FGF2 is a potent angiogenic molecule that has been shown to promote tumour cell mitosis and has been implicated in the differentiation of stromal and epithelial cells from a dormant to an invasive phenotype (Dow et al., 2000
). We have evaluated the effects of 25 SNPs in the FGF2
gene on the risk of invasive serous ovarian cancer in non-Hispanic White women enrolled in five case-control studies from the United States and Australia, and found no convincing evidence of an association of any FGF2
SNPs with serous ovarian tumours in our combined dataset. We acknowledge that the potential for variation in estimates is inherent in analyses involving samples from different countries, given the likelihood of differences in case-control selection criteria and population differences attributable to environmental factors or genetic background. However, all contributing studies included in our analysis selected controls from the same source population as cases, participants were predominantly non-Hispanic White (), and indeed there was no evidence of heterogeneity between the studies (non-Hispanic Whites only) for any of the SNPs included in this analysis (PHeterogeneity
The human FGF2
gene encompasses 71.53 kb of genomic sequences on chromosome 4. Using Hapmap SNP genotype frequency data for FGF2
SNPs, we estimated that the 25 SNPs presented in this report capture 97% of the known common variation (MAF ≥ 0.05) across the FGF2
locus at r2
≥ 0.8 for pairwise correlations. To the best of our knowledge, this is the first study to evaluate FGF2
SNPs in a large multi-center study. Based on the method of Purcell et al (Purcell et al., 2003
) we estimated that we had ≥80% power to detect ORs of 1.20 at an alpha of 0.05 for the 19 SNPs with MAFs ≥0.1 (). However, we acknowledge that we had considerably less power to detect these effect sizes with the six SNPs with MAFs < 0.1.
Our study highlights the importance of consortium-based approaches to investigating putative genetic association in case-control analyses, particularly for low-risk genes that require large sample sizes to detect small SNP effects. We note that three SNPs, in addition to the rs308447, achieved the minimal level of significance of p≤0.05 in study-specific per-allele estimates (data not shown), but not in the combined analysis. If we had reported the results of these individual case-control studies, it may have led other groups to attempt replication but our combined analysis provides a more accurate assessment of these associations and reduces publication bias.
FGF2 has been the focus of a plethora of studies into human tumour biology and has important implications for cancer therapies and clinical outcomes. FGF2 is one of several fibroblast growth factor molecules that interact with various vascular endothelial growth factors and cell surface receptors that are known to play a role in tumour growth and angiogenesis (Powers et al., 2000
; Presta et al., 2005
). The correlation between angiogenesis and the extent of metastatic disease has been widely demonstrated in a large and diverse range of human cancers (Macchiarini et al., 1992
; Weidner et al., 1993
; Weidner et al., 1991
) including advanced stage ovarian carcinoma (Hollingsworth et al., 1995
; Weidner, 1995
). Abnormally high concentrations of FGF2 have been found in the serum of patients with active metastatic cancers and have been shown to correlate significantly with extent of disease, clinical status and risk of future mortality (Nguyen et al., 1994
). These findings would support the assessment of FGF2
polymorphisms with regard to ovarian cancer survival and prognosis in future studies. To date several functional angiogenic gene SNPs have been studied in solid cancers with varying results derived from sample sizes that are too small to detect the modest effects anticipated from these low penetrance genes (Balasubramanian et al., 2002
). Large-scale epidemiologic studies of other genes involved in angiogenesis are therefore warranted to further enhance our understanding of tumour progression. This could lead to novel approaches to risk stratification or the use of anti-angiogenic treatment strategies, if angiogenic potential, and hence prognosis, can be predicted according to individual genotype.