0.78 (0.52-1.18) 0.68 (0.45-1.03) 
        Trend test(P 0.25 0.07 
    TNM stages 0, I, and II    
        GG 22/168 1.0 1.0 
        GA 56/469 0.91 (0.56-1.50) 0.89 (0.54-1.48) 
        AA 35/293 0.93 (0.55-1.59) 0.83 (0.48-1.42) 
        Trend test (P 0.83 0.50 
    TNM stages III and IV    
        GG 14/29 1.0 1.0 
        GA 26/57 0.87 (0.45-1.68) 0.76 (0.38-1.53) 
        AA 11/38 0.50 (0.23-1.10) 0.31 (0.13-0.74) 
        Trend test (P 0.08 <0.01 
    ER+/PR+    
        GG 14/76 1.0  
        GA 32/209 0.76 (0.40-1.42) 0.87 (0.45-1.67) 
        AA 19/135 0.68 (0.40-1.36) 0.61 (0.30-1.23) 
        Trend test (P 0.30 0.14 
    ER−/PR−    
        GG 9/39 1.0  
        GA 11/93 0.52 (0.21-1.28) 0.66 (0.24-1.81) 
        AA 8/68 0.53 (0.20-1.39) 0.46 (0.16-1.27) 
        Trend test (P 0.23 0.13 
Disease-free survival    
        GG 50/212 1.0 1.0 
        GA 117/560 0.88 (0.63-1.22) 0.85 (0.61-1.19) 
        AA 67/355 0.78 (0.54-1.12) 0.70 (0.49-1.02) 
        Trend test (P 0.18 0.06 
    TNM stages 0, I, and II    
        GG 29/168 1.0 1.0 
        GA 79/469 0.98 (0.64-1.50) 0.94 (0.61-1.45) 
        AA 46/293 0.90 (0.57-1.44) 0.84 (0.52-1.34) 
        Trend test (P 0.64 0.42 
    TNM stages III and IV    
        GG 15/29 1.0 1.0 
        GA 29/57 1.01 (0.54-1.90) 0.94 (0.49-1.82) 
        AA 13/38 0.61 (0.29-1.29) 0.41 (0.19-0.91) 
        Trend test (P 0.18 0.02 
    ER+/PR+    
        GG 18/76 1.0  
        GA 45/209 0.85 (0.49-1.47) 0.96 (0.55-1.68) 
        AA 24/135 0.69 (0.37-1.27) 0.66 (0.36-1.23) 
        Trend test (P 0.23 0.15 
    ER−/PR−    
        GG 12/39 1.0  
        GA 13/93 0.41 (0.19-0.90) 0.35 (0.15-0.80) 
        AA 11/68 0.44 (0.19-1.02) 0.32 (0.13-0.79) 
        Trend test (P 0.08 0.02 
CCND1 genotypeDeath/subjectsHazard ratio*(95% CI)Hazard ratio(95% CI)
Overall survival    
        GG 40/212 1.0 1.0 
        GA 91/560 0.85 (0.56-1.23) 0.83 (0.57-1.21) 
        AA 53/355 0.78 (0.52-1.18) 0.68 (0.45-1.03) 
        Trend test(P 0.25 0.07 
    TNM stages 0, I, and II    
        GG 22/168 1.0 1.0 
        GA 56/469 0.91 (0.56-1.50) 0.89 (0.54-1.48) 
        AA 35/293 0.93 (0.55-1.59) 0.83 (0.48-1.42) 
        Trend test (P 0.83 0.50 
    TNM stages III and IV    
        GG 14/29 1.0 1.0 
        GA 26/57 0.87 (0.45-1.68) 0.76 (0.38-1.53) 
        AA 11/38 0.50 (0.23-1.10) 0.31 (0.13-0.74) 
        Trend test (P 0.08 <0.01 
    ER+/PR+    
        GG 14/76 1.0  
        GA 32/209 0.76 (0.40-1.42) 0.87 (0.45-1.67) 
        AA 19/135 0.68 (0.40-1.36) 0.61 (0.30-1.23) 
        Trend test (P 0.30 0.14 
    ER−/PR−    
        GG 9/39 1.0  
        GA 11/93 0.52 (0.21-1.28) 0.66 (0.24-1.81) 
        AA 8/68 0.53 (0.20-1.39) 0.46 (0.16-1.27) 
        Trend test (P 0.23 0.13 
Disease-free survival    
        GG 50/212 1.0 1.0 
        GA 117/560 0.88 (0.63-1.22) 0.85 (0.61-1.19) 
        AA 67/355 0.78 (0.54-1.12) 0.70 (0.49-1.02) 
        Trend test (P 0.18 0.06 
    TNM stages 0, I, and II    
        GG 29/168 1.0 1.0 
        GA 79/469 0.98 (0.64-1.50) 0.94 (0.61-1.45) 
        AA 46/293 0.90 (0.57-1.44) 0.84 (0.52-1.34) 
        Trend test (P 0.64 0.42 
    TNM stages III and IV    
        GG 15/29 1.0 1.0 
        GA 29/57 1.01 (0.54-1.90) 0.94 (0.49-1.82) 
        AA 13/38 0.61 (0.29-1.29) 0.41 (0.19-0.91) 
        Trend test (P 0.18 0.02 
    ER+/PR+    
        GG 18/76 1.0  
        GA 45/209 0.85 (0.49-1.47) 0.96 (0.55-1.68) 
        AA 24/135 0.69 (0.37-1.27) 0.66 (0.36-1.23) 
        Trend test (P 0.23 0.15 
    ER−/PR−    
        GG 12/39 1.0  
        GA 13/93 0.41 (0.19-0.90) 0.35 (0.15-0.80) 
        AA 11/68 0.44 (0.19-1.02) 0.32 (0.13-0.79) 
        Trend test (P 0.08 0.02 
*

Adjusted for age.

Adjusted for age, education, radiotherapy chemotherapy, and tamoxifen use as well as ER/PR status or TNM stage whenever relevant.

In this large population-based case-control study, we found that the A allele of the CCND1 A870G polymorphism was only weakly associated with the risk of breast cancer among women ages <45 years. However, there was a strong indication that CCND1 A870G polymorphism may modify the association of endogenous sex hormone exposure with postmenopausal breast cancer risk. Among women with the GA or AA genotype, BMI and WHR, as well as blood levels of estrone and testosterone, were positively associated with postmenopausal breast cancer risk, whereas these variables were either unrelated or inversely related to risk among women with the GG genotype. We also found that the inverse association between SHBG level and postmenopausal breast cancer risk was restricted to women carrying the A allele of the CCND1 A870G polymorphism. Furthermore, we found that the CCND1 A870G polymorphism was associated with a favorable outcome, particularly for women with late-stage or ER/PR-negative breast cancer.

CCND1 A870G polymorphism produces an alternate protein, transcript-b, which has been suggested to have an increased half-life (14). However, one recent study indicated that transcript-b is not significantly more stable than CCND1 transcript-a and is a poor catalyst of RB phosphorylation/inactivation (34). Instead, transcript-b exhibits markedly enhanced cell transformation activity relative to transcript-a (34). Presence of the A allele (GA or AA genotype) has been reported to be positively associated with risk of colorectal cancer (15-17), adenomas (35), and cancers of the esophagus/stomach (18), head/neck (19), bladder (20), and prostate (21), although a null association has also been reported for cancers of the bladder (22), mouth (23), and esophagus (24). CCND1 A870G polymorphism was not associated with breast cancer in a recent case-control study involving 339 breast cancer and 327 age-matched controls (26). In an Austrian study of 500 breast cancer cases and the same number of controls, the AA genotype was related to an OR of 1.25 (95% CI, 0.94-1.67; ref. 29), which is similar to the point estimate found in our study. Information on traditional breast cancer risk factors, including hormone-related factors, was not available for the two previous studies. Neither of the earlier studies analyzed data by age at diagnosis.

The interaction found in our study between estrogen exposure and CCND1 A870G polymorphism has not been previously reported but is biologically possible. It is known that estrogen plays a critical role in breast cancer etiology (36). Epidemiological studies, including the Shanghai Breast Cancer Study, have repeatedly linked high levels of estrogens and low levels of SHBG (which affects bioavailable estrogen) to the risk of breast cancer, especially among postmenopausal women (37-39). The effect of BMI, a well-established risk factor for postmenopausal breast cancer (40-42), is also believed to be attributable to the increase of extraovarian production of estrogen in fat issue and the decrease in SHBG related to obesity (42, 43). WHR is positively associated with levels of androgens, the precursors of estrogen production in postmenopausal women, and is inversely related to SHBG levels (42, 44). WHR has also been linked to an increased risk of breast cancer (41, 45-47) and a recent review suggested that WHR was primarily related to premenopausal breast cancer after controlling for the effect of overall obesity (48). In addition to causing direct damage to DNA, estrogens can induce transcription of the CCND1 gene (49, 50). On the other hand, CCND1 can also bind directly to the estrogen receptor, transactivate estrogen receptor response elements (9), and regulate estrogen-dependent enhancer activity (50). Therefore, estrogen exposure and functional genetic polymorphism of the CCND1 gene may synergistically increase the risk of breast cancer. An earlier observation that oral contraceptive use was associated with an increased risk of breast cancer with CCND1 overexpression but was unrelated to those without CCND1 overpression lends further support to the interactive role of estrogen exposure and CCND1 on breast cancer risk (12).

Studies on CCND1 (A870G) polymorphism and cancer progression have produced mixed results. In a recent study of 31 patients with advanced preinvasive lesions of the larynx and/or oral cavity, the A allele of the CCND1 (A870G) polymorphism was found to be associated with increased CCND1 expression in the parabasal epithelial layer and poor disease outcomes (25). The A allele was also associated with shortened event-free survival and a greater risk of local relapse in non-small cell lung cancer (14). A study of ovarian cancer found no association of overall survival with CCND1 polymorphism, but the AA genotype was positively associated with early disease progression and reduced survival among women who responded to postoperative chemotherapy (27). However, the AA genotype was related to an increased disease-free interval, better differentiated tumors for squamous cell carcinoma of the head and neck (28), and differentiated hepatocellular carcinoma (51). The only previous study on A870G polymorphism and breast cancer survival (involving 339 cases) reported a null association with breast cancer prognosis (26). The inconsistent literature on CCND1 genotype and cancer prognosis may be attributable to the characteristics of cancers, study setting and design, as well as the treatment regimens. In this large population-based study, we found that carrying the A allele of the CCND1 A870G polymorphism was related to a favorable outcome for breast cancer, particularly among those with a stage III to IV or ER/PR-negative breast cancer. Our findings are in agreement with earlier observations that CCND1 induces apoptosis (9). Because rapidly proliferating breast cancer is likely to be more sensitive to chemotherapy (52), our finding of a stronger inverse association of CCND1 polymorphism with breast cancer survival among women with late-stage or ER/PR-negative breast cancer may be a result of increased response to chemotherapy due to the increased apotosis associated with the polymorphism and increased proliferation associated with advanced disease characteristics. Furthermore, it is possible that among patients with ER-positive breast cancer, the possible beneficial effect of CCND1 on prognosis may be offset by its ability to bind to the ER (50), compromising the effect of hormonal therapy (10). However, results from the stratified analyses should be interpreted with caution, given the small sample sizes and multiple comparisons involved. More studies are needed to confirm our findings and delineate the underlying biological mechanism(s).

Our study has many strengths. The comprehensive exposure and clinical information allowed evaluations of the interactions between genetic susceptibility and the traditional risk/prognostic factors and adjustment for nongenetic factors. In our study, 98% of the participants belong to the Han Chinese ethnic group; thus, the results are unlikely to be confounded by ethnicity. Excluding 23% of study participants from the current analyses due to the lack of genotype data raises concern about potential selection bias, although the population-based design and high response rates undoubtedly minimized this. It is also important to note that the nongenetic risk factors observed among subjects participating in the parent study and the current substudy were similar. In addition, it unlikely that subjects' decision about donating a blood sample is related to their CCND1 genotype. The small sample size used for some of the stratified analyses, particularly for those involving hormonal measurements, is another limitation, resulting in unstable risk estimates and insufficient statistical power for interaction tests.

In summary, we found that CCND1 A870G polymorphism does not seem to have a major gene effect on breast cancer. However, this polymorphism modifies the effects of estrogen on breast cancer development. In addition, it increases survival among Chinese breast cancer patients, particularly those with stage III to IV or ER-negative breast cancer.

Grant support: National Cancer Institute USPHS grants R01-CA64277 and RO1 CA90899

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

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