FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium

Abstract

Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium.Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression.Results:Little evidence of association with breast cancer risk was observed for SNPs in the FGF receptor genes. The strongest evidence in European women was for rs743682 in FGFR3; the estimated per-allele odds ratio was 1.05 (95% confidence interval=1.02–1.09, P=0.0020), which is substantially lower than that observed for SNPs in FGFR2.Conclusion:Our results suggest that common variants in the other FGF receptors are not associated with risk of breast cancer to the degree observed for FGFR2.

Gene-based analysis of the fibroblast growth factor receptor signaling pathway in relation to breast cancer in African American women: the AMBER consortium

“…To date, no systematic evaluation of germline variation in the FGF/FGFR signaling pathway in relation to breast cancer has been carried out. The Breast Cancer Association Consortium (BCAC) which includes predominantly European-ancestry subjects, evaluated genetic variation in four FGF gene receptors ( FGFR1 , FGFR3 , FGFR4 , and FGFRL1 ) and found little evidence of association with risk of breast cancer [9]. The Breast Cancer Health Disparities Study, which includes Hispanic and non-Hispanic white women, conducted gene-based analysis of seven growth factor genes including three genes in the FGF/FGFR signaling pathway ( FGFR2 , FGF1 , and FGF2 ).…”

A role for FGF2 in visceral adiposity-associated mammary epithelial transformation

“…The role of FGF2/FGFR1 in breast cancer onset is less clear. One study demonstrated that genetic variants in FGFR1, FGFR3, or FGFR4 had no impact on breast cancer risk, [38] whereas an intronic single-nucleotide polymorphism (SNP) in the FGFR2 gene was associated with an increased risk of breast cancer, particularly estrogen receptor (ER) positive disease [38]. A separate study demonstrated no significant associations with SNPs in FGF2 and breast cancer risk [39].…”

Fine‐scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

“…Fine‐mapping SNPs were selected for inclusion on the custom Illumina iSelect array (iCOGS), with the following criteria: ( i ) Defining the interval to include all SNPs with r 2 > 0.1 with the index SNPs rs13281615 and rs11780156 based on HapMap 2 CEU, which identified a region of 2.06 Mb (base positions 127,561,724–129,624,067; NCBI build 37 assembly); ( ii ) Identifying all SNPs in the interval using the 1,000 Genomes Project CEU (April 2010), and HapMap 3; ( iii ) Selecting high‐quality SNPs: only variants with the minor allele called at least twice in the 1,000 Genomes Project and an Illumina designability score >0.8 were included; ( iv ) Selecting all SNPs with r 2 > 0.1 with the index SNPs rs13281615 and rs11780156 from the CEU data set of the 1,000 Genomes Project or HapMap 3; ( v ) Selecting tagging SNPs at r 2 > 0.9 to capture the remaining SNPs that are not in LD with the index SNPs ( r 2 < 0.1). Genotyping of the iCOGS array and details of the genotyping calling and quality control has been described elsewhere . In order to improve SNP density and imputation quality, we conducted one‐step imputation (without phasing) using the program IMPUTE2 (see URLs) with the March 2012 release of the 1,000 Genomes Project as reference.…”

“…Genotyping of the iCOGS array and details of the genotyping calling and quality control has been described elsewhere. 4,11,12 In order to improve SNP density and imputation quality, we conducted one-step imputation (without phasing) using the program IMPUTE2 (see URLs) with the March 2012 release of the 1,000 Genomes Project as reference. Genotypes were successfully imputed for 10,593 variants in samples of European ancestry, 9,218 variants in samples of Asian ancestry and 17,964 variants in samples of African ancestry, all with imputation-r 2 > 0.3.…”