Skip Navigation


Carcinogenesis Advance Access originally published online on October 22, 2005
Carcinogenesis 2006 27(3):599-605; doi:10.1093/carcin/bgi246
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrowOA All Versions of this Article:
27/3/599    most recent
bgi246v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (6)
Google Scholar
Right arrow Articles by Colilla, S.
Right arrow Articles by Rebbeck, T. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Colilla, S.
Right arrow Articles by Rebbeck, T. R.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

The joint effect of smoking and AIB1 on breast cancer risk in BRCA1 mutation carriers

Susan Colilla *, Philip W. Kantoff 2, 3, Susan L. Neuhausen 4, Andrew K. Godwin 5, Mary B. Daly 5, Steven A. Narod 6, Judy E. Garber 2, Henry T. Lynch 7, Myles Brown 2, Barbara L. Weber 1 and Timothy R. Rebbeck

Department of Biostatistics and Epidemiology and 1 Medicine and Genetics, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA, 2 Department of Medical Oncology and 3 Lank Center for Genitourinary Cancer, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA, 4 Division of Epidemiology, Department of Medicine, University of California Irvine, Irvine, CA, USA, 5 Fox Chase Cancer Center, Philadelphia, PA 19111, USA, 6 Women's College Hospital, Toronto, ON M5G 1N8, Canada and 7 Department of Preventive Medicine, Creighton University, Omaha, NE 68179, USA

* To whom correspondence should be addressed at: Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, Room no. 916, 423 Guardian Drive, Philadelphia, PA 19104, USA. Tel: +1 215 746 0370; Fax: +1 215 573 2265; Email: scolilla{at}cceb.med.upenn.edu


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Women with BRCA1 mutations are at an elevated risk for breast cancer. AIB1 (NCOA3/SRC3) genotype and smoking may alter this risk. We examined the differences in breast cancer risk by AIB1 polyglutamine repeat polymorphism and pre-diagnosis smoking habits for BRCA1 mutation carriers to determine if there was an interaction between smoking and AIB1 genotype. Multivariate Cox proportional hazards regression was used with 316 female BRCA1 mutation carriers to model breast cancer risk. Ever having smoked was associated with a decreased breast cancer risk [Hazard Ratio (HR) = 0.63, 95% CI, 0.47–0.87]. A dose–response relationship between number of pack-years smoked and breast cancer risk was also found for women who smoked <20 pack years of cigarettes (HR = 0.72, 95% CI, 0.52–1.00) and for women who smoked ≥20 pack years (HR = 0.41, 95% CI, 0.23–0.71; P for trend = 0.0007). Women with a 28 repeat allele for AIB1 had a significantly reduced risk of breast cancer (HR = 0.72, 95% CI, 0.51–1.00). Women who smoked ≥20 pack-years with a 28 repeat allele had an even greater reduced risk of breast cancer (HR = 0.19, 95% CI, 0.07–0.54) compared to women who were never smokers with no 28 allele. Since AIB1 appears to modulate the effect of endogenous hormones via the estrogen receptor, and smoking affects circulating hormone levels, these results support evidence that steroid hormones play an important role in breast carcinogenesis in BRCA1 mutation carriers, and suggest mechanisms for developing novel cancer prevention strategies for BRCA1 mutation carriers.

Abbreviations: BRCA1, breast cancer susceptibility gene 1; CI, confidence interval; ER, estrogen receptor; df, degrees of freedom; HR, hazard ratio; SNPs, single nucleotide polymorphisms


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Women who have inherited a breast cancer susceptibility gene 1, BRCA1, mutation have a higher lifetime risk of developing breast or ovarian cancer than women without such a mutation (1–10). Breast cancer penetrance in women with a BRCA1 mutation is variable, however, and may in part be explained by other factors involved in breast carcinogenesis (6,11). Both environmental exposures and additional cancer susceptibility genes may alter the occurrence and timing of BRCA1-associated breast cancer.

Tobacco smoke is also a well-known carcinogen (12,13), but its relationship with breast cancer has been unclear. Studies have reported a higher prevalence of DNA adducts and p53 mutations in the breast tissue of smokers compared with non-smokers and these mutations are breast cancer risk factors (14–17). Cigarette smoking is also considered to have anti-estrogenic effects in women: early menopause, a decreased risk of endometrial cancer, and an increased risk of osteoporosis have all been reported at higher prevalences in smokers compared with non-smokers. (18–20) The direct relationship between cigarette smoking and breast cancer in epidemiologic studies, however, has been equivocal. For women in the general population, only smoking for long duration or prior to first term pregnancy may increase breast cancer risk (21,22). A recent prospective study reported that smoking was positively associated with estrogen receptor (ER)-positive breast cancer.(22)

Only a few studies have examined smoking as a risk factor for women with familial breast cancer (23–25). Brunet et al. (23) performed a matched case–control study of 186 BRCA1 and BRCA2 mutation carriers (including a subset of women in the present study), and reported a significant protective effect of smoking upon breast cancer risk. This study was expanded recently to >1000 matched case–control pairs but failed to replicate their earlier finding of a statistically significant protective effect of smoking on breast cancer risk in women with BRCA1/2 mutations (26).

A prospective study of women from high risk families, uncharacterized for BRCA1 or BRCA2 mutations, found smoking increased risk of breast cancer (24). Recently, Reynolds et al. (25) found active smoking increased breast cancer risk significantly in a cohort of California teachers, but smoking was not a significant risk factor for women who had a family history of breast cancer. Given these discrepant results, it remains unclear if smoking significantly affects breast cancer risk, and if smoking may have a different effect in women who are inherently at a higher risk for breast cancer.

Likewise, a woman's breast cancer risk may be dictated by genes that modulate estrogen effects. For example, the number of polyglutamine (CAG) repeats in the steroid receptor co-activator gene AIB1 (NCOA3/SRC3/AIB1) has been found to modulate the risk of breast cancer in women with a BRCA1 or BRCA2 mutation (27,28), although another study failed to find an association (29). The association between AIB1 polyglutamine repeat length genotype in two studies of familial non-BRCA mutation carriers also did not find an association with increased breast cancer risk (30,31), but a study examining single nucleotide polymorphisms (SNPs) within the AIB1 coding region did find a significant association between SNPs Q586H and T960T with breast cancer in a German and Polish population (32). Another study examining AIB1 polyglutamine repeat length and breast cancer risk in women with familial breast cancer failed to find an association (30). The variability of results may reflect an interaction between AIB1 genotype, environmental factors, in different BRCA mutation carrier populations and/or may also be reflective of the way AIB1 polyglutamine repeat length is coded and analyzed across the studies.

BRCA1-associated breast cancers are hormone-sensitive, as evidenced by the dramatic reduction in breast cancer risk observed after prophylactic oophorectomy (33). Because AIB1 is a co-activator that affects estrogen levels, (34–38) and smoking is considered to have potential anti-estrogenic effects, we evaluated the joint effect of smoking history and AIB1 genotype on breast cancer risk in women with BRCA1 mutations only. In particular, we limited our analysis to women with BRCA1 mutations only to increase the underlying homogeneity of our sample set and to focus the biological hypotheses, and re-examined the coding of the AIB1 repeat polymorphism, to determine the true effect that AIB1 genotype may have on breast cancer risk in these women.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Study population
Women who were either physicians or self-referred to risk evaluation clinics for genetic testing, generally because of a strong family history of breast and/or ovarian cancer, were ascertained at multiple sites in the USA and Canada (Creighton University, Omaha, NE; the Dana-Farber Institute, Boston, MA; Fox Chase Cancer Center, Philadelphia, PA; the University of Pennsylvania, Philadelphia, PA; and the Women's College Hospital, Toronto, Canada) (27). Women were eligible for entry into the study cohort if they tested positive for a known deleterious mutation in BRCA1. Institutional review board-approved written consent was obtained from all participants. DNA samples were available for 363 women who were genotyped for AIB1 polyglutamine repeat polymorphisms. Women were excluded if they were <18 years of age at time of BRCA1 testing, were missing information on year of birth, smoking, height, parity, menopausal status, oral contraceptive use and Jewish ethnicity. After exclusions, we had 176 women with breast cancer and 140 women without breast cancer available for analysis.

Information about invasive breast cancer, ovarian cancer, prophylactic mastectomy and prophylactic oophorectomy was obtained from medical records, and information on reproductive history and lifestyle habits was obtained by questionnaire. Pre-diagnosis smoking histories included information on whether the participant ever smoked regularly, age at which the participant started smoking and stopped smoking, the number of years the participant smoked and how many packs were smoked by the participant per week. DNA samples were genotyped to determine the number of CAG repeats in AIB1 as previously described (27). To examine a more homogenous group of women, who are at a similar risk for breast cancer, our study only included women with a disease-causing, deleterious inherited BRCA1 mutation.

Statistical analysis
We analyzed our data as a cohort, where the event of interest was the diagnosis of a first primary invasive breast cancer. Time to event was computed from 18 years of age to the year of breast cancer diagnosis. Women were censored at the time they experienced the following events which might alter their breast cancer risk: the occurrence of prophylactic mastectomy, prophylactic oophorectomy or ovarian cancer if these occurred prior to the breast cancer event. A woman's smoking history and menopausal status were censored to the exposure which occurred prior to a breast cancer diagnosis or other censoring event. Time to censoring was computed from age 18 to year of the first censoring event. For women without any of these censoring events or breast cancer diagnosis, the year of ascertainment was used as the censoring endpoint.

Cox proportional hazards regression and Kaplan–Meier survival distributions were calculated using SAS statistical software (39). Hazard ratios and 95% confidence intervals (CIs) from Cox proportional hazard regression were estimated for the association between smoking and/or AIB1 genotype and breast cancer. Variance–covariance estimates were adjusted for non-independence of participants (i.e. multiple participants within a family) using the robust covariance sandwich method of Lin et al. (40). We adjusted the proportional hazard models for potential confounding by year of birth, number of live births (parity), menopausal status, height, oral contraceptive use and Jewish ancestry. Age at first birth and age at menarche were also considered as potential confounders, but as they did not alter the point estimates for either AIB1 or smoking, they were not included as covariates in the regression models.

Smoking history was analyzed in several ways. First, we examined if ever versus never smoking affected breast cancer risk. Second, we examined if the number of pack-years (calculated as the number of packs per day multiplied by the number of years smoked) altered the risk of breast cancer. Because it has been suggested by others (41) that smoking exposure may only have an effect on breast cancer risk in long-term or heavy users of tobacco, we studied pack-years as a categorical variable, dividing the subjects into women who were never smokers, those who smoked <20 pack-years, and those women who smoked ≥20 pack-years.

Breast cancer risk was also assessed by AIB1 genotype (considering alleles with a genotype frequency >1%). AIB1 genotype has been examined in relation to breast cancer risk in several ways. Some reports have suggested that AIB1 polyglutamine polymorphisms ≥29 repeats increase risk for breast cancer in BRCA1/2 carriers (27,28), while others have suggested that ≤26 repeats was associated with higher breast density (42). Given the potential increased risk for breast cancer for either length, the shorter ≤26 repeat allele or the longer ≥29 repeat allele, we examined breast cancer risk by AIB1 genotype, using the most common middle length allele 28 as the referent group. Then, because some of the genotypes were rare, we collapsed the genotypes into groups of women who have at least one 28 repeat allele compared to women who did not have any 28 repeat allele because this was the most common low-risk allele, similar to a method used by Wilkening et al. (30). This categorization was chosen based on observations in previous reports that women with a 29 allele seem to be at greatest risk and women with a 28 allele are at lower risk for breast cancer (27,28), and represents a different approach from our previous report (27).

To test for an interaction under a multiplicative model between AIB1 and smoking history on breast cancer risk we used –2 log likelihood tests between regression models comparing the significance of a multiplicative interaction term combining smoking (yes/no) and AIB1 allele (≥ one 28 repeat allele/no 28 allele) variables. This interaction tests for deviation from a multiplicative statistical model between these two variables. The joint effect of AIB1 and smoking was also estimated for women with ever smoking exposure or heavy smoking exposure only (≥20 pack-years) with the AIB1 repeat allele, and compared with women who had never smoked and had a referent AIB1 allele (reference group).


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
Year of birth, age at interview, oral contraceptive use and menopausal status varied significantly by smoking and breast cancer status for the BRCA1 women in our sample (Table I). The frequency of other reproductive variables such as age at menarche, age at first pregnancy and parity did not vary significantly across all four groups of women.


View this table:
[in this window]
[in a new window]
  		Table I. Distribution of risk factors for breast cancer in women with a BRCA1 mutations

 
Ever smokers had a significantly decreased risk of breast cancer (HR = 0.63, 95% CI, 0.47–0.87) after adjusting for year of birth, parity, menopausal status, height, oral contraceptive use, and Jewish ancestry in the Cox regression models (Table II). In addition, there was a dose-response relationship between number of pack-years smoked and breast cancer risk (<20 pack-years HR = 0.72, 95% CI, 0.52–0.1.00; ≥20 pack-years HR = 0.41, 95% CI,0.23–0.71; P for trend = 0.007). We also examined smoking as a time-dependent covariate, but as the point estimates for smoking and breast cancer risk did not vary substantially from those obtained with the fixed smoking variables (data not shown), and there was a reduction in power when using the time-dependent covariates and drop; we did not use the time-dependent covariates in further analyses.


View this table:
[in this window]
[in a new window]
  		Table II. Frequency distribution and HR for smoking history and risk for breast cancer in women with a BRCA1 mutation

 
Consistent with our previous report (27), the frequency of women with either BRCA1 or BRCA2 mutations and with 29 polyglutamine repeats for AIB1, differed significantly between those who had breast cancer and those who did not ({chi}2 = 8.59, 1 df, P = 0.0034) after adjustment for covariates. Also, consistent with our previous analysis with AIB1, BRCA1 mutation carriers with at least one 28 repeat allele had a reduced risk of breast cancer (HR = 0.72, 95% CI, 0.51–1.00) (Table III), after adjustment for year of birth, parity, height, menopausal status, oral contraceptive use and Jewish ethnicity. A further decrease in breast cancer risk was found in women having at least one AIB1 28 repeat allele and a positive smoking history (Table IV). Among the never smokers, women with at least one 28 repeat allele had a significantly lower breast cancer risk than women with no 28 repeat allele (HR = 0.63, 95% CI, 0.40–1.00). Among women with no 28 repeat allele, those who had ever smoked had a statistically significant lower risk of breast cancer than women who had never smoked (HR = 0.57, 95% CI, 0.35–0.92). Ever smokers with at least one 28 repeat allele were at a significantly lower risk for breast cancer than never smokers with no 28 repeat allele (HR = 0.35, 95% CI, 0.21–0.58; P < 0.0001 for joint effect).


View this table:
[in this window]
[in a new window]
  		Table III. HRs for breast cancer in BRCA1 women by AIB1 genotype

 

View this table:
[in this window]
[in a new window]
  		Table IV. Multivariate HRsa of the joint effect between smoking and AIB1 repeat length alleles in women with a BRCA1 mutation

 
Women who were heavy smokers and had at least one 28 repeat allele had an even greater reduction in breast cancer risk, showing a highly significant difference in breast cancer risk compared with women who had never smoked and did not have a 28 repeat allele (HR = 0.19, 95% CI, 0.07–0.54; joint effect P = 0.002). The interaction term for AIB1 allele and smoking in the regression analysis did not deviate significantly from expectations under a multiplicative model for either ever smoking and AIB1 genotype (P = 0.69), or heavy smoking and AIB1 genotype (P = 0.81) (Table IV). Therefore, we conclude there is a strong joint effect of AIB1 and smoking on breast cancer risk in BRCA1 mutation carriers, and this effect is consistent with expectations of a multiplicative interaction between these two factors.


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
As an extension to our previous analysis where we found AIB1 genotype modulated breast cancer risk in women with BRCA1/2 mutations (27), we report here that smoking is associated with a decrease in breast cancer risk in a dose-dependent manner in our cohort of women with BRCA1 mutations only, and find evidence for a statistically significant joint effect between smoking and AIB1 genotype on breast cancer risk in these women with BRCA1 mutations. While data linking smoking and breast cancer risk in the general population have been inconsistent, it appears that an increase in number of pack-years smoked may have a protective effect in BRCA1/2 mutation carriers. This report suggests that the modulation of the effect of smoking on breast cancer risk may be due to variation in genotypes in estrogen regulatory genes in BRCA1 mutation carriers. A previous study examining the effect of smoking on breast cancer risk in women with BRCA1/2 mutations (23) included a subset of women in this study, and also found a highly protective effect of smoking. Smoking four pack-years or more was associated with a 50% reduction of breast cancer risk. Recently, however, a larger sample of including some of the same matched case-control study of BRCA1/2 mutation carriers as in the first study, reported no significant association between smoking and breast cancer (26), although there was evidence of a small, non-significant protective effect on breast cancer in heavy smokers (OR = 0.81, 95% CI. 0.57–1.15 for BRCA1/2 carriers who smoked ≥20 pack-years). The larger study also used a matched case-control study design and a large proportion of cases (>400) were excluded because a suitable control could not be found in the study; it also included both carriers of BRCA1 or BRCA2 mutations, whereas the present analysis is limited to BRCA1 carriers only and was analyzed as a retrospective cohort. A retrospective cohort study design provides a different approach to analyze the data because of the ability to account for censoring events, such as prophylactic surgeries and ovarian cancer which are common events in BRCA1 carriers that may alter breast cancer risk, without excluding unmatched women in the study. In addition, by using a cohort analysis, we are able to consider smoking exposures that occur prior to breast cancer diagnosis, unlike the study by Ghadirian et al. (26), where smoking history information was obtained for some cases after their breast cancer diagnosis.

Results from this study also suggest that different AIB1-CAG allele repeat lengths may have different effects upon BRCA1-associated breast cancer risk. Women with at least one 28 repeat allele appear to be at a lower risk for breast cancer in BRCA1 mutation carriers than women with longer repeat alleles (≥29 repeats) and possibly those with shorter repeat alleles (≤26 repeats). AIB1 is thought to modulate the effect of endogenous hormones through ER activity (43–45). If AIB1 repeat length alters AIB1 protein function, AIB1 repeat length polymorphisms would affect ER transcriptional activity which could alter breast cancer susceptibility.

The association between AIB1 repeat allele length and breast cancer has been recently confirmed by another study examining the risk of breast cancer in BRCA1 mutation carriers (28). The authors examined the average length of AIB1 alleles in women with BRCA1 mutations and found that longer AIB1 alleles were estimated to be associated with a higher risk of breast cancer. This study also found a significantly increased risk of breast cancer in women who had two alleles with 29 or more repeats compared with women who had shorter repeat length alleles. Therefore, two studies suggest that BRCA1 mutation carriers with a 29 repeat allele have a higher risk of breast cancer than women with the common shorter 28 repeat allele. More research will be needed to determine if shorter repeat allele lengths for AIB1 affect breast cancer risk in BRCA1 mutation carriers as well.

We also found that women smokers with a BRCA1 mutation who had at least one 28 repeat allele in AIB1 genotype, were at significantly reduced risk for breast cancer. To extend this result, we also found that women with at least one 28 allele, who were heavy smokers (≥20 pack-years) had >5-fold reduction in breast cancer risk compared with non-smokers with no 28 allele. The joint effect between smoking and AIB1 was consistent with that of a multiplicative model. The joint effect between smoking and AIB1 accounts for a large part of the variability in breast cancer risk in women with BRCA1 mutations in this study.

How might smoking affect breast cancer risk in women with BRCA1 mutations? Recently, cigarette smoke condensates have been shown to induce the 2-hydroxylation pathway in estrogen metabolism, shunting a percentage of circulating estrogen away from the more potent 16 {alpha}-hydroxylation pathway in mouse hepatoma cells (46). Thus, smoking may effectively decrease the circulating levels of the more carcinogenic estrogens. Their findings also suggested that cigarette-smoke condensates both bind to and activate the estrogen receptor and induce transcription, an effect that might increase breast cancer. It is unclear if these condensates could increase breast cancer risk with increased estrogen signaling or compete with estrogen for the ER. Given the multiple particulate substances in cigarette smoke, it is possible that cigarette smoke may have multiple effects on estrogen metabolism pathways.

Women with BRCA1 mutations tend to have estrogen receptor negative breast tumors (47,48); however, the diagnostic histopathology of a tumor may not be indicative of the effect of hormones on the etiology of a tumor. For example, prophylactic oophorectomy strongly reduces breast cancer risk in women with BRCA1 mutations (33). In addition, the regulation of BRCA1 in human breast cancer cells is hormonally dependent (49,50). BRCA1 has also been shown to inhibit the signaling of ligand-activated estrogen receptor in transfected cells, suggesting that mutations in BRCA1 disrupt the suppression of estrogen-dependent transcriptional pathways (51–53). Smoking has also been associated with the presence of ER negative tumors in both pre-menopausal and post-menopausal women (54,55). It is possible that in BRCA1 mutation carriers, heavy smoking exposure and AIB1 polymorphisms are jointly involved in common pathways involving ER activity and estrogen metabolism which may influence breast cancer risk.

Several factors in this study impact the generalizibility of the results. The women in this study were ascertained from risk evaluation clinics and most likely presented because of a family history of breast and/or ovarian cancer, and thus the women who participated in this study may not be representative of all BRCA1 mutation carriers in the general population (56). However, these participants do represent the sample of women who are most likely to seek and receive genetic test results, and therefore the present results are relevant to the population of women most likely to have knowledge of their BRCA1 mutation status. There may also be a survival bias in this retrospective cohort, in that women who died quickly after developing breast cancer may not have been tested for BRCA1/2 mutations. If these women were disproportionately smokers, then the reduced risk of breast cancer measured in this study could be overestimated. However, large differences in breast cancer mortality due to smoking has not been reported (57,58), making it unlikely that such a survival bias would account for a large part of the risk reduction we have observed.

Birth cohort effects in smoking trends may influence the results if the heavy smokers were more likely to be older women. The regression models, however, adjust for birth year in a multivariate analysis to account for such trends. We also analyzed the data by birth cohort (<1940 and ≥1940) (59) and obtained similar results (data not shown). A possible limitation in this study is that we did not have information on the timing of exogeneous hormone replacement therapy use or about the specific preparations used by these women, and therefore we were unable to consider the effect of hormone replacement therapy prior to the development of breast cancer in these women.

The magnitude of the association, but not the direction, differs from our previous analysis of AIB1 repeat length and breast cancer risk in women with BRCA1 or BRCA2 mutations (27). A number of differences between the present study and our previous study could explain these differences. Given that the initiating events and risk may differ in women with mutations in BRCA1 and BRCA2 (10,60), in the present study we only evaluated the effect of smoking and AIB1 repeat length in women with mutations in BRCA1. Women with BRCA2 mutations were too small in number to analyze separately, and cancer risks and modifying effects of other factors may differ between BRCA1 and BRCA2 mutation carriers. In addition, the present study used Cox proportional hazards regression to estimate the time at risk for breast cancer, censoring events such as prophylactic removal of breasts or ovaries. Thus, we were able to avoid ‘matching’ cases to controls and thereby included a more complete cohort of women than was done in our case–control study of AIB1. These study design and analysis differences may explain why the magnitude of our association between AIB1 repeat allele length and breast cancer were attenuated. The main effects, however, remain the same; women with at least one 29 repeat allele have a higher breast cancer risk than women with a 28 repeat allele.

Even though smoking has been associated with a lower risk of some diseases, such as ulcerative colitis and endometrial cancer (18,61), the deleterious effects of cigarette smoking are well-documented. Lung, oral, esophageal and bladder cancer, not to mention non-cancerous diseases such as heart disease and cerebrovascular disease are strongly associated with cigarette smoking (62–65). Thus, our results should not be used to endorse the initiation of smoking for the prevention of breast cancer in BRCA1 mutation carriers. Rather, the results are useful in elucidating the mechanisms involved in breast cancer development. Determining the mechanisms by which smoking may exert an anti-estrogenic effect, its potential interaction with estrogen signaling pathways, and the potential for regulation of these effects by AIB1, should be a focus for future research. Understanding the pharmacogenetics of smoking and its relation to hormonal pathways may provide insights into new cancer prevention and control modalities in BRCA1 mutation carriers.


   Acknowledgments
 
Supported by grants from the NIH (T32-CA009679 to SC; R21-ES-011658 to TR and SC; R01-CA83855 and R01-CA102776 to T.R.R.; R01-CA57601 to BLW; R01-CA74415 to S.L.N.), the Abramson Cancer Center (to T.R.R.), the Abramson Family Cancer Research Institute (to B.L.W.), the Breast Cancer Research Foundation (to B.L.W.), the Dana-Farber Women's Cancers Program (to J.E.G.), the Department of Defense (DAMD-17-96-I-6088to A.K.G. and DAMD-17-97-I-7112 to H.T.L.), and the Nebraska State Cancer and Smoking-Related Diseases Research Program (LB595 to H.T.L.). Funding to pay the Open Access publication charges for this article was provided by NCI grant R01-CA102776.

Conflict of Interest Statement: Myles Brown is a consultant for, and receives sponsored research support from Novartis.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

  1. Miki,Y., Swensen,J., Shattuck-Eidens,D. et al. (1994) A strong candidate for the breast and ovarian cancer susceptibility gene BRCA1. Science, 266, 66–71.[Abstract/Free Full Text]
  2. Porter,D.E., Cohen,B.B., Wallace,M.R., Smyth,E., Chetty,U., Dixon,J.M., Steel,C.M. and Carter,D.C. (1994) Breast cancer incidence, penetrance and survival in probable carriers of BRCA1 gene mutation in families linked to BRCA1 on chromosome 17q12-21. Br. J. Surg., 81, 1512–1515.[Web of Science][Medline]
  3. Couch,F.J., Garber,J., Kiousis,S. et al. (1995) Genetic analysis of eight breast-ovarian cancer families with suspected BRCA1 mutations. J. Natl Cancer Inst. Monogr., 9–14.
  4. Ford,D., Easton,D.F. and Peto,J. (1995) Estimates of the gene frequency of BRCA1 and its contribution to breast and ovarian cancer incidence. Am. J. Hum. Genet., 57, 1457–1462.[Web of Science][Medline]
  5. Levy-Lahad,E., Catane,R., Eisenberg,S. et al. (1997) Founder BRCA1 and BRCA2 mutations in Ashkenazi Jews in Israel: frequency and differential penetrance in ovarian cancer and in breast-ovarian cancer families. Am. J. Hum. Genet., 60, 1059–1067.[CrossRef][Web of Science][Medline]
  6. Ford,D., Easton,D.F., Stratton,M. et al. (1998) Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer Linkage Consortium. Am. J. Hum. Genet., 62, 676–689.[CrossRef][Web of Science][Medline]
  7. Hopper,J.L., Southey,M.C., Dite,G.S., Jolley,D.J., Giles,G.G., McCredie,M.R., Easton,D.F. and Venter,D.J. (1999) Population-based estimate of the average age-specific cumulative risk of breast cancer for a defined set of protein-truncating mutations in BRCA1 and BRCA2. Australian Breast Cancer Family Study. Cancer Epidemiol. Biomarkers Prev., 8, 741–747.[Abstract/Free Full Text]
  8. Peto,J., Collins,N., Barfoot,R., Seal,S., Warren,W., Rahman,N., Easton,D.F., Evans,C., Deacon,J. and Stratton,M.R. (1999) Prevalence of BRCA1 and BRCA2 gene mutations in patients with early-onset breast cancer. J. Natl Cancer Inst., 91, 943–949.[Abstract/Free Full Text]
  9. Warner,E., Foulkes,W., Goodwin,P. et al. (1999) Prevalence and penetrance of BRCA1 and BRCA2 gene mutations in unselected Ashkenazi Jewish women with breast cancer. J. Natl Cancer Inst., 91, 1241–1247.[Abstract/Free Full Text]
  10. Satagopan,J.M., Offit,K., Foulkes,W., Robson,M.E., Wacholder,S., Eng,C.M., Karp,S.E. and Begg,C.B. (2001) The lifetime risks of breast cancer in Ashkenazi Jewish carriers of BRCA1 and BRCA2 mutations. Cancer Epidemiol. Biomarkers Prev., 10, 467–473.[Abstract/Free Full Text]
  11. Weber,B.L. and Nathanson,K.L. (2000) Low penetrance genes associated with increased risk for breast cancer. Eur. J. Cancer, 36, 1193–1199.[CrossRef][Web of Science][Medline]
  12. Kuper,H., Boffetta,P. and Adami,H.O. (2002) Tobacco use and cancer causation: association by tumour type. J. Intern. Med., 252, 206–224.[CrossRef][Web of Science][Medline]
  13. Hecht,S.S. (2002) Tobacco smoke carcinogens and breast cancer. Environ. Mol. Mutagen., 39, 119–126.[CrossRef][Web of Science][Medline]
  14. Li,D., Walcott,F.L., Chang,P., Zhang,W., Zhu,J., Petrulis,E., Singletary,S.E., Sahin,A.A. and Bondy,M.L. (2002) Genetic and environmental determinants on tissue response to in vitro carcinogen exposure and risk of breast cancer. Cancer Res., 62, 4566–4570.[Abstract/Free Full Text]
  15. Conway,K., Edmiston,S.N., Cui,L. et al. (2002) Prevalence and spectrum of p53 mutations associated with smoking in breast cancer. Cancer Res., 62, 1987–1995.[Abstract/Free Full Text]
  16. Faraglia,B., Chen,S.Y., Gammon,M.D. et al. (2003) Evaluation of 4-aminobiphenyl-DNA adducts in human breast cancer: the influence of tobacco smoke. Carcinogenesis, 24, 719–725.[Abstract/Free Full Text]
  17. Firozi,P.F., Bondy,M.L., Sahin,A.A., Chang,P., Lukmanji,F., Singletary,E.S., Hassan,M.M. and Li,D. (2002) Aromatic DNA adducts and polymorphisms of CYP1A1, NAT2, and GSTM1 in breast cancer. Carcinogenesis, 23, 301–306.[Abstract/Free Full Text]
  18. Baron,J.A., La Vecchia,C. and Levi,F. (1990) The antiestrogenic effect of cigarette smoking in women. Am. J. Obstet. Gynecol., 162, 502–514.[Web of Science][Medline]
  19. Jensen,J. and Christiansen,C. (1988) Effects of smoking on serum lipoproteins and bone mineral content during postmenopausal hormone replacement therapy. Am. J. Obstet. Gynecol., 159, 820–825.[Web of Science][Medline]
  20. Ward,K.D. and Klesges,R.C. (2001) A meta-analysis of the effects of cigarette smoking on bone mineral density. Calcif. Tissue Int., 68, 259–270.[CrossRef][Web of Science][Medline]
  21. Terry,P.D. and Rohan,T.E. (2002) Cigarette smoking and the risk of breast cancer in women: a review of the literature. Cancer Epidemiol. Biomarkers Prev, 11, 953–971.[Abstract/Free Full Text]
  22. Al-Delaimy,W.K., Cho,E., Chen,W.Y., Colditz,G. and Willet,W.C. (2004) A prospective study of smoking and risk of breast cancer in young adult women. Cancer Epidemiol. Biomarkers Prev., 13, 398–404.[Abstract/Free Full Text]
  23. Brunet,J.S., Ghadirian,P., Rebbeck,T.R. et al. (1998) Effect of smoking on breast cancer in carriers of mutant BRCA1 or BRCA2 genes. J. Natl Cancer Inst., 90, 761–766.[Abstract/Free Full Text]
  24. Couch,F.J., Cerhan,J.R., Vierkant,R.A., Grabrick,D.M., Therneau,T.M., Pankratz,V.S., Hartmann,L.C., Olson,J.E., Vachon,C.M. and Sellers,T.A. (2001) Cigarette smoking increases risk for breast cancer in high-risk breast cancer families. Cancer Epidemiol. Biomarkers Prev., 10, 327–332.[Abstract/Free Full Text]
  25. Reynolds,P., Hurley,S., Goldberg,D.E. et al. (2004) Active smoking, household passive smoking, and breast cancer: evidence from the California Teachers Study. J. Natl Cancer Inst., 96, 29–37.[Abstract/Free Full Text]
  26. Ghadirian,P., Lubinski,J., Lynch,H. et al. (2004) Smoking and the risk of breast cancer among carriers of BRCA mutations. Int. J. Cancer, 110, 413–416.[CrossRef][Web of Science][Medline]
  27. Rebbeck,T.R., Wang,Y., Kantoff,P.W. et al. (2001) Modification of BRCA1- and BRCA2-associated breast cancer risk by AIB1 genotype and reproductive history. Cancer Res., 61, 5420–5424.[Abstract/Free Full Text]
  28. Kadouri,L., Kote-Jarai,Z., Easton,D.F., Hubert,A., Hamoudi,R., Glaser,B., Abeliovich,D., Peretz,T. and Eeles,R.A. (2004) Polyglutamine repeat length in the AIB1 gene modifies breast cancer susceptibility in BRCA1 carriers. Int. J. Cancer, 108, 399–403.[CrossRef][Web of Science][Medline]
  29. Hughes,D.J., Ginolhac,S.M., Coupier,I. et al. (2005) Breast cancer risk in BRCA1 and BRCA2 mutation carriers and polyglutamine repeat length in the AIB1 gene. Int. J. Cancer, 117, 230–233.[CrossRef][Web of Science][Medline]
  30. Wilkening,S., Burwinkel,B., Grzybowska,E., Klaes,R., Pamula,J., Pekala,W., Zientek,H., Hemminki,K. and Forsti,A. (2005) Polyglutamine repeat length in the NCOA3 does not affect risk in familial breast cancer. Cancer Epidemiol. Biomarkers Prev., 14, 291–292.[Free Full Text]
  31. Montgomery,K.G., Chang,J.H., Gertig,D.M., Dite,G.S., McCredie,M.R., Giles,G.G., Southey,M.C., Hopper,J.L. and Campbell,I.G. (2005) The AIB1 glutamine repeat polymorphism is not associated with risk of breast cancer before age 40 years in Australian women. Breast Cancer Res., 7, R353–R356.[CrossRef][Web of Science][Medline]
  32. Burwinkel,B., Wirtenberger,M., Klaes,R. et al. (2005) Association of NCOA3 polymorphisms with breast cancer risk. Clin. Cancer Res., 11, 2169–2174.[Abstract/Free Full Text]
  33. Rebbeck,T.R., Lynch,H.T., Neuhausen,S.L. et al. (2002) Prophylactic oophorectomy in carriers of BRCA1 or BRCA2 mutations. N. Engl. J. Med., 346, 1616–1622.[Abstract/Free Full Text]
  34. Xu,J. and Li,Q. (2003) Review of the in vivo functions of the p160 steroid receptor coactivator family. Mol. Endocrinol., 17, 1681–1692.[Abstract/Free Full Text]
  35. Schiff,R., Massarweh,S., Shou,J. and Osborne,C.K. (2003) Breast cancer endocrine resistance: how growth factor signaling and estrogen receptor coregulators modulate response. Clin. Cancer Res., 9, 447S–454S.[Abstract/Free Full Text]
  36. Anzick,S.L., Kononen,J., Walker,R.L., Azorsa,D.O., Tanner,M.M., Guan,X.Y., Sauter,G., Kallioniemi,O.P., Trent,J.M. and Meltzer,P.S. (1997) AIB1, a steroid receptor coactivator amplified in breast and ovarian cancer. Science, 277, 965–968.[Abstract/Free Full Text]
  37. Osborne,C.K., Bardou,V., Hopp,T.A., Chamness,G.C., Hilsenbeck,S.G., Fuqua,S.A., Wong,J., Allred,D.C., Clark,G.M. and Schiff,R. (2003) Role of the estrogen receptor coactivator AIB1 (SRC-3) and HER-2/neu in tamoxifen resistance in breast cancer. J. Natl Cancer Inst., 95, 353–361.[Abstract/Free Full Text]
  38. Xu,J., Liao,L., Ning,G., Yoshida-Komiya,H., Deng,C. and O'Malley,B.W. (2000) The steroid receptor coactivator SRC-3 (p/CIP/RAC3/AIB1/ACTR/TRAM-1) is required for normal growth, puberty, female reproductive function, and mammary gland development. Proc. Natl Acad. Sci. USA, 97, 6379–6384.[Abstract/Free Full Text]
  39. Institute,S. (2002) SAS release 8.0. Cary, NC.
  40. Lin,D.Y., Wei,L.J. and Weissfeld,L. (1989) Regression analysis of multivariate incomplete failure time data by modeling marginal distributions. JASA, 84, 1065–1073.
  41. Terry,P.D., Miller,A.B. and Rohan,T.E. (2002) Cigarette smoking and breast cancer risk: a long latency period? Int. J. Cancer, 100, 723–728.[CrossRef][Web of Science][Medline]
  42. Haiman,C.A., Hankinson,S.E., De Vivo,I., Guillemette,C., Ishibe,N., Hunter,D.J. and Byrne,C. (2003) Polymorphisms in steroid hormone pathway genes and mammographic density. Breast Cancer Res. Treat., 77, 27–36.[CrossRef][Web of Science][Medline]
  43. Kurebayashi,J., Otsuki,T., Kunisue,H., Tanaka,K., Yamamoto,S. and Sonoo,H. (2000) Expression levels of estrogen receptor-alpha, estrogen receptor-beta, coactivators, and corepressors in breast cancer. Clin. Cancer Res., 6, 512–518.[Abstract/Free Full Text]
  44. Font de Mora,J. and Brown,M. (2000) AIB1 is a conduit for kinase-mediated growth factor signaling to the estrogen receptor. Mol. Cell. Biol., 20, 5041–5047.[Abstract/Free Full Text]
  45. Iwase,H. (2003) Molecular action of the estrogen receptor and hormone dependency in breast cancer. Breast Cancer, 10, 89–96.[Medline]
  46. Meek,M.D. and Finch,G.L. (1999) Diluted mainstream cigarette smoke condensates activate estrogen receptor and aryl hydrocarbon receptor-mediated gene transcription. Environ. Res., 80, 9–17.[Medline]
  47. Foulkes,W.D., Metcalfe,K., Sun,P. et al. (2004) Estrogen receptor status in BRCA1- and BRCA2-related breast cancer: the influence of age, grade, and histological type. Clin. Cancer Res., 10, 2029–2034.[Abstract/Free Full Text]
  48. Karp,S.E., Tonin,P.N., Begin,L.R., Martinez,J.J., Zhang,J.C., Pollak,M.N. and Foulkes,W.D. (1997) Influence of BRCA1 mutations on nuclear grade and estrogen receptor status of breast carcinoma in Ashkenazi Jewish women. Cancer, 80, 435–441.[CrossRef][Web of Science][Medline]
  49. Gudas,J.M., Nguyen,H., Li,T. and Cowan,K.H. (1995) Hormone-dependent regulation of BRCA1 in human breast cancer cells. Cancer Res., 55, 4561–4565.[Abstract/Free Full Text]
  50. Rosen,E.M., Fan,S., Pestell,R.G. and Goldberg,I.D. (2003) BRCA1 in hormone-responsive cancers. Trends Endocrinol. Metab., 14, 378–385.[CrossRef][Web of Science][Medline]
  51. Fan,S., Wang,J., Yuan,R. et al. (1999) BRCA1 inhibition of estrogen receptor signaling in transfected cells. Science, 284, 1354–1356.[Abstract/Free Full Text]
  52. Fan,S., Ma,Y.X., Wang,C. et al. (2001) Role of direct interaction in BRCA1 inhibition of estrogen receptor activity. Oncogene, 20, 77–87.[CrossRef][Web of Science][Medline]
  53. Zheng,L., Annab,L.A., Afshari,C.A., Lee,W.H. and Boyer,T.G. (2001) BRCA1 mediates ligand-independent transcriptional repression of the estrogen receptor. Proc. Natl Acad. Sci. USA, 98, 9587–9592.[Abstract/Free Full Text]
  54. Morabia,A., Bernstein,M., Ruiz,J., Heritier,S., Diebold Berger,S. and Borisch,B. (1998) Relation of smoking to breast cancer by estrogen receptor status. Int. J. Cancer, 75, 339–342.[CrossRef][Web of Science][Medline]
  55. Cooper,J.A., Rohan,T.E., Cant,E.L., Horsfall,D.J. and Tilley,W.D. (1989) Risk factors for breast cancer by oestrogen receptor status: a population-based case–control study. Br. J. Cancer, 59, 119–125.[Web of Science][Medline]
  56. Klaren,H.M., van't Veer,L.J., van Leeuwen,F.E. and Rookus,M.A. (2003) Potential for bias in studies on efficacy of prophylactic surgery for BRCA1 and BRCA2 mutation. J. Natl Cancer Inst., 95, 941–947.[Free Full Text]
  57. Calle,E.E., Miracle-McMahill,H.L., Thun,M.J. and Heath,C.W. Jr (1994) Cigarette smoking and risk of fatal breast cancer. Am. J. Epidemiol., 139, 1001–1007.[Abstract/Free Full Text]
  58. Manjer,J., Andersson,I., Berglund,G., Bondesson,L., Garne,J.P., Janzon,L., Malina,J. and Matson,S. (2000) Survival of women with breast cancer in relation to smoking. Eur. J. Surg., 166, 852–858.[CrossRef][Web of Science][Medline]
  59. King,M.C., Marks,J.H. and Mandell,J.B. (2003) Breast and ovarian cancer risks due to inherited mutations in BRCA1 and BRCA2. Science, 302, 643–646.[Abstract/Free Full Text]
  60. Scott,C.L., Jenkins,M.A., Southey,M.C., Davis,T.A., Leary,J.A., Easton,D.F., Phillips,K.A. and Hopper,J.L. (2003) Average age-specific cumulative risk of breast cancer according to type and site of germline mutations in BRCA1 and BRCA2 estimated from multiple-case breast cancer families attending Australian family cancer clinics. Hum. Genet., 112, 542–551.[CrossRef][Web of Science][Medline]
  61. Rubin,D.T. and Hanauer,S.B. (2000) Smoking and inflammatory bowel disease. Eur. J. Gastroenterol. Hepatol., 12, 855–862.[Web of Science][Medline]
  62. Thun,M.J., Henley,S.J. and Calle,E.E. (2002) Tobacco use and cancer: an epidemiologic perspective for geneticists. Oncogene, 21, 7307–7325.[CrossRef][Web of Science][Medline]
  63. Leone,A. (2003) Relationship between cigarette smoking and other coronary risk factors in atherosclerosis: risk of cardiovascular disease and preventive measures. Curr. Pharm. Des., 9, 2417–2423.[CrossRef][Web of Science][Medline]
  64. Molgaard,C.A., Bartok,A., Peddecord,K.M. and Rothrock,J. (1986) The association between cerebrovascular disease and smoking: a case–control study. Neuroepidemiology, 5, 88–94.[Medline]
  65. Lindenstrom,E., Boysen,G. and Nyboe,J. (1993) Lifestyle factors and risk of cerebrovascular disease in women. The Copenhagen City Heart Study. Stroke, 24, 1468–1472.[Abstract/Free Full Text]
Received July 21, 2005; revised August 9, 2005; accepted October 12, 2005.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Occup. Environ. Med.Home page
J Vlaanderen, L E Moore, M T Smith, Q Lan, L Zhang, C F Skibola, N Rothman, and R Vermeulen
Application of OMICS technologies in occupational and environmental health research; current status and projections
Occup. Environ. Med., February 1, 2010; 67(2): 136 - 143.
[Abstract] [Full Text] [PDF]

Home page
 Hum Mol GenetHome page
A. Miremadi, M. Z. Oestergaard, P. D.P. Pharoah, and C. Caldas
Cancer genetics of epigenetic genes
Hum. Mol. Genet., April 15, 2007; 16(R1): R28 - R49.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrowOA All Versions of this Article:
27/3/599    most recent
bgi246v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (6)
Google Scholar
Right arrow Articles by Colilla, S.
Right arrow Articles by Rebbeck, T. R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Colilla, S.
Right arrow Articles by Rebbeck, T. R.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?