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Somatic alterations have been shown to correlate with breast cancer prognosis and survival, but less is known about the effects of common inherited genetic variation. Of particular interest are genes involved in cell cycle pathways, which regulate cell division.    Methods  We examined associations between common germline genetic variation in 13 genes involved in cell cycle control ( CCND1 ,  CCND2 ,  CCND3 ,  CCNE1 ,  CDK2  [p33],  CDK4 ,  CDK6 ,  CDKN1A  [p21, Cip1],  CDKN1B  [p27, Kip1],  CDKN2A  [p16],  CDKN2B  [p15],  CDKN2C  [p18], and  CDKN2D  [p19]) and survival among women diagnosed with invasive breast cancer participating in the SEARCH (Studies of Epidemiology and Risk factors in Cancer Heredity) breast cancer study. DNA from up to 4,470 women was genotyped for 85 polymorphisms that tag the known common polymorphisms (minor allele frequency > 0.05) in the genes. The genotypes of each polymorphism were tested for association with survival using Cox regression analysis.    Results  The rare allele of the tagging single nucleotide polymorphism (SNP) rs2479717 is associated with an increased risk of death (hazard ratio = 1.26 per rare allele carried, 95% confidence interval: 1.12 to 1.42;  P  = 0.0001), which was not attenuated after adjusting for tumour stage, grade, and treatment. This SNP is part of a large linkage disequilibrium block, which contains  CCND3 ,  BYSL ,  TRFP ,  USP49 ,  C6ofr49 ,  FRS3 , and  PGC . We evaluated the association of survival and somatic expression of these genes in breast tumours using expression microarray data from seven published datasets. Elevated expression of the  C6orf49  transcript was associated with breast cancer survival, adding biological interest to the finding.    Conclusion  It is possible that  CCND3  rs2479717, or another variant it tags, is associated with prognosis after a diagnosis of breast cancer. Further study is required to validate this finding.

Effects of common germline genetic variation in cell cycle control genes on breast cancer survival: results from a population-based cohort