• breast cancer;
  • FGFR2;
  • gene–environment interactions


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Recent genome-wide association studies have revealed several new candidate genes for breast cancer, including fibroblast growth factor receptor 2 (FGFR2) gene. The associations were also replicated in several other independent studies. The next important step is to study whether these common variants interact with known breast cancer risk factors, exogenous exposures and tumor characteristics. In a population-based case–control study of 1,170 breast cancer cases and 2,115 controls, we examined genetic associations of four intronic FGFR2 single-nucleotide polymorphisms (SNPs) and breast tumor characteristics and assessed the potential interactions with smoking, alcohol consumption, adiposity and known breast cancer risk factors. FGFR2 variants were significantly associated with breast cancer risk regardless of estrogen and progesterone receptor status, metastasis, lymph node involvement and histologic and nuclear grade. The FGFR2–breast cancer association was modified by smoking status, with increased risk for former and current smokers compared to never smokers; former/current smokers carrying two copies of the rs1219648 minor allele were at highest risk with a crude OR (95% confidence interval) of 2.11 (1.52–2.92) compared to never smokers with no rs1219648 variant alleles. Our study found no evidence for either modification of FGFR2 and breast cancer by alcohol intake or adiposity, even when analyses were stratified by menopausal status. Although these results require further replication, they may provide new insight into the possible new exposures that may interact with FGFR2 susceptibility alleles.

Genome-wide association studies (GWASs) have identified novel low-penetrance breast cancer susceptibility loci, all independently associated with breast cancer risk.1–3 These findings have been replicated in several independent case–control studies.4–10 Polygenic modeling of disease susceptibility suggests that these loci account for at least 5% of the genetic risk of breast cancer.11 A better understanding of the association of these genes with risk and their interactions with other breast cancer risk factors and exposures may allow us to better exploit these provocative findings and to ultimately shed further light on breast carcinogenesis.

Two independent GWASs identified single-nucleotide polymorphisms (SNPs) located in intron 2 of fibroblast growth factor receptor 2 (FGFR2) gene as being associated with breast cancer risk, with odds ratio (OR) values around 1.6 for variant homozygotes.1, 2 Easton et al. identified the FGFR2 SNP rs2981582, and concomitantly, Hunter et al. identified four other SNPs in intron 2 of FGFR2 (rs11200014, rs2981579, rs1219648 and rs2420946). The rs1219468 SNP has an r2 of 1.0 with rs2981582, and so both studies identified essentially the same association.

GWASs are hypothesis-free approaches, and none of the genes identified in the GWASs had been previously linked to breast cancer risk, with the exception of FGFR2, a gene encoding for a transmembrane tyrosine kinase known to be involved in mammary gland development and breast carcinogenesis.12 One GWAS and several other more focused consortia studies investigated whether FGFR2 associations were different by clinical and pathological characteristics of the breast tumors.4–7,10,13 It was reported that the variants within FGFR2 were associated with more favorable prognostic characteristics, including hormone receptor-positive and low-grade tumors.14 To date, potential interactions of these variants with exogenous factors have not been reported, with the exception of a recent study of Japanese women and the Women's Health Initiative (WHI) studies of low-fat diet and postmenopausal hormone therapy.15–17

What is lacking of our current understanding is whether there are important exposures and tumor characteristics that may interact with these common variants to increase breast cancer risk. The two goals of our study were to (i) evaluate differences in the FGFR2–breast cancer association with respect to clinical and tumor characteristics and (ii) explore gene–environment interactions with exogenous exposures and known breast cancer risk factors. We studied four SNPs in FGFR2 studied by Hunter et al.2

Material and Methods

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Study population

The Western New York Exposures and Breast Cancer Study is a population-based case–control study of incident, primary and histologically confirmed breast cancer, described in detail elsewhere.18, 19 Briefly, 1,170 female cases and 2,115 controls were enrolled from 1996 to 2001 in Erie and Niagara counties. Cases and controls were frequency matched on age. Extensive interview data regarding lifetime alcohol consumption, tobacco use, weight history and other breast cancer risk factors were collected. The majority of study participants were European American (92%). Our analyses here are restricted to Caucasians because the number of women from other racial/ethnic groups was too limited. All study protocols were approved by the University at Buffalo, Georgetown University Medical Center and participating hospital institutional review boards.

For all cases, tumor pathology and other characteristics were abstracted from medical charts using a standardized protocol; pathology data were independently confirmed by a pathologist at the Georgetown University as previously described.18 Benign breast disease data were abstracted from medical records and were defined as noncancerous breast lesions, thus excluding high-risk lesions such as atypical hyperplasia and lobular carcinoma in situ. Estrogen receptor (ER), progesterone receptor (PR) and Ki-67 status were determined by a single pathologist by immunohistochemistry on 5-μm slides using commercial antibodies and kits with the DAKO Autostainer (DAKO, Carpentaria, CA) using the Dako Cytomation EnVision + system-horseradish peroxidase (HRP) (DAB) kit and scored by estimating the proportion and average intensity of positive tumor cells. For ER and PR staining, the well-established Allred scoring system was used, and a value of 3 was chosen as cutoff to determine receptor status positivity, i.e., an Allred score of 3 or more was considered positive, in accordance with the common practice.20 For establishing Ki-67 status, as there is no clear consensus in choosing a cutoff value, we used a value of 20% positive stained cells as cutoff, similarly to the majority of previous studies using Ki-67 as a categorical variable in breast cancer, and recently summarized in a review on the subject.21 Because fewer than the total 1,077 breast cancer cases consented to and had tumor blocks available for analysis and the fact that the clinical/tumor data came in part from medical charts and part determined in our own laboratory, we have different missing rates for the different tumor characteristics and used every available woman for the analyses rather than selecting a group with all nonmissing values.


DNA was extracted from whole blood or oral cells (17% of cases and 8% of controls) using the DNAQuik™ isolation kit (BioServe, Beltsville, MD), according to the manufacturer's instructions. The four SNPs in intron 2 of FGFR2 (rs11200014, rs2981579, rs1219648 and rs2420946) were genotyped by allelic discrimination real-time PCR with TaqMan probes in an ABI 7900HT real-time PCR instrument (Applied Biosystems, Foster City, CA), using commercially available assays from Applied Biosystems, according to the manufacturer's instructions. Runs included cases and controls together; laboratory personnel were blinded to case–control status. As quality control measures, all assays were validated by genotyping members of seven multigenerational Centre d'Etude du Polymorphisme Humain (CEPH) families on DNA purchased from the Coriell Repositories (Coriell, Camden, NJ) to verify Mendelian patterns of inheritance. In addition, all runs contained 20% blind duplicates. The concordance rates between blinded duplicates were 97.2% for rs11200014, 98.0% for rs1219648, 98.0% for rs2420946 and 99.3% for rs2981579. The call rates were 92.7% for rs11200014, 96.1% for rs1219648, 93.3% for rs2420946 and 96.5% for rs2981579, hence in part the reason for the slightly different number of women analyzed for each SNP.

Statistical analyses

All statistical analyses were performed using SPSS v. 17 software. Differences in demographics and known breast cancer risk factors were tested using t-tests and χ2 tests as appropriate. For the SNP data, we assessed deviations from Hardy-Weinberg equilibrium in cases and controls separately using a χ2 test with one degree of freedom. To test associations of each SNP and breast cancer as well as test for interactions, we used logistic regression. We estimated allele frequencies, per-allele ORs and 95% confidence intervals (CIs) under log-additive genetic models to examine the association of FGFR2 variants and clinical/tumor characteristics, smoking, alcohol drinking, body mass index (BMI) and breast cancer risk factors. In building these models, we examined the influence of typical breast cancer risk factors (age, education, BMI, age at first birth, age at menarche, number of births, first degree family history of breast cancer, previous benign breast disease and menopausal status) as covariates.

To assess the potential heterogeneity of genetic association and breast cancer by tumor characteristics, we examined cases stratified according to ER, PR and Ki-67 status, metastasis, lymph node involvement, histological and nuclear tumor grade, stage and tumor size with classification according to categories presented in Table 2. In these analyses, we also performed case–case comparisons with regard to the same classifications of each factor and estimated p values for heterogeneity.

We analyzed whether factors such as smoking behavior, alcohol intake and adiposity modified the association of breast cancer and FGFR2. Lifetime smoking and drinking histories and physical measurements were collected via an interviewer-assisted, in-person interview. Total lifetime ounces of alcohol intake and drinks per drinking day (a measure of intensity) were defined for each woman.22 Categories of consumption were defined based on the median for each measure in controls. We examined whether smoking (smoking status and pack years), alcohol consumption (lifetime ounces and drinks per drinking day) and BMI modified the association of the FGFR2 variants and breast cancer by categorizing women according to exposure × genotype and use of dummy variables for each category of genotype and exposure variable. Interaction terms were created using the continuous measures when available (i.e., pack years of smoking, lifetime ounces of alcohol and BMI). We examined interaction terms in log-additive genetic models only.

Finally, we examined the association of FGFR2 variants and breast cancer according to known breast cancer risk factors, combining heterozygotes with rare homozygotes to preserve sample size. When exploring these associations, we present models adjusted for other known risk factors, using either the median cutoffs in controls for a particular factor with the exception of nulliparity for the parity factor to examine risk by category.


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

Descriptive characteristics for Caucasian cases and controls are presented in detail in Table 1. Overall, the mean age (±SD) was 58.2 (11.1) and 57.3 (11.7) for cases and controls, respectively. Of these cases, 72% had ER-positive tumors and 64% had PR-positive tumors. Cases were more likely to have fewer number of births or be nulliparous compared to controls (p = 0.001), and more cases had a first-degree relative with breast cancer and previous benign breast disease (p = 0.001).

Table 1. Demographics, breast cancer risk factors and tumor characteristics
inline image

All four FGFR2 SNPs were in Hardy Weinberg proportions and were in strong linkage disequilibrium in the controls (r2 > 0.9), therefore showing the same trend of associations in the statistical analyses. All four FGFR2 SNPs were statistically significantly associated with breast cancer, with similar and significant per-allele ORs ranging from 1.22 to 1.29 (Supporting Information Table 1). The same trend was observed in the stratified analysis according to menopausal status for all four SNPs (data not shown). Per allele ORs and 95% CIs for rs1219648 were 1.39 (1.12–1.73) and 1.21 (1.06–1.39) for premenopausal and postmenopausal women, respectively.

Table 2 presents the association of FGFR2 genetic variation and breast cancer stratified by tumor characteristics. We show results for rs1219648 only due to similarity in the associations of other three FGFR2 SNPs studied. When stratifying cases according to hormone receptor status, we observed significant associations regardless of ER and PR status. FGFR2 variants were associated with breast cancer risk only among women with tumors negative for the Ki-67 proliferation indicator; however, we cannot rule out that this lack of significance is due to small numbers of Ki-67 positive tumors in our study. No differences regarding the association with metastasis at presentation or lymph node involvement and breast cancer was observed for any of the four SNPs (data not shown). The association was in the similar direction for both histologic and nuclear grade. Regarding stage and tumor size, we found significant positive associations for all four SNPs among stages 0 and 1 and tumor size ≤2 cm only; however, the nonsignificant per allele OR in stage ≥2 and >2 cm tumor size may be due to small sample size within these strata.

Table 2. Association of FGFR2 rs1219648 and breast cancer stratified by clinical/tumor characteristics
inline image

Table 2 also shows case–case analyses, where we formally tested for heterogeneity according to different tumor characteristics. None of these p values were significant at p = 0.05, supporting the analyses stratified by the respective tumor characteristics, showing no significant differences in the association of FGFR2 variants and breast cancer according to any of the characteristics we examined.

The interaction of FGFR2 variants and smoking status is presented in Table 3. We observed an association of FGFR2 genotype and breast cancer among smokers, with significant risk increasing in a dose-dependent manner for women carrying either one or two copies of the minor allele. We observed the highest ORs for smokers carrying two FGFR2 minor alleles, with crude OR of 2.11, 95% CI: 1.52–2.92 for rs1219648. Multiplicative interaction terms with smoking status were significant at p = 0.10 for three of the FGFR2 SNPs (rs11200014, rs2981579 and rs1219648). The associations were similar for higher and lower lifetime pack years smoked; smokers who were carriers of one or two variant alleles had significant increased risk whether they smoked less than 20 pack years or more than 20 pack years (Supporting Information Table 2). It is important to note that in our study, smoking itself is not statistically significantly associated with breast cancer.

Table 3. Interaction between FGFR2 genotypes and smoking status1
inline image

Table 4 shows the association of rs1219648 and breast cancer with consideration of the following breast cancer risk factors: age, education, age at menarche, number of births, age at first birth, family history of breast cancer and previous benign breast disease. Not surprisingly, carriers of the minor alleles consistently had the highest breast cancer risk in combination with the breast cancer risk factors we examined. For rs1219648, there is a slight increase in risk for carriers (one or two copies of) of the minor allele in combination with age 58 and older, age at menarche less than 13 years, family history of breast cancer and benign breast disease. There was no evidence of interaction of these risk factors and FGFR2 variants except for parity, which was the only multiplicative interaction term that reached statistical significance at p < 0.05.

Table 4. Interaction of FGFR2 rs1219648 genotype and known breast cancer risk factors
inline image

The association of FGFR2 and breast cancer did not differ by alcohol intake using two different dimensions of intake: total lifetime ounces or drinks per drinking day (data not shown).

ORs were slightly higher for women with a BMI > 30 kg/m2 compared to women with BMI < 30 kg/m2; however, there were no significant multiplicative interaction terms for any of the SNPs studied, whether we considered crude or fully adjusted models (Supporting Information Table 3). This lack of interaction of FGFR2 variants and BMI was similar and nonsignificant in premenopausal and postmenopausal in both crude and adjusted statistical models (data not shown).


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

We investigated the FGFR2–breast cancer association in greater detail, examining the association of four intronic SNPs within strata defined by clinical and pathological characteristics and the modification of the association by other breast cancer risk factors and exogenous exposures including smoking, alcohol and obesity.

FGFR2 is a member of the receptor tyrosine kinase family, involved in mammary gland proliferation and development.23, 24 It has been shown that FGFR2 can transform normal human mammary epithelial cells and is overexpressed in up to 15% of breast tumors.25 Several transcription binding sites, including a putative ER-binding site, have been indentified in intron 2 of FGFR2,26 and SNPs in this region have been reported to be associated more with ER-positive than ER-negative breast tumors in several studies.5, 7, 10, 13 We did not find a difference in the association by ER status. We did find significant positive associations of FGFR2 variants for PR-positive cases, consistent with previous reports in Dutch and Irish studies.4, 6 PR can be directly activated in a ligand-independent fashion through the Mitogen-activated protein kinase gene (MAPK) pathway that can be stimulated by FGFR2.27 Additionally, the FGF2/FGFR2 axis may have a role in PR activation, inducing hormone-independent mammary tumor growth most likely through MAPK pathway activation.28

In this study, although we did not replicate the predominant association with ER-positive tumors, we did identify significant association of FGFR2 variants among women with risk factors related to endogenous estrogen exposure such as lower number of births. In this population, we did not see an association with lymph node positive tumors as reported previously,12, 13 although it should be noted that those previous findings were not consistent with the overall trend toward association with risk among those with favorable tumor characteristics.5, 13 Similar to what others have found,6, 12, 14 we found that there was a significant association of FGFR2 and breast cancer among those with a history of breast cancer in a first-degree family member.

One of our most interesting results is that the association of FGFR2 SNPs and breast cancer was limited to current and former smokers, with no significant association in never smokers. Smoking has been associated with breast cancer risk in several studies, but to date, there is inconclusive epidemiological evidence for a strong significant association,29, 30 and thus, modification by unknown susceptibility alleles may be partly to blame. There is evidence suggesting that smoking may modify the association between genetic factors and breast cancer risk, e.g., smokers who are breast cancer susceptibility gene (BRCA)1/2 or ataxia telangiectasia mutated gene (ATM) mutation carriers have a significant increase in risk.31, 32 A recent meta-analysis and pooled analysis found that variants in the N-acetyltransferase 2 gene (NAT2) modify the association between cigarette smoking and breast cancer risk; increased risk is associated with smoking among those with the NAT2-slow acetylator genotype.33, 34 In our study, we found effect modification of the association between FGFR2 SNPs and breast cancer risk by smoking, with a more than twofold increase in breast cancer risk for smokers with the variant genotype. Interestingly, there was no indication that the amount of cigarettes smoked had any additional effect per analyses of pack years. One limitation is the amount of never smokers in our study, which may have limited our power to detect associations in this group. Besides a direct carcinogenic effect, tobacco constituents induce and promote cell proliferation, invasion and epithelial–mesenchymal transformation in several types of cells, including normal mammary epithelial cells and breast cancer cells, e.g., by activating the MAPK pathway either independently or most likely through growth factor receptors.35, 36 It is possible that smoking activates the MAPK pathway either directly or by increasing the FGFR2 activity, which in turn could be already overexpressed in carriers of the variant genotype. Smoking could potentially act synergistically with, or directly on, the FGFR2/MAPK pathway to induce and promote the carcinogenic process in the breast. If this was the case, the effect might be independent of dose.

Alcohol consumption is another well-established risk factor for breast cancer.37 Although the mechanism of the observed association is unknown, the established impact of alcohol on estrogen levels may explain this phenomenon, at least in part.37, 38 In our study, both lifetime consumption and the intensity of alcohol drinking did not modify the association of the investigated variants and breast cancer.

There is consistent evidence that higher BMI and central adiposity is associated with increased postmenopausal breast cancer risk possibly through hormone-mediated mechanisms.39–41 When investigating adiposity expressed by BMI in interaction with the FGFR2 variants and breast cancer, we found no significant interaction in the entire sample or in premenopausal or postmenopausal women separately. The gene-only results for FGFR2 and breast cancer in our study were similar for premenopausal and postmenopausal women, which may suggest that the association of adiposity and breast cancer is independent of the FGFR2–breast cancer pathway.

To our knowledge, this is the first study to examine the interactions between exogenous exposures such as alcohol consumption and smoking and FGFR2 genotypes in a Caucasian population. However, the interest in gene–environment interaction in the context of FGFR2–breast cancer association is emerging; one study in the Japanese population has investigated the interaction with smoking and drinking with null results, and another study nested within the WHI investigated the interaction with a low-fat dietary pattern.15, 16 In general, our findings are consistent with the study in the Japanese population, except for the association with smoking, suggesting that the effect of FGFR2 variants on breast cancer risk is similar in different racial groups as also reported by two recent meta-analyses on the subject.42, 43 The discrepancies regarding the association with smoking might be due to the differences in smoking pattern among these two populations or the fact that the Japanese study had a much smaller sample size compared to ours, and therefore very small numbers in different strata.

Taken together, these data support the prevailing hypothesis that FGFR2 variants play a role in breast cancer etiology, particularly for women with a smoking history. The previously reported association with hormone receptor-positive tumors found by previous studies could simply be an artifact of the increased proportion of receptor-positive cases in all datasets investigated so far, as suggested recently.14

A hormone-mediated mechanism would likely not be consistent with our finding that smokers who carry FGFR2 variant alleles are at higher risk of developing breast cancer, in that smoking is thought to have an antiestrogenic effect.44 However, several epidemiology studies have not found significant differences in endogenous estrogen levels between smokers and nonsmokers,45, 46 and the observed modification by smoking may be related to other effects of smoking on the tissue environment. On the other hand, we observed a consistent association of FGFR2 SNPs with increased breast cancer risk within women with low parity, consistent with previous reports in other populations8, 15; however, we did not find increased risk with parity in the presence of FGFR2 minor alleles as compared to parity in the presence of common FGFR2 genotype. These reproductive risk factors are thought to be related to the endogenous hormone exposure, and thus, the hormone-mediated mechanism underlying the association of FGFR2 variants and breast cancer risk cannot be ruled out, suggesting that tobacco and hormonal exposures may be independent factors. Interestingly, a recent study of hormone therapy within the WHI trial showed an interaction of one FGFR2 SNP and breast cancer risk in case-only analyses.17 Their findings suggest that in women who carry two variants of rs3750817, estrogen alone is protective with regard to breast cancer risk. Clearly, large well-powered replication studies are needed to support this hypothesis. Together, our findings of a smoking interaction and these purported protective effects of estrogen in the presence of FGFR2 minor alleles suggests that estrogen plays a complex role in FGFR2-mediated breast cancer risk.

Consistent with the general epidemiological data on breast cancer, the cases in our study were significantly different when compared to controls in terms of age, parity, family history and the presence of previous benign breast disease. Although there seem to be an indication of a slight increase in risk for carriers of one or two copies of the minor allele in combination with these factors in our study, the only multiplicative term of interaction that reached significance was parity as discussed above. There are several other known genetic risk factors for breast cancer such as high-penetrance mutations (e.g., BRCA1 and BRCA2). If the case sample contains a significant number of BRCA carriers or breast cancer with familial aggregation that could contribute to the unbalanced number of first-degree relatives with breast cancer between cases and controls, it may have an effect on the risk estimates in our study, as recently suggested.47, 48 However, we could not investigate this in our study because of the lack of data regarding high-penetrance mutations and/or familial aggregation.

The strengths of our study include the population-based design and well-characterized clinical and pathological features of cases, as well as extensive data collected on demographics and other exposures such as lifetime smoking and drinking. We believe that the wealth of information particularly in regard to breast cancer tumors, lifetime exposure to tobacco smoke and alcohol intake in this study presented a unique opportunity to both test hypotheses regarding the association of genetic variants with tumor phenotypes and generate new hypotheses via investigation of gene–environment interactions.

We performed multiple statistical tests herein and therefore cannot rule out the possibility of our findings being due to chance. In many cases, the strata were small, thus limiting power to detect such effects. It is important to note that the significant interaction of FGFR2 and smoking does not remain significant with adjustment for multiple testing. There is a great deal of further statistical and biological confirmation of this putative interaction needed as well as a need to test whether these results are generalizable to women of other race/ethnic groups.

Little is known about the functional role of these FGFR2 SNPs and the biologic mechanisms by which they contribute to breast cancer etiology. The interaction of FGFR2 variants with smoking may provide some insight into the etiology and the biological mechanisms underlying breast carcinogenesis, hence generating hypotheses for further studies that could have implications in prevention, detection and treatment.


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

H.M.O.-B was supported by the National Cancer Institute, K07 CA136969.


  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Material and Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. References
  8. Supporting Information

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IJC_25686_sm_supptables.doc103KSupporting Tables

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