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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC 2011 January 1.
Published in final edited form as:
PMCID: PMC2806599
NIHMSID: NIHMS150772

Variation in the FGFR2 Gene and the Effect of a Low-Fat Dietary Pattern on Invasive Breast Cancer

Abstract

Background

The Women’s Health Initiative (WHI) dietary modification (DM) trial provided suggestive evidence of a benefit of a low-fat dietary pattern on breast cancer risk, with stronger evidence among women whose baseline diet was high in fat. Single nucleotide polymorphisms (SNPs) in the FGFR2 gene relate strongly to breast cancer risk, and could influence intervention effects.

Participants and Methods

All 48,835 trial participants were postmenopausal and aged 50–79 at enrollment (1993–98). We interrogated eight SNPs in intron 2 of the FGFR2 gene for 1676 women who developed breast cancer during trial follow-up (1993–2005). Case-only analyses were used to estimate odds ratios for the DM intervention in relation to SNP genotype.

Results

Odds ratios for the DM intervention did not vary significantly with the genotype for any of the eight FGFR2 SNPs (p≥0.18). However, odds ratios varied (p<0.05) with the genotype of six of these SNPs, among women having baseline percent of energy from fat in the upper quartile (≥36.8%). This variation is most evident for SNP rs3750817, with odds ratios (95% confidence intervals) for the DM intervention at 0, 1, and 2 minor SNP alleles of 1.06 (0.80, 1.41), 0.53 (0.38, 0.74), and 0.62 (0.33, 1.15). The nominal significance level for this interaction is p=0.005, and is p=0.03 following multiple testing adjustment, with most evidence deriving from hormone receptor-positive tumors.

Conclusion

Invasive breast cancer odds ratios for a low-fat dietary pattern, among women whose usual diets are high in fat, appear to vary with SNP rs3750817 in the FGFR2 gene.

Keywords: breast cancer, genotype, gene-intervention interaction, low fat dietary pattern, randomized controlled trial

INTRODUCTION

The Women’s Health Initiative (WHI) randomized controlled trial included evaluation of the health risks and benefits of four prevention interventions in a partial factorial design (1, 2). A total of 68,132 postmenopausal women were enrolled during 1993–98 at 40 U.S. clinical centers.

The dietary modification (DM) trial component tested whether a low-fat dietary pattern could reduce the incidence of breast and colorectal cancer. It enrolled 48,835 women, with random assignment of 40% to the intervention group and 60% to a usual-diet comparison group, and proceeded to its planned termination after an average 8.1 years of intervention and follow-up. The low-fat dietary pattern intervention goals included a reduction in dietary percent of energy from fat from baseline levels, estimated by food frequency questionnaire (FFQ) to be above 32% as an eligibility criterion, to 20%, and increase to five of daily vegetables and fruit servings, and increase to six in daily grain servings. The assessed change in percent of energy from fat was only about 70% of that assumed in the trial design (1), and the lower invasive breast cancer incidence in the intervention versus the comparison group was about 70% of that hypothesized in trial design, with hazard ratio (HR) of 0.91 with an associated 95% confidence interval (CI) of 0.83 to 1.01, with 1727 incident cases during follow-up (2).

However, the overall trial comparison may be diluted by the inclusion of many women having a relatively low-fat diet at baseline, who may have made little or no dietary change, if assigned to the intervention group. In fact, there was a significant (p=0.04) interaction between baseline percent of energy from fat, as assessed using 4-day food records, and intervention versus comparison group HR, with women in the top quartile (≥36.8%) of percent of energy from fat having a HR (95% CI) of 0.78 (0.64, 0.95) (2).

Findings from recent breast cancer genome-wide association studies provide an opportunity to seek genetic factors that may relate to dietary intervention effects on breast cancer. The strongest breast cancer association to emerge from these studies (3, 4) involves single nucleotide polymorphisms (SNPs) in intron 2 of the fibroblast growth factor receptor two gene (FGFR2). For example, SNP rs2981582, with a minor allele frequency of about 40%, has been found to convey a per minor-allele increase in breast cancer risk of about 30% (3, 4). FGFR2 splice variants have been shown to transform human mammary epithelial cells (5), and blocking FGFR2 signaling inhibits breast cancer cell proliferation (6). Intron 2 includes highly conserved regions and is dense in transcription factor binding sites, including sites thought to be relevant to the estrogen receptor (7).

We tested the FGFR2 SNP just mentioned, along with seven others in intron 2 of this gene, among women who developed invasive breast cancer during the follow-up period of the WHI clinical trial, and each case was matched to a corresponding control without a breast cancer diagnosis during the follow-up period. As recently reported, each of the eight SNPs was significantly related to breast cancer risk in this WHI cohort, with seven of the eight having p<1.0 × 10−7 (8). Moreover, the genotype of one of the eight SNPs, rs3750817, was associated with the breast cancer odds ratio (OR) for both postmenopausal estrogen plus progestin therapy (p=0.03) and estrogen-alone therapy (p=0.05), while the genotype of a second SNP, rs2981582, may also be associated (p=0.05) with estrogen-alone therapy. Here we report corresponding analyses for the dependence of odds ratios for the DM intervention on these SNPs.

MATERIALS AND METHODS

Study Population, Case Selection

WHI clinical trial enrollees were postmenopausal, in the age range 50–79, without a history of invasive breast cancer, and with no suggestion of breast cancer on baseline mammogram and clinical breast exam. Clinical outcomes were self-reported at six-month intervals. Breast cancers were confirmed (9) by review of pathology reports by local physician adjudicators, followed by adjudication at the Clinical Coordinating Center that included coding of estrogen receptor status and progesterone receptor status (positive or negative per local pathology report), histology, and extent of disease using the National Cancer Institute’s Surveillance, Epidemiology and End Results system. The trial was approved by human subjects review committees at each participating institution, and each study participant provided written informed consent.

All 1727 invasive breast cancer cases developing between randomization (1993–98) and the end of the intervention phase for the DM trial component (March 31, 2005) were considered for inclusion in the present analyses. Of these 1676 (97.0%) had adequate quantity and quality of DNA for SNP genotyping.

Laboratory Methods

The eight FGFR2 SNPs were included in a larger project involving 9039 SNPs selected from previous genome-wide association studies (3, 4), including a WHI-Perlegen Sciences collaboration (10). Genotyping and quality control methods at Perlegen, where genotyping took place, have been described (11). The average call rate for SNPs meeting quality assurance criteria was 99.8% in the overall project, and the average concordance rate for duplicate samples (157 pairs in dataset) was also 99.8%.

Six of the eight FGFR2 SNPs selected (rs2981582, rs1219648, rs2912774, rs2981579, rs11200014, and rs2420946) were from a single linkage disequilibrium (LD) region where much of the interest from genome-wide breast cancer association studies has focused. These SNPs have a minimum squared pairwise correlation (r2) of 0.83 among Caucasian women. A seventh SNP, rs17102287, is in the same genomic region, but is in much lower LD with the other six SNPs (maximum r2 of 0.32 among Caucasian women). The eighth SNP, rs3750817, is a little distant from the other seven and has a maximum pairwise r2 of 0.47 with the other SNPs among Caucasian women, but falls within a conserved region of the gene (3). For example, in the WHI clinical trial cohort studied here, SNP rs2981582 with a minor allele (G) frequency of 0.41 had an estimated per-minor allele breast cancer OR of 1.27 (p for trend 9.3 x 10−8), similar to that for the other SNPs in the same LD region, while SNP rs3750817 with a minor allele (T) frequency of 0.37, and negatively correlated with the other SNPs, had an estimated per-minor allele odds ratio of 0.78 (p for trend 8.2 x 10−8) (8).

Statistical Methods

Tests for SNP interactions with the DM intervention odds ratio were carried out using case-only data analyses (8, 1214). This approach, which here can be expected to yield essentially unbiased and highly efficient odds ratio estimates, involves logistic regression of intervention assignment (0 - comparison; 1 - intervention) on indicator variables for 0, 1, or 2 of the minor SNP alleles, with constant term given by log {q/(1−q)}, where q is the fraction (0.40) of the trial cohort assigned to active intervention in the dietary modification trial. Likelihood ratio (LR) tests with two degrees of freedom were used to test for intervention odds ratio variation with SNP genotype. The treatment indicator variable was randomly permuted and the LR statistic was recalculated to generate significance levels that are adjusted for the fact that eight FGFR2 SNPs were tested for odds ratio interaction. The multiple testing-adjusted significance level was calculated as the fraction of 1000 permutation samples for which the LR statistic was as large or larger than that observed.

RESULTS

The characteristics of the women participating in the DM trial have been published (2, 15). Women were postmenopausal at enrollment, with an average age of 63 years, and about 20% were of minority race/ethnicity. About two-thirds were overweight or obese. All women were without a prior breast cancer diagnosis at enrollment.

Table 1 shows DM intervention OR estimates (95% CIs) according to the number of minor SNP alleles, for all randomized women, and separately for those having baseline percent of energy from fat in the upper quartile. Significance levels for tests of independence of odds ratios with SNP genotype are also given. OR estimates for the entire randomized cohort may be slightly lower among women homozygous for the major allele for the first six highly correlated SNPs, and slightly lower for women having one or more minor alleles of rs3750817, though these variations are far from significant (p ≥ 0.18). These patterns are clearer, and mostly significant (p<0.05), however, upon restricting the analysis to women having baseline percent of energy from fat in the upper quartile. Relatively lower ORs among women having one or more T alleles for rs3750817 is particularly evident (p=0.005). To compare the evidence for interaction with the DM intervention effect among the FGFR2 SNPs studied, we carried out case-only analyses for women having baseline percent of energy from fat in the upper quartile in which the intervention effect was allowed to depend simultaneously on the number of minor alleles of rs3750817 and the original tagging SNP in the first LD region, rs2981582. A dependence of the intervention effect on rs3750817 genotype could be detected (p=0.03) when the intervention effect was allowed to depend on rs2981582 genotype, but this was not the case for rs2981582 (p=0.25) when the intervention effect was allowed to depend on rs3750817 genotype.

Table 1
Invasive breast cancer odds ratio estimates for a low-fat dietary pattern intervention according to the number of minor alleles of FGFR2 single nucleotide polymorphisms (SNPs)

With adjustment for the fact that eight FGFR2 SNPs were tested for interaction, the significance level for interaction with rs3750817 increases to 0.03. This multiple testing-adjusted test of interaction remained significant (p=0.05) when the analysis was restricted to Caucasian women (361 breast cancer cases), whereas the corresponding adjusted p-values were not close to significant (p ≥ 0.17) for the other seven FGFR2 SNPs.

Table 2 shows a further breakdown of ORs for women having baseline percent of energy from fat in the upper quartile, according to estrogen and progesterone receptor status of the breast tumor, both for rs2981582, as a representative SNP from the first linkage disequilibrium set, and for rs3750817. The patterns just described are not very apparent within tumor receptor status subtypes for rs2981582, but are pronounced for tumors that are estrogen receptor positive (p=0.008) or progesterone receptor positive (p=0.003) for rs3750817. With multiple testing adjustment, the p-values for rs3750817 increase to 0.05 for estrogen receptor positive tumors, and to 0.02 for progesterone receptor positive tumors. We tested whether the ORs shown in Table 2 for estrogen receptor positive tumors differed from those for estrogen receptor negative by a simple multiplicative factor and did not find evidence to the contrary (p=0.74), presumably due to the relatively few estrogen receptor negative tumors. The corresponding test comparing progesterone receptor positive and negative tumor ORs was also not significant (p=0.34).

Table 2
Dietary intervention odds ratio estimates for breast cancer among women having baseline percent of energy from fat in the upper quartile, according to the number of minor alleles of SNPs rs2981582 and rs3750817, by tumor hormone receptor status

DISCUSSION

The low-fat dietary pattern intervention implemented in the WHI provided suggestive evidence of a reduction in invasive breast cancer risk overall; and stronger evidence among women whose pre-randomization diet was relatively high in fat, who made a larger dietary change.

Among women in the upper quartile of percent of energy from fat, the dietary intervention odds ratio varied with the genotype of SNPs in the FGFR2 gene. This interaction was particularly evident (nominal p=0.005) in relation to SNP rs3750817, where evidence for a breast cancer risk reduction was confined to women having one or more minor (T) alleles. These patterns were apparent for estrogen receptor positive and for progesterone receptor positive tumors, and persisted upon allowing for the testing of eight FGFR2 SNPs. The randomized assignment of women to the low-fat dietary pattern intervention prevents population stratification from biasing dietary intervention odds ratios for the overall study population. However, stratification could influence odds ratio variations with SNP genotype, if both genotype and dietary intervention odds ratios varied among population strata. In fact, International HapMap data do indicate a lower frequency of the T allele of rs3750817 among persons of African, compared to European, ancestry. However, when analyses were restricted to the 84.3% of breast cancer cases among Caucasian women, the dietary intervention odds ratio pattern was unchanged, and the multiple testing-adjusted p-value of 0.05, versus 0.03 for the combined ethnicities, is as expected with the reduced sample size, if dietary modification odds ratios are unchanged. These findings tend to strengthen the evidence for a DM intervention benefit among women having a high fat content in their customary diets, since one would not expect evidence for interaction with rs3750817, or other SNPs, to arise if the DM intervention had no effect on breast cancer incidence.

It is interesting that rather similar breast cancer odds ratio patterns as a function of rs3750817 also arose for the randomized placebo controlled hormone therapy interventions in the WHI clinical trial (8). The elevated breast cancer risk with estrogen plus progestin arose from women having one or more major alleles of this SNP, while a suggested risk reduction with estrogen-alone arose from women homozygous for the minor allele. As previously noted (8), there is a high degree of sequence homology around rs3750817, and the region has a density of transcription factor binding sites, including the prediction (8) that the T allele introduces a YY1 transcription factor binding site into the human sequence. YY1 is involved in breast cancer cell migration (16), ERBB2 oncogene expression (17), and represses TRAIL-induced apoptosis (18).

The ability to assess the biological plausibility of an interaction of a DM intervention effect interaction with rs3750817 genotype is limited by incomplete knowledge of the regulation of FGFR2 protein expression. Meyer et al (19) studied protein expression in relation to several SNPs in the vicinity of those in the first LD region studied here, and concluded that SNPs associated with risk correlated with FGFR2 expression itself, rather than functioning through receptor-ligand interactions, and they identified two transcription factors whose binding affinity was altered by the SNPs studied. Corresponding studies have not been reported for rs3750817, or other SNPs in close proximity to rs3750817.

Reduced odds ratios among women having the T allele of rs3750817 could suggest a sensitivity of risk to variations in the circulating hormonal mileau. The low-fat dietary pattern intervention led to some reduction in plasma estradiol and increase in sex hormone binding globulin (2), whereas estrogen plus progestin and estrogen-alone give rise to major increases in both plasma estradiol and sex-hormone binding globulin.1

Similarly, a high body mass index (BMI) is an established risk factor for postmenopausal breast cancer and we observe in the case-control data for this project a significant (p=0.02) interaction between BMI and rs3750817 genotype in relation to breast cancer risk, with comparatively stronger evidence for BMI association with risk among women having one or two minor SNP alleles. However, the ORs for rs3750817 shown in Table 1 do not differ significantly (p=0.60) between obese (BMI ≥ 30) and non-obese women.

The strengths of this study are the randomized controlled trial design of the DM trial, which implies precise orthogonality between genotype and dietary intervention, justifying the highly efficient case-only data analysis method employed. Other strengths include prediagnostic blood specimens, collected and stored according to a standardized protocol, and quality controlled SNP genotyping.

Study limitations include incomplete knowledge of FGFR2 variants involved in breast cancer risk determination and in related dietary influences. Also, replication of the interactions reported here will be useful. Readily available WHI observational data are not well suited to this purpose, since 4-day food records have not undergone nutrient analysis for most of the controls in the present genotyping case-control studies, and food frequency questionnaire data, in contrast to food record data, provide little evidence of association between dietary fat and breast cancer (20). A replication study effort that will obtain FGFR2 genotypes for study subjects included in the earlier 4-day food record analyses (20) is in the planning stage.

In summary, SNP rs3750817 in a conserved region of the FGFR2 gene has been shown to be strongly associated with breast cancer risk, and is reported here to interact with the putative effect of a low-fat dietary pattern on breast cancer incidence. Women having one or more minor (T) alleles of this SNP may benefit from reduction from a high-fat to a lower-fat dietary pattern.

Acknowledgments

This work was supported by the National Heart, Lung, and Blood Institute, National Institutes of Health, U. S. Department of Health and Human Services [contracts HHSN268200764314C, N01WH22110, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-19, 32122, 42107-26, 42129-32, and 44221]. Clinical Trials Registration: ClinicalTrials.gov identifier: NCT00000611. Dr. Prentice’s work was partially supported by grant CA53996 from the National Cancer Institute.

Decisions concerning study design, data collection and analysis, interpretation of the results, the preparation of the manuscript, or the decision to submit the manuscript for publication resided with committees comprised of WHI investigators that included NHLBI representatives.

Footnotes

1Edlefsen KL, Jackson RD, Prentice RL, Janssen I, Rajkovic A, O’Sullivan MJ, Anderson G. The effects of postmenopausal hormone therapy on serum estrogen, progesterone and sex-hormone binding globulin levels in healthy postmenopausal women. Submitted for publication, Menopause, 2009.

Program Office: (National Heart, Lung, and Blood Institute, Bethesda, Maryland) Elizabeth Nabel, Jacques Rossouw, Shari Ludlam, Joan McGowan, Leslie Ford, and Nancy Geller.

Clinical Coordinating Center: (Fred Hutchinson Cancer Research Center, Seattle, WA) Ross Prentice, Garnet Anderson, Andrea LaCroix, Charles L. Kooperberg, Ruth E. Patterson, Anne McTiernan; (Medical Research Labs, Highland Heights, KY) Evan Stein; (University of California at San Francisco, San Francisco, CA) Steven Cummings.

Clinical Centers: (Albert Einstein College of Medicine, Bronx, NY) Sylvia Wassertheil-Smoller; (Baylor College of Medicine, Houston, TX) Aleksandar Rajkovic; (Brigham and Women’s Hospital, Harvard Medical School, Boston, MA) JoAnn E. Manson; (Brown University, Providence, RI) Charles B. Eaton; (Emory University, Atlanta, GA) Lawrence Phillips; (Fred Hutchinson Cancer Research Center, Seattle, WA) Shirley Beresford; (George Washington University Medical Center, Washington, DC) Lisa Martin; (Los Angeles Biomedical Research Institute at Harbor- UCLA Medical Center, Torrance, CA) Rowan Chlebowski; (Kaiser Permanente Center for Health Research, Portland, OR) Yvonne Michael; (Kaiser Permanente Division of Research, Oakland, CA) Bette Caan; (Medical College of Wisconsin, Milwaukee, WI) Jane Morley Kotchen; (MedStar Research Institute/Howard University, Washington, DC) Barbara V. Howard; (Northwestern University, Chicago/Evanston, IL) Linda Van Horn; (Rush Medical Center, Chicago, IL) Henry Black; (Stanford Prevention Research Center, Stanford, CA) Marcia L. Stefanick; (State University of New York at Stony Brook, Stony Brook, NY) Dorothy Lane; (The Ohio State University, Columbus, OH) Rebecca Jackson; (University of Alabama at Birmingham, Birmingham, AL) Cora E. Lewis; (University of Arizona, Tucson/Phoenix, AZ) Cynthia A Thomson; (University at Buffalo, Buffalo, NY) Jean Wactawski-Wende; (University of California at Davis, Sacramento, CA) John Robbins; (University of California at Irvine, CA) F. Allan Hubbell; (University of California at Los Angeles, Los Angeles, CA) Lauren Nathan; (University of California at San Diego, LaJolla/Chula Vista, CA) Robert D. Langer; (University of Cincinnati, Cincinnati, OH) Margery Gass; (University of Florida, Gainesville/Jacksonville, FL) Marian Limacher; (University of Hawaii, Honolulu, HI) J. David Curb; (University of Iowa, Iowa City/Davenport, IA) Robert Wallace; (University of Massachusetts/Fallon Clinic, Worcester, MA) Judith Ockene; (University of Medicine and Dentistry of New Jersey, Newark, NJ) Norman Lasser; (University of Miami, Miami, FL) Mary Jo O’Sullivan; (University of Minnesota, Minneapolis, MN) Karen Margolis; (University of Nevada, Reno, NV) Robert Brunner; (University of North Carolina, Chapel Hill, NC) Gerardo Heiss; (University of Pittsburgh, Pittsburgh, PA) Lewis Kuller; (University of Tennessee Health Science Center, Memphis, TN) Karen C. Johnson; (University of Texas Health Science Center, San Antonio, TX) Robert Brzyski; (University of Wisconsin, Madison, WI) Gloria E. Sarto; (Wake Forest University School of Medicine, Winston-Salem, NC) Mara Vitolins; (Wayne State University School of Medicine/Hutzel Hospital, Detroit, MI) Michael Simon.

Women’s Health Initiative Memory Study: (Wake Forest University School of Medicine, Winston-Salem, NC) Sally Shumaker.

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