Association between WT1 polymorphisms and susceptibility to breast cancer: results from a case-control study in a southwestern Chinese population

Wilms' tumor gene 1 (WT1) single nucleotide polymorphism (SNP), rs16754, has been considered as an independent prognostic factor in patients with acute myeloid leukemia and renal cell carcinoma. However, its biological role in breast cancer has not been reported. To test whether WT1 SNPs can be used as a molecular marker in order to improve the risk stratification of breast cancer, we performed a case-control study including 709 female sporadic breast cancer patients and 749 female healthy control subjects in the Southeast China. Five WT1 SNPs (rs16754, rs3930513, rs5030141, rs5030317, rs5030320) were selected and determined by polymerase chain reaction-ligase detection reaction to assess their associations with breast cancer risk. Results showed the distributions of the alleles of these WT1 SNPs were consistent with data from Chinese population as suggested by the International HapMap Project. Individuals with the minor alleles of rs16754, rs5030317 and rs5030320 showed a significant decrease of breast cancer risk in codominant model (OR = 0.6370, 95% CI: 0.4260-0.9520 for rs16754; OR = 0.5940, 95% CI: 0.3890-0.9070 for rs5030317; OR = 0.5870, 95% CI: 0.3850-0.8960 for 5030320, respectively) and recessive model. Stratified analyses showed the protective effects were more evident in the subjects with age = 50 years or in pre-menopausal status. To explore the potential mechanism, we conducted bioinformatics genotype-phenotype correlation analysis, and found that the mRNA expression level for homozygous rare allele of WT1 gene was lower than that in wild-type and heterozygous group (P = 0.0021) in Chinese population. In summary, our findings indicated that minor alleles of rs16754, rs5030317 and rs5030320 are associated with reduced risk of breast cancer, suggesting that WT1 SNPs may be a potential biomarker of individualized prediction of susceptibility to breast cancer. However, large prospective and molecular epidemiology studies are needed to verify this correlation and clarify its underlying mechanisms.